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
.envfile 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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