hobokenchicken
0ce5f4f490
Updated README, architecture, and TODO to reflect full feature parity, system metrics, and registry integration.
135 lines
4.2 KiB
Markdown
135 lines
4.2 KiB
Markdown
# LLM Proxy Gateway
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A unified, high-performance LLM proxy gateway built in Go. It provides a single OpenAI-compatible API to access multiple providers (OpenAI, Gemini, DeepSeek, Grok, Ollama) with built-in token tracking, real-time cost calculation, multi-user authentication, and a management dashboard.
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## Features
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- **Unified API:** OpenAI-compatible `/v1/chat/completions` and `/v1/models` endpoints.
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- **Multi-Provider Support:**
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- **OpenAI:** GPT-4o, GPT-4o Mini, o1, o3 reasoning models.
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- **Google Gemini:** Gemini 2.0 Flash, Pro, and vision models (with native CoT support).
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- **DeepSeek:** DeepSeek Chat and Reasoner (R1) models.
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- **xAI Grok:** Grok-2 models.
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- **Ollama:** Local LLMs running on your network.
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- **Observability & Tracking:**
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- **Asynchronous Logging:** Non-blocking request logging to SQLite using background workers.
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- **Token Counting:** Precise estimation and tracking of prompt, completion, and reasoning tokens.
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- **Database Persistence:** Every request logged to SQLite for historical analysis and dashboard analytics.
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- **Streaming Support:** Full SSE (Server-Sent Events) support for all providers.
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- **Multimodal (Vision):** Image processing (Base64 and remote URLs) across compatible providers.
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- **Multi-User Access Control:**
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- **Admin Role:** Full access to all dashboard features, user management, and system configuration.
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- **Viewer Role:** Read-only access to usage analytics, costs, and monitoring.
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- **Client API Keys:** Create and manage multiple client tokens for external integrations.
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- **Reliability:**
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- **Circuit Breaking:** Automatically protects when providers are down (coming soon).
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- **Rate Limiting:** Per-client and global rate limits (coming soon).
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## Security
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LLM Proxy is designed with security in mind:
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- **Signed Session Tokens:** Management dashboard sessions are secured using HMAC-SHA256 signed tokens.
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- **Encrypted Storage:** Support for encrypted provider API keys in the database.
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- **Auth Middleware:** Secure client authentication via database-backed API keys.
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**Note:** You must define an `LLM_PROXY__ENCRYPTION_KEY` in your `.env` file for secure session signing and encryption.
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## Tech Stack
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- **Runtime:** Go 1.22+
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- **Web Framework:** Gin Gonic
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- **Database:** sqlx with SQLite (CGO-free via `modernc.org/sqlite`)
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- **Frontend:** Vanilla JS/CSS with Chart.js for visualizations
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## Getting Started
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### Prerequisites
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- Go (1.22+)
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- SQLite3 (optional, driver is built-in)
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- Docker (optional, for containerized deployment)
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### Quick Start
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1. Clone and build:
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```bash
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git clone <repository-url>
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cd llm-proxy
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go build -o llm-proxy ./cmd/llm-proxy
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```
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2. Configure environment:
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```bash
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cp .env.example .env
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# Edit .env and add your configuration:
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# LLM_PROXY__ENCRYPTION_KEY=... (32-byte hex or base64 string)
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# OPENAI_API_KEY=sk-...
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# GEMINI_API_KEY=AIza...
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```
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3. Run the proxy:
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```bash
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./llm-proxy
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```
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The server starts on `http://0.0.0.0:8080` by default.
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### Deployment (Docker)
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```bash
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# Build the container
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docker build -t llm-proxy .
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# Run the container
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docker run -p 8080:8080 \
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-e LLM_PROXY__ENCRYPTION_KEY=your-secure-key \
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-v ./data:/app/data \
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llm-proxy
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```
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## Management Dashboard
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Access the dashboard at `http://localhost:8080`.
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- **Auth:** Login, session management, and status tracking.
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- **Usage:** Summary stats, time-series analytics, and provider breakdown.
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- **Clients:** API key management and per-client usage tracking.
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- **Providers:** Provider configuration and status monitoring.
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- **Users:** Admin-only user management for dashboard access.
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- **Monitoring:** Live request stream via WebSocket.
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### Default Credentials
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- **Username:** `admin`
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- **Password:** `admin123` (You will be prompted to change this on first login)
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**Forgot Password?**
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You can reset the admin password to default by running:
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```bash
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./llm-proxy -reset-admin
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```
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## API Usage
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The proxy is a drop-in replacement for OpenAI. Configure your client:
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### Python
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```python
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from openai import OpenAI
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client = OpenAI(
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base_url="http://localhost:8080/v1",
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api_key="YOUR_CLIENT_API_KEY" # Create in dashboard
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)
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response = client.chat.completions.create(
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model="gpt-4o",
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messages=[{"role": "user", "content": "Hello!"}]
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)
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```
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## License
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MIT
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