momentry_core/AGENTS.md

AGENTS.md - Momentry Core

Rust-based digital asset management system with video analysis and RAG capabilities.

Build & Run Commands

# Build project
cargo build
cargo build --release
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

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

# 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

# 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)

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

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)

#[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

#[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

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)

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

LLM Synonym Generation

Generate synonym database using llama.cpp (Gemma4):

# 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

# 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

# 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：

# 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

# 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

# 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

# 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。

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:

{
  "intelephense.stubs": ["wordpress"]
}

phpactor (CLI)

# 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