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Server implementation for LangGate AI Gateway

Project description

LangGate Server

Server implementation for the LangGate AI Gateway. This package provides the FastAPI server implementation that hosts the LangGate registry API.

Features

  • FastAPI-based API server
  • Registry endpoints for model information
  • Configurable settings through environment variables or config files
  • Structured logging with request context

Usage

# Run the server with uvicorn
import uvicorn
from langgate.server import app

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=4000)

Docker Deployment

The LangGate repository includes a Dockerfile specifically for running this server:

# Build the Docker image
docker build -t langgate-server .

# Run the container
docker run -p 4000:4000 langgate-server

You can also use the provided Docker Compose setup for a complete deployment (which runs the server behind an Envoy proxy on port 10000):

# Start the full LangGate stack
make compose-up

# For development with hot reloading
make compose-dev

Configuration

The server can be configured through:

  • Environment variables
  • A .env file in your working directory
  • A langgate_config.yaml file in your working directory
  • Command-line arguments to the uvicorn server

See the main LangGate documentation for more details on configuration options.

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