GopherGate/README.md

GopherGate

A unified, high-performance LLM proxy gateway built in Go. It provides a single OpenAI-compatible API to access multiple providers (OpenAI, Gemini, DeepSeek, Moonshot, Grok, Ollama) with built-in token tracking, real-time cost calculation, multi-user authentication, and a management dashboard.

Features

• Unified API: OpenAI-compatible /v1/chat/completions and /v1/models endpoints.
• Multi-Provider Support:
  • OpenAI: GPT-4o, GPT-4o Mini, o1, o3 reasoning models.
  • Google Gemini: Gemini 2.0 Flash, Pro, and vision models (with native CoT support).
  • DeepSeek: DeepSeek Chat and Reasoner (R1) models.
  • Moonshot: Kimi K2.5 and other Kimi models.
  • xAI Grok: Grok-4 models.
  • Ollama: Local LLMs running on your network.
• Observability & Tracking:
  • Asynchronous Logging: Non-blocking request logging to SQLite using background workers.
  • Token Counting: Precise estimation and tracking of prompt, completion, and reasoning tokens.
  • Database Persistence: Every request logged to SQLite for historical analysis and dashboard analytics.
  • Streaming Support: Full SSE (Server-Sent Events) support for all providers.
• Multimodal (Vision): Image processing (Base64 and remote URLs) across compatible providers.
• Multi-User Access Control:
  • Admin Role: Full access to all dashboard features, user management, and system configuration.
  • Viewer Role: Read-only access to usage analytics, costs, and monitoring.
  • Client API Keys: Create and manage multiple client tokens for external integrations.
• Reliability:
  • Circuit Breaking: Automatically protects when providers are down (coming soon).
  • Rate Limiting: Per-client and global rate limits (coming soon).

Security

GopherGate is designed with security in mind:

• Signed Session Tokens: Management dashboard sessions are secured using HMAC-SHA256 signed tokens.
• Encrypted Storage: Support for encrypted provider API keys in the database.
• Auth Middleware: Secure client authentication via database-backed API keys.

Note: You must define an LLM_PROXY__ENCRYPTION_KEY in your .env file for secure session signing and encryption.

Tech Stack

• Runtime: Go 1.22+
• Web Framework: Gin Gonic
• Database: sqlx with SQLite (CGO-free via modernc.org/sqlite)
• Frontend: Vanilla JS/CSS with Chart.js for visualizations

Getting Started

Prerequisites

• Go (1.22+)
• SQLite3 (optional, driver is built-in)
• Docker (optional, for containerized deployment)

Quick Start

1. Clone and build:

   git clone <repository-url>
   cd gophergate
   go build -o gophergate ./cmd/gophergate
   

2. Configure environment:

   cp .env.example .env
   # Edit .env and add your configuration:
   # LLM_PROXY__ENCRYPTION_KEY=... (32-byte hex or base64 string)
   # OPENAI_API_KEY=sk-...
   # GEMINI_API_KEY=AIza...
   # MOONSHOT_API_KEY=...
   

3. Run the proxy:

   ./gophergate
   

The server starts on http://0.0.0.0:8080 by default.

Deployment (Docker)

# Build the container
docker build -t gophergate .

# Run the container
docker run -p 8080:8080 \
  -e LLM_PROXY__ENCRYPTION_KEY=your-secure-key \
  -v ./data:/app/data \
  gophergate

Management Dashboard

Access the dashboard at http://localhost:8080.

• Auth: Login, session management, and status tracking.
• Usage: Summary stats, time-series analytics, and provider breakdown.
• Clients: API key management and per-client usage tracking.
• Providers: Provider configuration and status monitoring.
• Users: Admin-only user management for dashboard access.
• Monitoring: Live request stream via WebSocket.

Default Credentials

• Username: admin
• Password: admin123 (You will be prompted to change this on first login)

Forgot Password? You can reset the admin password to default by running:

./gophergate -reset-admin

API Usage

The proxy is a drop-in replacement for OpenAI. Configure your client:

Moonshot models are available through the same OpenAI-compatible endpoint. For example, use kimi-k2.5 as the model name after setting MOONSHOT_API_KEY in your environment.

Python

from openai import OpenAI

client = OpenAI(
    base_url="http://localhost:8080/v1",
    api_key="YOUR_CLIENT_API_KEY"  # Create in dashboard
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}]
)

License

MIT