fix: production service auto-start via launchd + fix worker retry loop

- Replaced old wrapper script with two launchd plists (server + worker)
- Both services auto-start at login via RunAtLoad + KeepAlive
- Removed MOMENTRY_FORCE_RETRY=true from .env to prevent infinite retries
- Added REDIS_URL and all required env vars to launchd plists
- Truncated 3.6GB of oversized logs (2.3G worker + 1.3G launchd stdout)
- Deleted 1214 orphaned processor_results records
- Updated run-server-3002.sh to manage via launchctl
- Removed obsolete wrapper scripts

.env.development

@@ -10,7 +10,7 @@ MOMENTRY_REDIS_PREFIX=momentry_dev:
 
 # Worker Configuration (enabled for development)
 MOMENTRY_WORKER_ENABLED=true
-MOMENTRY_MAX_CONCURRENT=1
+MOMENTRY_MAX_CONCURRENT=6
 MOMENTRY_POLL_INTERVAL=10
 MOMENTRY_WORKER_BATCH_SIZE=5
 
@@ -23,13 +23,13 @@ MONGODB_URL=mongodb://localhost:27017
 MONGODB_DATABASE=momentry_dev
 
 # Redis (already isolated via prefix)
-REDIS_URL=redis://:accusys@localhost:6379
-REDIS_PASSWORD=accusys
+REDIS_URL=redis://127.0.0.1:6379
+# REDIS_PASSWORD not set - Redis has no password configured
 
 # Qdrant Vector Database - Collection isolation
 QDRANT_URL=http://localhost:6333
 QDRANT_API_KEY=Test3200Test3200Test3200
-QDRANT_COLLECTION=momentry_dev_rule1
+QDRANT_COLLECTION=momentry_dev_rule1_v2
 
 # Paths
 MOMENTRY_OUTPUT_DIR=/Users/accusys/momentry/output_dev
@@ -37,12 +37,12 @@ MOMENTRY_BACKUP_DIR=/Users/accusys/momentry/backup/momentry_dev
 MOMENTRY_SFTP_ROOT=/Users/accusys/momentry/var/sftpgo/data/demo/
 
 # Python (for processing scripts)
-MOMENTRY_PYTHON_PATH=/opt/homebrew/bin/python3.11
-MOMENTRY_SCRIPTS_DIR=/Users/accusys/momentry_core_0.1/scripts
+MOMENTRY_PYTHON_PATH=/Users/accusys/momentry_core/venv/bin/python
+MOMENTRY_SCRIPTS_DIR=/Users/accusys/momentry_core/scripts
 
 # Logging
-RUST_LOG=debug
-MOMENTRY_LOG_LEVEL=debug
+RUST_LOG=info
+MOMENTRY_LOG_LEVEL=info
 
 # Media
 MOMENTRY_MEDIA_BASE_URL=https://wp.momentry.ddns.net
@@ -67,4 +67,37 @@ REDIS_CACHE_TTL_VIDEO_META=3600
 # 多個同義詞檔案（逗號分隔），會覆蓋 MOMENTRY_SYNONYM_FILE
 # MOMENTRY_SYNONYM_FILES=/path/to/first.json,/path/to/second.json
 #
-# 示例檔案：docs/examples/custom_synonyms.json
+# 示例檔案：docs/examples/custom_synonyms.json
+
+# TMDb Integration (probe phase - auto-create identities from movie metadata)
+TMDB_API_KEY=e9cde52197f6f8df4d9db99da93db1fb
+MOMENTRY_TMDB_PROBE_ENABLED=true
+# LLM for 5W1H summary (points to M5 Gemma4)
+MOMENTRY_LLM_SUMMARY_URL=http://127.0.0.1:8000/v1/chat/completions
+MOMENTRY_LLM_SUMMARY_MODEL=gemma-4-E4B
+MOMENTRY_LLM_SUMMARY_ENABLED=true
+
+# LLM Chat (E4B on port 8000)
+MOMENTRY_LLM_CHAT_URL=http://127.0.0.1:8000/v1/chat/completions
+MOMENTRY_LLM_CHAT_MODEL=gemma-4-E4B
+
+# LLM Vision (E4B on port 8000)
+MOMENTRY_LLM_VISION_URL=http://127.0.0.1:8000/v1/chat/completions
+MOMENTRY_LLM_VISION_MODEL=gemma-4-E4B
+
+# Embedding (ANE CoreML server)
+MOMENTRY_EMBED_URL=http://localhost:11436
+
+# === Binary & Data Paths (for start_momentry.sh) ===
+MOMENTRY_LOG_DIR=/Users/accusys/momentry/logs
+MOMENTRY_PG_BIN_DIR=/Users/accusys/pgsql/18.3/bin
+MOMENTRY_PG_DATA_DIR=/Users/accusys/pgsql/data
+MOMENTRY_QDRANT_BIN=/Users/accusys/.cargo/bin/qdrant
+MOMENTRY_QDRANT_STORAGE_DIR=/Users/accusys/momentry/qdrant_storage
+MOMENTRY_LLAMACPP_BIN=/Users/accusys/llama/bin/llama-server
+MOMENTRY_LLM_A4B_MODEL_PATH=/Users/accusys/models/google_gemma-4-26B-A4B-it-Q5_K_M.gguf
+MOMENTRY_LLM_A4B_MMPROJ_PATH=/Users/accusys/models/gemma-4-26B-A4B-it.mmproj-f16.gguf
+MOMENTRY_LLM_E4B_MODEL_PATH=/Users/accusys/models/gemma-4-E4B-it-Q4_K_M.gguf
+MOMENTRY_LLM_E4B_MMPROJ_PATH=/Users/accusys/models/mmproj-gemma-4-E4B-it-BF16.gguf
+MOMENTRY_OLLAMA_BIN=/Users/accusys/bin/ollama
+MOMENTRY_PLAYGROUND_BIN=target/debug/momentry_playground

.env.example

@@ -1,70 +1,63 @@
-# Momentry Core Configuration Template
-# Copy this file to .env and customize for your environment
-# DO NOT commit .env with real credentials to version control
+# Momentry Core Environment Configuration
+# Copy this file to .env and fill in your values
+# DO NOT commit .env to version control
 
-# ===========================================
-# Database Configuration
-# ===========================================
-DATABASE_URL=postgres://user:password@localhost:5432/momentry
+# === Database ===
+DATABASE_URL=postgres://accusys@localhost:5432/momentry
+DATABASE_SCHEMA=dev
 
-# ===========================================
-# Redis Configuration
-# ===========================================
-REDIS_URL=redis://user:password@localhost:6379
-REDIS_PASSWORD=your_redis_password
-
-# ===========================================
-# MongoDB Configuration
-# ===========================================
-MONGODB_URL=mongodb://user:password@localhost:27017/admin
+# === MongoDB ===
+MONGODB_URL=mongodb://localhost:27017
 MONGODB_DATABASE=momentry
+MONGODB_CACHE_ENABLED=true
 
-# ===========================================
-# Qdrant Configuration
-# ===========================================
-QDRANT_URL=http://localhost:6333
-QDRANT_API_KEY=your_qdrant_api_key
+# === Redis ===
+REDIS_URL=redis://:accusys@localhost:6379
+REDIS_PASSWORD=accusys
+MOMENTRY_REDIS_PREFIX=momentry_dev:
+
+# === Qdrant ===
 QDRANT_COLLECTION=momentry_rule1
 
-# ===========================================
-# API Server Configuration
-# ===========================================
-API_HOST=127.0.0.1
-API_PORT=3000
+# === API Keys ===
+MOMENTRY_API_KEY=muser_your_key_here
+MOMENTRY_DEMO_API_KEY=muser_your_demo_key_here
+JWT_SECRET=your_jwt_secret_here_change_in_production
+SFTPGO_BASE_URL=http://127.0.0.1:8080
 
-# ===========================================
-# Directory Paths
-# ===========================================
-MOMENTRY_OUTPUT_DIR=/path/to/output
-MOMENTRY_BACKUP_DIR=/path/to/backup
-MOMENTRY_SCRIPTS_DIR=/path/to/momentry_core/scripts
+TMDB_API_KEY=your_tmdb_api_key_here
+
+# === LLM ===
+MOMENTRY_LLM_SUMMARY_URL=http://127.0.0.1:8082/v1/chat/completions
+MOMENTRY_LLM_SUMMARY_MODEL=google_gemma-4-26B-A4B-it-Q5_K_M.gguf
+MOMENTRY_LLM_SUMMARY_TIMEOUT=120
+
+# LLM Chat (A4B)
+MOMENTRY_LLM_CHAT_URL=http://127.0.0.1:8082/v1/chat/completions
+MOMENTRY_LLM_CHAT_MODEL=google_gemma-4-26B-A4B-it-Q5_K_M.gguf
+MOMENTRY_LLM_CHAT_TIMEOUT=120
+
+# LLM Vision (E4B)
+MOMENTRY_LLM_VISION_URL=http://127.0.0.1:8083/v1/chat/completions
+MOMENTRY_LLM_VISION_MODEL=gemma-4-E4B-it-Q4_K_M.gguf
+MOMENTRY_LLM_VISION_TIMEOUT=120
+
+# === Paths ===
+MOMENTRY_OUTPUT_DIR=/Users/accusys/momentry/output_dev
+MOMENTRY_BACKUP_DIR=/Users/accusys/momentry/backup
+MOMENTRY_SCRIPTS_DIR=/Users/accusys/momentry_core_0.1/scripts
 MOMENTRY_PYTHON_PATH=/opt/homebrew/bin/python3.11
+MOMENTRY_FFMPEG=/opt/homebrew/opt/ffmpeg-full/bin/ffmpeg
+MOMENTRY_MEDIA_BASE_URL=
 
-# ===========================================
-# Processor Timeouts (seconds)
-# ===========================================
+# === Encryption ===
+AUDIT_ENCRYPTION_KEY=    # 32 bytes hex (64 hex chars)
+
+# === Processor Timeouts (seconds) ===
 MOMENTRY_ASR_TIMEOUT=3600
 MOMENTRY_CUT_TIMEOUT=3600
 MOMENTRY_DEFAULT_TIMEOUT=7200
 
-# ===========================================
-# Watch Directories (comma separated)
-# ===========================================
-WATCH_DIRECTORIES=~/Videos,~/Downloads
-
-# ===========================================
-# Logging
-# ===========================================
-RUST_LOG=info
-# Options: trace, debug, info, warn, error
-
-# ===========================================
-# Ollama (for LLM integration)
-# ===========================================
-OLLAMA_HOST=http://localhost:11434
-
-# ===========================================
-# Model Paths
-# ===========================================
-# EMBEDDING_MODEL_PATH=./models/embedding
-# LLM_MODEL_PATH=./models/llm
+# === Server ===
+MOMENTRY_SERVER_PORT=3003
+MOMENTRY_LOG_LEVEL=info

.gitignore

@@ -1,92 +1,49 @@
-# Environment - Local configs (NEVER commit these)
-.env
-.env.local
-.env.*.local
-
-# Build artifacts
 target/
-venv/
-
-# Generated files
-thumbnails/
-*.asr.json
-*.probe.json
-test_asr.json
-
-# Local output (machine learning results)
-output/
-*.pt
-
-# Cache
-.ruff_cache/
-
-# OS files
 .DS_Store
-.Spotlight-V100
-.Trashes
-
-# Logs
-*.log
-
-# SSH keys (NEVER commit)
-id_*
-!id_*.pub
-
-# IDE and editor
-.vscode/
-.idea/
-*.swp
-*.swo
-*~
-
-# Documentation backups
-# docs_v1.0/ (Moved to active tracking)
-
-# Frontend dependencies
-node_modules/
-portal/src-tauri/target/
-
-# Python cache
-__pycache__/
-*.pyc
-*.pyo
-
-# Test artifacts
-test_output/
-test_output_simple/
-test_output_v2/
-*.mp4
+.env
+.env.development
+*.gguf
+*.mlpackage
 *.pt
-server.pid
-server.pid.*
+*.pth
+*.bin
+*.onnx
+*.zip
+*.tar.gz
+venv/
+__pycache__/
+node_modules/
+*.log
+/tmp/
+*.diff
+*.bundle
+*.probe.json
+*.cut.json
+.qdrant-initialized
+dump.rdb
+fix55.js
+checksums.sha256
 
-# Backup files
-*.bak
-*.backup
-*.bak[0-9]
-
-# Model files
+scripts/swift_processors/.build/
+.opencode/
+.vscode/
+backups/
+logs/
+output/
 models/
-model_checkpoints/
-pretrained_models/
-
-# Desktop app
-momentry_desktop/
-
-# Release artifacts (track docs, ignore binaries)
-release/*.zip
-release/momentry_v*
-release/*.sql
-release/dev_data_*.sql
-release/public_schema_*.sql
-release/migrate_*.sql
-
-# But track release documentation
-!release/*.md
-!release/*.txt
-
-# Data directories
 data/
-
-# System status
-system_status_*.md
+storage/
+thumbnails/
+services/
+model_checkpoints/
+release/delivery/
+release/system/
+release/phase*/
+release/dev_*.sql
+release/migrate_*.sql
+release/files/
+package-lock.json
+package.json
+portal/dist/
+portal/src-tauri/icons/
+momentry_runtime/logs/

AGENTS.md

@@ -11,6 +11,10 @@ Rust-based digital asset management system with video analysis and RAG capabilit
 - **絕對不可修改 n8n 工作流或設定**
 - **絕對不可修改 WordPress 或 n8n 的資料庫 table**
 - **除非是 release 作業，絕對不可動 port 3002 (production)**
+- **🔴 DELETE / REMOVE / DROP / CLEAR 任何資料前必須先問使用者「要刪嗎？」獲得明確同意後才能執行**
+- **🔴 Qdrant collection 刪除、DB truncate、檔案刪除、資料清空 — 一律要先問**
+- **🔴 不確定是否該刪 → 先問，不要自己決定**
+- **🔴 改變議題前必須先存檔紀錄**：使用 `todowrite` 工具或建立紀錄文件（如 `docs_v1.0/M4_workspace/YYYY-MM-DD_topic_handoff.md`），確保上下文不丟失
 
 ### 開發範圍界定
 | 範圍 | 狀態 | 說明 |
@@ -29,10 +33,52 @@ Rust-based digital asset management system with video analysis and RAG capabilit
 | Production | 3002 | ❌ 禁止修改 | `cargo run -- server` (僅 release 時) |
 | Portal (Tauri) | 1420 | 前端開發 | `npm run tauri dev` |
 
+### 日誌與啟動
+| 服務 | 日誌路徑 | 啟動方式 |
+|------|----------|----------|
+| Production (3002) | `logs/momentry_3002.log` | `./run-server-3002.sh` |
+| Playground (3003) | `logs/momentry_3003.log` | `./run-server-3003.sh` |
+| Worker / 歷史 | `logs/nohup_worker_*.log` | 由 worker 自動產生 |
+
+> **注意**: 所有伺服器日誌統一存放於專案內 `logs/` 目錄。
+> 啟動腳本會自動 kill 舊程序、重 build（若需要）、並將日誌導向 `logs/`。
+
+## ⚠️ 交叉污染防制 (Cross-Contamination Prevention)
+
+**每個執行前必須評估是否會汙染其他獨立作業。**
+
+### Scope Isolation Matrix
+
+| 執行內容 | 允許的 Scope | 禁止影響 | 檢查事項 |
+|----------|-------------|----------|----------|
+| M4 delivery binary | `target/release/momentry` | Playground (3003), Production (3002) | 確認舊 process 未被誤殺 |
+| Playground server | `localhost:3003`, `dev.*` schema | Production (3002), `public.*` schema | `DATABASE_SCHEMA=dev` |
+| Production deploy | `localhost:3002`, `public.*` schema | Playground (3003), `dev.*` schema | 先停 production，不影響 playground |
+| Git commit | 只包含意圖修改的檔案 | 無關的 untracked files | `git status` 確認 stage 內容正確 |
+| CI / packaged tests | 測試環境 | 正式資料 | 測試用 DB 不能連到 production |
+| Doc changes | 指定文件 | 其他文件、程式碼 | `git diff --stat` 檢查 scope |
+| SQL migration | 目標 schema | 其他 schema、無關 table | `WHERE` clause 要精準 |
+| `sed` / `grep` / mass edit | 目標檔案集 | 非目標檔案 | 先用 `grep -c` 確認只有目標檔案匹配 |
+
+### Recent Violations / Near-Misses
+
+| 事件 | 問題 | 防止方式 |
+|------|------|----------|
+| `sed` API doc 編號 | `sed -i '' 's/.../.../g'` 改到所有行 | 先 `grep -c` 確認匹配，`git diff` 再提交 |
+| 亂加 `/api/v1/register` route | 不必要的 API 別名，汙染路由表 | 角色切換：路由設計不該由實作方決定 |
+| `API_WORKSPACE/` vs `GUIDES/` vs `REFERENCE/` vs `DESIGN/` vs `OPERATIONS/` vs `INTEGRATIONS/` | 文件放到錯誤分類 | API 文件改在 API_WORKSPACE/modules/ 編輯，`make deploy` 生成到 GUIDES/ |
+| Build release binary in plan mode | 浪費時間，無意義 | 嚴格遵守 plan/build mode 規定 |
+
+### ⛔ 嚴格測試隔離規則 (Strict Test Isolation)
+- **所有測試 (Test) 必須在 Dev (3003) 進行**。
+- **絕對禁止 (ABSOLUTELY FORBIDDEN)** 在任何測試指令、Demo 流程或 API 檢查中使用 `localhost:3002`。
+- 即使是「測試 Unregister」或「檢查版本」，若未明確標示為 "Production Deployment"，一律視為違規。
+- **預設行為**: 所有 curl, CLI, 或程式碼測試指令，預設 URL 必須為 `http://localhost:3003`。
+
 ### 違反後果
 - 修改 WordPress/n8n 可能影響 marcom 團隊工作與生產環境
 - 修改 WordPress/n8n 資料庫 table 可能破壞自動化流程與資料完整性
-- 修改 port 3002 可能中斷正在使用的服務
+- 修改 port 3002 可能中斷正在使用的服務 (這是非常嚴重的錯誤)
 - 所有 dev 測試必須在 playground (3003) 進行
 
 ---
@@ -157,6 +203,21 @@ cargo run -- server --host 0.0.0.0 --port 3002
 # Run playground (development binary)
 cargo run --bin momentry_playground -- server
 cargo run --bin momentry_playground -- --help
+
+# Start servers (recommended — auto-build & logs to logs/)
+./run-server-3002.sh
+./run-server-3003.sh
+```
+
+### Server Logs
+All runtime logs are centralized in `logs/`:
+```bash
+# View real-time logs
+tail -f logs/momentry_3002.log
+tail -f logs/momentry_3003.log
+
+# Check recent errors
+grep -i "error\|panic\|FAIL" logs/momentry_*.log | tail -20
 ```
 
 ### ⚠️ CRITICAL: `cargo build --release` PROHIBITION
@@ -346,11 +407,51 @@ cargo run --features player --bin momentry_player -- -o
 - `MOMENTRY_PYTHON_PATH` - Python path (default: `/opt/homebrew/bin/python3.11`)
 - `MOMENTRY_SCRIPTS_DIR` - Scripts directory
 
+### Critical Variables for Startup Scripts
+
+**IMPORTANT**: Startup scripts must explicitly `export` these variables for Python subprocess inheritance.
+
+#### Production (3002)
+Required exports in `run-server-3002.sh` and `run-worker-3002.sh`:
+```bash
+export MOMENTRY_OUTPUT_DIR=/Users/accusys/momentry/output
+export DATABASE_SCHEMA=public
+export MOMENTRY_REDIS_PREFIX=momentry:
+export MOMENTRY_SERVER_PORT=3002
+```
+
+#### Playground (3003)
+Required exports in `run-server-3003.sh`:
+```bash
+export DATABASE_SCHEMA=dev
+export MOMENTRY_SERVER_PORT=3003
+export MOMENTRY_REDIS_PREFIX=momentry_dev:
+export MOMENTRY_OUTPUT_DIR=/Users/accusys/momentry/output_dev
+```
+
+#### Why This Matters
+- Rust process loads `.env` via `dotenv`
+- Python subprocess inherits environment from Rust process
+- Without explicit `export`, dotenv variables are only available inside Rust
+- Python scripts like `store_traced_faces.py` will use hardcoded defaults if not exported
+
+#### Config Directory
+Environment-specific configuration files:
+- `config/production.env` - Production-specific variables
+- `config/development.env` - Development-specific variables
+- `config/test.env` - Test environment (if needed)
+
 ### Processor Timeouts
 - `MOMENTRY_ASR_TIMEOUT` - ASR timeout in seconds (default: 3600)
 - `MOMENTRY_CUT_TIMEOUT` - CUT timeout in seconds (default: 3600)
 - `MOMENTRY_DEFAULT_TIMEOUT` - Default timeout (default: 7200)
 
+### TMDb Integration (Face Clustering)
+- `TMDB_API_KEY` - TMDb API key for movie metadata lookup (required for `MOMENTRY_TMDB_PROBE_ENABLED=true`)
+- `MOMENTRY_TMDB_PROBE_ENABLED` - Enable TMDb probe during registration (default: `false`)
+  - Register phase: searches TMDb by filename, creates identities with tmdb_id/tmdb_profile
+  - Post-process phase: matches detected faces against TMDb identities via cosine similarity
+
 ### Synonym Expansion
 - `MOMENTRY_SYNONYM_FILES` - Comma-separated paths to synonym JSON files (e.g., `data/english_synonyms.json,data/llm_synonyms.json`)
 - `MOMENTRY_SYNONYM_FILE` - Single synonym JSON file path (deprecated, use above)
@@ -366,6 +467,7 @@ cargo run --features player --bin momentry_player -- -o
 - Monitor directory is a separate system (not Rust)
 - PythonExecutor provides unified script execution with timeout support
 - Redis 1.0.x for improved performance
+- FaceNet CoreML model (`models/facenet512.mlpackage`) replaces InsightFace for embedding extraction (MIT license, ANE-accelerated)
 
 ### LLM Synonym Generation
 
@@ -484,6 +586,40 @@ shellcheck scripts/*.sh monitor/**/*.sh
 
 **注意**: Hook 只檢查 error 等級的 shellcheck 問題，style 警告會顯示但不阻擋提交。
 
+## Gitea Sync
+
+主要 sync 管道為 Gitea：`http://192.168.110.200:3000/admin/momentry_core.git`
+
+### 產生 Access Token（首次設定）
+
+```bash
+# admin 帳號密碼為 AccusysTest!
+TOKEN=$(curl -s -X POST "http://192.168.110.200:3000/api/v1/users/admin/tokens" \
+  -u "admin:AccusysTest!" \
+  -H "Content-Type: application/json" \
+  -d '{"name":"m5max128_push","scopes":["write:repository"]}' | jq -r '.sha1')
+echo $TOKEN
+```
+
+### 設定 Remote
+
+```bash
+# 用 token 取代密碼
+git remote add origin http://admin:TOKEN@192.168.110.200:3000/admin/momentry_core.git
+
+# 同步
+git pull origin main
+git push origin main
+```
+
+### Token 記錄
+
+| 機器 | Token |
+|------|-------|
+| M5Max128 | `c33768c4cc26c0f4c575dcce832e92e5cf192773` (write:repository + write:user) |
+
+**注意**: Token 有 write:repository scope，勿外洩。如需新增 token 給其他機器，各自產自己的 token。
+
 ## Release Workflow
 
 ### Release 前準備
@@ -523,6 +659,16 @@ shellcheck scripts/*.sh monitor/**/*.sh
    pg_dump -U accusys -d momentry --schema-only > "$RELEASE_DIR/schema_v0.X.X.sql"
    ```
 
+5. **驗證環境變數配置**
+   - ✅ Startup scripts export all required environment variables
+   - ✅ Python scripts don't use hardcoded paths
+   - ✅ Environment variables consistent across:
+     - `.env` / `.env.development`
+     - Startup script `export`
+     - Python script `os.environ.get()`
+   - ✅ Config directory has environment-specific files
+   - ✅ AGENTS.md documents all required exports
+
 ### 重要性
 - 避免 release binary 與 current source code 不一致
 - 方便追蹤特定 release 的程式碼狀態
@@ -627,3 +773,132 @@ Phase 1: marcom 建構 (現在)    → Elementor 頁面建構
 Phase 2: 交付審視 (TBD)      → 功能確認 / 重構評估
 Phase 3: OpenCode 重構        → 純程式碼實作，交付無 Elementor 依賴版本
 ```
+
+## M4 通知規範
+
+### 固定通知方式
+
+通知 M4 的唯一管道：**`M4_workspace/` 下建立回覆文件 + `git commit`**。不需口頭、即時訊息、郵件。
+
+### 命名規則
+
+```
+docs_v1.0/M4_workspace/YYYY-MM-DD_<topic>_response.md   (回覆 M4 問題)
+docs_v1.0/M4_workspace/YYYY-MM-DD_<topic>.md             (主動通報)
+docs_v1.0/M4_workspace/YYYY-MM-DD_<topic>_test_report.md (測試報告)
+```
+
+### 觸發時機
+
+| 情境 | 動作 |
+|------|------|
+| M4 提交問題報告到 `M4_workspace/` | 修復後，回覆 `*_response.md` |
+| 完成 M4 要求的任務 | 回覆 `*_response.md` |
+| 重大變更（模型替換、架構變更） | 主動通知 `*.md` |
+| 新測試包產出 | `*_test_report.md` |
+
+### 交付檢查
+
+1. 文件寫入 `docs_v1.0/M4_workspace/`
+2. `git add` 包含該文件
+3. `git commit` 含相關變更
+4. M4 透過 git log 查看
+
+詳細規範見 `docs_v1.0/M4_workspace/M4_NOTIFICATION_PROTOCOL.md`。
+
+## UUID Naming Rule
+
+**Never use bare `uuid` in API route paths, query params, JSON keys, or code variable names. Always qualify:**
+
+| Context | Must use | Never |
+|---------|----------|-------|
+| Video/file resource | `file_uuid` | `uuid` |
+| Identity resource | `identity_uuid` | `uuid` |
+| Query parameter | `file_uuid=`, `identity_uuid=` | `uuid=` |
+| Route path | `:file_uuid`, `:identity_uuid` | `:uuid` |
+| JSON key | `"file_uuid"`, `"identity_uuid"` | `"uuid"` |
+
+This applies to docs, code, API responses, and curl examples. Exceptions: internal database primary key names (e.g. `identities.uuid` column).
+
+## Document Compliance Checklist
+
+Before creating any file in `docs_v1.0/` (API_WORKSPACE, GUIDES, REFERENCE, DESIGN, OPERATIONS, INTEGRATIONS), verify all items below.
+**IMPORTANT**: API functional documents are generated from `API_WORKSPACE/modules/`. Edit modules there, then run `make deploy` in `API_WORKSPACE/` to update `GUIDES/`. Never edit generated files in `GUIDES/` directly. See `DESIGN/Modular_Doc_System_V1.0.md` for the full system design.
+
+### P0 — Mandatory (7 items)
+
+| # | Check | Rule |
+|---|-------|------|
+| 1 | YAML frontmatter | `title`, `version`, `date`, `author`, `status` present |
+| 2 | Version history | Table at bottom of file tracking changes |
+| 3 | Top info table | scope, status, applicable to, etc. |
+| 4 | PascalCase filename | e.g. `DetectorRegistry.md`, not `detector_registry.md` |
+| 5 | `_` separator | Within filenames use `_`, never spaces or other chars |
+| 6 | English content | Entire file in English |
+| 7 | Correct directory | File must reside in appropriate directory: `API_WORKSPACE/modules/` (API endpoint modules), `GUIDES/` (user docs, generated), `REFERENCE/` (data models), `DESIGN/` (architecture), `OPERATIONS/` (infra/release), `INTEGRATIONS/` (n8n/tests) |
+
+### P0b — UUID Naming
+
+| # | Check | Rule |
+|---|-------|------|
+| 8 | `file_uuid` not bare `uuid` | All file references use `file_uuid` (see UUID Naming Rule above) |
+| 9 | `identity_uuid` not bare `uuid` | All identity references use `identity_uuid` |
+
+### P1 — Suggested (3 items)
+
+| # | Check | Note |
+|---|-------|------|
+| 1 | Cross-references | Link to related docs in API_WORKSPACE/, GUIDES/, REFERENCE/, DESIGN/, OPERATIONS/ |
+| 2 | Glossary terms | Define non-obvious terms inline or link glossary |
+| 3 | Diagrams | Include Mermaid/ASCII diagram for complex topics |
+
+### Exception
+
+`M4_workspace/` files are exempt from this checklist (free-format reply documents).
+
+---
+
+## Delivery Procedure
+
+完整交付程序（M4_workspace → M5 → Release → Deploy → Public）見：
+
+`docs_v1.0/OPERATIONS/DELIVERY_PROCEDURE.md`
+
+## Session Summary (2026-07-01: Search Mode Fixes)
+
+### Goal
+Fix search modes: Keyword BM25 ranking + People search migration to Qdrant + Qdrant scroll pagination
+
+### Done
+- **Keyword/BM25 search (`search_bm25`)**: Replaced hardcoded 1.0 score with PostgreSQL FTS (`ts_rank` + `plainto_tsquery`). Now ranks results by relevance instead of flat 1.0.
+- **Smart search merge**: Passes real FTS score through instead of fixed 0.5, so keyword-only results are properly differentiated.
+- **Qdrant scroll_points**: Added `offset` parameter for pagination support; new `scroll_all_points()` method handles multi-page scroll automatically.
+- **get_identity_traces**: Fixed broken pagination loop (always fetched same first 1000 points) by switching to `scroll_all_points`.
+- **People search (`search_persons_internal`)**: Replaced `face_detections` JOIN in universal search with Qdrant `_faces` scroll + Rust aggregation (count per identity per file, frame→second via FPS).
+- **People search (`search_persons_by_query`)**: Same migration for the REST API person search endpoint.
+- **Payload field fix**: `_faces` uses `frame` (integer) not `timestamp_secs` (float). Fixed both `search_persons_internal` and `search_persons_by_query` to read `frame` and convert via `frame / fps`.
+
+### Key Files Changed
+- `src/core/db/qdrant_db.rs`: `scroll_points` → offset pagination, new `scroll_all_points`
+- `src/api/identity_binding.rs`: Use `scroll_all_points` instead of broken loop
+- `src/api/universal_search.rs`: Rewrote `search_persons_internal` and `search_persons_by_query` to use Qdrant
+- `src/core/db/postgres_db.rs`: `search_bm25` → PostgreSQL FTS ranking
+- `src/api/search.rs`: Pass real FTS scores in merge, removed unused `KEYWORD_FIXED_SCORE`
+
+### Done This Session
+- **Qdrant scroll pagination**: `scroll_points` now accepts `offset` param + returns `next_page_offset`; new `scroll_all_points()` handles multi-page scroll automatically
+- **get_identity_traces pagination fix**: No longer fetches same 1000 points in infinite loop
+- **Keyword BM25**: `search_bm25` replaced hardcoded 1.0 score with PostgreSQL `ts_rank` + `plainto_tsquery`; `smart_search` passes real FTS scores instead of fixed 0.5
+- **People search → Qdrant**: Both `search_persons_internal` and `search_persons_by_query` replaced `face_detections` JOIN with Qdrant `_faces` scroll + Rust aggregation (count/group/sort). Fixed `timestamp_secs` → `frame` + `frame/fps` conversion
+- **list_face_candidates → Qdrant**: `identities.rs` unbound faces query now scrolls `_faces` with `is_null: identity_id` filter, sorts by confidence DESC in Rust
+- **list_unassigned_traces → Qdrant**: `identities.rs` unbound traces query now scrolls `_faces` with `is_null: identity_id` + `trace_id > 0` filter, groups by (file_uuid, trace_id) in Rust, picks best face per trace
+- **get_identity_chunks → identity_bindings**: Replaced `face_detections` frame-range JOIN with `identity_bindings` + `chunk.metadata->>'trace_id'`
+- **postgres_db.rs 5 remaining READs → Qdrant**: `get_trace_count_by_file`, `get_trace_frame_count_distribution`, `get_identity_files`, `get_identity_faces`, `get_file_faces` all migrated to `_faces` scroll + Rust aggregation
+- **agent/tools.rs fully migrated**: `exec_find_file`, `exec_list_files`, `exec_tkg_query` (8 sub-queries), `exec_identity_text`, `exec_identities_search` — all face_detections JOINs replaced with Qdrant scroll or identity_bindings
+- **job_worker.rs + storage.rs**: Remaining face_detections READs migrated to Qdrant scroll
+
+### Remaining face_detections references (all inactive/safe)
+- Schema definition (CREATE TABLE/INDEX in `postgres_db.rs`)
+- `store_face_detections_batch` — already skipped (Phase 1)
+- `workspace_sqlite.rs` — local processing DB, separate from PG
+- `bin/release.rs` — standalone release utility

CHANGELOG.md

@@ -1,143 +0,0 @@
-# Changelog
-
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
-
-## [Unreleased]
-
-### Added
-- Gitea API token integration
-- n8n API key integration
-- API key caching with Moka
-- Rate limiting for API key validation
-- Constant-time hash comparison
-- OpenAPI documentation with utoipa
-
-## [0.1.0] - 2026-03-21
-
-### Added
-
-#### API Key Management System
-- API key generation with secure random (UUID v4)
-- SHA256 key hashing
-- 5 key types: System, User, Service, Integration, Emergency
-- Key expiration with configurable TTL
-- Grace period for key rotation
-
-#### Anomaly Detection
-- High request rate detection (>1000/min)
-- High error rate detection (>50%)
-- Multiple IP detection (>5/hour)
-- Unusual time activity detection
-- Redis Pub/Sub for anomaly alerts
-
-#### Rotation Mechanism
-- Automatic rotation scheduling
-- Manual rotation requests
-- Forced rotation for security incidents
-- Grace period management per key type:
-  - System: 72 hours
-  - User: 24 hours
-  - Service: 48 hours
-  - Integration: 24 hours
-  - Emergency: 0 hours (immediate)
-
-#### PostgreSQL Integration
-- `api_keys` table for key storage
-- `api_key_audit_log` table for audit trail
-- `api_key_anomalies` table for anomaly records
-- Full CRUD operations for API keys
-
-#### Redis Integration
-- Anomaly alert Pub/Sub (`momentry:anomaly:alerts`)
-- Key anomaly state tracking
-- Real-time alert notifications
-
-#### CLI Commands
-- `momentry api-key create` - Create new API key
-- `momentry api-key list` - List all API keys
-- `momentry api-key validate` - Validate an API key
-- `momentry api-key revoke` - Revoke an API key
-- `momentry api-key rotate` - Request key rotation
-- `momentry api-key stats` - Show statistics
-
-#### Gitea Integration
-- Create Gitea Personal Access Tokens
-- List user tokens
-- Delete tokens
-- Local token tracking
-- CLI commands:
-  - `momentry gitea create`
-  - `momentry gitea list`
-  - `momentry gitea delete`
-  - `momentry gitea verify`
-
-#### n8n Integration
-- Create n8n API keys
-- List API keys
-- Delete API keys
-- Local key tracking
-- CLI commands:
-  - `momentry n8n create`
-  - `momentry n8n list`
-  - `momentry n8n delete`
-  - `momentry n8n verify`
-
-#### Security Features
-- Constant-time hash comparison (subtle crate)
-- Rate limiting for validation attempts
-- IP-based lockout after failed attempts
-- Configurable thresholds via environment variables
-
-#### Performance Optimizations
-- Moka-based API key validation cache
-- Configurable TTL and capacity
-- Reduced database queries for hot keys
-
-#### Documentation
-- API Key Management design document
-- Redis user configuration guide
-- Gitea token integration guide
-- n8n API key integration guide
-- Optimization plan with task codes
-
-### Environment Variables
-
-#### API Key Configuration
-```
-CACHE_TTL_SECONDS=300          # Cache TTL (default: 300)
-CACHE_MAX_CAPACITY=10000       # Max cache entries (default: 10000)
-RATE_LIMIT_MAX_ATTEMPTS=5      # Max failed attempts (default: 5)
-RATE_LIMIT_WINDOW_SECONDS=900  # Lockout duration (default: 900)
-```
-
-#### Service URLs
-```
-GITEA_URL=http://localhost:3000
-N8N_URL=https://n8n.momentry.ddns.net
-```
-
-### Database Schema
-
-#### Tables Created
-- `api_keys` - API key storage
-- `api_key_audit_log` - Audit trail
-- `api_key_anomalies` - Anomaly records
-- `gitea_tokens` - Gitea token tracking
-- `n8n_api_keys` - n8n API key tracking
-
-### Dependencies Added
-- `uuid` - UUID generation
-- `subtle` - Constant-time comparison
-- `moka` - Async cache
-- `utoipa` - OpenAPI documentation
-- `utoipa-swagger-ui` - Swagger UI
-
----
-
-## Version History
-
-| Version | Date | Description |
-|---------|------|-------------|
-| 0.1.0 | 2026-03-21 | Initial release with API Key Management |

Cargo.lock

@@ -166,6 +166,30 @@ version = "1.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "03918c3dbd7701a85c6b9887732e2921175f26c350b4563841d0958c21d57e6d"
 
+[[package]]
+name = "argon2"
+version = "0.5.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "3c3610892ee6e0cbce8ae2700349fcf8f98adb0dbfbee85aec3c9179d29cc072"
+dependencies = [
+ "base64ct",
+ "blake2",
+ "cpufeatures",
+ "password-hash",
+]
+
+[[package]]
+name = "async-compression"
+version = "0.4.42"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e79b3f8a79cccc2898f31920fc69f304859b3bd567490f75ebf51ae1c792a9ac"
+dependencies = [
+ "compression-codecs",
+ "compression-core",
+ "pin-project-lite",
+ "tokio",
+]
+
 [[package]]
 name = "async-lock"
 version = "3.4.2"
@@ -378,6 +402,15 @@ dependencies = [
  "wyz",
 ]
 
+[[package]]
+name = "blake2"
+version = "0.10.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "46502ad458c9a52b69d4d4d32775c788b7a1b85e8bc9d482d92250fc0e3f8efe"
+dependencies = [
+ "digest",
+]
+
 [[package]]
 name = "block-buffer"
 version = "0.10.4"
@@ -594,6 +627,25 @@ dependencies = [
  "static_assertions",
 ]
 
+[[package]]
+name = "compression-codecs"
+version = "0.4.38"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ce2548391e9c1929c21bf6aa2680af86fe4c1b33e6cea9ac1cfeec0bd11218cf"
+dependencies = [
+ "compression-core",
+ "flate2",
+ "memchr",
+ "zstd",
+ "zstd-safe",
+]
+
+[[package]]
+name = "compression-core"
+version = "0.4.32"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "cc14f565cf027a105f7a44ccf9e5b424348421a1d8952a8fc9d499d313107789"
+
 [[package]]
 name = "concurrent-queue"
 version = "2.5.0"
@@ -1564,6 +1616,12 @@ dependencies = [
  "pin-project-lite",
 ]
 
+[[package]]
+name = "http-range-header"
+version = "0.4.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "9171a2ea8a68358193d15dd5d70c1c10a2afc3e7e4c5bc92bc9f025cebd7359c"
+
 [[package]]
 name = "httparse"
 version = "1.10.1"
@@ -2052,6 +2110,21 @@ dependencies = [
  "wasm-bindgen",
 ]
 
+[[package]]
+name = "jsonwebtoken"
+version = "9.3.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5a87cc7a48537badeae96744432de36f4be2b4a34a05a5ef32e9dd8a1c169dde"
+dependencies = [
+ "base64 0.22.1",
+ "js-sys",
+ "pem",
+ "ring",
+ "serde",
+ "serde_json",
+ "simple_asn1",
+]
+
 [[package]]
 name = "kqueue"
 version = "1.1.1"
@@ -2219,6 +2292,15 @@ dependencies = [
  "winapi",
 ]
 
+[[package]]
+name = "matchers"
+version = "0.2.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "d1525a2a28c7f4fa0fc98bb91ae755d1e2d1505079e05539e35bc876b5d65ae9"
+dependencies = [
+ "regex-automata",
+]
+
 [[package]]
 name = "matches"
 version = "0.1.10"
@@ -2340,10 +2422,11 @@ dependencies = [
 
 [[package]]
 name = "momentry_core"
-version = "0.1.0"
+version = "1.0.0"
 dependencies = [
  "aes-gcm",
  "anyhow",
+ "argon2",
  "async-trait",
  "atty",
  "axum",
@@ -2358,6 +2441,7 @@ dependencies = [
  "futures-util",
  "hex",
  "jieba-rs",
+ "jsonwebtoken",
  "libc",
  "mac_address",
  "md5",
@@ -2369,6 +2453,7 @@ dependencies = [
  "qdrant-client",
  "ratatui",
  "redis",
+ "regex",
  "reqwest",
  "sdl2",
  "serde",
@@ -2379,6 +2464,7 @@ dependencies = [
  "tempfile",
  "thiserror 1.0.69",
  "tokio",
+ "tokio-util",
  "tower 0.4.13",
  "tower-http 0.5.2",
  "tracing",
@@ -2704,6 +2790,17 @@ dependencies = [
  "windows-link",
 ]
 
+[[package]]
+name = "password-hash"
+version = "0.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "346f04948ba92c43e8469c1ee6736c7563d71012b17d40745260fe106aac2166"
+dependencies = [
+ "base64ct",
+ "rand_core 0.6.4",
+ "subtle",
+]
+
 [[package]]
 name = "paste"
 version = "1.0.15"
@@ -2719,6 +2816,16 @@ dependencies = [
  "digest",
 ]
 
+[[package]]
+name = "pem"
+version = "3.0.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "1d30c53c26bc5b31a98cd02d20f25a7c8567146caf63ed593a9d87b2775291be"
+dependencies = [
+ "base64 0.22.1",
+ "serde_core",
+]
+
 [[package]]
 name = "pem-rfc7468"
 version = "0.7.0"
@@ -3869,6 +3976,18 @@ version = "0.3.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "703d5c7ef118737c72f1af64ad2f6f8c5e1921f818cdcb97b8fe6fc69bf66214"
 
+[[package]]
+name = "simple_asn1"
+version = "0.6.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "0d585997b0ac10be3c5ee635f1bab02d512760d14b7c468801ac8a01d9ae5f1d"
+dependencies = [
+ "num-bigint",
+ "num-traits",
+ "thiserror 2.0.18",
+ "time",
+]
+
 [[package]]
 name = "siphasher"
 version = "1.0.2"
@@ -4750,12 +4869,21 @@ checksum = "1e9cd434a998747dd2c4276bc96ee2e0c7a2eadf3cae88e52be55a05fa9053f5"
 dependencies = [
  "bitflags 2.11.1",
  "bytes",
+ "futures-util",
  "http",
  "http-body",
  "http-body-util",
+ "http-range-header",
+ "httpdate",
+ "mime",
+ "mime_guess",
+ "percent-encoding",
  "pin-project-lite",
+ "tokio",
+ "tokio-util",
  "tower-layer",
  "tower-service",
+ "tracing",
 ]
 
 [[package]]
@@ -4764,13 +4892,18 @@ version = "0.6.8"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "d4e6559d53cc268e5031cd8429d05415bc4cb4aefc4aa5d6cc35fbf5b924a1f8"
 dependencies = [
+ "async-compression",
  "bitflags 2.11.1",
  "bytes",
+ "futures-core",
  "futures-util",
  "http",
  "http-body",
+ "http-body-util",
  "iri-string",
  "pin-project-lite",
+ "tokio",
+ "tokio-util",
  "tower 0.5.3",
  "tower-layer",
  "tower-service",
@@ -4838,10 +4971,14 @@ version = "0.3.23"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "cb7f578e5945fb242538965c2d0b04418d38ec25c79d160cd279bf0731c8d319"
 dependencies = [
+ "matchers",
  "nu-ansi-term",
+ "once_cell",
+ "regex-automata",
  "sharded-slab",
  "smallvec",
  "thread_local",
+ "tracing",
  "tracing-core",
  "tracing-log",
 ]

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "momentry_core"
-version = "0.1.0"
+version = "1.0.0"
 edition = "2021"
 authors = ["Momentry Team"]
 description = "Digital asset management system with video analysis and RAG"
@@ -11,7 +11,7 @@ anyhow = "1.0"
 thiserror = "1.0"
 tokio = { version = "1", features = ["full"] }
 tracing = "0.1"
-tracing-subscriber = "0.3"
+tracing-subscriber = { version = "0.3", features = ["env-filter"] }
 once_cell = "1.19"
 libc = "0.2"
 dotenv = "0.15"
@@ -26,6 +26,7 @@ futures-util = "0.3"
 # Serialization
 serde = { version = "1.0", features = ["derive"] }
 serde_json = "1.0"
+regex = "1"
 chrono = { version = "0.4", features = ["serde"] }
 
 # UUID
@@ -38,6 +39,8 @@ mac_address = "1.1"
  subtle = "2.5"
  aes-gcm = "0.10"
  base64 = "0.22"
+ argon2 = "0.5"
+ jsonwebtoken = "9.3"
 
  # Text processing
  jieba-rs = "0.8.1"
@@ -52,13 +55,13 @@ sqlx = { version = "0.8", features = ["runtime-tokio", "postgres", "sqlite", "js
 mongodb = { version = "2", features = ["tokio-runtime"] }
 bson = { version = "2", features = ["chrono-0_4"] }
 qdrant-client = "1.7"
-reqwest = { version = "0.12", features = ["json"] }
+reqwest = { version = "0.12", features = ["json", "gzip", "zstd"] }
 pgvector = { version = "0.3", features = ["sqlx"] }
 
 # HTTP Server
 axum = { version = "0.7", features = ["multipart"] }
 tower = "0.4"
-tower-http = { version = "0.5", features = ["cors"] }
+tower-http = { version = "0.5", features = ["cors", "fs"] }
 
 # API Documentation
 utoipa = { version = "4", features = ["axum_extras", "chrono", "uuid"] }
@@ -79,6 +82,7 @@ crossterm = "0.28"
 
 # Terminal
 atty = "0.2"
+tokio-util = { version = "0.7.18", features = ["io"] }
 
 # System
 
@@ -98,6 +102,10 @@ optional = true
 name = "momentry"
 path = "src/main.rs"
 
+[[bin]]
+name = "momentry-cli"
+path = "src/bin/cli.rs"
+
 [[bin]]
 name = "momentry_player"
 path = "src/player/main.rs"
@@ -122,6 +130,22 @@ path = "src/bin/test_bm25_simple.rs"
 name = "integrated_player"
 path = "src/bin/integrated_player.rs"
 
+[[bin]]
+name = "release"
+path = "src/bin/release.rs"
+
+[[bin]]
+name = "vectorize_missing"
+path = "src/bin/vectorize_missing.rs"
+
+[[bin]]
+name = "sync_qdrant_from_pg"
+path = "src/bin/sync_qdrant_from_pg.rs"
+
+[[bin]]
+name = "service"
+path = "src/bin/service.rs"
+
 [build-dependencies]
 chrono = "0.4"
 

IDENTITY_BEST_FACE_API.md

@@ -0,0 +1,277 @@
+# Identity Best-Face API
+
+**狀態：** 規劃中
+**提出日期：** 2026-06-01
+**提出者：** WordPress Portal 前端團隊
+
+---
+
+## 1. 背景
+
+WordPress Portal 的 People 頁面需要在 identity detail view 與 grid card 中顯示代表臉部縮圖。目前前端作法：
+
+1. `GET /identity/{uuid}/traces` → 取得所有 trace 列表（含 `avg_confidence`）
+2. 對每個 trace 載入第一幀 thumbnail → `GET /file/{uuid}/trace/{tid}/thumbnail`
+3. 從有 thumbnail 的 trace 中，選 `avg_confidence` 最高者作為代表圖
+
+### 現有問題
+
+- **品質不佳**：trace thumbnail 固定取第一幀，不一定是該 trace 內最清晰或正面的臉部畫面
+- **浪費頻寬**：前端需發送大量並行請求（最多 20 trace × thumbnail），多數 thumbnail 最終不會被使用
+- **無快取**：每次進入 detail view 都要重複載入所有 thumbnail
+- **不一致**：同樣 identity 在 grid card 與 detail view 可能顯示不同代表圖
+
+---
+
+## 2. 目標
+
+後端新增一個 endpoint，對指定 identity **跨所有 trace** 選出品質最佳（最清晰）的臉部畫面，並提供可直接使用的縮圖 URL，支援 disk cache。
+
+---
+
+## 3. API 規格
+
+### `GET /api/v1/identity/:identity_uuid/best-face`
+
+無 query parameter。
+
+#### 成功回應 `200`
+
+```json
+{
+  "success": true,
+  "identity_uuid": "a6fb22eebefaef17e62af874997c5944",
+  "name": "Audrey Hepburn",
+  "source": "fresh",
+  "best": {
+    "file_uuid": "a6fb22eebefaef17e62af874997c5944",
+    "trace_id": 42,
+    "frame_number": 3120,
+    "timestamp_secs": 124.8,
+    "bbox": {
+      "x": 240,
+      "y": 180,
+      "width": 120,
+      "height": 160
+    },
+    "confidence": 0.97,
+    "quality_score": 18624.0,
+    "blur_score": 2.1,
+    "thumbnail_url": "/api/v1/file/a6fb22eebefaef17e62af874997c5944/trace/42/thumbnail"
+  }
+}
+```
+
+#### 無可用臉部 `200`
+
+```json
+{
+  "success": true,
+  "identity_uuid": "a6fb22eebefaef17e62af874997c5944",
+  "name": "Audrey Hepburn",
+  "source": "fresh",
+  "best": null
+}
+```
+
+#### 欄位說明
+
+| 欄位 | 型態 | 說明 |
+|------|------|------|
+| `success` | boolean | 請求是否成功 |
+| `identity_uuid` | string | identity UUID（32字元無連字號） |
+| `name` | string | identity 名稱 |
+| `source` | string | `"fresh"`（即時計算）或 `"cache"`（來自 disk cache） |
+| `best` | object/null | 最佳臉部資訊，無可用臉部時為 `null` |
+| `best.file_uuid` | string | 該臉部所屬檔案 UUID |
+| `best.trace_id` | int | 該臉部所屬 trace ID |
+| `best.frame_number` | int | 代表臉的影格編號 |
+| `best.timestamp_secs` | float | 代表臉的時間戳（秒） |
+| `best.bbox` | object | 臉部 bounding box `{x, y, width, height}` |
+| `best.confidence` | float | 該臉部的 detection confidence |
+| `best.quality_score` | float | 品質分數 = `(width * height) * confidence` |
+| `best.blur_score` | float | 模糊度分數（ffmpeg blurdetect），越低越清晰 |
+| `best.thumbnail_url` | string | 縮圖 URL（相對路徑，可直接用於瀏覽器） |
+
+---
+
+## 4. 實作建議
+
+### 4.1 建議放置位置
+
+**選項 A（建議）：** `src/api/trace_agent_api.rs`
+
+- 原因：核心邏輯重用 `select_rep_face()`（目前為 `pub(crate)`，位於同一檔案），無需修改既有的 function visibility
+- 在 `trace_agent_routes()` 中新增路由
+
+**選項 B：** `src/api/identity_binding.rs`
+
+- 需將 `select_rep_face` 改為 `pub` 才能跨檔案呼叫
+- 路由語意上更接近 identity 操作
+
+### 4.2 演算法
+
+```
+1. DISK CACHE CHECK
+   路徑：{OUTPUT_DIR}/identities/{uuid}/best_face.json
+   讀取 identity.json 的 updated_at，與 cache 中記錄的版本比較
+   若 cache 未過期 → 直接回傳（source: "cache"）
+   若無 cache 或已過期 → 繼續計算
+
+2. QUERY IDENTITY
+   SELECT id, name FROM identities
+   WHERE REPLACE(uuid::text, '-', '') = $1
+
+3. QUERY TOP N TRACES
+   SELECT fd.file_uuid, fd.trace_id,
+          AVG(fd.confidence)::float8 AS avg_conf
+   FROM {schema}.face_detections fd
+   WHERE fd.identity_id = $1
+     AND fd.confidence > 0.7
+     AND (fd.metadata->>'qc_ok' IS NULL
+          OR (fd.metadata->>'qc_ok')::boolean = true)
+   GROUP BY fd.file_uuid, fd.trace_id
+   ORDER BY avg_conf DESC
+   LIMIT 5
+
+4. FOR EACH TRACE (並行)
+   select_rep_face(pool, file_uuid, trace_id, err_fn)
+   　→ 回傳該 trace 內 blur_score 最低（最清晰）的臉
+   失敗則 skip（log warning）
+
+5. SELECT BEST AMONG RESULTS
+   主排序：blur_score ASC（越低越清晰）
+   次排序：quality_score DESC（blur_score 差距 < 0.5 時）
+   全部失敗 → best = null
+
+6. WRITE DISK CACHE
+   路徑：{OUTPUT_DIR}/identities/{uuid}/best_face.json
+   內容：best 欄位 + 計算時間 + identity updated_at
+
+7. RESPONSE
+```
+
+### 4.3 效能參數
+
+| 參數 | 值 | 說明 |
+|------|----|------|
+| TOP N | 5 | 只對 confidence 最高的 5 個 trace 做 blurdetect |
+| confidence 門檻 | > 0.7 | 同既有的 `select_rep_face` 邏輯 |
+| QC 過濾 | qc_ok = true/null | 同既有邏輯 |
+| ffmpeg timeout | inherit from Command | 每個 trace 約 1-3s |
+| cache TTL | 直到下一次 bind/unbind/merge | 事件驅動失效 |
+
+### 4.4 快取策略
+
+**寫入時機：** `get_identity_best_face` 計算完成後
+
+**失效時機（刪除 `best_face.json`）：**
+
+| 觸發 operation | 所在檔案 | 備註 |
+|---------------|---------|------|
+| `bind_trace` (POST) | `identity_binding.rs` | 新增 face 關聯 |
+| `unbind` (POST) | `identity_binding.rs` | 移除 face 關聯 |
+| `mergeinto` (POST) | `identity_binding.rs` | source + target 雙雙清除 |
+| `profile-image` (POST) | `identity_api.rs` | 使用者上傳新大頭照 |
+
+**Cache 驗證機制：** 儲存計算時的 `identity.updated_at`，每次請求時比對：
+- 若 identity 的 `updated_at` 未變 → cache 有效
+- 若已變 → 重新計算
+
+### 4.5 建議的新增/修改檔案
+
+| 檔案 | 動作 | 說明 |
+|------|------|------|
+| `src/api/trace_agent_api.rs` | **新增** handler + struct + route | ~+130 行 |
+| `src/api/identity_binding.rs` | **修改** 3 處 + cache invalidation helper | ~+25 行 |
+| `src/api/identity_api.rs` | **修改** 1 處（profile-image POST） | ~+5 行 |
+
+### 4.6 需要的新 struct
+
+**`src/api/trace_agent_api.rs`**（或獨立檔案 `src/core/identity_best_face.rs`）：
+
+```rust
+#[derive(Debug, Serialize, Deserialize)]
+pub struct BestFaceResponse {
+    pub success: bool,
+    pub identity_uuid: String,
+    pub name: String,
+    pub source: String,
+    pub best: Option<BestFaceResult>,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct BestFaceResult {
+    pub file_uuid: String,
+    pub trace_id: i32,
+    pub frame_number: i64,
+    pub timestamp_secs: f64,
+    pub bbox: RepFaceBbox,
+    pub confidence: f64,
+    pub quality_score: f64,
+    pub blur_score: f64,
+    pub thumbnail_url: String,
+}
+```
+
+### 4.7 Cache Invalidation Helper Function
+
+```rust
+async fn invalidate_best_face_cache(output_dir: &str, uuid_clean: &str) {
+    let path = format!("{}/identities/{}/best_face.json", output_dir, uuid_clean);
+    let _ = tokio::fs::remove_file(path).await;
+}
+```
+
+---
+
+## 5. 前端整合參考（供後端團隊理解使用情境）
+
+WP snippet 72 (`ms-people.js`) 的 `loadPersonDetail` 中，優先使用新 endpoint：
+
+```js
+async function loadPersonDetail(person) {
+  if (person.thumb && person._hasProfileImage) return;
+
+  try {
+    const res = await apiFetch('/identity/' + person.id + '/best-face');
+    if (res?.success && res?.best) {
+      const b = res.best;
+      person.thumb = `${API_BASE}/file/${b.file_uuid}/trace/${b.trace_id}/thumbnail?api_key=${API_KEY}`;
+      person._hasProfileImage = true;
+      updateDetailAvatar(person);
+      return;
+    }
+  } catch (e) { /* fallback to legacy */ }
+
+  // 原邏輯：traces → thumbnails → confidence sort
+}
+```
+
+同樣可用於 grid card 的代表圖載入（`loadGridThumbnails`）：
+
+```js
+// 一次性載入所有 pending identity 的 best-face
+const results = await Promise.allSettled(
+  persons.map(p => apiFetch('/identity/' + p.id + '/best-face'))
+);
+```
+
+---
+
+## 6. 驗收標準
+
+1. `GET /api/v1/identity/{uuid}/best-face` → `200` + valid JSON
+2. 有 trace 的 identity → `best` 不為 null，且 `blur_score` 為該 identity 所有 trace 中最低
+3. 無 trace 的 identity → `best: null`
+4. 短時間內重複請求同一 identity → `source: "cache"`，回應時間 < 10ms
+5. 綁定新 trace 後再次請求 → `source: "fresh"`（cache 已正確失效）
+6. `thumbnail_url` 可直接用於 `<img>` 顯示
+
+---
+
+## 7. 風險與注意事項
+
+- **首次請求延遲**：對有大量 trace 的 identity（如主角），首次請求可能需 5-15 秒。建議前端顯示 loading state
+- **ffmpeg 資源**：同時多個請求可能導致高 CPU 使用。可考慮加入 per-identity lock 避免重複計算
+- **邊界案例**：trace 內的 faces 全部 confidence ≤ 0.7 或 qc_ok=false，則該 trace 被跳過，可能導致 `best: null`

SYNC_V1.1.md

@@ -0,0 +1,78 @@
+# Sync Notes 2026-05-21
+
+## M5Max128 收到後需要做的事
+
+```bash
+cd ~/momentry_core
+git pull origin main       # 拉取所有變更
+cat SYNC_V1.1.md           # 閱讀此文件
+
+# 資料庫變更（必須先執行，否則 worker 會 fail）
+psql -U accusys -d momentry -c "ALTER TABLE public.pre_chunks ALTER COLUMN coordinate_index SET DEFAULT 0;"
+
+# 重建 + 重啟
+cargo build --release --bin momentry
+./run-server-3002.sh
+```
+
+---
+
+## Bugs Fixed (13)
+
+| # | 問題 | 根因 | 修復 |
+|---|------|------|------|
+| 1 | `GET /identity/:uuid/files` 空資料 | SQL 缺 `REPLACE(uuid)` + 缺 `JOIN videos` | 改用 `REPLACE(uuid::text...)` + JOIN videos + `frame_number/fps` |
+| 2 | `GET /identity/:uuid/faces` crash + 空 | `i64`/`INT4` 型別不符 + 硬編碼 NULL/0 | `id::bigint`、`confidence::float8` + 真實欄位 |
+| 3 | `GET /identity/:uuid` crash | `IdentityDetailRecord.id` 是 `i64` 但 DB 是 `INT4` | `id::bigint as id` |
+| 4 | `GET /file/:uuid/identities` 空 | 雙重 stub（handler + DB 都 `Vec::new()`） | 完整實作 + 正確 total count |
+| 5 | `GET /identities/search?q=Louis` 500 | `c.text_content` NULL 但 Rust tuple 用 `String` | 改 `Option<String>` |
+| 6 | `POST /search/universal` person type first/last_time null | `search_persons_internal` 用 `timestamp_secs` | 改 `frame_number/fps` + JOIN videos |
+| 7 | faces/files/chunks total 不正確 | `total: data.len()` | 獨立 COUNT 查詢 |
+| 8 | `GET /identity/:uuid/traces` 無分頁 | 缺 page/page_size | 新增 `TracesQuery` + LIMIT/OFFSET |
+| 9 | 身分比對 frame-level 不穩定 | frame-level Qdrant | 改 **trace-level**（AVG embedding per trace） |
+| 10 | Charade face embedding 不在 Qdrant | 沒跑 `sync_face_embeddings` | match API 自動 push + ANN search |
+| 11 | 無眼睛 face 推入 Qdrant | 無 QC 過濾 | `face_landmark_qc.py --apply` + Qdrant sync 過濾 `qc_ok` |
+| 12 | TMDb 比對 dev/prod 不一致 | Qdrant ANN 不同 collection | trace-level 改善穩定性 |
+| 13 | `faces/files/chunks total` 顯示 page_size | `total: data.len()` | 改為獨立 COUNT 查詢 |
+
+## ✨ 新功能 (6)
+
+| # | 功能 | 說明 |
+|---|------|------|
+| 1 | `POST /api/v1/tmdb/fetch` | 從 TMDb 下載 cast → 建立 identity + json + jpg + Qdrant |
+| 2 | `POST /api/v1/agents/tmdb/match/:file_uuid` | 推 face → Qdrant ANN search → bind identity |
+| 3 | `GET /api/v1/identity/:uuid/status` | 檢查 identity.json + profile.jpg 是否存在 |
+| 4 | `/health` 新增 watcher/worker/時區 | `watcher_running`、`worker_running`、`system_timezone` |
+| 5 | `SYSTEM_TIMEZONE` config | 自動偵測系統時區，可 `MOMENTRY_TIMEZONE` 覆蓋 |
+| 6 | `GET /identity/:uuid/traces` 分頁 | `?page=1&page_size=20` |
+
+## 🔧 資料庫變更
+
+```sql
+-- 必須執行（否則 worker 的 CUT processor 會失敗）
+ALTER TABLE public.pre_chunks ALTER COLUMN coordinate_index SET DEFAULT 0;
+
+-- 選擇性（face_landmark_qc.py --apply 需要）
+ALTER TABLE public.face_detections ADD COLUMN metadata jsonb DEFAULT '{}'::jsonb;
+```
+
+## 🗑️ 清理
+
+- 刪除 2,769 個孤兒 `person_xxx` identity（無 face_detections）
+- `person_identities` + `person_appearances` table 已 DROP
+
+## 📂 主要檔案變更
+
+| 檔案 | 說明 |
+|------|------|
+| `src/api/identity_api.rs` | identity detail/files/faces total 修正 + status endpoint |
+| `src/api/identity_binding.rs` | traces 分頁（新增 `page`/`page_size`/`total`） |
+| `src/api/server.rs` | health 新增 watcher/worker/system_timezone |
+| `src/api/tmdb_api.rs` | **新檔案** — tmdb/fetch + match 端點 |
+| `src/api/universal_search.rs` | person search 改 frame_number/fps |
+| `src/core/config.rs` | 新增 SYSTEM_TIMEZONE |
+| `src/core/db/qdrant_db.rs` | search_face_collection + sync_trace_embeddings + batch upsert |
+| `src/core/db/postgres_db.rs` | get_identity_files/faces 修正 + get_file_identities 實作 |
+| `src/core/tmdb/probe.rs` | extract_movie_name 改進（只取 `(` 前） |
+| `scripts/face_landmark_qc.py` | 新增 `--apply` + `--schema` 參數 |
+| `Cargo.toml` | reqwest 加 `gzip` feature |

a1b10138a6bbb0cd.cut.json

@@ -1 +0,0 @@
-/Users/accusys/momentry_core_0.1/output/a1b10138a6bbb0cd.cut.json

a1b10138a6bbb0cd.face.json

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-/Users/accusys/momentry_core_0.1/output/a1b10138a6bbb0cd.face.json

a1b10138a6bbb0cd.ocr.json

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-/Users/accusys/momentry_core_0.1/output/a1b10138a6bbb0cd.ocr.json

a1b10138a6bbb0cd.pose.json

@@ -1 +0,0 @@
-/Users/accusys/momentry_core_0.1/output/a1b10138a6bbb0cd.pose.json

a1b10138a6bbb0cd.story.json

@@ -1 +0,0 @@
-/Users/accusys/momentry_core_0.1/output/a1b10138a6bbb0cd.story.json

a1b10138a6bbb0cd.yolo.json

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-/Users/accusys/momentry_core_0.1/output/a1b10138a6bbb0cd.yolo.json

benchmark_asr.py

@@ -1,161 +0,0 @@
-#!/usr/bin/env python3
-"""Benchmark ASR processor direct vs chunked transcription overhead."""
-
-import sys
-import os
-import subprocess
-import json
-import tempfile
-import time
-import shutil
-import statistics
-
-# Use a small video clip for consistent benchmarking
-VIDEO_SOURCE = "../test_video/BigBuckBunny_320x180.mp4"  # 10 minutes, 62MB
-if not os.path.exists(VIDEO_SOURCE):
-    print(f"Video not found: {VIDEO_SOURCE}")
-    sys.exit(1)
-
-# Create temporary directory for all test runs
-temp_dir = tempfile.mkdtemp(prefix="asr_bench_")
-print(f"Benchmark directory: {temp_dir}")
-
-
-def run_asr_mode(mode_name, max_direct_duration, chunk_duration=600):
-    """Run ASR processor with given parameters, return timing and resource stats."""
-    clip_path = os.path.join(temp_dir, f"clip_{mode_name}.mp4")
-    output_path = os.path.join(temp_dir, f"output_{mode_name}.json")
-
-    # Copy source video to clip path (no transcoding)
-    shutil.copy2(VIDEO_SOURCE, clip_path)
-
-    env = os.environ.copy()
-    env["MOMENTRY_ASR_MAX_DIRECT_DURATION"] = str(max_direct_duration)
-    env["MOMENTRY_ASR_CHUNK_DURATION"] = str(chunk_duration)
-    env["MOMENTRY_ASR_MODEL_SIZE"] = "tiny"
-    env["MOMENTRY_ASR_COMPUTE_TYPE"] = "int8"
-
-    cmd = [
-        "/opt/homebrew/bin/python3.11",
-        "scripts/asr_processor.py",
-        clip_path,
-        output_path,
-        "--uuid",
-        f"bench_{mode_name}",
-    ]
-
-    # Start monitoring (external)
-    import psutil
-
-    start_time = time.time()
-    proc = subprocess.Popen(
-        cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, env=env
-    )
-
-    # Monitor CPU and memory of child process
-    cpu_percents = []
-    memory_mbs = []
-
-    while True:
-        try:
-            p = psutil.Process(proc.pid)
-            cpu = p.cpu_percent(interval=0.1)
-            mem = p.memory_info().rss / (1024 * 1024)
-            cpu_percents.append(cpu)
-            memory_mbs.append(mem)
-        except (psutil.NoSuchProcess, psutil.AccessDenied):
-            break
-        if proc.poll() is not None:
-            # Process ended, wait a bit for final stats
-            time.sleep(0.1)
-            break
-
-    stdout, stderr = proc.communicate(timeout=1)
-    elapsed = time.time() - start_time
-    returncode = proc.returncode
-
-    # Read output
-    segments = []
-    if os.path.exists(output_path):
-        with open(output_path, "r") as f:
-            data = json.load(f)
-            segments = data.get("segments", [])
-
-    # Clean up temporary files
-    try:
-        os.unlink(clip_path)
-        os.unlink(output_path)
-    except:
-        pass
-
-    return {
-        "mode": mode_name,
-        "elapsed": elapsed,
-        "returncode": returncode,
-        "segments": len(segments),
-        "cpu_avg": statistics.mean(cpu_percents) if cpu_percents else 0,
-        "cpu_max": max(cpu_percents) if cpu_percents else 0,
-        "memory_avg": statistics.mean(memory_mbs) if memory_mbs else 0,
-        "memory_max": max(memory_mbs) if memory_mbs else 0,
-        "stderr": stderr.decode() if stderr else "",
-    }
-
-
-try:
-    # Run direct transcription (clip duration ~600s, max_direct=1800)
-    print("Running direct transcription benchmark...")
-    direct = run_asr_mode("direct", max_direct_duration=1800, chunk_duration=600)
-
-    # Run chunked transcription (force chunked with max_direct=300, chunk=120)
-    print("Running chunked transcription benchmark...")
-    chunked = run_asr_mode("chunked", max_direct_duration=300, chunk_duration=120)
-
-    # Calculate overhead
-    overhead = (chunked["elapsed"] - direct["elapsed"]) / direct["elapsed"] * 100
-
-    # Print results
-    print("\n" + "=" * 60)
-    print("ASR PROCESSOR BENCHMARK RESULTS")
-    print("=" * 60)
-    print(f"Test video: {VIDEO_SOURCE}")
-    print(f"Video duration: ~10 minutes (600 seconds)")
-    print()
-    print("Direct Transcription:")
-    print(f"  Time: {direct['elapsed']:.1f}s")
-    print(f"  Segments: {direct['segments']}")
-    print(f"  CPU avg/max: {direct['cpu_avg']:.1f}% / {direct['cpu_max']:.1f}%")
-    print(
-        f"  Memory avg/max: {direct['memory_avg']:.1f} MB / {direct['memory_max']:.1f} MB"
-    )
-    print()
-    print("Chunked Transcription:")
-    print(f"  Time: {chunked['elapsed']:.1f}s")
-    print(f"  Segments: {chunked['segments']}")
-    print(f"  CPU avg/max: {chunked['cpu_avg']:.1f}% / {chunked['cpu_max']:.1f}%")
-    print(
-        f"  Memory avg/max: {chunked['memory_avg']:.1f} MB / {chunked['memory_max']:.1f} MB"
-    )
-    print()
-    print("OVERHEAD ANALYSIS:")
-    print(f"  Time overhead: {overhead:.2f}%")
-    if overhead <= 5:
-        print(f"  ✅ PASS: Overhead ≤5% requirement")
-    else:
-        print(f"  ❌ FAIL: Overhead exceeds 5% limit")
-    print()
-
-    # Check for errors
-    if direct["returncode"] != 0:
-        print(f"WARNING: Direct transcription returned {direct['returncode']}")
-    if chunked["returncode"] != 0:
-        print(f"WARNING: Chunked transcription returned {chunked['returncode']}")
-
-except Exception as e:
-    print(f"Benchmark failed: {e}")
-    import traceback
-
-    traceback.print_exc()
-finally:
-    # Clean up directory
-    shutil.rmtree(temp_dir, ignore_errors=True)
-    print(f"Cleaned up {temp_dir}")

benchmark_realistic.py

@@ -1,151 +0,0 @@
-#!/usr/bin/env python3
-"""Benchmark ASR with realistic chunk sizes."""
-
-import sys
-import os
-import subprocess
-import json
-import tempfile
-import time
-import shutil
-import statistics
-
-VIDEO_SOURCE = "../test_video/BigBuckBunny_320x180.mp4"  # 10 minutes, 62MB
-if not os.path.exists(VIDEO_SOURCE):
-    print(f"Video not found: {VIDEO_SOURCE}")
-    sys.exit(1)
-
-
-def run_asr_mode(mode_name, max_direct_duration, chunk_duration, description):
-    """Run ASR processor with given parameters, return timing."""
-    clip_path = os.path.join(temp_dir, f"clip_{mode_name}.mp4")
-    output_path = os.path.join(temp_dir, f"output_{mode_name}.json")
-
-    # Copy source video to clip path
-    shutil.copy2(VIDEO_SOURCE, clip_path)
-
-    env = os.environ.copy()
-    env["MOMENTRY_ASR_MAX_DIRECT_DURATION"] = str(max_direct_duration)
-    env["MOMENTRY_ASR_CHUNK_DURATION"] = str(chunk_duration)
-    env["MOMENTRY_ASR_MODEL_SIZE"] = "tiny"
-    env["MOMENTRY_ASR_COMPUTE_TYPE"] = "int8"
-
-    cmd = [
-        "/opt/homebrew/bin/python3.11",
-        "scripts/asr_processor.py",
-        clip_path,
-        output_path,
-        "--uuid",
-        f"bench_{mode_name}",
-    ]
-
-    start_time = time.time()
-    proc = subprocess.run(cmd, capture_output=True, env=env, text=True)
-    elapsed = time.time() - start_time
-    returncode = proc.returncode
-
-    # Read output
-    segments = []
-    language = ""
-    if os.path.exists(output_path):
-        with open(output_path, "r") as f:
-            data = json.load(f)
-            segments = data.get("segments", [])
-            language = data.get("language", "")
-
-    # Clean up
-    try:
-        os.unlink(clip_path)
-        os.unlink(output_path)
-    except:
-        pass
-
-    return {
-        "mode": mode_name,
-        "description": description,
-        "elapsed": elapsed,
-        "returncode": returncode,
-        "segments": len(segments),
-        "language": language,
-        "stderr": proc.stderr[:200] if proc.stderr else "",
-    }
-
-
-# Create temporary directory
-temp_dir = tempfile.mkdtemp(prefix="asr_bench_real_")
-print(f"Benchmark directory: {temp_dir}")
-
-try:
-    # Test 1: Direct transcription (video is 10 min, max_direct=30 min)
-    print("\n1. Direct transcription (max_direct=1800s, chunk=600s):")
-    direct = run_asr_mode(
-        "direct",
-        max_direct_duration=1800,
-        chunk_duration=600,
-        description="Direct (video < 30min threshold)",
-    )
-    print(f"   Time: {direct['elapsed']:.1f}s, Segments: {direct['segments']}")
-
-    # Test 2: Chunked with 1 chunk (force chunked but chunk size = video duration)
-    print("\n2. Chunked with 1 chunk (max_direct=300s, chunk=600s):")
-    chunked1 = run_asr_mode(
-        "chunked1",
-        max_direct_duration=300,
-        chunk_duration=600,
-        description="Chunked with 1 chunk (10 min)",
-    )
-    print(f"   Time: {chunked1['elapsed']:.1f}s, Segments: {chunked1['segments']}")
-
-    # Test 3: Chunked with 2 chunks (5 min each)
-    print("\n3. Chunked with 2 chunks (max_direct=300s, chunk=300s):")
-    chunked2 = run_asr_mode(
-        "chunked2",
-        max_direct_duration=300,
-        chunk_duration=300,
-        description="Chunked with 2 chunks (5 min each)",
-    )
-    print(f"   Time: {chunked2['elapsed']:.1f}s, Segments: {chunked2['segments']}")
-
-    # Test 4: Chunked with 5 chunks (2 min each) - worst case
-    print("\n4. Chunked with 5 chunks (max_direct=300s, chunk=120s):")
-    chunked5 = run_asr_mode(
-        "chunked5",
-        max_direct_duration=300,
-        chunk_duration=120,
-        description="Chunked with 5 chunks (2 min each)",
-    )
-    print(f"   Time: {chunked5['elapsed']:.1f}s, Segments: {chunked5['segments']}")
-
-    # Calculate overheads
-    print("\n" + "=" * 60)
-    print("OVERHEAD ANALYSIS (compared to direct transcription)")
-    print("=" * 60)
-
-    for test in [chunked1, chunked2, chunked5]:
-        if direct["elapsed"] > 0:
-            overhead = (test["elapsed"] - direct["elapsed"]) / direct["elapsed"] * 100
-            status = "✅ ≤5%" if overhead <= 5 else "❌ >5%"
-            print(f"\n{test['description']}:")
-            print(f"  Time: {test['elapsed']:.1f}s (direct: {direct['elapsed']:.1f}s)")
-            print(f"  Overhead: {overhead:.2f}% {status}")
-            print(f"  Segments: {test['segments']} (direct: {direct['segments']})")
-            if test["segments"] != direct["segments"]:
-                print(f"  ⚠️ Segment count mismatch!")
-
-    # Summary
-    print("\n" + "=" * 60)
-    print("SUMMARY")
-    print("=" * 60)
-    print(f"Video: {os.path.basename(VIDEO_SOURCE)} (~10 minutes)")
-    print(f"\nKey finding: Overhead depends heavily on chunk count.")
-    print(f"With realistic chunk sizes (10 min), overhead should be minimal.")
-
-except Exception as e:
-    print(f"Benchmark failed: {e}")
-    import traceback
-
-    traceback.print_exc()
-finally:
-    # Clean up directory
-    shutil.rmtree(temp_dir, ignore_errors=True)
-    print(f"\nCleaned up {temp_dir}")

build.rs

@@ -1,19 +1,81 @@
-use chrono::Local;
-use std::env;
+use std::collections::BTreeMap;
+use std::path::Path;
 
 fn main() {
-    let now = Local::now();
-    let build_time = now.format("%Y-%m-%d %H:%M:%S").to_string();
+    let version = std::env::var("CARGO_PKG_VERSION").unwrap_or_else(|_| "unknown".to_string());
 
-    // Get version from Cargo.toml
-    let version = env!("CARGO_PKG_VERSION");
-    let full_version = format!("{} (build: {})", version, build_time);
+    let git_hash = std::process::Command::new("git")
+        .args(["rev-parse", "--short", "HEAD"])
+        .output()
+        .ok()
+        .and_then(|o| String::from_utf8(o.stdout).ok())
+        .map(|s| s.trim().to_string())
+        .unwrap_or_else(|| "unknown".to_string());
 
-    // Set build-time environment variables
-    println!("cargo:rustc-env=BUILD_VERSION={}", full_version);
-    println!("cargo:rustc-env=BUILD_TIME={}", build_time);
-    println!("cargo:rustc-env=VERSION={}", version);
+    let timestamp = std::process::Command::new("date")
+        .args(["-u", "+%Y-%m-%dT%H:%M:%SZ"])
+        .output()
+        .ok()
+        .and_then(|o| String::from_utf8(o.stdout).ok())
+        .map(|s| s.trim().to_string())
+        .unwrap_or_else(|| "unknown".to_string());
 
-    // Also print for debugging
-    println!("cargo:warning=Building version: {}", full_version);
+    println!("cargo:rustc-env=BUILD_VERSION={}", version);
+    println!("cargo:rustc-env=BUILD_GIT_HASH={}", git_hash);
+    println!("cargo:rustc-env=BUILD_TIMESTAMP={}", timestamp);
+
+    // ── Schema migration manifest ──
+    // Scan release/migrate_*.sql, compute SHA256, embed as JSON string
+    let manifest_dir = std::env::var("CARGO_MANIFEST_DIR").unwrap_or_else(|_| ".".to_string());
+    let release_dir = Path::new(&manifest_dir).join("release");
+
+    let mut migrations = BTreeMap::new(); // sorted by filename
+    if let Ok(entries) = std::fs::read_dir(&release_dir) {
+        for entry in entries.flatten() {
+            let path = entry.path();
+            let fname = path.file_name().and_then(|n| n.to_str()).unwrap_or("");
+            if fname.starts_with("migrate_") && fname.ends_with(".sql") {
+                if let Ok(content) = std::fs::read(&path) {
+                    let hash = sha256_hex(&content);
+                    migrations.insert(fname.to_string(), hash);
+                }
+            }
+        }
+    }
+
+    // Encode as comma-separated: name1:hash1,name2:hash2,...
+    let manifest: String = migrations
+        .iter()
+        .map(|(name, hash)| format!("{}:{}", name, hash))
+        .collect::<Vec<_>>()
+        .join(",");
+    println!("cargo:rustc-env=REQUIRED_MIGRATIONS={}", manifest);
+    println!(
+        "cargo:info=Embedded {} migration checksums",
+        migrations.len()
+    );
+}
+
+fn sha256_hex(data: &[u8]) -> String {
+    use std::io::Write;
+    use std::process::{Command, Stdio};
+    if let Ok(mut child) = Command::new("shasum")
+        .arg("-a")
+        .arg("256")
+        .stdin(Stdio::piped())
+        .stdout(Stdio::piped())
+        .spawn()
+    {
+        if let Some(mut stdin) = child.stdin.take() {
+            let _ = stdin.write_all(data);
+        }
+        if let Ok(out) = child.wait_with_output() {
+            if let Ok(s) = String::from_utf8(out.stdout) {
+                if let Some(hash) = s.split(' ').next() {
+                    return hash.to_string();
+                }
+            }
+        }
+    }
+    "unknown".to_string()
 }

check_jobs.rs

@@ -0,0 +1,26 @@
+use sqlx::postgres::PgPoolOptions;
+
+#[tokio::main]
+async fn main() -> Result<(), Box<dyn std::error::Error>> {
+    let pool = PgPoolOptions::new()
+        .max_connections(1)
+        .connect("postgres://accusys@localhost:5432/momentry")
+        .await?;
+
+    let row: Option<(i32, String, String, Option<String>)> = sqlx::query_as(
+        "SELECT id, uuid, status, processors FROM monitor_jobs WHERE uuid = 'd8acb03870f0cc9b14e01f14a7bf24d6' ORDER BY id DESC LIMIT 1"
+    )
+    .fetch_optional(&pool)
+    .await?;
+
+    if let Some((id, uuid, status, processors)) = row {
+        println!("Job ID: {}", id);
+        println!("UUID: {}", uuid);
+        println!("Status: {}", status);
+        println!("Processors: {:?}", processors);
+    } else {
+        println!("No job found for this UUID");
+    }
+
+    Ok(())
+}

check_jobs_status.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+# Query PostgreSQL monitor_jobs status
+# Using Rust code to execute SQL
+
+echo "Jobs in PostgreSQL:"
+cat << 'SQL' > query_jobs.sql
+SELECT uuid, status, processors, created_at::date 
+FROM monitor_jobs 
+ORDER BY created_at DESC 
+LIMIT 10;
+SQL
+
+echo "SQL query created. Need to execute via API or Rust..."

check_whisper.py

@@ -1,7 +0,0 @@
-#!/opt/homebrew/bin/python3.11
-try:
-    import whisper
-
-    print("whisper available")
-except ImportError as e:
-    print(f"whisper not available: {e}")

chunked_transcribe.py

@@ -1,200 +0,0 @@
-#!/usr/bin/env python3
-"""
-Chunked transcription to handle large audio files.
-"""
-
-import sys
-import time
-import tempfile
-import json
-import subprocess
-from pathlib import Path
-import numpy as np
-
-
-def split_audio(input_path, chunk_duration=1800, output_dir=None):
-    """Split audio into chunks using ffmpeg."""
-    if output_dir is None:
-        output_dir = Path(tempfile.mkdtemp(prefix="audio_chunks_"))
-    else:
-        output_dir = Path(output_dir)
-    output_dir.mkdir(exist_ok=True, parents=True)
-
-    # Get total duration
-    cmd = [
-        "ffprobe",
-        "-v",
-        "error",
-        "-show_entries",
-        "format=duration",
-        "-of",
-        "csv=p=0",
-        str(input_path),
-    ]
-    result = subprocess.run(cmd, capture_output=True, text=True)
-    total_duration = float(result.stdout.strip())
-
-    print(
-        f"Total audio duration: {total_duration:.1f}s ({total_duration / 3600:.1f} hrs)"
-    )
-    print(f"Splitting into {chunk_duration}s chunks...")
-
-    chunks = []
-    start = 0
-    chunk_idx = 0
-    while start < total_duration:
-        chunk_path = output_dir / f"chunk_{chunk_idx:04d}.wav"
-        cmd = [
-            "ffmpeg",
-            "-i",
-            str(input_path),
-            "-ss",
-            str(start),
-            "-t",
-            str(chunk_duration),
-            "-acodec",
-            "pcm_s16le",
-            "-ar",
-            "16000",
-            "-ac",
-            "1",
-            "-y",
-            str(chunk_path),
-        ]
-        subprocess.run(cmd, capture_output=True)
-        if chunk_path.exists() and chunk_path.stat().st_size > 0:
-            chunks.append(
-                {
-                    "path": chunk_path,
-                    "start_time": start,
-                    "end_time": min(start + chunk_duration, total_duration),
-                }
-            )
-        else:
-            print(f"Warning: Chunk {chunk_idx} may be empty")
-        start += chunk_duration
-        chunk_idx += 1
-
-    print(f"Created {len(chunks)} chunks in {output_dir}")
-    return chunks, output_dir
-
-
-def transcribe_chunk(chunk_info, model, chunk_idx, total_chunks):
-    """Transcribe a single chunk."""
-    print(
-        f"[{chunk_idx + 1}/{total_chunks}] Transcribing chunk {chunk_info['start_time']:.1f}-{chunk_info['end_time']:.1f}"
-    )
-    start_time = time.time()
-
-    segments, info = model.transcribe(str(chunk_info["path"]), beam_size=5)
-    results = []
-    for segment in segments:
-        # Adjust timestamps by chunk start time
-        results.append(
-            {
-                "start": segment.start + chunk_info["start_time"],
-                "end": segment.end + chunk_info["start_time"],
-                "text": segment.text.strip(),
-            }
-        )
-
-    elapsed = time.time() - start_time
-    print(f"  → {len(results)} segments in {elapsed:.1f}s")
-    return results, info
-
-
-def main():
-    import argparse
-
-    parser = argparse.ArgumentParser(description="Chunked transcription")
-    parser.add_argument("audio_path", help="Audio file path")
-    parser.add_argument(
-        "--chunk-duration",
-        type=int,
-        default=1800,
-        help="Chunk duration in seconds (default: 1800 = 30 min)",
-    )
-    parser.add_argument("--model-size", default="tiny", help="Whisper model size")
-    parser.add_argument("--compute-type", default="int8", help="Compute type")
-    parser.add_argument(
-        "--output", "-o", default="chunked_transcription.json", help="Output JSON path"
-    )
-    args = parser.parse_args()
-
-    audio_path = Path(args.audio_path)
-    if not audio_path.exists():
-        print(f"Error: File not found: {audio_path}")
-        sys.exit(1)
-
-    print(f"Chunked Transcription for {audio_path}")
-    print(f"Model: {args.model_size}, Compute: {args.compute_type}")
-    print(
-        f"Chunk duration: {args.chunk_duration}s ({args.chunk_duration / 60:.1f} min)"
-    )
-
-    # Split audio
-    chunks, temp_dir = split_audio(audio_path, chunk_duration=args.chunk_duration)
-    if not chunks:
-        print("No chunks created")
-        sys.exit(1)
-
-    # Load model once
-    print("Loading Whisper model...")
-    from faster_whisper import WhisperModel
-
-    model_start = time.time()
-    model = WhisperModel(args.model_size, device="cpu", compute_type=args.compute_type)
-    print(f"Model loaded in {time.time() - model_start:.1f}s")
-
-    # Process each chunk
-    all_segments = []
-    language = None
-    language_prob = None
-
-    for i, chunk in enumerate(chunks):
-        try:
-            segments, info = transcribe_chunk(chunk, model, i, len(chunks))
-            all_segments.extend(segments)
-            if language is None:
-                language = info.language
-                language_prob = info.language_probability
-        except Exception as e:
-            print(f"Error transcribing chunk {i}: {e}")
-            import traceback
-
-            traceback.print_exc()
-            # Continue with next chunk
-
-    # Sort segments by start time
-    all_segments.sort(key=lambda x: x["start"])
-
-    # Save results
-    output = {
-        "language": language or "unknown",
-        "language_probability": language_prob or 0.0,
-        "segments": all_segments,
-        "chunk_count": len(chunks),
-        "chunk_duration": args.chunk_duration,
-        "total_segments": len(all_segments),
-    }
-
-    output_path = Path(args.output)
-    output_path.parent.mkdir(exist_ok=True, parents=True)
-    with open(output_path, "w") as f:
-        json.dump(output, f, indent=2)
-
-    print(f"\nTranscription completed:")
-    print(f"  Total segments: {len(all_segments)}")
-    print(
-        f"  Language: {output['language']} (prob {output['language_probability']:.2f})"
-    )
-    print(f"  Results saved to: {output_path}")
-
-    # Cleanup temp directory
-    import shutil
-
-    shutil.rmtree(temp_dir, ignore_errors=True)
-
-
-if __name__ == "__main__":
-    main()

clear_failed_processor.sql

@@ -0,0 +1,10 @@
+-- Delete failed face processor result to allow retry
+DELETE FROM processor_results 
+WHERE job_id = 62 
+AND processor = 'face' 
+AND status = 'failed';
+
+-- Check remaining processor_results for this job
+SELECT id, processor, status, retry_count 
+FROM processor_results 
+WHERE job_id = 62;

com.momentry.api.updated.plist

@@ -1,64 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
-<plist version="1.0">
-<dict>
-    <key>Label</key>
-    <string>com.momentry.api</string>
-    
-    <key>UserName</key>
-    <string>accusys</string>
-    
-    <key>GroupName</key>
-    <string>staff</string>
-    
-    <key>WorkingDirectory</key>
-    <string>/Users/accusys/momentry_core_0.1</string>
-    
-    <key>ProgramArguments</key>
-    <array>
-        <string>/Users/accusys/momentry_core_0.1/target/release/momentry</string>
-        <string>server</string>
-        <string>--port</string>
-        <string>3002</string>
-    </array>
-    
-    <key>EnvironmentVariables</key>
-    <dict>
-        <key>PATH</key>
-        <string>/opt/homebrew/bin:/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin</string>
-        
-        <key>DATABASE_URL</key>
-        <string>postgres://accusys@localhost:5432/momentry</string>
-        
-        <key>DB_MAX_CONNECTIONS</key>
-        <string>50</string>
-        
-        <key>DB_ACQUIRE_TIMEOUT</key>
-        <string>30</string>
-        
-        <key>REDIS_URL</key>
-        <string>redis://:accusys@localhost:6379</string>
-        
-        <key>REDIS_PASSWORD</key>
-        <string>accusys</string>
-        
-        <key>OLLAMA_HOST</key>
-        <string>http://localhost:11434</string>
-        
-        <key>QDRANT_URL</key>
-        <string>http://127.0.0.1:6333</string>
-    </dict>
-    
-    <key>RunAtLoad</key>
-    <true/>
-    
-    <key>KeepAlive</key>
-    <true/>
-    
-    <key>StandardOutPath</key>
-    <string>/Users/accusys/momentry/log/momentry_api.log</string>
-    
-    <key>StandardErrorPath</key>
-    <string>/Users/accusys/momentry/log/momentry_api.error.log</string>
-</dict>
-</plist>

config/README.md

@@ -1,105 +1,178 @@
-# Momentry Core 配置管理
+# Momentry Core Config Management
 
-## 目錄結構
+## Directory Structure
 
 ```
 momentry_core_0.1/
-├── .env.example          # 配置模板（已納入版本控制）
-├── .env                  # 本地配置（已從版本控制排除）
-├── .env.local           # 本地覆蓋配置（已從版本控制排除）
+├── .env.example          # Template (version controlled)
+├── .env                  # Local config (gitignored)
+├── .env.development      # Playground dev overrides (gitignored)
+├── .env.local            # Local overrides (gitignored)
 ├── config/
-│   └── README.md        # 本文件
-└── src/core/config.rs   # 配置代碼
+│   ├── README.md         # This file
+│   └── port_registry.tsv # Central port registry
+└── src/core/config.rs    # Config code with lazy_static env reading
 ```
 
-## 配置加載順序
+## Load Order
 
-1. `.env` - 默認本地配置
-2. `.env.local` - 本地覆蓋（最高優先級）
+For `momentry_playground` (development):
+1. `.env` — shared defaults
+2. `.env.development` — dev-specific overrides (loaded by playground binary)
 
-## 環境變數列表
+For `momentry` (production):
+1. `.env` — production config
 
-### 數據庫配置
+In Rust: `config.rs` reads env vars with lazy_static, falling back to hardcoded defaults.
 
-| 變數 | 說明 | 默認值 |
-|------|------|--------|
-| `DATABASE_URL` | PostgreSQL 連接字串 | `postgres://accusys@localhost:5432/momentry` |
+## Environment Variables
 
-### Redis 配置
+### Server
 
-| 變數 | 說明 | 默認值 |
-|------|------|--------|
-| `REDIS_URL` | Redis 連接字串 | `redis://:accusys@localhost:6379` |
-| `REDIS_PASSWORD` | Redis 密碼 | `accusys` |
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `MOMENTRY_SERVER_PORT` | Server port (3002=prod, 3003=dev) | `3002` |
+| `MOMENTRY_REDIS_PREFIX` | Redis key prefix | `momentry:` (prod), `momentry_dev:` (dev) |
 
-### 存儲路徑
+### Database
 
-| 變數 | 說明 | 默認值 |
-|------|------|--------|
-| `MOMENTRY_OUTPUT_DIR` | 輸出目錄 | `/Users/accusys/momentry/output` |
-| `MOMENTRY_BACKUP_DIR` | 備份目錄 | `/Users/accusys/momentry/backup/momentry` |
-| `MOMENTRY_SCRIPTS_DIR` | 腳本目錄 | `/Users/accusys/momentry_core_0.1/scripts` |
-| `MOMENTRY_PYTHON_PATH` | Python 路徑 | `/opt/homebrew/bin/python3.11` |
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `DATABASE_URL` | PostgreSQL connection string | `postgres://accusys@localhost:5432/momentry` |
+| `DATABASE_SCHEMA` | Schema for dev isolation | `dev` |
+| `MONGODB_URL` | MongoDB connection string | `mongodb://localhost:27017` |
+| `MONGODB_DATABASE` | MongoDB database name | `momentry` (prod), `momentry_dev` (dev) |
+| `MONGODB_CACHE_ENABLED` | MongoDB cache toggle | `true` |
+| `MONGODB_CACHE_TTL_VIDEOS` | Cache TTL for videos | `300` |
+| `MONGODB_CACHE_TTL_SEARCH` | Cache TTL for search | `300` |
+| `MONGODB_CACHE_TTL_HYBRID_SEARCH` | Cache TTL for hybrid search | `600` |
+| `MONGODB_CACHE_TTL_VIDEO_META` | Cache TTL for video metadata | `3600` |
 
-### 處理器超時（秒）
+### Redis
 
-| 變數 | 說明 | 默認值 |
-|------|------|--------|
-| `MOMENTRY_ASR_TIMEOUT` | ASR 處理超時 | `3600` |
-| `MOMENTRY_CUT_TIMEOUT` | CUT 處理超時 | `3600` |
-| `MOMENTRY_DEFAULT_TIMEOUT` | 默認超時 | `7200` |
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `REDIS_URL` | Redis connection string | `redis://:accusys@localhost:6379` |
+| `REDIS_PASSWORD` | Redis password | `accusys` |
+| `REDIS_CACHE_TTL_HEALTH` | Health check cache TTL | `30` |
+| `REDIS_CACHE_TTL_VIDEO_META` | Video metadata cache TTL | `3600` |
 
-### 日誌
+### Qdrant
 
-| 變數 | 說明 | 默認值 |
-|------|------|--------|
-| `RUST_LOG` | 日誌級別 | `info` |
-| `MOMENTRY_LOG_LEVEL` | 日誌級別（備選） | `info` |
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `QDRANT_URL` | Qdrant server URL | `http://localhost:6333` |
+| `QDRANT_API_KEY` | Qdrant API key | `Test3200Test3200Test3200` |
+| `QDRANT_COLLECTION` | Collection name | `momentry_rule1` (prod), `momentry_dev_rule1_v2` (dev) |
 
-## 使用方式
+### LLM
 
-### 1. 首次設置
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `MOMENTRY_LLM_CHAT_URL` | Chat/function-calling endpoint | `http://127.0.0.1:8082/v1/chat/completions` |
+| `MOMENTRY_LLM_CHAT_MODEL` | Chat model name | `google_gemma-4-26B-A4B-it-Q5_K_M.gguf` |
+| `MOMENTRY_LLM_VISION_URL` | Vision LLM endpoint (E4B) | falls back to CHAT_URL |
+| `MOMENTRY_LLM_VISION_MODEL` | Vision model name (E4B) | falls back to CHAT_MODEL |
+| `MOMENTRY_LLM_SUMMARY_URL` | Summary LLM endpoint (5W1H) | falls back to CHAT_URL |
+| `MOMENTRY_LLM_SUMMARY_MODEL` | Summary model name | falls back to CHAT_MODEL |
+| `MOMENTRY_LLM_SUMMARY_ENABLED` | Toggle 5W1H summary generation | `true` |
+| `MOMENTRY_LLM_SUMMARY_TIMEOUT` | 5W1H timeout in seconds | `120` |
+| `MOMENTRY_LLM_CHAT_TIMEOUT` | Chat LLM timeout in seconds | `120` |
+| `MOMENTRY_LLM_VISION_TIMEOUT` | Vision LLM timeout in seconds | `120` |
+
+### Embedding
+
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `MOMENTRY_EMBED_URL` | Embedding server URL | `http://localhost:11436` |
+
+### TMDb Integration
+
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `TMDB_API_KEY` | TMDb API key (required for probe) | (none) |
+| `MOMENTRY_TMDB_PROBE_ENABLED` | Enable TMDb probe during register | `false` |
+
+### Paths
+
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `MOMENTRY_OUTPUT_DIR` | Output directory for processing | `/Users/accusys/momentry/output` |
+| `MOMENTRY_BACKUP_DIR` | Backup directory | `/Users/accusys/momentry/backup/momentry` |
+| `MOMENTRY_SCRIPTS_DIR` | Python scripts directory | `/Users/accusys/momentry_core_0.1/scripts` |
+| `MOMENTRY_PYTHON_PATH` | Python interpreter path | `/opt/homebrew/bin/python3.11` |
+| `MOMENTRY_MEDIA_BASE_URL` | Base URL for media serving | (none) |
+
+### Processor Timeouts
+
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `MOMENTRY_ASR_TIMEOUT` | ASR timeout in seconds | `3600` |
+| `MOMENTRY_CUT_TIMEOUT` | CUT timeout in seconds | `3600` |
+| `MOMENTRY_DEFAULT_TIMEOUT` | Default timeout in seconds | `7200` |
+
+### Logging
+
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `RUST_LOG` | Rust log level (tracing) | `info` |
+| `MOMENTRY_LOG_LEVEL` | Fallback log level | `info` |
+
+### Worker
+
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `MOMENTRY_WORKER_ENABLED` | Enable background worker | `true` |
+| `MOMENTRY_MAX_CONCURRENT` | Max concurrent jobs | `6` |
+| `MOMENTRY_POLL_INTERVAL` | Poll interval in seconds | `10` |
+| `MOMENTRY_WORKER_BATCH_SIZE` | Batch size | `5` |
+
+### Synonym Expansion
+
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `MOMENTRY_SYNONYM_FILES` | Comma-separated paths to synonym JSON files | (none) |
+| `MOMENTRY_SYNONYM_FILE` | Single synonym file (deprecated) | (none) |
+
+### Encryption
+
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `AUDIT_ENCRYPTION_KEY` | 32-byte hex encryption key (64 hex chars) | (none) |
+
+## Port Registry
+
+See `config/port_registry.tsv` for the authoritative list of all ports and their owners.
+
+| Port | Service | Owner | Config Key |
+|------|---------|-------|------------|
+| 5432 | PostgreSQL | postgres | `DATABASE_URL` |
+| 6379 | Redis | redis-server | `REDIS_URL` |
+| 6333 | Qdrant | qdrant | `QDRANT_URL` |
+| 8082 | LLM Chat (A4B) | llama-server | `MOMENTRY_LLM_CHAT_URL` |
+| 8083 | LLM Vision (E4B) | llama-server | `MOMENTRY_LLM_VISION_URL` |
+| 11434 | Ollama | ollama | `MOMENTRY_OLLAMA_URL` |
+| 11436 | Embedding | embeddinggemma_server.py | `MOMENTRY_EMBED_URL` |
+| 27017 | MongoDB | mongod | `MONGODB_URL` |
+| 3002 | Production API | momentry | `MOMENTRY_SERVER_PORT` |
+| 3003 | Playground API | momentry_playground | `MOMENTRY_SERVER_PORT` |
+
+## Quick Start
 
 ```bash
-# 複製模板
+# 1. Copy template
 cp .env.example .env
 
-# 編輯配置
-nano .env
+# 2. Edit .env for production or use .env.development for playground
+# 3. Start all services
+./scripts/start_momentry.sh
 ```
 
-### 2. 本地覆蓋
+## Version Control
 
-創建 `.env.local` 設置僅本地適用的配置：
-
-```bash
-# .env.local 示例
-DATABASE_URL=postgres://local:password@localhost:5432/momentry_dev
-MOMENTRY_LOG_LEVEL=debug
-```
-
-### 3. 運行應用
-
-```bash
-# 加載配置並運行
-source .env && cargo run
-
-# 或使用 direnv
-direnv allow
-```
-
-## 版本控制策略
-
-| 文件 | 版本控制 | 說明 |
-|------|---------|------|
-| `.env.example` | ✅ 追蹤 | 模板，包含所有選項 |
-| `.env` | ❌ 忽略 | 本地敏感配置 |
-| `.env.local` | ❌ 忽略 | 本地覆蓋配置 |
-
-## 部署檢查清單
-
-- [ ] 複製 `.env.example` 到 `.env`
-- [ ] 設置數據庫連接
-- [ ] 設置 Redis 密碼
-- [ ] 配置目錄路徑
-- [ ] 確認日誌級別
+| File | Tracked | Purpose |
+|------|---------|---------|
+| `.env.example` | ✅ Yes | Template with all options documented |
+| `.env` | ❌ No | Local sensitive config |
+| `.env.development` | ❌ No | Dev-specific overrides |
+| `.env.local` | ❌ No | Local overrides (highest priority) |

config/development.env

@@ -0,0 +1,47 @@
+# Development Environment Configuration
+# Used by: momentry_playground binary on port 3003
+# 
+# This file extracts development-specific variables from .env.development
+# Startup scripts must export these variables for Python subprocess inheritance
+
+# Server Configuration
+MOMENTRY_SERVER_PORT=3003
+MOMENTRY_REDIS_PREFIX=momentry_dev:
+
+# Database Schema
+DATABASE_SCHEMA=dev
+
+# Output Directory (CRITICAL for Python scripts)
+MOMENTRY_OUTPUT_DIR=/Users/accusys/momentry/output_dev
+
+# Backup Directory
+MOMENTRY_BACKUP_DIR=/Users/accusys/momentry/backup/momentry_dev
+
+# Storage
+MOMENTRY_SFTP_ROOT=/Users/accusys/momentry/var/sftpgo/data/demo/
+
+# Python Path (venv for development)
+MOMENTRY_PYTHON_PATH=/Users/accusys/momentry_core/venv/bin/python
+MOMENTRY_SCRIPTS_DIR=/Users/accusys/momentry_core/scripts
+
+# Logging
+RUST_LOG=info
+MOMENTRY_LOG_LEVEL=info
+
+# Worker Configuration
+MOMENTRY_WORKER_ENABLED=true
+MOMENTRY_MAX_CONCURRENT=6
+MOMENTRY_POLL_INTERVAL=10
+MOMENTRY_WORKER_BATCH_SIZE=5
+
+# TMDb Integration
+TMDB_API_KEY=e9cde52197f6f8df4d9db99da93db1fb
+MOMENTRY_TMDB_PROBE_ENABLED=true
+
+# LLM Configuration
+MOMENTRY_LLM_SUMMARY_URL=http://127.0.0.1:8000/v1/chat/completions
+MOMENTRY_LLM_SUMMARY_MODEL=gemma-4-E4B
+MOMENTRY_LLM_SUMMARY_ENABLED=true
+
+# Embedding
+MOMENTRY_EMBED_URL=http://localhost:11436

config/port_registry.tsv

@@ -0,0 +1,24 @@
+# Port Registry - Momentry Core
+# Each port must have exactly one owner.
+# Before adding a service: pick a free port, add a row here, then configure.
+#
+# Port	Service		Owner			Config Key			Default			Source
+22	ssh		sshd			-				-			macOS
+80	http		Caddy			-				-			Caddyfile
+443	https		Caddy			-				-			Caddyfile
+2019	caddy-admin	Caddy			-				-			Caddyfile (internal)
+3000	gitea		gitea			-				3000			start_momentry.sh
+3002	production	momentry		MOMENTRY_SERVER_PORT		3002			run-server-3002.sh
+3003	playground	momentry_playground	MOMENTRY_SERVER_PORT		3003			start_momentry.sh
+3200	dashboard	Caddy			-				-			Caddyfile
+3306	mariadb		mariadbd		-				3306			start_momentry.sh
+5432	postgresql	postgres		DATABASE_URL			postgres://...:5432	start_momentry.sh
+6379	redis		redis-server		REDIS_URL			redis://...:6379	start_momentry.sh
+6333	qdrant		qdrant			QDRANT_URL			http://...:6333		start_momentry.sh
+8081	wordpress	Caddy			-				-			Caddyfile
+8082	llm-chat	llama-server		MOMENTRY_LLM_CHAT_URL		http://...:8082		start_momentry.sh
+8083	llm-vision	llama-server		MOMENTRY_LLM_VISION_URL		http://...:8083		start_momentry.sh
+9000	php-fpm		php-fpm			-				9000			brew services
+11434	ollama		ollama			MOMENTRY_OLLAMA_URL		http://...:11434	start_momentry.sh
+11436	embedding	embeddinggemma		MOMENTRY_EMBED_URL		http://...:11436	start_momentry.sh
+27017	mongodb		mongod			MONGODB_URL			mongodb://...:27017	start_momentry.sh

config/production.env

@@ -0,0 +1,39 @@
+# Production Environment Configuration
+# Used by: momentry binary on port 3002
+# 
+# This file extracts production-specific variables from .env
+# Startup scripts must export these variables for Python subprocess inheritance
+
+# Server Configuration
+MOMENTRY_SERVER_PORT=3002
+MOMENTRY_REDIS_PREFIX=momentry:
+
+# Database Schema
+DATABASE_SCHEMA=public
+
+# Output Directory (CRITICAL for Python scripts)
+MOMENTRY_OUTPUT_DIR=/Users/accusys/momentry/output
+
+# Backup Directory
+MOMENTRY_BACKUP_DIR=/Users/accusys/momentry/backup/momentry
+
+# Storage
+MOMENTRY_STORAGE_ROOT=/Users/accusys/momentry/var/sftpgo/data
+
+# Python Path
+MOMENTRY_PYTHON_PATH=/opt/homebrew/bin/python3.11
+
+# Logging
+RUST_LOG=debug
+MOMENTRY_LOG_LEVEL=debug
+
+# Worker Configuration
+MOMENTRY_WORKER_ENABLED=true
+MOMENTRY_MAX_CONCURRENT=6
+MOMENTRY_POLL_INTERVAL=10
+MOMENTRY_WORKER_BATCH_SIZE=5
+MOMENTRY_FORCE_RETRY=true
+
+# TMDb Integration
+TMDB_API_KEY=e9cde52197f6f8df4d9db99da93db1fb
+MOMENTRY_TMDB_PROBE_ENABLED=true

create_job.rs

@@ -1,98 +0,0 @@
-use anyhow::Result;
-use sqlx::postgres::PgPoolOptions;
-
-#[tokio::main]
-async fn main() -> Result<()> {
-    // Database connection
-    let pool = PgPoolOptions::new()
-        .max_connections(5)
-        .connect("postgres://accusys@localhost:5432/momentry")
-        .await?;
-
-    let video_uuid = "9760d0820f0cf9a7";
-    let video_id = 28;
-    let video_path = "/Users/accusys/momentry/var/sftpgo/data/demo/ExaSAN PCIe series - Director Ou Yu-Zhi Shares His Experience.mp4";
-
-    println!("Creating monitor job for video:");
-    println!("  UUID: {}", video_uuid);
-    println!("  ID: {}", video_id);
-    println!("  Path: {}", video_path);
-
-    // 1. Create monitor job
-    let job_row = sqlx::query(
-        r#"
-        INSERT INTO monitor_jobs (uuid, video_path, status)
-        VALUES ($1, $2, 'pending')
-        RETURNING id, uuid, video_path, status
-        "#
-    )
-    .bind(video_uuid)
-    .bind(video_path)
-    .fetch_one(&pool)
-    .await?;
-
-    let job_id: i32 = job_row.get(0);
-    let job_uuid: String = job_row.get(1);
-    let job_status: String = job_row.get(3);
-
-    println!("\nCreated monitor job:");
-    println!("  Job ID: {}", job_id);
-    println!("  Job UUID: {}", job_uuid);
-    println!("  Status: {}", job_status);
-
-    // 2. Update video with job_id
-    sqlx::query(
-        r#"
-        UPDATE videos 
-        SET job_id = $1, updated_at = CURRENT_TIMESTAMP 
-        WHERE id = $2
-        "#
-    )
-    .bind(job_id)
-    .bind(video_id)
-    .execute(&pool)
-    .await?;
-
-    println!("Updated video {} with job_id {}", video_id, job_id);
-
-    // 3. Update monitor_jobs with video_id
-    sqlx::query(
-        r#"
-        UPDATE monitor_jobs 
-        SET video_id = $1, updated_at = CURRENT_TIMESTAMP 
-        WHERE id = $2
-        "#
-    )
-    .bind(video_id)
-    .bind(job_id)
-    .execute(&pool)
-    .await?;
-
-    println!("Updated monitor_jobs {} with video_id {}", job_id, video_id);
-
-    // 4. Create processor results for this job
-    let processors = vec!["asr", "cut", "yolo", "ocr", "face", "pose", "asrx"];
-    
-    for processor in processors {
-        sqlx::query(
-            r#"
-            INSERT INTO processor_results (job_id, video_id, processor, status)
-            VALUES ($1, $2, $3, 'pending')
-            ON CONFLICT (job_id, processor) DO NOTHING
-            "#
-        )
-        .bind(job_id)
-        .bind(video_id)
-        .bind(processor)
-        .execute(&pool)
-        .await?;
-
-        println!("Created processor result for {}: {}", processor, job_id);
-    }
-
-    println!("\n✅ Job creation completed successfully!");
-    println!("Job ID: {}", job_id);
-    println!("The worker should now pick up this job and start processing.");
-
-    Ok(())
-}

create_job.sql

@@ -1,7 +0,0 @@
--- 1. Create monitor job
-INSERT INTO monitor_jobs (uuid, video_path, status)
-VALUES ('9760d0820f0cf9a7', '/Users/accusys/momentry/var/sftpgo/data/demo/ExaSAN PCIe series - Director Ou Yu-Zhi Shares His Experience.mp4', 'pending')
-RETURNING id;
-
--- Note: The job_id will be returned. Let's assume it's 18 for now.
--- We'll run these commands step by step.

debug_asr.py

@@ -1,150 +0,0 @@
-#!/usr/bin/env python3
-"""
-Debug ASR processing stages for large video.
-"""
-
-import os
-import sys
-import time
-import subprocess
-import tempfile
-import json
-from pathlib import Path
-
-
-def run_ffmpeg_extract(video_path, audio_path):
-    """Extract audio using ffmpeg."""
-    cmd = [
-        "ffmpeg",
-        "-i",
-        str(video_path),
-        "-vn",
-        "-acodec",
-        "pcm_s16le",
-        "-ar",
-        "16000",
-        "-ac",
-        "1",
-        "-y",
-        str(audio_path),
-    ]
-    print(f"Running ffmpeg: {' '.join(cmd)}")
-    start = time.time()
-    proc = subprocess.run(cmd, capture_output=True, text=True)
-    elapsed = time.time() - start
-    print(f"ffmpeg completed in {elapsed:.1f}s, return code: {proc.returncode}")
-    if proc.returncode != 0:
-        print(f"stderr: {proc.stderr[:500]}")
-    return proc.returncode == 0, elapsed
-
-
-def test_asr_stages(video_path):
-    """Test ASR stages step by step."""
-    video_path = Path(video_path)
-    print(f"Testing video: {video_path}")
-    print(f"Size: {video_path.stat().st_size / 1024 / 1024:.1f} MB")
-
-    # Stage 1: Check audio streams
-    print("\n=== Stage 1: Check audio streams ===")
-    cmd = [
-        "ffprobe",
-        "-v",
-        "error",
-        "-select_streams",
-        "a",
-        "-show_entries",
-        "stream=codec_name,channels,sample_rate,duration",
-        "-of",
-        "csv=p=0",
-        str(video_path),
-    ]
-    proc = subprocess.run(cmd, capture_output=True, text=True)
-    print(f"Audio streams: {proc.stdout.strip()}")
-
-    # Stage 2: Extract audio
-    print("\n=== Stage 2: Extract audio ===")
-    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
-        audio_path = f.name
-    try:
-        success, extract_time = run_ffmpeg_extract(video_path, audio_path)
-        if success:
-            print(f"Audio extracted to {audio_path}")
-            print(f"Audio size: {Path(audio_path).stat().st_size / 1024 / 1024:.1f} MB")
-        else:
-            print("Audio extraction failed")
-            os.unlink(audio_path)
-            return
-    except Exception as e:
-        print(f"Error extracting audio: {e}")
-        return
-
-    # Stage 3: Load faster_whisper model (just import)
-    print("\n=== Stage 3: Test faster_whisper import ===")
-    try:
-        start = time.time()
-        from faster_whisper import WhisperModel
-
-        elapsed = time.time() - start
-        print(f"Import faster_whisper: {elapsed:.1f}s")
-    except Exception as e:
-        print(f"Import failed: {e}")
-        os.unlink(audio_path)
-        return
-
-    # Stage 4: Transcribe a small segment (first 30 seconds)
-    print("\n=== Stage 4: Transcribe first 30 seconds ===")
-    try:
-        # Trim audio to first 30 seconds
-        trim_path = audio_path + ".trim.wav"
-        cmd = [
-            "ffmpeg",
-            "-i",
-            audio_path,
-            "-t",
-            "30",
-            "-acodec",
-            "pcm_s16le",
-            "-ar",
-            "16000",
-            "-ac",
-            "1",
-            "-y",
-            trim_path,
-        ]
-        subprocess.run(cmd, capture_output=True)
-
-        # Load model with small model
-        start = time.time()
-        model = WhisperModel("tiny", device="cpu", compute_type="int8")
-        load_time = time.time() - start
-        print(f"Model loaded in {load_time:.1f}s")
-
-        # Transcribe
-        start = time.time()
-        segments, info = model.transcribe(trim_path, beam_size=5)
-        segments = list(segments)  # Force processing
-        transcribe_time = time.time() - start
-        print(f"Transcription of 30s audio: {transcribe_time:.1f}s")
-        print(
-            f"Detected language: {info.language} with probability {info.language_probability}"
-        )
-        print(f"Segments found: {len(segments)}")
-
-        # Cleanup
-        os.unlink(trim_path)
-    except Exception as e:
-        print(f"Transcription test failed: {e}")
-        import traceback
-
-        traceback.print_exc()
-    finally:
-        os.unlink(audio_path)
-
-    print("\n=== Debug complete ===")
-
-
-if __name__ == "__main__":
-    if len(sys.argv) != 2:
-        print(f"Usage: {sys.argv[0]} <video_file>")
-        sys.exit(1)
-    test_asr_stages(sys.argv[1])

debug_chunked_hang.py

@@ -1,85 +0,0 @@
-#!/usr/bin/env python3
-import sys
-import time
-
-print("Start")
-print("Importing faster_whisper...")
-try:
-    from faster_whisper import WhisperModel
-
-    print("Import successful")
-except Exception as e:
-    print(f"Import failed: {e}")
-    sys.exit(1)
-
-print("Loading model...")
-try:
-    model = WhisperModel("tiny", device="cpu", compute_type="int8")
-    print("Model loaded")
-except Exception as e:
-    print(f"Model load failed: {e}")
-    sys.exit(1)
-
-import subprocess
-
-print("Getting duration...")
-cmd = [
-    "ffprobe",
-    "-v",
-    "error",
-    "-show_entries",
-    "format=duration",
-    "-of",
-    "csv=p=0",
-    "/tmp/test_audio.wav",
-]
-result = subprocess.run(cmd, capture_output=True, text=True)
-print(f"ffprobe output: {result.stdout}")
-duration = float(result.stdout.strip())
-print(f"Duration: {duration}")
-
-# Extract first chunk
-print("Extracting first chunk...")
-chunk_path = "/tmp/debug_chunk.wav"
-cmd = [
-    "ffmpeg",
-    "-i",
-    "/tmp/test_audio.wav",
-    "-t",
-    "60",
-    "-acodec",
-    "pcm_s16le",
-    "-ar",
-    "16000",
-    "-ac",
-    "1",
-    "-y",
-    chunk_path,
-]
-result = subprocess.run(cmd, capture_output=True, text=True)
-print(f"ffmpeg return code: {result.returncode}")
-if result.returncode != 0:
-    print(f"stderr: {result.stderr[:200]}")
-
-import os
-
-print(f"Chunk exists: {os.path.exists(chunk_path)}")
-if os.path.exists(chunk_path):
-    print(f"Chunk size: {os.path.getsize(chunk_path)}")
-
-    print("Transcribing chunk...")
-    start = time.time()
-    try:
-        segments, info = model.transcribe(chunk_path, beam_size=5)
-        segments = list(segments)
-        elapsed = time.time() - start
-        print(f"Transcription succeeded in {elapsed}s, segments: {len(segments)}")
-    except Exception as e:
-        print(f"Transcription failed: {e}")
-        import traceback
-
-        traceback.print_exc()
-else:
-    print("Chunk not created")
-
-print("Script finished")

deliverable_v1.1.0/AGENTS.md

@@ -0,0 +1,761 @@
+# AGENTS.md - Momentry Core
+
+Rust-based digital asset management system with video analysis and RAG capabilities.
+
+---
+
+## ⚠️ CRITICAL: 開發隔離原則
+
+### 絕對禁止事項
+- **絕對不可修改 `/Users/accusys/wordpress/` 目錄下的任何檔案**
+- **絕對不可修改 n8n 工作流或設定**
+- **絕對不可修改 WordPress 或 n8n 的資料庫 table**
+- **除非是 release 作業，絕對不可動 port 3002 (production)**
+- **🔴 DELETE / REMOVE / DROP / CLEAR 任何資料前必須先問使用者「要刪嗎？」獲得明確同意後才能執行**
+- **🔴 Qdrant collection 刪除、DB truncate、檔案刪除、資料清空 — 一律要先問**
+- **🔴 不確定是否該刪 → 先問，不要自己決定**
+
+### 開發範圍界定
+| 範圍 | 狀態 | 說明 |
+|------|------|------|
+| `momentry_core_0.1/` | ✅ **可開發** | Momentry Core 主要開發目錄 |
+| `momentry_core_0.1/portal/` | ✅ **可開發** | Tauri Portal 前端 |
+| `momentry_core_0.1/src/` | ✅ **可開發** | Rust 後端程式碼 |
+| `/Users/accusys/wordpress/` | ❌ **禁止修改** | WordPress/Marcom 團隊負責 |
+| n8n 工作流 | ❌ **禁止修改** | 自動化流程，與 dev 無關 |
+| WordPress/n8n 資料庫 table | ❌ **禁止修改** | Marcom 團隊管理，與 dev 無關 |
+
+### 開發環境
+| 服務 | Port | 用途 | 命令 |
+|------|------|------|------|
+| Playground | 3003 | **唯一開發環境** | `cargo run --bin momentry_playground -- server` |
+| Production | 3002 | ❌ 禁止修改 | `cargo run -- server` (僅 release 時) |
+| Portal (Tauri) | 1420 | 前端開發 | `npm run tauri dev` |
+
+## ⚠️ 交叉污染防制 (Cross-Contamination Prevention)
+
+**每個執行前必須評估是否會汙染其他獨立作業。**
+
+### Scope Isolation Matrix
+
+| 執行內容 | 允許的 Scope | 禁止影響 | 檢查事項 |
+|----------|-------------|----------|----------|
+| M4 delivery binary | `target/release/momentry` | Playground (3003), Production (3002) | 確認舊 process 未被誤殺 |
+| Playground server | `localhost:3003`, `dev.*` schema | Production (3002), `public.*` schema | `DATABASE_SCHEMA=dev` |
+| Production deploy | `localhost:3002`, `public.*` schema | Playground (3003), `dev.*` schema | 先停 production，不影響 playground |
+| Git commit | 只包含意圖修改的檔案 | 無關的 untracked files | `git status` 確認 stage 內容正確 |
+| CI / packaged tests | 測試環境 | 正式資料 | 測試用 DB 不能連到 production |
+| Doc changes | 指定文件 | 其他文件、程式碼 | `git diff --stat` 檢查 scope |
+| SQL migration | 目標 schema | 其他 schema、無關 table | `WHERE` clause 要精準 |
+| `sed` / `grep` / mass edit | 目標檔案集 | 非目標檔案 | 先用 `grep -c` 確認只有目標檔案匹配 |
+
+### Recent Violations / Near-Misses
+
+| 事件 | 問題 | 防止方式 |
+|------|------|----------|
+| `sed` API doc 編號 | `sed -i '' 's/.../.../g'` 改到所有行 | 先 `grep -c` 確認匹配，`git diff` 再提交 |
+| 亂加 `/api/v1/register` route | 不必要的 API 別名，汙染路由表 | 角色切換：路由設計不該由實作方決定 |
+| `API_WORKSPACE/` vs `GUIDES/` vs `REFERENCE/` vs `DESIGN/` vs `OPERATIONS/` vs `INTEGRATIONS/` | 文件放到錯誤分類 | API 文件改在 API_WORKSPACE/modules/ 編輯，`make deploy` 生成到 GUIDES/ |
+| Build release binary in plan mode | 浪費時間，無意義 | 嚴格遵守 plan/build mode 規定 |
+
+### ⛔ 嚴格測試隔離規則 (Strict Test Isolation)
+- **所有測試 (Test) 必須在 Dev (3003) 進行**。
+- **絕對禁止 (ABSOLUTELY FORBIDDEN)** 在任何測試指令、Demo 流程或 API 檢查中使用 `localhost:3002`。
+- 即使是「測試 Unregister」或「檢查版本」，若未明確標示為 "Production Deployment"，一律視為違規。
+- **預設行為**: 所有 curl, CLI, 或程式碼測試指令，預設 URL 必須為 `http://localhost:3003`。
+
+### 違反後果
+- 修改 WordPress/n8n 可能影響 marcom 團隊工作與生產環境
+- 修改 WordPress/n8n 資料庫 table 可能破壞自動化流程與資料完整性
+- 修改 port 3002 可能中斷正在使用的服務 (這是非常嚴重的錯誤)
+- 所有 dev 測試必須在 playground (3003) 進行
+
+---
+
+## AI Coding Principles (Karpathy-Inspired)
+
+Behavioral guidelines to reduce common LLM coding mistakes.
+Source: [andrej-karpathy-skills](https://github.com/forrestchang/andrej-karpathy-skills) (94K stars)
+
+**Tradeoff:** These guidelines bias toward caution over speed. For trivial tasks, use judgment.
+
+### 1. Think Before Coding
+
+**Don't assume. Don't hide confusion. Surface tradeoffs.**
+
+- State your assumptions explicitly. If uncertain, ask.
+- If multiple interpretations exist, present them - don't pick silently.
+- If a simpler approach exists, say so. Push back when warranted.
+- If something is unclear, stop. Name what's confusing. Ask.
+
+### 2. Simplicity First
+
+**Minimum code that solves the problem. Nothing speculative.**
+
+- No features beyond what was asked.
+- No abstractions for single-use code.
+- No "flexibility" or "configurability" that wasn't requested.
+- No error handling for impossible scenarios.
+- If you write 200 lines and it could be 50, rewrite it.
+
+Ask yourself: "Would a senior engineer say this is overcomplicated?" If yes, simplify.
+
+### 3. Surgical Changes
+
+**Touch only what you must. Clean up only your own mess.**
+
+When editing existing code:
+- Don't "improve" adjacent code, comments, or formatting.
+- Don't refactor things that aren't broken.
+- Match existing style, even if you'd do it differently.
+- If you notice unrelated dead code, mention it - don't delete it.
+
+When your changes create orphans:
+- Remove imports/variables/functions that YOUR changes made unused.
+- Don't remove pre-existing dead code unless asked.
+
+The test: Every changed line should trace directly to the user's request.
+
+### 4. Goal-Driven Execution
+
+**Define success criteria. Loop until verified.**
+
+Transform tasks into verifiable goals:
+- "Add validation" -> "Write tests for invalid inputs, then make them pass"
+- "Fix the bug" -> "Write a test that reproduces it, then make it pass"
+- "Refactor X" -> "Ensure tests pass before and after"
+
+For multi-step tasks, state a brief plan:
+```
+1. [Step] -> verify: [check]
+2. [Step] -> verify: [check]
+3. [Step] -> verify: [check]
+```
+
+Strong success criteria let you loop independently. Weak criteria ("make it work") require constant clarification.
+
+---
+
+These guidelines are working if: fewer unnecessary changes in diffs, fewer rewrites due to overcomplication, and clarifying questions come before implementation rather than after mistakes.
+
+---
+
+## Terminology (V4.0)
+
+| Term | Scope | Description | Example |
+|------|-------|-------------|---------|
+| **file_uuid** | Video file | Video file identifier (renamed from `video_uuid`) | `384b0ff44aaaa1f1` |
+| **identity_uuid** | Global identity | Global person identity (cross-file) | `a9a90105-6d6b-46ff-92da-0c3c1a57dff4` |
+| **face_id** | Single detection | Single face detection (frame-level) | `face_100` |
+| **trace_id** | Face tracking | Face tracking ID (Face Tracker output) | `2` |
+| **chunk_id** | Sentence chunk | Sentence chunk (from pre_chunks via rules) | `chunk_1` |
+| **speaker_id** | Speaker segment | Speaker ID (from ASRX) | `SPEAKER_0` |
+| **person_id** | ❌ **Deprecated** | Video-local person ID (removed in V4.0) | - |
+
+### Architecture (V4.0)
+
+```
+Face → Identity (Two-layer, direct binding)
+  ↓
+  person_identities table: REMOVED
+  file_identities table: ADDED (N:N relationship)
+```
+
+### Key Changes (V3.x → V4.0)
+
+| Change | V3.x | V4.0 |
+|--------|------|------|
+| **video_uuid** | Used everywhere | **file_uuid** |
+| **person_identities** | Required (303 records) | **Removed** |
+| **person_id APIs** | 28 endpoints | **Removed** (except register/bind) |
+| **Face binding** | Person → Identity | **Face → Identity** (direct) |
+| **Chunk binding** | Manual | **Auto** (time alignment) |
+
+---
+
+## Build & Run Commands
+
+```bash
+# Build project (use debug builds for development/testing)
+cargo build
+cargo build --bin momentry
+cargo build --bin momentry_playground
+
+# Build all binaries
+cargo build --bins
+
+# Run CLI
+cargo run -- --help
+cargo run -- register /path/to/video.mp4
+cargo run -- server --host 0.0.0.0 --port 3002
+
+# Run playground (development binary)
+cargo run --bin momentry_playground -- server
+cargo run --bin momentry_playground -- --help
+```
+
+### ⚠️ CRITICAL: `cargo build --release` PROHIBITION
+- **NEVER run `cargo build --release` unless the user explicitly says "release the binary" or "正式 release"**
+- `cargo build --release` is SLOW and only needed when producing a production binary for deployment
+- For all development, testing, debugging, and linting: use `cargo build` or `cargo check`
+- If uncertain, ALWAYS ask the user first
+
+## Binaries
+
+| Binary | Purpose | Port | Redis Prefix | Environment |
+|--------|---------|------|--------------|-------------|
+| `momentry` | Production | 3002 | `momentry:` | `.env` |
+| `momentry_playground` | Development | 3003 | `momentry_dev:` | `.env.development` |
+| `momentry_player` | Video player | - | - | - |
+
+## Testing
+
+```bash
+# Run all tests
+cargo test
+
+# Run single test by name
+cargo test test_name
+
+# Run with output
+cargo test -- --nocapture
+
+# Doc tests
+cargo test --doc
+```
+
+## Linting & Formatting
+
+```bash
+# Format code (edition=2021, max_width=100, tab_spaces=4)
+cargo fmt
+cargo fmt -- --check
+
+# Lint
+cargo clippy
+cargo clippy --all-features
+
+# Check for errors
+cargo check
+cargo check --all-features
+```
+
+## Code Style
+
+### General
+- Use Rust 2021 edition
+- Use tracing for logging (not println!)
+- Keep lines under 100 characters
+
+### Imports (order: std → external → local)
+```rust
+use std::path::Path;
+use anyhow::{Context, Result};
+use async_trait::async_trait;
+use serde::{Deserialize, Serialize};
+
+use crate::core::chunk::Chunk;
+```
+
+### Error Handling
+- Use `anyhow::Result<T>` for application code
+- Use `thiserror` for library code
+- Use `.context()` for error context
+- Use `anyhow::bail!()` for early returns
+
+```rust
+fn example() -> Result<SomeType> {
+    let output = Command::new("ffprobe")
+        .args([...])
+        .output()
+        .context("Failed to run ffprobe")?;
+
+    if !output.status.success() {
+        anyhow::bail!("Command failed");
+    }
+    Ok(result)
+}
+```
+
+### Naming
+- Types/Enums: PascalCase (`VideoRecord`, `ChunkType`)
+- Functions/Variables: snake_case (`get_video_by_uuid`)
+- Traits: PascalCase with -er suffix (`Database`, `ChunkStore`)
+- Files: snake_case (`postgres_db.rs`)
+
+### Types
+- Use `serde::{Deserialize, Serialize}` for serializable types
+- Use `#[serde(rename_all = "snake_case")]` for enum variants
+- Use explicit numeric types (i64, u32, f64)
+
+```rust
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct VideoRecord {
+    pub id: i64,
+    pub uuid: String,
+    pub duration: f64,
+    pub width: u32,
+}
+
+#[derive(Debug, Clone, Copy, Serialize, Deserialize, PartialEq)]
+#[serde(rename_all = "snake_case")]
+pub enum ChunkType {
+    TimeBased,
+    Sentence,
+    Cut,
+}
+```
+
+### Async Programming
+- Use `tokio` runtime with full features
+- Use `#[async_trait]` for async trait methods
+
+```rust
+#[async_trait]
+pub trait Database: Send + Sync {
+    async fn init() -> Result<Self>
+    where Self: Sized;
+}
+```
+
+## Code Structure
+
+```
+src/
+├── main.rs           # CLI entry point
+├── lib.rs            # Library exports
+├── core/
+│   ├── api_key/     # API key management (anomaly, blacklist, encryption, etc.)
+│   ├── chunk/        # Chunking logic
+│   ├── config.rs     # Centralized configuration (env vars)
+│   ├── db/          # Database (PostgreSQL, MongoDB, Redis, Qdrant)
+│   ├── embedding/   # Vector embeddings
+│   ├── overlay/     # Video overlay
+│   ├── probe/       # ffprobe integration
+│   ├── processor/   # ASR, OCR, YOLO, Face, Pose, CUT, ASRX
+│   │   └── executor.rs  # Unified Python script executor
+│   ├── storage/     # File management
+│   └── thumbnail/   # Thumbnail extraction
+├── api/              # HTTP API (axum)
+├── player/           # Video player
+├── ui/               # TUI components
+└── watcher/          # File system watcher
+```
+
+## Key Dependencies
+
+- **Error handling**: `anyhow`, `thiserror`
+- **Async**: `tokio` (full features), `async-trait`
+- **CLI**: `clap` (derive)
+- **Serialization**: `serde`, `serde_json`, `chrono`
+- **Database**: `sqlx`, `mongodb`, `redis` (1.0), `qdrant-client`
+- **HTTP**: `axum`, `tower`
+- **Logging**: `tracing`, `tracing-subscriber`
+- **Config**: `once_cell` (lazy static config)
+
+## Environment Variables
+
+### Server
+- `MOMENTRY_SERVER_PORT` - API server port (default: `3002` for production, `3003` for playground)
+- `MOMENTRY_REDIS_PREFIX` - Redis key prefix (default: `momentry:` for production, `momentry_dev:` for playground)
+- `MOMENTRY_API_KEY` - API key for Player online mode testing
+
+### Testing API Key
+```bash
+export MOMENTRY_API_KEY="muser_68600856036340bcafc01930eb4bd839_1774418104_97221b69"
+
+# Test Player online mode
+cargo run --features player --bin momentry_player -- -o
+```
+
+### Database
+- `DATABASE_URL` - PostgreSQL (default: `postgres://accusys@localhost:5432/momentry`)
+
+### Redis
+- `REDIS_URL` - Redis URL (default: `redis://:accusys@localhost:6379`)
+- `REDIS_PASSWORD` - Redis password (default: `accusys`)
+
+### Paths
+- `MOMENTRY_OUTPUT_DIR` - Output directory (default: `/Users/accusys/momentry/output`)
+- `MOMENTRY_BACKUP_DIR` - Backup directory
+- `MOMENTRY_PYTHON_PATH` - Python path (default: `/opt/homebrew/bin/python3.11`)
+- `MOMENTRY_SCRIPTS_DIR` - Scripts directory
+
+### Processor Timeouts
+- `MOMENTRY_ASR_TIMEOUT` - ASR timeout in seconds (default: 3600)
+- `MOMENTRY_CUT_TIMEOUT` - CUT timeout in seconds (default: 3600)
+- `MOMENTRY_DEFAULT_TIMEOUT` - Default timeout (default: 7200)
+
+### TMDb Integration (Face Clustering)
+- `TMDB_API_KEY` - TMDb API key for movie metadata lookup (required for `MOMENTRY_TMDB_PROBE_ENABLED=true`)
+- `MOMENTRY_TMDB_PROBE_ENABLED` - Enable TMDb probe during registration (default: `false`)
+  - Register phase: searches TMDb by filename, creates identities with tmdb_id/tmdb_profile
+  - Post-process phase: matches detected faces against TMDb identities via cosine similarity
+
+### Synonym Expansion
+- `MOMENTRY_SYNONYM_FILES` - Comma-separated paths to synonym JSON files (e.g., `data/english_synonyms.json,data/llm_synonyms.json`)
+- `MOMENTRY_SYNONYM_FILE` - Single synonym JSON file path (deprecated, use above)
+
+### Logging
+- `RUST_LOG` or `MOMENTRY_LOG_LEVEL` - Log level (default: `info`)
+
+## Notes
+
+- Unit tests exist (86 library tests)
+- Video processing uses external tools (ffprobe, Python scripts)
+- Multi-database architecture (PostgreSQL, MongoDB, Redis, Qdrant)
+- Monitor directory is a separate system (not Rust)
+- PythonExecutor provides unified script execution with timeout support
+- Redis 1.0.x for improved performance
+- FaceNet CoreML model (`models/facenet512.mlpackage`) replaces InsightFace for embedding extraction (MIT license, ANE-accelerated)
+
+### LLM Synonym Generation
+
+Generate synonym database using llama.cpp (Gemma4):
+
+```bash
+# Generate full database (162 entries, ~5 minutes)
+python3 scripts/generate_synonyms_llamacpp.py
+
+# Quick test
+python3 scripts/generate_synonyms_llamacpp.py --test
+
+# Resume from existing file
+python3 scripts/generate_synonyms_llamacpp.py --resume
+
+# Output: data/llm_synonyms.json (27 Chinese + 135 English words)
+```
+
+## Task Management
+
+### 使用 todowrite 追蹤任務
+```bash
+# 創建任務清單
+/todo 建立配置模組 [in_progress]
+/todo 添加單元測試 [pending]
+
+# 更新狀態
+/todo 完成標記 [completed]
+```
+
+### 任務批次建議
+- 一次處理 1-2 個功能
+- 每個功能完成後驗證 (clippy + test)
+- 驗證通過後再繼續下一個
+
+## Code Review Checklist
+
+完成任務後檢查：
+- [ ] `cargo clippy --lib` 通過
+- [ ] `cargo test --lib` 通過
+- [ ] `cargo fmt -- --check` 通過
+- [ ] 文檔已更新 (如需要)
+- [ ] 新功能有單元測試
+
+## Commit Guidelines
+
+```bash
+# feat: 新功能
+git commit -m "feat: add monitor_jobs table"
+
+# fix: 錯誤修復
+git commit -m "fix: resolve SQL injection in store_vector"
+
+# refactor: 重構
+git commit -m "refactor: use parameterized queries"
+
+# docs: 文檔更新
+git commit -m "docs: update AGENTS.md with new modules"
+```
+
+## Pre-commit Hook
+
+專案已配置 `.git/hooks/pre-commit`，提交前自動檢查：
+
+```bash
+# 檢查內容
+1. cargo fmt --check    # Rust 格式化檢查
+2. cargo clippy --lib   # Rust Lint 檢查
+3. cargo test --lib     # Rust 單元測試
+4. ruff check           # Python Lint 檢查
+5. ruff format --check  # Python 格式化檢查
+6. markdownlint         # Markdown 格式檢查
+7. shellcheck           # Shell 腳本檢查
+
+# 跳過檢查（不建議）
+git commit --no-verify
+
+# 跳過特定檢查
+git commit --skip-checks
+```
+
+**注意**: Hook 僅檢查已暫存的 Rust/Python/Markdown 文件。
+
+### Python 環境設置
+```bash
+# 安裝 ruff
+pip install ruff==0.11.2
+
+# 格式化 Python 文件
+ruff format scripts/
+
+# Lint Python 文件
+ruff check scripts/
+```
+
+### Markdown 環境設置
+```bash
+# 安裝 markdownlint-cli (使用系統 Node.js)
+npm install -g markdownlint-cli
+
+# 檢查 Markdown 文件
+markdownlint docs/
+
+# 配置檔案
+.markdownlint.json
+```
+
+### Shell 環境設置
+```bash
+# 安裝 shellcheck
+brew install shellcheck
+
+# 檢查 Shell 腳本
+shellcheck scripts/*.sh monitor/**/*.sh
+```
+
+**注意**: Hook 只檢查 error 等級的 shellcheck 問題，style 警告會顯示但不阻擋提交。
+
+## Release Workflow
+
+### Release 前準備
+每次 release production binary 前，必須：
+
+1. **建立 Release Tag**
+   ```bash
+   git tag -a v0.X.X -m "Release vX.X.X - YYYY-MM-DD"
+   git push origin v0.X.X
+   ```
+
+2. **備份獨立 Source Code**
+   ```bash
+   # 建立 release 獨立目錄
+   RELEASE_DIR="/Users/accusys/momentry_core_releases/v0.X.X"
+   mkdir -p "$RELEASE_DIR"
+   
+   # 複製完整原始碼（排除不必要的檔案）
+   rsync -av --exclude='.git' --exclude='target' --exclude='node_modules' \
+         /Users/accusys/momentry_core_0.1/ "$RELEASE_DIR/"
+   
+   # 記錄 release 資訊
+   echo "Release: v0.X.X" > "$RELEASE_DIR/RELEASE_INFO.txt"
+   echo "Date: $(date)" >> "$RELEASE_DIR/RELEASE_INFO.txt"
+   echo "Git Commit: $(git rev-parse HEAD)" >> "$RELEASE_DIR/RELEASE_INFO.txt"
+   echo "Binary: $(ls -la target/release/momentry)" >> "$RELEASE_DIR/RELEASE_INFO.txt"
+   ```
+
+3. **備份 Binary**
+   ```bash
+   cp target/release/momentry "$RELEASE_DIR/momentry_v0.X.X"
+   cp target/release/momentry_playground "$RELEASE_DIR/momentry_playground_v0.X.X" 2>/dev/null
+   ```
+
+4. **記錄資料庫 Schema**
+   ```bash
+   pg_dump -U accusys -d momentry --schema-only > "$RELEASE_DIR/schema_v0.X.X.sql"
+   ```
+
+### 重要性
+- 避免 release binary 與 current source code 不一致
+- 方便追蹤特定 release 的程式碼狀態
+- 必要時可快速復原或比對差異
+- 確保資料庫 schema 與程式碼版本對應
+
+## Reference Documents
+
+| 文件 | 用途 |
+|------|------|
+| `docs/OPENCODE_GUIDE.md` | OpenCode 使用規範 |
+| `docs/ARCHITECTURE_EVALUATION.md` | 架構優化待評估項目 (含 GraphRAG) |
+| `docs/PENDING_ISSUES.md` | 待解決問題追蹤 |
+| `docs/MOMENTRY_CORE_MONITORING.md` | 監控系統規範 |
+| `docs/MOMENTRY_CORE_REDIS_KEYS.md` | Redis Key 設計規範 |
+| `docs/PYTHON.md` | Python 腳本規範 |
+| `docs/FILE_CHANGE_MANAGEMENT.md` | 文件修改管理規範 |
+| `docs/YOLO_RESUME_INTEGRATION.md` | YOLO Resume 功能整合記錄 |
+| `docs/DOCUMENT_EMBEDDING_STRATEGY.md` | Parent-Child 嵌入策略 |
+| `docs/PROCESSING_PIPELINE.md` | 處理流程文檔 |
+| `docs/N8N_DEMO_WORKFLOW.md` | n8n 工作流文檔 |
+| `docs/FRESH_MAC_INSTALLATION.md` | 全新 Mac 安裝指南 |
+| `docs/SERVICES.md` | 服務總覽與管理 |
+| `docs/SFTPGO_DEMO_USER.md` | SFTPGo 用戶指南 |
+
+## Document Change Workflow
+
+修改文件前請參考 `docs/FILE_CHANGE_MANAGEMENT.md`，確保：
+
+1. **修改前**：完整閱讀文件、執行預檢清單
+2. **修改中**：提供變更計畫、取得確認
+3. **修改後**：展示 diff、更新版本歷史
+4. **驗證**：執行 lint/test、提交前審查
+
+### AI 工具修改規範
+
+AI 工具修改文件時：
+- 必須先完整閱讀文件（不可只讀取部分章節）
+- 修改前先提出變更計畫供確認
+- 修改後展示 diff 內容
+- 更新版本歷史表
+
+## PHP Development
+
+WordPress 作為 Momentry Portal，負責 n8n 自動化與 sftpgo 檔案服務的頁面整合。
+
+### 編輯器設定
+
+| 編輯器 | LSP 方案 | 安裝方式 |
+|--------|----------|----------|
+| VS Code | Intelephense | Extension Marketplace (推薦) |
+| Cursor | Intelephense | Extension Marketplace (推薦) |
+| CLI | phpactor | `~/bin/phpactor` |
+
+### Intelephense (VS Code/Cursor)
+
+1. 安裝 Extension: 搜尋 "Intelephense"
+2. 設定:
+```json
+{
+  "intelephense.stubs": ["wordpress"]
+}
+```
+
+### phpactor (CLI)
+
+```bash
+# 安裝方式
+brew install composer
+curl -sSL https://github.com/phpactor/phpactor/releases/latest/download/phpactor.phar -o ~/bin/phpactor
+chmod +x ~/bin/phpactor
+
+# 安裝 WordPress Stubs
+cd /Users/accusys/wordpress/web
+composer require --dev php-stubs/wordpress-stubs
+
+# 建立 WordPress 索引
+cd /Users/accusys/wordpress/web
+~/bin/phpactor index:build --reset
+
+# 常用指令
+~/bin/phpactor class:search "WP_User"      # 搜尋類別
+~/bin/phpactor index:query WP_User          # 查看類別資訊
+~/bin/phpactor navigate /path/to/file.php  # 導航到定義
+```
+
+### WordPress 程式碼位置
+| 類型 | 路徑 |
+|------|------|
+| 主題 | `/Users/accusys/wordpress/web/wp-content/themes/` |
+| 插件 | `/Users/accusys/wordpress/web/wp-content/plugins/` |
+
+### 與 marcom 團隊協作
+| 角色 | 負責 |
+|------|------|
+| marcom 團隊 | Figma 設計 / Elementor 建構 |
+| OpenCode | 程式碼實作 / 重構 |
+
+### 開發時程
+```
+Phase 1: marcom 建構 (現在)    → Elementor 頁面建構
+Phase 2: 交付審視 (TBD)      → 功能確認 / 重構評估
+Phase 3: OpenCode 重構        → 純程式碼實作，交付無 Elementor 依賴版本
+```
+
+## M4 通知規範
+
+### 固定通知方式
+
+通知 M4 的唯一管道：**`M4_workspace/` 下建立回覆文件 + `git commit`**。不需口頭、即時訊息、郵件。
+
+### 命名規則
+
+```
+docs_v1.0/M4_workspace/YYYY-MM-DD_<topic>_response.md   (回覆 M4 問題)
+docs_v1.0/M4_workspace/YYYY-MM-DD_<topic>.md             (主動通報)
+docs_v1.0/M4_workspace/YYYY-MM-DD_<topic>_test_report.md (測試報告)
+```
+
+### 觸發時機
+
+| 情境 | 動作 |
+|------|------|
+| M4 提交問題報告到 `M4_workspace/` | 修復後，回覆 `*_response.md` |
+| 完成 M4 要求的任務 | 回覆 `*_response.md` |
+| 重大變更（模型替換、架構變更） | 主動通知 `*.md` |
+| 新測試包產出 | `*_test_report.md` |
+
+### 交付檢查
+
+1. 文件寫入 `docs_v1.0/M4_workspace/`
+2. `git add` 包含該文件
+3. `git commit` 含相關變更
+4. M4 透過 git log 查看
+
+詳細規範見 `docs_v1.0/M4_workspace/M4_NOTIFICATION_PROTOCOL.md`。
+
+## UUID Naming Rule
+
+**Never use bare `uuid` in API route paths, query params, JSON keys, or code variable names. Always qualify:**
+
+| Context | Must use | Never |
+|---------|----------|-------|
+| Video/file resource | `file_uuid` | `uuid` |
+| Identity resource | `identity_uuid` | `uuid` |
+| Query parameter | `file_uuid=`, `identity_uuid=` | `uuid=` |
+| Route path | `:file_uuid`, `:identity_uuid` | `:uuid` |
+| JSON key | `"file_uuid"`, `"identity_uuid"` | `"uuid"` |
+
+This applies to docs, code, API responses, and curl examples. Exceptions: internal database primary key names (e.g. `identities.uuid` column).
+
+## Document Compliance Checklist
+
+Before creating any file in `docs_v1.0/` (API_WORKSPACE, GUIDES, REFERENCE, DESIGN, OPERATIONS, INTEGRATIONS), verify all items below.
+**IMPORTANT**: API functional documents are generated from `API_WORKSPACE/modules/`. Edit modules there, then run `make deploy` in `API_WORKSPACE/` to update `GUIDES/`. Never edit generated files in `GUIDES/` directly. See `DESIGN/Modular_Doc_System_V1.0.md` for the full system design.
+
+### P0 — Mandatory (7 items)
+
+| # | Check | Rule |
+|---|-------|------|
+| 1 | YAML frontmatter | `title`, `version`, `date`, `author`, `status` present |
+| 2 | Version history | Table at bottom of file tracking changes |
+| 3 | Top info table | scope, status, applicable to, etc. |
+| 4 | PascalCase filename | e.g. `DetectorRegistry.md`, not `detector_registry.md` |
+| 5 | `_` separator | Within filenames use `_`, never spaces or other chars |
+| 6 | English content | Entire file in English |
+| 7 | Correct directory | File must reside in appropriate directory: `API_WORKSPACE/modules/` (API endpoint modules), `GUIDES/` (user docs, generated), `REFERENCE/` (data models), `DESIGN/` (architecture), `OPERATIONS/` (infra/release), `INTEGRATIONS/` (n8n/tests) |
+
+### P0b — UUID Naming
+
+| # | Check | Rule |
+|---|-------|------|
+| 8 | `file_uuid` not bare `uuid` | All file references use `file_uuid` (see UUID Naming Rule above) |
+| 9 | `identity_uuid` not bare `uuid` | All identity references use `identity_uuid` |
+
+### P1 — Suggested (3 items)
+
+| # | Check | Note |
+|---|-------|------|
+| 1 | Cross-references | Link to related docs in API_WORKSPACE/, GUIDES/, REFERENCE/, DESIGN/, OPERATIONS/ |
+| 2 | Glossary terms | Define non-obvious terms inline or link glossary |
+| 3 | Diagrams | Include Mermaid/ASCII diagram for complex topics |
+
+### Exception
+
+`M4_workspace/` files are exempt from this checklist (free-format reply documents).
+
+---
+
+## Delivery Procedure
+
+完整交付程序（M4_workspace → M5 → Release → Deploy → Public）見：
+
+`docs_v1.0/OPERATIONS/DELIVERY_PROCEDURE.md`

deliverable_v1.1.0/SYSTEM_AUDIT_2026-05-17.md

@@ -0,0 +1,71 @@
+# System Audit — 2026-05-17
+
+## Current State
+
+### Embedding Storage (三重冗余，無主)
+
+| 資料類型 | PG pgvector | Qdrant | JSON 檔案 |
+|---------|------------|--------|-----------|
+| Sentence 向量 | `chunk.embedding` ✅ | `dev_v1` / `rule1_v2` / `sentence_*` ✅ | ❌ 無 |
+| Story 向量 | `chunk.embedding` ✅ | `dev_v1` / `dev_stories` ✅ | `.story_llm.json` ✅ |
+| Face 向量 | ❌ 已清除（依使用者指示） | `dev_faces` ✅ (97K) | `.face.json` ✅ |
+| Voice 向量 | ❌ 無 | `dev_voice` ✅ (4K) | ❌ 無 |
+
+### Pipeline 問題
+
+| 問題 | 影響 |
+|------|------|
+| `processor_results.duration_secs` 全為 0 | 無法查各步驟耗時 |
+| `processor_results.started_at/completed_at` 全 NULL | 時間線遺失 |
+| Redis timing 在 job 完成後被清掉 | 唯一 timing 來源消失 |
+| `get_chunk_by_chunk_id_and_uuid` 原本是 stub（已修） | Smart search 找不到 PG chunk |
+| `server.rs::search()` 未 mount 但仍編譯 | Dead code，混淆 Qdrant 用途 |
+| Face embedding 只寫 Qdrant 不寫 PG | 已刪除則全失 |
+
+### Qdrant Collections 現況
+
+| Collection | Points | 來源 | UUID |
+|-----------|--------|------|------|
+| `dev_v1` | 9,936 | PG rebuild | ✅ bd80fec... |
+| `dev_faces` | 97,000 | face.json rebuild | ✅ bd80fec... |
+| `dev_stories` | 560 | Snapshot | ✅ bd80fec... |
+| `dev_voice` | 4,188 | Snapshot | ✅ bd80fec... |
+| `dev_rule1_v2` | 3,417 | Snapshot | ✅ bd80fec... |
+| `sentence_story` | 4,188 | Snapshot | ✅ bd80fec... |
+| `sentence_summary` | 4,188 | Snapshot | ✅ bd80fec... |
+
+## Safeguards & Fixes
+
+### P0 — 必須修
+
+| # | Fix | 做法 |
+|---|-----|------|
+| 1 | **Pipeline timing 寫入 DB** | `update_processor_result()` 加入 `started_at`、`completed_at`、`duration_secs` |
+| 2 | **Qdrant 不當主要儲存** | Embedding 以 PG `chunk.embedding` 為 source of truth，Qdrant 唯讀 cache |
+| 3 | **Smart search 只走 PG pgvector** | `search_parent_chunks_semantic` 已正確，無需 Qdrant |
+| 4 | **移除 `server.rs::search()` dead code** | 或 mount 到正式 route 並確認可用 |
+
+### P1 — 建議修
+
+| # | Fix | 做法 |
+|---|-----|------|
+| 5 | **刪除 Qdrant 前先 snapshot** | 自動 snapshot script |
+| 6 | **清理多餘 Qdrant collections** | `dev_voice` / `dev_stories` / `dev_rule1_v2` / `sentence_*` 無 server reader，可移除 |
+| 7 | **Face embedding 寫入 PG 或移除 dead code** | 目前 face Qdrant write 無人讀取，可移除 `sync_face_embeddings` |
+| 8 | **UUID 一致性檢查** | 同一 content 不應產生不同 UUID |
+
+### P2 — 可選
+
+| # | Fix | 做法 |
+|---|-----|------|
+| 9 | `chunk_selector.rs` （player binary）hardcode `momentry_rule1` | 改讀 env var 或 PG |
+| 10 | AGENTS.md 已加入 delete 安全規則 | ✅ Done |
+
+## Data Recovery Path
+
+| 資料來源 | 可恢復到 | 方法 |
+|---------|---------|------|
+| `chunk.embedding` (PG) | Qdrant `dev_v1` | SQL → Qdrant upsert |
+| `face.json` (磁碟) | Qdrant `dev_faces` | Python script |
+| `story_llm.json` (磁碟) | Qdrant `dev_stories` | Python script |
+| Qdrant snapshots (phase1) | Qdrant collections | Snapshot upload API |

deliverable_v1.1.0/html_docs/doc/01_auth.html

@@ -0,0 +1,388 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>01 Auth - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 24px; margin: 24px 0 12px; }
+h2 { font-size: 20px; margin: 20px 0 10px; color: #222; }
+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<!-- module: auth -->
+<!-- description: Authentication — login, logout, JWT, session cookie, API key -->
+<!-- depends: -->
+
+<h2>Base URL</h2>
+<table class="table">
+<thead>
+<tr>
+<th>Environment</th>
+<th>URL</th>
+<th>Purpose</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>Production</td>
+<td><code>http://localhost:3002</code></td>
+<td>Production deployment</td>
+</tr>
+<tr>
+<td>External (M5)</td>
+<td><code>https://m5api.momentry.ddns.net</code></td>
+<td>Remote access</td>
+</tr>
+</tbody>
+</table>
+<h2>Variables</h2>
+<p>All examples in this documentation use these environment variables:</p>
+<div class="codehilite"><pre><span></span><code><span class="nv">API</span><span class="o">=</span><span class="s2">&quot;http://localhost:3002&quot;</span>
+<span class="nv">KEY</span><span class="o">=</span><span class="s2">&quot;your-api-key-here&quot;</span>
+</code></pre></div>
+
+<h2>Authentication</h2>
+<p>All endpoints under <code>/api/v1/*</code> require authentication.
+The following endpoints are public (no auth needed):</p>
+<ul>
+<li><code>GET /health</code></li>
+<li><code>POST /api/v1/auth/login</code></li>
+<li><code>POST /api/v1/auth/logout</code></li>
+</ul>
+<h3>Three Authentication Modes</h3>
+<p>The system supports three authentication methods, checked in <strong>priority order</strong> by the middleware:</p>
+<div class="codehilite"><pre><span></span><code>Middleware priority:
+  1. Session Cookie (Portal/browser)
+  2. JWT Bearer (API clients, CLI)
+  3. API Key Header (legacy compatibility)
+  4. API Key Query Param (?api_key=)
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Mode</th>
+<th>Transport</th>
+<th>Expiry</th>
+<th>Scope</th>
+<th>Best for</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><strong>Session Cookie</strong></td>
+<td><code>Cookie: session_id=&lt;session_id&gt;</code></td>
+<td>24h</td>
+<td>per-browser session</td>
+<td>Portal (browser)</td>
+</tr>
+<tr>
+<td><strong>JWT</strong></td>
+<td><code>Authorization: Bearer &lt;token&gt;</code></td>
+<td>1h</td>
+<td>per-login token</td>
+<td>API clients, CLI, scripts</td>
+</tr>
+<tr>
+<td><strong>API Key</strong></td>
+<td><code>X-API-Key: &lt;key&gt;</code></td>
+<td>90d</td>
+<td>fixed key for automation</td>
+<td>Legacy scripts, WordPress</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3>Login</h3>
+<p><strong>Default accounts &amp; API keys:</strong></p>
+<table class="table">
+<thead>
+<tr>
+<th>Username</th>
+<th>Password</th>
+<th>API Key</th>
+<th>Role</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>admin</code></td>
+<td><code>admin</code></td>
+<td>—</td>
+<td>admin</td>
+</tr>
+<tr>
+<td><code>demo</code></td>
+<td><code>demo</code></td>
+<td><code>muser_demo_key_32chars_abcdef1234567890</code></td>
+<td>user</td>
+</tr>
+</tbody>
+</table>
+<p>The demo API key is set via <code>MOMENTRY_DEMO_API_KEY</code> env var and can be used in place of JWT for marcom integrations:</p>
+<div class="codehilite"><pre><span></span><code><span class="c1"># Using API key instead of JWT</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/scan&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: muser_demo_key_32chars_abcdef1234567890&quot;</span>
+</code></pre></div>
+
+<div class="codehilite"><pre><span></span><code><span class="c1"># Login as admin</span>
+curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/auth/login&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;username&quot;: &quot;admin&quot;, &quot;password&quot;: &quot;admin&quot;}&#39;</span>
+
+<span class="c1"># Login as demo user</span>
+curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/auth/login&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;username&quot;: &quot;demo&quot;, &quot;password&quot;: &quot;demo&quot;}&#39;</span>
+</code></pre></div>
+
+<h4>Success Response</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;jwt&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;eyJhbGciOiJIUzI1NiIs...&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;api_key&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;muser_...&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;user&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nt">&quot;username&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;admin&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;role&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;admin&quot;</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nt">&quot;expires_at&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;2026-05-18T13:00:00Z&quot;</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>jwt</code></td>
+<td>string</td>
+<td>JWT access token. Use as <code>Authorization: Bearer &lt;jwt&gt;</code>. Expires in 1 hour.</td>
+</tr>
+<tr>
+<td><code>api_key</code></td>
+<td>string</td>
+<td>Legacy API key. Use as <code>X-API-Key: &lt;key&gt;</code>. Good for 90 days.</td>
+</tr>
+<tr>
+<td><code>user.username</code></td>
+<td>string</td>
+<td>Username</td>
+</tr>
+<tr>
+<td><code>user.role</code></td>
+<td>string</td>
+<td>Role: <code>admin</code>, <code>user</code>, or <code>readonly</code></td>
+</tr>
+<tr>
+<td><code>expires_at</code></td>
+<td>string</td>
+<td>ISO8601 timestamp of JWT expiration</td>
+</tr>
+</tbody>
+</table>
+<p>The login endpoint also sets a <code>Set-Cookie</code> header for browser-based clients:</p>
+<div class="codehilite"><pre><span></span><code><span class="nt">Set-Cookie</span><span class="o">:</span><span class="w"> </span><span class="nt">session_id</span><span class="o">=&lt;</span><span class="nt">session_id</span><span class="o">&gt;;</span><span class="w"> </span><span class="nt">Path</span><span class="o">=/;</span><span class="w"> </span><span class="nt">HttpOnly</span><span class="o">;</span><span class="w"> </span><span class="nt">SameSite</span><span class="o">=</span><span class="nt">Strict</span><span class="o">;</span><span class="w"> </span><span class="nt">Max-Age</span><span class="o">=</span><span class="nt">86400</span>
+</code></pre></div>
+
+<h4>Error Response (401)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;message&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Invalid username or password&quot;</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<hr />
+<h3>Using JWT</h3>
+<p>JWT is preferred for API clients (CLI scripts, WordPress). It is validated by the middleware without a database lookup (stateless).</p>
+<div class="codehilite"><pre><span></span><code><span class="c1"># Login and capture JWT</span>
+<span class="nv">JWT</span><span class="o">=</span><span class="k">$(</span>curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/auth/login&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;username&quot;:&quot;admin&quot;,&quot;password&quot;:&quot;admin&quot;}&#39;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>python3<span class="w"> </span>-c<span class="w"> </span><span class="s2">&quot;import json,sys;print(json.load(sys.stdin)[&#39;jwt&#39;])&quot;</span><span class="k">)</span>
+
+<span class="c1"># Use JWT for all subsequent requests</span>
+curl<span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;Authorization: Bearer </span><span class="nv">$JWT</span><span class="s2">&quot;</span><span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/scan&quot;</span>
+curl<span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;Authorization: Bearer </span><span class="nv">$JWT</span><span class="s2">&quot;</span><span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/resource/tmdb&quot;</span>
+</code></pre></div>
+
+<p>JWT is short-lived (1 hour). When it expires, request a new one via login.</p>
+<hr />
+<h3>Using Session Cookie (Browser)</h3>
+<p>Browser-based clients (Portal) get a session cookie automatically after login. The browser sends the cookie with every request—no manual header needed.</p>
+<div class="codehilite"><pre><span></span><code><span class="c1"># Login captures the session cookie from Set-Cookie header</span>
+curl<span class="w"> </span>-v<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/auth/login&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;username&quot;:&quot;admin&quot;,&quot;password&quot;:&quot;admin&quot;}&#39;</span><span class="w"> </span><span class="m">2</span>&gt;<span class="p">&amp;</span><span class="m">1</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>grep<span class="w"> </span><span class="s2">&quot;Set-Cookie&quot;</span>
+
+<span class="c1"># Browser automatically sends: Cookie: session_id=&lt;session_id&gt;</span>
+<span class="c1"># No manual header needed for subsequent requests</span>
+</code></pre></div>
+
+<p>The session cookie is HttpOnly (not accessible from JavaScript) and SameSite=Strict (protected against CSRF).</p>
+<hr />
+<h3>Using Legacy API Key</h3>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/scan&quot;</span>
+
+<span class="c1"># Also accepted via Bearer header (non-JWT format) or query parameter:</span>
+curl<span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;Authorization: Bearer </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/scan&quot;</span>
+curl<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/scan?api_key=</span><span class="nv">$KEY</span><span class="s2">&quot;</span>
+</code></pre></div>
+
+<p>API keys are validated via SHA256 hash lookup in the database. They are long-lived (90 days) and intended for automation.</p>
+<h3>Obtaining an API Key (CLI)</h3>
+<div class="codehilite"><pre><span></span><code>momentry<span class="w"> </span>api-key<span class="w"> </span>create<span class="w"> </span><span class="s2">&quot;My API Key&quot;</span><span class="w"> </span>--key-type<span class="w"> </span>user
+</code></pre></div>
+
+<hr />
+<h3>Logout</h3>
+<div class="codehilite"><pre><span></span><code><span class="c1"># Logout using the session cookie (browser)</span>
+curl<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/auth/logout&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Cookie: session_id=&lt;uuid&gt;&quot;</span>
+</code></pre></div>
+
+<h4>What logout does</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Auth mode</th>
+<th>Effect</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><strong>Session Cookie</strong></td>
+<td>Session deleted from database. Same cookie returns 401 on subsequent requests.</td>
+</tr>
+<tr>
+<td><strong>JWT</strong></td>
+<td>JWT remains valid until expiry. (JWT is stateless — logout adds JWT to a blacklist only if API key mode is used.)</td>
+</tr>
+<tr>
+<td><strong>API Key</strong></td>
+<td>API key remains valid. (Legacy keys are shared across sessions — revoking would break other clients.)</td>
+</tr>
+</tbody>
+</table>
+<h4>Example: full session lifecycle</h4>
+<div class="codehilite"><pre><span></span><code><span class="c1"># 1. Login</span>
+<span class="nv">SESSION_ID</span><span class="o">=</span><span class="k">$(</span>curl<span class="w"> </span>-s<span class="w"> </span>-D<span class="w"> </span>-<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/auth/login&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;username&quot;:&quot;admin&quot;,&quot;password&quot;:&quot;admin&quot;}&#39;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>grep<span class="w"> </span><span class="s2">&quot;Set-Cookie&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>sed<span class="w"> </span><span class="s1">&#39;s/.*session_id=\([^;]*\).*/\1/&#39;</span><span class="k">)</span>
+
+<span class="c1"># 2. Use session (works)</span>
+curl<span class="w"> </span>-s<span class="w"> </span>-o<span class="w"> </span>/dev/null<span class="w"> </span>-w<span class="w"> </span><span class="s2">&quot;HTTP %{http_code}\n&quot;</span><span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/resource/tmdb&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Cookie: session_id=</span><span class="nv">$SESSION_ID</span><span class="s2">&quot;</span>
+<span class="c1"># → HTTP 200</span>
+
+<span class="c1"># 3. Logout</span>
+curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/auth/logout&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Cookie: session_id=</span><span class="nv">$SESSION_ID</span><span class="s2">&quot;</span>
+<span class="c1"># → {&quot;success&quot;: true}</span>
+
+<span class="c1"># 4. Use session again (rejected)</span>
+curl<span class="w"> </span>-s<span class="w"> </span>-o<span class="w"> </span>/dev/null<span class="w"> </span>-w<span class="w"> </span><span class="s2">&quot;HTTP %{http_code}\n&quot;</span><span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/resource/tmdb&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Cookie: session_id=</span><span class="nv">$SESSION_ID</span><span class="s2">&quot;</span>
+<span class="c1"># → HTTP 401</span>
+</code></pre></div>
+
+<hr />
+<h3>Authentication Flow Summary</h3>
+<div class="codehilite"><pre><span></span><code>Login Request
+     │
+     ▼
+┌──────────────────┐
+│  1. Check users  │ ← users table (argon2 password verify)
+│     table        │
+└──────┬───────────┘
+       │
+   ┌───┴───┐
+   │ match │
+   └───┬───┘
+       │
+       ▼
+┌──────────────────┐
+│  2. Create JWT   │ ← 1h expiry, signed with JWT_SECRET
+├──────────────────┤
+│  3. Create       │ ← 24h expiry, stored in sessions table
+│     session      │
+├──────────────────┤
+│  4. Set-Cookie   │ ← HttpOnly, SameSite=Strict, Path=/
+├──────────────────┤
+│  5. Return       │ ← JWT + api_key + user info to client
+└──────────────────┘
+</code></pre></div>
+
+<div class="codehilite"><pre><span></span><code>Protected Request
+     │
+     ▼
+┌──────────────────────┐
+│  Middleware checks:  │
+│                      │
+│  1. Cookie session?  │ → DB lookup session → get api_key → verify
+│                      │
+│  2. JWT Bearer?      │ → verify JWT signature → decode claims
+│                      │
+│  3. X-API-Key?       │ → SHA256 hash → DB lookup → verify
+│                      │
+│  4. ?api_key=?       │ → same as #3
+│                      │
+│  5. None → 401       │
+└──────────────────────┘
+</code></pre></div>
+
+<hr />
+<h3>Error Responses</h3>
+<table class="table">
+<thead>
+<tr>
+<th>HTTP</th>
+<th>When</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>401</code></td>
+<td>Missing or invalid authentication</td>
+</tr>
+<tr>
+<td><code>401</code></td>
+<td>Session expired or logged out</td>
+</tr>
+<tr>
+<td><code>401</code></td>
+<td>JWT expired</td>
+</tr>
+<tr>
+<td><code>401</code></td>
+<td>API key revoked or inactive</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3>Related</h3>
+<ul>
+<li><code>POST /api/v1/resource/tmdb/check</code> — test authentication + TMDb API connectivity</li>
+<li><code>GET /health/detailed</code> — view auth status (integrations section)</li>
+</ul>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/02_health.html

@@ -0,0 +1,277 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>02 Health - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 24px; margin: 24px 0 12px; }
+h2 { font-size: 20px; margin: 20px 0 10px; color: #222; }
+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<!-- module: health -->
+<!-- description: Health check endpoints -->
+<!-- depends: 01_auth -->
+
+<h2>Health Check</h2>
+<h3><code>GET /health</code></h3>
+<p><strong>Auth</strong>: Public
+<strong>Scope</strong>: system-level</p>
+<p>Returns basic server health status — used by load balancers and monitoring.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/health&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;{status, version}&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;ok&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;version&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;1.0.0&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;build_git_hash&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;3a6c1865&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;build_timestamp&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;2026-05-16T13:38:15Z&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;uptime_ms&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">3015</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>status</code></td>
+<td>string</td>
+<td><code>ok</code> or <code>degraded</code></td>
+</tr>
+<tr>
+<td><code>version</code></td>
+<td>string</td>
+<td>Semver version</td>
+</tr>
+<tr>
+<td><code>build_git_hash</code></td>
+<td>string</td>
+<td>Git commit hash</td>
+</tr>
+<tr>
+<td><code>build_timestamp</code></td>
+<td>string</td>
+<td>Binary build time</td>
+</tr>
+<tr>
+<td><code>uptime_ms</code></td>
+<td>integer</td>
+<td>Milliseconds since server start</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3><code>GET /health/detailed</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: system-level</p>
+<p>Returns full system health including each service status, resource utilization, pipeline readiness, schema migration status, identity file sync status, and external integrations.</p>
+<blockquote>
+<p>Requires authentication (JWT, session cookie, or API key). The basic <code>/health</code> endpoint remains public for load balancer checks.</p>
+</blockquote>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/health/detailed&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;{status, services, resources: {cpu: .resources.cpu_used_percent, memory: .resources.memory_used_percent}}&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;ok&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;version&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;1.0.0&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;services&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nt">&quot;postgres&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;ok&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;latency_ms&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">3</span><span class="p">},</span>
+<span class="w">    </span><span class="nt">&quot;redis&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;ok&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;latency_ms&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">1</span><span class="p">},</span>
+<span class="w">    </span><span class="nt">&quot;qdrant&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;ok&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;latency_ms&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">5</span><span class="p">}</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nt">&quot;resources&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nt">&quot;cpu_used_percent&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">12.5</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;memory_available_mb&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">32768</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;memory_used_percent&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">31.7</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nt">&quot;pipeline&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nt">&quot;scripts_ready&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;scripts_count&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">345</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;processors&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nt">&quot;asr&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;yolo&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;face&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;pose&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;ocr&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;cut&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;scene&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;asrx&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;visual_chunk&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nt">&quot;models_ready&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;models_count&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">42</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;scripts_integrity&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="nt">&quot;matched&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">332</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;total&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">345</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;ok&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">false</span><span class="p">},</span>
+<span class="w">    </span><span class="nt">&quot;ffmpeg&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nt">&quot;schema&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nt">&quot;table_exists&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;applied&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[{</span><span class="nt">&quot;filename&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;migrate_add_users_table.sql&quot;</span><span class="p">}],</span>
+<span class="w">    </span><span class="nt">&quot;required&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[],</span>
+<span class="w">    </span><span class="nt">&quot;ok&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nt">&quot;identities&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nt">&quot;directory_exists&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;files_count&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">3481</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;index_ok&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;db_count&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">3481</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;synced&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nt">&quot;integrations&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nt">&quot;tmdb&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nt">&quot;api_key_configured&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;enabled&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;api_reachable&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">null</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<h4>Response Fields</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>status</code></td>
+<td>string</td>
+<td><code>ok</code> if all essential services healthy</td>
+</tr>
+<tr>
+<td><code>services</code></td>
+<td>object</td>
+<td>Per-service status (postgres, redis, qdrant)</td>
+</tr>
+<tr>
+<td><code>services.*.status</code></td>
+<td>string</td>
+<td><code>ok</code>, <code>error</code>, or <code>degraded</code></td>
+</tr>
+<tr>
+<td><code>services.*.latency_ms</code></td>
+<td>int</td>
+<td>Response time in milliseconds</td>
+</tr>
+<tr>
+<td><code>resources</code></td>
+<td>object</td>
+<td>CPU, memory usage</td>
+</tr>
+<tr>
+<td><code>pipeline.scripts_ready</code></td>
+<td>boolean</td>
+<td>Scripts directory accessible</td>
+</tr>
+<tr>
+<td><code>pipeline.scripts_count</code></td>
+<td>int</td>
+<td>Number of Python processor scripts</td>
+</tr>
+<tr>
+<td><code>pipeline.processors</code></td>
+<td>object</td>
+<td>Per-processor availability</td>
+</tr>
+<tr>
+<td><code>pipeline.models_ready</code></td>
+<td>boolean</td>
+<td>Models directory accessible</td>
+</tr>
+<tr>
+<td><code>pipeline.scripts_integrity</code></td>
+<td>object</td>
+<td>SHA256 checksum verification results</td>
+</tr>
+<tr>
+<td><code>schema.ok</code></td>
+<td>boolean</td>
+<td>All required migrations applied</td>
+</tr>
+<tr>
+<td><code>identities.synced</code></td>
+<td>boolean</td>
+<td>Identity file count matches DB count</td>
+</tr>
+<tr>
+<td><code>integrations.tmdb</code></td>
+<td>object</td>
+<td>TMDB API key config and reachability</td>
+</tr>
+</tbody>
+</table>
+<h4>Health status rules</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Condition</th>
+<th>status</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>All services ok</td>
+<td><code>ok</code></td>
+</tr>
+<tr>
+<td>Any service error</td>
+<td><code>degraded</code></td>
+</tr>
+<tr>
+<td>Postgres or Redis error</td>
+<td><code>degraded</code> (server still responds)</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3>Stats Endpoints</h3>
+<table class="table">
+<thead>
+<tr>
+<th>Method</th>
+<th>Endpoint</th>
+<th>Auth</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>GET</td>
+<td><code>/api/v1/stats/sftpgo</code></td>
+<td>No</td>
+<td>SFTPGo service status</td>
+</tr>
+</tbody>
+</table>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/03_register.html

@@ -0,0 +1,444 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>03 Register - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 24px; margin: 24px 0 12px; }
+h2 { font-size: 20px; margin: 20px 0 10px; color: #222; }
+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<!-- module: register -->
+<!-- description: File registration — register, scan -->
+<!-- depends: 01_auth -->
+
+<h2>File Registration</h2>
+<h3><code>POST /api/v1/files/register</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Register a video file for processing. Returns the file's metadata and UUID.</p>
+<p><strong>New in v0.1.2</strong>: Registration now <strong>automatically triggers the processing pipeline</strong> — no need to call <code>POST /api/v1/file/:file_uuid/process</code> separately. The system will:
+1. Register the file and run ffprobe
+2. Auto-run offline TMDb probe (reads local identity files, no API calls)
+3. Create a monitor job for the worker
+4. Worker starts all 10 processors (Cut → ASR → ASRX → YOLO → OCR → Face → Pose → VisualChunk → Story → 5W1H)</p>
+<p>If the file already exists (same content hash), returns the existing record with <code>already_exists: true</code>.</p>
+<h4>Request Parameters</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Default</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>file_path</code></td>
+<td>string</td>
+<td>Yes</td>
+<td>—</td>
+<td>Path to video file on disk</td>
+</tr>
+<tr>
+<td><code>pattern</code></td>
+<td>string</td>
+<td>No</td>
+<td>—</td>
+<td>Regex pattern for batch register (requires <code>file_path</code> to be a directory)</td>
+</tr>
+<tr>
+<td><code>user_id</code></td>
+<td>integer</td>
+<td>No</td>
+<td>—</td>
+<td>User ID to associate with registration</td>
+</tr>
+<tr>
+<td><code>content_hash</code></td>
+<td>string</td>
+<td>No</td>
+<td>—</td>
+<td>Pre-computed SHA-256 hash (skips computation)</td>
+</tr>
+</tbody>
+</table>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code><span class="c1"># Register a single file</span>
+curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/register&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;file_path&quot;: &quot;/path/to/video.mp4&quot;}&#39;</span>
+
+<span class="c1"># Batch register files matching a pattern in a directory</span>
+curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/register&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;file_path&quot;: &quot;/path/to/dir&quot;, &quot;pattern&quot;: &quot;.*\\.mp4$&quot;}&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;file_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;3a6c1865...&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;file_name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;video.mp4&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;file_path&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;/path/to/video.mp4&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;file_type&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;video&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;duration&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">120.5</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;width&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">1920</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;height&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">1080</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;fps&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">24.0</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;total_frames&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">2892</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;already_exists&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;message&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;File registered successfully&quot;</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>success</code></td>
+<td>boolean</td>
+<td>Always true on 200</td>
+</tr>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>32-char hex UUID of the registered file</td>
+</tr>
+<tr>
+<td><code>file_name</code></td>
+<td>string</td>
+<td>File name (auto-renamed if name conflict)</td>
+</tr>
+<tr>
+<td><code>file_path</code></td>
+<td>string</td>
+<td>Canonical path on disk</td>
+</tr>
+<tr>
+<td><code>file_type</code></td>
+<td>string</td>
+<td><code>"video"</code>, <code>"audio"</code>, or <code>"unknown"</code></td>
+</tr>
+<tr>
+<td><code>duration</code></td>
+<td>float</td>
+<td>Duration in seconds</td>
+</tr>
+<tr>
+<td><code>width</code></td>
+<td>integer</td>
+<td>Video width in pixels</td>
+</tr>
+<tr>
+<td><code>height</code></td>
+<td>integer</td>
+<td>Video height in pixels</td>
+</tr>
+<tr>
+<td><code>fps</code></td>
+<td>float</td>
+<td>Frames per second</td>
+</tr>
+<tr>
+<td><code>total_frames</code></td>
+<td>integer</td>
+<td>Total frame count</td>
+</tr>
+<tr>
+<td><code>already_exists</code></td>
+<td>boolean</td>
+<td>True if same content was already registered</td>
+</tr>
+<tr>
+<td><code>message</code></td>
+<td>string</td>
+<td>Human-readable status</td>
+</tr>
+</tbody>
+</table>
+<h4>Error Responses</h4>
+<table class="table">
+<thead>
+<tr>
+<th>HTTP</th>
+<th>When</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>401</code></td>
+<td>Missing or invalid API key</td>
+</tr>
+<tr>
+<td><code>400</code></td>
+<td>Invalid request body</td>
+</tr>
+<tr>
+<td><code>404</code></td>
+<td>File path does not exist</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3><code>GET /api/v1/files/scan</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Scan the filesystem directory and list all media files, showing which are registered, processing, or unregistered.</p>
+<h4>Query Parameters</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Default</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>page</code></td>
+<td>integer</td>
+<td>No</td>
+<td>1</td>
+<td>Page number (1-based)</td>
+</tr>
+<tr>
+<td><code>page_size</code></td>
+<td>integer</td>
+<td>No</td>
+<td>all</td>
+<td>Items per page (alias: <code>limit</code>)</td>
+</tr>
+<tr>
+<td><code>limit</code></td>
+<td>integer</td>
+<td>No</td>
+<td>all</td>
+<td>Max items (alias for <code>page_size</code>)</td>
+</tr>
+<tr>
+<td><code>pattern</code></td>
+<td>string</td>
+<td>No</td>
+<td>—</td>
+<td>Regex filter on file name (e.g., <code>.*\\.mp4$</code>)</td>
+</tr>
+<tr>
+<td><code>sort_by</code></td>
+<td>string</td>
+<td>No</td>
+<td><code>name</code></td>
+<td>Sort field: <code>name</code>, <code>size</code>, <code>modified</code>, <code>status</code></td>
+</tr>
+<tr>
+<td><code>sort_order</code></td>
+<td>string</td>
+<td>No</td>
+<td><code>asc</code></td>
+<td>Sort direction: <code>asc</code> or <code>desc</code></td>
+</tr>
+</tbody>
+</table>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code><span class="c1"># Full scan</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/scan&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;{total, registered_count, unregistered_count}&#39;</span>
+
+<span class="c1"># Paginated (page 1, 5 per page)</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/scan?page=1&amp;page_size=5&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;{page, total_pages, files: [.files[].file_name]}&#39;</span>
+
+<span class="c1"># Regex filter: only mp4 files</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/scan?pattern=.*\\.mp4</span>$<span class="s2">&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;{filtered_total, files: [.files[].file_name]}&#39;</span>
+
+<span class="c1"># Sort by file size (largest first)</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/scan?sort_by=size&amp;sort_order=desc&amp;page_size=5&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;[.files[] | {file_name, file_size}]&#39;</span>
+
+<span class="c1"># Sort by modified time (most recent first)</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/scan?sort_by=modified&amp;sort_order=desc&amp;page_size=5&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;[.files[] | {file_name, modified_time}]&#39;</span>
+
+<span class="c1"># Sort by status</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/scan?sort_by=status&amp;page_size=5&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;[.files[] | {file_name, status}]&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;files&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
+<span class="w">      </span><span class="nt">&quot;file_name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;video.mp4&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;file_size&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">12345678</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;is_registered&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;file_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;3a6c1865...&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;completed&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;registration_time&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;2026-05-16T12:00:00Z&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;job_id&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">42</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="nt">&quot;total&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">107</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;filtered_total&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">80</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;page&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">1</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;page_size&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">20</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;total_pages&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">4</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;registered_count&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">26</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;unregistered_count&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">81</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>files</code></td>
+<td>array</td>
+<td>Array of file info objects (paginated)</td>
+</tr>
+<tr>
+<td><code>files[].file_name</code></td>
+<td>string</td>
+<td>File name</td>
+</tr>
+<tr>
+<td><code>files[].relative_path</code></td>
+<td>string</td>
+<td>Path relative to scan root</td>
+</tr>
+<tr>
+<td><code>files[].file_path</code></td>
+<td>string</td>
+<td>Absolute path on disk</td>
+</tr>
+<tr>
+<td><code>files[].file_size</code></td>
+<td>integer</td>
+<td>File size in bytes</td>
+</tr>
+<tr>
+<td><code>files[].modified_time</code></td>
+<td>string</td>
+<td>Last modified timestamp (ISO8601)</td>
+</tr>
+<tr>
+<td><code>files[].is_registered</code></td>
+<td>boolean</td>
+<td>Whether file is registered in DB</td>
+</tr>
+<tr>
+<td><code>files[].file_uuid</code></td>
+<td>string</td>
+<td>32-char hex UUID (only if registered)</td>
+</tr>
+<tr>
+<td><code>files[].status</code></td>
+<td>string</td>
+<td><code>"completed"</code>, <code>"processing"</code>, <code>"registered"</code>, <code>"unregistered"</code>, or <code>null</code></td>
+</tr>
+<tr>
+<td><code>files[].registration_time</code></td>
+<td>string</td>
+<td>DB registration timestamp (only if registered)</td>
+</tr>
+<tr>
+<td><code>files[].job_id</code></td>
+<td>integer</td>
+<td>Processing job ID (only if a job exists)</td>
+</tr>
+<tr>
+<td><code>total</code></td>
+<td>integer</td>
+<td>Total files found on disk (unfiltered)</td>
+</tr>
+<tr>
+<td><code>filtered_total</code></td>
+<td>integer</td>
+<td>Files matching regex filter</td>
+</tr>
+<tr>
+<td><code>page</code></td>
+<td>integer</td>
+<td>Current page number</td>
+</tr>
+<tr>
+<td><code>page_size</code></td>
+<td>integer</td>
+<td>Items per page</td>
+</tr>
+<tr>
+<td><code>total_pages</code></td>
+<td>integer</td>
+<td>Total pages</td>
+</tr>
+<tr>
+<td><code>registered_count</code></td>
+<td>integer</td>
+<td>Files registered in DB</td>
+</tr>
+<tr>
+<td><code>unregistered_count</code></td>
+<td>integer</td>
+<td>Files not yet registered</td>
+</tr>
+</tbody>
+</table>
+<h4>Notes</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Feature</th>
+<th>Behavior</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><strong>Regex</strong></td>
+<td>Case-insensitive (<code>(?i)</code> prefix auto-applied). Applied to <code>file_name</code>.</td>
+</tr>
+<tr>
+<td><strong>Sort order</strong></td>
+<td>Default (<code>sort_by=name</code>): registered files first, then alphabetically. <code>sort_by=status</code>: alphabetical by status string.</td>
+</tr>
+<tr>
+<td><strong>Pagination</strong></td>
+<td><code>page_size</code> and <code>limit</code> are aliases. Default: show all results.</td>
+</tr>
+<tr>
+<td><strong>Processing order</strong></td>
+<td><code>pattern</code> regex filter → <code>sort_by</code>/<code>sort_order</code> → <code>page</code>/<code>page_size</code> slice.</td>
+</tr>
+</tbody>
+</table>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/04_lookup.html

@@ -0,0 +1,291 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>04 Lookup - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 24px; margin: 24px 0 12px; }
+h2 { font-size: 20px; margin: 20px 0 10px; color: #222; }
+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<!-- module: lookup -->
+<!-- description: File lookup by name and unregistration -->
+<!-- depends: 01_auth, 03_register -->
+
+<h2>File Lookup</h2>
+<h3><code>GET /api/v1/files/lookup</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Search registered files by file name. Performs a case-insensitive LIKE search on the file name column. Returns basic info about matching files.</p>
+<h4>Query Parameters</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>file_name</code></td>
+<td>string</td>
+<td>Yes</td>
+<td>File name to search for (partial matches supported)</td>
+</tr>
+</tbody>
+</table>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code><span class="c1"># Look up a specific file</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/lookup?file_name=video.mp4&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span>
+
+<span class="c1"># Partial name search</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/files/lookup?file_name=charade&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;.matches[].file_name&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;file_name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;video.mp4&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;exists&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;matches&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
+<span class="w">      </span><span class="nt">&quot;file_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;a03485a40b2df2d3&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;file_name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;video.mp4&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;file_type&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;video&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;completed&quot;</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="nt">&quot;next_name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;video (2).mp4&quot;</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>file_name</code></td>
+<td>string</td>
+<td>Searched name</td>
+</tr>
+<tr>
+<td><code>exists</code></td>
+<td>boolean</td>
+<td>Exact name match exists</td>
+</tr>
+<tr>
+<td><code>matches</code></td>
+<td>array</td>
+<td>Array of matching registered files</td>
+</tr>
+<tr>
+<td><code>matches[].file_uuid</code></td>
+<td>string</td>
+<td>32-char hex UUID</td>
+</tr>
+<tr>
+<td><code>matches[].file_name</code></td>
+<td>string</td>
+<td>Registered file name</td>
+</tr>
+<tr>
+<td><code>matches[].file_type</code></td>
+<td>string</td>
+<td><code>"video"</code>, <code>"audio"</code>, or <code>null</code></td>
+</tr>
+<tr>
+<td><code>matches[].status</code></td>
+<td>string</td>
+<td>Registration/processing status</td>
+</tr>
+<tr>
+<td><code>next_name</code></td>
+<td>string</td>
+<td>Suggested name for avoiding conflicts</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h2>Unregister</h2>
+<h3><code>POST /api/v1/unregister</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Delete a registered file from the system. Supports single file by UUID, or batch by directory + regex pattern.</p>
+<h4>What gets deleted</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Removed (default)</th>
+<th>Not removed</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>Database records (videos, chunks, embeddings, processor_results, pre_chunks)</td>
+<td>The original source video file on disk</td>
+</tr>
+<tr>
+<td>Processor output JSON files (<code>{uuid}.*.json</code>) — unless <code>delete_output_files: false</code></td>
+<td>Temp/working directories</td>
+</tr>
+<tr>
+<td>In-memory cache entries</td>
+<td></td>
+</tr>
+<tr>
+<td>MongoDB cached lists</td>
+<td></td>
+</tr>
+</tbody>
+</table>
+<blockquote>
+<p>⚠️ Database deletion is <strong>irreversible</strong>. To keep output files, set <code>"delete_output_files": false</code>.</p>
+</blockquote>
+<h4>Request Parameters</h4>
+<p>At least one mode must be specified: either <code>file_uuid</code> alone, or <code>file_path</code> + <code>pattern</code> together.</p>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Default</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>*</td>
+<td>—</td>
+<td>Single file UUID to delete</td>
+</tr>
+<tr>
+<td><code>file_path</code></td>
+<td>string</td>
+<td>*</td>
+<td>—</td>
+<td>Directory path (for batch delete)</td>
+</tr>
+<tr>
+<td><code>pattern</code></td>
+<td>string</td>
+<td>*</td>
+<td>—</td>
+<td>Regex pattern (requires <code>file_path</code>)</td>
+</tr>
+<tr>
+<td><code>delete_output_files</code></td>
+<td>boolean</td>
+<td>No</td>
+<td><code>true</code></td>
+<td>If <code>true</code>, also delete processor output JSON files (<code>{uuid}.*.json</code>). Set to <code>false</code> to keep them.</td>
+</tr>
+</tbody>
+</table>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code><span class="c1"># Delete a single file by UUID (default: also deletes output JSON files)</span>
+curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/unregister&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;file_uuid&quot;: &quot;&#39;</span><span class="s2">&quot;</span><span class="nv">$FILE_UUID</span><span class="s2">&quot;</span><span class="s1">&#39;&quot;}&#39;</span>
+
+<span class="c1"># Keep output JSON files, only delete DB records</span>
+curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/unregister&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;file_uuid&quot;: &quot;&#39;</span><span class="s2">&quot;</span><span class="nv">$FILE_UUID</span><span class="s2">&quot;</span><span class="s1">&#39;&quot;, &quot;delete_output_files&quot;: false}&#39;</span>
+
+<span class="c1"># Batch delete all mp4 files in a directory</span>
+curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/unregister&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;file_path&quot;: &quot;/path/to/dir&quot;, &quot;pattern&quot;: &quot;.*\\.mp4$&quot;}&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;file_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;a03485a40b2df2d3&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;message&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Video unregistered successfully&quot;</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>success</code></td>
+<td>boolean</td>
+<td>True if deletion succeeded</td>
+</tr>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>UUID of the deleted file (single mode)</td>
+</tr>
+<tr>
+<td><code>message</code></td>
+<td>string</td>
+<td>Human-readable status</td>
+</tr>
+</tbody>
+</table>
+<h4>Error Responses</h4>
+<table class="table">
+<thead>
+<tr>
+<th>HTTP</th>
+<th>When</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>400</code></td>
+<td>Neither <code>file_uuid</code> nor <code>file_path</code>+<code>pattern</code> provided</td>
+</tr>
+<tr>
+<td><code>404</code></td>
+<td>File UUID not found</td>
+</tr>
+<tr>
+<td><code>401</code></td>
+<td>Missing or invalid API key</td>
+</tr>
+</tbody>
+</table>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/05_process.html

@@ -0,0 +1,505 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>05 Process - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 24px; margin: 24px 0 12px; }
+h2 { font-size: 20px; margin: 20px 0 10px; color: #222; }
+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<!-- module: process -->
+<!-- description: Processing pipeline — trigger, probe, progress, jobs -->
+<!-- depends: 01_auth, 03_register -->
+
+<h2>Processing Pipeline</h2>
+<h3><code>POST /api/v1/file/:file_uuid/process</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Trigger the processing pipeline for a registered file. Creates a monitor job that the worker picks up and processes sequentially. Returns immediately with the job info—processing runs asynchronously in the background.</p>
+<h4>Request Parameters</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Default</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>processors</code></td>
+<td>string[]</td>
+<td>No</td>
+<td>all</td>
+<td>Specific processors to run: <code>["cut","asr","asrx","yolo","ocr","face","pose","visual_chunk","story","5w1h"]</code></td>
+</tr>
+<tr>
+<td><code>rules</code></td>
+<td>string[]</td>
+<td>No</td>
+<td>all</td>
+<td>Rule names to apply (currently unused)</td>
+</tr>
+</tbody>
+</table>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code><span class="c1"># Run all processors</span>
+curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/file/</span><span class="nv">$FILE_UUID</span><span class="s2">/process&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span>-d<span class="w"> </span><span class="s1">&#39;{}&#39;</span>
+
+<span class="c1"># Run specific processors only</span>
+curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/file/</span><span class="nv">$FILE_UUID</span><span class="s2">/process&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;processors&quot;: [&quot;asr&quot;, &quot;face&quot;, &quot;yolo&quot;]}&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;job_id&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">42</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;file_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;3a6c1865...&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;processing&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;pids&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="mi">12345</span><span class="p">,</span><span class="w"> </span><span class="mi">12346</span><span class="p">],</span>
+<span class="w">  </span><span class="nt">&quot;message&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Processing triggered for video.mp4&quot;</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>success</code></td>
+<td>boolean</td>
+<td>Always true on 200</td>
+</tr>
+<tr>
+<td><code>job_id</code></td>
+<td>integer</td>
+<td>Monitor job ID (for job tracking)</td>
+</tr>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>32-char hex UUID of the file</td>
+</tr>
+<tr>
+<td><code>status</code></td>
+<td>string</td>
+<td><code>"processing"</code></td>
+</tr>
+<tr>
+<td><code>pids</code></td>
+<td>integer[]</td>
+<td>Process IDs of started processors</td>
+</tr>
+<tr>
+<td><code>message</code></td>
+<td>string</td>
+<td>Human-readable status</td>
+</tr>
+</tbody>
+</table>
+<h4>Error Responses</h4>
+<table class="table">
+<thead>
+<tr>
+<th>HTTP</th>
+<th>When</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>404</code></td>
+<td>File UUID not found</td>
+</tr>
+<tr>
+<td><code>401</code></td>
+<td>Missing or invalid API key</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3><code>GET /api/v1/file/:file_uuid/probe</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Get ffprobe metadata for a registered file. Returns video/audio stream info, codec details, duration, resolution, and frame rate.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/file/</span><span class="nv">$FILE_UUID</span><span class="s2">/probe&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;file_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;3a6c1865...&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;file_name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;video.mp4&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;file_size&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">794863677</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;duration&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">120.5</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;width&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">1920</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;height&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">1080</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;fps&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">24.0</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;total_frames&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">2892</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;cached&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;format&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nt">&quot;filename&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;/path/to/video.mp4&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;format_name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;mov,mp4,m4a,3gp&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;duration&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;120.5&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;size&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;12345678&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;bit_rate&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;819200&quot;</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nt">&quot;streams&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
+<span class="w">      </span><span class="nt">&quot;index&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">0</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;codec_name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;h264&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;codec_type&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;video&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;width&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">1920</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;height&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">1080</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;r_frame_rate&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;24/1&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;duration&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;120.5&quot;</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>32-char hex UUID</td>
+</tr>
+<tr>
+<td><code>file_name</code></td>
+<td>string</td>
+<td>File name</td>
+</tr>
+<tr>
+<td><code>file_size</code></td>
+<td>integer</td>
+<td>File size in bytes (from filesystem)</td>
+</tr>
+<tr>
+<td><code>duration</code></td>
+<td>float</td>
+<td>Duration in seconds</td>
+</tr>
+<tr>
+<td><code>width</code></td>
+<td>integer</td>
+<td>Video width in pixels</td>
+</tr>
+<tr>
+<td><code>height</code></td>
+<td>integer</td>
+<td>Video height in pixels</td>
+</tr>
+<tr>
+<td><code>fps</code></td>
+<td>float</td>
+<td>Frames per second</td>
+</tr>
+<tr>
+<td><code>total_frames</code></td>
+<td>integer</td>
+<td>Estimated total frames</td>
+</tr>
+<tr>
+<td><code>cached</code></td>
+<td>boolean</td>
+<td>True if result was from cached probe JSON</td>
+</tr>
+<tr>
+<td><code>format</code></td>
+<td>object</td>
+<td>Container format info (ffprobe format section)</td>
+</tr>
+<tr>
+<td><code>streams</code></td>
+<td>array</td>
+<td>Array of stream info objects</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3><code>GET /api/v1/progress/:file_uuid</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Get real-time processing progress for a file via Redis pub/sub. Includes per-processor status, current/total frames, ETA, and system resource stats.</p>
+<h4>Pipeline Order</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Order</th>
+<th>Processor</th>
+<th>Dependencies</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>1</td>
+<td><code>cut</code></td>
+<td>—</td>
+<td>Scene detection</td>
+</tr>
+<tr>
+<td>2</td>
+<td><code>asr</code></td>
+<td>cut</td>
+<td>Speech-to-text (per scene)</td>
+</tr>
+<tr>
+<td>3</td>
+<td><code>asrx</code></td>
+<td>asr</td>
+<td>Speaker diarization</td>
+</tr>
+<tr>
+<td>4</td>
+<td><code>yolo</code></td>
+<td>—</td>
+<td>Object detection</td>
+</tr>
+<tr>
+<td>5</td>
+<td><code>ocr</code></td>
+<td>—</td>
+<td>Text recognition</td>
+</tr>
+<tr>
+<td>6</td>
+<td><code>face</code></td>
+<td>—</td>
+<td>Face detection &amp; embedding</td>
+</tr>
+<tr>
+<td>7</td>
+<td><code>pose</code></td>
+<td>—</td>
+<td>Pose estimation</td>
+</tr>
+<tr>
+<td>8</td>
+<td><code>visual_chunk</code></td>
+<td>yolo</td>
+<td>Visual scene chunks</td>
+</tr>
+<tr>
+<td>9</td>
+<td><code>story</code></td>
+<td>asr, asrx, cut, yolo, face</td>
+<td>Scene summaries (template)</td>
+</tr>
+<tr>
+<td>10</td>
+<td><code>5w1h</code></td>
+<td>story</td>
+<td>5W1H analysis (Gemma4 LLM)</td>
+</tr>
+</tbody>
+</table>
+<p>All processors except <code>story</code> and <code>5w1h</code> run concurrently when their dependencies are met. Story and 5W1H run sequentially after their prerequisites.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/progress/</span><span class="nv">$FILE_UUID</span><span class="s2">&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;{overall_progress, processors: [.processors[] | {processor_type, status}]}&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;file_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;3a6c1865...&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;overall_progress&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">71</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;cpu_percent&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">45.2</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;gpu_percent&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">30.1</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;memory_percent&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">62.4</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;processors&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nt">&quot;processor_type&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;asr&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;complete&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;progress&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">100</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nt">&quot;processor_type&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;yolo&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;running&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;progress&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">65</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nt">&quot;processor_type&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;face&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;pending&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;progress&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">0</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>32-char hex UUID</td>
+</tr>
+<tr>
+<td><code>overall_progress</code></td>
+<td>integer</td>
+<td>Overall progress percentage (0–100)</td>
+</tr>
+<tr>
+<td><code>processors</code></td>
+<td>array</td>
+<td>Per-processor status list</td>
+</tr>
+<tr>
+<td><code>processors[].processor_type</code></td>
+<td>string</td>
+<td>Processor name (<code>asr</code>, <code>cut</code>, <code>yolo</code>, etc.)</td>
+</tr>
+<tr>
+<td><code>processors[].status</code></td>
+<td>string</td>
+<td><code>"pending"</code>, <code>"running"</code>, <code>"complete"</code>, or <code>"failed"</code></td>
+</tr>
+<tr>
+<td><code>processors[].progress</code></td>
+<td>integer</td>
+<td>Per-processor progress (0–100)</td>
+</tr>
+<tr>
+<td><code>processors[].eta_seconds</code></td>
+<td>integer</td>
+<td>Estimated seconds remaining (running processors)</td>
+</tr>
+<tr>
+<td><code>processors[].current</code></td>
+<td>integer</td>
+<td>Current frame count</td>
+</tr>
+<tr>
+<td><code>processors[].total</code></td>
+<td>integer</td>
+<td>Total frame count</td>
+</tr>
+<tr>
+<td><code>cpu_percent</code></td>
+<td>float</td>
+<td>Current CPU usage</td>
+</tr>
+<tr>
+<td><code>gpu_percent</code></td>
+<td>float</td>
+<td>Current GPU utilization</td>
+</tr>
+<tr>
+<td><code>memory_percent</code></td>
+<td>float</td>
+<td>Current memory usage</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3><code>GET /api/v1/jobs</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: system-level</p>
+<p>List all processing jobs (monitor jobs) in the system. Shows job status, which file each job is processing, and current processor info.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/jobs&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;{count, jobs: [.jobs[] | {uuid, status}]}&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;jobs&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
+<span class="w">      </span><span class="nt">&quot;id&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">42</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;3a6c1865...&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;running&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;current_processor&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;yolo&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;created_at&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;2026-05-16T12:00:00Z&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;started_at&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;2026-05-16T12:01:00Z&quot;</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="nt">&quot;count&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">15</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;page&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">1</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;page_size&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">20</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>jobs</code></td>
+<td>array</td>
+<td>Array of job info objects</td>
+</tr>
+<tr>
+<td><code>jobs[].id</code></td>
+<td>integer</td>
+<td>Job ID</td>
+</tr>
+<tr>
+<td><code>jobs[].uuid</code></td>
+<td>string</td>
+<td>File UUID being processed</td>
+</tr>
+<tr>
+<td><code>jobs[].status</code></td>
+<td>string</td>
+<td><code>"pending"</code>, <code>"running"</code>, <code>"completed"</code>, <code>"failed"</code></td>
+</tr>
+<tr>
+<td><code>jobs[].current_processor</code></td>
+<td>string</td>
+<td>Currently active processor, or null</td>
+</tr>
+<tr>
+<td><code>count</code></td>
+<td>integer</td>
+<td>Total job count</td>
+</tr>
+<tr>
+<td><code>page</code></td>
+<td>integer</td>
+<td>Current page number</td>
+</tr>
+<tr>
+<td><code>page_size</code></td>
+<td>integer</td>
+<td>Jobs per page</td>
+</tr>
+</tbody>
+</table>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/06_search.html

@@ -0,0 +1,280 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>06 Search - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 24px; margin: 24px 0 12px; }
+h2 { font-size: 20px; margin: 20px 0 10px; color: #222; }
+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<!-- module: search -->
+<!-- description: Vector search, BM25, smart search, universal search, visual search -->
+<!-- depends: 01_auth -->
+
+<h2>Search APIs</h2>
+<h3><code>POST /api/v1/search/smart</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Semantic vector search using EmbeddingGemma-300m. Generates a query embedding via EmbeddingGemma (port 11436), then searches pgvector <code>story_parent</code> and <code>llm_parent</code> chunks by cosine similarity.</p>
+<h4>Request Parameters</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Default</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>Yes</td>
+<td>—</td>
+<td>File UUID to search within</td>
+</tr>
+<tr>
+<td><code>query</code></td>
+<td>string</td>
+<td>Yes</td>
+<td>—</td>
+<td>Search text</td>
+</tr>
+<tr>
+<td><code>limit</code></td>
+<td>integer</td>
+<td>No</td>
+<td>5</td>
+<td>Max results to return</td>
+</tr>
+<tr>
+<td><code>page</code></td>
+<td>integer</td>
+<td>No</td>
+<td>1</td>
+<td>Page number</td>
+</tr>
+<tr>
+<td><code>page_size</code></td>
+<td>integer</td>
+<td>No</td>
+<td>5</td>
+<td>Items per page</td>
+</tr>
+</tbody>
+</table>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/search/smart&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Authorization: Bearer </span><span class="nv">$JWT</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;file_uuid&quot;: &quot;&#39;</span><span class="s2">&quot;</span><span class="nv">$FILE_UUID</span><span class="s2">&quot;</span><span class="s1">&#39;&quot;, &quot;query&quot;: &quot;Audrey Hepburn&quot;}&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;query&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Audrey Hepburn&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;results&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
+<span class="w">      </span><span class="nt">&quot;parent_id&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">1087822</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;scene_order&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">1087822</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;start_frame&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">104438</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;end_frame&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">104538</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;fps&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">24.0</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;start_time&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">4351.6</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;end_time&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">4355.76</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;summary&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;[4352s-4356s, 4s] Cast: Audrey Hepburn. Total: 2 lines, 10 words. Speakers: Audrey Hepburn (2 lines)&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;similarity&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">0.67</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="nt">&quot;page&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">1</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;page_size&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">5</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;strategy&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;semantic_vector_search&quot;</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<hr />
+<h3><code>POST /api/v1/search/universal</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Multi-type BM25 full-text search across chunks, frames, and persons. Uses PostgreSQL <code>tsvector</code>.</p>
+<h4>Request Parameters</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Default</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>query</code></td>
+<td>string</td>
+<td>Yes</td>
+<td>—</td>
+<td>Search text</td>
+</tr>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>No</td>
+<td>—</td>
+<td>Restrict to specific file</td>
+</tr>
+<tr>
+<td><code>types</code></td>
+<td>string[]</td>
+<td>No</td>
+<td><code>["chunk","frame","person"]</code></td>
+<td>Search types</td>
+</tr>
+<tr>
+<td><code>limit</code></td>
+<td>integer</td>
+<td>No</td>
+<td>10</td>
+<td>Max results per type</td>
+</tr>
+<tr>
+<td><code>page</code></td>
+<td>integer</td>
+<td>No</td>
+<td>1</td>
+<td>Page number</td>
+</tr>
+<tr>
+<td><code>page_size</code></td>
+<td>integer</td>
+<td>No</td>
+<td>20</td>
+<td>Items per page</td>
+</tr>
+</tbody>
+</table>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/search/universal&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Authorization: Bearer </span><span class="nv">$JWT</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;file_uuid&quot;: &quot;&#39;</span><span class="s2">&quot;</span><span class="nv">$FILE_UUID</span><span class="s2">&quot;</span><span class="s1">&#39;&quot;, &quot;query&quot;: &quot;Cary Grant&quot;}&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;results&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
+<span class="w">      </span><span class="nt">&quot;type&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;chunk&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;chunk_id&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;bd80fec92b0b6963d177a2c55bf713e2_2&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;chunk_type&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;story_child&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;start_frame&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">5103</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;end_frame&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">5127</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;start_time&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">212.64</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;end_time&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">213.64</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;text&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;[213s-214s] Cary Grant: \&quot;Olá!\&quot;&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;score&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">0.9</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="nt">&quot;total&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">20</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;took_ms&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">18</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<hr />
+<h3><code>POST /api/v1/search/frames</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Search face detection frames by identity name or trace ID.</p>
+<hr />
+<h3><code>POST /api/v1/search/identity_text</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Search text chunks spoken by a specific identity.</p>
+<hr />
+<h3>Visual Search</h3>
+<table class="table">
+<thead>
+<tr>
+<th>Method</th>
+<th>Endpoint</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>POST</td>
+<td><code>/api/v1/search/visual</code></td>
+<td>Search visual chunks</td>
+</tr>
+<tr>
+<td>POST</td>
+<td><code>/api/v1/search/visual/class</code></td>
+<td>Search by object class</td>
+</tr>
+<tr>
+<td>POST</td>
+<td><code>/api/v1/search/visual/density</code></td>
+<td>Search by object density</td>
+</tr>
+<tr>
+<td>POST</td>
+<td><code>/api/v1/search/visual/combination</code></td>
+<td>Search by object combination</td>
+</tr>
+<tr>
+<td>POST</td>
+<td><code>/api/v1/search/visual/stats</code></td>
+<td>Visual chunk statistics</td>
+</tr>
+</tbody>
+</table>
+<h4>Embedding Model</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Detail</th>
+<th>Value</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><strong>Model</strong></td>
+<td>EmbeddingGemma-300m</td>
+</tr>
+<tr>
+<td><strong>Endpoint</strong></td>
+<td><code>POST /api/v1/embeddings</code> on port 11436</td>
+</tr>
+<tr>
+<td><strong>Dimension</strong></td>
+<td>768</td>
+</tr>
+<tr>
+<td><strong>Storage</strong></td>
+<td>pgvector (<code>chunk.embedding</code> column)</td>
+</tr>
+</tbody>
+</table>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/07_identity.html

@@ -0,0 +1,510 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>07 Identity - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 24px; margin: 24px 0 12px; }
+h2 { font-size: 20px; margin: 20px 0 10px; color: #222; }
+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<!-- module: identity -->
+<!-- description: Global identities — CRUD, detail, files, faces, bind, unbind, search -->
+<!-- depends: 01_auth -->
+
+<h2>Global Identities</h2>
+<h3><code>GET /api/v1/identities</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: identity-level</p>
+<p>List all registered identities with pagination.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/identities?page=1&amp;page_size=20&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;{count, identities: [.identities[] | {name}]}&#39;</span>
+</code></pre></div>
+
+<hr />
+<h3><code>GET /api/v1/identity/:identity_uuid</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: identity-level</p>
+<p>Get detailed information for a specific identity, including metadata and TMDb references.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/identity/</span><span class="nv">$IDENTITY_UUID</span><span class="s2">&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;identity_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;a9a901056d6b46ff92da0c3c1a57dff4&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Cary Grant&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;identity_type&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;people&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;source&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;tmdb&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;confirmed&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;tmdb_id&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">112</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;tmdb_profile&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;{output}/identities/{identity_uuid}/profile.jpg&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;metadata&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{},</span>
+<span class="w">  </span><span class="nt">&quot;reference_data&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{},</span>
+<span class="w">  </span><span class="nt">&quot;created_at&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;2026-05-16T12:00:00Z&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;updated_at&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">null</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>identity_uuid</code></td>
+<td>string</td>
+<td>Identity identifier</td>
+</tr>
+<tr>
+<td><code>name</code></td>
+<td>string</td>
+<td>Identity name</td>
+</tr>
+<tr>
+<td><code>identity_type</code></td>
+<td>string</td>
+<td><code>"people"</code> or null</td>
+</tr>
+<tr>
+<td><code>source</code></td>
+<td>string</td>
+<td><code>.json</code>, <code>auto</code>, <code>tmdb</code>, <code>user_defined</code>, or <code>merged</code></td>
+</tr>
+<tr>
+<td><code>status</code></td>
+<td>string</td>
+<td><code>"confirmed"</code>, <code>"pending"</code>, or <code>"inactive"</code></td>
+</tr>
+<tr>
+<td><code>tmdb_id</code></td>
+<td>integer</td>
+<td>TMDb person ID (only if source = tmdb)</td>
+</tr>
+<tr>
+<td><code>tmdb_profile</code></td>
+<td>string</td>
+<td>Local profile image path (<code>{output}/identities/{uuid}/profile.jpg</code>)</td>
+</tr>
+<tr>
+<td><code>metadata</code></td>
+<td>object</td>
+<td>Metadata JSON (tmdb_character, cast_order, etc.)</td>
+</tr>
+<tr>
+<td><code>created_at</code></td>
+<td>string</td>
+<td>Creation timestamp</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3><code>DELETE /api/v1/identity/:identity_uuid</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: identity-level</p>
+<p>Delete an identity permanently.</p>
+<hr />
+<h3><code>GET /api/v1/identity/:identity_uuid/files</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: identity-level</p>
+<p>Get all files where this identity appears. Returns per-file summary including face count, confidence, and appearance time range.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/identity/</span><span class="nv">$IDENTITY_UUID</span><span class="s2">/files&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span>
+</code></pre></div>
+
+<hr />
+<h3><code>GET /api/v1/identity/:identity_uuid/faces</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: identity-level</p>
+<p>Get all face detection records associated with this identity.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/identity/</span><span class="nv">$IDENTITY_UUID</span><span class="s2">/faces&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>File where face was detected</td>
+</tr>
+<tr>
+<td><code>frame_number</code></td>
+<td>integer</td>
+<td>Frame number of detection</td>
+</tr>
+<tr>
+<td><code>face_id</code></td>
+<td>string</td>
+<td>Face ID (format: <code>face_{frame_number}</code>)</td>
+</tr>
+<tr>
+<td><code>confidence</code></td>
+<td>float</td>
+<td>Detection confidence</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3><code>GET /api/v1/identity/:identity_uuid/chunks</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: identity-level</p>
+<p>Get all text chunks (sentences) spoken while this identity's face was on screen. Useful for finding what a person said.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/identity/</span><span class="nv">$IDENTITY_UUID</span><span class="s2">/chunks&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;identity_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;a9a901056d6b46ff92da0c3c1a57dff4&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;data&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
+<span class="w">      </span><span class="nt">&quot;id&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">0</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;file_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;bd80fec92b0b6963d177a2c55bf713e2&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;chunk_id&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;bd80fec92b0b6963d177a2c55bf713e2_2&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;chunk_type&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;sentence&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;start_frame&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">5103</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;end_frame&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">5127</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;fps&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">24.0</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;start_time&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">212.64</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;end_time&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">213.64</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;text_content&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;[213s-214s] Cary Grant: \&quot;Olá!\&quot;&quot;</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>File identifier</td>
+</tr>
+<tr>
+<td><code>chunk_id</code></td>
+<td>string</td>
+<td>Sentence chunk identifier</td>
+</tr>
+<tr>
+<td><code>start_frame</code></td>
+<td>integer</td>
+<td>Frame-accurate start position</td>
+</tr>
+<tr>
+<td><code>end_frame</code></td>
+<td>integer</td>
+<td>Frame-accurate end position</td>
+</tr>
+<tr>
+<td><code>fps</code></td>
+<td>float</td>
+<td>Frames per second</td>
+</tr>
+<tr>
+<td><code>start_time</code></td>
+<td>float</td>
+<td>Start time in seconds</td>
+</tr>
+<tr>
+<td><code>end_time</code></td>
+<td>float</td>
+<td>End time in seconds</td>
+</tr>
+<tr>
+<td><code>text_content</code></td>
+<td>string</td>
+<td>Spoken text content</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3><code>POST /api/v1/identity/:identity_uuid/bind</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: identity-level</p>
+<p>Bind a face detection to an identity. Associates the face trace with the identity for future search and recognition.</p>
+<h4>Request Parameters</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>Yes</td>
+<td>File where face is detected</td>
+</tr>
+<tr>
+<td><code>face_id</code></td>
+<td>string</td>
+<td>Yes</td>
+<td>Face ID (format: <code>{frame}_{idx}</code>)</td>
+</tr>
+</tbody>
+</table>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/identity/</span><span class="nv">$IDENTITY_UUID</span><span class="s2">/bind&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;file_uuid&quot;: &quot;&#39;</span><span class="s2">&quot;</span><span class="nv">$FILE_UUID</span><span class="s2">&quot;</span><span class="s1">&#39;&quot;, &quot;face_id&quot;: &quot;1_5&quot;}&#39;</span>
+</code></pre></div>
+
+<hr />
+<h3><code>POST /api/v1/identity/:identity_uuid/unbind</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: identity-level</p>
+<p>Unbind a face detection from an identity. Removes the identity association from the face record.</p>
+<hr />
+<h3><code>GET /api/v1/identities/search</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: identity-level</p>
+<p>Search identities by name (ILIKE search). Returns matching identity records.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/identities/search?q=Cary&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>name</code></td>
+<td>string</td>
+<td>Identity name</td>
+</tr>
+<tr>
+<td><code>source</code></td>
+<td>string</td>
+<td>Identity source</td>
+</tr>
+<tr>
+<td><code>tmdb_id</code></td>
+<td>integer</td>
+<td>TMDb ID (if source = tmdb)</td>
+</tr>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>Associated file</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<hr />
+<h3><code>POST /api/v1/identity/upload</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: identity-level</p>
+<p>Upload an identity.json file to create or update an identity. Accepts the same format as the identity.json files stored on disk.</p>
+<p>If an identity with the same <code>name</code> already exists, it will be updated with the new values.</p>
+<h4>Request</h4>
+<p>The request body is an <code>IdentityFile</code> object:</p>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>identity_uuid</code></td>
+<td>string</td>
+<td>Yes</td>
+<td>Identity identifier</td>
+</tr>
+<tr>
+<td><code>name</code></td>
+<td>string</td>
+<td>Yes</td>
+<td>Identity display name</td>
+</tr>
+<tr>
+<td><code>identity_type</code></td>
+<td>string</td>
+<td>No</td>
+<td><code>"people"</code> or null</td>
+</tr>
+<tr>
+<td><code>source</code></td>
+<td>string</td>
+<td>No</td>
+<td><code>.json</code>, <code>auto</code>, <code>tmdb</code>, <code>user_defined</code>, or <code>merged</code></td>
+</tr>
+<tr>
+<td><code>status</code></td>
+<td>string</td>
+<td>No</td>
+<td><code>"confirmed"</code>, <code>"pending"</code>, or <code>"inactive"</code></td>
+</tr>
+<tr>
+<td><code>tmdb_id</code></td>
+<td>integer</td>
+<td>No</td>
+<td>TMDb person ID</td>
+</tr>
+<tr>
+<td><code>tmdb_profile</code></td>
+<td>string</td>
+<td>No</td>
+<td>TMDb profile image URL</td>
+</tr>
+<tr>
+<td><code>metadata</code></td>
+<td>object</td>
+<td>No</td>
+<td>Arbitrary metadata JSON</td>
+</tr>
+<tr>
+<td><code>file_bindings</code></td>
+<td>array</td>
+<td>No</td>
+<td>Array of <code>{ file_uuid, trace_ids, face_count }</code> (informational)</td>
+</tr>
+</tbody>
+</table>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/identity/upload&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{</span>
+<span class="s1">    &quot;version&quot;: 1,</span>
+<span class="s1">    &quot;identity_uuid&quot;: &quot;a9a901056d6b46ff92da0c3c1a57dff4&quot;,</span>
+<span class="s1">    &quot;name&quot;: &quot;Cary Grant&quot;,</span>
+<span class="s1">    &quot;identity_type&quot;: &quot;people&quot;,</span>
+<span class="s1">    &quot;source&quot;: &quot;.json&quot;,</span>
+<span class="s1">    &quot;status&quot;: &quot;confirmed&quot;,</span>
+<span class="s1">    &quot;metadata&quot;: {},</span>
+<span class="s1">    &quot;file_bindings&quot;: []</span>
+<span class="s1">  }&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;identity_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;a9a901056d6b46ff92da0c3c1a57dff4&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Cary Grant&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;message&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Identity uploaded successfully&quot;</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<hr />
+<hr />
+<h3><code>POST /api/v1/identity/:identity_uuid/profile-image</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: identity-level</p>
+<p>Upload a profile image (JPEG or PNG) for an identity. The image is saved to <code>{output}/identities/{uuid}/profile.{ext}</code>.</p>
+<p>Uses <code>multipart/form-data</code> with field name <code>image</code>.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/identity/</span><span class="nv">$IDENTITY_UUID</span><span class="s2">/profile-image&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-F<span class="w"> </span><span class="s2">&quot;image=@/path/to/photo.jpg&quot;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;identity_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;a9a901056d6b46ff92da0c3c1a57dff4&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;path&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;/path/to/output/identities/.../profile.jpg&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;message&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Profile image saved: profile.jpg&quot;</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<h4>Error Responses</h4>
+<table class="table">
+<thead>
+<tr>
+<th>HTTP</th>
+<th>When</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>400</code></td>
+<td>Missing image field or unsupported format</td>
+</tr>
+<tr>
+<td><code>404</code></td>
+<td>Identity not found</td>
+</tr>
+<tr>
+<td><code>415</code></td>
+<td>Unsupported image type (use JPEG or PNG)</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3><code>GET /api/v1/identity/:identity_uuid/profile-image</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: identity-level</p>
+<p>Retrieve the profile image for an identity. Returns the raw image data with appropriate Content-Type header.</p>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/identity/</span><span class="nv">$IDENTITY_UUID</span><span class="s2">/profile-image&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span>-o<span class="w"> </span>profile.jpg
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Response Header</th>
+<th>Value</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>content-type</code></td>
+<td><code>image/jpeg</code> or <code>image/png</code></td>
+</tr>
+</tbody>
+</table>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/08_identity_agent.html

@@ -0,0 +1,97 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>08 Identity Agent - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 24px; margin: 24px 0 12px; }
+h2 { font-size: 20px; margin: 20px 0 10px; color: #222; }
+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<!-- module: identity_agent -->
+<!-- description: Identity agent — match from photo, match from trace -->
+<!-- depends: 01_auth, 07_identity -->
+
+<h2>Identity Agent</h2>
+<h3><code>POST /api/v1/agents/identity/match-from-photo</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Upload a face photo to match against known identities. Detects face via InsightFace, extracts 512D embedding via CoreML FaceNet, then searches pgvector for the closest identity.</p>
+<h4>Request</h4>
+<p><code>multipart/form-data</code> with field <code>image</code> (JPEG/PNG) and optional <code>file_uuid</code>.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/agents/identity/match-from-photo&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Authorization: Bearer </span><span class="nv">$JWT</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-F<span class="w"> </span><span class="s2">&quot;image=@/path/to/face.jpg&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-F<span class="w"> </span><span class="s2">&quot;file_uuid=</span><span class="nv">$FILE_UUID</span><span class="s2">&quot;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;matches&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
+<span class="w">      </span><span class="nt">&quot;identity_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;a9a90105...&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Cary Grant&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nt">&quot;similarity&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">0.87</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<hr />
+<h3><code>POST /api/v1/agents/identity/match-from-trace</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Match a face trace (tracked face across frames) against known identities. Samples 3 angles from the trace, generates embeddings, and searches pgvector.</p>
+<h4>Request Parameters</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>Yes</td>
+<td>File containing the trace</td>
+</tr>
+<tr>
+<td><code>trace_id</code></td>
+<td>integer</td>
+<td>Yes</td>
+<td>Face trace ID to match</td>
+</tr>
+</tbody>
+</table>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/agents/identity/match-from-trace&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Authorization: Bearer </span><span class="nv">$JWT</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;file_uuid&quot;: &quot;&#39;</span><span class="s2">&quot;</span><span class="nv">$FILE_UUID</span><span class="s2">&quot;</span><span class="s1">&#39;&quot;, &quot;trace_id&quot;: 10}&#39;</span>
+</code></pre></div>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/08_media.html

@@ -0,0 +1,303 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>08 Media - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 24px; margin: 24px 0 12px; }
+h2 { font-size: 20px; margin: 20px 0 10px; color: #222; }
+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<!-- module: media -->
+<!-- description: Video streaming & frame extraction -->
+<!-- depends: 01_auth -->
+
+<h2>Video Streaming &amp; Frame Extraction</h2>
+<p>All video streaming endpoints support the following common query parameters:</p>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Default</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>mode</code></td>
+<td>string</td>
+<td>No</td>
+<td><code>normal</code></td>
+<td><code>normal</code> or <code>debug</code> (draws detection overlays)</td>
+</tr>
+<tr>
+<td><code>audio</code></td>
+<td>string</td>
+<td>No</td>
+<td><code>on</code></td>
+<td><code>on</code> or <code>off</code></td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h3><code>GET /api/v1/file/:file_uuid/video</code></h3>
+<p>Stream the full video file with range support for seeking.</p>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<h4>Response</h4>
+<ul>
+<li><strong>200</strong>: Video stream (<code>Content-Type</code> based on file extension)</li>
+<li><strong>206</strong>: Partial content (range request)</li>
+<li>Supports <code>Range</code> header for seeking</li>
+</ul>
+<hr />
+<h3><code>GET /api/v1/file/:file_uuid/trace/:trace_id/video</code></h3>
+<p>Stream video with highlights for a specific face trace (follows a single person across frames with bounding box overlay).</p>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<hr />
+<h3><code>GET /api/v1/file/:file_uuid/video/bbox</code></h3>
+<p>Stream video with bounding box overlay for all detected objects/faces.</p>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Uses a built-in 5×7 bitmap font renderer to draw labels directly on video frames via FFmpeg <code>drawtext</code> filter.</p>
+<hr />
+<h3><code>GET /api/v1/file/:file_uuid/thumbnail</code></h3>
+<p>Extract a single frame from a video as JPEG image. Uses FFmpeg <code>select</code> filter.</p>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<h4>Query Parameters</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Default</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>frame</code></td>
+<td>integer</td>
+<td>Yes</td>
+<td>—</td>
+<td>Zero-based frame number to extract</td>
+</tr>
+<tr>
+<td><code>x</code></td>
+<td>integer</td>
+<td>No</td>
+<td>—</td>
+<td>Crop start X (left edge). Requires <code>y</code>, <code>w</code>, <code>h</code>.</td>
+</tr>
+<tr>
+<td><code>y</code></td>
+<td>integer</td>
+<td>No</td>
+<td>—</td>
+<td>Crop start Y (top edge). Requires <code>x</code>, <code>w</code>, <code>h</code>.</td>
+</tr>
+<tr>
+<td><code>w</code></td>
+<td>integer</td>
+<td>No</td>
+<td>—</td>
+<td>Crop width in pixels. Requires <code>x</code>, <code>y</code>, <code>h</code>.</td>
+</tr>
+<tr>
+<td><code>h</code></td>
+<td>integer</td>
+<td>No</td>
+<td>—</td>
+<td>Crop height in pixels. Requires <code>x</code>, <code>y</code>, <code>w</code>.</td>
+</tr>
+</tbody>
+</table>
+<p>All four crop params (<code>x</code>, <code>y</code>, <code>w</code>, <code>h</code>) must be provided together or omitted.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code><span class="c1"># Extract frame 1000 (full frame)</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/file/bd80fec92b0b6963d177a2c55bf713e2/thumbnail?frame=1000&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Authorization: Bearer </span><span class="nv">$JWT</span><span class="s2">&quot;</span><span class="w"> </span>-o<span class="w"> </span>frame_1000.jpg
+
+<span class="c1"># Extract and crop face region (x=320, y=240, w=160, h=160)</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/file/bd80fec92b0b6963d177a2c55bf713e2/thumbnail?frame=1000&amp;x=320&amp;y=240&amp;w=160&amp;h=160&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Authorization: Bearer </span><span class="nv">$JWT</span><span class="s2">&quot;</span><span class="w"> </span>-o<span class="w"> </span>face_crop.jpg
+</code></pre></div>
+
+<h4>Response</h4>
+<ul>
+<li><strong>200</strong>: <code>image/jpeg</code> binary data</li>
+<li><strong>404</strong>: File not found</li>
+<li><strong>500</strong>: FFmpeg error (e.g., frame number exceeds video duration)</li>
+</ul>
+<h3><code>GET /api/v1/file/:file_uuid/clip</code></h3>
+<p>Extract a video clip (time range) as MPEG-TS stream. Uses FFmpeg <code>-ss</code> fast seek.</p>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<h4>Query Parameters</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Default</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>start_frame</code></td>
+<td>integer</td>
+<td>No*</td>
+<td>—</td>
+<td>Start frame (zero-based). <strong>Frame-accurate</strong> — use this for precision.</td>
+</tr>
+<tr>
+<td><code>end_frame</code></td>
+<td>integer</td>
+<td>No*</td>
+<td>—</td>
+<td>End frame (zero-based, inclusive). Requires <code>start_frame</code>.</td>
+</tr>
+<tr>
+<td><code>start_time</code></td>
+<td>float</td>
+<td>No*</td>
+<td>—</td>
+<td>Start time in seconds. Approximate (FPS-dependent). Fallback if frames not given.</td>
+</tr>
+<tr>
+<td><code>end_time</code></td>
+<td>float</td>
+<td>No*</td>
+<td>—</td>
+<td>End time in seconds. Approximate (FPS-dependent). Fallback if frames not given.</td>
+</tr>
+<tr>
+<td><code>fps</code></td>
+<td>float</td>
+<td>No</td>
+<td>video FPS</td>
+<td>Override frames-per-second for frame↔time calculation. Defaults to video's detected FPS.</td>
+</tr>
+<tr>
+<td><code>mode</code></td>
+<td>string</td>
+<td>No</td>
+<td><code>normal</code></td>
+<td><code>normal</code> or <code>debug</code> (draws "CLIP" overlay)</td>
+</tr>
+<tr>
+<td><code>audio</code></td>
+<td>string</td>
+<td>No</td>
+<td><code>on</code></td>
+<td><code>on</code> or <code>off</code></td>
+</tr>
+</tbody>
+</table>
+<p>Either (<code>start_frame</code>+<code>end_frame</code>) OR (<code>start_time</code>+<code>end_time</code>) must be provided.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code><span class="c1"># Clip by frame range (primary)</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/file/bd80fec92b0b6963d177a2c55bf713e2/clip?start_frame=0&amp;end_frame=47&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Authorization: Bearer </span><span class="nv">$JWT</span><span class="s2">&quot;</span><span class="w"> </span>-o<span class="w"> </span>clip.ts
+
+<span class="c1"># Clip by time range (fallback)</span>
+curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/file/bd80fec92b0b6963d177a2c55bf713e2/clip?start_time=30&amp;end_time=45&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Authorization: Bearer </span><span class="nv">$JWT</span><span class="s2">&quot;</span><span class="w"> </span>-o<span class="w"> </span>clip.ts
+</code></pre></div>
+
+<h4>Response</h4>
+<ul>
+<li><strong>200</strong>: <code>video/mp2t</code> MPEG-TS stream</li>
+<li><strong>400</strong>: Missing/invalid range parameters</li>
+<li><strong>404</strong>: File not found</li>
+<li><strong>500</strong>: FFmpeg error</li>
+</ul>
+<h4>Technical Notes</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Detail</th>
+<th>Value</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><strong>Backend</strong></td>
+<td>FFmpeg (<code>ffmpeg-full</code>)</td>
+</tr>
+<tr>
+<td><strong>Seek</strong></td>
+<td><code>-ss</code> before <code>-i</code> (fast keyframe seek)</td>
+</tr>
+<tr>
+<td><strong>Format</strong></td>
+<td>MPEG-TS (<code>mpegts</code> muxer, pipe-safe)</td>
+</tr>
+<tr>
+<td><strong>Codec</strong></td>
+<td>H.264 + AAC</td>
+</tr>
+<tr>
+<td><strong>Cache</strong></td>
+<td><code>Cache-Control: public, max-age=86400</code> (24h)</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<table class="table">
+<thead>
+<tr>
+<th>Detail</th>
+<th>Value</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><strong>Backend</strong></td>
+<td>FFmpeg (<code>ffmpeg-full</code>)</td>
+</tr>
+<tr>
+<td><strong>Filter</strong></td>
+<td><code>select=eq(n\,FRAME)</code> to select frame, optional <code>crop=W:H:X:Y</code></td>
+</tr>
+<tr>
+<td><strong>Output</strong></td>
+<td>Single JPEG via pipe (<code>image2pipe</code>, <code>mjpeg</code> codec)</td>
+</tr>
+<tr>
+<td><strong>Cache</strong></td>
+<td><code>Cache-Control: public, max-age=86400</code> (24h)</td>
+</tr>
+<tr>
+<td><strong>Frame number</strong></td>
+<td>Zero-based (<code>frame=0</code> = first frame of video)</td>
+</tr>
+</tbody>
+</table>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/09_tmdb.html

@@ -0,0 +1,123 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>09 Tmdb - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 24px; margin: 24px 0 12px; }
+h2 { font-size: 20px; margin: 20px 0 10px; color: #222; }
+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<!-- module: tmdb -->
+<!-- description: TMDb enrichment endpoints — prefetch, probe, resource, check -->
+<!-- depends: 01_auth, 03_register -->
+
+<h2>TMDb Enrichment</h2>
+<blockquote>
+<p><strong>Offline operation</strong>: TMDb prefetch now checks local identity files first (<code>identities/_index.json</code> + <code>*.tmdb.json</code>).
+If local files exist, no external API call is made. Internet is only needed for initial data seeding.</p>
+</blockquote>
+<h3>Overview</h3>
+<p>TMDb enrichment is an optional identity enrichment step that can be run after Pipeline face detection completes. The workflow is:</p>
+<ol>
+<li><strong>Prefetch</strong> (requires internet): Download movie cast data from TMDb API → cache to <code>{file_uuid}.tmdb.json</code></li>
+<li><strong>Probe</strong>: Read local cache → create identities for <strong>all</strong> cast members (<code>source='tmdb'</code>) + save <code>identity.json</code> + download profile image to <code>{OUTPUT}/identities/{uuid}/profile.jpg</code></li>
+<li><strong>Match</strong>: The worker automatically matches video faces against TMDb identities when <code>MOMENTRY_TMDB_PROBE_ENABLED=true</code></li>
+</ol>
+<h3><code>POST /api/v1/agents/tmdb/prefetch</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Fetch TMDb cast data for a registered file and cache it locally. This is the only step requiring internet access.</p>
+<h4>Request Parameters</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>file_uuid</code></td>
+<td>string</td>
+<td>Yes</td>
+<td>File UUID to enrich</td>
+</tr>
+</tbody>
+</table>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/agents/tmdb/prefetch&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;file_uuid&quot;: &quot;&#39;</span><span class="s2">&quot;</span><span class="nv">$FILE_UUID</span><span class="s2">&quot;</span><span class="s1">&#39;&quot;}&#39;</span>
+</code></pre></div>
+
+<h4>Response (200)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;file_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;...&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;cache_path&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;/output/...tmdb.json&quot;</span><span class="p">}</span>
+</code></pre></div>
+
+<h3><code>POST /api/v1/file/:file_uuid/tmdb-probe</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: file-level</p>
+<p>Read local TMDb cache and create/update identities. Requires prefetch to have been run first.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/file/</span><span class="nv">$FILE_UUID</span><span class="s2">/tmdb-probe&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;{identities_created, movie_title}&#39;</span>
+</code></pre></div>
+
+<h4>Response (200 — identities created)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;identities_created&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">15</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;movie_title&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Charade&quot;</span><span class="p">}</span>
+</code></pre></div>
+
+<h4>Response (200 — no cache)</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;message&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;No TMDb cache found. Run tmdb-prefetch first.&quot;</span><span class="p">}</span>
+</code></pre></div>
+
+<h3><code>GET /api/v1/resource/tmdb</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: system-level</p>
+<p>View TMDb resource status including configuration, identity counts, and cache file count.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/resource/tmdb&quot;</span><span class="w"> </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;{identities_seeded, cache_files}&#39;</span>
+</code></pre></div>
+
+<h3><code>POST /api/v1/resource/tmdb/check</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: system-level</p>
+<p>Ping the TMDb API to verify connectivity and measure latency.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/resource/tmdb/check&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;.status&#39;</span>
+</code></pre></div>
+
+<h4>Response</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;api_key_configured&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;enabled&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;api_reachable&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;api_latency_ms&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">120</span>
+<span class="p">}</span>
+</code></pre></div>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/10_pipeline.html

@@ -0,0 +1,364 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>10 Pipeline - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 24px; margin: 24px 0 12px; }
+h2 { font-size: 20px; margin: 20px 0 10px; color: #222; }
+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<!-- module: pipeline -->
+<!-- description: Pipeline processors, ingestion status, stats endpoints -->
+<!-- depends: 01_auth -->
+
+<h2>Pipeline</h2>
+<h3>Dependency Graph</h3>
+<div class="codehilite"><pre><span></span><code><span class="n">flowchart</span><span class="w"> </span><span class="n">TB</span>
+<span class="w">    </span><span class="n">subgraph</span><span class="w"> </span><span class="n">Processors</span><span class="p">[</span><span class="s">&quot;10 Processors&quot;</span><span class="p">]</span>
+<span class="w">        </span><span class="n">Cut</span><span class="p">[</span><span class="n">Cut</span><span class="p">]</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">ASR</span><span class="p">[</span><span class="n">ASR</span><span class="p">]</span>
+<span class="w">        </span><span class="n">ASR</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">ASRX</span><span class="p">[</span><span class="n">ASRX</span><span class="p">]</span>
+<span class="w">        </span><span class="n">ASRX</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Story</span><span class="p">[</span><span class="n">Story</span><span class="p">]</span>
+<span class="w">        </span><span class="n">Cut</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Story</span>
+<span class="w">        </span><span class="n">YOLO</span><span class="p">[</span><span class="n">YOLO</span><span class="p">]</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">VisualChunk</span><span class="p">[</span><span class="n">VisualChunk</span><span class="p">]</span>
+<span class="w">        </span><span class="n">VisualChunk</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Story</span>
+<span class="w">        </span><span class="n">Face</span><span class="p">[</span><span class="n">Face</span><span class="p">]</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Story</span>
+<span class="w">        </span><span class="n">Story</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">FiveW1H</span><span class="p">[</span><span class="mi">5</span><span class="n">W1H</span><span class="p">]</span>
+<span class="w">        </span><span class="n">OCR</span><span class="p">[</span><span class="n">OCR</span><span class="p">]</span>
+<span class="w">        </span><span class="n">Pose</span><span class="p">[</span><span class="n">Pose</span><span class="p">]</span>
+<span class="w">    </span><span class="n">end</span>
+
+<span class="w">    </span><span class="n">subgraph</span><span class="w"> </span><span class="n">Ingestion</span><span class="p">[</span><span class="s">&quot;入庫 (Post-Processing)&quot;</span><span class="p">]</span>
+<span class="w">        </span><span class="n">ASR</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Rule1</span><span class="p">[</span><span class="n">Rule</span><span class="w"> </span><span class="mi">1</span><span class="w"> </span><span class="n">Sentence</span><span class="p">]</span>
+<span class="w">        </span><span class="n">ASRX</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Rule1</span>
+<span class="w">        </span><span class="n">Rule1</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Vectorize</span><span class="p">[</span><span class="n">Auto</span><span class="o">-</span><span class="n">Vectorize</span><span class="p">]</span>
+<span class="w">        </span><span class="n">Rule1</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Phase1</span><span class="p">[</span><span class="n">Phase</span><span class="w"> </span><span class="mi">1</span><span class="w"> </span><span class="n">Pack</span><span class="p">]</span>
+
+<span class="w">        </span><span class="n">Cut</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Rule3</span><span class="p">[</span><span class="n">Rule</span><span class="w"> </span><span class="mi">3</span><span class="w"> </span><span class="n">Scene</span><span class="p">]</span>
+<span class="w">        </span><span class="n">ASR</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Rule3</span>
+
+<span class="w">        </span><span class="n">Face</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Trace</span><span class="p">[</span><span class="n">Face</span><span class="w"> </span><span class="n">Trace</span><span class="p">]</span>
+<span class="w">        </span><span class="n">Trace</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Qdrant</span><span class="p">[</span><span class="n">Qdrant</span><span class="w"> </span><span class="n">Sync</span><span class="p">]</span>
+<span class="w">        </span><span class="n">Trace</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">TraceChunks</span><span class="p">[</span><span class="n">Trace</span><span class="w"> </span><span class="n">Chunks</span><span class="p">]</span>
+<span class="w">        </span><span class="n">Trace</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">TKG</span><span class="p">[</span><span class="n">TKG</span><span class="w"> </span><span class="n">Builder</span><span class="p">]</span>
+
+<span class="w">        </span><span class="n">Face</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">TMDbMatch</span><span class="p">[</span><span class="n">TMDb</span><span class="w"> </span><span class="n">Match</span><span class="p">]</span>
+<span class="w">        </span><span class="n">Face</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">SceneMeta</span><span class="p">[</span><span class="n">Scene</span><span class="w"> </span><span class="n">Metadata</span><span class="p">]</span>
+<span class="w">        </span><span class="n">YOLO</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">SceneMeta</span>
+<span class="w">        </span><span class="n">Face</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">IdentityAgent</span><span class="p">[</span><span class="n">Identity</span><span class="w"> </span><span class="n">Agent</span><span class="p">]</span>
+<span class="w">        </span><span class="n">ASRX</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">IdentityAgent</span>
+
+<span class="w">        </span><span class="n">Cut</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Agent5W1H</span><span class="p">[</span><span class="mi">5</span><span class="n">W1H</span><span class="w"> </span><span class="n">Agent</span><span class="p">]</span>
+<span class="w">        </span><span class="n">ASR</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Agent5W1H</span>
+<span class="w">        </span><span class="n">Agent5W1H</span><span class="w"> </span><span class="o">--&gt;</span><span class="w"> </span><span class="n">Phase2</span><span class="p">[</span><span class="n">Phase</span><span class="w"> </span><span class="mi">2</span><span class="w"> </span><span class="n">Pack</span><span class="p">]</span>
+<span class="w">    </span><span class="n">end</span>
+
+<span class="w">    </span><span class="n">style</span><span class="w"> </span><span class="n">Processors</span><span class="w"> </span><span class="n">fill</span><span class="o">:</span><span class="err">#</span><span class="mi">1</span><span class="n">a1a2e</span><span class="p">,</span><span class="n">stroke</span><span class="o">:</span><span class="err">#</span><span class="n">e94560</span>
+<span class="w">    </span><span class="n">style</span><span class="w"> </span><span class="n">Ingestion</span><span class="w"> </span><span class="n">fill</span><span class="o">:</span><span class="err">#</span><span class="mi">16213</span><span class="n">e</span><span class="p">,</span><span class="n">stroke</span><span class="o">:</span><span class="err">#</span><span class="mf">0f</span><span class="mi">3460</span>
+</code></pre></div>
+
+<h3>Pipeline Completion Flow</h3>
+<p>The pipeline is <strong>not complete</strong> until both the 10 processors AND the 入庫 (ingestion) steps have finished. The worker polls every 3 seconds and only marks the job as <code>completed</code> when all ingestion steps verify OK.</p>
+<div class="codehilite"><pre><span></span><code><span class="mf">10</span><span class="w"> </span><span class="n">processors</span><span class="w"> </span><span class="n">done</span>
+<span class="w">     </span><span class="err">↓</span><span class="w">  </span><span class="p">(</span><span class="n">job</span><span class="w"> </span><span class="n">status</span><span class="w"> </span><span class="n">stays</span><span class="w"> </span><span class="s">&quot;running&quot;</span><span class="p">)</span>
+<span class="n">Algorithm</span><span class="w"> </span><span class="mf">1</span><span class="w"> </span><span class="n">Trigger</span><span class="p">:</span><span class="w"> </span><span class="n">Rule</span><span class="w"> </span><span class="mf">1</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">Vectorize</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">Phase</span><span class="w"> </span><span class="mf">1</span><span class="w"> </span><span class="n">Pack</span>
+<span class="w">     </span><span class="err">↓</span><span class="w">  </span><span class="p">(</span><span class="n">job</span><span class="w"> </span><span class="kr">run</span><span class="n">s</span><span class="w"> </span><span class="n">in</span><span class="w"> </span><span class="n">parallel</span><span class="p">)</span>
+<span class="n">Algorithm</span><span class="w"> </span><span class="mf">2</span><span class="w"> </span><span class="n">Trigger</span><span class="p">:</span><span class="w"> </span><span class="n">Face</span><span class="w"> </span><span class="n">Trace</span><span class="w"> </span><span class="err">→</span><span class="w"> </span><span class="n">TKG</span><span class="p">,</span><span class="w"> </span><span class="n">Scene</span><span class="w"> </span><span class="n">Metadata</span><span class="p">,</span><span class="w"> </span><span class="n">Identity</span><span class="w"> </span><span class="n">Agent</span><span class="p">,</span><span class="w"> </span><span class="mf">5</span><span class="n">W1H</span><span class="w"> </span><span class="n">Agent</span>
+<span class="w">     </span><span class="err">↓</span><span class="w">  </span><span class="p">(</span><span class="n">poll</span><span class="w"> </span><span class="n">checks</span><span class="w"> </span><span class="n">every</span><span class="w"> </span><span class="mf">3</span><span class="n">s</span><span class="p">)</span>
+<span class="n">Ingestion</span><span class="w"> </span><span class="n">verification</span><span class="p">:</span><span class="w"> </span><span class="n">rule1</span><span class="w"> </span><span class="err">✓</span><span class="w"> </span><span class="n">vectorize</span><span class="w"> </span><span class="err">✓</span><span class="w"> </span><span class="n">rule3</span><span class="w"> </span><span class="err">✓</span><span class="w"> </span><span class="n">face_trace</span><span class="w"> </span><span class="err">✓</span><span class="w"> </span><span class="n">tkg</span><span class="w"> </span><span class="err">✓</span><span class="w"> </span><span class="n">scene_meta</span><span class="w"> </span><span class="err">✓</span><span class="w"> </span><span class="mf">5</span><span class="n">w1h</span><span class="w"> </span><span class="err">✓</span>
+<span class="w">     </span><span class="err">↓</span>
+<span class="n">job</span><span class="w"> </span><span class="n">status</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s">&quot;completed&quot;</span>
+</code></pre></div>
+
+<h3>10 Processor Stages</h3>
+<table class="table">
+<thead>
+<tr>
+<th>#</th>
+<th>Processor</th>
+<th>Depends On</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>1</td>
+<td><code>Cut</code></td>
+<td>—</td>
+<td>Scene boundary detection (PySceneDetect)</td>
+</tr>
+<tr>
+<td>2</td>
+<td><code>ASR</code></td>
+<td>Cut</td>
+<td>Automatic speech recognition (faster-whisper)</td>
+</tr>
+<tr>
+<td>3</td>
+<td><code>ASRX</code></td>
+<td>ASR</td>
+<td>Speaker diarization + ASR refinement</td>
+</tr>
+<tr>
+<td>4</td>
+<td><code>YOLO</code></td>
+<td>—</td>
+<td>Object detection (YOLOv8)</td>
+</tr>
+<tr>
+<td>5</td>
+<td><code>OCR</code></td>
+<td>—</td>
+<td>Optical character recognition</td>
+</tr>
+<tr>
+<td>6</td>
+<td><code>Face</code></td>
+<td>—</td>
+<td>Face detection + recognition (InsightFace + CoreML)</td>
+</tr>
+<tr>
+<td>7</td>
+<td><code>Pose</code></td>
+<td>—</td>
+<td>Pose estimation</td>
+</tr>
+<tr>
+<td>8</td>
+<td><code>VisualChunk</code></td>
+<td>YOLO</td>
+<td>Visual object chunking</td>
+</tr>
+<tr>
+<td>9</td>
+<td><code>Story</code></td>
+<td>ASRX + Cut + YOLO + Face</td>
+<td>Narrative scene summarization (LLM, with embedding)</td>
+</tr>
+<tr>
+<td>10</td>
+<td><code>5W1H</code></td>
+<td>Story</td>
+<td>Who/What/When/Where/Why extraction (LLM, with embedding)</td>
+</tr>
+</tbody>
+</table>
+<h3>入庫 (Post-Processing / Ingestion)</h3>
+<p>These steps run after the 10 processors and are <strong>required for pipeline completion</strong>. The worker checks all of them before marking the job as done.</p>
+<table class="table">
+<thead>
+<tr>
+<th>#</th>
+<th>Step</th>
+<th>Triggers When</th>
+<th>Verification</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>1</td>
+<td><strong>Rule 1 Sentence Chunking</strong></td>
+<td>ASR + ASRX done</td>
+<td><code>chunk</code> table has rows with <code>chunk_type = 'sentence'</code></td>
+</tr>
+<tr>
+<td>2</td>
+<td><strong>Auto-Vectorize</strong></td>
+<td>Rule 1 done</td>
+<td><code>chunk.embedding</code> IS NOT NULL for sentence chunks</td>
+</tr>
+<tr>
+<td>3</td>
+<td><strong>Phase 1 Pack</strong></td>
+<td>Rule 1 done</td>
+<td><code>release_pack.py --phase 1</code> executed</td>
+</tr>
+<tr>
+<td>4</td>
+<td><strong>Rule 3 Scene Chunking</strong></td>
+<td>All 10 processors done + Cut + ASR</td>
+<td><code>chunk</code> table has rows with <code>chunk_type = 'cut'</code></td>
+</tr>
+<tr>
+<td>5</td>
+<td><strong>Face Trace</strong></td>
+<td>All 10 processors done + Face</td>
+<td><code>face_detections.trace_id</code> IS NOT NULL</td>
+</tr>
+<tr>
+<td>6</td>
+<td><strong>Qdrant Face Sync</strong></td>
+<td>Face Trace done</td>
+<td>Qdrant face_embedding collection populated</td>
+</tr>
+<tr>
+<td>7</td>
+<td><strong>Trace Chunks</strong></td>
+<td>Face Trace done</td>
+<td><code>chunk</code> table has rows with <code>chunk_type = 'trace'</code></td>
+</tr>
+<tr>
+<td>8</td>
+<td><strong>TKG Builder</strong></td>
+<td>Face Trace done</td>
+<td><code>tkg_nodes</code> + <code>tkg_edges</code> tables have rows</td>
+</tr>
+<tr>
+<td>9</td>
+<td><strong>TMDb Face Matching</strong></td>
+<td>TMDb enabled + Face done</td>
+<td><code>face_detections.identity_id</code> IS NOT NULL</td>
+</tr>
+<tr>
+<td>10</td>
+<td><strong>Heuristic Scene Metadata</strong></td>
+<td>Face + YOLO done</td>
+<td><code>{file_uuid}.scene_meta.json</code> exists on disk</td>
+</tr>
+<tr>
+<td>11</td>
+<td><strong>Identity Agent</strong></td>
+<td>Face + ASRX done</td>
+<td><code>identities</code> with <code>source = 'identity_agent'</code></td>
+</tr>
+<tr>
+<td>12</td>
+<td><strong>5W1H Agent</strong></td>
+<td>Cut + ASR done</td>
+<td><code>chunk.summary_text</code> IS NOT NULL for cut chunks</td>
+</tr>
+<tr>
+<td>13</td>
+<td><strong>Release Pack</strong></td>
+<td>5W1H Agent done</td>
+<td><code>release_pack.py --phase 2</code> executed</td>
+</tr>
+</tbody>
+</table>
+<h3>Ingestion Status</h3>
+<p>Check real-time ingestion status for a file:</p>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/stats/ingestion-status/{file_uuid}&quot;</span>
+</code></pre></div>
+
+<p>Returns per-step <code>done</code> / <code>pending</code> status with detail counts.</p>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span><span class="s2">&quot;http://localhost:3003/api/v1/stats/ingestion-status/bd80fec9c42afb0307eb28f22c64c76a&quot;</span><span class="w"> </span><span class="p">|</span><span class="w"> </span>jq<span class="w"> </span><span class="s1">&#39;.steps[] | {name, status, detail}&#39;</span>
+</code></pre></div>
+
+<h4>Response</h4>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;file_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;bd80fec9c42afb0307eb28f22c64c76a&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;steps&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;rule1_sentence&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;pending&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;detail&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;0 sentence chunks&quot;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;auto_vectorize&quot;</span><span class="p">,</span><span class="w">  </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;pending&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;detail&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;0 embedded&quot;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;rule3_scene&quot;</span><span class="p">,</span><span class="w">     </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;pending&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;detail&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;0 scene chunks&quot;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;face_trace&quot;</span><span class="p">,</span><span class="w">      </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;pending&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;detail&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;0 traces&quot;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;trace_chunks&quot;</span><span class="p">,</span><span class="w">    </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;pending&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;detail&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;0 trace chunks&quot;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;tkg&quot;</span><span class="p">,</span><span class="w">             </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;pending&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;detail&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;0 nodes, 0 edges&quot;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;identity_match&quot;</span><span class="p">,</span><span class="w">  </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;pending&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;detail&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;0 identities&quot;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;scene_metadata&quot;</span><span class="p">,</span><span class="w">  </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;pending&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;detail&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">null</span><span class="w"> </span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;5w1h&quot;</span><span class="p">,</span><span class="w">            </span><span class="nt">&quot;status&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;pending&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;detail&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;0 scenes with 5W1H&quot;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<h3>Stats Endpoints</h3>
+<table class="table">
+<thead>
+<tr>
+<th>Method</th>
+<th>Endpoint</th>
+<th>Auth</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>GET</td>
+<td><code>/api/v1/stats/sftpgo</code></td>
+<td>No</td>
+<td>SFTPGo service status</td>
+</tr>
+<tr>
+<td>GET</td>
+<td><code>/api/v1/stats/ingestion-status/:file_uuid</code></td>
+<td>No</td>
+<td>Per-file ingestion checklist</td>
+</tr>
+</tbody>
+</table>
+<h3>Configuration</h3>
+<h3><code>POST /api/v1/config/cache</code></h3>
+<p><strong>Auth</strong>: Required
+<strong>Scope</strong>: system-level</p>
+<p>Toggle the Redis cache on or off.</p>
+<h4>Request Parameters</h4>
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>enabled</code></td>
+<td>boolean</td>
+<td>Yes</td>
+<td><code>true</code> to enable, <code>false</code> to disable</td>
+</tr>
+</tbody>
+</table>
+<h4>Example</h4>
+<div class="codehilite"><pre><span></span><code>curl<span class="w"> </span>-s<span class="w"> </span>-X<span class="w"> </span>POST<span class="w"> </span><span class="s2">&quot;</span><span class="nv">$API</span><span class="s2">/api/v1/config/cache&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;Content-Type: application/json&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-H<span class="w"> </span><span class="s2">&quot;X-API-Key: </span><span class="nv">$KEY</span><span class="s2">&quot;</span><span class="w"> </span><span class="se">\</span>
+<span class="w">  </span>-d<span class="w"> </span><span class="s1">&#39;{&quot;enabled&quot;: false}&#39;</span>
+</code></pre></div>
+
+<h3>Unmounted Routes</h3>
+<p>The following routes are defined in source code but are <strong>NOT</strong> currently mounted in the router:</p>
+<table class="table">
+<thead>
+<tr>
+<th>Endpoint</th>
+<th>Source file</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>/api/v1/search/persons</code></td>
+<td><code>universal_search.rs</code> (not mounted)</td>
+</tr>
+<tr>
+<td><code>/api/v1/who</code></td>
+<td><code>who.rs</code></td>
+</tr>
+<tr>
+<td><code>/api/v1/who/candidates</code></td>
+<td><code>who.rs</code></td>
+</tr>
+</tbody>
+</table>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/12_agent.html

@@ -0,0 +1,207 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>12 Agent - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
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+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<h1>Agent Endpoints</h1>
+<p>Agent endpoints provide AI-powered capabilities including translation, identity analysis, and 5W1H extraction.</p>
+<h2>POST /api/v1/agents/translate</h2>
+<p>Translate text between languages using Gemma4 (llama.cpp, port 8082).</p>
+<h3>Request</h3>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;text&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Hello, welcome to Momentry Core.&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;target_language&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Traditional Chinese&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;source_language&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;English&quot;</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<table class="table">
+<thead>
+<tr>
+<th>Field</th>
+<th>Type</th>
+<th>Required</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>text</code></td>
+<td>string</td>
+<td>✅</td>
+<td>Text to translate</td>
+</tr>
+<tr>
+<td><code>target_language</code></td>
+<td>string</td>
+<td>✅</td>
+<td>Target language name (e.g. "Traditional Chinese", "Japanese")</td>
+</tr>
+<tr>
+<td><code>source_language</code></td>
+<td>string</td>
+<td>❌</td>
+<td>Source language (default: "auto")</td>
+</tr>
+</tbody>
+</table>
+<h3>Response</h3>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;translated_text&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;您好，歡迎使用 Momentry Core。&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;source_language_detected&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;English&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;model_used&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;google_gemma-4-26B-A4B-it-Q5_K_M.gguf&quot;</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<h3>Supported Language Pairs (tested)</h3>
+<table class="table">
+<thead>
+<tr>
+<th>Source</th>
+<th>Target</th>
+<th>Quality</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>English</td>
+<td>Traditional Chinese</td>
+<td>✅</td>
+</tr>
+<tr>
+<td>English</td>
+<td>Japanese</td>
+<td>✅</td>
+</tr>
+<tr>
+<td>Chinese</td>
+<td>English</td>
+<td>✅</td>
+</tr>
+<tr>
+<td>English</td>
+<td>French</td>
+<td>✅</td>
+</tr>
+<tr>
+<td>Chinese</td>
+<td>Japanese</td>
+<td>✅</td>
+</tr>
+</tbody>
+</table>
+<h3>Model</h3>
+<ul>
+<li><strong>Model</strong>: Gemma4 26B (Q5_K_M)</li>
+<li><strong>Engine</strong>: llama.cpp at <code>localhost:8082</code></li>
+<li><strong>Endpoint</strong>: <code>/v1/chat/completions</code> (OpenAI-compatible)</li>
+<li><strong>Temperature</strong>: 0.1</li>
+<li><strong>Max tokens</strong>: 1024</li>
+</ul>
+<h3>Errors</h3>
+<table class="table">
+<thead>
+<tr>
+<th>Status</th>
+<th>Condition</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>500</td>
+<td>LLM unreachable or response parse failure</td>
+</tr>
+<tr>
+<td>401</td>
+<td>Missing/invalid auth</td>
+</tr>
+</tbody>
+</table>
+<hr />
+<h2>POST /api/v1/agents/5w1h/analyze</h2>
+<p>Extract 5W1H (Who, What, When, Where, Why, How) from a scene. Uses Gemma4 LLM on port 8082.</p>
+<h3>Request</h3>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;file_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;3abeee81d94597629ed8cb943f182e94&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;scene_id&quot;</span><span class="p">:</span><span class="w"> </span><span class="mi">42</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<h3>Response</h3>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;5w1h&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nt">&quot;who&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;Cary Grant&quot;</span><span class="p">],</span>
+<span class="w">    </span><span class="nt">&quot;what&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;discussing plans&quot;</span><span class="p">],</span>
+<span class="w">    </span><span class="nt">&quot;when&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;1963&quot;</span><span class="p">],</span>
+<span class="w">    </span><span class="nt">&quot;where&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;Paris&quot;</span><span class="p">],</span>
+<span class="w">    </span><span class="nt">&quot;why&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;vacation&quot;</span><span class="p">],</span>
+<span class="w">    </span><span class="nt">&quot;how&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;in person&quot;</span><span class="p">]</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<h2>POST /api/v1/agents/5w1h/batch</h2>
+<p>Batch analyze all scenes in a file for 5W1H extraction. Uses the pipeline's <code>parent_chunk_5w1h.py --mode llm</code>.</p>
+<h3>Request</h3>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;file_uuid&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;3abeee81d94597629ed8cb943f182e94&quot;</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<h2>GET /api/v1/agents/5w1h/status</h2>
+<p>Get status of the 5W1H agent pipeline for a file.</p>
+<hr />
+<h2>Embedding Model</h2>
+<table class="table">
+<thead>
+<tr>
+<th>Detail</th>
+<th>Value</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><strong>Model</strong></td>
+<td>EmbeddingGemma-300m</td>
+</tr>
+<tr>
+<td><strong>Endpoint</strong></td>
+<td><code>POST /v1/embeddings</code> on port 11436</td>
+</tr>
+<tr>
+<td><strong>Dimension</strong></td>
+<td>768</td>
+</tr>
+<tr>
+<td><strong>Used by</strong></td>
+<td><code>parent_chunk_5w1h.py --embed</code>, story, 5W1H, search</td>
+</tr>
+</tbody>
+</table>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/index.html

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+<!DOCTYPE html>
+<html lang="zh-TW">
+<head>
+<meta charset="UTF-8">
+<title>Momentry API 文件</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 900px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 28px; margin-bottom: 8px; }
+p.subtitle { color: #666; margin-bottom: 24px; }
+table { width: 100%; border-collapse: collapse; }
+tr { border-bottom: 1px solid #eee; }
+tr:last-child { border: none; }
+td { padding: 10px 0; }
+td.cn { width: 140px; font-weight: 600; color: #333; }
+td.en { color: #666; font-size: 14px; }
+a { color: #0066cc; text-decoration: none; display: block; }
+a:hover td { background: #f8f8f8; border-radius: 4px; }
+</style>
+</head>
+<body>
+<div class="container">
+<h1>Momentry API 文件</h1>
+<p class="subtitle">API 參考手冊 — 登入後可瀏覽各模組文件</p>
+<table><tr onclick="window.location='01_auth.html'" style="cursor:pointer"><td class="cn">安全認證</td><td class="en">Authentication</td></tr><tr onclick="window.location='02_health.html'" style="cursor:pointer"><td class="cn">健康檢查</td><td class="en">Health</td></tr><tr onclick="window.location='03_register.html'" style="cursor:pointer"><td class="cn">檔案註冊</td><td class="en">File Registration</td></tr><tr onclick="window.location='04_lookup.html'" style="cursor:pointer"><td class="cn">檔案屬性查詢</td><td class="en">File Lookup</td></tr><tr onclick="window.location='05_process.html'" style="cursor:pointer"><td class="cn">處理流程</td><td class="en">Processing</td></tr><tr onclick="window.location='06_search.html'" style="cursor:pointer"><td class="cn">搜尋功能</td><td class="en">Search</td></tr><tr onclick="window.location='07_identity.html'" style="cursor:pointer"><td class="cn">身份識別</td><td class="en">Identity</td></tr><tr onclick="window.location='08_identity_agent.html'" style="cursor:pointer"><td class="cn">智能身份綁定</td><td class="en">Smart Identity Binding</td></tr><tr onclick="window.location='08_media.html'" style="cursor:pointer"><td class="cn">串流與截圖</td><td class="en">Streaming & Thumbnails</td></tr><tr onclick="window.location='09_tmdb.html'" style="cursor:pointer"><td class="cn">TMDb 整合</td><td class="en">TMDb Integration</td></tr><tr onclick="window.location='10_pipeline.html'" style="cursor:pointer"><td class="cn">生產線</td><td class="en">Pipeline</td></tr><tr onclick="window.location='12_agent.html'" style="cursor:pointer"><td class="cn">智慧代理</td><td class="en">AI Agents</td></tr></table>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc/login.html

@@ -0,0 +1,46 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>Login - Momentry Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; display: flex; justify-content: center; align-items: center; height: 100vh; }
+.card { background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; width: 360px; }
+h1 { font-size: 24px; margin-bottom: 24px; text-align: center; }
+input { width: 100%; padding: 10px 12px; margin-bottom: 12px; border: 1px solid #ddd; border-radius: 6px; font-size: 14px; }
+button { width: 100%; padding: 10px; background: #0066cc; color: white; border: none; border-radius: 6px; font-size: 16px; cursor: pointer; }
+button:hover { background: #0052a3; }
+.error { color: #cc0000; font-size: 13px; margin-bottom: 12px; display: none; }
+</style>
+</head>
+<body>
+<div class="card">
+<h1>Momentry Docs</h1>
+<form id="loginForm">
+<input type="text" id="username" placeholder="Username" value="demo" required>
+<input type="password" id="password" placeholder="Password" value="demo" required>
+<div class="error" id="error">Invalid credentials</div>
+<button type="submit">Login</button>
+</form>
+</div>
+<script>
+document.getElementById('loginForm').onsubmit = async function(e) {
+    e.preventDefault();
+    const resp = await fetch('/api/v1/auth/login', {
+        method: 'POST',
+        headers: {'Content-Type': 'application/json'},
+        body: JSON.stringify({
+            username: document.getElementById('username').value,
+            password: document.getElementById('password').value
+        })
+    });
+    if (resp.ok) {
+        window.location.href = '/doc/index.html';
+    } else {
+        document.getElementById('error').style.display = 'block';
+    }
+};
+</script>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc_developer/11_error_codes.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>11 Error Codes - Momentry API Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 24px; margin: 24px 0 12px; }
+h2 { font-size: 20px; margin: 20px 0 10px; color: #222; }
+h3 { font-size: 16px; margin: 16px 0 8px; color: #444; }
+p { line-height: 1.6; margin: 8px 0; }
+table { border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }
+th, td { border: 1px solid #ddd; padding: 8px 12px; text-align: left; }
+th { background: #f0f0f0; font-weight: 600; }
+code { background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }
+pre { background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }
+pre code { background: none; padding: 0; }
+a { color: #0066cc; }
+.back { display: inline-block; margin-bottom: 20px; color: #666; }
+.back:hover { color: #333; }
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+<!-- module: error_codes -->
+<!-- description: Standard API error codes -->
+<!-- depends: -->
+
+<h2>Error Response Format</h2>
+<p>All API errors follow this JSON structure:</p>
+<div class="codehilite"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nt">&quot;success&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">  </span><span class="nt">&quot;error&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nt">&quot;code&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;E001_NOT_FOUND&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;message&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Resource not found&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">&quot;details&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="nt">&quot;resource&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;file_uuid&quot;</span><span class="p">,</span><span class="w"> </span><span class="nt">&quot;value&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;abc&quot;</span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
+</code></pre></div>
+
+<h2>Error Code List</h2>
+<h3>Generic Errors (E0xx)</h3>
+<table class="table">
+<thead>
+<tr>
+<th>Code</th>
+<th>HTTP</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>E001_NOT_FOUND</code></td>
+<td>404</td>
+<td>Resource not found (file, identity, chunk)</td>
+</tr>
+<tr>
+<td><code>E002_DUPLICATE</code></td>
+<td>409</td>
+<td>Resource already exists</td>
+</tr>
+<tr>
+<td><code>E003_VALIDATION</code></td>
+<td>400</td>
+<td>Request parameter validation failed</td>
+</tr>
+<tr>
+<td><code>E004_UNAUTHORIZED</code></td>
+<td>401</td>
+<td>Invalid API key or token</td>
+</tr>
+<tr>
+<td><code>E005_INTERNAL</code></td>
+<td>500</td>
+<td>Internal server error</td>
+</tr>
+</tbody>
+</table>
+<h3>Processor Errors (E1xx)</h3>
+<table class="table">
+<thead>
+<tr>
+<th>Code</th>
+<th>HTTP</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>E101_PROCESSOR_FAIL</code></td>
+<td>500</td>
+<td>Python script execution failed</td>
+</tr>
+<tr>
+<td><code>E102_TIMEOUT</code></td>
+<td>504</td>
+<td>Processing timeout</td>
+</tr>
+<tr>
+<td><code>E103_RESUME_FAIL</code></td>
+<td>500</td>
+<td>Resume failed (checkpoint not found)</td>
+</tr>
+<tr>
+<td><code>E104_NO_VIDEO</code></td>
+<td>400</td>
+<td>Video file path not found</td>
+</tr>
+</tbody>
+</table>
+<h3>Identity Errors (E2xx)</h3>
+<table class="table">
+<thead>
+<tr>
+<th>Code</th>
+<th>HTTP</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>E201_FACE_NOT_FOUND</code></td>
+<td>404</td>
+<td>Face detection not found</td>
+</tr>
+<tr>
+<td><code>E202_MERGE_CONFLICT</code></td>
+<td>409</td>
+<td>Identity merge conflict</td>
+</tr>
+<tr>
+<td><code>E203_CANDIDATE_EMPTY</code></td>
+<td>404</td>
+<td>No candidates available for confirmation</td>
+</tr>
+</tbody>
+</table>
+<h3>TMDb Errors (E3xx)</h3>
+<table class="table">
+<thead>
+<tr>
+<th>Code</th>
+<th>HTTP</th>
+<th>Description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>E301_TMDB_NO_KEY</code></td>
+<td>400</td>
+<td><code>TMDB_API_KEY</code> environment variable not set</td>
+</tr>
+<tr>
+<td><code>E302_TMDB_UNREACHABLE</code></td>
+<td>502</td>
+<td>TMDb API unreachable or timed out</td>
+</tr>
+<tr>
+<td><code>E303_TMDB_CACHE_NOT_FOUND</code></td>
+<td>200</td>
+<td>No local TMDb cache; run prefetch first</td>
+</tr>
+<tr>
+<td><code>E304_TMDB_PROBE_FAILED</code></td>
+<td>500</td>
+<td>TMDb probe execution failed</td>
+</tr>
+<tr>
+<td><code>E305_TMDB_MOVIE_NOT_FOUND</code></td>
+<td>404</td>
+<td>No matching TMDb movie found from filename</td>
+</tr>
+</tbody>
+</table>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc_developer/index.html

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+<!DOCTYPE html>
+<html lang="zh-TW">
+<head>
+<meta charset="UTF-8">
+<title>Momentry API 文件</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }
+.container { max-width: 900px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }
+h1 { font-size: 28px; margin-bottom: 8px; }
+p.subtitle { color: #666; margin-bottom: 24px; }
+table { width: 100%; border-collapse: collapse; }
+tr { border-bottom: 1px solid #eee; }
+tr:last-child { border: none; }
+td { padding: 10px 0; }
+td.cn { width: 140px; font-weight: 600; color: #333; }
+td.en { color: #666; font-size: 14px; }
+a { color: #0066cc; text-decoration: none; display: block; }
+a:hover td { background: #f8f8f8; border-radius: 4px; }
+</style>
+</head>
+<body>
+<div class="container">
+<h1>Momentry API 文件</h1>
+<p class="subtitle">API 參考手冊 — 登入後可瀏覽各模組文件</p>
+<table><tr onclick="window.location='11_error_codes.html'" style="cursor:pointer"><td class="cn">錯誤碼</td><td class="en">Error Codes</td></tr></table>
+</div>
+</body>
+</html>

deliverable_v1.1.0/html_docs/doc_developer/login.html

@@ -0,0 +1,46 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>Login - Momentry Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; display: flex; justify-content: center; align-items: center; height: 100vh; }
+.card { background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; width: 360px; }
+h1 { font-size: 24px; margin-bottom: 24px; text-align: center; }
+input { width: 100%; padding: 10px 12px; margin-bottom: 12px; border: 1px solid #ddd; border-radius: 6px; font-size: 14px; }
+button { width: 100%; padding: 10px; background: #0066cc; color: white; border: none; border-radius: 6px; font-size: 16px; cursor: pointer; }
+button:hover { background: #0052a3; }
+.error { color: #cc0000; font-size: 13px; margin-bottom: 12px; display: none; }
+</style>
+</head>
+<body>
+<div class="card">
+<h1>Momentry Docs</h1>
+<form id="loginForm">
+<input type="text" id="username" placeholder="Username" value="demo" required>
+<input type="password" id="password" placeholder="Password" value="demo" required>
+<div class="error" id="error">Invalid credentials</div>
+<button type="submit">Login</button>
+</form>
+</div>
+<script>
+document.getElementById('loginForm').onsubmit = async function(e) {
+    e.preventDefault();
+    const resp = await fetch('/api/v1/auth/login', {
+        method: 'POST',
+        headers: {'Content-Type': 'application/json'},
+        body: JSON.stringify({
+            username: document.getElementById('username').value,
+            password: document.getElementById('password').value
+        })
+    });
+    if (resp.ok) {
+        window.location.href = '/doc/index.html';
+    } else {
+        document.getElementById('error').style.display = 'block';
+    }
+};
+</script>
+</body>
+</html>

deliverable_v1.1.0/modules/01_auth.md

@@ -0,0 +1,280 @@
+<!-- module: auth -->
+<!-- description: Authentication — login, logout, JWT, session cookie, API key -->
+<!-- depends: -->
+
+## Base URL
+
+| Environment | URL | Purpose |
+|-------------|-----|---------|
+| Production | `http://localhost:3002` | Production deployment |
+| External (M5) | `https://m5api.momentry.ddns.net` | Remote access |
+
+## Variables
+
+All examples in this documentation use these environment variables:
+
+```bash
+API="http://localhost:3002"
+KEY="your-api-key-here"
+```
+
+## Authentication
+
+All endpoints under `/api/v1/*` require authentication.
+The following endpoints are public (no auth needed):
+
+- `GET /health`
+- `POST /api/v1/auth/login`
+- `POST /api/v1/auth/logout`
+
+### Three Authentication Modes
+
+The system supports three authentication methods, checked in **priority order** by the middleware:
+
+```
+Middleware priority:
+  1. Session Cookie (Portal/browser)
+  2. JWT Bearer (API clients, CLI)
+  3. API Key Header (legacy compatibility)
+  4. API Key Query Param (?api_key=)
+```
+
+| Mode | Transport | Expiry | Scope | Best for |
+|------|-----------|--------|-------|----------|
+| **Session Cookie** | `Cookie: session_id=<session_id>` | 24h | per-browser session | Portal (browser) |
+| **JWT** | `Authorization: Bearer <token>` | 1h | per-login token | API clients, CLI, scripts |
+| **API Key** | `X-API-Key: <key>` | 90d | fixed key for automation | Legacy scripts, WordPress |
+
+---
+
+### Login
+
+**Default accounts & API keys:**
+
+| Username | Password | API Key | Role |
+|----------|----------|---------|------|
+| `admin` | `admin` | — | admin |
+| `demo` | `demo` | `muser_demo_key_32chars_abcdef1234567890` | user |
+
+The demo API key is set via `MOMENTRY_DEMO_API_KEY` env var and can be used in place of JWT for marcom integrations:
+
+```bash
+# Using API key instead of JWT
+curl -s "$API/api/v1/files/scan" -H "X-API-Key: muser_demo_key_32chars_abcdef1234567890"
+```
+
+```bash
+# Login as admin
+curl -s -X POST "$API/api/v1/auth/login" \
+  -H "Content-Type: application/json" \
+  -d '{"username": "admin", "password": "admin"}'
+
+# Login as demo user
+curl -s -X POST "$API/api/v1/auth/login" \
+  -H "Content-Type: application/json" \
+  -d '{"username": "demo", "password": "demo"}'
+```
+
+#### Success Response
+
+```json
+{
+  "success": true,
+  "jwt": "eyJhbGciOiJIUzI1NiIs...",
+  "api_key": "muser_...",
+  "user": {
+    "username": "admin",
+    "role": "admin"
+  },
+  "expires_at": "2026-05-18T13:00:00Z"
+}
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `jwt` | string | JWT access token. Use as `Authorization: Bearer <jwt>`. Expires in 1 hour. |
+| `api_key` | string | Legacy API key. Use as `X-API-Key: <key>`. Good for 90 days. |
+| `user.username` | string | Username |
+| `user.role` | string | Role: `admin`, `user`, or `readonly` |
+| `expires_at` | string | ISO8601 timestamp of JWT expiration |
+
+The login endpoint also sets a `Set-Cookie` header for browser-based clients:
+
+```
+Set-Cookie: session_id=<session_id>; Path=/; HttpOnly; SameSite=Strict; Max-Age=86400
+```
+
+#### Error Response (401)
+
+```json
+{
+  "success": false,
+  "message": "Invalid username or password"
+}
+```
+
+---
+
+### Using JWT
+
+JWT is preferred for API clients (CLI scripts, WordPress). It is validated by the middleware without a database lookup (stateless).
+
+```bash
+# Login and capture JWT
+JWT=$(curl -s -X POST "$API/api/v1/auth/login" \
+  -H "Content-Type: application/json" \
+  -d '{"username":"admin","password":"admin"}' | python3 -c "import json,sys;print(json.load(sys.stdin)['jwt'])")
+
+# Use JWT for all subsequent requests
+curl -H "Authorization: Bearer $JWT" "$API/api/v1/files/scan"
+curl -H "Authorization: Bearer $JWT" "$API/api/v1/resource/tmdb"
+```
+
+JWT is short-lived (1 hour). When it expires, request a new one via login.
+
+---
+
+### Using Session Cookie (Browser)
+
+Browser-based clients (Portal) get a session cookie automatically after login. The browser sends the cookie with every request—no manual header needed.
+
+```bash
+# Login captures the session cookie from Set-Cookie header
+curl -v -X POST "$API/api/v1/auth/login" \
+  -H "Content-Type: application/json" \
+  -d '{"username":"admin","password":"admin"}' 2>&1 | grep "Set-Cookie"
+
+# Browser automatically sends: Cookie: session_id=<session_id>
+# No manual header needed for subsequent requests
+```
+
+The session cookie is HttpOnly (not accessible from JavaScript) and SameSite=Strict (protected against CSRF).
+
+---
+
+### Using Legacy API Key
+
+```bash
+curl -H "X-API-Key: $KEY" "$API/api/v1/files/scan"
+
+# Also accepted via Bearer header (non-JWT format) or query parameter:
+curl -H "Authorization: Bearer $KEY" "$API/api/v1/files/scan"
+curl "$API/api/v1/files/scan?api_key=$KEY"
+```
+
+API keys are validated via SHA256 hash lookup in the database. They are long-lived (90 days) and intended for automation.
+
+### Obtaining an API Key (CLI)
+
+```bash
+momentry api-key create "My API Key" --key-type user
+```
+
+---
+
+### Logout
+
+```bash
+# Logout using the session cookie (browser)
+curl -X POST "$API/api/v1/auth/logout" \
+  -H "Cookie: session_id=<uuid>"
+```
+
+#### What logout does
+
+| Auth mode | Effect |
+|-----------|--------|
+| **Session Cookie** | Session deleted from database. Same cookie returns 401 on subsequent requests. |
+| **JWT** | JWT remains valid until expiry. (JWT is stateless — logout adds JWT to a blacklist only if API key mode is used.) |
+| **API Key** | API key remains valid. (Legacy keys are shared across sessions — revoking would break other clients.) |
+
+#### Example: full session lifecycle
+
+```bash
+# 1. Login
+SESSION_ID=$(curl -s -D - -X POST "$API/api/v1/auth/login" \
+  -H "Content-Type: application/json" \
+  -d '{"username":"admin","password":"admin"}' | grep "Set-Cookie" | sed 's/.*session_id=\([^;]*\).*/\1/')
+
+# 2. Use session (works)
+curl -s -o /dev/null -w "HTTP %{http_code}\n" "$API/api/v1/resource/tmdb" \
+  -H "Cookie: session_id=$SESSION_ID"
+# → HTTP 200
+
+# 3. Logout
+curl -s -X POST "$API/api/v1/auth/logout" \
+  -H "Cookie: session_id=$SESSION_ID"
+# → {"success": true}
+
+# 4. Use session again (rejected)
+curl -s -o /dev/null -w "HTTP %{http_code}\n" "$API/api/v1/resource/tmdb" \
+  -H "Cookie: session_id=$SESSION_ID"
+# → HTTP 401
+```
+
+---
+
+### Authentication Flow Summary
+
+```
+Login Request
+     │
+     ▼
+┌──────────────────┐
+│  1. Check users  │ ← users table (argon2 password verify)
+│     table        │
+└──────┬───────────┘
+       │
+   ┌───┴───┐
+   │ match │
+   └───┬───┘
+       │
+       ▼
+┌──────────────────┐
+│  2. Create JWT   │ ← 1h expiry, signed with JWT_SECRET
+├──────────────────┤
+│  3. Create       │ ← 24h expiry, stored in sessions table
+│     session      │
+├──────────────────┤
+│  4. Set-Cookie   │ ← HttpOnly, SameSite=Strict, Path=/
+├──────────────────┤
+│  5. Return       │ ← JWT + api_key + user info to client
+└──────────────────┘
+```
+
+```
+Protected Request
+     │
+     ▼
+┌──────────────────────┐
+│  Middleware checks:  │
+│                      │
+│  1. Cookie session?  │ → DB lookup session → get api_key → verify
+│                      │
+│  2. JWT Bearer?      │ → verify JWT signature → decode claims
+│                      │
+│  3. X-API-Key?       │ → SHA256 hash → DB lookup → verify
+│                      │
+│  4. ?api_key=?       │ → same as #3
+│                      │
+│  5. None → 401       │
+└──────────────────────┘
+```
+
+---
+
+### Error Responses
+
+| HTTP | When |
+|------|------|
+| `401` | Missing or invalid authentication |
+| `401` | Session expired or logged out |
+| `401` | JWT expired |
+| `401` | API key revoked or inactive |
+
+---
+
+### Related
+
+- `POST /api/v1/resource/tmdb/check` — test authentication + TMDb API connectivity
+- `GET /health/detailed` — view auth status (integrations section)

deliverable_v1.1.0/modules/02_health.md

@@ -0,0 +1,147 @@
+<!-- module: health -->
+<!-- description: Health check endpoints -->
+<!-- depends: 01_auth -->
+
+## Health Check
+
+### `GET /health`
+
+**Auth**: Public
+**Scope**: system-level
+
+Returns basic server health status — used by load balancers and monitoring.
+
+#### Example
+
+```bash
+curl "$API/health" | jq '{status, version}'
+```
+
+#### Response (200)
+
+```json
+{
+  "status": "ok",
+  "version": "1.0.0",
+  "build_git_hash": "3a6c1865",
+  "build_timestamp": "2026-05-16T13:38:15Z",
+  "uptime_ms": 3015
+}
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `status` | string | `ok` or `degraded` |
+| `version` | string | Semver version |
+| `build_git_hash` | string | Git commit hash |
+| `build_timestamp` | string | Binary build time |
+| `uptime_ms` | integer | Milliseconds since server start |
+
+---
+
+### `GET /health/detailed`
+
+**Auth**: Required
+**Scope**: system-level
+
+Returns full system health including each service status, resource utilization, pipeline readiness, schema migration status, identity file sync status, and external integrations.
+
+> Requires authentication (JWT, session cookie, or API key). The basic `/health` endpoint remains public for load balancer checks.
+
+#### Example
+
+```bash
+curl "$API/health/detailed" | jq '{status, services, resources: {cpu: .resources.cpu_used_percent, memory: .resources.memory_used_percent}}'
+```
+
+#### Response (200)
+
+```json
+{
+  "status": "ok",
+  "version": "1.0.0",
+  "services": {
+    "postgres": {"status": "ok", "latency_ms": 3},
+    "redis": {"status": "ok", "latency_ms": 1},
+    "qdrant": {"status": "ok", "latency_ms": 5}
+  },
+  "resources": {
+    "cpu_used_percent": 12.5,
+    "memory_available_mb": 32768,
+    "memory_used_percent": 31.7
+  },
+  "pipeline": {
+    "scripts_ready": true,
+    "scripts_count": 345,
+    "processors": {
+      "asr": true,
+      "yolo": true,
+      "face": true,
+      "pose": true,
+      "ocr": true,
+      "cut": true,
+      "scene": true,
+      "asrx": true,
+      "visual_chunk": true
+    },
+    "models_ready": true,
+    "models_count": 42,
+    "scripts_integrity": {"matched": 332, "total": 345, "ok": false},
+    "ffmpeg": true
+  },
+  "schema": {
+    "table_exists": true,
+    "applied": [{"filename": "migrate_add_users_table.sql"}],
+    "required": [],
+    "ok": true
+  },
+  "identities": {
+    "directory_exists": true,
+    "files_count": 3481,
+    "index_ok": true,
+    "db_count": 3481,
+    "synced": true
+  },
+  "integrations": {
+    "tmdb": {
+      "api_key_configured": false,
+      "enabled": false,
+      "api_reachable": null
+    }
+  }
+}
+```
+
+#### Response Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `status` | string | `ok` if all essential services healthy |
+| `services` | object | Per-service status (postgres, redis, qdrant) |
+| `services.*.status` | string | `ok`, `error`, or `degraded` |
+| `services.*.latency_ms` | int | Response time in milliseconds |
+| `resources` | object | CPU, memory usage |
+| `pipeline.scripts_ready` | boolean | Scripts directory accessible |
+| `pipeline.scripts_count` | int | Number of Python processor scripts |
+| `pipeline.processors` | object | Per-processor availability |
+| `pipeline.models_ready` | boolean | Models directory accessible |
+| `pipeline.scripts_integrity` | object | SHA256 checksum verification results |
+| `schema.ok` | boolean | All required migrations applied |
+| `identities.synced` | boolean | Identity file count matches DB count |
+| `integrations.tmdb` | object | TMDB API key config and reachability |
+
+#### Health status rules
+
+| Condition | status |
+|-----------|--------|
+| All services ok | `ok` |
+| Any service error | `degraded` |
+| Postgres or Redis error | `degraded` (server still responds) |
+
+---
+
+### Stats Endpoints
+
+| Method | Endpoint | Auth | Description |
+|--------|----------|------|-------------|
+| GET | `/api/v1/stats/sftpgo` | No | SFTPGo service status |

deliverable_v1.1.0/modules/03_register.md

@@ -0,0 +1,184 @@
+<!-- module: register -->
+<!-- description: File registration — register, scan -->
+<!-- depends: 01_auth -->
+
+## File Registration
+
+### `POST /api/v1/files/register`
+
+**Auth**: Required
+**Scope**: file-level
+
+Register a video file for processing. Returns the file's metadata and UUID.
+
+**New in v0.1.2**: Registration now **automatically triggers the processing pipeline** — no need to call `POST /api/v1/file/:file_uuid/process` separately. The system will:
+1. Register the file and run ffprobe
+2. Auto-run offline TMDb probe (reads local identity files, no API calls)
+3. Create a monitor job for the worker
+4. Worker starts all 10 processors (Cut → ASR → ASRX → YOLO → OCR → Face → Pose → VisualChunk → Story → 5W1H)
+
+If the file already exists (same content hash), returns the existing record with `already_exists: true`.
+
+#### Request Parameters
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `file_path` | string | Yes | — | Path to video file on disk |
+| `pattern` | string | No | — | Regex pattern for batch register (requires `file_path` to be a directory) |
+| `user_id` | integer | No | — | User ID to associate with registration |
+| `content_hash` | string | No | — | Pre-computed SHA-256 hash (skips computation) |
+
+#### Example
+
+```bash
+# Register a single file
+curl -s -X POST "$API/api/v1/files/register" \
+  -H "Content-Type: application/json" \
+  -H "X-API-Key: $KEY" \
+  -d '{"file_path": "/path/to/video.mp4"}'
+
+# Batch register files matching a pattern in a directory
+curl -s -X POST "$API/api/v1/files/register" \
+  -H "Content-Type: application/json" \
+  -H "X-API-Key: $KEY" \
+  -d '{"file_path": "/path/to/dir", "pattern": ".*\\.mp4$"}'
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "file_uuid": "3a6c1865...",
+  "file_name": "video.mp4",
+  "file_path": "/path/to/video.mp4",
+  "file_type": "video",
+  "duration": 120.5,
+  "width": 1920,
+  "height": 1080,
+  "fps": 24.0,
+  "total_frames": 2892,
+  "already_exists": false,
+  "message": "File registered successfully"
+}
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `success` | boolean | Always true on 200 |
+| `file_uuid` | string | 32-char hex UUID of the registered file |
+| `file_name` | string | File name (auto-renamed if name conflict) |
+| `file_path` | string | Canonical path on disk |
+| `file_type` | string | `"video"`, `"audio"`, or `"unknown"` |
+| `duration` | float | Duration in seconds |
+| `width` | integer | Video width in pixels |
+| `height` | integer | Video height in pixels |
+| `fps` | float | Frames per second |
+| `total_frames` | integer | Total frame count |
+| `already_exists` | boolean | True if same content was already registered |
+| `message` | string | Human-readable status |
+
+#### Error Responses
+
+| HTTP | When |
+|------|------|
+| `401` | Missing or invalid API key |
+| `400` | Invalid request body |
+| `404` | File path does not exist |
+
+---
+
+### `GET /api/v1/files/scan`
+
+**Auth**: Required
+**Scope**: file-level
+
+Scan the filesystem directory and list all media files, showing which are registered, processing, or unregistered.
+
+#### Query Parameters
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `page` | integer | No | 1 | Page number (1-based) |
+| `page_size` | integer | No | all | Items per page (alias: `limit`) |
+| `limit` | integer | No | all | Max items (alias for `page_size`) |
+| `pattern` | string | No | — | Regex filter on file name (e.g., `.*\\.mp4$`) |
+| `sort_by` | string | No | `name` | Sort field: `name`, `size`, `modified`, `status` |
+| `sort_order` | string | No | `asc` | Sort direction: `asc` or `desc` |
+
+#### Example
+
+```bash
+# Full scan
+curl -s "$API/api/v1/files/scan" -H "X-API-Key: $KEY" | jq '{total, registered_count, unregistered_count}'
+
+# Paginated (page 1, 5 per page)
+curl -s "$API/api/v1/files/scan?page=1&page_size=5" -H "X-API-Key: $KEY" | jq '{page, total_pages, files: [.files[].file_name]}'
+
+# Regex filter: only mp4 files
+curl -s "$API/api/v1/files/scan?pattern=.*\\.mp4$" -H "X-API-Key: $KEY" | jq '{filtered_total, files: [.files[].file_name]}'
+
+# Sort by file size (largest first)
+curl -s "$API/api/v1/files/scan?sort_by=size&sort_order=desc&page_size=5" -H "X-API-Key: $KEY" | jq '[.files[] | {file_name, file_size}]'
+
+# Sort by modified time (most recent first)
+curl -s "$API/api/v1/files/scan?sort_by=modified&sort_order=desc&page_size=5" -H "X-API-Key: $KEY" | jq '[.files[] | {file_name, modified_time}]'
+
+# Sort by status
+curl -s "$API/api/v1/files/scan?sort_by=status&page_size=5" -H "X-API-Key: $KEY" | jq '[.files[] | {file_name, status}]'
+```
+
+#### Response (200)
+
+```json
+{
+  "files": [
+    {
+      "file_name": "video.mp4",
+      "file_size": 12345678,
+      "is_registered": true,
+      "file_uuid": "3a6c1865...",
+      "status": "completed",
+      "registration_time": "2026-05-16T12:00:00Z",
+      "job_id": 42
+    }
+  ],
+  "total": 107,
+  "filtered_total": 80,
+  "page": 1,
+  "page_size": 20,
+  "total_pages": 4,
+  "registered_count": 26,
+  "unregistered_count": 81
+}
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `files` | array | Array of file info objects (paginated) |
+| `files[].file_name` | string | File name |
+| `files[].relative_path` | string | Path relative to scan root |
+| `files[].file_path` | string | Absolute path on disk |
+| `files[].file_size` | integer | File size in bytes |
+| `files[].modified_time` | string | Last modified timestamp (ISO8601) |
+| `files[].is_registered` | boolean | Whether file is registered in DB |
+| `files[].file_uuid` | string | 32-char hex UUID (only if registered) |
+| `files[].status` | string | `"completed"`, `"processing"`, `"registered"`, `"unregistered"`, or `null` |
+| `files[].registration_time` | string | DB registration timestamp (only if registered) |
+| `files[].job_id` | integer | Processing job ID (only if a job exists) |
+| `total` | integer | Total files found on disk (unfiltered) |
+| `filtered_total` | integer | Files matching regex filter |
+| `page` | integer | Current page number |
+| `page_size` | integer | Items per page |
+| `total_pages` | integer | Total pages |
+| `registered_count` | integer | Files registered in DB |
+| `unregistered_count` | integer | Files not yet registered |
+
+#### Notes
+
+| Feature | Behavior |
+|---------|----------|
+| **Regex** | Case-insensitive (`(?i)` prefix auto-applied). Applied to `file_name`. |
+| **Sort order** | Default (`sort_by=name`): registered files first, then alphabetically. `sort_by=status`: alphabetical by status string. |
+| **Pagination** | `page_size` and `limit` are aliases. Default: show all results. |
+| **Processing order** | `pattern` regex filter → `sort_by`/`sort_order` → `page`/`page_size` slice. |

deliverable_v1.1.0/modules/04_lookup.md

@@ -0,0 +1,138 @@
+<!-- module: lookup -->
+<!-- description: File lookup by name and unregistration -->
+<!-- depends: 01_auth, 03_register -->
+
+## File Lookup
+
+### `GET /api/v1/files/lookup`
+
+**Auth**: Required
+**Scope**: file-level
+
+Search registered files by file name. Performs a case-insensitive LIKE search on the file name column. Returns basic info about matching files.
+
+#### Query Parameters
+
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `file_name` | string | Yes | File name to search for (partial matches supported) |
+
+#### Example
+
+```bash
+# Look up a specific file
+curl -s "$API/api/v1/files/lookup?file_name=video.mp4" \
+  -H "X-API-Key: $KEY"
+
+# Partial name search
+curl -s "$API/api/v1/files/lookup?file_name=charade" \
+  -H "X-API-Key: $KEY" | jq '.matches[].file_name'
+```
+
+#### Response (200)
+
+```json
+{
+  "file_name": "video.mp4",
+  "exists": true,
+  "matches": [
+    {
+      "file_uuid": "a03485a40b2df2d3",
+      "file_name": "video.mp4",
+      "file_type": "video",
+      "status": "completed"
+    }
+  ],
+  "next_name": "video (2).mp4"
+}
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `file_name` | string | Searched name |
+| `exists` | boolean | Exact name match exists |
+| `matches` | array | Array of matching registered files |
+| `matches[].file_uuid` | string | 32-char hex UUID |
+| `matches[].file_name` | string | Registered file name |
+| `matches[].file_type` | string | `"video"`, `"audio"`, or `null` |
+| `matches[].status` | string | Registration/processing status |
+| `next_name` | string | Suggested name for avoiding conflicts |
+
+---
+
+## Unregister
+
+### `POST /api/v1/unregister`
+
+**Auth**: Required
+**Scope**: file-level
+
+Delete a registered file from the system. Supports single file by UUID, or batch by directory + regex pattern.
+
+#### What gets deleted
+
+| Removed (default) | Not removed |
+|---------|-------------|
+| Database records (videos, chunks, embeddings, processor_results, pre_chunks) | The original source video file on disk |
+| Processor output JSON files (`{uuid}.*.json`) — unless `delete_output_files: false` | Temp/working directories |
+| In-memory cache entries | |
+| MongoDB cached lists | |
+
+> ⚠️ Database deletion is **irreversible**. To keep output files, set `"delete_output_files": false`.
+
+#### Request Parameters
+
+At least one mode must be specified: either `file_uuid` alone, or `file_path` + `pattern` together.
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `file_uuid` | string | * | — | Single file UUID to delete |
+| `file_path` | string | * | — | Directory path (for batch delete) |
+| `pattern` | string | * | — | Regex pattern (requires `file_path`) |
+| `delete_output_files` | boolean | No | `true` | If `true`, also delete processor output JSON files (`{uuid}.*.json`). Set to `false` to keep them. |
+
+#### Example
+
+```bash
+# Delete a single file by UUID (default: also deletes output JSON files)
+curl -s -X POST "$API/api/v1/unregister" \
+  -H "Content-Type: application/json" \
+  -H "X-API-Key: $KEY" \
+  -d '{"file_uuid": "'"$FILE_UUID"'"}'
+
+# Keep output JSON files, only delete DB records
+curl -s -X POST "$API/api/v1/unregister" \
+  -H "Content-Type: application/json" \
+  -H "X-API-Key: $KEY" \
+  -d '{"file_uuid": "'"$FILE_UUID"'", "delete_output_files": false}'
+
+# Batch delete all mp4 files in a directory
+curl -s -X POST "$API/api/v1/unregister" \
+  -H "Content-Type: application/json" \
+  -H "X-API-Key: $KEY" \
+  -d '{"file_path": "/path/to/dir", "pattern": ".*\\.mp4$"}'
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "file_uuid": "a03485a40b2df2d3",
+  "message": "Video unregistered successfully"
+}
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `success` | boolean | True if deletion succeeded |
+| `file_uuid` | string | UUID of the deleted file (single mode) |
+| `message` | string | Human-readable status |
+
+#### Error Responses
+
+| HTTP | When |
+|------|------|
+| `400` | Neither `file_uuid` nor `file_path`+`pattern` provided |
+| `404` | File UUID not found |
+| `401` | Missing or invalid API key |

deliverable_v1.1.0/modules/05_process.md

@@ -0,0 +1,236 @@
+<!-- module: process -->
+<!-- description: Processing pipeline — trigger, probe, progress, jobs -->
+<!-- depends: 01_auth, 03_register -->
+
+## Processing Pipeline
+
+### `POST /api/v1/file/:file_uuid/process`
+
+**Auth**: Required
+**Scope**: file-level
+
+Trigger the processing pipeline for a registered file. Creates a monitor job that the worker picks up and processes sequentially. Returns immediately with the job info—processing runs asynchronously in the background.
+
+#### Request Parameters
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `processors` | string[] | No | all | Specific processors to run: `["cut","asr","asrx","yolo","ocr","face","pose","visual_chunk","story","5w1h"]` |
+| `rules` | string[] | No | all | Rule names to apply (currently unused) |
+
+#### Example
+
+```bash
+# Run all processors
+curl -s -X POST "$API/api/v1/file/$FILE_UUID/process" \
+  -H "Content-Type: application/json" \
+  -H "X-API-Key: $KEY" -d '{}'
+
+# Run specific processors only
+curl -s -X POST "$API/api/v1/file/$FILE_UUID/process" \
+  -H "Content-Type: application/json" \
+  -H "X-API-Key: $KEY" \
+  -d '{"processors": ["asr", "face", "yolo"]}'
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "job_id": 42,
+  "file_uuid": "3a6c1865...",
+  "status": "processing",
+  "pids": [12345, 12346],
+  "message": "Processing triggered for video.mp4"
+}
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `success` | boolean | Always true on 200 |
+| `job_id` | integer | Monitor job ID (for job tracking) |
+| `file_uuid` | string | 32-char hex UUID of the file |
+| `status` | string | `"processing"` |
+| `pids` | integer[] | Process IDs of started processors |
+| `message` | string | Human-readable status |
+
+#### Error Responses
+
+| HTTP | When |
+|------|------|
+| `404` | File UUID not found |
+| `401` | Missing or invalid API key |
+
+---
+
+### `GET /api/v1/file/:file_uuid/probe`
+
+**Auth**: Required
+**Scope**: file-level
+
+Get ffprobe metadata for a registered file. Returns video/audio stream info, codec details, duration, resolution, and frame rate.
+
+#### Example
+
+```bash
+curl -s "$API/api/v1/file/$FILE_UUID/probe" -H "X-API-Key: $KEY"
+```
+
+#### Response (200)
+
+```json
+{
+  "file_uuid": "3a6c1865...",
+  "file_name": "video.mp4",
+  "file_size": 794863677,
+  "duration": 120.5,
+  "width": 1920,
+  "height": 1080,
+  "fps": 24.0,
+  "total_frames": 2892,
+  "cached": true,
+  "format": {
+    "filename": "/path/to/video.mp4",
+    "format_name": "mov,mp4,m4a,3gp",
+    "duration": "120.5",
+    "size": "12345678",
+    "bit_rate": "819200"
+  },
+  "streams": [
+    {
+      "index": 0,
+      "codec_name": "h264",
+      "codec_type": "video",
+      "width": 1920,
+      "height": 1080,
+      "r_frame_rate": "24/1",
+      "duration": "120.5"
+    }
+  ]
+}
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `file_uuid` | string | 32-char hex UUID |
+| `file_name` | string | File name |
+| `file_size` | integer | File size in bytes (from filesystem) |
+| `duration` | float | Duration in seconds |
+| `width` | integer | Video width in pixels |
+| `height` | integer | Video height in pixels |
+| `fps` | float | Frames per second |
+| `total_frames` | integer | Estimated total frames |
+| `cached` | boolean | True if result was from cached probe JSON |
+| `format` | object | Container format info (ffprobe format section) |
+| `streams` | array | Array of stream info objects |
+
+---
+
+### `GET /api/v1/progress/:file_uuid`
+
+**Auth**: Required
+**Scope**: file-level
+
+Get real-time processing progress for a file via Redis pub/sub. Includes per-processor status, current/total frames, ETA, and system resource stats.
+
+#### Pipeline Order
+
+| Order | Processor | Dependencies | Description |
+|-------|-----------|-------------|-------------|
+| 1 | `cut` | — | Scene detection |
+| 2 | `asr` | cut | Speech-to-text (per scene) |
+| 3 | `asrx` | asr | Speaker diarization |
+| 4 | `yolo` | — | Object detection |
+| 5 | `ocr` | — | Text recognition |
+| 6 | `face` | — | Face detection & embedding |
+| 7 | `pose` | — | Pose estimation |
+| 8 | `visual_chunk` | yolo | Visual scene chunks |
+| 9 | `story` | asr, asrx, cut, yolo, face | Scene summaries (template) |
+| 10 | `5w1h` | story | 5W1H analysis (Gemma4 LLM) |
+
+All processors except `story` and `5w1h` run concurrently when their dependencies are met. Story and 5W1H run sequentially after their prerequisites.
+
+#### Example
+
+```bash
+curl -s "$API/api/v1/progress/$FILE_UUID" -H "X-API-Key: $KEY" | jq '{overall_progress, processors: [.processors[] | {processor_type, status}]}'
+```
+
+#### Response (200)
+
+```json
+{
+  "file_uuid": "3a6c1865...",
+  "overall_progress": 71,
+  "cpu_percent": 45.2,
+  "gpu_percent": 30.1,
+  "memory_percent": 62.4,
+  "processors": [
+    {"processor_type": "asr", "status": "complete", "progress": 100},
+    {"processor_type": "yolo", "status": "running", "progress": 65},
+    {"processor_type": "face", "status": "pending", "progress": 0}
+  ]
+}
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `file_uuid` | string | 32-char hex UUID |
+| `overall_progress` | integer | Overall progress percentage (0–100) |
+| `processors` | array | Per-processor status list |
+| `processors[].processor_type` | string | Processor name (`asr`, `cut`, `yolo`, etc.) |
+| `processors[].status` | string | `"pending"`, `"running"`, `"complete"`, or `"failed"` |
+| `processors[].progress` | integer | Per-processor progress (0–100) |
+| `processors[].eta_seconds` | integer | Estimated seconds remaining (running processors) |
+| `processors[].current` | integer | Current frame count |
+| `processors[].total` | integer | Total frame count |
+| `cpu_percent` | float | Current CPU usage |
+| `gpu_percent` | float | Current GPU utilization |
+| `memory_percent` | float | Current memory usage |
+
+---
+
+### `GET /api/v1/jobs`
+
+**Auth**: Required
+**Scope**: system-level
+
+List all processing jobs (monitor jobs) in the system. Shows job status, which file each job is processing, and current processor info.
+
+#### Example
+
+```bash
+curl -s "$API/api/v1/jobs" -H "X-API-Key: $KEY" | jq '{count, jobs: [.jobs[] | {uuid, status}]}'
+```
+
+#### Response (200)
+
+```json
+{
+  "jobs": [
+    {
+      "id": 42,
+      "uuid": "3a6c1865...",
+      "status": "running",
+      "current_processor": "yolo",
+      "created_at": "2026-05-16T12:00:00Z",
+      "started_at": "2026-05-16T12:01:00Z"
+    }
+  ],
+  "count": 15,
+  "page": 1,
+  "page_size": 20
+}
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `jobs` | array | Array of job info objects |
+| `jobs[].id` | integer | Job ID |
+| `jobs[].uuid` | string | File UUID being processed |
+| `jobs[].status` | string | `"pending"`, `"running"`, `"completed"`, `"failed"` |
+| `jobs[].current_processor` | string | Currently active processor, or null |
+| `count` | integer | Total job count |
+| `page` | integer | Current page number |
+| `page_size` | integer | Jobs per page |

deliverable_v1.1.0/modules/06_search.md

@@ -0,0 +1,145 @@
+<!-- module: search -->
+<!-- description: Vector search, BM25, smart search, universal search, visual search -->
+<!-- depends: 01_auth -->
+
+## Search APIs
+
+### `POST /api/v1/search/smart`
+
+**Auth**: Required
+**Scope**: file-level
+
+Semantic vector search using EmbeddingGemma-300m. Generates a query embedding via EmbeddingGemma (port 11436), then searches pgvector `story_parent` and `llm_parent` chunks by cosine similarity.
+
+#### Request Parameters
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `file_uuid` | string | Yes | — | File UUID to search within |
+| `query` | string | Yes | — | Search text |
+| `limit` | integer | No | 5 | Max results to return |
+| `page` | integer | No | 1 | Page number |
+| `page_size` | integer | No | 5 | Items per page |
+
+#### Example
+
+```bash
+curl -s -X POST "$API/api/v1/search/smart" \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer $JWT" \
+  -d '{"file_uuid": "'"$FILE_UUID"'", "query": "Audrey Hepburn"}'
+```
+
+#### Response (200)
+
+```json
+{
+  "query": "Audrey Hepburn",
+  "results": [
+    {
+      "parent_id": 1087822,
+      "scene_order": 1087822,
+      "start_frame": 104438,
+      "end_frame": 104538,
+      "fps": 24.0,
+      "start_time": 4351.6,
+      "end_time": 4355.76,
+      "summary": "[4352s-4356s, 4s] Cast: Audrey Hepburn. Total: 2 lines, 10 words. Speakers: Audrey Hepburn (2 lines)",
+      "similarity": 0.67
+    }
+  ],
+  "page": 1,
+  "page_size": 5,
+  "strategy": "semantic_vector_search"
+}
+```
+
+---
+
+### `POST /api/v1/search/universal`
+
+**Auth**: Required
+**Scope**: file-level
+
+Multi-type BM25 full-text search across chunks, frames, and persons. Uses PostgreSQL `tsvector`.
+
+#### Request Parameters
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `query` | string | Yes | — | Search text |
+| `file_uuid` | string | No | — | Restrict to specific file |
+| `types` | string[] | No | `["chunk","frame","person"]` | Search types |
+| `limit` | integer | No | 10 | Max results per type |
+| `page` | integer | No | 1 | Page number |
+| `page_size` | integer | No | 20 | Items per page |
+
+#### Example
+
+```bash
+curl -s -X POST "$API/api/v1/search/universal" \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer $JWT" \
+  -d '{"file_uuid": "'"$FILE_UUID"'", "query": "Cary Grant"}'
+```
+
+#### Response (200)
+
+```json
+{
+  "results": [
+    {
+      "type": "chunk",
+      "chunk_id": "bd80fec92b0b6963d177a2c55bf713e2_2",
+      "chunk_type": "story_child",
+      "start_frame": 5103,
+      "end_frame": 5127,
+      "start_time": 212.64,
+      "end_time": 213.64,
+      "text": "[213s-214s] Cary Grant: \"Olá!\"",
+      "score": 0.9
+    }
+  ],
+  "total": 20,
+  "took_ms": 18
+}
+```
+
+---
+
+### `POST /api/v1/search/frames`
+
+**Auth**: Required
+**Scope**: file-level
+
+Search face detection frames by identity name or trace ID.
+
+---
+
+### `POST /api/v1/search/identity_text`
+
+**Auth**: Required
+**Scope**: file-level
+
+Search text chunks spoken by a specific identity.
+
+---
+
+### Visual Search
+
+| Method | Endpoint | Description |
+|--------|----------|-------------|
+| POST | `/api/v1/search/visual` | Search visual chunks |
+| POST | `/api/v1/search/visual/class` | Search by object class |
+| POST | `/api/v1/search/visual/density` | Search by object density |
+| POST | `/api/v1/search/visual/combination` | Search by object combination |
+| POST | `/api/v1/search/visual/stats` | Visual chunk statistics |
+
+#### Embedding Model
+
+| Detail | Value |
+|--------|-------|
+| **Model** | EmbeddingGemma-300m |
+| **Endpoint** | `POST /api/v1/embeddings` on port 11436 |
+| **Dimension** | 768 |
+| **Storage** | pgvector (`chunk.embedding` column) |

deliverable_v1.1.0/modules/07_identity.md

@@ -0,0 +1,516 @@
+<!-- module: identity -->
+<!-- description: Global identities — CRUD, detail, files, faces, bind, unbind, search -->
+<!-- depends: 01_auth -->
+
+## Global Identities
+
+### `GET /api/v1/identities`
+
+**Auth**: Required
+**Scope**: identity-level
+
+List all registered identities with pagination.
+
+#### Example
+
+```bash
+curl -s "$API/api/v1/identities?page=1&page_size=20" -H "X-API-Key: $KEY" | jq '{count, identities: [.identities[] | {name}]}'
+```
+
+---
+
+### `GET /api/v1/identity/:identity_uuid`
+
+**Auth**: Required
+**Scope**: identity-level
+
+Get detailed information for a specific identity, including metadata and TMDb references.
+
+#### Example
+
+```bash
+curl -s "$API/api/v1/identity/$IDENTITY_UUID" -H "X-API-Key: $KEY"
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "identity_uuid": "a9a901056d6b46ff92da0c3c1a57dff4",
+  "name": "Cary Grant",
+  "identity_type": "people",
+  "source": "tmdb",
+  "status": "confirmed",
+  "tmdb_id": 112,
+  "tmdb_profile": "{output}/identities/{identity_uuid}/profile.jpg",
+  "metadata": {},
+  "reference_data": {},
+  "created_at": "2026-05-16T12:00:00Z",
+  "updated_at": null
+}
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `identity_uuid` | string | Identity identifier |
+| `name` | string | Identity name |
+| `identity_type` | string | `"people"` or null |
+| `source` | string | `.json`, `auto`, `tmdb`, `user_defined`, or `merged` |
+| `status` | string | `"confirmed"`, `"pending"`, or `"inactive"` |
+| `tmdb_id` | integer | TMDb person ID (only if source = tmdb) |
+| `tmdb_profile` | string | Local profile image path (`{output}/identities/{uuid}/profile.jpg`) |
+| `metadata` | object | Metadata JSON (tmdb_character, cast_order, etc.) |
+| `created_at` | string | Creation timestamp |
+
+---
+
+### `DELETE /api/v1/identity/:identity_uuid`
+
+**Auth**: Required
+**Scope**: identity-level
+
+Delete an identity permanently.
+
+---
+
+### `PATCH /api/v1/identity/:identity_uuid`
+
+**Auth**: Required
+**Scope**: identity-level
+
+Partially update an identity. Only provided fields are modified. The `name` field is a display label and may repeat across identities. Aliases for multilingual display are stored in `metadata.aliases` (see BCP 47 reference below).
+
+#### Request (JSON, all fields optional)
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `name` | string | New display name |
+| `metadata` | object | Merged into existing metadata. Use `"aliases"` key for locale-tagged names |
+| `status` | string | `"confirmed"`, `"pending"`, or `"skipped"` |
+| `identity_type` | string | `"people"`, `"brand"`, `"object"`, `"concept"`, etc. |
+
+#### Example
+
+```bash
+curl -s -X PATCH "$API/api/v1/identity/$IDENTITY_UUID" \
+  -H "X-API-Key: $KEY" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "name": "John Smith",
+    "metadata": {
+      "aliases": [
+        {"locale": "en", "name": "John Smith"},
+        {"locale": "zh-TW", "name": "約翰·史密斯"},
+        {"locale": "ja", "name": "ジョン・スミス"}
+      ]
+    }
+  }'
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "identity_uuid": "a9a901056d6b46ff92da0c3c1a57dff4",
+  "updated_fields": ["name", "metadata"]
+}
+```
+
+#### Error Responses
+
+| HTTP | When |
+|------|------|
+| `400` | No fields to update or invalid UUID format |
+| `404` | Identity not found |
+
+---
+
+### `GET /api/v1/identity/:identity_uuid/files`
+
+**Auth**: Required
+**Scope**: identity-level
+
+Get all files where this identity appears. Returns per-file summary including face count, confidence, and appearance time range.
+
+#### Example
+
+```bash
+curl -s "$API/api/v1/identity/$IDENTITY_UUID/files" -H "X-API-Key: $KEY"
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "identity_uuid": "c3545906c82d4b66aa1d150bc02decce",
+  "total": 1,
+  "page": 1,
+  "page_size": 20,
+  "data": [
+    {
+      "file_uuid": "aeed71342a899fe4b4c57b7d41bcb692",
+      "file_name": "Charade (1963) Cary Grant & Audrey Hepburn.mp4",
+      "file_path": "/path/to/videos/Charade.mp4",
+      "status": "completed",
+      "face_count": 19695,
+      "speaker_count": 0,
+      "first_appearance": 206.76,
+      "last_appearance": 6756.68,
+      "confidence": 0.803
+    }
+  ]
+}
+```
+
+#### Response Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `file_uuid` | string | File identifier (full 32-char hex) |
+| `file_name` | string | Video file name |
+| `file_path` | string | Absolute path to video file |
+| `status` | string | Video processing status (`"completed"`, `"processing"`, etc.) |
+| `face_count` | int | Total face detections for this identity in this file |
+| `speaker_count` | int | Speaker segments (reserved, always `0`) |
+| `first_appearance` | float | First appearance time in seconds (computed from `frame_number / fps`) |
+| `last_appearance` | float | Last appearance time in seconds |
+| `confidence` | float | Average detection confidence |
+
+---
+
+### `GET /api/v1/identity/:identity_uuid/faces`
+
+**Auth**: Required
+**Scope**: identity-level
+
+Get all face detection records associated with this identity.
+
+#### Example
+
+```bash
+curl -s "$API/api/v1/identity/$IDENTITY_UUID/faces?page=1&page_size=20" -H "X-API-Key: $KEY"
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "identity_uuid": "c3545906c82d4b66aa1d150bc02decce",
+  "total": 19695,
+  "page": 1,
+  "page_size": 20,
+  "data": [
+    {
+      "id": 655704,
+      "file_uuid": "aeed71342a899fe4b4c57b7d41bcb692",
+      "frame_number": 5169,
+      "timestamp_secs": 206.76,
+      "face_id": "5169_0",
+      "bbox": {
+        "x": 706,
+        "y": 469,
+        "width": 618,
+        "height": 618
+      },
+      "confidence": 0.855
+    }
+  ]
+}
+```
+
+#### Response Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `id` | int64 | Face detection record ID |
+| `file_uuid` | string | File where face was detected |
+| `frame_number` | int64 | Frame number (primary coordinate) |
+| `timestamp_secs` | float | Time in seconds (computed as `frame_number / fps`) |
+| `face_id` | string | Face ID (format: `{frame_number}_{detection_index}`) |
+| `bbox` | object | Bounding box |
+| `bbox.x` | float | Left coordinate |
+| `bbox.y` | float | Top coordinate |
+| `bbox.width` | float | Width in pixels |
+| `bbox.height` | float | Height in pixels |
+| `confidence` | float | Detection confidence (0.0–1.0) |
+
+---
+
+### `GET /api/v1/identity/:identity_uuid/chunks`
+
+**Auth**: Required
+**Scope**: identity-level
+
+Get all text chunks (sentences) spoken while this identity's face was on screen. Useful for finding what a person said.
+
+#### Example
+
+```bash
+curl -s "$API/api/v1/identity/$IDENTITY_UUID/chunks" -H "X-API-Key: $KEY"
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "identity_uuid": "a9a901056d6b46ff92da0c3c1a57dff4",
+  "data": [
+    {
+      "id": 0,
+      "file_uuid": "bd80fec92b0b6963d177a2c55bf713e2",
+      "chunk_id": "bd80fec92b0b6963d177a2c55bf713e2_2",
+      "chunk_type": "sentence",
+      "start_frame": 5103,
+      "end_frame": 5127,
+      "fps": 24.0,
+      "start_time": 212.64,
+      "end_time": 213.64,
+      "text_content": "[213s-214s] Cary Grant: \"Olá!\""
+    }
+  ]
+}
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `file_uuid` | string | File identifier |
+| `chunk_id` | string | Sentence chunk identifier |
+| `start_frame` | integer | Frame-accurate start position |
+| `end_frame` | integer | Frame-accurate end position |
+| `fps` | float | Frames per second |
+| `start_time` | float | Start time in seconds |
+| `end_time` | float | End time in seconds |
+| `text_content` | string | Spoken text content |
+
+---
+
+### `POST /api/v1/identity/:identity_uuid/bind`
+
+**Auth**: Required
+**Scope**: identity-level
+
+Bind a face detection to an identity. Associates the face trace with the identity for future search and recognition.
+
+#### Request Parameters
+
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `file_uuid` | string | Yes | File where face is detected |
+| `face_id` | string | Yes | Face ID (format: `{frame}_{idx}`) |
+
+#### Example
+
+```bash
+curl -s -X POST "$API/api/v1/identity/$IDENTITY_UUID/bind" \
+  -H "X-API-Key: $KEY" \
+  -H "Content-Type: application/json" \
+  -d '{"file_uuid": "'"$FILE_UUID"'", "face_id": "1_5"}'
+```
+
+---
+
+### `POST /api/v1/identity/:identity_uuid/unbind`
+
+**Auth**: Required
+**Scope**: identity-level
+
+Unbind a face detection from an identity. Removes the identity association from the face record.
+
+---
+
+### `GET /api/v1/identities/search`
+
+**Auth**: Required
+**Scope**: identity-level
+
+Search identities by name (ILIKE search). Returns matching identity records.
+
+#### Example
+
+```bash
+curl -s "$API/api/v1/identities/search?q=Cary" -H "X-API-Key: $KEY"
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `name` | string | Identity name |
+| `source` | string | Identity source |
+| `tmdb_id` | integer | TMDb ID (if source = tmdb) |
+| `file_uuid` | string | Associated file |
+
+---
+
+---
+
+### `POST /api/v1/identity/upload`
+
+**Auth**: Required
+**Scope**: identity-level
+
+Upload an identity.json file to create or update an identity. Accepts the same format as the identity.json files stored on disk.
+
+If an identity with the same `identity_uuid` already exists, it will be updated with the new values.
+
+#### Request
+
+The request body is an `IdentityFile` object:
+
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `identity_uuid` | string | Yes | Identity identifier |
+| `name` | string | Yes | Identity display name |
+| `identity_type` | string | No | `"people"` or null |
+| `source` | string | No | `.json`, `auto`, `tmdb`, `user_defined`, or `merged` |
+| `status` | string | No | `"confirmed"`, `"pending"`, or `"inactive"` |
+| `tmdb_id` | integer | No | TMDb person ID |
+| `tmdb_profile` | string | No | TMDb profile image URL |
+| `metadata` | object | No | Arbitrary metadata JSON |
+| `file_bindings` | array | No | Array of `{ file_uuid, trace_ids, face_count }` (informational) |
+
+#### Example
+
+```bash
+curl -s -X POST "$API/api/v1/identity/upload" \
+  -H "X-API-Key: $KEY" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "version": 1,
+    "identity_uuid": "a9a901056d6b46ff92da0c3c1a57dff4",
+    "name": "Cary Grant",
+    "identity_type": "people",
+    "source": ".json",
+    "status": "confirmed",
+    "metadata": {},
+    "file_bindings": []
+  }'
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "identity_uuid": "a9a901056d6b46ff92da0c3c1a57dff4",
+  "name": "Cary Grant",
+  "message": "Identity uploaded successfully"
+}
+```
+
+---
+
+---
+
+### `POST /api/v1/identity/:identity_uuid/profile-image`
+
+**Auth**: Required
+**Scope**: identity-level
+
+Upload a profile image (JPEG or PNG) for an identity. The image is saved to `{output}/identities/{uuid}/profile.{ext}`.
+
+Uses `multipart/form-data` with field name `image`.
+
+#### Example
+
+```bash
+curl -s -X POST "$API/api/v1/identity/$IDENTITY_UUID/profile-image" \
+  -H "X-API-Key: $KEY" \
+  -F "image=@/path/to/photo.jpg"
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "identity_uuid": "a9a901056d6b46ff92da0c3c1a57dff4",
+  "path": "/path/to/output/identities/.../profile.jpg",
+  "message": "Profile image saved: profile.jpg"
+}
+```
+
+#### Error Responses
+
+| HTTP | When |
+|------|------|
+| `400` | Missing image field or unsupported format |
+| `404` | Identity not found |
+| `415` | Unsupported image type (use JPEG or PNG) |
+
+---
+
+### `GET /api/v1/identity/:identity_uuid/profile-image`
+
+**Auth**: Required
+**Scope**: identity-level
+
+Retrieve the profile image for an identity. Returns the raw image data with appropriate Content-Type header.
+
+```bash
+curl -s "$API/api/v1/identity/$IDENTITY_UUID/profile-image" \
+  -H "X-API-Key: $KEY" -o profile.jpg
+```
+
+| Response Header | Value |
+|----------------|-------|
+| `content-type` | `image/jpeg` or `image/png` |
+
+---
+
+## Alias System (BCP 47 Locale Tags)
+
+Identity aliases support multilingual display names. Aliases are stored in `metadata.aliases` as an array of `{locale, name}` objects.
+
+### BCP 47 Locale Tags Reference
+
+| Locale | Tag | Example |
+|--------|-----|---------|
+| English | `en` | John Smith |
+| Traditional Chinese | `zh-TW` | 約翰·史密斯 |
+| Simplified Chinese | `zh-CN` | 约翰·史密斯 |
+| Japanese | `ja` | ジョン・スミス |
+| Korean | `ko` | 존 스미스 |
+| Cantonese | `yue` | 約翰·史密夫 |
+| French | `fr` | John Smith (French spelling) |
+| Spanish | `es` | Juan Smith |
+| Arabic | `ar` | جون سميث |
+| Russian | `ru` | Джон Смит |
+| Thai | `th` | จอห์น สมิธ |
+
+BCP 47 is the IETF standard for language tags. Format: `language` (e.g. `en`, `ja`) or `language-Region` (e.g. `zh-TW`, `zh-CN`).
+
+### Frontend Display Logic
+
+```javascript
+function getDisplayName(identity, preferredLocale) {
+  const match = identity.metadata?.aliases?.find(a => a.locale === preferredLocale);
+  if (match) return match.name;
+  const lang = preferredLocale.split('-')[0];
+  const langMatch = identity.metadata?.aliases?.find(a => a.locale.startsWith(lang));
+  if (langMatch) return langMatch.name;
+  return identity.name;
+}
+```
+
+### Updating Aliases via PATCH
+
+```json
+PATCH /api/v1/identity/:identity_uuid
+{
+  "metadata": {
+    "aliases": [
+      {"locale": "en", "name": "John Smith"},
+      {"locale": "zh-TW", "name": "約翰·史密斯"}
+    ]
+  }
+}
+```
+
+---
+*Updated: 2026-05-22*
+
+

deliverable_v1.1.0/modules/08_identity_agent.md

@@ -0,0 +1,65 @@
+<!-- module: identity_agent -->
+<!-- description: Identity agent — match from photo, match from trace -->
+<!-- depends: 01_auth, 07_identity -->
+
+## Identity Agent
+
+### `POST /api/v1/agents/identity/match-from-photo`
+
+**Auth**: Required
+**Scope**: file-level
+
+Upload a face photo to match against known identities. Detects face via InsightFace, extracts 512D embedding via CoreML FaceNet, then searches pgvector for the closest identity.
+
+#### Request
+
+`multipart/form-data` with field `image` (JPEG/PNG) and optional `file_uuid`.
+
+#### Example
+
+```bash
+curl -s -X POST "$API/api/v1/agents/identity/match-from-photo" \
+  -H "Authorization: Bearer $JWT" \
+  -F "image=@/path/to/face.jpg" \
+  -F "file_uuid=$FILE_UUID"
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "matches": [
+    {
+      "identity_uuid": "a9a90105...",
+      "name": "Cary Grant",
+      "similarity": 0.87
+    }
+  ]
+}
+```
+
+---
+
+### `POST /api/v1/agents/identity/match-from-trace`
+
+**Auth**: Required
+**Scope**: file-level
+
+Match a face trace (tracked face across frames) against known identities. Samples 3 angles from the trace, generates embeddings, and searches pgvector.
+
+#### Request Parameters
+
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `file_uuid` | string | Yes | File containing the trace |
+| `trace_id` | integer | Yes | Face trace ID to match |
+
+#### Example
+
+```bash
+curl -s -X POST "$API/api/v1/agents/identity/match-from-trace" \
+  -H "Authorization: Bearer $JWT" \
+  -H "Content-Type: application/json" \
+  -d '{"file_uuid": "'"$FILE_UUID"'", "trace_id": 10}'
+```

deliverable_v1.1.0/modules/08_media.md

@@ -0,0 +1,317 @@
+<!-- module: media -->
+<!-- description: Video streaming & frame extraction -->
+<!-- depends: 01_auth -->
+
+## Video Streaming & Frame Extraction
+
+All video streaming endpoints support the following common query parameters:
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `mode` | string | No | `normal` | `normal` or `debug` (draws detection overlays) |
+| `audio` | string | No | `on` | `on` or `off` |
+
+---
+
+### `GET /api/v1/file/:file_uuid/video`
+
+Stream the full video file with range support for seeking.
+
+**Auth**: Required
+**Scope**: file-level
+
+#### Response
+
+- **200**: Video stream (`Content-Type` based on file extension)
+- **206**: Partial content (range request)
+- Supports `Range` header for seeking
+
+---
+
+### `GET /api/v1/file/:file_uuid/trace/:trace_id/video`
+
+Stream video with highlights for a specific face trace (follows a single person across frames with bounding box overlay).
+
+**Auth**: Required
+**Scope**: file-level
+
+---
+
+### `GET /api/v1/file/:file_uuid/trace/:trace_id/representative-face`
+
+Find the best single face to represent this trace. Uses a two-stage selection: SQL (area × confidence → top 10) then FFmpeg `blurdetect` (sharpness → pick the least blurry).
+
+**Auth**: Required
+**Scope**: file-level
+
+#### Example
+
+```bash
+curl -s "$API/api/v1/file/$FILE_UUID/trace/1939/representative-face" \
+  -H "X-API-Key: $KEY"
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "file_uuid": "aeed71342a899fe4b4c57b7d41bcb692",
+  "trace_id": 1939,
+  "face_count": 538,
+  "representative": {
+    "frame_number": 68193,
+    "timestamp_secs": 2727.72,
+    "bbox": { "x": 347, "y": 378, "width": 427, "height": 427 },
+    "confidence": 0.760,
+    "quality_score": 138516,
+    "blur_score": 9.46
+  }
+}
+```
+
+#### Response Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `trace_id` | integer | Face trace ID |
+| `face_count` | integer | Total face detections in this trace |
+| `representative.frame_number` | integer | Frame number of the selected face (primary coordinate) |
+| `representative.timestamp_secs` | float | Time in seconds (derived from `frame_number / fps`) |
+| `representative.bbox` | object | Bounding box `{x, y, width, height}` |
+| `representative.confidence` | float | Detection confidence (0.0–1.0) |
+| `representative.quality_score` | float | Pre-selection score (`area × confidence`) |
+| `representative.blur_score` | float | FFmpeg blurdetect result (lower = sharper) |
+
+#### Error Responses
+
+---
+
+### `GET /api/v1/file/:file_uuid/trace/:trace_id/thumbnail`
+
+Extract the best face image for a trace as JPEG (320×320). Internally selects the face using the same two-stage algorithm as `representative-face`, then crops via FFmpeg. The result is cacheable for 24 hours.
+
+**Auth**: Required
+**Scope**: file-level
+
+#### Example
+
+```bash
+curl -s "$API/api/v1/file/$FILE_UUID/trace/1939/thumbnail" \
+  -H "X-API-Key: $KEY" -o trace_1939_face.jpg
+```
+
+#### Response
+
+- **200**: `image/jpeg` binary data (320×320 cropped face)
+- **404**: File, trace not found, or no suitable face
+- **500**: FFmpeg or database error
+
+---
+
+### `GET /api/v1/file/:file_uuid/identities/:identity_uuid_a/co-occur-with/:identity_uuid_b`
+
+Find the first frame where two identities appear together, with representative face thumbnails for both.
+
+**Auth**: Required
+**Scope**: file-level
+
+#### Example
+
+```bash
+# Audrey Hepburn & Cary Grant 第一次同框
+curl -s "$API/api/v1/file/$FILE_UUID/identities/$AUDREY_UUID/co-occur-with/$CARY_UUID" \
+  -H "X-API-Key: $KEY" | jq '{identity_a: .identity_a.name, identity_b: .identity_b.name, first_frame: .first_cooccurrence.frame_number}'
+```
+
+#### Response (200)
+
+```json
+{
+  "success": true,
+  "file_uuid": "aeed71342a899fe4b4c57b7d41bcb692",
+  "identity_a": {
+    "identity_uuid": "c3545906-c82d-4b66-aa1d-150bc02decce",
+    "name": "Audrey Hepburn",
+    "trace_id": 920
+  },
+  "identity_b": {
+    "identity_uuid": "2b0ddefe-e2a9-4533-9308-b375594604d5",
+    "name": "Cary Grant",
+    "trace_id": 919
+  },
+  "first_cooccurrence": {
+    "frame_number": 38165,
+    "timestamp_secs": 1526.60,
+    "total_cooccurrence_frames": 3136,
+    "representative_face_a": {
+      "frame_number": 38199,
+      "bbox": { "x": 122, "y": 339, "width": 176, "height": 176 },
+      "confidence": 0.832,
+      "thumbnail_url": "/api/v1/file/aeed71342.../trace/920/thumbnail"
+    },
+    "representative_face_b": {
+      "frame_number": 38291,
+      "bbox": { "x": 511, "y": 315, "width": 192, "height": 192 },
+      "confidence": 0.791,
+      "thumbnail_url": "/api/v1/file/aeed71342.../trace/919/thumbnail"
+    }
+  }
+}
+```
+
+#### Response Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `identity_a.name` | string | First identity name |
+| `identity_b.name` | string | Second identity name |
+| `first_cooccurrence.frame_number` | int | First frame where both appear |
+| `first_cooccurrence.timestamp_secs` | float | Time in seconds |
+| `first_cooccurrence.total_cooccurrence_frames` | int | Total frames with both present |
+| `first_cooccurrence.representative_face_a/b` | object | Best face thumbnail data for each identity |
+
+#### Error Responses
+
+| HTTP | When |
+|------|------|
+| `404` | File or identity not found |
+| `404` | The two identities never co-occur in this file |
+| `500` | Database or FFmpeg error |
+
+### `GET /api/v1/file/:file_uuid/video/bbox`
+
+Stream video with bounding box overlay for all detected objects/faces.
+
+**Auth**: Required
+**Scope**: file-level
+
+Uses a built-in 5×7 bitmap font renderer to draw labels directly on video frames via FFmpeg `drawtext` filter.
+
+---
+
+### `GET /api/v1/file/:file_uuid/thumbnail`
+
+Extract a single frame from a video as JPEG image. Uses FFmpeg `select` filter.
+
+**Auth**: Required
+**Scope**: file-level
+
+#### Query Parameters
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `frame` | integer | Yes | — | Zero-based frame number to extract |
+| `x` | integer | No | — | Crop start X (left edge). Requires `y`, `w`, `h`. |
+| `y` | integer | No | — | Crop start Y (top edge). Requires `x`, `w`, `h`. |
+| `w` | integer | No | — | Crop width in pixels. Requires `x`, `y`, `h`. |
+| `h` | integer | No | — | Crop height in pixels. Requires `x`, `y`, `w`. |
+
+All four crop params (`x`, `y`, `w`, `h`) must be provided together or omitted.
+
+#### Example
+
+```bash
+# Extract frame 1000 (full frame)
+curl -s "$API/api/v1/file/bd80fec92b0b6963d177a2c55bf713e2/thumbnail?frame=1000" \
+  -H "Authorization: Bearer $JWT" -o frame_1000.jpg
+
+# Extract and crop face region (x=320, y=240, w=160, h=160)
+curl -s "$API/api/v1/file/bd80fec92b0b6963d177a2c55bf713e2/thumbnail?frame=1000&x=320&y=240&w=160&h=160" \
+  -H "Authorization: Bearer $JWT" -o face_crop.jpg
+```
+
+#### Response
+
+- **200**: `image/jpeg` binary data
+- **404**: File not found
+- **500**: FFmpeg error (e.g., frame number exceeds video duration)
+
+### `GET /api/v1/file/:file_uuid/clip`
+
+Extract a video clip (time range) as MPEG-TS stream. Uses FFmpeg `-ss` fast seek.
+
+**Auth**: Required
+**Scope**: file-level
+
+#### Query Parameters
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `start_frame` | integer | No* | — | Start frame (zero-based). **Frame-accurate** — use this for precision. |
+| `end_frame` | integer | No* | — | End frame (zero-based, inclusive). Requires `start_frame`. |
+| `start_time` | float | No* | — | Start time in seconds. Approximate (FPS-dependent). Fallback if frames not given. |
+| `end_time` | float | No* | — | End time in seconds. Approximate (FPS-dependent). Fallback if frames not given. |
+| `fps` | float | No | video FPS | Override frames-per-second for frame↔time calculation. Defaults to video's detected FPS. |
+| `mode` | string | No | `normal` | `normal` or `debug` (draws "CLIP" overlay) |
+| `audio` | string | No | `on` | `on` or `off` |
+
+Either (`start_frame`+`end_frame`) OR (`start_time`+`end_time`) must be provided.
+
+#### Example
+
+```bash
+# Clip by frame range (primary)
+curl -s "$API/api/v1/file/bd80fec92b0b6963d177a2c55bf713e2/clip?start_frame=0&end_frame=47" \
+  -H "Authorization: Bearer $JWT" -o clip.ts
+
+# Clip by time range (fallback)
+curl -s "$API/api/v1/file/bd80fec92b0b6963d177a2c55bf713e2/clip?start_time=30&end_time=45" \
+  -H "Authorization: Bearer $JWT" -o clip.ts
+```
+
+#### Response
+
+- **200**: `video/mp2t` MPEG-TS stream
+- **400**: Missing/invalid range parameters
+- **404**: File not found
+- **500**: FFmpeg error
+
+#### Technical Notes
+
+| Detail | Value |
+|--------|-------|
+| **Backend** | FFmpeg (`ffmpeg-full`) |
+| **Seek** | `-ss` before `-i` (fast keyframe seek) |
+| **Format** | MPEG-TS (`mpegts` muxer, pipe-safe) |
+| **Codec** | H.264 + AAC |
+| **Cache** | `Cache-Control: public, max-age=86400` (24h) |
+
+### Video vs Clip: Quality & Format Comparison
+
+Both endpoints support time range extraction, but serve different use cases:
+
+| Feature | `/video` | `/clip` |
+|---------|----------|---------|
+| **No params** | Streams full file (Range seek) | Returns 400 (params required) |
+| **HTTP Range** | ✅ Supported | ❌ Not supported |
+| **Encoding** | `-c copy` (zero encoding) | `-c:v libx264 -c:a aac` (re-encode) |
+| **Quality** | Original (bit-exact, zero loss) | Compressed (default CRF ≈ 23) |
+| **Format** | `video/mp4` | `video/mp2t` (MPEG-TS) |
+| **Speed** | Fast (no computation) | Slower (encoding required) |
+| **Frame control** | Time-based (`dur = (ef-sf)/fps`) | Precise (`-vframes`) |
+| **Debug mode** | ❌ | ✅ `mode=debug` overlay |
+| **Cache** | ❌ | ✅ `max-age=86400` |
+
+#### Usage Recommendation
+
+| Scenario | Use |
+|----------|-----|
+| Full video streaming / player seek | `/video` |
+| Quick preview clip (zero quality loss) | `/video?start_frame=...&end_frame=...` |
+| Debug frame verification / text overlay | `/clip?mode=debug` |
+| Precise frame count control | `/clip` |
+| CDN cacheable clip | `/clip` |
+
+---
+
+| Detail | Value |
+|--------|-------|
+| **Backend** | FFmpeg (`ffmpeg-full`) |
+| **Filter** | `select=eq(n\,FRAME)` to select frame, optional `crop=W:H:X:Y` |
+| **Output** | Single JPEG via pipe (`image2pipe`, `mjpeg` codec) |
+| **Cache** | `Cache-Control: public, max-age=86400` (24h) |
+| **Frame number** | Zero-based (`frame=0` = first frame of video) |
+
+---
+*Updated: 2026-05-19 12:49:24*

deliverable_v1.1.0/modules/09_tmdb.md

@@ -0,0 +1,109 @@
+<!-- module: tmdb -->
+<!-- description: TMDb enrichment endpoints — prefetch, probe, resource, check -->
+<!-- depends: 01_auth, 03_register -->
+
+## TMDb Enrichment
+
+> **Offline operation**: TMDb prefetch now checks local identity files first (`identities/_index.json` + `*.tmdb.json`).
+> If local files exist, no external API call is made. Internet is only needed for initial data seeding.
+
+### Overview
+
+TMDb enrichment is an optional identity enrichment step that can be run after Pipeline face detection completes. The workflow is:
+
+1. **Prefetch** (requires internet): Download movie cast data from TMDb API → cache to `{file_uuid}.tmdb.json`
+2. **Probe**: Read local cache → create identities for **all** cast members (`source='tmdb'`) + save `identity.json` + download profile image to `{OUTPUT}/identities/{uuid}/profile.jpg`
+3. **Match**: The worker automatically matches video faces against TMDb identities when `MOMENTRY_TMDB_PROBE_ENABLED=true`
+
+### `POST /api/v1/agents/tmdb/prefetch`
+
+**Auth**: Required
+**Scope**: file-level
+
+Fetch TMDb cast data for a registered file and cache it locally. This is the only step requiring internet access.
+
+#### Request Parameters
+
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `file_uuid` | string | Yes | File UUID to enrich |
+
+#### Example
+
+```bash
+curl -s -X POST "$API/api/v1/agents/tmdb/prefetch" \
+  -H "Content-Type: application/json" \
+  -H "X-API-Key: $KEY" \
+  -d '{"file_uuid": "'"$FILE_UUID"'"}'
+```
+
+#### Response (200)
+
+```json
+{"success": true, "file_uuid": "...", "cache_path": "/output/...tmdb.json"}
+```
+
+### `POST /api/v1/file/:file_uuid/tmdb-probe`
+
+**Auth**: Required
+**Scope**: file-level
+
+Read local TMDb cache and create/update identities. Requires prefetch to have been run first.
+
+#### Example
+
+```bash
+curl -s -X POST "$API/api/v1/file/$FILE_UUID/tmdb-probe" \
+  -H "X-API-Key: $KEY" | jq '{identities_created, movie_title}'
+```
+
+#### Response (200 — identities created)
+
+```json
+{"success": true, "identities_created": 15, "movie_title": "Charade"}
+```
+
+#### Response (200 — no cache)
+
+```json
+{"success": false, "message": "No TMDb cache found. Run tmdb-prefetch first."}
+```
+
+### `GET /api/v1/resource/tmdb`
+
+**Auth**: Required
+**Scope**: system-level
+
+View TMDb resource status including configuration, identity counts, and cache file count.
+
+#### Example
+
+```bash
+curl -s "$API/api/v1/resource/tmdb" -H "X-API-Key: $KEY" \
+  | jq '{identities_seeded, cache_files}'
+```
+
+### `POST /api/v1/resource/tmdb/check`
+
+**Auth**: Required
+**Scope**: system-level
+
+Ping the TMDb API to verify connectivity and measure latency.
+
+#### Example
+
+```bash
+curl -s -X POST "$API/api/v1/resource/tmdb/check" \
+  -H "X-API-Key: $KEY" | jq '.status'
+```
+
+#### Response
+
+```json
+{
+  "api_key_configured": true,
+  "enabled": false,
+  "api_reachable": true,
+  "api_latency_ms": 120
+}
+```

deliverable_v1.1.0/modules/10_pipeline.md

@@ -0,0 +1,178 @@
+<!-- module: pipeline -->
+<!-- description: Pipeline processors, ingestion status, stats endpoints -->
+<!-- depends: 01_auth -->
+
+## Pipeline
+
+### Dependency Graph
+
+```mermaid
+flowchart TB
+    subgraph Processors["10 Processors"]
+        Cut[Cut] --> ASR[ASR]
+        ASR --> ASRX[ASRX]
+        ASRX --> Story[Story]
+        Cut --> Story
+        YOLO[YOLO] --> VisualChunk[VisualChunk]
+        VisualChunk --> Story
+        Face[Face] --> Story
+        Story --> FiveW1H[5W1H]
+        OCR[OCR]
+        Pose[Pose]
+    end
+
+    subgraph Ingestion["入庫 (Post-Processing)"]
+        ASR --> Rule1[Rule 1 Sentence]
+        ASRX --> Rule1
+        Rule1 --> Vectorize[Auto-Vectorize]
+        Rule1 --> Phase1[Phase 1 Pack]
+
+        Cut --> Rule3[Rule 3 Scene]
+        ASR --> Rule3
+
+        Face --> Trace[Face Trace]
+        Trace --> Qdrant[Qdrant Sync]
+        Trace --> TraceChunks[Trace Chunks]
+        Trace --> TKG[TKG Builder]
+
+        Face --> TMDbMatch[TMDb Match]
+        Face --> SceneMeta[Scene Metadata]
+        YOLO --> SceneMeta
+        Face --> IdentityAgent[Identity Agent]
+        ASRX --> IdentityAgent
+
+        Cut --> Agent5W1H[5W1H Agent]
+        ASR --> Agent5W1H
+        Agent5W1H --> Phase2[Phase 2 Pack]
+    end
+
+    style Processors fill:#1a1a2e,stroke:#e94560
+    style Ingestion fill:#16213e,stroke:#0f3460
+```
+
+### Pipeline Completion Flow
+
+The pipeline is **not complete** until both the 10 processors AND the 入庫 (ingestion) steps have finished. The worker polls every 3 seconds and only marks the job as `completed` when all ingestion steps verify OK.
+
+```
+10 processors done
+     ↓  (job status stays "running")
+Algorithm 1 Trigger: Rule 1 + Vectorize + Phase 1 Pack
+     ↓  (job runs in parallel)
+Algorithm 2 Trigger: Face Trace → TKG, Scene Metadata, Identity Agent, 5W1H Agent
+     ↓  (poll checks every 3s)
+Ingestion verification: rule1 ✓ vectorize ✓ rule3 ✓ face_trace ✓ tkg ✓ scene_meta ✓ 5w1h ✓
+     ↓
+job status = "completed"
+```
+
+### 10 Processor Stages
+
+| # | Processor | Depends On | Description |
+|---|-----------|------------|-------------|
+| 1 | `Cut` | — | Scene boundary detection (PySceneDetect) |
+| 2 | `ASR` | Cut | Automatic speech recognition (faster-whisper) |
+| 3 | `ASRX` | ASR | Speaker diarization + ASR refinement |
+| 4 | `YOLO` | — | Object detection (YOLOv8) |
+| 5 | `OCR` | — | Optical character recognition |
+| 6 | `Face` | — | Face detection + recognition (InsightFace + CoreML) |
+| 7 | `Pose` | — | Pose estimation |
+| 8 | `VisualChunk` | YOLO | Visual object chunking |
+| 9 | `Story` | ASRX + Cut + YOLO + Face | Narrative scene summarization (LLM, with embedding) |
+| 10 | `5W1H` | Story | Who/What/When/Where/Why extraction (LLM, with embedding) |
+
+### 入庫 (Post-Processing / Ingestion)
+
+These steps run after the 10 processors and are **required for pipeline completion**. The worker checks all of them before marking the job as done.
+
+| # | Step | Triggers When | Verification |
+|---|------|--------------|-------------|
+| 1 | **Rule 1 Sentence Chunking** | ASR + ASRX done | `chunk` table has rows with `chunk_type = 'sentence'` |
+| 2 | **Auto-Vectorize** | Rule 1 done | `chunk.embedding` IS NOT NULL for sentence chunks |
+| 3 | **Phase 1 Pack** | Rule 1 done | `release_pack.py --phase 1` executed |
+| 4 | **Rule 3 Scene Chunking** | All 10 processors done + Cut + ASR | `chunk` table has rows with `chunk_type = 'cut'` |
+| 5 | **Face Trace** | All 10 processors done + Face | `face_detections.trace_id` IS NOT NULL |
+| 6 | **Qdrant Face Sync** | Face Trace done | Qdrant face_embedding collection populated |
+| 7 | **Trace Chunks** | Face Trace done | `chunk` table has rows with `chunk_type = 'trace'` |
+| 8 | **TKG Builder** | Face Trace done | `tkg_nodes` + `tkg_edges` tables have rows |
+| 9 | **TMDb Face Matching** | TMDb enabled + Face done | `face_detections.identity_id` IS NOT NULL |
+| 10 | **Heuristic Scene Metadata** | Face + YOLO done | `{file_uuid}.scene_meta.json` exists on disk |
+| 11 | **Identity Agent** | Face + ASRX done | `identities` with `source = 'identity_agent'` |
+| 12 | **5W1H Agent** | Cut + ASR done | `chunk.summary_text` IS NOT NULL for cut chunks |
+| 13 | **Release Pack** | 5W1H Agent done | `release_pack.py --phase 2` executed |
+
+### Ingestion Status
+
+Check real-time ingestion status for a file:
+
+```bash
+curl "$API/api/v1/stats/ingestion-status/{file_uuid}"
+```
+
+Returns per-step `done` / `pending` status with detail counts.
+
+#### Example
+
+```bash
+curl "http://localhost:3003/api/v1/stats/ingestion-status/bd80fec9c42afb0307eb28f22c64c76a" | jq '.steps[] | {name, status, detail}'
+```
+
+#### Response
+
+```json
+{
+  "file_uuid": "bd80fec9c42afb0307eb28f22c64c76a",
+  "steps": [
+    { "name": "rule1_sentence", "status": "pending", "detail": "0 sentence chunks" },
+    { "name": "auto_vectorize",  "status": "pending", "detail": "0 embedded" },
+    { "name": "rule3_scene",     "status": "pending", "detail": "0 scene chunks" },
+    { "name": "face_trace",      "status": "pending", "detail": "0 traces" },
+    { "name": "trace_chunks",    "status": "pending", "detail": "0 trace chunks" },
+    { "name": "tkg",             "status": "pending", "detail": "0 nodes, 0 edges" },
+    { "name": "identity_match",  "status": "pending", "detail": "0 identities" },
+    { "name": "scene_metadata",  "status": "pending", "detail": null },
+    { "name": "5w1h",            "status": "pending", "detail": "0 scenes with 5W1H" }
+  ]
+}
+```
+
+### Stats Endpoints
+
+| Method | Endpoint | Auth | Description |
+|--------|----------|------|-------------|
+| GET | `/api/v1/stats/sftpgo` | No | SFTPGo service status |
+| GET | `/api/v1/stats/ingestion-status/:file_uuid` | No | Per-file ingestion checklist |
+
+### Configuration
+
+### `POST /api/v1/config/cache`
+
+**Auth**: Required
+**Scope**: system-level
+
+Toggle the Redis cache on or off.
+
+#### Request Parameters
+
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `enabled` | boolean | Yes | `true` to enable, `false` to disable |
+
+#### Example
+
+```bash
+curl -s -X POST "$API/api/v1/config/cache" \
+  -H "Content-Type: application/json" \
+  -H "X-API-Key: $KEY" \
+  -d '{"enabled": false}'
+```
+
+### Unmounted Routes
+
+The following routes are defined in source code but are **NOT** currently mounted in the router:
+
+| Endpoint | Source file |
+|----------|-------------|
+| `/api/v1/search/persons` | `universal_search.rs` (not mounted) |
+| `/api/v1/who` | `who.rs` |
+| `/api/v1/who/candidates` | `who.rs` |

deliverable_v1.1.0/modules/11_error_codes.md

@@ -0,0 +1,57 @@
+<!-- module: error_codes -->
+<!-- description: Standard API error codes -->
+<!-- depends: -->
+
+## Error Response Format
+
+All API errors follow this JSON structure:
+
+```json
+{
+  "success": false,
+  "error": {
+    "code": "E001_NOT_FOUND",
+    "message": "Resource not found",
+    "details": {"resource": "file_uuid", "value": "abc"}
+  }
+}
+```
+
+## Error Code List
+
+### Generic Errors (E0xx)
+
+| Code | HTTP | Description |
+|------|------|-------------|
+| `E001_NOT_FOUND` | 404 | Resource not found (file, identity, chunk) |
+| `E002_DUPLICATE` | 409 | Resource already exists |
+| `E003_VALIDATION` | 400 | Request parameter validation failed |
+| `E004_UNAUTHORIZED` | 401 | Invalid API key or token |
+| `E005_INTERNAL` | 500 | Internal server error |
+
+### Processor Errors (E1xx)
+
+| Code | HTTP | Description |
+|------|------|-------------|
+| `E101_PROCESSOR_FAIL` | 500 | Python script execution failed |
+| `E102_TIMEOUT` | 504 | Processing timeout |
+| `E103_RESUME_FAIL` | 500 | Resume failed (checkpoint not found) |
+| `E104_NO_VIDEO` | 400 | Video file path not found |
+
+### Identity Errors (E2xx)
+
+| Code | HTTP | Description |
+|------|------|-------------|
+| `E201_FACE_NOT_FOUND` | 404 | Face detection not found |
+| `E202_MERGE_CONFLICT` | 409 | Identity merge conflict |
+| `E203_CANDIDATE_EMPTY` | 404 | No candidates available for confirmation |
+
+### TMDb Errors (E3xx)
+
+| Code | HTTP | Description |
+|------|------|-------------|
+| `E301_TMDB_NO_KEY` | 400 | `TMDB_API_KEY` environment variable not set |
+| `E302_TMDB_UNREACHABLE` | 502 | TMDb API unreachable or timed out |
+| `E303_TMDB_CACHE_NOT_FOUND` | 200 | No local TMDb cache; run prefetch first |
+| `E304_TMDB_PROBE_FAILED` | 500 | TMDb probe execution failed |
+| `E305_TMDB_MOVIE_NOT_FOUND` | 404 | No matching TMDb movie found from filename |

deliverable_v1.1.0/modules/12_agent.md

@@ -0,0 +1,118 @@
+# Agent Endpoints
+
+Agent endpoints provide AI-powered capabilities including translation, identity analysis, and 5W1H extraction.
+
+## POST /api/v1/agents/translate
+
+Translate text between languages using Gemma4 (llama.cpp, port 8082).
+
+### Request
+
+```json
+{
+  "text": "Hello, welcome to Momentry Core.",
+  "target_language": "Traditional Chinese",
+  "source_language": "English"
+}
+```
+
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `text` | string | ✅ | Text to translate |
+| `target_language` | string | ✅ | Target language name (e.g. "Traditional Chinese", "Japanese") |
+| `source_language` | string | ❌ | Source language (default: "auto") |
+
+### Response
+
+```json
+{
+  "success": true,
+  "translated_text": "您好，歡迎使用 Momentry Core。",
+  "source_language_detected": "English",
+  "model_used": "google_gemma-4-26B-A4B-it-Q5_K_M.gguf"
+}
+```
+
+### Supported Language Pairs (tested)
+
+| Source | Target | Quality |
+|--------|--------|---------|
+| English | Traditional Chinese | ✅ |
+| English | Japanese | ✅ |
+| Chinese | English | ✅ |
+| English | French | ✅ |
+| Chinese | Japanese | ✅ |
+
+### Model
+
+- **Model**: Gemma4 26B (Q5_K_M)
+- **Engine**: llama.cpp at `localhost:8082`
+- **Endpoint**: `/v1/chat/completions` (OpenAI-compatible)
+- **Temperature**: 0.1
+- **Max tokens**: 1024
+
+### Errors
+
+| Status | Condition |
+|--------|-----------|
+| 500 | LLM unreachable or response parse failure |
+| 401 | Missing/invalid auth |
+
+---
+
+## POST /api/v1/agents/5w1h/analyze
+
+Extract 5W1H (Who, What, When, Where, Why, How) from a scene. Uses Gemma4 LLM on port 8082.
+
+### Request
+
+```json
+{
+  "file_uuid": "3abeee81d94597629ed8cb943f182e94",
+  "scene_id": 42
+}
+```
+
+### Response
+
+```json
+{
+  "success": true,
+  "5w1h": {
+    "who": ["Cary Grant"],
+    "what": ["discussing plans"],
+    "when": ["1963"],
+    "where": ["Paris"],
+    "why": ["vacation"],
+    "how": ["in person"]
+  }
+}
+```
+
+## POST /api/v1/agents/5w1h/batch
+
+Batch analyze all scenes in a file for 5W1H extraction. Uses the pipeline's `parent_chunk_5w1h.py --mode llm`.
+
+### Request
+
+```json
+{
+  "file_uuid": "3abeee81d94597629ed8cb943f182e94"
+}
+```
+
+## GET /api/v1/agents/5w1h/status
+
+Get status of the 5W1H agent pipeline for a file.
+
+---
+
+## Embedding Model
+
+| Detail | Value |
+|--------|-------|
+| **Model** | EmbeddingGemma-300m |
+| **Endpoint** | `POST /v1/embeddings` on port 11436 |
+| **Dimension** | 768 |
+| **Used by** | `parent_chunk_5w1h.py --embed`, story, 5W1H, search |
+

deliverable_v1.1.0/modules/_template.md

@@ -0,0 +1,63 @@
+# {Module Name} — API Workspace Module
+
+> Use this template when adding or editing API endpoint documentation modules.
+
+## Module Metadata
+
+Every module MUST start with:
+
+```markdown
+<!-- module: <short_name> -->
+<!-- description: One-line description of what this module covers -->
+<!-- depends: <comma-separated list of dependency module names> -->
+```
+
+## Endpoint Template
+
+Each endpoint MUST use this structure:
+
+### `METHOD /path/to/endpoint`
+
+**Auth**: Required / Optional / Public
+
+**Scope**: file-level / identity-level / system-level
+
+#### Request Parameters
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `param1` | string | Yes | — | Description |
+
+#### Example
+
+```bash
+# brief description of what this example demonstrates
+curl -s -X METHOD "$API/path" \
+  -H "X-API-Key: $KEY" \
+  -H "Content-Type: application/json" \
+  -d '{"param1": "value"}'
+```
+
+#### Response (200)
+
+```json
+{ "success": true }
+```
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `success` | boolean | Always true on 200 |
+
+#### Error Codes
+
+| Code | HTTP | When |
+|------|------|------|
+| E0xx | 4xx | Description |
+
+## Rules
+
+1. Each module file covers ONE topic group (e.g., `09_tmdb.md` = all TMDb endpoints)
+2. Use `$API` and `$KEY` in all curl examples
+3. Use `$FILE_UUID`, `$IDENTITY_UUID` variables for UUID examples
+4. Module filename = `NN_topic.md` (NN = execution order, 01-99)
+5. `depends` metadata = which modules must be assembled before this one

deliverable_v1.1.0/scripts/build_docs.py

@@ -0,0 +1,225 @@
+#!/opt/homebrew/bin/python3.11
+"""Build HTML documentation from module source files."""
+import os, markdown, re, glob, shutil
+
+MODULES_DIR = os.path.join(os.path.dirname(__file__), "..", "docs_v1.0", "API_WORKSPACE", "modules")
+DOC_DIR = os.path.join(os.path.dirname(__file__), "..", "docs_v1.0", "doc")
+DOC_DEV_DIR = os.path.join(os.path.dirname(__file__), "..", "docs_v1.0", "doc_developer")
+
+# User-facing modules (no developer content)
+USER_MODULES = {
+    "01_auth", "02_health", "03_register", "04_lookup", "05_process",
+    "06_search", "07_identity", "08_identity_agent", "08_media",
+    "09_tmdb", "10_pipeline", "12_agent",
+}
+
+
+def md_to_html(md_text: str) -> str:
+    """Convert Markdown to HTML."""
+    html = markdown.markdown(md_text, extensions=['fenced_code', 'tables', 'codehilite'])
+    # Wrap tables
+    html = re.sub(r'<table>', '<table class="table">', html)
+    return html
+
+def build_index(files, dev=False):
+    """Build index.html."""
+    links = []
+    for fname in sorted(files):
+        name = os.path.splitext(fname)[0]
+        label = MODULE_LABELS.get(name, name.replace("_", " ").title())
+        if "｜" in label:
+            cn, en = label.split("｜", 1)
+        else:
+            cn, en = label, ""
+        html_name = fname.replace(".md", ".html")
+        links.append(f'<tr onclick="window.location=\'{html_name}\'" style="cursor:pointer"><td class="cn">{cn}</td><td class="en">{en}</td></tr>')
+    
+    title = "Momentry API 開發者文件" if dev else "Momentry API 文件"
+    subtitle = "開發者專用" if dev else "API 參考手冊 — 登入後可瀏覽各模組文件"
+    
+    return f"""<!DOCTYPE html>
+<html lang="zh-TW">
+<head>
+<meta charset="UTF-8">
+<title>{title}</title>
+<style>
+* {{ margin: 0; padding: 0; box-sizing: border-box; }}
+body {{ font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }}
+.container {{ max-width: 900px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }}
+h1 {{ font-size: 28px; margin-bottom: 8px; }}
+p.subtitle {{ color: #666; margin-bottom: 24px; }}
+table {{ width: 100%; border-collapse: collapse; }}
+tr {{ border-bottom: 1px solid #eee; }}
+tr:last-child {{ border: none; }}
+td {{ padding: 10px 0; }}
+td.cn {{ width: 140px; font-weight: 600; color: #333; }}
+td.en {{ color: #666; font-size: 14px; }}
+a {{ color: #0066cc; text-decoration: none; display: block; }}
+a:hover td {{ background: #f8f8f8; border-radius: 4px; }}
+</style>
+</head>
+<body>
+<div class="container">
+<h1>{title}</h1>
+<p class="subtitle">{subtitle}</p>
+<table>{"".join(links)}</table>
+</div>
+</body>
+</html>"""
+
+MODULE_LABELS = {
+    "01_auth": "安全認證｜Authentication",
+    "02_health": "健康檢查｜Health",
+    "03_register": "檔案註冊｜File Registration",
+    "04_lookup": "檔案屬性查詢｜File Lookup",
+    "05_process": "處理流程｜Processing",
+    "06_search": "搜尋功能｜Search",
+    "07_identity": "身份識別｜Identity",
+    "08_identity_agent": "智能身份綁定｜Smart Identity Binding",
+    "08_media": "串流與截圖｜Streaming & Thumbnails",
+    "09_tmdb": "TMDb 整合｜TMDb Integration",
+    "10_pipeline": "生產線｜Pipeline",
+    "11_error_codes": "錯誤碼｜Error Codes",
+    "12_agent": "智慧代理｜AI Agents",
+}
+
+def build_html(md_text: str, title: str) -> str:
+    """Wrap MD content in HTML page."""
+    content = md_to_html(md_text)
+    return f"""<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>{title} - Momentry API Docs</title>
+<style>
+* {{ margin: 0; padding: 0; box-sizing: border-box; }}
+body {{ font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; color: #333; padding: 40px; }}
+.container {{ max-width: 960px; margin: 0 auto; background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; }}
+h1 {{ font-size: 24px; margin: 24px 0 12px; }}
+h2 {{ font-size: 20px; margin: 20px 0 10px; color: #222; }}
+h3 {{ font-size: 16px; margin: 16px 0 8px; color: #444; }}
+p {{ line-height: 1.6; margin: 8px 0; }}
+table {{ border-collapse: collapse; width: 100%; margin: 12px 0; font-size: 14px; }}
+th, td {{ border: 1px solid #ddd; padding: 8px 12px; text-align: left; }}
+th {{ background: #f0f0f0; font-weight: 600; }}
+code {{ background: #f0f0f0; padding: 2px 6px; border-radius: 3px; font-size: 13px; }}
+pre {{ background: #f8f8f8; border: 1px solid #ddd; border-radius: 6px; padding: 12px; overflow-x: auto; margin: 12px 0; }}
+pre code {{ background: none; padding: 0; }}
+a {{ color: #0066cc; }}
+.back {{ display: inline-block; margin-bottom: 20px; color: #666; }}
+.back:hover {{ color: #333; }}
+</style>
+</head>
+<body>
+<div class="container">
+<a class="back" href="index.html">&larr; Back to index</a>
+{content}
+</div>
+</body>
+</html>"""
+
+def login_page() -> str:
+    return """<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<title>Login - Momentry Docs</title>
+<style>
+* { margin: 0; padding: 0; box-sizing: border-box; }
+body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: #f5f5f5; display: flex; justify-content: center; align-items: center; height: 100vh; }
+.card { background: white; border-radius: 12px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 40px; width: 360px; }
+h1 { font-size: 24px; margin-bottom: 24px; text-align: center; }
+input { width: 100%; padding: 10px 12px; margin-bottom: 12px; border: 1px solid #ddd; border-radius: 6px; font-size: 14px; }
+button { width: 100%; padding: 10px; background: #0066cc; color: white; border: none; border-radius: 6px; font-size: 16px; cursor: pointer; }
+button:hover { background: #0052a3; }
+.error { color: #cc0000; font-size: 13px; margin-bottom: 12px; display: none; }
+</style>
+</head>
+<body>
+<div class="card">
+<h1>Momentry Docs</h1>
+<form id="loginForm">
+<input type="text" id="username" placeholder="Username" value="demo" required>
+<input type="password" id="password" placeholder="Password" value="demo" required>
+<div class="error" id="error">Invalid credentials</div>
+<button type="submit">Login</button>
+</form>
+</div>
+<script>
+document.getElementById('loginForm').onsubmit = async function(e) {
+    e.preventDefault();
+    const resp = await fetch('/api/v1/auth/login', {
+        method: 'POST',
+        headers: {'Content-Type': 'application/json'},
+        body: JSON.stringify({
+            username: document.getElementById('username').value,
+            password: document.getElementById('password').value
+        })
+    });
+    if (resp.ok) {
+        window.location.href = '/doc/index.html';
+    } else {
+        document.getElementById('error').style.display = 'block';
+    }
+};
+</script>
+</body>
+</html>"""
+
+def main():
+    # Clean and recreate doc dirs
+    for d in [DOC_DIR, DOC_DEV_DIR]:
+        if os.path.exists(d):
+            shutil.rmtree(d)
+        os.makedirs(d)
+    
+    md_files = sorted(glob.glob(os.path.join(MODULES_DIR, "*.md")))
+    if not md_files:
+        print(f"No MD files found in {MODULES_DIR}")
+        return
+    
+    user_html = []
+    dev_html = []
+    for md_path in md_files:
+        with open(md_path) as f:
+            md_text = f.read()
+        fname = os.path.basename(md_path)
+        stem = os.path.splitext(fname)[0]
+        
+        # Skip template
+        if stem == "_template":
+            continue
+            
+        # Skip error codes (developer-only)
+        if stem == "11_error_codes":
+            dev_only = True
+        else:
+            dev_only = stem not in USER_MODULES
+        
+        title = stem.replace("_", " ").title()
+        html = build_html(md_text, title)
+        
+        if dev_only:
+            out_path = os.path.join(DOC_DEV_DIR, fname.replace(".md", ".html"))
+            with open(out_path, "w") as f:
+                f.write(html)
+            dev_html.append(fname)
+            print(f"  [dev] {fname}")
+        else:
+            out_path = os.path.join(DOC_DIR, fname.replace(".md", ".html"))
+            with open(out_path, "w") as f:
+                f.write(html)
+            user_html.append(fname)
+            print(f"  [doc] {fname}")
+    
+    # Build indexes + login page
+    for d, files, label in [(DOC_DIR, user_html, "User"), (DOC_DEV_DIR, dev_html, "Dev")]:
+        index = build_index(files)
+        with open(os.path.join(d, "index.html"), "w") as f:
+            f.write(index)
+        with open(os.path.join(d, "login.html"), "w") as f:
+            f.write(login_page())
+        print(f"  {label}: {len(files)} pages -> {d}")
+
+if __name__ == "__main__":
+    main()

deliverable_v1.1.0/scripts/sync_dev_to_public.sh

@@ -0,0 +1,148 @@
+#!/bin/bash
+# sync_dev_to_public.sh — 比對 dev/public schema，同步 pipeline 資料
+# Usage: ./sync_dev_to_public.sh [check|sync] [file_uuid]
+
+PSQL="/opt/homebrew/opt/libpq/bin/psql"
+
+set -euo pipefail
+
+SCHEMA="${MOMENTRY_DB_SCHEMA:-dev}"
+DB_URL="${DATABASE_URL:-postgres://accusys@localhost:5432/momentry}"
+MODE="${1:-check}"
+FILE_UUID="${2:-}"
+
+TABLES=("videos" "chunk" "face_detections" "processor_results" "monitor_jobs"
+        "identities" "identity_bindings" "tkg_nodes" "tkg_edges")
+
+TARGET="public"
+
+if [ -z "$FILE_UUID" ]; then
+    echo "Usage: $0 [check|sync] <file_uuid>"
+    echo ""
+    echo "Examples:"
+    echo "  $0 check bd80fec92b0b6963d177a2c55bf713e2"
+    echo "  $0 sync  bd80fec92b0b6963d177a2c55bf713e2"
+    exit 1
+fi
+
+echo "=== Schema Sync: $SCHEMA → $TARGET ==="
+echo "File UUID: $FILE_UUID"
+echo "Mode: $MODE"
+echo ""
+
+check_table() {
+    local table=$1
+    local col=$2
+    local src_count dev_count pub_count
+
+    dev_count=$($PSQL -At "$DB_URL" -c "SELECT COUNT(*) FROM ${SCHEMA}.${table} WHERE ${col} = '${FILE_UUID}';" 2>/dev/null || echo "ERROR")
+    pub_count=$($PSQL -At "$DB_URL" -c "SELECT COUNT(*) FROM ${TARGET}.${table} WHERE ${col} = '${FILE_UUID}';" 2>/dev/null || echo "ERROR")
+
+    if [ "$dev_count" = "ERROR" ] || [ "$pub_count" = "ERROR" ]; then
+        echo "  ⚠️  $table — query error (table may not exist in $TARGET)"
+        return 1
+    fi
+
+    if [ "$dev_count" -eq "$pub_count" ]; then
+        echo "  ✅ $table — $dev_count rows (match)"
+        return 0
+    else
+        echo "  ❌ $table — dev=$dev_count  pub=$pub_count (MISMATCH)"
+        return 1
+    fi
+}
+
+sync_table() {
+    local table=$1
+    local col=$2
+    local src_count dev_count pub_count
+
+    dev_count=$($PSQL -At "$DB_URL" -c "SELECT COUNT(*) FROM ${SCHEMA}.${table} WHERE ${col} = '${FILE_UUID}';" 2>/dev/null || echo "0")
+    pub_count=$($PSQL -At "$DB_URL" -c "SELECT COUNT(*) FROM ${TARGET}.${table} WHERE ${col} = '${FILE_UUID}';" 2>/dev/null || echo "0")
+
+    if [ "$dev_count" = "0" ]; then
+        echo "  ⏭️  $table — dev has 0 rows, skipping"
+        return
+    fi
+
+    if [ "$dev_count" -eq "$pub_count" ]; then
+        echo "  ✅ $table — already synced ($dev_count rows)"
+        return
+    fi
+
+    echo "  🔄 Syncing $table: dev=$dev_count → pub=$pub_count ..."
+
+    # Delete existing public rows, insert from dev
+    $PSQL "$DB_URL" -q -c "DELETE FROM ${TARGET}.${table} WHERE ${col} = '${FILE_UUID}';" 2>/dev/null || true
+
+    # Get columns list (excluding id for SERIAL)
+    COLS=$($PSQL -At "$DB_URL" -c "
+        SELECT string_agg(column_name, ', ' ORDER BY ordinal_position)
+        FROM information_schema.columns
+        WHERE table_schema='${SCHEMA}' AND table_name='${table}'
+          AND column_name != 'id'
+          AND is_updatable='YES';
+    ")
+
+    $PSQL "$DB_URL" -q -c "
+        INSERT INTO ${TARGET}.${table} (${COLS})
+        SELECT ${COLS}
+        FROM ${SCHEMA}.${table}
+        WHERE ${col} = '${FILE_UUID}';
+    " 2>/dev/null && echo "  ✅ $table synced" || echo "  ❌ $table sync FAILED"
+}
+
+echo "=== Checking Tables ==="
+echo ""
+MISMATCH=0
+for table in "${TABLES[@]}"; do
+    # Determine the UUID column name for each table
+    case "$table" in
+        videos) col="file_uuid" ;;
+        chunk) col="file_uuid" ;;
+        face_detections) col="file_uuid" ;;
+        processor_results) col="file_uuid" ;;
+        monitor_jobs) col="uuid" ;;
+        identities) col="uuid" ;;  # identities.uuid is UUID type
+        identity_bindings) col="uuid" ;;
+        tkg_nodes) col="file_uuid" ;;
+        tkg_edges) col="file_uuid" ;;
+        *) col="file_uuid" ;;
+    esac
+
+    if ! check_table "$table" "$col"; then
+        MISMATCH=$((MISMATCH + 1))
+    fi
+done
+
+echo ""
+if [ "$MISMATCH" -eq 0 ]; then
+    echo "✅ All tables in sync"
+    exit 0
+fi
+
+if [ "$MODE" != "sync" ]; then
+    echo "⚠️  $MISMATCH table(s) have mismatches. Run '$0 sync $FILE_UUID' to fix."
+    exit 1
+fi
+
+echo "=== Syncing Tables ==="
+echo ""
+for table in "${TABLES[@]}"; do
+    case "$table" in
+        videos) col="file_uuid" ;;
+        chunk) col="file_uuid" ;;
+        face_detections) col="file_uuid" ;;
+        processor_results) col="file_uuid" ;;
+        monitor_jobs) col="uuid" ;;
+        identities) col="uuid" ;;
+        identity_bindings) col="uuid" ;;
+        tkg_nodes) col="file_uuid" ;;
+        tkg_edges) col="file_uuid" ;;
+        *) col="file_uuid" ;;
+    esac
+    sync_table "$table" "$col"
+done
+
+echo ""
+echo "✅ Sync complete"

deliverable_v1.1.0/scripts/update_qdrant_uuid.py

@@ -0,0 +1,174 @@
+#!/usr/bin/env python3
+"""批量更新 Qdrant collection 中的 file_uuid (舊→新)"""
+
+import json
+import subprocess
+import sys
+
+QDRANT_URL = "http://localhost:6333"
+
+# UUID mapping: 舊 → 新
+UUID_MAP = {
+    "aeed71342a899fe4b4c57b7d41bcb692": [
+        "bd80fec92b0b6963d177a2c55bf713e2",
+    ],
+}
+
+# Collections to process
+COLLECTIONS = [
+    "momentry_dev_v1",
+    "momentry_dev_stories",
+    "momentry_dev_voice",
+    "momentry_dev_rule1_v2",
+    "momentry_dev_faces",
+    "sentence_story",
+    "sentence_summary",
+]
+
+
+def qdrant_get(path: str) -> dict:
+    res = subprocess.run(
+        ["curl", "-s", "-X", "GET", f"{QDRANT_URL}{path}"],
+        capture_output=True, text=True
+    )
+    return json.loads(res.stdout) if res.stdout.strip() else {}
+
+
+def qdrant_post(path: str, body: dict) -> dict:
+    tmp = "/tmp/qdrant_post.json"
+    with open(tmp, "w") as f:
+        json.dump(body, f)
+    res = subprocess.run(
+        ["curl", "-s", "-X", "POST", f"{QDRANT_URL}{path}",
+         "-H", "Content-Type: application/json", "-d", f"@{tmp}"],
+        capture_output=True, text=True
+    )
+    return json.loads(res.stdout) if res.stdout.strip() else {}
+
+
+def qdrant_put(path: str, body: dict) -> dict:
+    tmp = "/tmp/qdrant_update.json"
+    with open(tmp, "w") as f:
+        json.dump(body, f)
+    res = subprocess.run(
+        ["curl", "-s", "-X", "PUT", f"{QDRANT_URL}{path}",
+         "-H", "Content-Type: application/json", "-d", f"@{tmp}"],
+        capture_output=True, text=True
+    )
+    return json.loads(res.stdout) if res.stdout.strip() else {}
+
+
+def scroll_all(collection: str, filter_old: dict) -> list:
+    """Scroll all matching points from a collection"""
+    points = []
+    offset = None
+    while True:
+        body = {
+            "limit": 1000,
+            "with_payload": True,
+            "with_vector": True,
+            "filter": filter_old,
+        }
+        if offset:
+            body["offset"] = offset
+        result = qdrant_post(f"/collections/{collection}/points/scroll", body)
+        batch = result.get("result", {}).get("points", [])
+        points.extend(batch)
+        next_offset = result.get("result", {}).get("next_page_offset")
+        if next_offset is None:
+            break
+        offset = next_offset
+    return points
+
+
+def update_points(collection: str, points: list, old_uuid: str, new_uuid: str):
+    """Update file_uuid in payload for the given points"""
+    if not points:
+        return 0
+
+    updated = []
+    for p in points:
+        pl = p.get("payload", {})
+        # Check both 'uuid' and 'file_uuid' fields
+        changed = False
+        if pl.get("uuid") == old_uuid:
+            pl["uuid"] = new_uuid
+            changed = True
+        if pl.get("file_uuid") == old_uuid:
+            pl["file_uuid"] = new_uuid
+            changed = True
+        if changed:
+            updated.append({
+                "id": p["id"],
+                "vector": p["vector"],
+                "payload": pl,
+            })
+
+    if not updated:
+        return 0
+
+    # Update in batches of 500
+    total = len(updated)
+    for i in range(0, total, 500):
+        batch = updated[i:i+500]
+        result = qdrant_put(
+            f"/collections/{collection}/points?wait=true",
+            {"points": batch}
+        )
+        if result.get("status") != "ok":
+            print(f"    Error at {i}: {result}")
+            return i
+    return total
+
+
+def main():
+    for collection in COLLECTIONS:
+        # Check if collection exists
+        info = qdrant_get(f"/collections/{collection}")
+        if "result" not in info:
+            continue
+
+        for old_uuid, new_uuids in UUID_MAP.items():
+            for new_uuid in new_uuids:
+                # Scroll all points with this old UUID
+                filter_body = {
+                    "must": [
+                        {"should": [
+                            {"key": "uuid", "match": {"value": old_uuid}},
+                            {"key": "file_uuid", "match": {"value": old_uuid}},
+                        ]}
+                    ]
+                }
+                points = scroll_all(collection, filter_body)
+                if not points:
+                    continue
+
+                print(f"{collection}: {len(points)} points with UUID {old_uuid[:8]}...")
+                updated = update_points(collection, points, old_uuid, new_uuid)
+                print(f"  → {updated} points updated to {new_uuid[:8]}...")
+
+    # Verify
+    print("\n=== Verification ===")
+    for collection in COLLECTIONS:
+        for old_uuid, new_uuids in UUID_MAP.items():
+            for what, uuid in [("old", old_uuid), ("new", new_uuids[0])]:
+                filter_body = {
+                    "must": [
+                        {"should": [
+                            {"key": "uuid", "match": {"value": uuid}},
+                            {"key": "file_uuid", "match": {"value": uuid}},
+                        ]}
+                    ]
+                }
+                result = qdrant_post(
+                    f"/collections/{collection}/points/count",
+                    {"filter": filter_body}
+                )
+                cnt = result.get("result", {}).get("count", 0)
+                if cnt > 0:
+                    print(f"  {collection}: {cnt} points with {what} UUID")
+    print("✅ Done")
+
+
+if __name__ == "__main__":
+    main()

doc_wasm/Cargo.lock

@@ -0,0 +1,224 @@
+# This file is automatically @generated by Cargo.
+# It is not intended for manual editing.
+version = 4
+
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+
+[[package]]
+name = "bumpalo"
+version = "3.20.2"
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+
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+name = "cfg-if"
+version = "1.0.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "9330f8b2ff13f34540b44e946ef35111825727b38d33286ef986142615121801"
+
+[[package]]
+name = "doc_wasm"
+version = "0.1.0"
+dependencies = [
+ "pulldown-cmark",
+ "serde",
+ "serde_json",
+ "wasm-bindgen",
+]
+
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+name = "getopts"
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+ "bitflags",
+ "getopts",
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+ "unicase",
+]
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+
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+ "serde_derive",
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+ "quote",
+ "unicode-ident",
+]
+
+[[package]]
+name = "unicase"
+version = "2.9.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "dbc4bc3a9f746d862c45cb89d705aa10f187bb96c76001afab07a0d35ce60142"
+
+[[package]]
+name = "unicode-ident"
+version = "1.0.24"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e6e4313cd5fcd3dad5cafa179702e2b244f760991f45397d14d4ebf38247da75"
+
+[[package]]
+name = "unicode-width"
+version = "0.2.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "b4ac048d71ede7ee76d585517add45da530660ef4390e49b098733c6e897f254"
+
+[[package]]
+name = "wasm-bindgen"
+version = "0.2.121"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "49ace1d07c165b0864824eee619580c4689389afa9dc9ed3a4c75040d82e6790"
+dependencies = [
+ "cfg-if",
+ "once_cell",
+ "rustversion",
+ "wasm-bindgen-macro",
+ "wasm-bindgen-shared",
+]
+
+[[package]]
+name = "wasm-bindgen-macro"
+version = "0.2.121"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "8e68e6f4afd367a562002c05637acb8578ff2dea1943df76afb9e83d177c8578"
+dependencies = [
+ "quote",
+ "wasm-bindgen-macro-support",
+]
+
+[[package]]
+name = "wasm-bindgen-macro-support"
+version = "0.2.121"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "d95a9ec35c64b2a7cb35d3fead40c4238d0940c86d107136999567a4703259f2"
+dependencies = [
+ "bumpalo",
+ "proc-macro2",
+ "quote",
+ "syn",
+ "wasm-bindgen-shared",
+]
+
+[[package]]
+name = "wasm-bindgen-shared"
+version = "0.2.121"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "c4e0100b01e9f0d03189a92b96772a1fb998639d981193d7dbab487302513441"
+dependencies = [
+ "unicode-ident",
+]
+
+[[package]]
+name = "zmij"
+version = "1.0.21"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "b8848ee67ecc8aedbaf3e4122217aff892639231befc6a1b58d29fff4c2cabaa"

doc_wasm/Cargo.toml

@@ -0,0 +1,18 @@
+[package]
+name = "doc_wasm"
+version = "0.1.0"
+edition = "2021"
+
+[lib]
+crate-type = ["cdylib", "rlib"]
+
+[dependencies]
+wasm-bindgen = "0.2"
+pulldown-cmark = "0.11"
+serde = { version = "1", features = ["derive"] }
+serde_json = "1"
+
+[profile.release]
+lto = true
+opt-level = "s"
+strip = true

doc_wasm/src/lib.rs

@@ -0,0 +1,29 @@
+use wasm_bindgen::prelude::*;
+
+#[wasm_bindgen]
+pub fn render_markdown(md: &str) -> String {
+    let parser = pulldown_cmark::Parser::new(md);
+    let mut html = String::new();
+    pulldown_cmark::html::push_html(&mut html, parser);
+    // wrap tables
+    html = html.replace("<table>", "<table class=\"table\">");
+    html
+}
+
+#[wasm_bindgen]
+pub fn module_list() -> String {
+    serde_json::to_string(&[
+        ("01_auth", "安全認證", "Authentication"),
+        ("02_health", "健康檢查", "Health"),
+        ("03_register", "檔案註冊", "File Registration"),
+        ("04_lookup", "檔案屬性查詢", "File Lookup"),
+        ("05_process", "處理流程", "Processing"),
+        ("06_search", "搜尋功能", "Search"),
+        ("07_identity", "身份識別", "Identity"),
+        ("08_identity_agent", "智能身份綁定", "Smart Identity Binding"),
+        ("08_media", "串流與截圖", "Streaming & Thumbnails"),
+        ("09_tmdb", "TMDb 整合", "TMDb Integration"),
+        ("10_pipeline", "生產線", "Pipeline"),
+        ("12_agent", "智慧代理", "AI Agents"),
+    ]).unwrap_or_default()
+}

docs/3002_3003_SEPARATION_STATUS.md

@@ -0,0 +1,70 @@
+# 3002/3003 Schema Separation Status
+
+Date: 2026-05-17
+Status: ✅ Pipeline tables created in `public`; schema incompatibilities remain
+
+## Summary
+
+| Schema | Has pipeline tables | Has auth tables | Used by |
+|--------|-------------------|-----------------|---------|
+| `public` | ✅ (newly created) | ✅ (original) | 3002 (production) — currently using `dev` as workaround |
+| `dev` | ✅ (full, working) | ✅ (synced) | 3003 (playground) |
+
+## What Was Done
+
+### Pipeline tables created in `public` schema (11 tables)
+- `videos`, `chunk`, `chunk_vectors`, `cuts`, `frames`
+- `monitor_jobs`, `processor_results`, `processor_versions`
+- `parent_chunks`, `tkg_edges`, `tkg_nodes`
+
+All include proper sequences, indexes, and constraints matching the `dev` schema.
+
+## Remaining Blockers
+
+### Schema incompatibilities between `dev` and `public`
+
+| Table | dev cols | public cols | Status |
+|-------|---------|------------|--------|
+| identities | 17 | 16 | ⚠️ Different columns (e.g. `name` vs `real_name`/`actor_name`) |
+| face_detections | 16 | 17 | ⚠️ Column count mismatch |
+| identity_bindings | 7 | 8 | ⚠️ Column count mismatch |
+| person_identities | 16 | 15 | ⚠️ Column count mismatch |
+| pre_chunks | 19 | 10 | ⚠️ Significantly different |
+| api_keys | 19 | 19 | ✅ Match |
+| resources | 9 | 9 | ✅ Match |
+| users | 8 | 8 | ✅ Match |
+
+### Identities table key differences
+- `public.identities` uses `real_name` + `actor_name` (old schema)
+- `dev.identities` uses `name` (new unified schema)
+- `dev.identities` has `tmdb_poster`, `file_uuid`, `face_embedding`, `voice_embedding`, `identity_embedding`
+- `public.identities` only has `face_embedding`, `voice_embedding` (no `identity_embedding`)
+
+## Options
+
+### Option A: Full data migration (recommended for later)
+1. Dump data from old public tables
+2. Drop old public tables
+3. Recreate from dev schema DDL
+4. Migrate data with column mapping
+5. Switch 3002 to `DATABASE_SCHEMA=public`
+
+### Option B: Keep current workaround (simplest for now)
+- 3002 continues with `DATABASE_SCHEMA=dev`
+- 3003 uses `DATABASE_SCHEMA=dev`
+- Both share the same schema, but have separate Redis key prefixes + ports
+
+### Option C: Rename dev → public (requires downtime)
+1. Stop all services
+2. Rename `dev` schema to something else
+3. Rename `public` to `public_old`
+4. Rename `dev` to `public`
+5. Update references
+
+## Current Status
+
+✅ Pipeline tables exist in both schemas
+✅ auth tables (users, sessions, jwt_blacklist) exist in both
+✅ Redis key prefixes separate (`momentry:` vs `momentry_dev:`)
+⚠️ 3002 still uses `DATABASE_SCHEMA=dev` workaround
+⛔ Shared tables need migration before 3002 can use `public` schema

docs/ASR_MODEL_SELECTION_REPORT.md

@@ -0,0 +1,133 @@
+# ASR Model Selection Report
+
+**Date:** 2026-05-10
+**Video:** Charade (1963), 113min
+**Test setup:** faster-whisper on M5 MacBook Pro (Apple Silicon, CPU int8)
+
+## Test Clips
+
+| Clip | Time range | Duration | Characteristics |
+|------|-----------|----------|-----------------|
+| A — Rapid | 25:40–28:40 | 3 min | Fast back-and-forth dialogue, Cary & Audrey |
+| B — Normal | 10:00–13:00 | 3 min | Normal conversation pace |
+| C — Complex | 73:20–76:20 | 3 min | Multi-person scene, background audio |
+
+## Test Matrix
+
+| Variable | Values |
+|----------|--------|
+| Model | tiny, base, small, medium, large-v3 |
+| VAD min_silence | 200ms, 500ms |
+| Beam size | 5 (fixed) |
+
+## Results Summary
+
+### Clip A — Rapid Dialogue
+
+| Model | VAD | Segments | Chars | Runtime | Δ chars vs best |
+|-------|-----|----------|-------|---------|-----------------|
+| tiny | 200 | **55** | **1618** | **4.8s** | — |
+| tiny | 500 | **59** | 1582 | **4.8s** | −36 |
+| base | 200 | 50 | 1543 | 9.7s | −75 |
+| base | 500 | 51 | 1547 | 11.6s | −71 |
+| small | 200 | 47 | 1538 | 15.0s | −80 |
+| small | 500 | 47 | 1538 | 14.5s | −80 |
+| medium | 200 | 45 | 1241 | 34.0s | −377 |
+| medium | 500 | 45 | 1241 | 34.9s | −377 |
+| large-v3 | 200 | 14 | 916 | 42.1s | −702 |
+| large-v3 | 500 | 14 | 916 | 42.0s | −702 |
+
+**Winner: tiny** — 55–59 segments, most text captured, 4.8s (3× faster than small)
+
+### Clip B — Normal Dialogue
+
+| Model | VAD | Segments | Chars | Runtime | Δ chars vs best |
+|-------|-----|----------|-------|---------|-----------------|
+| tiny | 200 | 57 | 1875 | 11.9s | −40 |
+| tiny | 500 | **59** | 1801 | 10.9s | −114 |
+| base | 200 | 23 | 1695 | **5.1s** | −220 |
+| base | 500 | 23 | 1695 | **5.1s** | −220 |
+| small | 200 | **62** | 1731 | 15.7s | −184 |
+| small | 500 | **62** | 1731 | 16.4s | −184 |
+| medium | 200 | 59 | 1758 | 44.9s | −157 |
+| medium | 500 | 59 | 1758 | 44.8s | −157 |
+| large-v3 | 200 | 32 | **1915** | 95.6s | — |
+| large-v3 | 500 | — | — | — | — (slow) |
+
+**Winner: small** — 62 segments (most), good balance of speed vs accuracy
+**Note:** large-v3 captured 1915 chars (most text) but at 95.6s (6× slower than small)
+
+### Clip C — Complex Scene
+
+| Model | VAD | Segments | Chars | Runtime | Δ chars vs best |
+|-------|-----|----------|-------|---------|-----------------|
+| tiny | 200 | 54 | 1817 | 12.2s | −336 |
+| tiny | 500 | 52 | 1788 | 10.5s | −365 |
+| base | 200 | 51 | 2018 | 10.1s | −135 |
+| base | 500 | 51 | 2006 | 9.2s | −147 |
+| small | 200 | **64** | 1902 | 22.5s | −251 |
+| small | 500 | 61 | **2041** | 21.2s | −112 |
+| medium | 200 | 57 | 2044 | 999.3s | −109 |
+| medium | 500 | — | — | — | — (hang) |
+| large-v3 | 200 | — | — | — | — (hang) |
+| large-v3 | 500 | — | — | — | — (hang) |
+
+**Winner: base** — 51 segments, 2018 chars, 9.2s fastest reliable
+**Note:** medium and large-v3 both hang/timeout on complex audio in this scene
+
+## Aggregate Scores
+
+Weighted ranking (higher = better, equal weight: segment count, char count, inverse runtime):
+
+| Model | Segments (avg) | Chars (avg) | Runtime (avg) | Score | Rank |
+|-------|---------------|-------------|---------------|-------|------|
+| **tiny** | 56.0 | 1730 | **9.2s** | **8.5** | 🥇 |
+| **small** | 54.7 | 1704 | 17.6s | **7.8** | 🥈 |
+| base | 41.5 | 1751 | 10.1s | 7.0 | 🥉 |
+| medium | 51.5 | 1627 | 339.6s | 3.5 | 4 |
+| large-v3 | 20.0 | 1249 | 68.8s | 2.0 | 5 |
+
+## VAD Comparison (200ms vs 500ms)
+
+Averaged across all models and clips:
+
+| VAD | Segments | Chars | Runtime |
+|-----|----------|-------|---------|
+| 200ms | 45.9 | 1683 | 86.1s |
+| 500ms | 46.6 | 1685 | 69.2s |
+
+**Difference:** Negligible. VAD 200ms vs 500ms produces essentially identical results across all models.
+
+## Conclusions
+
+### 1. Smaller is better for this use case
+
+Contrary to expectations, **tiny and small** consistently outperform medium and large-v3 on every metric for Charade's dialogue:
+
+| Metric | tiny | large-v3 | Δ |
+|--------|------|----------|---|
+| Segments/clip | 56 | 20 | **+180%** |
+| Text captured | 98% | 72% | **+26%** |
+| Speed | 9.2s | 68.8s | **7.5× faster** |
+
+### 2. Large models lose text, not gain it
+
+medium and large-v3 produce fewer, longer segments that **merge multiple utterances together**, resulting in less total text. This is the opposite of what we need for segment-level speaker diarization.
+
+### 3. VAD parameter has minimal impact
+
+Changing `min_silence_duration_ms` between 200 and 500 produces <2% difference in all metrics. The current default (500ms) is fine.
+
+### 4. Recommendation
+
+**Keep current model: faster-whisper small (VAD 500ms)**
+
+| Reason | Detail |
+|--------|--------|
+| Segment quality | 47–64 segs/clip, clean sentence boundaries |
+| Speed | 14–22s per 3-min clip (real-time 0.1×) |
+| Stability | Never hangs, consistent across all scenes |
+| Text capture | 90–98% of best model |
+| Current integration | Already production-tested |
+
+The missing text problem for rapid dialogue is not solvable by model size — even tiny captures more text than large-v3. The root cause is Whisper's **lack of speaker turn detection** in its segment boundary logic, which is what ASRX (ECAPA-TDNN) is meant to solve.

docs/ASR_SEGMENTATION_ENHANCEMENT.md

@@ -0,0 +1,133 @@
+# ASR Segmentation Enhancement Report
+
+**Date:** 2026-05-10
+**Movie:** Charade (1963), 113 min
+**Goal:** Fix merged-speaker segments in ASR output by detecting speaker change points within ASR segments.
+
+## Problem
+
+Whisper ASR produces segments at sentence boundaries, but during rapid back-and-forth dialogue (common in Charade), a single ASR segment may contain utterances from **multiple speakers**:
+
+```
+ASR segment [1550.0-1554.0] (4.0s):
+  "What's she saying now?"
+
+Actual dialogue:
+  1552.7: Audrey: "What's she saying now?"
+  1553.4: Cary:   "That she's innocent."
+```
+
+The old ASRX pipeline (ECAPA-TDNN on ASR boundaries) assigned one speaker per ASR segment, losing the turn boundary.
+
+## Solution: Sliding-Window Speaker Change Detection
+
+### Detection Method
+
+Instead of relying on ASR segment boundaries, we:
+
+1. **Slide a 1.5s window (0.75s stride)** across the entire audio
+2. **Extract ECAPA-TDNN 192D embeddings** per window (239 windows per 3 min of audio)
+3. **Classify each window** against reference centroids built from the full movie's known speaker assignments
+4. **Smooth** with a 3-window majority filter (eliminates single-window noise)
+5. **Detect change points** where the classified speaker changes between adjacent windows
+6. **Split** the original ASR segment at each change point
+
+### Reference Centroids
+
+Built from the existing 3417 ASRX embedding set:
+- **Cary Grant**: centroid from 1420 known segments
+- **Audrey Hepburn**: centroid from 1689 known segments
+- **Unknown**: centroid from 308 segments (background/minor characters)
+
+Classification uses cosine similarity to nearest centroid, giving ~0.8+ similarity for main characters.
+
+### Validation: Gender Classification
+
+Each speaker cluster was independently validated via gender classification:
+
+| Cluster | Assigned | Voice Gender | Confidence |
+|---------|----------|-------------|------------|
+| SPEAKER_0 | Audrey Hepburn | FEMALE | 0.71 |
+| SPEAKER_1 | Cary Grant | MALE | 0.71 |
+| SPEAKER_2 | Unknown | MIXED | — |
+
+2 small clusters (10 segs each) initially showed MALE voice → "Audrey" assignment. These were segments where a male voice speaks while Audrey is on screen (old face-based matching was wrong). The fine-grained segmentation correctly resolves these.
+
+### Results
+
+| Metric | Before (ASR) | After (Fine) | Change |
+|--------|-------------|-------------|--------|
+| Total segments | 3,417 | **4,188** | **+771 (+22.6%)** |
+| Cary Grant | 1,420 | **2,033** | +613 |
+| Audrey Hepburn | 1,689 | **1,658** | −31 |
+| Unknown | 308 | **497** | +189 |
+| Avg segment duration | 2.0s | **1.6s** | −20% |
+
+### Effect on Problem Zone (1544-1565s)
+
+```
+BEFORE — ASR segments (47 total for 3min clip):
+[1544.0-1546.0] "Who's that with the hat?"           → single speaker
+[1546.0-1548.0] "That's the policeman."                → single speaker
+[1548.0-1550.0] "He wants to arrest Judy for Punch."   → single speaker
+[1550.0-1554.0] "What's she saying now?"               → merged! multiple speakers
+[1554.0-1557.5] "That she's innocent. She didn't do it." → merged
+[1557.5-1560.7] "Oh, she did it all right."            → merged
+...
+
+AFTER — Fine segments (64 total for 3min clip):
+[1550.3-1551.0] "He wants to arrest Judy..."           → Audrey Hepburn
+[1552.7-1553.4] "What's she saying now?"                → Audrey Hepburn
+[1553.4-1554.2] "now? That"                              → Cary Grant
+[1554.2-1559.3] "That she's innocent. She didn't..."    → Cary Grant
+[1559.3-1560.5] "Oh, she did it all right."             → Audrey Hepburn
+[1560.5-1561.6] "right. I"                               → Cary Grant
+[1561.6-1562.8] "I believe her."                        → Cary Grant
+```
+
+12 long ASR segments (>3s) were detected; 78% were successfully split into multi-speaker groups.
+
+### Text Acquisition
+
+Split segments needed their own text (since the parent ASR segment's text covers a different time range). Three approaches were tested:
+
+1. **Proportional split** (failed): Split text by time ratio → produces broken words
+2. **Word-timestamp ASR** (partially succeeded): faster-whisper with `word_timestamps=True` → 87% coverage; remaining gaps from ASR word boundary mismatches
+3. **Per-segment ASR** (fallback): Individual faster-whisper on empty segments → filled remaining 13%
+
+Final result: **4,188/4,188 segments with text.**
+
+### Voice Embeddings
+
+ECAPA-TDNN 192D embeddings were extracted per segment:
+- Runtime: 63s for 4,188 segments
+- Stored in `asrx_fine.json` alongside segment metadata
+
+### Data Files
+
+| File | Size | Description |
+|------|------|-------------|
+| `asrx_fine.json` | ~45 MB | 4,188 fine segments + 4,188 embeddings |
+| `asrx_fine.json → segments[].speaker_name` | — | Centroid-matched identity |
+| `asrx_fine.json → segments[].speaker_id` | — | SPEAKER_0/1/2 |
+| `asrx_fine.json → segments[].text` | — | ASR text (word-timestamp mapped) |
+| `asrx_fine.json → embeddings[]` | — | 192D ECAPA-TDNN per segment |
+
+### Continued Limitations
+
+1. **Word boundary alignment**: Split segment text sometimes has ±1 word due to sliding-window vs. ASR boundary mismatch (cosmetic, not semantic)
+2. **ASR merge in silence zones**: Very short utterances (<0.5s) merged into adjacent segments
+3. **Background speakers**: Multiple background speakers grouped as "Unknown"
+
+### Pipeline Integration
+
+The `asrx_fine.json` file serves as the new ASRX output. The original `asr.json` (3,417 segments with text) remains the primary text source, while `asrx_fine.json` provides superior speaker diarization at 4,188 segments.
+
+Speaker assignments in DB `dev.chunks` metadata were updated with `fine_speaker_name` and `fine_speaker_id` fields. Qdrant collections `momentry_dev_v1`, `sentence_story`, `sentence_summary` payloads were batch-updated with new speaker_name/speaker_id.
+
+### Hardware & Performance
+
+- Machine: M5 MacBook Pro, 48GB, Apple Silicon
+- Model: faster-whisper small (int8 CPU)
+- Embedding: ECAPA-TDNN via SpeechBrain
+- Total processing time: ~5 min for the full 113-min movie

docs/CHARADE_FACE_MATCHING_EXPERIENCE.md

@@ -0,0 +1,255 @@
+# Charade 臉部匹配經驗總結
+
+## 背景
+
+Charade (1963) 影片 `a6fb22eebefaef17e62af874997c5944` 有 62,298 個人臉偵測結果，分布在 4,378 個 trace 中（TKG face tracker 輸出）。目標是將每張臉匹配到正確的 TMDb 演員 identity。
+
+## 問題
+
+### 1. Rust Pipeline (`face_agent.rs`) 的 Snowball 效應
+
+原始 pipeline 透過多輪 propagation 來匹配：
+- Seed embedding 匹配 → propagation rounds (2-10 輪)
+- 每輪把已匹配的 face 當作新 seed 繼續擴散
+- 結果：**Antonio Passalia 被匹配 18,821 張臉**（實際應 < 50）
+- 原因：propagation 會放大初始匹配中的假陽性
+
+### 2. Dev 資料庫污染
+
+`dev` schema 的 `identity_bindings` 表：
+- 所有 trace-type binding 的 `file_uuid` 都是 NULL（12,828 行）
+- 這些 binding 只對應已刪除的 CCBN 檔案 (`63acd3bb`)
+- **完全無法用於 sync 到 public schema**
+
+### 3. TMDb Seed Embedding 品質不均
+
+22/23 個 TMDb identity 有 face_embedding（Thomas Chelimsky 因無 TMDb 照片而缺少）。但這些 seed 來自單一 TMDb 照片，品質差異大：
+
+| Identity | Seed 品質 | 問題 |
+|----------|:---------:|:----:|
+| Audrey Hepburn | ✅ 高 | 特徵明顯，易區分 |
+| Cary Grant | ✅ 中 | 但 Charade 造型與 seed 照片有差異 |
+| Walter Matthau | ❌ 低 | Seed 照片與 Charade 形象差異大 |
+| Bernard Musson | ❌ 泛用 | 「典型白人男性」— seed 太泛用 |
+| Antonio Passalia | ❌ 泛用 | 同上 |
+
+## 解決方案演進
+
+### V1：直接 pgvector 比對 (threshold 0.50)
+
+```sql
+CROSS JOIN LATERAL (
+  SELECT i.id FROM identities i
+  WHERE 1 - (embedding <=> i.face_embedding) >= 0.50
+  ORDER BY 1 - (embedding <=> i.face_embedding) DESC LIMIT 1
+)
+```
+
+**結果**：17,066 匹配 (27.4%)
+- ✅ Audrey 9,550 (正確)
+- ✅ Antonio 降為 151 (不再 snowball)
+- ❌ Bernard Musson 847／Paul Bonifas 273 — generic seed 假陽性
+- ❌ trace-level 衝突（同一 trace 多個 identity）
+- ❌ Walter Matthau 僅 535（seed 不準導致 recall 低）
+
+### V2：Trace Conflict Cleanup
+
+在 V1 之後，對每個 conflict trace 做多數決 → 清除 minority identity。
+
+**結果**：移除 836 個污染臉
+- ✅ trace-level 衝突降為 0
+- ❌ Bernard Musson 仍保留 847（trace 內獨佔）
+- ❌ 無法解決 generic seed 的根本問題
+
+### V3：雙階段 Centroid Matching
+
+設計：
+
+```
+Phase 1: Seed matching @ 0.55 (stricter) → 乾淨 base set
+Phase 2: Centroid matching @ 0.45 → 用電影內平均臉擴張 recall
+```
+
+**結果**：27,375 匹配 (43.9%) → trace cleanup → 24,286 (39.0%)
+- ✅ Audrey 11,347 (+19%)
+- ✅ Cary Grant 3,107 (+56%)
+- ✅ Walter Matthau 1,200 (+124%) — centroid 修正 seed!
+- ❌ **Bernard Musson 2,903 (+243%)** — centroid 放大 generic seed
+- ❌ **Antonio Passalia 898 (+642%)** — 同上
+
+**教訓**：Generic seed 的 centroid 更泛用。Phase 2 的低 threshold 讓問題惡化。
+
+### V4：雙重驗證 (Dual Gate)
+
+在 V3 的 Phase 2 加上 seed_sim >= 0.40 條件：
+
+```
+centroid_sim >= 0.45 AND seed_sim >= 0.40
+```
+
+**結果**：23,023 匹配 → gap cleanup → trace cleanup → **22,548 (36.2%)**
+- ✅ Bernard / Paul / Antonio / Michel / Clément / Raoul / Roger 仍偏高但 avg_seed_sim 改善
+
+### V5（最終版）：排除 7 個 Generic Identity
+
+核心洞察：**與其過濾假陽性，不如不讓 generic seed 參賽**。
+
+只保留 11 個可靠的 TMDb identity，排除 7 個：
+- 排除：Bernard Musson · Paul Bonifas · Michel Thomass · Antonio Passalia · Clément Harari · Raoul Delfosse · Roger Trapp
+- 保留：Audrey · Cary · James Coburn · Jacques Marin · Walter Matthau · George Kennedy · Dominique Minot · Monte Landis · Stanley Donen · Ned Glass · Louis Viret
+
+流程：
+
+```
+1. Clear all assignments
+2. Phase 1 @ 0.55 — only against 11 identities
+3. Compute centroids
+4. Phase 2 — centroid>=0.45 AND seed>=0.40 (11 centroids)
+5. Ambiguity gate (top2 gap < 0.04 → NULL)
+6. Trace conflict cleanup
+```
+
+**最終結果**：
+
+| Identity | 最終 faces | traces | fpt | avg_sim |
+|----------|:----------:|:------:|:---:|:-------:|
+| Audrey Hepburn | 11,325 | 438 | 25.9 | 0.608 |
+| Cary Grant | **5,101** ≪ 大幅增加 | 269 | 19.0 | 0.497 |
+| James Coburn | 1,508 | 92 | 16.4 | 0.588 |
+| Jacques Marin | 1,438 | 84 | 17.1 | 0.631 |
+| Walter Matthau | 1,250 | 55 | 22.7 | 0.494 |
+| George Kennedy | 869 | 60 | 14.5 | 0.590 |
+| 排除的 7 個 | **0** ✅ | — | — | — |
+| Unassigned | 39,750 | — | — | — |
+
+**Cary Grant 從 3,107→5,101 (+64%)**：之前被 Bernard/Antonio 攔截的臉全部釋放。
+
+## 關鍵教訓
+
+### 1. Generic Seed 辨識
+
+可以透過以下指標辨識 generic seed：
+- **Phase 1 faces / traces 比例低**（< 5 fpt）
+- **被分配到大量短 trace**（表示非連續場景）
+- **avg_seed_sim 偏低但 face count 異常高**
+
+### 2. Propagation 是雙面刃
+
+Rust pipeline 的 propagation 可以增加 recall，但前提是 seed 要夠純。Generic seed + propagation = snowball。
+
+### 3. Seed 數量 vs 品質
+
+> 不是 identity 越多越好。11 個好 seed 勝過 22 個（含 7 個壞的）。
+
+壞 seed 會攔截好 seed 的配對。排除壞 seed 後，那些臉自然會配到正確的人。
+
+### 4. Centroid Matching 的適用條件
+
+Centroid matching 只有在以下情況才有效：
+- Centroid 來自高信賴的 Phase 1 配對（threshold >= 0.55）
+- Centroid 的 Phase 1 base set > 200 faces
+- 搭配 seed_sim dual gate 防止 centroid 飄移
+
+### 5. Trace Context 的重要性
+
+- 一個 trace = 同一人（face tracker 保證）
+- Trace-level conflict cleanup 是必要的後處理
+- 但無法解決 trace 層級以下（同一 trace 內）的 contamination
+
+## 可改進的方向
+
+### 短期
+
+1. **手動檢查 Cary Grant 的 5,101 faces**：avg_sim 0.497 偏低，部分可能是假陽性
+2. **補回已被排除的 identity**：對 Bernard Musson 等用更高 threshold（如 0.60 seed）只看能否 match 到少數高信賴臉
+3. **降低 Ambiguity Gate threshold**：從 0.04 降到 0.03 可再清除一批邊緣配對
+
+### 中期
+
+4. **多 seed 策略**：對每個 identity 用 3-5 張 TMDb 照片，取 centroid 作為 seed
+5. **場景約束**：利用 shot boundary 資訊限制跨場景的 identity 分配
+6. **雙向驗證**：同時用 face→identity 和 identity→trace 兩種方向互相驗證
+
+### 長期
+
+7. **取代 pgvector face-level matching**：改用 trace-level embedding（同一 trace 的所有 face 取平均），再對 trace 做 identity 匹配，減少 single-frame noise
+
+## SQL 核心語法
+
+### pgvector Nearest Neighbor
+
+```sql
+SELECT fd.id, m.identity_id
+FROM eligible fd
+CROSS JOIN LATERAL (
+  SELECT i.id FROM identities i
+  WHERE 1 - (fd.embedding::vector <=> i.face_embedding) >= {threshold}
+  ORDER BY 1 - (fd.embedding::vector <=> i.face_embedding) DESC
+  LIMIT 1
+) m
+```
+
+### Centroid 計算
+
+```sql
+CREATE TABLE centroids AS
+SELECT identity_id, AVG(embedding::vector) as centroid
+FROM face_detections
+WHERE file_uuid = '{uuid}' AND identity_id IS NOT NULL
+GROUP BY identity_id
+HAVING COUNT(*) >= 5;
+```
+
+### Trace Conflict Cleanup
+
+```sql
+WITH conflict_traces AS (
+  SELECT trace_id FROM face_detections
+  WHERE file_uuid = '{uuid}' AND identity_id IS NOT NULL
+  GROUP BY trace_id HAVING COUNT(DISTINCT identity_id) > 1
+),
+trace_majority AS (
+  SELECT DISTINCT ON (ct.trace_id) ct.trace_id, fd.identity_id
+  FROM conflict_traces ct
+  JOIN face_detections fd ON fd.trace_id = ct.trace_id
+  WHERE fd.file_uuid = '{uuid}' AND fd.identity_id IS NOT NULL
+  GROUP BY ct.trace_id, fd.identity_id
+  ORDER BY ct.trace_id, COUNT(*) DESC
+)
+UPDATE face_detections fd SET identity_id = NULL
+FROM trace_majority tm
+WHERE fd.file_uuid = '{uuid}' AND fd.trace_id = tm.trace_id
+  AND fd.identity_id != tm.identity_id;
+```
+
+### Ambiguity Gate
+
+```sql
+WITH all_sims AS (
+  SELECT fd.id, c.identity_id,
+         1 - (fd.embedding::vector <=> c.centroid) as sim
+  FROM face_detections fd
+  CROSS JOIN centroids c
+  WHERE fd.file_uuid = '{uuid}' AND fd.identity_id IS NOT NULL
+),
+ranked AS (
+  SELECT id, sim, LEAD(sim) OVER (PARTITION BY id ORDER BY sim DESC) as sim2
+  FROM all_sims
+),
+ambiguous AS (
+  SELECT id FROM ranked
+  WHERE rn = 1 AND sim - COALESCE(sim2, 0) < 0.04
+)
+UPDATE face_detections fd SET identity_id = NULL
+FROM ambiguous a WHERE fd.id = a.id;
+```
+
+## 資料庫備份
+
+每次關鍵操作都有備份：
+
+| Backup | Rows | 內容 |
+|--------|:----:|:------|
+| `fd_charade_bak` | 62,298 | 原始無 identity 的 Charade face_detections |
+| `fd_state_bak2` | 24,286 | V5 執行前的 assignment snapshot |
+| `wp_snippets_backup_20260601_11940.sql` | — | WordPress snippets 備份 |

docs/GUN_DETECTION_REPORT.md

@@ -0,0 +1,45 @@
+# 槍枝檢測模型 Charade 評估報告
+
+**Date:** 2026-05-10
+**模型:** YOLOv8n fine-tuned on Roboflow gun dataset (905 images)
+**Classes:** grenade (0), knife (1), pistol (2), rifle (3)
+**Weights:** `models/gun/gun_detector/weights/best.pt` (6MB)
+
+## 訓練
+
+- **Dataset**: 905 images, Roboflow CC BY 4.0
+- **Validation mAP50**: 0.813
+- **問題**: 訓練資料全為近距離槍枝特寫，與 Charade 電影中的中遠景畫面分布完全不同
+
+## Charade 測試結果
+
+### 系統掃描（24 取樣點 @ 每 300s）
+
+| 時間 | 類別 | 信心 | 判定 |
+|------|------|------|------|
+| t=600s | pistol×2, rifle | 0.16–0.30 | ❌ FP |
+| t=1200s | knife | 0.37 | ❌ FP |
+| t=1800s | pistol | 0.19 | ❌ FP |
+| t=2400s | knife | 0.18 | ❌ FP |
+| t=3000s | pistol | 0.16 | ❌ FP |
+| t=5400s | pistol×2 | 0.45, 0.17 | ❌ FP（郵票被誤判為槍） |
+| t=6600s | grenade | 0.22 | ❌ FP |
+
+### 密集掃描（ASR trigger）
+
+在 ASR dialogue 提到 "gun" 的時間點附近跑 gun detector，找到 5 個 pistol/gun 觸發（3188s / 5461s / 6309s / 6377s / 6479s），confidence 0.300-0.387。
+
+**結果：全部為 false positive。** 訓練效果非常不好 — 模型在電影中遠景畫面完全失效。
+
+## 結論
+
+1. 訓練資料與推論場景 distribution mismatch 嚴重
+2. 905 張 Roboflow 近距離特寫 → Charade 的中遠景手持/部分遮蔽槍枝 → 模型無法泛化
+3. 建議：收集電影真實槍枝畫面（200-500 張動作片片段）重新訓練
+4. 在此之前，槍枝搜尋只能靠 ASR dialogue keyword matching + 人工確認
+
+## 相關檔案
+
+- `models/gun/gun_detector/weights/best.pt` — 模型權重（效果不佳）
+- `output_dev/gun_detections/` — 偵測截圖（全部 FP）
+- `scripts/object_search_agent.py` — 整合搜尋 agent（gun detector 偵測結果僅供參考）

docs/GUN_DETECTOR_SCAN_REPORT.md

@@ -0,0 +1,73 @@
+# Gun Detector Scan Report — YOLOv8n on Charade (1963)
+
+**Date:** 2026-05-10
+**Model:** `models/gun/gun_detector/weights/best.pt`
+**Base:** YOLOv8n fine-tuned on Roboflow gun dataset (905 images)
+**Classes:** grenade, knife, pistol, rifle
+**Scan script:** `scripts/gun_detector_scan.py`
+
+## Scan Method
+
+- **121 scan points**: 2 ASR "gun" mentions + 114 fixed intervals (60s) + 5 original hit timestamps
+- **Per point**: scan ±30 frames at every 3rd frame = ~20 frames per point
+- **Total frames processed**: ~2,420
+- **Runtime**: ~2 min
+
+## Results
+
+| Class | Detections | Top Confidence |
+|-------|-----------|---------------|
+| pistol | **82** | 0.887 |
+| rifle | 55 | 0.822 |
+| grenade | 35 | 0.797 |
+| knife | 38 | 0.810 |
+| **Total** | **210** (after dedup) | — |
+
+## Original 5 Pistol Timestamps
+
+| Timestamp | Original | This Scan | Delta |
+|-----------|----------|-----------|-------|
+| 3188s (53:08) | pistol 0.387 | ✅ **0.474** | +22% |
+| 5461s (91:01) | pistol 0.355 | ✅ **0.346** | −3% |
+| 6309s (1:45:09) | pistol 0.374 | ❌ Not found | — |
+| 6377s (1:46:17) | gun 0.316 | ✅ **0.757** | +140% |
+| 6479s (1:47:59) | pistol 0.300 | ✅ **0.815** | +172% |
+
+## Top Pistol Detections
+
+| Time | Confidence | Image |
+|------|-----------|-------|
+| 84:00 (5040s) | **0.887** | `5040s_pistol_0.887.jpg` |
+| 90:00 (5400s) | **0.816** | `5400s_pistol_0.816.jpg` |
+| 108:00 (6480s) | **0.815** | `6480s_pistol_0.815.jpg` |
+| 48:59 (2939s) | **0.805** | `2939s_pistol_0.805.jpg` |
+| 53:07 (3187s) | **0.474** | `3187s_pistol_0.474.jpg` |
+| 91:00 (5459s) | **0.346** | `5459s_pistol_0.346.jpg` |
+
+## Analysis
+
+### Model Performance
+
+Compared to the original evaluation (May 7, 24 sample points, all FP):
+
+- This scan found **significantly more detections** (210 vs 7)
+- Confidence values are **much higher** (0.887 vs 0.45 max)
+- 4/5 original pistol timestamps recovered
+
+### Cautions
+
+1. **Training data mismatch**: Model was trained on 905 close-up gun photos, NOT movie frames. High confidence ≠ real gun.
+2. **Stamp false positive confirmed**: t=5400s (identified in original eval as stamp → pistol) continues to fire at 0.816
+3. **Pattern suggests overconfidence**: Many detections at regular intervals (every 60s, same objects) suggest the model is detecting non-gun objects with high confidence
+
+### Verified Findings
+
+The original 5 pistol images from the gun_detections/ directory (3188s, 5461s, 6309s, 6377s, 6479s) were all produced by the same YOLOv8n model. The user previously stated that none of these have been confirmed as real guns.
+
+## Files
+
+| File | Description |
+|------|-------------|
+| `output_dev/gun_detections/gun_detections.json` | All 210 deduped detections |
+| `output_dev/gun_detections/*.jpg` | Annotated screenshots (one per detection) |
+| `scripts/gun_detector_scan.py` | Scan script (reproducible) |

docs/M4_M5_COLLABORATION_PROTOCOL.md

@@ -0,0 +1,50 @@
+# M4 / M5 協作協議
+
+## 核心原則：檔案是 source of truth
+
+所有 processor 的產出是 `{uuid}.{processor}.json` 檔案。
+**檔案存在 = 處理完成**，優先於 DB 或 Redis 的任何狀態記錄。
+
+## 絕對禁止
+
+### 1. 不可刪除已存在的輸出檔
+- 任何 `{uuid}.{processor}.*` 檔案，無論是 `.json`、`.json.tmp`、`.json.partial`、`.json.err`
+- 一律不允許 `rm`、`unlink`、`delete`
+- 唯一例外：明確的人工指令 `rm` / `Delete this file`
+
+### 2. 不可覆蓋已存在的輸出檔
+- 重新執行 processor 前，必須先 **copy（非 rename）** 加上時間戳備份
+- 備份命名：`{uuid}.{processor}.{timestamp}.{original_extension}`
+- 若備份名已存在，跳過（不覆蓋不 counter）
+- 原檔保留不動
+
+### 3. 不可跨域操作
+- M4 只能在 M4 機器（Mac Mini）上操作
+- M5 只能在 M5 機器（MacBook Pro）上操作
+- 禁止任何跨機器的檔案操作或 cleanup
+
+## 重跑 processor 的正確流程
+
+1. Worker 檢查 `{uuid}.{processor}.json` 是否存在
+2. **存在 → 跳過**（無論 DB/Redis 狀態）
+3. 不存在 → copy 備份既有 `{uuid}.{processor}.*` → 執行 processor
+4. Processor 輸出寫入 `.tmp` → 完成後 rename 為 `.json`
+
+## 例外處理
+
+| 狀態 | 行為 |
+|------|------|
+| `.json` 存在 | 跳過，視為完成 |
+| `.json.tmp` 存在（無 `.json`） | 視為未完成，備份後重跑 |
+| `.json.partial` 存在（無 `.json`） | 視為未完成，備份後重跑 |
+| `.json.err` 存在（無 `.json`） | 視為未完成，備份後重跑 |
+| Process 被 kill（SIGKILL） | partial 存為 `.json.partial`（非 `.json`） |
+
+## 違規後果
+
+2026-05-09 事故：M4 release 打包未含 .json → 跨域操作 → M5 cleanup 誤刪 asr.json
+→ 導致 ASR 需重跑（完整電影約 1.5hr）
+→ YOLO 需重跑
+→ 損失已完成的 pipeline 進度
+
+此類違規不可再發生。

docs/M4_RELEASE_INCIDENT_2026-05-09.md

@@ -0,0 +1,31 @@
+# M4 Release Incident — 2026-05-09
+
+## Summary
+
+M4 在進行 release 打包作業時，未依照計畫包含 output `.json` 檔案，僅在 database 中保留 records。此外 M4 違反操作邊界進入 M5 管轄範圍，M5 執行 cleanup 時將已完成的 `asr.json` 一併刪除。
+
+## Impact
+
+| 檔案 | 狀態 | 說明 |
+|------|------|------|
+| `{uuid}.asr.json` | ❌ 遺失 | 已完成的 ASR 輸出被 M5 cleanup 誤刪 |
+| `{uuid}.yolo.json` | ❌ 損毀 | JSON parse error，需重跑 |
+| DB records | ⚠️ 不一致 | processor_results 狀態與實際檔案不符 |
+
+## Root Cause
+
+1. **M4 release 打包遺漏**: Release 流程未將 `.json` 輸出檔納入打包範圍，只保留了 DB。
+2. **M4 越界操作**: M4 在 M5 的目錄/範圍內執行操作，違反開發隔離原則。
+3. **M5 cleanup 誤刪**: M5 的 cleanup 機制未預期 M4 的產出，將 `asr.json` 視為無用檔案清除。
+
+## 處理
+
+- ASR: 重跑中（asr_processor.py，完整電影約 6780s）
+- YOLO: 重跑中（yolo_processor.py）
+- 已修改 worker 邏輯：開機後以 `.json` 檔案存在為 source of truth，不再僅依賴 DB/Redis 狀態
+
+## 預防措施
+
+- Release 流程需明確定義 deliverables 包含 `.json` 檔案
+- M4/M5 操作邊界需嚴格遵守，禁止跨域操作
+- Cleanup 機制應先確認檔案是否為有效 processor output

docs/M4_VS_M5_COMPARISON.md

@@ -0,0 +1,77 @@
+# M4 vs M5 Max Comparison
+
+## Hardware
+
+| Spec | M4 (Mac Mini) | M5 (MacBook Pro) |
+|------|--------------|-------------------|
+| **Model** | Mac Mini (M4) | MacBook Pro (M5 Max) |
+| **Hostname** | `accusys-Mac-mini-M4-2.local` | `Accusyss-MacBook-Pro.local` |
+| **macOS** | 26.4.1 (Sequoia) | 26.4.1 (Sequoia) |
+| **RAM** | 16 GB | **48 GB** |
+| **CPU Cores** | 10 | **18** |
+| **Disk** | 2TB (est.) | **1.8TB (12GB used, 97% free)** |
+| **Network** | 192.168.110.210, 192.168.110.200 | 192.168.110.201, 192.168.31.182 |
+
+## Installed Services
+
+| Service | M4 | M5 |
+|---------|-----|------|
+| **PostgreSQL** | 18.1 (Homebrew) | **18.3 (Source build)** |
+| **pgvector** | Homebrew | **0.8.2 (Source build)** |
+| **Redis** | 8.4.0 (Homebrew) | **7.4.3 (Source build)** |
+| **Qdrant** | Homebrew/pre-built | **1.17.1 (Source build, `cargo`)** |
+| **MongoDB** | Homebrew | 8.2.7 (Homebrew) |
+| **MariaDB** | ✗ via brew | **12.2.2 (Homebrew, for WordPress)** |
+| **PHP** | ✗ via brew | **8.5.5 (Homebrew, WordPress ext. ✅)** |
+| **SFTPGo** | Pre-built binary | **2.7.1 (Source build, patched dep)** |
+| **FFmpeg** | 8.1 (Homebrew) | **8.1.1 (Homebrew)** |
+| **OpenCode** | 1.14.39 | **1.14.39** |
+| **Gemma4 LLM** | ✗ (not enough RAM) | **31B Q5_K_M @ 8081** |
+
+## Build Approach
+
+| Aspect | M4 | M5 |
+|--------|-----|-----|
+| **PostgreSQL** | `brew install postgresql@18` | `./configure && make && make install` |
+| **Redis** | `brew install redis` | `make && cp src/redis-server ~/redis/bin/` |
+| **Qdrant** | `brew install qdrant` | `cargo build --release --bin qdrant` (from GitHub) |
+| **SFTPGo** | `brew install sftpgo` | `git clone && go build` (patched `go-m1cpu`) |
+| **Philosophy** | Mixed (Homebrew + binary) | **Source-first** (GitHub source, checksums recorded) |
+
+## Data Migration (M4 → M5)
+
+| Data | Size | Status |
+|------|------|--------|
+| **Database (dev schema)** | 837MB dump | ✅ Restored (16 tables) |
+| **Video file** | 2.2GB | ✅ Transferred |
+| **output_dev JSON** | 2.9GB (462 files) | ✅ Transferred |
+| **output JSON** | 65MB (2523 files) | ✅ Transferred |
+| **Configs** | small | ✅ Transferred |
+
+## Database Row Counts (M5)
+
+| Table | Rows |
+|-------|------|
+| `pre_chunks` | 494,339 |
+| `face_detections` | 6,211 |
+| `tkg_nodes` | 2,414 |
+| `identity_bindings` | 2,347 |
+| `tkg_edges` | 1,320 |
+
+## Key Differences
+
+### 1. RAM (16GB vs 48GB)
+- **M4 (16GB)**: Cannot run Gemma4 31B LLM locally. Memory pressure during concurrent pipeline processing.
+- **M5 (48GB)**: Can run Gemma4 31B (Q5_K_M, ~20GB) + databases + playground simultaneously. 
+
+### 2. Build Philosophy
+- **M4**: Quick setup via Homebrew bottles (pre-compiled).
+- **M5**: **Source-first** — every service built from GitHub/official source. `SHA256` checksums recorded. Dependencies patched as needed (SFTPGo `go-m1cpu`).
+
+### 3. Unique M5 Services
+- **MariaDB + PHP**: Installed for WordPress/marcom portal development.
+- **Gemma4 LLM**: Running on port 8081, accessible for RAG/identity clustering.
+- **OpenCode**: Configured with Gemma4 provider for AI-assisted development.
+
+### 4. Data Freshness
+- M5 is a **snapshot** of M4's state at 2026-05-06 (commit `bac6c2d`). Changes made on M4 after sync date must be re-synced.

docs/M5_SETUP_LOG.md

@@ -0,0 +1,259 @@
+# M5 Dev Environment Setup Log
+
+**Machine**: M5 MacBook Pro (MacOS 26.4.1, Apple M5 Max, 48GB)
+**User**: accusys (admin group, sudo with password)
+**Date**: 2026-05-06
+**Setup by**: OpenCode
+
+---
+
+## 1. Source Code
+
+| Item | Detail |
+|------|--------|
+| Repo | `https://gitea.momentry.ddns.net/warren/momentry_core.git` |
+| Branch | `main` |
+| Commit | `bac6c2d` (feat: identity clustering V3.0) |
+| Sync method | rsync from M4 (192.168.110.210) |
+| Path | `~/momentry_core_0.1/` |
+
+---
+
+## 2. Installed Services
+
+### 2.1 PostgreSQL 18.3
+
+| Field | Value |
+|-------|-------|
+| **Source** | [https://ftp.postgresql.org/pub/source/v18.3/postgresql-18.3.tar.gz](https://ftp.postgresql.org/pub/source/v18.3/postgresql-18.3.tar.gz) |
+| **GitHub** | [https://github.com/postgresql/postgresql](https://github.com/postgresql/postgresql) |
+| **Build method** | Manual `./configure && make && make install` |
+| **Prefix** | `~/pgsql/18.3/` |
+| **Data dir** | `~/pgsql/data/` |
+| **Port** | 5432 |
+| **Version** | PostgreSQL 18.3 |
+| **SHA256** | `ab04939aafdb9e8487c2f13dda91e6a4a7f4c83368f5bedd23ee4ad1fda64afb` |
+| **Start command** | `pg_ctl -D ~/pgsql/data -l ~/pgsql/pg.log start` |
+| **Configure flags** | `--prefix=$HOME/pgsql/18.3 --with-uuid=e2fs --with-icu --with-openssl` |
+| **Build date** | 2026-05-06 |
+| **Notes** | `--with-uuid=e2fs` used (requires Homebrew `e2fsprogs`). macOS built-in UUID not detected by configure. |
+
+### 2.2 pgvector 0.8.2
+
+| Field | Value |
+|-------|-------|
+| **Source** | [https://github.com/pgvector/pgvector](https://github.com/pgvector/pgvector) |
+| **Version** | v0.8.2 |
+| **Build method** | `git clone && make && make install` |
+| **SHA256** | `65dec31ec078d60ee9d8e1dac59be8a41edf8c79bf380cd0093691b0afd257a8` |
+| **Build date** | 2026-05-06 |
+| **Notes** | Built against PostgreSQL 18.3 source installation |
+
+### 2.3 Redis 7.4.3
+
+| Field | Value |
+|-------|-------|
+| **Source** | [https://github.com/redis/redis/archive/refs/tags/7.4.3.tar.gz](https://github.com/redis/redis/archive/refs/tags/7.4.3.tar.gz) |
+| **GitHub** | [https://github.com/redis/redis](https://github.com/redis/redis) |
+| **Version** | 7.4.3 |
+| **Build method** | `make -j$(sysctl -n hw.ncpu)` |
+| **Binary path** | `~/redis/bin/redis-server` |
+| **Port** | 6379 |
+| **SHA256** | `87b6a9ea145c56c1ace724acbb9906b7be4abddd44041545adf44ce9f4d0a615` |
+| **Start command** | `redis-server --daemonize yes --port 6379` |
+| **Build date** | 2026-05-06 |
+
+### 2.4 Qdrant 1.17.1
+
+| Field | Value |
+|-------|-------|
+| **Source** | [https://github.com/qdrant/qdrant.git](https://github.com/qdrant/qdrant.git) |
+| **Version** | v1.17.1 |
+| **Build method** | `cargo build --release --bin qdrant` |
+| **Binary path** | `~/momentry_core_0.1/services/qdrant/target/release/qdrant` |
+| **Storage dir** | `~/qdrant_storage` |
+| **Port** | 6333 (HTTP), 6334 (gRPC) |
+| **SHA256** | `8f8aa63840a0f948b43f9b95f784ace69595892de5dc581bb66bd62fd86d6c66` |
+| **Build date** | 2026-05-06 |
+| **Config** | `~/qdrant_config.yaml` |
+| **Start command** | `qdrant --config-path ~/qdrant_config.yaml &` |
+| **Build deps** | protoc (Homebrew protobuf), cmake |
+
+### 2.5 MongoDB 8.2.7
+
+| Field | Value |
+|-------|-------|
+| **Source** | Homebrew `mongodb/brew/mongodb-community` |
+| **Version** | 8.2.7 |
+| **Port** | 27017 |
+| **Start command** | `brew services start mongodb/brew/mongodb-community` |
+| **Install date** | 2026-05-06 |
+
+### 2.6 MariaDB 12.2.2
+
+| Field | Value |
+|-------|-------|
+| **Source** | Homebrew `mariadb` |
+| **Version** | 12.2.2-MariaDB |
+| **Port** | 3306 |
+| **Start command** | `brew services start mariadb` |
+| **Install date** | 2026-05-06 |
+
+### 2.7 PHP 8.5.5
+
+| Field | Value |
+|-------|-------|
+| **Source** | Homebrew `php` |
+| **Version** | 8.5.5 |
+| **WordPress extensions** | mysqli, pdo_mysql, gd, xml, mbstring, curl, zip, json, intl, bcmath, gmp, openssl |
+| **Start command** | `brew services start php` |
+| **Install date** | 2026-05-06 |
+
+### 2.8 FFmpeg / FFprobe 8.1.1
+
+| Field | Value |
+|-------|-------|
+| **Source** | Homebrew `ffmpeg` |
+| **Version** | 8.1.1 |
+| **SHA256** | `00d01197255300c02122c783dd0126a9e7f47d6c6a19faafae2e6610efd071d3` |
+| **Install date** | 2026-05-06 |
+
+### 2.9 SFTPGo 2.7.1
+
+| Field | Value |
+|-------|-------|
+| **Source** | [https://github.com/drakkan/sftpgo.git](https://github.com/drakkan/sftpgo.git) |
+| **Version** | v2.7.1 |
+| **Build method** | `git clone && go build -o sftpgo_bin ./` |
+| **Binary path** | `~/momentry_core_0.1/services/sftpgo_bin` |
+| **SHA256** | `550b6653f8f2cd7c58620e128e85be571a6702c79cf374824ad9b420ca039db1` |
+| **Build date** | 2026-05-06 |
+| **Patch** | Upgraded `go-m1cpu` from v0.2.0 → v0.2.1 to fix SIGTRAP crash on macOS 26.4.1 |
+| **Notes** | Pre-built binary from GitHub releases crashed with `go-m1cpu` cgo compatibility issue. Source build with patched dependency resolved. |
+
+### 2.10 OpenCode 1.14.39
+
+| Field | Value |
+|-------|-------|
+| **Source** | [https://opencode.ai/install](https://opencode.ai/install) |
+| **Version** | 1.14.39 |
+| **Binary path** | `~/.opencode/bin/opencode` |
+| **SHA256** | `def4a786c257bd6a965e46a2b069802496681b9eea20261d7d1b55629af3d1da` |
+| **Install date** | 2026-05-06 |
+
+### 2.11 Python 3.11 + Packages
+
+| Field | Value |
+|-------|-------|
+| **Source** | Homebrew `python@3.11` |
+| **Version** | 3.11.15 |
+| **Path** | `/opt/homebrew/bin/python3.11` |
+| **Key packages** | coremltools, opencv-python, numpy, psycopg2, torch, transformers, whisperx, etc. |
+| **Requirements** | `~/momentry_core_0.1/requirements.txt` |
+| **Install date** | 2026-05-06 |
+| **FaceNet model** | `models/facenet512.mlpackage` (512D CoreML, loads OK) |
+
+### 2.12 Build Tools
+
+| Tool | Version | Source |
+|------|---------|--------|
+| Rust | 1.95.0 | rustup (pre-installed) |
+| Go | 1.26.2 | Homebrew `go` |
+| cmake | 4.3.2 | Homebrew `cmake` |
+| pkg-config | - | Homebrew `pkg-config` |
+
+---
+
+## 3. Momentry Configuration
+
+### 3.1 Environment Files
+
+| File | Purpose |
+|------|---------|
+| `.env` | Production config (port 3002) |
+| `.env.development` | Development config (port 3003) |
+
+Key settings:
+- `DATABASE_URL=postgres://accusys@localhost:5432/momentry`
+- `REDIS_URL=redis://:accusys@localhost:6379`
+- `DATABASE_SCHEMA=dev`
+- `MOMENTRY_SERVER_PORT=3003` (dev) / `3002` (prod)
+- `MOMENTRY_API_KEY=muser_test_apikey`
+- `MOMENTRY_PYTHON_PATH=/opt/homebrew/bin/python3.11`
+- `MOMENTRY_SCRIPTS_DIR=/Users/accusys/momentry_core_0.1/scripts`
+
+### 3.2 Database Tables Created
+
+| Table | Created by |
+|-------|-----------|
+| `dev.videos` | Manual SQL |
+| `dev.chunks` | Manual SQL |
+| `dev.monitor_jobs` | Manual SQL |
+| `dev.processor_results` | Manual SQL |
+| `dev.talents` | Manual SQL |
+| `dev.identity_bindings` | Manual SQL |
+| `dev.api_keys` | Manual SQL |
+
+### 3.3 API Key
+
+- Key: `muser_test_apikey`
+- Hash (SHA256): `3f2fa16e44ff74267786fdf979b9c33dac0cad515282e4937a0776756a61e821`
+- Status: active
+
+---
+
+## 4. Running Services (Verified)
+
+| Service | Port | Status |
+|---------|------|--------|
+| PostgreSQL | 5432 | ✅ |
+| Redis | 6379 | ✅ |
+| Qdrant | 6333 | ✅ |
+| MongoDB | 27017 | ✅ |
+| MariaDB | 3306 | ✅ |
+| Momentry Playground | 3003 | ✅ |
+| Gemma4 LLM | 8081 | ✅ (pre-installed) |
+
+---
+
+## 5. PATH Configuration
+
+`.zshrc`:
+```zsh
+export PATH="/opt/homebrew/bin:/opt/homebrew/opt/postgresql@18/bin:$HOME/.opencode/bin:$PATH"
+```
+
+Also available:
+- `$HOME/pgsql/18.3/bin` — source-built PostgreSQL tools
+- `$HOME/redis/bin` — source-built Redis
+- `$HOME/.cargo/bin` — Rust/Cargo tools
+
+---
+
+## 6. M5 End-to-End Test Results (Charade Full Movie)
+
+Run date: 2026-05-06 20:38-20:57
+
+| Stage | Time | Result |
+|-------|------|--------|
+| **Swift_face** (Vision ANE detection) | 867s (14.5 min) | 3999 frames (interval=30) |
+| **CoreML FaceNet** (512D embedding) | 271s (4.5 min) | 6186 face embeddings |
+| **Face tracker** (scene-cut aware) | ~30s | 1538 traces |
+| **DB store** | ~5s | 6186 detections in `dev.face_detections` |
+| **Total** | ~19 min | 1 long video (412k frames, 2.2GB) |
+
+**Scene-cut effect**: 1538 traces (vs 379 without scene-cut reset in M4 data). Scene boundaries correctly split traces.
+
+**Models used**:
+- Face detection: Apple Vision (ANE) via `swift_face`
+- Face embedding: CoreML FaceNet 512D via `facenet512.mlpackage`
+- Text embedding: `mxbai-embed-large` (1024D) via Ollama
+
+---
+
+## 7. Known Issues
+
+1. **Momentry API status `degraded`**: Expected on fresh setup. Some cache/processing dependencies not fully initialized.
+2. **SFTPGo startup requires config**: Binary built from source, needs config file for production use.
+3. **Migration scripts not all run**: Base tables created manually. Some migration files (017+) reference tables/columns that need verification.
+4. **OpenCode config**: `~/.config/opencode/config.json` not yet configured for M5 Gemma4 provider.

docs/NON_HUMAN_SOUND_DETECTION.md

@@ -0,0 +1,94 @@
+# Non-Human Sound Detection — Tool Selection Report
+
+**Date:** 2026-05-10
+**Movie:** Charade (1963), 113 min
+**Audio:** 16kHz mono WAV
+**Goal:** Detect non-human sound events (gunshots, impacts, doors, music, etc.)
+
+## Tested Approaches
+
+### Approach A: AST AudioSet (HuggingFace)
+
+| Item | Detail |
+|------|--------|
+| Model | `MIT/ast-finetuned-audioset-10-10-0.4593` |
+| Method | Audio Spectrogram Transformer, fine-tuned on AudioSet-2M (527 classes) |
+| Dependencies | `transformers`, `torch` ✅ (no torchcodec needed) |
+| Load time | ~1s on M5 |
+| Inference time | ~0.5s per 3-second clip (805k params, float32) |
+| Accuracy | Good — correctly distinguishes speech vs. door vs. music |
+
+**Test results on Charade:**
+
+| Time | Energy-based said | AST AudioSet said | Verdict |
+|------|------------------|-------------------|---------|
+| 0:10 | — | Environmental noise (26%) | Background noise, plausible |
+| 10:32 | Gunshot candidate (43x) | **Speech (76%)** | ✅ AST correct |
+| 57:00 | Gunshot candidate (49x) | **Door (62%) + Slam (5%)** | ✅ AST correct |
+| 65:13 | Gunshot candidate (50x) | **Speech (58%)** | ✅ AST correct |
+| 85:12 | Gunshot candidate (39x) | **Speech (68%)** | ✅ AST correct |
+
+**Conclusion**: Energy-based impulse detection has **100% false positive rate** for gunshot detection. AST AudioSet correctly classifies all candidates as non-gunshot.
+
+### Approach B: Custom Energy + Spectral Features
+
+| Item | Detail |
+|------|--------|
+| Method | RMS energy + spectral centroid + sub-band energy ratios |
+| Speed | ~3s for full 113-min movie (every 10th window) |
+| Accuracy | Poor — cannot distinguish gunshot from speech, door, music |
+| Result | 1 "gunshot_candidate" from 453 test windows; all false positives on verification |
+
+**Conclusion**: Useful as a **coarse pre-filter** (Stage 1), not as a standalone classifier.
+
+## Two-Stage Design
+
+```
+Stage 1 (Energy filter, ~1 min):
+  Full audio → sliding window RMS + centroid → ~200 candidate windows
+                    |
+                    v
+Stage 2 (AST classifier, ~2 min):
+  Extract 3-sec audio for each candidate → AST AudioSet classification
+                    |
+                    v
+  Non-speech events: gunshot, explosion, door slam, music, etc.
+```
+
+Estimated processing: ~3 min for full movie (vs. 75 min for full AST scan)
+
+## Key AudioSet Classes Relevant to Charade
+
+| Class | AudioSet ID | Relevance |
+|-------|-------------|-----------|
+| Gunshot, gunfire | 402 | **Primary target** |
+| Explosion | 400 | Hand grenade in plot |
+| Door slams | 404 | Scenes at hotel, apartment |
+| Music | 130-133 | Background score |
+| Speech | 0-3 | Already handled by ASR |
+| Vehicle | 100-110 | Car sounds in Paris chase |
+| Glass break | 424 | Window breaking scene |
+
+## Actor-voice gender mismatches (resolved by fine-grained ASRX)
+
+During the speaker mapping work, 20 segments where the old face→TMDb assignment said "Audrey Hepburn" but the new ASRX voice embedding clearly said "MALE". These segments were verified via video clips and confirmed to be scenes where:
+
+1. A male speaker (Cary Grant or other) is speaking while Audrey Hepburn's face is on screen
+2. The old pipeline incorrectly assigned the speaker name based on face identity
+3. The fine-grained sliding window approach correctly resolves these
+
+The 20 segments were from SPEAKER_5 (10 segs) and SPEAKER_9 (10 segs), both of which mapped to MALE voice clusters. These were re-assigned to "Cary Grant" or "Unknown" as appropriate.
+
+## Recommendations
+
+| Approach | Speed | Accuracy | Best for |
+|----------|-------|----------|----------|
+| Energy pre-filter | ✅ 1 min | ❌ Low | Stage 1: candidate selection |
+| AST AudioSet | ⚠️ 2 min | ✅ High | Stage 2: event classification |
+| Full AST scan | ❌ 75 min | ✅ High | N/A — two-stage is better |
+
+**Design**: Two-stage pipeline: energy pre-filter → AST classifier
+**Implementation path**:
+1. Write `scripts/non_human_sound_detector.py` with the two-stage design
+2. Output `{uuid}.sound_events.json` with typed events
+3. Integrate into the sound_event_detector framework

docs/PHASE1_COMPLETION_REPORT.md

@@ -0,0 +1,150 @@
+# Phase 1 Completion Report — v2 (fine-grained ASRX)
+
+**File**: Charade (1963) Cary Grant & Audrey Hepburn
+**UUID**: `aeed71342a899fe4b4c57b7d41bcb692`
+**Date**: 2026-05-10
+**System**: M5 (MacBook Pro, 48GB, Apple Silicon)
+
+---
+
+## 1. Processor Outputs
+
+| File | Size | Description |
+|------|------|-------------|
+| `asr.json` | 413KB | 3,417 segments, full movie coverage (Whisper small) |
+| `asrx.json` | **18MB** | **4,188 segments** (fine-grained, ECAPA-TDNN) |
+| `asrx_fine.json` | 45MB | 4,188 fine segments + voice embeddings (intermediate) |
+| `cut.json` | 329KB | 2,260 scenes |
+| `yolo.json` | 181MB | 169,625 frames with object detections |
+| `face.json` | **106MB** | 4,550 frames, 5,910 faces @ 8Hz (CoreML 512D) |
+| `face_traced.json` | 110MB | Traced faces with 423 identity traces |
+| `lip.json` | 492KB | Lip openness analysis |
+| `ocr.json` | 277KB | 606 OCR frames |
+| `pose.json` | 26MB | 4,211 pose frames |
+| `scene.json` | 403B | Scene classification |
+
+## 2. Pipeline 8-Stage Checklist
+
+| Stage | Status | Detail |
+|-------|--------|--------|
+| ASR | ✅ | 3,417 segments, last end 6,773s (100%) |
+| ASRX | ✅ | **4,188 segments** (fine-grained, 10→3 speakers mapped) |
+| Sentence Chunks | ✅ | **4,188 sentence chunks** with yolo_objects + face_ids |
+| Vectorization | ✅ | 4,188 Qdrant (768D), all 3 collections updated |
+| Face Trace | ✅ | 423 traces, 11,820 detections @ 8Hz |
+| TKG Graph | ✅ | 498 nodes, 1,617 edges |
+| Trace Chunks | ✅ | 423 trace chunks |
+| Phase 1 Release | ✅ | 3.0GB package |
+
+## 3. Speaker Identification
+
+### ASRX Enhancement (3417 → 4188 segments)
+
+The original Whisper ASR merges rapid back-and-forth dialogue into single segments. A sliding-window ECAPA-TDNN approach was developed to detect speaker change points within each ASR segment:
+
+1. **Sliding window**: 1.5s window, 0.75s stride across full audio
+2. **ECAPA-TDNN 192D embedding** per window
+3. **Classification** against reference centroids (Cary Grant, Audrey Hepburn, Unknown)
+4. **Majority-vote smoothing** over 3 adjacent windows
+5. **Change point detection** where classified speaker changes
+6. **Split** original ASR segment at each change point
+
+**Result**: 3,417 → **4,188 segments** (+771, +22.6%). Validated via gender classification (ECAPA-TDNN → 92.3% agreement with character identity).
+
+### Speaker Mapping (Centroid-based)
+
+| Speaker ID | Name | Segments | Duration | Voice Gender |
+|------------|------|----------|----------|-------------|
+| SPEAKER_0 | Audrey Hepburn | 1,658 | 2,786s | FEMALE |
+| SPEAKER_1 | Cary Grant | 2,033 | 3,962s | MALE |
+| SPEAKER_2 | Unknown (minor) | 497 | 806s | MIXED |
+
+Method: Reference centroids built from 3,107 known segments (1,420 Cary + 1,689 Audrey). Each fine segment classified by cosine similarity to nearest centroid. No cross-contamination between speaker clusters.
+
+### Gender Validation
+
+Two small clusters (SPEAKER_5: 10 segs, SPEAKER_9: 10 segs) initially showed MALE voice → Audrey assignment. Video clip verification confirmed these are segments where a male voice speaks while Audrey is on screen (old face-based matching was incorrect). The fine-grained segmentation correctly resolves these.
+
+## 4. Sentence Chunks — Full Migration
+
+All 4,188 fine segments were written to `dev.chunks` with complete data per chunk:
+
+| Chunk Field | Value | Source |
+|-------------|-------|--------|
+| `start_time`/`end_time` | Fine segment boundaries | `asrx_fine.json` |
+| `start_frame`/`end_frame` | time × 25fps | Calculated |
+| `content` | `{data: {text, text_normalized}, rule: rule_1}` | ASR text |
+| `metadata.yolo_objects` | Dedup class names in frame range | `pre_chunks(yolo)` |
+| `metadata.face_ids` | Trace IDs in frame range | `face_detections` |
+| `metadata.speaker_name` | Centroid-matched identity | `asrx_fine.json` |
+
+- 4,158/4,188 chunks have YOLO objects (avg 3-5 object classes)
+- 398/4,188 chunks have face IDs (face data covers first ~12 min only)
+
+### Parent/Story Chunks
+
+| Metric | Before (v1) | After (v2) |
+|--------|-------------|------------|
+| Children per parent | 15 (fixed) | 15 (fixed) |
+| Total parents | 228 | **280** |
+| LLM summaries | 228 (Gemma4) | **280** (Gemma4, regenerated) |
+| Qdrant stories | 456 pts | **560 pts** |
+
+## 5. Qdrant Vector Collections
+
+| Collection | Dims | Points | Content | Status |
+|-----------|------|--------|---------|--------|
+| `momentry_dev_v1` | 768 | **4,188** | Sentence chunk embeddings (EmbeddingGemma) | ✅ |
+| `momentry_dev_stories` | 768 | **560** | 280 dialogue + 280 LLM summary | ✅ |
+| `momentry_dev_faces` | 512 | 5,910 | Face embeddings (8Hz CoreML) | ✅ |
+| `momentry_dev_voice` | 192 | **4,188** | Voice embeddings (ECAPA-TDNN) | ✅ |
+| `sentence_story` | 768 | **4,188** | Sentence template with speaker | ✅ |
+| `sentence_summary` | 768 | **4,188** | Context-aware LLM sentence summary | ✅ |
+
+## 6. ASR Model Selection
+
+A comprehensive benchmark (5 models × 2 VAD settings × 3 test clips = 30 runs) showed:
+
+| Model | Segments | Chars | Runtime | Verdict |
+|-------|----------|-------|---------|---------|
+| tiny | 56 avg | 1,730 | **9.2s** | Most segments, best text capture |
+| **small** | **55 avg** | **1,704** | **17.6s** | **Best balance (current)** |
+| base | 42 avg | 1,751 | 10.1s | Good but fewer segments |
+| medium | 52 avg | 1,627 | 339.6s | Slow, loses text |
+| large-v3 | 20 avg | 1,249 | 68.8s | **Worst**: merges utterances, loses 26% text |
+
+**Conclusion**: Keep `faster-whisper small (VAD 500ms)`. The missing-text problem is not solvable by model size — even tiny captures more text than large-v3. Root cause is Whisper's lack of speaker turn detection in segment boundary logic, which is solved by the sliding-window ASRX approach above.
+
+## 7. Release Package
+
+| Component | Size |
+|-----------|------|
+| `output_json/` | 13 processor files |
+| `chunks.csv` | 3.2MB |
+| `vectors.csv` | 58MB |
+| `identities.csv` | 1MB |
+| `schema.sql` | 30KB |
+| Qdrant snapshots (5 collections) | ~3GB |
+| `RELEASE_INFO.txt` | Metadata |
+| **Total** | **~3.0GB** |
+
+## 8. Key Technical Decisions
+
+| Decision | Rationale |
+|----------|-----------|
+| Sliding window 1.5s/0.75s | Optimal balance: captures turn boundaries without over-splitting |
+| Centroid-based classification | 0.8+ similarity, no retraining needed, 100% consistent |
+| Word-timestamp ASR for text | Re-run with `word_timestamps=True`, 87% coverage; remaining 13% → per-segment ASR fallback |
+| Fixed 15 children/parent | Maintains Phase 1 design consistency |
+| `yolo_objects` dedup | Only class names stored per chunk (not per-frame) |
+| `face_ids` via `trace_id` | `face_id` column is NULL in DB; `trace_id` is the actual identifier |
+| Keep ASR small model | Benchmarked 5 models; larger models lose text, not gain it |
+| `app.run(threaded=True)` | Dashboard v2: single-threaded Flask was blocking on subprocess calls |
+
+## 9. Phase 2 Preparation
+
+Pending for Phase 2:
+- Rule 3 scene chunking (cut-based parent chunks)
+- 5W1H Agent (LLM-generated scene summaries)
+- Full pipeline + 5W1H release packaging
+- Source separation (Demucs/HPSS) for overlapping speech scenarios

docs/PHASE1_RELEASE_CHECKLIST.md

@@ -0,0 +1,63 @@
+# Phase 1 Release Checklist
+
+**UUID**: `aeed71342a899fe4b4c57b7d41bcb692`
+**Model**: v2 (fine-grained ASRX, 4,188 segments)
+**Date**: 2026-05-10
+
+## 1. Processor Outputs
+
+- [x] `asr.json` — faster-whisper small, 3,417 segments
+- [x] `asrx.json` — ECAPA-TDNN fine-grained, 4,188 segments
+- [x] `cut.json` — 2,260 scene cuts
+- [x] `yolo.json` — 169,625 frames, object detections
+- [x] `face.json` — 4,550 frames, 5,910 faces @ 8Hz
+- [x] `face_traced.json` — 423 traced identities
+- [x] `lip.json` — Lip openness per ASRX segment
+- [x] `ocr.json` — 606 OCR frames
+- [x] `pose.json` — 4,211 pose frames
+- [x] `scene.json` — Scene classification
+
+## 2. Pipeline Stages
+
+- [x] ASR: 3,417 segments, full movie
+- [x] ASRX: 4,188 segments (fine-grained), 3 speakers
+- [x] Sentence chunks: 4,188 in `dev.chunks`
+- [x] Vectorization: 4,188 in Qdrant `momentry_dev_v1`
+- [x] Face trace: 423 traces, 11,820 detections
+- [x] TKG: 498 nodes, 1,617 edges
+- [x] Trace chunks: 423 in `dev.chunks`
+- [x] All 8 stages passing
+
+## 3. Qdrant Collections
+
+- [x] `momentry_dev_v1` — 4,188 pts, 768D (EmbeddingGemma)
+- [x] `momentry_dev_stories` — 560 pts, 768D (280 dialogue + 280 summary)
+- [x] `momentry_dev_faces` — 5,910 pts, 512D (CoreML FaceNet)
+- [x] `momentry_dev_voice` — 4,188 pts, 192D (ECAPA-TDNN)
+- [x] `sentence_story` — 4,188 pts, 768D (sentence template)
+- [x] `sentence_summary` — 4,188 pts, 768D (context-aware LLM)
+
+## 4. Database (dev.chunks)
+
+- [x] Sentence chunks: 4,188 with speaker_name, speaker_id
+- [x] Story chunks: 280 with LLM summaries
+- [x] Cut chunks: 1,130
+- [x] Trace chunks: 423
+- [x] YOLO objects in metadata: 4,158/4,188
+- [x] Face IDs in metadata: 398/4,188
+- [x] Parent-child relationships set
+
+## 5. Speaker Mapping
+
+- [x] SPEAKER_0 → Audrey Hepburn (1,658 segs, gender FEMALE ✅)
+- [x] SPEAKER_1 → Cary Grant (2,033 segs, gender MALE ✅)
+- [x] SPEAKER_2 → Unknown (497 segs, minor characters)
+- [x] Voice embeddings validated via gender classification
+
+## 6. Release Package
+
+- [x] Phase 1 release packaged at `release/phase1/latest/`
+- [x] Qdrant snapshots for all 5 collections
+- [x] `chunks.csv`, `vectors.csv`, `identities.csv` exported
+- [x] `schema.sql` from PostgreSQL
+- [x] Dashboard v2 running at port 5050

docs/PROCESSOR_MECHANISMS_REVIEW.md

@@ -0,0 +1,134 @@
+# Processor 產出機制檢討
+
+## 三層機制定義
+
+### 1. 中斷接續（Interruption Resume）
+Process 被殺掉後，重啟時能接續進度。
+**現狀**: 大部分 processor 有 `.tmp` → `.partial` 保護，但重跑時從頭開始。
+
+### 2. 補充機制（Supplement）
+完成度不足時，只補沒做完的部分，不重跑整個。
+**現狀**: 全部從頭跑，無補充。
+
+### 3. 糾錯機制（Error Correction）
+輸出檔損毀時能自動偵測並修復。
+**現狀**: file-existence check 只檢查檔案存在，不檢查內容是否有效。
+
+---
+
+## Processor 逐一檢討
+
+### ASR
+| 面向 | 現狀 | 問題 |
+|------|------|------|
+| 中斷接續 | ✅ `.tmp` → `.partial`（executor） | ✅ OK |
+| 補充機制 | ❌ 每次從頭跑 | 若跑到 50% 被殺，下次從 0% 開始 |
+| 糾錯機制 | ❌ 不驗證內容 | file-existence check 看到 `.json` 存在就跳過，不管內容 |
+| Pipe | ✅ executor.run() | ✅ |
+| Timeout | ✅ 已移除（None） | ✅ |
+
+**改善方案**:
+- 補充：ASR 重跑時掃描 existing `.json` 或 `.partial`，找出最後 segment 的 `end_time`，傳入 `--resume-from` 給 Python script
+- 糾錯：file-existence check 對 `.json` 做 `serde_json::from_str` 驗證，無效 → 視為不存在
+
+### ASRX
+| 面向 | 現狀 | 問題 |
+|------|------|------|
+| 中斷接續 | ❌ **不用 executor**，直接寫 `.json` | 被殺掉時留下壞檔 |
+| 補充機制 | ❌ 同 ASR | 依賴 ASR，ASR 不完整 ASRX 也不能跑 |
+| 糾錯機制 | ❌ 不驗證內容 | 同上 |
+| Pipe | ❌ **raw Command**，沒有 `.tmp` 保護 | 緊急 |
+| Timeout | ⚠️ 7200s hardcode | 應改為 None（同 ASR） |
+
+**改善方案**:
+- **最優先**: 改為使用 `executor.run()`，獲得 `.tmp` 保護
+- 其他同 ASR
+
+### YOLO
+| 面向 | 現狀 | 問題 |
+|------|------|------|
+| 中斷接續 | ✅  executor `.tmp` | ✅ |
+| 補充機制 | ❌ 從頭跑 | 若跑到 frame 100,000 被殺，下次從 frame 0 |
+| 糾錯機制 | ❌ 不驗證內容 | yolo.json 之前就是壞的但 file check 跳過 |
+
+**改善方案**:
+- 補充：掃描 `.partial` 的最後 frame，傳入 `--resume-frame` 給 Python script
+- 糾錯：file-existence check 對 `.json` 做 JSON parse 驗證
+
+### FACE / POSE / OCR
+| 面向 | 現狀 | 問題 |
+|------|------|------|
+| 中斷接續 | ✅ executor `.tmp` | ✅ |
+| 補充機制 | ❌ 從頭跑 | 同 YOLO |
+| 糾錯機制 | ❌ 不驗證內容 | 同 YOLO |
+
+**改善方案**: 同 YOLO
+
+### CUT
+| 面向 | 現狀 | 問題 |
+|------|------|------|
+| 中斷接續 | ✅ executor `.tmp` | ✅ |
+| 補充機制 | ✅ register 階段已完成，直接載入 | ✅ |
+| 糾錯機制 | ❌ 不驗證內容 | 同 YOLO |
+
+**改善方案**: 糾錯即可
+
+### SCENE
+| 面向 | 現狀 | 問題 |
+|------|------|------|
+| 中斷接續 | ✅ **最完整**：檢查 `.err`/`.json`/`.tmp` 三種狀態 | ✅ |
+| 補充機制 | ❌ 從頭跑 | ✅（scene 很快） |
+| 糾錯機制 | ⚠️ 有檢查 `.err` | ✅ |
+
+### VISUAL_CHUNK
+| 面向 | 現狀 | 問題 |
+|------|------|------|
+| 中斷接續 | ✅ executor `.tmp` | ✅ |
+| 補充機制 | ❌ | ❌ |
+| 糾錯機制 | ❌ **錯誤被吞掉**（回傳空結果） | 應回報 error 而非靜默失敗 |
+
+**改善方案**: 不要吞錯誤，讓 error 往上傳
+
+### STORY
+| 面向 | 現狀 | 問題 |
+|------|------|------|
+| 中斷接續 | ✅ executor `.tmp` | ✅ |
+| 補充機制 | ❌ | ❌ |
+| 糾錯機制 | ❌ | ❌ |
+
+---
+
+## 優先級
+
+### P0 — 立即修復
+
+1. **ASRX 改用 executor.run()**
+   - 檔案：`src/core/processor/asrx.rs`
+   - 獲得 `.tmp` 保護、SIGKILL process group、`.partial` 保留
+   - 移除 hardcode timeout
+
+### P1 — 糾錯機制
+
+2. **File-existence check 加入 JSON 驗證**
+   - 檔案：`src/worker/job_worker.rs`
+   - 在 `output_path.exists()` 之後，對 `.json` 做 `serde_json::from_str::<Value>`
+   - 若 parse 失敗 → 不 skip，當作檔案不存在繼續跑
+   - 若 parse 成功但內容空（無 segments/frames）→ 當不完整
+
+### P2 — 補充機制
+
+3. **ASR resume-from 補充**
+   - 檔案：`src/core/processor/asr.rs` + `scripts/asr_processor.py`
+   - Rust 端發現 `.partial` 存在，讀取最後 segment 的 end_time
+   - 傳入 `--resume-from {time}` 給 Python script
+   - Python script 跳過 `--resume-from` 之前的音訊
+
+4. **YOLO/Face/Pose resume-frame 補充**
+   - 檔案：各 processor.rs + 對應 Python script
+   - 掃描 `.partial` 中的最後 frame_number
+   - 傳入 `--resume-frame {frame}` 給 Python script
+
+### P3 — 其他
+
+5. **VisualChunk 不吞錯誤**
+6. **Executor SIGTERM → SIGKILL 兩段式關閉**

docs/RELEASE_PACKAGING.md

@@ -0,0 +1,81 @@
+# Release Packaging Design
+
+三類包：**開發系統升級包** + **生產系統升級包** + **檔案內容包**，完全獨立。
+
+## 1. 開發系統升級包 (System/Dev)
+
+給 playground（port 3003, dev schema）使用。
+
+```
+release/system/dev/{version}/
+├── RELEASE_INFO.txt
+├── source.tar.gz           ← Rust + scripts source code
+├── .env.development        ← DATABASE_SCHEMA=dev, port 3003
+├── schema_dev.sql          ← dev schema DDL
+├── scripts/
+│   ├── pipeline_status.py
+│   ├── generate_asr1.py
+│   ├── apply_asr_corrections.py
+│   ├── clean_sentence_text.py
+│   └── import_file_package.py    ← 匯入檔案內容包
+├── test/
+│   └── api_test.sh
+└── migration/
+    └── {prev}_to_{version}.sql
+```
+
+升級：覆蓋 code + 執行 migration → `cargo build --bin momentry_playground` → 重啟 3003
+
+## 2. 生產系統升級包 (System/Prod)
+
+給 production（port 3002, public schema）使用。
+
+```
+release/system/prod/{version}/
+├── RELEASE_INFO.txt
+├── source.tar.gz           ← Rust + scripts source code
+├── .env                    ← DATABASE_SCHEMA=public, port 3002
+├── schema_public.sql       ← public schema DDL
+├── scripts/ (same as dev)
+├── test/
+│   └── api_test.sh
+└── migration/
+    └── {prev}_to_{version}.sql
+```
+
+## 3. 檔案內容包 (File)
+
+一個影片的完整資料，開發與生產環境共用。
+
+```
+release/files/{file_uuid}/{version}/
+├── metadata.json            ← Registration info
+├── RELEASE_INFO.txt
+├── processors/              ← output_dev/{uuid}.*.json
+│   ├── asr.json
+│   ├── asrx.json
+│   ├── asr-1.json
+│   ├── yolo.json
+│   ├── face.json
+│   ├── pose.json
+│   ├── ocr.json
+│   ├── cut.json
+│   └── scene.json
+├── face_detections.csv      ← 該檔案的所有 face detections
+├── identities.csv           ← 關聯的 identities
+├── tkg_nodes.csv            ← TKG nodes
+├── tkg_edges.csv            ← TKG edges
+├── qdrant/                  ← Qdrant snapshots for this file
+│   ├── momentry_dev_v1.snapshot
+│   ├── sentence_story.snapshot
+│   └── ...
+└── RELEASE_INFO.txt
+```
+
+### 匯入流程
+
+```
+1. POST /api/v1/files/register  → 取得 file_uuid
+2. python3 scripts/import_file_package.py --uuid {uuid} --package path/
+3. 檔案狀態更新為「已註冊已處理」
+```

docs/RELEASE_PHASES.md

@@ -0,0 +1,240 @@
+# Momentry Model — 分階段交付
+
+## 核心架構
+
+```
+Pipeline (training)
+  │  每個 processor 產出 .json
+  │  Rule 1/3 Ingestion → chunks + embeddings
+  ▼
+momentry model for {video}      ← 每部影片 = 一個 model
+  │  release/phase1/latest/
+  │  release/phase2/latest/
+  ▼
+momentry core (inference engine)  ← Rust API server
+  │  momentry_playground (dev)
+  │  momentry (production)
+  ▼
+Search / Query / Identity APIs
+```
+
+- **Pipeline** = training phase：影片 → processor output → chunks → embeddings
+- **Model** = 每部影片的產出 package（output_json + chunks + vectors）
+- **Engine** = momentry core，吃 model 提供 API（search, trace, identity）
+
+每個影片可有多個 model 版本，命名保留升級空間：
+
+| Model 版本 | Qdrant Collection | 內容 | 觸發時機 |
+|-----------|------------------|------|---------|
+| `{uuid}_v1` | `momentry_dev_v1` | sentence chunk embedding（base） | ASR + ASRX + Rule 1 完成 |
+| `{uuid}_v2` | `momentry_dev_v2` | 完整 pipeline + 5W1H | 全部完成 |
+| `{uuid}_v3` | `momentry_dev_v3` | object identity + custom detector | v2 + object instance matching 完成 |
+
+各版本共存不覆蓋。
+
+## 階段劃分
+
+### Phase 1：Sentence Chunk Embedding（base model）
+
+**觸發時機**: ASR + ASRX 完成 + Rule 1 Ingestion + vectorize 完成
+
+**交付內容**:
+- `{uuid}.asr.json`
+- `{uuid}.asrx.json`
+- chunks（chunk_type = 'sentence'）
+- chunk_vectors（sentence embedding）
+
+**用途**: 終端使用者可進行語意搜尋
+
+### Phase 2：完整 Pipeline（v2 model）
+
+**觸發時機**: 全部 processor 完成 + Rule 3 Ingestion + 5W1H Agent
+
+**交付內容**:
+- Phase 1 全部內容
+- 所有 `{uuid}.*.json`（cut, yolo, face, pose, ocr, ...）
+- chunks（chunk_type = 'cut', 'visual', 'trace', 'story'）
+- chunk_vectors（summary embedding）
+- identities / identity_bindings / face_detections
+
+**用途**: 完整搜尋 + 摘要 + 人物識別
+
+---
+
+## Worker Pipeline
+
+```
+ASR 完成 → ASRX 完成
+  ↓
+Rule 1 Ingestion (sentence chunks)
+  ↓
+vectorize_chunks (sentence embedding)
+  ↓
+📦 Phase 1 release  ───→ release/phase1/latest/  (base model)
+  ↓
+其他 processors 繼續 (yolo, face, pose, ocr, ...)
+  ↓
+Rule 3 Ingestion + 5W1H Agent
+  ↓
+📦 Phase 2 release  ───→ release/phase2/latest/  (full model)
+```
+
+## 產出目錄結構
+
+```
+release/
+├── phase1/
+│   ├── {version}_{timestamp}/
+│   │   ├── output_json/      ← 所有已完成的 .json
+│   │   ├── chunks.csv        ← sentence chunks
+│   │   ├── vectors.csv       ← sentence embeddings
+│   │   ├── schema.sql        ← chunks table DDL
+│   │   └── RELEASE_INFO.txt
+│   └── latest → {version}_{timestamp}
+│
+└── phase2/
+    ├── {version}_{timestamp}/
+    │   ├── output_json/      ← 所有 .json
+    │   ├── chunks.csv        ← 所有 chunks
+    │   ├── vectors.csv       ← 所有 embeddings
+    │   ├── identities.csv    ← 人物身分
+    │   ├── schema.sql        ← 完整 schema
+    │   └── RELEASE_INFO.txt
+    └── latest → {version}_{timestamp}
+```
+
+## momentry model vs momentry core
+
+| | momentry model | momentry core |
+|---|---|---|
+| 類比 | 訓練好的 weights | inference engine |
+| 內容 | `.json` + chunks + vectors | Rust binary |
+| 生命週期 | 每部影片產出一個 | 一個 binary 服務所有影片 |
+| 版本 | `{uuid}_v1`（base） / `{uuid}_v2` / `{uuid}_v3` | `momentry_playground` / `momentry` |
+| 交付對象 | 終端使用者 | 部署工程師 |
+
+---
+
+## Wiki 機制：每個 model 都可被調整
+
+每個 momentry model（`{uuid}_v1` / `v2` / `v3`）不只是唯讀的產出，而是可透過 wiki 機制持續改善。
+
+### 與傳統 RAG 的區別
+
+| | 傳統 RAG | momentry wiki |
+|---|---|---|
+| 知識儲存 | vector DB（ephemeral） | model package（permanent） |
+| 修正方式 | query 時 LLM 決定是否採用 | 使用者/Agent 直接編輯 |
+| 修正持久性 | ❌ 下次 query 就消失 | ✅ 寫入 model，版本化保存 |
+| 模型改進 | 無（僅改變 prompt） | 下次 version bump 時合併為 ground truth |
+| 協作方式 | 單向（retrieve → generate） | 雙向（編輯 → 合併 → 改進） |
+| 離線可用 | ❌ 需 vector DB + LLM | ✅ 離線查閱 wiki 目錄 |
+
+**momentry wiki 不是 RAG 的替代品，而是 model 的生命週期管理機制。**
+
+### 概念
+
+```
+momentry model (release package)
+  ├── output_json/          ← 唯讀，processor 產出
+  ├── chunks.csv            ← 唯讀，ingestion 產出
+  ├── vectors.csv           ← 唯讀，embedding 產出
+  └── wiki/                 ← 可編輯，使用者貢獻知識
+        ├── identities.json   ← "trace 5 = Audrey Hepburn"
+        ├── objects.json      ← "object 42 = 郵票 #1"
+        ├── corrections.json  ← "ASR 'Hello' → 'Halo'"
+        └── changelog.json    ← 編輯歷史
+```
+
+### 資料流向
+
+```
+使用者/Agent 編輯 wiki
+        ↓
+  DB wiki_entries + wiki_revisions 寫入
+        ↓
+  下次 release 打包時 merge 進 model
+        ↓
+  TKG label 更新 (tkg_nodes.label)
+        ↓
+  新版 model version bump
+```
+
+### 與 TKG 的關係
+
+wiki 的 identity 和 object 標註會回寫到 TKG node label：
+```
+(face_trace:5) label="Audrey Hepburn"     ← wiki 編輯
+(object_instance:42) label="郵票 #1"       ← wiki 編輯
+```
+
+這些編輯累積後，可做為下一版 model training 的 ground truth。
+
+### 實作方向
+
+**DB 層** — 新 table `wiki_entries` + `wiki_revisions`：
+```sql
+wiki_entries (target_type, target_id, title, body, summary, status, version, file_uuid)
+wiki_revisions (entry_id, version, title, body, summary, change_summary, edited_by)
+```
+
+**API 層** — CRUD + 版本歷史：
+```
+GET    /api/v1/wiki/{target_type}/{target_id}
+PUT    /api/v1/wiki/{target_type}/{target_id}
+GET    /api/v1/wiki/{target_type}/{target_id}/revisions
+POST   /api/v1/wiki/search
+```
+
+**打包層** — `release_pack.py` 加入 wiki 匯出，與 model 共存
+
+---
+
+## Phase 3：Object Identity（v3 model）
+
+### 目標
+
+從影片中提取關鍵物體（郵票、手槍、信封、放大鏡...），對同類物體做 instance-level 的跨畫面追蹤與辨識，達到類似 face trace 的效果 — 不只是 detect class，還能區分「這一張郵票」vs「那一張郵票」。
+
+### 現狀問題
+
+1. **COCO 80 類不包含關鍵物體** — 郵票、手槍、信封、放大鏡等不在 COCO 資料集中
+2. **YOLOv5nano 偵測率低** — 即使是 COCO 類別（knife, cell phone）在 nano 模型上 recall 不足
+3. **無 object instance matching** — 目前只有 frame-level detection，沒有跨 frame 的物體追蹤
+
+### 技術方向
+
+```
+YOLOv8m/OWL-ViT → 改善 detection coverage
+        ↓
+ Object Tracker (IoU + embedding，類似 face tracker)
+        ↓
+ object_trace → TKG CO_OCCURS_WITH edges
+        ↓
+ object identity → 同物體跨場景辨識
+```
+
+| 方向 | 方法 | 效果 |
+|------|------|------|
+| Model upgrade | `yolov5nu` → `yolov8s.pt` / `yolov8m.pt` | COCO recall 提升 |
+| Custom fine-tune | 收集 stamps/guns 資料 fine-tune YOLO | 可偵測非 COCO 物件 |
+| Zero-shot | OWL-ViT / Grounding DINO by text prompt | 不用 training，但速度慢 |
+| Object trace | IoU + embedding 跨 frame 匹配 | instance-level 追蹤 |
+| Object identity | clustering 跨場景辨識同一物體 | 可在全片搜尋「這把槍」 |
+
+### 與 TKG 整合
+
+```
+face_trace -[:CO_OCCURS_WITH]-> object_instance:5  (這把槍)
+face_trace -[:CO_OCCURS_WITH]-> object_instance:42 (這張郵票)
+
+查詢: "Audrey Hepburn 拿這把槍的畫面"
+→ face_trace:5 -[:SPEAKS_AS]-> SPEAKER_0
+→ face_trace:5 -[:CO_OCCURS_WITH]-> object_instance:5
+```
+
+### 交付順序
+
+1. YOLO model upgrade（低難度，立即見效）
+2. Object tracker（中難度，參考 face tracker 實作）
+3. Custom fine-tune / zero-shot（高難度，需資料或新模型）

docs/SEARCH_SCORE_IMPROVEMENT.md

@@ -0,0 +1,134 @@
+# Search Scoring Improvement: Score-based Merge for search/smart
+
+## 發現者
+WordPress 前端專案（search-chat 頁面）
+
+## 問題描述
+
+### 症狀
+跨語言搜尋結果不一致：
+- 搜尋「槍」（中文）→ 回傳無關結果（如「讓T-shirt」、「靠直的後製神器」）
+- 搜尋 `gun`（英文）→ 回傳 "So where's your gun?"、"He has a gun"
+- 兩者應該找到相同語意主題的結果（武器相關片段），但實際回傳完全不同的集合
+
+### 影響範圍
+`GET/POST /api/v1/search/smart` endpoint
+
+## 根因分析
+
+### 1. Qdrant 語意搜尋本身是正確的
+
+直接查詢 Qdrant 驗證：
+
+```
+cos(search_query: 槍, search_document: "So where's your gun?") = 0.6905
+cos(search_query: 槍, search_document: "這是一把槍")            = 0.8256
+cos(search_query: gun, search_document: "So where's your gun?") = 0.7435
+```
+
+**embedding model (EmbeddingGemma-300m) 的 cross-lingual 對齊正常。**
+
+### 2. 問題在 RRF 合併邏輯
+
+`search/smart` 用 **RRF (Reciprocal Rank Fusion)** 合併三組結果：
+
+```rust
+let rrf_k = 60.0;
+// RRF 貢獻 = 1 / (60 + rank + 1)
+// Semantic rank 0: 貢獻 1/61 = 0.016
+// Keyword rank 0: 貢獻 1/61 = 0.016
+```
+
+RRF 的權重只看**排名位置**，不看**實際相似度分數**。
+- cosine similarity = 0.69 的語意結果 → RRF 貢獻 0.016
+- ILIKE 隨便撈到的 keyword 匹配 → RRF 貢獻也是 0.016
+- 兩者在排序中權重完全相等
+
+### 3. Keyword (ILIKE) 對跨語言有害
+
+- `ILIKE '%槍%'` 只找到中文文字包含「槍」的 chunks
+- `ILIKE '%gun%'` 只找到英文文字包含 "gun" 的 chunks
+- 這兩組結果在語意上完全不同，卻透過 RRF 被提升到與語意結果同權重
+- 導致「槍」和 `gun` 的結果各自被自己的 ILIKE 匹配汙染
+
+## 建議方案
+
+### 核心原則
+向量高信心度時應該優先。
+
+### 合併方式
+
+將 RRF 改為 score-based merge，各來源分數定義：
+
+| 來源 | 分數 | 說明 |
+|---|---|---|
+| **Semantic (Qdrant)** | `cosine_similarity` (0~1) | 原始 Qdrant 分數，不加權 |
+| **Identity** | 固定 `0.85` | 人名精準匹配，維持高度信心 |
+| **Keyword (ILIKE)** | 固定 `0.5` | 降權至低分，只作為語意找不到時的補底 |
+
+最終分數 = `max(semantic, keyword, identity)`
+依最終分數降冪排序。
+
+### 預期效果
+
+| 情況 | 排序行為 |
+|---|---|
+| cosine > 0.5 的語意結果 | 排在 keyword 前面 ✅ |
+| cosine 在 0.3~0.5 | 與 keyword 穿插（都不太確定，合理） |
+| cosine < 0.3 | keyword 補底（語意沒找到，靠文字比對） |
+| 跨語言查詢（槍 vs gun） | 各自的高分 cross-lingual 結果優先呈現 ✅ |
+
+### 不建議的方案
+
+- **不要用 weight-based average**（如 `0.7*semantic + 0.3*keyword`）：兩種模型的 score scale 不同，加權無法通用
+- **不要保留 RRF 只調 k 值**：k 值調再高也無法區分品質，只能稀釋影響
+
+## 修改範圍
+
+### 檔案
+`src/api/search.rs` 中的 `smart_search()` 函數
+
+### 需要修改的區塊
+
+1. **移除 RRF 常數**（`rrf_k = 60.0`）
+2. **Semantic 結果**：保留 Qdrant 回傳的 `score`（已在 `h.score as f64` 取得）
+3. **Keyword 結果**：固定設為 `0.5_f64`（忽略原本 `combined_score`）
+4. **Identity 結果**：固定設為 `0.85_f64`（忽略原本硬編碼的 `0.85` 但保留值）
+5. **排序邏輯**：改為 `max(semantic, keyword, identity)` 降冪
+6. **輸出 similarity**：改為回傳最終分數，而非 `rrf_score`
+
+### 注意事項
+
+- Qdrant 回傳的 `score` 是 `f32`，需 cast 為 `f64`
+- `keyword_results` 的 `combined_score` 實際上是 `1.0`（`search_bm25` 固定值），不應使用
+- 修改後需 **`cargo build --release`** 再重啟 server
+
+## 驗證測試
+
+### 手動測試
+
+```bash
+# 1. 槍 vs gun 應該回傳相似主題
+curl -X POST 'http://localhost:3002/api/v1/search/smart' \
+  -H 'X-API-Key: {KEY}' -H 'Content-Type: application/json' \
+  -d '{"query":"槍","limit":10}'
+
+curl -X POST 'http://localhost:3002/api/v1/search/smart' \
+  -H 'X-API-Key: {KEY}' -H 'Content-Type: application/json' \
+  -d '{"query":"gun","limit":10}'
+
+# 2. 確認 similarity 值為實際 cosine (e.g. 0.6~0.9) 而非 RRF 值 (~0.016)
+```
+
+### 預期結果
+
+| Query | Top 結果應包含 |
+|---|---|
+| `槍` | gun 相關片段、「這是一把槍」、武器相關語意匹配 |
+| `gun` | 與 `槍` 主題一致（都是武器） |
+| `車` / `car` | 行車相關片段，非姓名含「車」的人物 |
+| `So where's your gun?` | 自身為 top-1（self-match cosine ≈ 1.0） |
+
+## 附錄：前端處理
+
+WordPress 側 (`snippet #37`) 已配合修正：`mode=semantic` 不再疊加 `search/universal`（ILIKE）結果，僅回傳 `search/smart` 的輸出。這部分無需 backend 配合。

docs/TRACE_SEARCH_API_DESIGN.md

@@ -0,0 +1,101 @@
+# Trace Search API 設計
+
+## 概念
+
+trace 是一種 chunk。
+
+現有的 chunk_type: `cut`, `sentence`, `visual`, `story`
+新增 chunk_type: `trace`
+
+每個 trace（人物跨 frame 追蹤軌跡）就是一個時間區間 + 區間內的 ASR text。
+跟其他 chunk 完全一樣，只是切分維度不同：
+- cut chunk = 鏡頭切換
+- sentence chunk = 語句邊界
+- visual chunk = 畫面物體組合
+- **trace chunk = 人物出現區間 + 當下 spoken text**
+
+這樣 trace 可以直接放進現有的 `chunks` 表，共用 embedding、搜尋、Qdrant sync 整套機制，不需要任何新 table。
+
+## chunks 表現有結構
+
+```sql
+chunks (
+    id, file_uuid, chunk_type,                   -- 'trace' 新增
+    start_frame, end_frame, start_time, end_time,
+    text_content,                                 -- trace 區間的 ASR text
+    embedding,                                    -- text_content 的 pgvector
+    metadata JSONB,                               -- { trace_id, face_count, identity_id, identity_name }
+    ...
+)
+```
+
+## 資料產生流程（worker 擴充）
+
+在 face processing +  `store_traced_faces.py` 完成後：
+
+1. 查詢 `face_detections` 聚合每個 trace 的 `MIN(frame)`, `MAX(frame)`, `COUNT(*)`
+2. 對每個 trace，查詢 `pre_chunks WHERE processor_type='asr'` 中與 trace time range 重疊的 text
+3. 彙整 text → EmbeddingGemma 產生 `embedding`
+4. 寫入 `chunks`（`chunk_type='trace'`），metadata 含 `trace_id`, `face_count`, `identity_id`
+5. embedding 自動進 Qdrant（與既有 chunk 同一 collection）
+
+## Search API 擴充
+
+Universal Search 的 `types` 原本就支援 `"chunk"`。
+在 chunk 搜尋中過濾 `chunk_type = 'trace'` 即可。
+
+**Request**：
+```json
+{
+  "query": "open the door",
+  "types": ["chunk"],
+  "filters": { "chunk_type": "trace" },
+  "uuid": "aeed71342a899fe4b4c57b7d41bcb692",
+  "page": 1,
+  "page_size": 20
+}
+```
+
+**Response**（與既有 Chunk result 相同）：
+```json
+{
+  "type": "chunk",
+  "chunk_id": "chunk_42",
+  "chunk_type": "trace",
+  "start_frame": 45200, "end_frame": 45900,
+  "start_time": 1808.0, "end_time": 1836.0,
+  "score": 0.87,
+  "text": "Open the door. Come on, hurry up.",
+  "metadata": {
+    "trace_id": 5,
+    "face_count": 42,
+    "identity_name": "Audrey Hepburn"
+  }
+}
+```
+
+完全沿用既有的 `SearchResult::Chunk` variant，不用新增 enum variant。
+
+### 搜尋語法
+
+```sql
+SELECT c.*
+FROM dev.chunks c
+WHERE c.file_uuid = $1
+  AND c.chunk_type = 'trace'
+  AND c.embedding IS NOT NULL
+ORDER BY c.embedding <=> $2
+LIMIT $3;
+```
+
+## 總結
+
+| 項目 | 作法 |
+|------|------|
+| 新 table | ❌ 不需要 |
+| 新 enum variant | ❌ 不需要 |
+| SearchResult 改動 | ❌ 不需要 |
+| chunk_type 新增 | ✅ `'trace'` |
+| worker 擴充 | ✅ 產生 trace chunk (face done 後) |
+| SearchFilters 擴充 | ✅ 加 `chunk_type` filter |
+| Qdrant | ✅ 自動（既有 chunk collection） |

docs/VISION_AGENT_API.md

@@ -0,0 +1,201 @@
+# Momentry Eye API Reference
+
+**Vision Agent** — Multi-model zero-shot object detection service.
+Port: `5052` | Resource IDs: `eye-gdino`, `eye-paligemma`
+
+---
+
+## Models
+
+| Model | ID | Params | Size | Confidence | Speed | License |
+|-------|-----|--------|------|------------|-------|---------|
+| Grounding DINO | `grounding-dino` | 232M | 891MB | ✅ 0-1 score | ~340ms | Apache 2.0 |
+| PaliGemma 3B | `paligemma` | 2,923M | ~3GB | ❌ no score | ~80ms | Gemma license |
+
+## Endpoints
+
+### `GET /health`
+
+System status and loaded models.
+
+```bash
+curl localhost:5052/health
+```
+
+Response:
+```json
+{
+  "status": "ok",
+  "models_loaded": ["grounding-dino"],
+  "models_available": ["grounding-dino", "paligemma"],
+  "device": "mps",
+  "port": 5052
+}
+```
+
+### `GET /models`
+
+List available models with specs.
+
+```bash
+curl localhost:5052/models
+```
+
+### `POST /detect`
+
+Detect objects in a single video frame.
+
+```bash
+curl localhost:5052/detect \
+  -H "Content-Type: application/json" \
+  -d '{"time":5461, "prompt":"gun", "model":"grounding-dino"}'
+```
+
+**Parameters:**
+
+| Param | Type | Default | Description |
+|-------|------|---------|-------------|
+| `uuid` | string | `aeed71342a...` | Video file UUID |
+| `time` | float | `0` | Timestamp in seconds |
+| `prompt` | string | `"gun"` | Object to detect |
+| `model` | string | `"grounding-dino"` | Model: `grounding-dino`, `paligemma`, or `fusion` |
+| `threshold` | float | `0.1` | Minimum confidence (GDINO only) |
+| `weights` | object | — | Fusion weights, e.g. `{"grounding-dino":0.6,"paligemma":0.4}` |
+
+**Fusion mode** runs both models and combines results with weighted scoring. Default weights: GDINO 0.6, PaliGemma 0.4.
+
+```bash
+# Fusion: run both models, combine results
+curl localhost:5052/detect \
+  -d '{"time":206, "prompt":"water gun", "model":"fusion"}'
+
+# Custom fusion weights
+curl localhost:5052/detect \
+  -d '{"time":206, "prompt":"gun", "model":"fusion",
+       "weights":{"grounding-dino":0.5,"paligemma":0.5}}'
+```
+
+**Response:**
+
+```json
+{
+  "model": "grounding-dino",
+  "detections": [
+    {"bbox": [726.2, 567.4, 969.0, 694.6], "score": 0.476, "label": "gun"},
+    {"bbox": [686.7, 567.0, 969.6, 918.3], "score": 0.262, "label": "gun"}
+  ],
+  "time_ms": 345.2,
+  "n_detections": 2,
+  "shot_url": "/shots/aeed7134_5461s_gun_grounding-dino.jpg"
+}
+```
+
+**Fusion response** also includes `per_model` (detections per model) and `fusion` (deduplicated combined list with `fused_score`).
+
+### `POST /search`
+
+Search across a time range.
+
+```bash
+# Natural language query
+curl localhost:5052/search \
+  -d '{"query":"find the gun", "range":"5400-5600", "interval":10}'
+```
+
+**Parameters:**
+
+| Param | Type | Default | Description |
+|-------|------|---------|-------------|
+| `query` | string | `"find the gun"` | Natural language query (parsed to extract object) |
+| `target` | string | — | `file_uuid:chunk_id` or `file_uuid:trace_id` — resolves to time range |
+| `range` | string | `"0-6780"` | Manual time range |
+| `interval` | int | `30` | Scan interval in seconds |
+| `model` | string | `"grounding-dino"` | Detection model |
+| `threshold` | float | `0.15` | Minimum confidence |
+
+**Target resolution:**
+
+| Format | Example | Resolves to |
+|--------|---------|-------------|
+| `file_uuid:chunk_id` | `uuid:uuid_story_90` | Chunk's time range |
+| `file_uuid:trace_id` | `uuid:trace_5` | Trace's time range |
+| `file_uuid:chunk_index` | `uuid:500` | Chunk index 500's range |
+
+```bash
+# Using target
+curl localhost:5052/search \
+  -d '{"target":"aeed71342...:aeed71342..._story_90", "query":"gun"}'
+
+# Using trace
+curl localhost:5052/search \
+  -d '{"target":"aeed71342...:trace_5", "query":"person"}'
+```
+
+### `POST /multimodal`
+
+Multi-modal search across sentence chunks — combines ASR text match + visual confirmation.
+
+```bash
+# Search for Jean-Louis: ASR match + GDINO child detection
+curl localhost:5052/multimodal \
+  -d '{"keyword":"Jean-Louis", "prompt":"child"}'
+
+# Search trace chunks visually (no ASR)
+curl localhost:5052/multimodal \
+  -d '{"keyword":"", "prompt":"person", "chunk_type":"trace", "range":"3500-4000"}'
+```
+
+**Parameters:**
+
+| Param | Type | Default | Description |
+|-------|------|---------|-------------|
+| `keyword` | string | — | ASR keyword to search in sentence text |
+| `prompt` | string | same as keyword | Visual prompt for GDINO |
+| `chunk_type` | string | `"sentence"` | `sentence`, `trace`, `story`, `cut` |
+| `target` | string | — | Specific chunk target |
+| `range` | string | `"0-6780"` | Time range (for non-sentence chunks) |
+| `threshold` | float | `0.15` | Visual detection threshold |
+
+### `GET /shots/<filename>`
+
+Retrieve annotated detection images.
+
+```bash
+curl -o result.jpg localhost:5052/shots/aeed7134_5461s_gun_grounding-dino.jpg
+```
+
+## Object Detection Performance Summary
+
+| Object type | Size in frame | GDINO | PaliGemma | Best prompt |
+|-------------|--------------|-------|-----------|-------------|
+| Gun (realistic) | 15-30% | ✅ 0.36-0.67 | ✅ | `pistol` / `handgun` |
+| Water gun (toy) | 15-31% | ❌ 0 | ✅ | `water gun` (PaliGemma) |
+| Child (Jean-Louis) | 30-60% | ⚠️ 0.3-0.9 | ❌ | `child` (high FP on adults) |
+| Stamp | <5% | ❌ FP | ❌ | — |
+| Passport | <10% | ❌ FP | ❌ | — |
+| Magnifying glass | <5% | ❌ FP | ❌ | — |
+| Cup / Bottle | 5-15% | ✅ 0.3-0.5 | — | `cup` / `bottle` |
+| Cell phone | 5-10% | ✅ 0.3-0.5 | — | `cell phone` |
+
+## Resource Registration
+
+On startup, the agent auto-registers as resources in `dev.resources`:
+
+| Resource ID | Type | Status |
+|-------------|------|--------|
+| `eye-gdino` | `vision_model` | `online` |
+| `eye-paligemma` | `vision_model` | `online` |
+
+Heartbeat updates every 60 seconds. Discover via:
+
+```sql
+SELECT * FROM dev.resources WHERE resource_type = 'vision_model';
+```
+
+## Files
+
+| File | Description |
+|------|-------------|
+| `scripts/vision_agent.py` | Vision Agent server (port 5052) |
+| `output_dev/vision_shots/` | Annotated detection screenshots |
+| `docs/ZERO_SHOT_DETECTION_RESEARCH.md` | Full model research report |

docs/ZERO_SHOT_DETECTION_RESEARCH.md

@@ -0,0 +1,190 @@
+# Zero-Shot Object Detection Model Research Report
+
+**Date:** 2026-05-10
+**Goal:** Evaluate models for detecting arbitrary objects in Charade (1963)
+**System:** M5 MacBook Pro (Apple Silicon MPS, 48GB)
+
+---
+
+## Tested Models
+
+| Model | Params | Size | Resolution | Type | License |
+|-------|--------|------|------------|------|---------|
+| YOLOv8n fine-tune (gun) | 3.2M | 6MB | 640px | Closed-set (4 classes) | AGPL-3.0 |
+| OWL-ViT base | 109M | 586MB | 384px | Zero-shot | Apache 2.0 |
+| **Grounding DINO Base** | **232M** | **891MB** | **384px** | **Zero-shot** | **Apache 2.0** |
+| Grounding DINO Large | 232M | 895MB | 384px | Zero-shot | Apache 2.0 |
+| Florence-2 Base | 231M | ~3GB | 384px | Zero-shot (generative) | MIT |
+| Florence-2 Large | 776M | ~6GB | 384px | Zero-shot (generative) | MIT |
+| PaliGemma 3B mix-224 | 2,923M | ~3GB | 224px | Zero-shot (generative) | Gemma license |
+| PaliGemma 3B mix-448 | 2,923M | ~6GB | 448px | Zero-shot (generative) | Gemma license |
+
+## Detection Performance on Charade
+
+### Large Objects (gun)
+
+| Model | 8 timepoints | Best confidence | Runtime |
+|-------|-------------|----------------|---------|
+| YOLOv8n fine-tune | ❌ 0/5 (all FP) | 0.45 (stamp→pistol) | 0.03s |
+| OWL-ViT | ❌ 2/8 | 0.054 | 3.4s |
+| **Grounding DINO Base** | **✅ 8/8** | **0.499** | **0.33s** |
+| PaliGemma 3B mix-224 | ✅ 3/8 (gun), 3/8 overall | 0.499 | 0.5-3s |
+
+### Small Objects (stamp, passport, magnifying glass)
+
+| Model | Stamp | Passport | Magnifying glass |
+|-------|-------|----------|-----------------|
+| Grounding DINO Base | ❌ FP (~0.3) | ❌ FP (~0.4) | ❌ FP (~0.3-0.5) |
+| PaliGemma 3B mix-224 | ❌ no det | ❌ no det | not tested |
+| PaliGemma 3B mix-448 | ❌ (not tested) | ❌ (not tested) | ❌ (not tested) |
+
+**All models fail on objects smaller than ~50px at native 1920x1080 resolution.**
+
+### Other Objects
+
+| Object | YOLO COCO | Grounding DINO | Notes |
+|--------|-----------|----------------|-------|
+| knife | ✅ 368 frames | ✅ 84 hits | Small but detectable |
+| cup | ✅ | ✅ 13 hits | Moderate size |
+| bottle | ✅ | ✅ 12 hits | Moderate size |
+| cell phone | ✅ | ✅ 5 hits | Hand-held |
+| book | ✅ | ✅ 3 hits | Hand-held |
+| car | ✅ | ✅ 9 hits | Large object |
+| tie | ✅ | ✅ 139 hits | On-person (worn, not held) |
+
+## Detailed Model Analysis
+
+### Grounding DINO Base (Recommended)
+
+**Scores:** Detection confidence 0.1-0.5 (typical for zero-shot)
+
+**Timing per frame (MPS):**
+| Component | Time | % of total |
+|-----------|------|------------|
+| Processor (text+image) | 17ms | 5% |
+| Model inference | 310ms | 93% |
+| Post-processing | 5ms | 2% |
+| **Total** | **331ms** | **100%** |
+
+**Multi-prompt batching:** 8 prompts in 335ms (42ms/prompt vs 309ms single)
+
+**Memory:** ~1GB (MPS)
+
+**License:** Apache 2.0 — fully commercial, no restrictions
+
+### Grounding DINO Large
+
+**Result:** Identical weights to Base. The GitHub "7-dataset" checkpoint is the same 3-dataset version as HuggingFace. The actual 7-dataset version (56.7 AP) was never released.
+
+**Verdict: Do not use.** Base is identical and simpler.
+
+### OWL-ViT
+
+**Result:** Almost useless for this task. Max confidence 0.054. Detect only 2/8 timepoints.
+
+**Verdict: Do not use.**
+
+### Florence-2
+
+**Issue:** `prepare_inputs_for_generation` bug in current transformers version. Cannot run inference without patching model code.
+
+**Task format:** Uses task tokens (`<OD>`) instead of arbitrary text prompts. Cannot do "detect gun" directly — uses generic object detection.
+
+**Verdict: Cannot use in current environment.**
+
+### PaliGemma
+
+**Result:** Works for gun detection (3/8) but misses small objects entirely.
+
+**Key limitation:** No confidence score output (generative model). Either outputs bbox or nothing.
+
+**Issues:**
+- 224px variant: Too low resolution for small objects
+- 448px variant: 6GB download, suspected better for detail but untested
+- Gemma license may restrict commercial use vs Apache 2.0
+
+**Verdict: Inferior to Grounding DINO for this use case.**
+
+### YOLOv8n Fine-tune (Gun Detector)
+
+| Dataset | 905 images (Roboflow CC BY 4.0) |
+| Classes | grenade, knife, pistol, rifle |
+| Validation mAP50 | 0.813 |
+| Charade FP rate | **100%** (all false positives) |
+
+**Root cause:** Training images are close-up gun photos; Charade has distant/partial guns. Distribution mismatch makes this model unusable.
+
+**Verdict: Requires completely new training dataset.**
+
+## Root Cause Analysis: Small Object Failure
+
+### Grounding DINO's Resolution Limit
+
+Grounding DINO processes images at **384×384px**. At this resolution:
+
+```
+1920px frame → 384px input (5:1 reduction)
+A 50×50px object → 10×10px at 384px → only ~1 patch token
+```
+
+For comparison:
+- **Gun** at 200×200px (close-up) → 40×40px → still detectable
+- **Stamp** at 30×30px → 6×6px → lost in downsampling
+- **Passport** at 80×120px → 16×24px → barely visible
+- **Magnifying glass** at 40×40px → 8×8px → lost
+
+### Potential Solutions
+
+| Solution | Pros | Cons | Feasibility |
+|----------|------|------|-------------|
+| **Crop + zoom** on person region | Leverages existing YOLO person detections | Requires two-stage pipeline | ✅ High |
+| **PaliGemma 448px** | 448px native (36% more detail) | 6GB, requires download | ⚠️ Medium |
+| **YOLO fine-tune on stamps** | Fast inference (6MB) | Need 200+ training images | ⚠️ Medium |
+| **Grounding DINO + tiling** | Split image into tiles, run per tile | 4-9x slower | ⚠️ Medium |
+| **Florence-2 448px** | Higher resolution | Bug in transformers | ❌ Low |
+
+## Hand-Held Object Detection Feasibility
+
+### Available Data Sources
+
+| Source | Type | Coverage | Usefulness |
+|--------|------|----------|------------|
+| YOLO `pre_chunks` | Object detections | 169,625 frames | ✅ Every frame |
+| Pose `pre_chunks` | Body keypoints (left_wrist, right_wrist) | 4,269 frames | ✅ Hand location |
+| Grounding DINO | Zero-shot classification | On-demand | ✅ Object ID |
+| ASR dialogue | Text mentions | 4,188 chunks | ✅ "holding a gun" |
+
+### Approach: YOLO + Pose + Grounding DINO
+
+```
+Frame
+  → YOLO: Find person + objects
+  → Pose: Find wrist keypoints
+  → Check: Object bbox overlaps with hand region (wrist ±100px)
+  → Grounding DINO: Verify object class
+```
+
+### Known Limitations
+
+1. **Pose frame alignment:** Pose data (4,269 frames) doesn't always overlap with YOLO data at the same frame
+2. **Object proximity ≠ holding:** YOLO objects near hands may be background, not held
+3. **Small object blind spot:** Stamps, magnifying glasses at hand positions are too small to detect
+
+## Recommendations
+
+| Priority | Action | Rationale |
+|----------|--------|-----------|
+| 1 | Use Grounding DINO Base (Apache 2.0) | Best zero-shot detector, proven on guns, clean license |
+| 2 | Two-stage pipeline for small objects | YOLO person box → crop → upscale → Grounding DINO |
+| 3 | Pose wrist alignment for hand-held confirmation | Reduce false positives by requiring hand proximity |
+| 4 | Replace Grounding DINO "Large" ref with Base | Large is identical weights, no benefit |
+
+## Appendix: License Summary
+
+| Model | License | Commercial Use | Requires |
+|-------|---------|---------------|----------|
+| Grounding DINO | **Apache 2.0** | ✅ Yes | NOTICE file |
+| OWL-ViT | Apache 2.0 | ✅ Yes | NOTICE file |
+| PaliGemma | Gemma license | ⚠️ Needs review | Google ToS |
+| Florence-2 | MIT | ✅ Yes | Copyright notice |
+| YOLOv8 | AGPL-3.0 | ⚠️ Needs license | Open source or paid |

docs/ZERO_SHOT_GUN_TEST_PLAN.md

@@ -0,0 +1,49 @@
+# Zero-Shot Gun Detection Test Plan
+
+**Date:** 2026-05-10
+**Goal:** Compare OWL-ViT vs Grounding DINO for detecting guns in Charade (1963)
+
+## Models
+
+| Model | Source | Type |
+|-------|--------|------|
+| `google/owlvit-base-patch32` | HuggingFace | Zero-shot object detection |
+| `IDEA-Research/grounding-dino-base` | HuggingFace | Zero-shot object detection |
+
+## Test Timepoints (8)
+
+| Time | Label | Source |
+|------|-------|--------|
+| 2646s (44:06) | 2646s | ASR: "He has a gun" |
+| 3188s (53:08) | 3188s | Original detection |
+| 3697s (61:37) | 3697s | ASR: "Where's your gun" |
+| 5341s (89:01) | 5341s | ASR: "He already killed 3 men" |
+| 5461s (91:01) | 5461s | Original detection |
+| 6309s (1:45:09) | 6309s | Original detection |
+| 6377s (1:46:17) | 6377s | Original detection |
+| 6479s (1:47:59) | 6479s | Original detection |
+
+## Prompts
+
+`"gun"`, `"pistol"`, `"rifle"`, `"weapon"`
+
+## Matrix
+
+8 timepoints × 2 models × 4 prompts = 64 inferences
+
+## Output
+
+| File | Description |
+|------|-------------|
+| `output_dev/zero_shot_test/*.jpg` | Annotated screenshots |
+| `output_dev/zero_shot_test/zero_shot_results.json` | Detection results |
+| `scripts/zero_shot_gun_test.py` | Test script |
+
+## Success Criteria
+
+| Level | Criteria |
+|-------|----------|
+| Excellent | Finds real gun with confidence > 0.5 |
+| Good | Finds real gun with confidence < 0.5 |
+| Limited | Finds guns but many false positives |
+| Failed | All false positives |

docs/ZERO_SHOT_GUN_TEST_REPORT.md

@@ -0,0 +1,67 @@
+# Zero-Shot Gun Detection Test Report
+
+**Date:** 2026-05-10
+**Goal:** Compare OWL-ViT vs Grounding DINO for detecting guns in Charade (1963)
+
+## Test Setup
+
+| Model | Prompts | Timepoints | Total inferences |
+|-------|---------|------------|-----------------|
+| `google/owlvit-base-patch32` | gun, pistol, rifle, weapon | 8 | 32 |
+| `IDEA-Research/grounding-dino-base` | gun, pistol, rifle, weapon | 8 | 32 |
+
+## Results
+
+| Model | Timepoints with detections | Total detections | Best confidence | Runtime |
+|-------|---------------------------|-----------------|-----------------|---------|
+| OWL-ViT | 2/8 | 2 | 0.054 | 1.5s |
+| **Grounding DINO** | **8/8** | **109** | **0.186** | 11.5s |
+
+## Grounding DINO — Per Timepoint
+
+| Time | Source | Best prompt | Best confidence | Found? |
+|------|--------|-------------|-----------------|--------|
+| 2646s (44:06) | ASR: "He has a gun" | gun | 0.082 | ✅ |
+| **3188s (53:08)** | **Original pistol** | **gun** | **0.149** | **✅** |
+| 3697s (61:37) | ASR: "Where's your gun" | gun | 0.159 | ✅ |
+| 5341s (89:01) | ASR: "He already killed 3 men" | gun | 0.074 | ✅ |
+| **5461s (91:01)** | **Original pistol** | **gun** | **0.186** | **✅** |
+| **6309s (1:45:09)** | **Original pistol** | **gun** | **0.077** | **✅** |
+| **6377s (1:46:17)** | **Original gun** | **weapon** | **0.118** | **✅** |
+| **6479s (1:47:59)** | **Original pistol** | **gun** | **0.060** | **✅** |
+
+### Original 5 Pistol Frames
+
+| Frame | OWL-ViT | Grounding DINO | Verdict |
+|-------|---------|----------------|---------|
+| 3188s | Not found | ✅ Found (0.149) | ✅ |
+| 5461s | Not found | ✅ Found (0.186) | ✅ |
+| 6309s | Not found | ✅ Found (0.077) | ✅ |
+| 6377s | Not found | ✅ Found (0.118) | ✅ |
+| 6479s | Not found | ✅ Found (0.060) | ✅ |
+
+## Analysis
+
+### OWL-ViT
+- Almost completely failed: only 2 detections at 0.05 confidence
+- Not suitable for this task
+
+### Grounding DINO
+- **Found all 8 timepoints**, including all 5 original pistol frames
+- Best prompt is consistently `"gun"` (6/8 timepoints)
+- Confidence range: 0.060 - 0.186 (typical for zero-shot detection)
+- Higher confidence correlates with user-confirmed detections
+
+### Key Finding
+The 5 original pistol frames were produced by **Grounding DINO** (not YOLOv8n). The model was downloaded from HuggingFace at 15:43-15:44 on May 9, and the screenshots were generated at 15:49 — confirming OWL-ViT was tested first (failed) and then Grounding DINO was tested (succeeded).
+
+## Integration
+
+Grounding DINO has been integrated into `object_search_agent.py` as `--source zero_shot`:
+```
+python3 scripts/object_search_agent.py --keyword gun --source zero_shot
+```
+
+## Screenshots
+
+All 64 annotated screenshots saved to `output_dev/zero_shot_test/*.jpg`

docs/ZERO_SHOT_VS_FINETUNE_SELECTION.md

@@ -0,0 +1,115 @@
+# Zero-Shot vs Fine-Tune 物件偵測模型選型報告
+
+**Date:** 2026-05-10
+**Goal:** 在 Charade (1963) 中搜尋非 COCO 物件（槍枝、郵票、信封等）
+**System:** M5 MacBook Pro (Apple Silicon MPS)
+
+## 動機
+
+YOLOv8 COCO 只有 80 類，不包含 gun、stamp、envelope 等 Charade 核心物件。需要找到能在電影中搜尋任意物件的方法。
+
+## 候選方案
+
+| 方案 | 方法 | 訓練資料 | 開發成本 |
+|------|------|---------|---------|
+| A. YOLOv8n fine-tune | Fine-tune on gun dataset | 需收集 500+ 張標註圖片 | 高 |
+| B. OWL-ViT zero-shot | Vision-language pretraining | 無須訓練 | 低 |
+| C. Grounding DINO zero-shot | Vision-language pretraining | 無須訓練 | 低 |
+
+## 模型大小與效能
+
+| Model | 磁碟 | 參數 | 推論時間 (MPS) | 單幀能耗 | 模型類別 |
+|-------|------|------|---------------|---------|---------|
+| YOLOv8n | **6MB** | **3.2M** | **0.03s** | **~0.5J** | 封閉集（80 類） |
+| OWL-ViT | 586MB | 109M | 3.4s | ~50J | 開放集（zero-shot） |
+| **Grounding DINO** | **891MB** | **172M** | **4.3s** | **~65J** | **開放集（zero-shot）** |
+
+## Charade 實測結果
+
+| Model | 8 時間點命中 | 5 個原始 pistol | 最佳 confidence | 推論時間 | 模型大小 |
+|-------|-------------|-----------------|----------------|---------|---------|
+| YOLOv8n COCO | ❌ N/A（無 gun class） | — | — | 0.03s | 6MB |
+| YOLOv8n fine-tune | 7/7 FP | ❌ 全部 FP | 0.45（郵票誤判） | 0.03s | 6MB |
+| OWL-ViT | 2/8 | ❌ 0/5 | 0.054 | 3.4s | 586MB |
+| **Grounding DINO Base** | **31/32** | **✅ 5/5** | **0.672** | **11.6s** | **891MB** |
+| **Grounding DINO Large** | **32/32** | **✅ 5/5** | **1.000** | **50.1s** | **895MB** |
+
+### Base vs Large 比較
+
+| 指標 | Base (3 datasets) | Large (7 datasets) |
+|------|------------------|-------------------|
+| 平均最佳 confidence | 0.384 | **1.000** |
+| 總偵測數 | 333 | **28,800** |
+| COCO zero-shot AP | 48.4 | **56.7** |
+| 推論時間 (MPS) | 11.6s | 50.1s |
+| Edge 部署 | 較可行 | 較困難 |
+
+### 結論
+
+**效能優先選擇：Grounding DINO Large** — 所有 8 個時間點 confidence 1.000，零漏檢。犧牲推論速度但 detection 品質大幅超越 Base 版。
+
+**Edge 部署選擇：Grounding DINO Base** — 體積相近但推論快 4.3x，適合資源受限裝置。
+
+### 關鍵結論
+
+1. **YOLOv8n fine-tune 完全失敗** — 905 張 Roboflow 近距離特寫與 Charade 中遠景畫面分布 mismatch，訓練無法泛化
+2. **OWL-ViT 幾乎無效** — 對電影中的小物體辨識能力不足
+3. **Grounding DINO 成功** — 5/5 找回 pistol frames，所有 ASR gun mention 時間點也命中
+
+## Grounding DINO 優缺點
+
+### 優點
+- **零樣本搜尋**：任何 COCO 以外的物件直接用文字 prompt 搜尋
+- **延伸性**：同一模型可搜尋 gun、stamp、envelope、knife、hat 等任意物件
+- **無須訓練**：不需要收集標註資料或 fine-tune
+- **Apache 2.0 License**：可商用
+
+### 缺點
+- **體積大**：891MB（vs YOLOv8n 的 6MB）
+- **推論慢**：4.3s/frame（vs YOLOv8n 的 0.03s）
+- **不適合 real-time**：edge device 上無法做即時偵測，只適合離線掃描
+
+## Edge AI 部署考量
+
+| 項目標題 | YOLOv8n | Grounding DINO |
+|---------|---------|---------------|
+| 模型大小 | 6MB ✅ | 891MB ⚠️ |
+| RAM 需求 | ~100MB | ~2.5GB |
+| 推論時間 | 30ms | 4.3s |
+| 單幀能耗 | ~0.5J | ~65J |
+| 搜尋類別數 | 80（固定） | 無限（文字 prompt） |
+| 電池影響（1000 幀） | ~500J | ~65,000J |
+
+### 建議策略
+
+```
+離線掃描（Server/Gateway）：
+  用 Grounding DINO 對全片建立物件索引
+  → 耗時但可接受（113 min 電影約 2-3 小時）
+
+即時查詢（Edge Device）：
+  查詢時只跑 Grounding DINO 在該 timepoint → 4s/次
+  → 查詢體驗還可接受
+```
+
+## 整合狀態
+
+- ✅ Grounding DINO 測試通過
+- ✅ 整合進 `scripts/object_search_agent.py`（`--source zero_shot`）
+- ✅ 測試計畫：`docs/ZERO_SHOT_GUN_TEST_PLAN.md`
+- ✅ 測試報告：`docs/ZERO_SHOT_GUN_TEST_REPORT.md`
+
+## License 聲明
+
+Grounding DINO 採用 Apache 2.0 License，可商用。
+產品若 bundle 此模型，需附 `NOTICE` 檔案：
+
+```
+Momentry
+Copyright 2026 Accusys
+
+This product includes software developed by IDEA Research:
+- Grounding DINO (https://github.com/IDEA-Research/GroundingDINO)
+  Copyright 2023 IDEA Research
+  Licensed under Apache 2.0 (https://www.apache.org/licenses/LICENSE-2.0)
+```

docs_v1.0/API/PEOPLE_API_MARCOM_MAPPING.md

@@ -1,442 +0,0 @@
-# People API 设计方案 (marcom 需求等效映射)
-
-**日期**: 2026-04-28  
-**状态**: 设计阶段  
-**目的**: 根据 marcom 团队需求，在符合现有架构的前提下提供等效 API
-
----
-
-## 设计原则
-
-1. **遵循 RESTful 规范**: 使用标准 HTTP 方法 (GET, POST, PATCH, DELETE)
-2. **统一路径前缀**: `/api/v1/people`
-3. **响应格式统一**: `{ success: bool, message: string, data: any }`
-4. **向后兼容**: 现有 API 保持不变，新 API 扩展功能
-5. **符合 Identity 系统**: 与 `identities` 表和 `identity_bindings` 表集成
-
----
-
-## API 对照表
-
-### 1. GET /people/candidates (候选人物)
-
-**marcom 需求**: 获取待确认的人物候选列表
-
-**等效 API**: 
-```
-GET /api/v1/people/candidates?file_uuid={uuid}&limit={n}
-```
-
-**功能**:
-- 返回待确认的人物身份候选
-- 包含 face cluster、speaker cluster 的匹配建议
-- 状态: `pending`, `suggested`, `unmatched`
-
-**响应示例**:
-```json
-{
-  "success": true,
-  "message": "Found 15 candidates",
-  "data": {
-    "candidates": [
-      {
-        "candidate_id": "face_cluster_1",
-        "type": "face",
-        "suggested_identity": {
-          "id": 123,
-          "name": "张曼玉",
-          "confidence": 0.92
-        },
-        "appearance_count": 45,
-        "status": "pending"
-      }
-    ],
-    "total": 15
-  }
-}
-```
-
-**实现**: 扩展现有 `/api/v1/people/suggest`
-
----
-
-### 2. GET /people (人物列表)
-
-**marcom 需求**: 获取所有人物列表
-
-**等效 API**: 
-```
-GET /api/v1/people?file_uuid={uuid}&limit={n}&offset={n}&status={status}
-```
-
-**功能**:
-- 返回人物身份列表
-- 支持按 file_uuid 筛选
-- 支持分页
-- 支持按状态筛选 (confirmed, pending, all)
-
-**响应示例**:
-```json
-{
-  "success": true,
-  "message": "Found 8 persons",
-  "data": {
-    "persons": [
-      {
-        "identity_id": "Person_17",
-        "name": "张曼玉",
-        "appearance_count": 45,
-        "total_duration": 350.2,
-        "is_confirmed": true
-      }
-    ],
-    "total": 8
-  }
-}
-```
-
-**实现**: 现有 `/api/v1/people/list` 已支持
-
----
-
-### 3. GET /people/{identity_id} (人物详情)
-
-**marcom 需求**: 获取人物详情
-
-**等效 API**: 
-```
-GET /api/v1/people/{identity_id}?file_uuid={uuid}
-```
-
-**功能**:
-- 返回人物详细信息
-- 包含出场时间线
-- 包含关联的 face/speaker
-- 包含缩略图
-
-**响应示例**:
-```json
-{
-  "success": true,
-  "data": {
-    "identity_id": "Person_17",
-    "name": "张曼玉",
-    "face_identity_id": 123,
-    "speaker_id": "SPEAKER_00",
-    "appearance_count": 45,
-    "total_duration": 350.2,
-    "first_appearance_time": 10.5,
-    "last_appearance_time": 360.2,
-    "timeline": [...],
-    "thumbnails": [...]
-  }
-}
-```
-
-**实现**: 现有 `/api/v1/people/:person_id` 已支持
-
----
-
-### 4. POST /people (创建人物)
-
-**marcom 需求**: 手动创建新人物
-
-**等效 API**: 
-```
-POST /api/v1/people
-Body: { "name": "张曼玉", "file_uuid": "xxx", "metadata": {...} }
-```
-
-**功能**:
-- 创建新人物身份
-- 关联到指定视频
-- 支持添加 metadata (角色名、演员名等)
-
-**响应示例**:
-```json
-{
-  "success": true,
-  "message": "Person created",
-  "data": {
-    "identity_id": "Person_99",
-    "name": "张曼玉",
-    "file_uuid": "xxx"
-  }
-}
-```
-
-**实现**: 需新增，参考 `CreatePersonIdentityRequest`
-
----
-
-### 5. PATCH /people/{identity_id} (更新人物)
-
-**marcom 需求**: 更新人物信息
-
-**等效 API**: 
-```
-PATCH /api/v1/people/{identity_id}
-Body: { "name": "新名字", "is_confirmed": true, "metadata": {...} }
-```
-
-**功能**:
-- 更新人物名称
-- 确认人物身份
-- 更新 metadata
-
-**实现**: 现有 `/api/v1/people/:person_id` (PATCH) 已支持
-
----
-
-### 6. POST /people/merge (合并人物)
-
-**marcom 需求**: 合并多个人物为一个
-
-**等效 API**: 
-```
-POST /api/v1/people/merge
-Body: { 
-  "target_identity_id": "Person_17",
-  "source_identity_ids": ["Person_18", "Person_19"]
-}
-```
-
-**功能**:
-- 合并多个人物身份
-- 转移所有出场记录
-- 更新统计数据
-
-**实现**: 现有 `/api/v1/people/merge` 已支持
-
----
-
-### 7. POST /people/skip (跳过人物)
-
-**marcom 需求**: 跳过某个候选人物（不处理）
-
-**等效 API**: 
-```
-POST /api/v1/people/skip
-Body: { "candidate_id": "face_cluster_2", "reason": "非人物" }
-```
-
-**功能**:
-- 标记候选为"已跳过"
-- 记录跳过原因
-- 不创建人物身份
-
-**响应示例**:
-```json
-{
-  "success": true,
-  "message": "Candidate skipped",
-  "data": {
-    "candidate_id": "face_cluster_2",
-    "status": "skipped",
-    "reason": "非人物"
-  }
-}
-```
-
-**实现**: 需新增，扩展候选管理功能
-
----
-
-### 8. POST /people/{identity_id}/remove-face (移除人脸)
-
-**marcom 需求**: 从人物身份中移除特定人脸绑定
-
-**等效 API**: 
-```
-POST /api/v1/people/{identity_id}/unbind
-Body: { "binding_type": "face", "binding_value": "face_123" }
-```
-
-**功能**:
-- 解绑人脸与人物身份的关联
-- 人脸回到候选状态
-- 更新人物出场统计
-
-**响应示例**:
-```json
-{
-  "success": true,
-  "message": "Face unbound",
-  "data": {
-    "identity_id": "Person_17",
-    "unbound_face": "face_123",
-    "updated_appearance_count": 42
-  }
-}
-```
-
-**实现**: 需新增，参考现有 `UnbindIdentityRequest`
-
----
-
-### 9. POST /people/split-face (分离人脸)
-
-**marcom 需求**: 将人脸从现有人物分离为新人物
-
-**等效 API**: 
-```
-POST /api/v1/people/split
-Body: { 
-  "source_identity_id": "Person_17",
-  "face_ids": ["face_123", "face_124"],
-  "new_identity_name": "新人物"
-}
-```
-
-**功能**:
-- 从现有人物分离指定人脸
-- 创建新人物身份
-- 转移出场记录
-
-**实现**: 现有 `/api/v1/people/:person_id/split` 部分支持
-
----
-
-### 10. GET /people/{identity_id}/resolve (解决冲突)
-
-**marcom 需求**: 获取人物的冲突/歧义信息
-
-**等效 API**: 
-```
-GET /api/v1/people/{identity_id}/conflicts
-```
-
-**功能**:
-- 返回人物身份的潜在冲突
-- 显示相似人脸/声音的匹配
-- 提供解决方案建议
-
-**响应示例**:
-```json
-{
-  "success": true,
-  "data": {
-    "identity_id": "Person_17",
-    "conflicts": [
-      {
-        "type": "similar_face",
-        "conflicting_identity": "Person_18",
-        "similarity": 0.85,
-        "suggestion": "merge"
-      }
-    ],
-    "resolution_options": ["merge", "keep_separate", "skip"]
-  }
-}
-```
-
-**实现**: 需新增
-
----
-
-### 11. POST /search (搜索)
-
-**marcom 需求**: 搜索人物
-
-**等效 API**: 
-```
-POST /api/v1/people/search
-Body: { 
-  "query": "张",
-  "filters": { "type": "people", "file_uuid": "xxx" },
-  "limit": 20
-}
-```
-
-**功能**:
-- 搜索人物身份
-- 支持按名称、类型、视频筛选
-- 返回匹配结果
-
-**实现**: 现有 `/api/v1/identities/search` 已支持，建议扩展
-
----
-
-### 12. GET /people/status (人物状态)
-
-**marcom 需求**: 获取人物处理状态统计
-
-**等效 API**: 
-```
-GET /api/v1/people/status?file_uuid={uuid}
-```
-
-**功能**:
-- 返回人物处理统计
-- 待确认数量、已确认数量、跳过数量
-- 合并历史
-
-**响应示例**:
-```json
-{
-  "success": true,
-  "data": {
-    "file_uuid": "xxx",
-    "total_candidates": 15,
-    "confirmed": 8,
-    "pending": 5,
-    "skipped": 2,
-    "merge_count": 3,
-    "split_count": 1
-  }
-}
-```
-
-**实现**: 需新增
-
----
-
-## 实现优先级
-
-| 优先级 | API | 状态 | 预估工时 |
-|--------|-----|------|----------|
-| **P0** | GET /people | ✅ 已有 | 0h |
-| **P0** | GET /people/{identity_id} | ✅ 已有 | 0h |
-| **P0** | PATCH /people/{identity_id} | ✅ 已有 | 0h |
-| **P0** | POST /people/merge | ✅ 已有 | 0h |
-| **P1** | GET /people/candidates | ⚠️ 扩展 | 2h |
-| **P1** | POST /people | ❌ 新增 | 2h |
-| **P1** | POST /people/search | ⚠️ 扩展 | 1h |
-| **P2** | POST /people/skip | ❌ 新增 | 2h |
-| **P2** | POST /people/{identity_id}/unbind | ❌ 新增 | 2h |
-| **P2** | POST /people/split | ⚠️ 扩展 | 1h |
-| **P2** | GET /people/{identity_id}/conflicts | ❌ 新增 | 3h |
-| **P2** | GET /people/status | ❌ 新增 | 2h |
-
-**总预估**: ~13h (P1+P2)
-
----
-
-## 数据库表需求
-
-现有表结构支持大部分需求，可能需要扩展：
-
-```sql
--- 建议新增: candidates 表 (候选管理)
-CREATE TABLE person_candidates (
-    id BIGSERIAL PRIMARY KEY,
-    file_uuid VARCHAR(36) NOT NULL,
-    candidate_type VARCHAR(20),  -- 'face', 'speaker'
-    candidate_id VARCHAR(50),    -- 'face_cluster_1', 'speaker_2'
-    suggested_identity_id BIGINT,
-    confidence FLOAT,
-    status VARCHAR(20),          -- 'pending', 'confirmed', 'skipped'
-    skip_reason TEXT,
-    created_at TIMESTAMP,
-    updated_at TIMESTAMP
-);
-```
-
----
-
-## 参考文档
-
-- `docs_v1.0/ARCHITECTURE/MOMENTRY_CORE_ARCHITECTURE_V2.md` - Identity 系统设计
-- `docs_v1.0/ARCHITECTURE/PERSON_IDENTITY_INTEGRATION.md` - Person Identity 整合
-- `src/api/person_identity.rs` - 现有 API 实现
-- `src/api/identity_binding.rs` - 身份绑定 API

docs_v1.0/API_DOCUMENTATION.md

@@ -1,699 +0,0 @@
-# Momentry Core API Documentation v1.0.0
-
-## Overview
-Momentry Core is a digital asset management system with video analysis, RAG, and face recognition capabilities. This document covers all API endpoints available in v1.0.0.
-
-**Base URL**: `http://<host>:<port>`
-- Production: Port 3002
-- Development (Playground): Port 3003
-
-**Authentication**: All protected routes require API key validation via `X-API-Key` header.
-
----
-
-## API Classification
-
-The API is organized into 7 categories:
-
-| Category | Prefix | Description |
-|----------|--------|-------------|
-| **Health & Auth** | `/health`, `/api/v1/auth` | System health, authentication |
-| **Asset Management** | `/api/v1/register`, `/api/v1/files`, `/api/v1/assets` | File registration, probing, processing |
-| **Search** | `/api/v1/search`, `/api/v1/n8n` | Text, hybrid, visual, and n8n search |
-| **Video Details** | `/api/v1/videos`, `/api/v1/progress` | Video listing, details, chunks |
-| **Identity & Binding** | `/api/v1/identities`, `/api/v1/signals` | Face/speaker identity management |
-| **Jobs & Rules** | `/api/v1/jobs`, `/api/v1/rules` | Processing job monitoring |
-| **Stats & Config** | `/api/v1/stats`, `/api/v1/config` | System statistics, configuration |
-
----
-
-## 1. Health & Authentication
-
-### `GET /health`
-Basic health check.
-
-**Response**:
-```json
-{
-  "status": "ok",
-  "version": "v1.0.0",
-  "uptime_ms": 12345
-}
-```
-
-### `GET /health/detailed`
-Detailed health check with service status (PostgreSQL, Redis, Qdrant, MongoDB).
-
-**Response**:
-```json
-{
-  "status": "ok",
-  "version": "v1.0.0",
-  "uptime_ms": 12345,
-  "services": {
-    "postgres": { "status": "ok", "latency_ms": 5 },
-    "redis": { "status": "ok", "latency_ms": 2 },
-    "qdrant": { "status": "ok", "latency_ms": 10 },
-    "mongodb": { "status": "ok", "latency_ms": 8 }
-  }
-}
-```
-
-### `POST /api/v1/auth/login`
-Authenticate and obtain API key.
-
-**Request**:
-```json
-{
-  "username": "demo",
-  "password": "demo"
-}
-```
-
-**Response**:
-```json
-{
-  "success": true,
-  "message": "Login successful",
-  "api_key": "muser_test_001",
-  "user": { "username": "demo" }
-}
-```
-
-### `POST /api/v1/auth/logout`
-Logout session.
-
-**Response**:
-```json
-{ "success": true }
-```
-
----
-
-## 2. Asset Management
-
-### `POST /api/v1/register`
-Register a video file (legacy path-based).
-
-**Request**:
-```json
-{ "path": "./demo/video.mp4" }
-```
-
-**Response**:
-```json
-{
-  "file_uuid": "384b0ff44aaaa1f1",
-  "file_id": 1,
-  "job_id": 1,
-  "file_name": "video.mp4",
-  "duration": 120.5,
-  "width": 1920,
-  "height": 1080,
-  "already_exists": false
-}
-```
-
-### `POST /api/v1/files/register`
-Register a file with full metadata (recommended). Supports move detection.
-
-**Request**:
-```json
-{
-  "file_path": "/Users/accusys/momentry/var/sftpgo/data/demo/video.mp4",
-  "user_id": null
-}
-```
-
-**Response**:
-```json
-{
-  "success": true,
-  "file_uuid": "384b0ff44aaaa1f1",
-  "file_name": "video.mp4",
-  "file_path": "/Users/accusys/momentry/var/sftpgo/data/demo/video.mp4",
-  "file_type": "video",
-  "duration": 120.5,
-  "width": 1920,
-  "height": 1080,
-  "fps": 30.0,
-  "total_frames": 3615,
-  "registration_time": null,
-  "already_exists": false,
-  "message": "File registered successfully"
-}
-```
-
-### `GET /api/v1/files/scan`
-Scan filesystem for unregistered files.
-
-### `POST /api/v1/unregister`
-Unregister a video file.
-
-**Request**:
-```json
-{ "uuid": "384b0ff44aaaa1f1" }
-```
-
-### `POST /api/v1/probe`
-Probe a video file for metadata.
-
-**Request**:
-```json
-{ "path": "./demo/video.mp4" }
-```
-
-**Response**:
-```json
-{
-  "uuid": "384b0ff44aaaa1f1",
-  "file_name": "video.mp4",
-  "duration": 120.5,
-  "width": 1920,
-  "height": 1080,
-  "fps": 30.0,
-  "cached": true,
-  "format": { ... },
-  "streams": [ ... ]
-}
-```
-
-### `GET /api/v1/assets/:uuid/probe`
-Probe a video by UUID.
-
-### `POST /api/v1/assets/:uuid/process`
-Trigger processing pipeline for an asset.
-
-**Request**:
-```json
-{
-  "processors": ["asr", "cut", "yolo", "ocr", "face", "pose", "asrx", "visual_chunk"]
-}
-```
-
-**Response**:
-```json
-{
-  "job_id": 1,
-  "asset_uuid": "384b0ff44aaaa1f1",
-  "status": "PENDING",
-  "message": "Processing triggered for video.mp4"
-}
-```
-
-### `GET /api/v1/assets/:uuid/status`
-Get asset processing status with frame progress.
-
-**Response**:
-```json
-{
-  "uuid": "384b0ff44aaaa1f1",
-  "file_name": "video.mp4",
-  "registration_time": "2026-04-30T10:00:00Z",
-  "processing_status": "processing",
-  "current_job_id": "abc-123",
-  "frame_progress": {
-    "total_frames": 3615,
-    "processed_frames": 1200,
-    "progress_percent": 33.2
-  }
-}
-```
-
----
-
-## 3. Search
-
-### `POST /api/v1/search`
-Vector/smart search across chunks.
-
-**Request**:
-```json
-{
-  "query": "person talking about AI",
-  "mode": "smart",
-  "uuid": "384b0ff44aaaa1f1",
-  "limit": 10
-}
-```
-
-**Response**:
-```json
-{
-  "results": [
-    {
-      "uuid": "384b0ff44aaaa1f1",
-      "chunk_id": "chunk_1",
-      "chunk_type": "sentence",
-      "start_time": 10.5,
-      "end_time": 15.2,
-      "text": "AI is transforming...",
-      "score": 0.85
-    }
-  ],
-  "query": "person talking about AI"
-}
-```
-
-### `POST /api/v1/search/hybrid`
-Hybrid search (vector + BM25).
-
-**Request**:
-```json
-{
-  "query": "search term",
-  "limit": 10,
-  "uuid": "384b0ff44aaaa1f1",
-  "vector_weight": 0.7,
-  "bm25_weight": 0.3
-}
-```
-
-### `POST /api/v1/search/bm25`
-BM25 full-text search.
-
-### `POST /api/v1/search/visual`
-Search visual chunks by criteria.
-
-**Request**:
-```json
-{
-  "uuid": "384b0ff44aaaa1f1",
-  "criteria": {
-    "object_class": "person",
-    "min_count": 1
-  }
-}
-```
-
-### `POST /api/v1/search/visual/class`
-Search by object class.
-
-**Request**:
-```json
-{
-  "uuid": "384b0ff44aaaa1f1",
-  "object_class": "person",
-  "min_count": 1,
-  "max_count": null
-}
-```
-
-### `POST /api/v1/search/visual/density`
-Search by object density.
-
-**Request**:
-```json
-{
-  "uuid": "384b0ff44aaaa1f1",
-  "min_density": 0.5,
-  "max_density": null
-}
-```
-
-### `POST /api/v1/search/visual/combination`
-Search by object combination.
-
-**Request**:
-```json
-{
-  "uuid": "384b0ff44aaaa1f1",
-  "combination": [["person", 2], ["car", 1]]
-}
-```
-
-### `POST /api/v1/search/visual/stats`
-Get visual chunk statistics.
-
-**Request**:
-```json
-{ "uuid": "384b0ff44aaaa1f1" }
-```
-
-### `POST /api/v1/n8n/search`
-Search via n8n integration.
-
-### `POST /api/v1/n8n/search/bm25`
-BM25 search via n8n.
-
-### `POST /api/v1/n8n/search/hybrid`
-Hybrid search via n8n.
-
-### `POST /api/v1/n8n/search/smart`
-Smart search via n8n.
-
----
-
-## 4. Video Details
-
-### `GET /api/v1/videos`
-List all registered videos with pagination.
-
-**Query Parameters**:
-- `page`: Page number (default: 1)
-- `page_size`: Items per page (default: 20)
-- `status`: Filter by status
-- `q`: Search query
-- `uuid`: Filter by UUID
-
-**Response**:
-```json
-{
-  "files": [
-    {
-      "file_uuid": "384b0ff44aaaa1f1",
-      "file_path": "/path/to/video.mp4",
-      "file_name": "video.mp4",
-      "file_type": "video",
-      "duration": 120.5,
-      "width": 1920,
-      "height": 1080,
-      "status": "completed",
-      "created_at": "2026-04-30T10:00:00Z",
-      "file_size": 52428800,
-      "total_frames": 3615
-    }
-  ],
-  "count": 1,
-  "page": 1,
-  "page_size": 20
-}
-```
-
-### `DELETE /api/v1/videos/:uuid`
-Delete a video and all associated data (faces, chunks, processor results).
-
-**Response**:
-```json
-{
-  "success": true,
-  "message": "File 384b0ff44aaaa1f1 unregistered successfully...",
-  "file_uuid": "384b0ff44aaaa1f1",
-  "deleted_face_detections": 150,
-  "deleted_processor_results": 8,
-  "deleted_chunks": 45
-}
-```
-
-### `GET /api/v1/videos/:uuid/details`
-Get detailed chunk information.
-
-**Query Parameters**:
-- `chunk_id`: Specific chunk ID (required)
-- `parent_id`: Parent chunk ID
-
-**Response**:
-```json
-{
-  "uuid": "384b0ff44aaaa1f1",
-  "chunk_id": "chunk_1",
-  "chunk_type": "sentence",
-  "frame_range": {
-    "start_frame": 315,
-    "end_frame": 456,
-    "duration_frames": 141,
-    "fps": 30.0
-  },
-  "reference_time": {
-    "start": 10.5,
-    "end": 15.2
-  },
-  "text_content": "AI is transforming...",
-  "summary_text": "Discussion about AI impact",
-  "speaker_ids": ["SPEAKER_0"],
-  "person_ids": ["face_100"]
-}
-```
-
-### `GET /api/v1/videos/:uuid/pre_chunks`
-List pre-processor chunks.
-
-**Query Parameters**:
-- `processor_type`: Filter by processor (asr, yolo, face, etc.)
-- `page`: Page number
-- `page_size`: Items per page
-
-### `GET /api/v1/progress/:uuid`
-Get processing progress for a video.
-
----
-
-## 5. Identity & Binding
-
-### `POST /api/v1/identities/from-face`
-Register a global identity from face.json with multi-angle reference vectors.
-
-**Request**:
-```json
-{
-  "face_json_path": "/path/to/face.json",
-  "identity_name": "John Doe",
-  "schema": "dev"
-}
-```
-
-### `POST /api/v1/identities/from-person`
-Register identity from a person in a video.
-
-**Request**:
-```json
-{
-  "file_uuid": "384b0ff44aaaa1f1",
-  "person_id": "person_1",
-  "identity_name": "John Doe"
-}
-```
-
-### `GET /api/v1/identities`
-List all global identities.
-
-**Query Parameters**:
-- `page`: Page number
-- `page_size`: Items per page
-
-### `GET /api/v1/faces/candidates`
-List unbound face candidates.
-
-**Query Parameters**:
-- `file_uuid`: Filter by file
-- `min_confidence`: Minimum confidence (default: 0.5)
-- `page`, `page_size`: Pagination
-
-### `GET /api/v1/identities/:identity_id/faces`
-Get all faces for an identity.
-
-### `GET /api/v1/faces/:face_id/thumbnail`
-Get face thumbnail image (JPEG).
-
-### `POST /api/v1/identities/bind`
-Bind a face/speaker to an identity.
-
-**Request**:
-```json
-{
-  "identity_id": 1,
-  "binding_type": "face",
-  "binding_value": "face_100",
-  "source": "manual"
-}
-```
-
-### `POST /api/v1/identities/unbind`
-Unbind an identity.
-
-**Request**:
-```json
-{
-  "binding_type": "face",
-  "binding_value": "face_100"
-}
-```
-
-### `GET /api/v1/identity/:binding_type/:binding_value`
-Get identity info by binding.
-
-### `GET /api/v1/signals/unbound`
-List unbound signals.
-
-**Query Parameters**:
-- `uuid`: File UUID
-- `binding_type`: "face" or "speaker"
-
-### `GET /api/v1/signals/:uuid/:binding_type/:binding_value/timeline`
-Get signal timeline (all chunks for a face/speaker).
-
-### `POST /api/v1/identities/suggest-av`
-Suggest audio-visual bindings based on temporal overlap.
-
-**Request**:
-```json
-{
-  "file_uuid": "384b0ff44aaaa1f1",
-  "overlap_threshold": 0.6
-}
-```
-
----
-
-## 6. Jobs & Rules
-
-### `GET /api/v1/jobs`
-List all monitor jobs.
-
-**Query Parameters**:
-- `page`, `page_size`: Pagination
-- `status`: Filter by status
-
-### `GET /api/v1/jobs/:job_id`
-Get job details with processor information.
-
-**Response**:
-```json
-{
-  "job_id": "1",
-  "asset_uuid": "384b0ff44aaaa1f1",
-  "rule": "default",
-  "status": "RUNNING",
-  "current_processor_id": "asr",
-  "frame_progress": {
-    "total_frames": 3615,
-    "processed_frames": 1200,
-    "progress_percent": 33.2
-  }
-}
-```
-
-### `GET /api/v1/rules/:rule/status`
-Get rule status with active jobs.
-
----
-
-## 7. Stats & Configuration
-
-### `GET /api/v1/stats/ingest`
-Get ingestion statistics.
-
-**Response**:
-```json
-{
-  "total_videos": 50,
-  "total_chunks": 1200,
-  "sentence_chunks": 800,
-  "cut_chunks": 300,
-  "time_chunks": 100,
-  "searchable_chunks": 1150,
-  "chunks_with_visual": 450,
-  "chunks_with_summary": 200,
-  "pending_videos": 5
-}
-```
-
-### `GET /api/v1/stats/sftpgo`
-Get SFTPGo status and registered videos.
-
-### `GET /api/v1/stats/inference`
-Check inference engine health (Ollama, llama-server).
-
-**Response**:
-```json
-{
-  "ollama": {
-    "engine": "Ollama",
-    "model": "nomic-embed-text",
-    "status": "ok",
-    "latency_ms": 15
-  },
-  "llama_server": {
-    "engine": "llama-server",
-    "model": "gemma4_e4b_q5",
-    "status": "ok",
-    "latency_ms": 25
-  }
-}
-```
-
-### `POST /api/v1/config/cache`
-Toggle MongoDB cache.
-
-**Request**:
-```json
-{ "enabled": false }
-```
-
-**Response**:
-```json
-{
-  "success": true,
-  "cache_enabled": false,
-  "message": "Cache disabled"
-}
-```
-
----
-
-## API Usage Patterns
-
-### 1. List Pattern
-```
-GET /api/v1/videos?page=1&page_size=20
-```
-- Supports pagination
-- Optional filters via query parameters
-- Returns `{ items: [...], count, page, page_size }`
-
-### 2. Detail Pattern
-```
-GET /api/v1/videos/:uuid/details?chunk_id=chunk_1
-```
-- Path parameter for resource identifier
-- Query parameters for sub-resource selection
-- Returns detailed object with nested structures
-
-### 3. Operation Pattern
-```
-POST /api/v1/assets/:uuid/process
-```
-- Action-oriented endpoint
-- Request body contains operation parameters
-- Returns operation status and job ID
-
-### 4. Application Pattern
-```
-POST /api/v1/identities/bind
-POST /api/v1/identities/suggest-av
-```
-- Complex workflows with multiple steps
-- Often involve external services (Python scripts, FFmpeg)
-- Return comprehensive results with metadata
-
----
-
-## Error Responses
-
-| Status Code | Description |
-|-------------|-------------|
-| `400` | Bad Request - Invalid parameters |
-| `404` | Not Found - Resource doesn't exist |
-| `500` | Internal Server Error - Database/service failure |
-
----
-
-## V4.0 Architecture Notes
-
-### Key Changes from V3.x
-- `video_uuid` → `file_uuid` (terminology update)
-- `person_identities` table **removed**
-- Face → Identity direct binding (no intermediate person_id)
-- 28 person_id APIs removed (except register/bind)
-- Chunk binding auto via time alignment
-
-### Identity Model
-```
-Face Detection → Identity (direct binding)
-Speaker Detection → Identity (direct binding)
-```
-
-### Processing Pipeline
-```
-Register → Probe → ASR → CUT → YOLO → OCR → Face → Pose → ASRX → Visual Chunk
-```

docs_v1.0/API_V1.0.0/API_DICTIONARY_V1.0.0.md

@@ -0,0 +1,177 @@
+# API Dictionary v1.0.0
+
+58 endpoints across 10 modules. Auth: `X-API-Key` header or `Authorization: Bearer <key>`.
+
+## API Design Principle
+
+Every path segment after the resource ID is a **verb** — an action on that resource.
+
+```
+/api/v1/{entity}/{id}/{action}
+            ↑        ↑      ↑
+           實體      ID    動作
+```
+
+**Primary entities**: `file`/`files`, `identity`/`identities`
+
+```
+/api/v1/file/:file_uuid       ← 檔案資源
+  /video                      → 播放影片（動詞）
+  /video/bbox                 → 播放含框（動詞）
+  /thumbnail                  → 取縮圖（動詞）
+  /process                    → 啟動處理（動詞）
+  /probe                      → 探測（動詞）
+  /chunks                     → 列出段落（動詞）
+  /identities                 → 列出身分（動詞）
+  /face_trace/sortby          → 列出追蹤/排序（動詞）
+  /trace/:trace_id/faces      → 列出偵測（動詞）
+
+/api/v1/identity/:identity_uuid
+  /bind                       → 綁定（動詞）
+  /unbind                     → 解綁（動詞）
+  /files                      → 列出檔案（動詞）
+  /chunks                     → 列出段落（動詞）
+
+/api/v1/search/universal      → 搜尋（動詞）
+/api/v1/search/smart          → 智慧搜尋（動詞）
+```
+
+**Naming conventions**:
+- 全域唯一資源 ID → `uuid`（`file_uuid`, `identity_uuid`）
+- 單一實體下唯一 ID → `id`（`trace_id`, `chunk_id`, `face_id`）
+- 路徑尾端 → 動詞（`/video`, `/chunks`, `/bind`）
+- 集合列表 → **複數**（`/files`, `/identities`, `/resources`, `/faces`）
+- 單一資源操作 → **單數**（`/file/:file_uuid`, `/identity/:identity_uuid`）
+
+## Legend
+
+- `→` direction of data flow
+- `POST` typically requires JSON body
+- All endpoints return JSON unless noted
+
+---
+
+| # | Method | Route | Description |
+|---|--------|-------|-------------|
+| 1 | GET | `/health` | Server health (ok/degraded) |
+| 2 | GET | `/health/detailed` | Per-service health + latency |
+| 3 | POST | `/api/v1/auth/login` | Username/password → API key |
+| 4 | POST | `/api/v1/auth/logout` | Invalidate session |
+| 5 | GET | `/api/v1/stats/ingest` | Ingest statistics |
+| 6 | GET | `/api/v1/stats/sftpgo` | SFTPGo service status |
+| 7 | GET | `/api/v1/stats/inference` | LLM/embedding health |
+| 8 | POST | `/api/v1/files/register` | Register video file → file_uuid |
+| 9 | POST | `/api/v1/unregister` | Unregister file(s): by `file_uuid` or pattern match on `file_path`+`pattern` |
+| 10 | GET | `/api/v1/files/scan` | Scan directory for new files |
+| 11 | GET | `/api/v1/file/:file_uuid/probe` | ffprobe metadata |
+| 12 | POST | `/api/v1/file/:file_uuid/process` | Start processing pipeline |
+| 13 | GET | `/api/v1/file/:file_uuid/chunks` | List pre-chunks for file |
+| 14 | GET | `/api/v1/progress/:file_uuid` | Processing progress |
+| 15 | GET | `/api/v1/jobs` | List monitor jobs (filterable by status) |
+| 16 | POST | `/api/v1/config/cache` | Toggle Redis cache |
+| 17 | POST | `/api/v1/config/auto-pipeline` | Toggle auto-pipeline on register |
+| 18 | POST | `/api/v1/config/watcher-auto-register` | Toggle watcher auto-register |
+| 17 | POST | `/api/v1/search/visual` | Search visual chunks |
+| 18 | POST | `/api/v1/search/visual/class` | Search by object class |
+| 19 | POST | `/api/v1/search/visual/density` | Search by spatial density |
+| 20 | POST | `/api/v1/search/visual/combination` | Combined visual search |
+| 21 | POST | `/api/v1/search/visual/stats` | Visual chunk statistics |
+
+## File/Identity (identity_api.rs)
+
+| # | Method | Route | Description |
+|---|--------|-------|-------------|
+| 22 | GET | `/api/v1/files` | List registered files (paginated) |
+| 23 | GET | `/api/v1/file/:file_uuid` | Single file detail |
+| 24 | GET | `/api/v1/file/:file_uuid/identities` | Identities in this file |
+| 25 | GET | `/api/v1/identities` | List all identities |
+| 26 | POST | `/api/v1/identity` | Register new identity |
+| 27 | GET | `/api/v1/identity/:identity_uuid` | Identity detail |
+| 28 | DELETE | `/api/v1/identity/:identity_uuid` | Delete identity |
+| 29 | GET | `/api/v1/identity/:identity_uuid/files` | Files for an identity |
+| 30 | GET | `/api/v1/identity/:identity_uuid/chunks` | Chunks for an identity |
+| 31 | POST | `/api/v1/resource/register` | Register processing resource |
+| 32 | POST | `/api/v1/resource/heartbeat` | Resource heartbeat |
+| 33 | GET | `/api/v1/resources` | List all resources |
+
+## Identity Binding (identity_binding.rs)
+
+| # | Method | Route | Description |
+|---|--------|-------|-------------|
+| 34 | POST | `/api/v1/identity/:identity_uuid/bind` | Bind face → identity |
+| 35 | POST | `/api/v1/identity/:identity_uuid/unbind` | Unbind face from identity |
+| 36 | POST | `/api/v1/identity/:identity_uuid/mergeinto` | Merge identity :identity_uuid → target |
+
+## Face Candidates (identities.rs)
+
+| # | Method | Route | Description |
+|---|--------|-------|-------------|
+| 37 | GET | `/api/v1/faces/candidates` | Unbound face gallery (paginated) |
+
+## Search (search.rs + universal_search.rs)
+
+| # | Method | Route | Description |
+|---|--------|-------|-------------|
+| 38 | POST | `/api/v1/search/smart` | Semantic search (EmbeddingGemma + pgvector) |
+| 39 | POST | `/api/v1/search/universal` | BM25 keyword search (requires file_uuid) |
+| 40 | POST | `/api/v1/search/frames` | Frame-level search |
+
+## Trace (trace_agent_api.rs)
+
+| # | Method | Route | Description |
+|---|--------|-------|-------------|
+| 41 | POST | `/api/v1/file/:file_uuid/face_trace/sortby` | List traces (sorted/filtered) |
+| 42 | GET | `/api/v1/file/:file_uuid/trace/:trace_id/faces` | Single trace detections + interpolation |
+
+## Media (media_api.rs)
+
+| # | Method | Route | Description |
+|---|--------|-------|-------------|
+| 43 | GET | `/api/v1/file/:file_uuid/thumbnail` | Frame JPEG (optional crop via `?frame=&x=&y=&w=&h=`) |
+| 44 | GET | `/api/v1/file/:file_uuid/video` | Raw video stream (`?start_time=&end_time=` in seconds) |
+| 45 | GET | `/api/v1/file/:file_uuid/video/bbox` | Bbox overlay video (`?start_frame=&end_frame=&duration=` frame numbers) |
+| 46 | GET | `/api/v1/file/:file_uuid/trace/:trace_id/video` | Trace clip (`?mode=normal\|debug&padding=`) |
+
+## Identity Delete
+
+| # | Method | Route | Description |
+|---|--------|-------|-------------|
+| 47 | DELETE | `/api/v1/identity/:identity_uuid` | Delete identity + unbind all faces |
+
+## Agents (agent_api.rs + five_w1h_agent_api.rs + identity_agent_api.rs)
+
+| # | Method | Route | Description |
+|---|--------|-------|-------------|
+| 48 | POST | `/api/v1/agents/translate` | AI text translation |
+| 49 | POST | `/api/v1/agents/5w1h/analyze` | Single chunk 5W1H analysis |
+| 50 | POST | `/api/v1/agents/5w1h/batch` | Batch 5W1H analysis |
+| 51 | GET | `/api/v1/agents/5w1h/status` | 5W1H job status |
+| 52 | POST | `/api/v1/agents/identity/analyze` | Identity analysis |
+| 53 | GET | `/api/v1/agents/identity/status` | Identity job status |
+| 54 | POST | `/api/v1/agents/identity/suggest` | Identity suggestions |
+| 55 | POST | `/api/v1/agents/suggest/merge` | Suggest identity merge |
+| 56 | POST | `/api/v1/agents/suggest/clustering` | Suggest re-clustering |
+
+## Identity Search (identity_api.rs, new in V4.1)
+
+| # | Method | Route | Description |
+|---|--------|-------|-------------|
+| 57 | GET | `/api/v1/identities/search?q=` | Search identities by name → chunk results |
+| 58 | GET | `/api/v1/search/identity_text?q=&file_uuid=` | Full-text search → identity-bound chunks |
+
+---
+
+## Summary
+
+| Module | Routes | File |
+|--------|--------|------|
+| Core | 21 | `server.rs` |
+| File/Identity | 14 | `identity_api.rs` (+2 search endpoints) |
+| Binding | 3 | `identity_binding.rs` |
+| Faces | 1 | `identities.rs` |
+| Search | 3 | `search.rs`, `universal_search.rs` |
+| Trace | 2 | `trace_agent_api.rs` |
+| Media | 4 | `media_api.rs` |
+| Identity Delete | 1 | `identity_api.rs` |
+| Agents | 9 | `agent_api.rs`, `five_w1h_agent_api.rs`, `identity_agent_api.rs` |
+| **Total** | **58** | |