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README.md
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README.md
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# Agent Media 🎬
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# Alfred Media Organizer 🎬
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An AI-powered agent for managing your local media library with natural language. Search, download, and organize movies and TV shows effortlessly.
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An AI-powered agent for managing your local media library with natural language. Search, download, and organize movies and TV shows effortlessly through a conversational interface.
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## Features
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[](https://www.python.org/downloads/)
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[](https://python-poetry.org/)
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[](https://opensource.org/licenses/MIT)
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[](https://github.com/astral-sh/ruff)
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- 🤖 **Natural Language Interface**: Talk to your media library in plain language
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- 🔍 **Smart Search**: Find movies and TV shows via TMDB
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- 📥 **Torrent Integration**: Search and download via qBittorrent
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- 🧠 **Contextual Memory**: Remembers your preferences and conversation history
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- 📁 **Auto-Organization**: Keeps your media library tidy
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- 🌐 **API Compatible**: OpenAI-compatible API for easy integration
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## ✨ Features
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## Architecture
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- 🤖 **Natural Language Interface** — Talk to your media library in plain language
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- 🔍 **Smart Search** — Find movies and TV shows via TMDB with rich metadata
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- 📥 **Torrent Integration** — Search and download via qBittorrent
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- 🧠 **Contextual Memory** — Remembers your preferences and conversation history
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- 📁 **Auto-Organization** — Keeps your media library tidy and well-structured
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- 🌐 **OpenAI-Compatible API** — Works with any OpenAI-compatible client
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- 🖥️ **LibreChat Frontend** — Beautiful web UI included out of the box
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- 🔒 **Secure by Default** — Auto-generated secrets and encrypted credentials
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Built with **Domain-Driven Design (DDD)** principles:
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## 🏗️ Architecture
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Built with **Domain-Driven Design (DDD)** principles for clean separation of concerns:
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```
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agent_media/
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├── agent/ # AI agent orchestration
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├── application/ # Use cases & DTOs
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├── domain/ # Business logic & entities
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└── infrastructure/ # External services & persistence
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alfred/
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├── agent/ # AI agent orchestration
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│ ├── llm/ # LLM clients (Ollama, DeepSeek)
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│ └── tools/ # Tool implementations
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├── application/ # Use cases & DTOs
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│ ├── movies/ # Movie search use cases
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│ ├── torrents/ # Torrent management
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│ └── filesystem/ # File operations
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├── domain/ # Business logic & entities
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│ ├── movies/ # Movie entities
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│ ├── tv_shows/ # TV show entities
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│ └── subtitles/ # Subtitle entities
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└── infrastructure/ # External services & persistence
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├── api/ # External API clients (TMDB, qBittorrent)
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├── filesystem/ # File system operations
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└── persistence/ # Memory & repositories
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```
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See [architecture_diagram.md](docs/architecture_diagram.md) for architectural details.
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See [docs/architecture_diagram.md](docs/architecture_diagram.md) for detailed architectural diagrams.
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## Quick Start
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## 🚀 Quick Start
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### Prerequisites
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- Python 3.12+
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- Poetry
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- qBittorrent (optional, for downloads)
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- API Keys:
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- DeepSeek API key (or Ollama for local LLM)
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- TMDB API key
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- **Python 3.14+** (required)
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- **Poetry** (dependency manager)
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- **Docker & Docker Compose** (recommended for full stack)
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- **API Keys:**
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- TMDB API key ([get one here](https://www.themoviedb.org/settings/api))
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- Optional: DeepSeek, OpenAI, Anthropic, or other LLM provider keys
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### Installation
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```bash
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# Clone the repository
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git clone https://github.com/your-username/agent-media.git
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cd agent-media
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git clone https://github.com/francwa/alfred_media_organizer.git
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cd alfred_media_organizer
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# Install dependencies
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poetry install
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make install
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# Copy environment template
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cp .env.example .env
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# Bootstrap environment (generates .env with secure secrets)
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make bootstrap
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# Edit .env with your API keys
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nano .env
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```
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### Configuration
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Edit `.env`:
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### Running with Docker (Recommended)
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```bash
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# LLM Provider (deepseek or ollama)
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LLM_PROVIDER=deepseek
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DEEPSEEK_API_KEY=your-api-key-here
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# Start all services (LibreChat + Alfred + MongoDB + Ollama)
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make up
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# TMDB (for movie/TV show metadata)
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TMDB_API_KEY=your-tmdb-key-here
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# Or start with specific profiles
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make up p=rag,meili # Include RAG and Meilisearch
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make up p=qbittorrent # Include qBittorrent
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make up p=full # Everything
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# qBittorrent (optional)
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QBITTORRENT_HOST=http://localhost:8080
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QBITTORRENT_USERNAME=admin
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QBITTORRENT_PASSWORD=adminadmin
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# View logs
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make logs
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# Stop all services
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make down
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```
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### Run
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The web interface will be available at **http://localhost:3080**
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### Running Locally (Development)
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```bash
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# Install dependencies
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poetry install
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# Start the API server
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poetry run uvicorn app:app --reload
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# Or with Docker
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docker-compose up
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poetry run uvicorn alfred.app:app --reload --port 8000
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```
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The API will be available at `http://localhost:8000`
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## ⚙️ Configuration
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## Usage
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### Environment Bootstrap
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Alfred uses a smart bootstrap system that:
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1. **Generates secure secrets** automatically (JWT tokens, database passwords, encryption keys)
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2. **Syncs build variables** from `pyproject.toml` (versions, image names)
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3. **Preserves existing secrets** when re-running (never overwrites your API keys)
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4. **Computes database URIs** automatically from individual components
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```bash
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# First time setup
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make bootstrap
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# Re-run after updating pyproject.toml (secrets are preserved)
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make bootstrap
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```
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### Configuration File (.env)
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The `.env` file is generated from `.env.example` with secure defaults:
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```bash
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# --- CORE SETTINGS ---
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HOST=0.0.0.0
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PORT=3080
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MAX_HISTORY_MESSAGES=10
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MAX_TOOL_ITERATIONS=10
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# --- LLM CONFIGURATION ---
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# Providers: 'local' (Ollama), 'deepseek', 'openai', 'anthropic', 'google'
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DEFAULT_LLM_PROVIDER=local
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# Local LLM (Ollama - included in Docker stack)
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OLLAMA_BASE_URL=http://ollama:11434
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OLLAMA_MODEL=llama3.3:latest
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LLM_TEMPERATURE=0.2
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# --- API KEYS (fill only what you need) ---
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TMDB_API_KEY=your-tmdb-key-here # Required for movie search
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DEEPSEEK_API_KEY= # Optional
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OPENAI_API_KEY= # Optional
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ANTHROPIC_API_KEY= # Optional
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# --- SECURITY (auto-generated, don't modify) ---
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JWT_SECRET=<auto-generated>
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JWT_REFRESH_SECRET=<auto-generated>
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CREDS_KEY=<auto-generated>
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CREDS_IV=<auto-generated>
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# --- DATABASES (auto-generated passwords) ---
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MONGO_PASSWORD=<auto-generated>
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POSTGRES_PASSWORD=<auto-generated>
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```
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### Security Keys
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Security keys are defined in `pyproject.toml` and generated automatically:
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```toml
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[tool.alfred.security]
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jwt_secret = "32:b64" # 32 bytes, base64 URL-safe
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jwt_refresh_secret = "32:b64"
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creds_key = "32:hex" # 32 bytes, hexadecimal (AES-256)
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creds_iv = "16:hex" # 16 bytes, hexadecimal (AES IV)
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mongo_password = "16:hex"
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postgres_password = "16:hex"
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```
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**Formats:**
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- `b64` — Base64 URL-safe (for JWT tokens)
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- `hex` — Hexadecimal (for encryption keys, passwords)
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## 🐳 Docker Services
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### Service Architecture
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```
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┌─────────────────────────────────────────────────────────────┐
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│ alfred-net (bridge) │
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├─────────────────────────────────────────────────────────────┤
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│ │
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│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
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│ │ LibreChat │───▶│ Alfred │───▶│ MongoDB │ │
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│ │ :3080 │ │ (core) │ │ :27017 │ │
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│ └──────────────┘ └──────────────┘ └──────────────┘ │
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│ │ │ │
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│ │ ▼ │
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│ │ ┌──────────────┐ │
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│ │ │ Ollama │ │
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│ │ │ (local) │ │
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│ │ └──────────────┘ │
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│ │ │
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│ ┌──────┴───────────────────────────────────────────────┐ │
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│ │ Optional Services (profiles) │ │
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│ ├──────────────┬──────────────┬──────────────┬─────────┤ │
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│ │ Meilisearch │ RAG API │ VectorDB │qBittor- │ │
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│ │ :7700 │ :8000 │ :5432 │ rent │ │
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│ │ [meili] │ [rag] │ [rag] │[qbit..] │ │
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│ └──────────────┴──────────────┴──────────────┴─────────┘ │
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│ │
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└─────────────────────────────────────────────────────────────┘
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```
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### Docker Profiles
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| Profile | Services | Use Case |
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|---------|----------|----------|
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| (default) | LibreChat, Alfred, MongoDB, Ollama | Basic setup |
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| `meili` | + Meilisearch | Fast search |
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| `rag` | + RAG API, VectorDB | Document retrieval |
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| `qbittorrent` | + qBittorrent | Torrent downloads |
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| `full` | All services | Complete setup |
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```bash
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# Start with specific profiles
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make up p=rag,meili
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make up p=full
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```
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### Docker Commands
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```bash
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make up # Start containers (default profile)
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make up p=full # Start with all services
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make down # Stop all containers
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make restart # Restart containers
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make logs # Follow logs
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make ps # Show container status
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make shell # Open bash in Alfred container
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make build # Build production image
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make build-test # Build test image
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```
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## 🛠️ Available Tools
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The agent has access to these tools for interacting with your media library:
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| Tool | Description |
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|------|-------------|
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| `find_media_imdb_id` | Search for movies/TV shows on TMDB by title |
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| `find_torrent` | Search for torrents across multiple indexers |
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| `get_torrent_by_index` | Get detailed info about a specific torrent result |
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| `add_torrent_by_index` | Download a torrent by its index in search results |
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| `add_torrent_to_qbittorrent` | Add a torrent via magnet link directly |
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| `set_path_for_folder` | Configure folder paths for media organization |
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| `list_folder` | List contents of a folder |
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| `set_language` | Set preferred language for searches |
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## 💬 Usage Examples
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### Via Web Interface (LibreChat)
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Navigate to **http://localhost:3080** and start chatting:
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```
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You: Find Inception in 1080p
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Alfred: I found 3 torrents for Inception (2010):
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1. Inception.2010.1080p.BluRay.x264 (150 seeders) - 2.1 GB
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2. Inception.2010.1080p.WEB-DL.x265 (80 seeders) - 1.8 GB
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3. Inception.2010.1080p.REMUX (45 seeders) - 25 GB
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You: Download the first one
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Alfred: ✓ Added to qBittorrent! Download started.
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Saving to: /downloads/Movies/Inception (2010)/
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You: What's downloading right now?
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Alfred: You have 1 active download:
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- Inception.2010.1080p.BluRay.x264 (45% complete, ETA: 12 min)
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```
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### Via API
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@@ -91,219 +279,177 @@ The API will be available at `http://localhost:8000`
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# Health check
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curl http://localhost:8000/health
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# Chat with the agent
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# Chat with the agent (OpenAI-compatible)
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curl -X POST http://localhost:8000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": "agent-media",
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"model": "alfred",
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"messages": [
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{"role": "user", "content": "Find Inception 1080p"}
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{"role": "user", "content": "Find The Matrix 4K"}
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]
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}'
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# List available models
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curl http://localhost:8000/v1/models
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# View memory state (debug)
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curl http://localhost:8000/memory/state
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# Clear session memory
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curl -X POST http://localhost:8000/memory/clear-session
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```
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### Via OpenWebUI
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### Via OpenWebUI or Other Clients
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Agent Media is compatible with [OpenWebUI](https://github.com/open-webui/open-webui):
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Alfred is compatible with any OpenAI-compatible client:
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1. Add as OpenAI-compatible endpoint: `http://localhost:8000/v1`
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2. Model name: `agent-media`
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3. Start chatting!
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2. Model name: `alfred`
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3. No API key required (or use any placeholder)
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### Example Conversations
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## 🧠 Memory System
|
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```
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You: Find Inception in 1080p
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Agent: I found 3 torrents for Inception:
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1. Inception.2010.1080p.BluRay.x264 (150 seeders)
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2. Inception.2010.1080p.WEB-DL.x265 (80 seeders)
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3. Inception.2010.720p.BluRay (45 seeders)
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You: Download the first one
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Agent: Added to qBittorrent! Download started.
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You: List my downloads
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Agent: You have 1 active download:
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- Inception.2010.1080p.BluRay.x264 (45% complete)
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```
|
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|
||||
## Available Tools
|
||||
|
||||
The agent has access to these tools:
|
||||
|
||||
| Tool | Description |
|
||||
|------|-------------|
|
||||
| `find_media_imdb_id` | Search for movies/TV shows on TMDB |
|
||||
| `find_torrents` | Search for torrents |
|
||||
| `get_torrent_by_index` | Get torrent details by index |
|
||||
| `add_torrent_by_index` | Download torrent by index |
|
||||
| `add_torrent_to_qbittorrent` | Add torrent via magnet link |
|
||||
| `set_path_for_folder` | Configure folder paths |
|
||||
| `list_folder` | List folder contents |
|
||||
|
||||
## Memory System
|
||||
|
||||
Agent Media uses a three-tier memory system:
|
||||
Alfred uses a three-tier memory system for context management:
|
||||
|
||||
### Long-Term Memory (LTM)
|
||||
- **Persistent** (saved to JSON)
|
||||
- Configuration, preferences, media library
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||||
- Survives restarts
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||||
- **Persistent** — Saved to JSON files
|
||||
- **Contents:** Configuration, user preferences, media library state
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||||
- **Survives:** Application restarts
|
||||
|
||||
### Short-Term Memory (STM)
|
||||
- **Session-based** (RAM only)
|
||||
- Conversation history, current workflow
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||||
- Cleared on restart
|
||||
- **Session-based** — Stored in RAM
|
||||
- **Contents:** Conversation history, current workflow state
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||||
- **Cleared:** On session end or restart
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||||
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||||
### Episodic Memory
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||||
- **Transient** (RAM only)
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||||
- Search results, active downloads, recent errors
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||||
- Cleared frequently
|
||||
- **Transient** — Stored in RAM
|
||||
- **Contents:** Search results, active downloads, recent errors
|
||||
- **Cleared:** Frequently, after task completion
|
||||
|
||||
## Development
|
||||
## 🧪 Development
|
||||
|
||||
### Project Structure
|
||||
### Project Setup
|
||||
|
||||
```
|
||||
agent_media/
|
||||
├── agent/
|
||||
│ ├── agent.py # Main agent orchestrator
|
||||
│ ├── prompts.py # System prompt builder
|
||||
│ ├── registry.py # Tool registration
|
||||
│ ├── tools/ # Tool implementations
|
||||
│ └── llm/ # LLM clients (DeepSeek, Ollama)
|
||||
├── application/
|
||||
│ ├── movies/ # Movie use cases
|
||||
│ ├── torrents/ # Torrent use cases
|
||||
│ └── filesystem/ # Filesystem use cases
|
||||
├── domain/
|
||||
│ ├── movies/ # Movie entities & value objects
|
||||
│ ├── tv_shows/ # TV show entities
|
||||
│ ├── subtitles/ # Subtitle entities
|
||||
│ └── shared/ # Shared value objects
|
||||
├── infrastructure/
|
||||
│ ├── api/ # External API clients
|
||||
│ │ ├── tmdb/ # TMDB client
|
||||
│ │ ├── knaben/ # Torrent search
|
||||
│ │ └── qbittorrent/ # qBittorrent client
|
||||
│ ├── filesystem/ # File operations
|
||||
│ └── persistence/ # Memory & repositories
|
||||
├── tests/ # Test suite (~500 tests)
|
||||
└── docs/ # Documentation
|
||||
```bash
|
||||
# Install all dependencies (including dev)
|
||||
poetry install
|
||||
|
||||
# Install pre-commit hooks
|
||||
make install-hooks
|
||||
|
||||
# Run the development server
|
||||
poetry run uvicorn alfred.app:app --reload
|
||||
```
|
||||
|
||||
### Running Tests
|
||||
|
||||
```bash
|
||||
# Run all tests
|
||||
poetry run pytest
|
||||
# Run all tests (parallel execution)
|
||||
make test
|
||||
|
||||
# Run with coverage
|
||||
poetry run pytest --cov
|
||||
# Run with coverage report
|
||||
make coverage
|
||||
|
||||
# Run specific test file
|
||||
poetry run pytest tests/test_agent.py
|
||||
poetry run pytest tests/test_agent.py -v
|
||||
|
||||
# Run specific test
|
||||
poetry run pytest tests/test_agent.py::TestAgent::test_step
|
||||
poetry run pytest tests/test_config_loader.py::TestBootstrapEnv -v
|
||||
```
|
||||
|
||||
### Code Quality
|
||||
|
||||
```bash
|
||||
# Linting
|
||||
poetry run ruff check .
|
||||
# Lint and auto-fix
|
||||
make lint
|
||||
|
||||
# Formatting
|
||||
poetry run black .
|
||||
# Format code
|
||||
make format
|
||||
|
||||
# Type checking (if mypy is installed)
|
||||
poetry run mypy .
|
||||
# Clean build artifacts
|
||||
make clean
|
||||
```
|
||||
|
||||
### Adding a New Tool
|
||||
|
||||
Quick example:
|
||||
1. **Create the tool function** in `alfred/agent/tools/`:
|
||||
|
||||
```python
|
||||
# 1. Create the tool function in agent/tools/api.py
|
||||
def my_new_tool(param: str) -> Dict[str, Any]:
|
||||
"""Tool description."""
|
||||
# alfred/agent/tools/api.py
|
||||
def my_new_tool(param: str) -> dict[str, Any]:
|
||||
"""
|
||||
Short description of what this tool does.
|
||||
|
||||
This will be shown to the LLM to help it decide when to use this tool.
|
||||
"""
|
||||
memory = get_memory()
|
||||
# Implementation
|
||||
return {"status": "ok", "data": "result"}
|
||||
|
||||
# 2. Register in agent/registry.py
|
||||
Tool(
|
||||
name="my_new_tool",
|
||||
description="What this tool does",
|
||||
func=api_tools.my_new_tool,
|
||||
parameters={
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"param": {"type": "string", "description": "Parameter description"},
|
||||
},
|
||||
"required": ["param"],
|
||||
},
|
||||
),
|
||||
# Your implementation here
|
||||
result = do_something(param)
|
||||
|
||||
return {
|
||||
"status": "success",
|
||||
"data": result
|
||||
}
|
||||
```
|
||||
|
||||
## Docker
|
||||
2. **Register in the registry** (`alfred/agent/registry.py`):
|
||||
|
||||
### Build
|
||||
```python
|
||||
tool_functions = [
|
||||
# ... existing tools ...
|
||||
api_tools.my_new_tool, # Add your tool here
|
||||
]
|
||||
```
|
||||
|
||||
The tool will be automatically registered with its parameters extracted from the function signature.
|
||||
|
||||
### Version Management
|
||||
|
||||
```bash
|
||||
docker build -t agent-media .
|
||||
# Bump version (must be on main branch)
|
||||
make patch # 0.1.7 -> 0.1.8
|
||||
make minor # 0.1.7 -> 0.2.0
|
||||
make major # 0.1.7 -> 1.0.0
|
||||
```
|
||||
|
||||
### Run
|
||||
|
||||
```bash
|
||||
docker run -p 8000:8000 \
|
||||
-e DEEPSEEK_API_KEY=your-key \
|
||||
-e TMDB_API_KEY=your-key \
|
||||
-v $(pwd)/memory_data:/app/memory_data \
|
||||
agent-media
|
||||
```
|
||||
|
||||
### Docker Compose
|
||||
|
||||
```bash
|
||||
# Start all services (agent + qBittorrent)
|
||||
docker-compose up -d
|
||||
|
||||
# View logs
|
||||
docker-compose logs -f
|
||||
|
||||
# Stop
|
||||
docker-compose down
|
||||
```
|
||||
|
||||
## API Documentation
|
||||
## 📚 API Reference
|
||||
|
||||
### Endpoints
|
||||
|
||||
#### `GET /health`
|
||||
Health check endpoint.
|
||||
|
||||
**Response:**
|
||||
```json
|
||||
{
|
||||
"status": "healthy",
|
||||
"version": "0.2.0"
|
||||
"version": "0.1.7"
|
||||
}
|
||||
```
|
||||
|
||||
#### `GET /v1/models`
|
||||
List available models (OpenAI-compatible).
|
||||
|
||||
```json
|
||||
{
|
||||
"object": "list",
|
||||
"data": [
|
||||
{
|
||||
"id": "alfred",
|
||||
"object": "model",
|
||||
"owned_by": "alfred"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
#### `POST /v1/chat/completions`
|
||||
Chat with the agent (OpenAI-compatible).
|
||||
|
||||
**Request:**
|
||||
```json
|
||||
{
|
||||
"model": "agent-media",
|
||||
"model": "alfred",
|
||||
"messages": [
|
||||
{"role": "user", "content": "Find Inception"}
|
||||
],
|
||||
@@ -317,7 +463,7 @@ Chat with the agent (OpenAI-compatible).
|
||||
"id": "chatcmpl-xxx",
|
||||
"object": "chat.completion",
|
||||
"created": 1234567890,
|
||||
"model": "agent-media",
|
||||
"model": "alfred",
|
||||
"choices": [{
|
||||
"index": 0,
|
||||
"message": {
|
||||
@@ -330,71 +476,120 @@ Chat with the agent (OpenAI-compatible).
|
||||
```
|
||||
|
||||
#### `GET /memory/state`
|
||||
View full memory state (debug).
|
||||
View full memory state (debug endpoint).
|
||||
|
||||
#### `POST /memory/clear-session`
|
||||
Clear session memories (STM + Episodic).
|
||||
|
||||
## Troubleshooting
|
||||
## 🔧 Troubleshooting
|
||||
|
||||
### Agent doesn't respond
|
||||
- Check API keys in `.env`
|
||||
- Verify LLM provider is running (Ollama) or accessible (DeepSeek)
|
||||
- Check logs: `docker-compose logs agent-media`
|
||||
|
||||
1. Check API keys in `.env`
|
||||
2. Verify LLM provider is running:
|
||||
```bash
|
||||
# For Ollama
|
||||
docker logs alfred-ollama
|
||||
|
||||
# Check if model is pulled
|
||||
docker exec alfred-ollama ollama list
|
||||
```
|
||||
3. Check Alfred logs: `docker logs alfred-core`
|
||||
|
||||
### qBittorrent connection failed
|
||||
- Verify qBittorrent is running
|
||||
- Check `QBITTORRENT_HOST` in `.env`
|
||||
- Ensure Web UI is enabled in qBittorrent settings
|
||||
|
||||
1. Verify qBittorrent is running: `docker ps | grep qbittorrent`
|
||||
2. Check Web UI is enabled in qBittorrent settings
|
||||
3. Verify credentials in `.env`:
|
||||
```bash
|
||||
QBITTORRENT_URL=http://qbittorrent:16140
|
||||
QBITTORRENT_USERNAME=admin
|
||||
QBITTORRENT_PASSWORD=<check-your-env>
|
||||
```
|
||||
|
||||
### Database connection issues
|
||||
|
||||
1. Check MongoDB is healthy: `docker logs alfred-mongodb`
|
||||
2. Verify credentials match in `.env`
|
||||
3. Try restarting: `make restart`
|
||||
|
||||
### Memory not persisting
|
||||
- Check `memory_data/` directory exists and is writable
|
||||
- Verify volume mounts in Docker
|
||||
|
||||
1. Check `data/` directory exists and is writable
|
||||
2. Verify volume mounts in `docker-compose.yaml`
|
||||
3. Check file permissions: `ls -la data/`
|
||||
|
||||
### Bootstrap fails
|
||||
|
||||
1. Ensure `.env.example` exists
|
||||
2. Check `pyproject.toml` has required sections:
|
||||
```toml
|
||||
[tool.alfred.settings]
|
||||
[tool.alfred.security]
|
||||
```
|
||||
3. Run manually: `python scripts/bootstrap.py`
|
||||
|
||||
### Tests failing
|
||||
- Run `poetry install` to ensure dependencies are up to date
|
||||
- Check logs for specific error messages
|
||||
|
||||
## Contributing
|
||||
1. Update dependencies: `poetry install`
|
||||
2. Check Python version: `python --version` (needs 3.14+)
|
||||
3. Run specific failing test with verbose output:
|
||||
```bash
|
||||
poetry run pytest tests/test_failing.py -v --tb=long
|
||||
```
|
||||
|
||||
Contributions are welcome!
|
||||
## 🤝 Contributing
|
||||
|
||||
### Development Workflow
|
||||
Contributions are welcome! Please follow these steps:
|
||||
|
||||
1. Fork the repository
|
||||
2. Create a feature branch: `git checkout -b feature/my-feature`
|
||||
3. Make your changes
|
||||
4. Run tests: `poetry run pytest`
|
||||
5. Run linting: `poetry run ruff check . && poetry run black .`
|
||||
6. Commit: `git commit -m "Add my feature"`
|
||||
7. Push: `git push origin feature/my-feature`
|
||||
8. Create a Pull Request
|
||||
1. **Fork** the repository
|
||||
2. **Create** a feature branch: `git checkout -b feature/my-feature`
|
||||
3. **Make** your changes
|
||||
4. **Run** tests: `make test`
|
||||
5. **Run** linting: `make lint && make format`
|
||||
6. **Commit**: `git commit -m "feat: add my feature"`
|
||||
7. **Push**: `git push origin feature/my-feature`
|
||||
8. **Create** a Pull Request
|
||||
|
||||
## Documentation
|
||||
### Commit Convention
|
||||
|
||||
- [Architecture Diagram](docs/architecture_diagram.md) - System architecture overview
|
||||
- [Class Diagram](docs/class_diagram.md) - Class structure and relationships
|
||||
- [Component Diagram](docs/component_diagram.md) - Component interactions
|
||||
- [Sequence Diagram](docs/sequence_diagram.md) - Sequence flows
|
||||
- [Flowchart](docs/flowchart.md) - System flowcharts
|
||||
We use [Conventional Commits](https://www.conventionalcommits.org/):
|
||||
|
||||
## License
|
||||
- `feat:` New feature
|
||||
- `fix:` Bug fix
|
||||
- `docs:` Documentation
|
||||
- `refactor:` Code refactoring
|
||||
- `test:` Adding tests
|
||||
- `chore:` Maintenance
|
||||
|
||||
MIT License - see [LICENSE](LICENSE) file for details.
|
||||
## 📖 Documentation
|
||||
|
||||
## Acknowledgments
|
||||
- [Architecture Diagram](docs/architecture_diagram.md) — System architecture overview
|
||||
- [Class Diagram](docs/class_diagram.md) — Class structure and relationships
|
||||
- [Component Diagram](docs/component_diagram.md) — Component interactions
|
||||
- [Sequence Diagram](docs/sequence_diagram.md) — Sequence flows
|
||||
- [Flowchart](docs/flowchart.md) — System flowcharts
|
||||
|
||||
- [DeepSeek](https://www.deepseek.com/) - LLM provider
|
||||
- [TMDB](https://www.themoviedb.org/) - Movie database
|
||||
- [qBittorrent](https://www.qbittorrent.org/) - Torrent client
|
||||
- [FastAPI](https://fastapi.tiangolo.com/) - Web framework
|
||||
## 📄 License
|
||||
|
||||
## Support
|
||||
MIT License — see [LICENSE](LICENSE) file for details.
|
||||
|
||||
## 🙏 Acknowledgments
|
||||
|
||||
- [LibreChat](https://github.com/danny-avila/LibreChat) — Beautiful chat interface
|
||||
- [Ollama](https://ollama.ai/) — Local LLM runtime
|
||||
- [DeepSeek](https://www.deepseek.com/) — LLM provider
|
||||
- [TMDB](https://www.themoviedb.org/) — Movie database
|
||||
- [qBittorrent](https://www.qbittorrent.org/) — Torrent client
|
||||
- [FastAPI](https://fastapi.tiangolo.com/) — Web framework
|
||||
- [Pydantic](https://docs.pydantic.dev/) — Data validation
|
||||
|
||||
## 📬 Support
|
||||
|
||||
- 📧 Email: francois.hodiaumont@gmail.com
|
||||
- 🐛 Issues: [GitHub Issues](https://github.com/your-username/agent-media/issues)
|
||||
- 💬 Discussions: [GitHub Discussions](https://github.com/your-username/agent-media/discussions)
|
||||
- 🐛 Issues: [GitHub Issues](https://github.com/francwa/alfred_media_organizer/issues)
|
||||
- 💬 Discussions: [GitHub Discussions](https://github.com/francwa/alfred_media_organizer/discussions)
|
||||
|
||||
---
|
||||
|
||||
Made with ❤️ by Francwa
|
||||
<p align="center">Made with ❤️ by <a href="https://github.com/francwa">Francwa</a></p>
|
||||
|
||||
Reference in New Issue
Block a user