CLIProxyAPI

README

CLI Proxy API

A proxy server that provides an OpenAI-compatible API interface for CLI. This allows you to use CLI models with tools and libraries designed for the OpenAI API.

Features

• OpenAI-compatible API endpoints for CLI models
• Support for both streaming and non-streaming responses
• Function calling/tools support
• Multimodal input support (text and images)
• Multiple account support with load balancing
• Simple CLI authentication flow

Installation

Prerequisites

• Go 1.24 or higher
• A Google account with access to CLI models

Building from Source

1. Clone the repository:

   git clone https://github.com/luispater/CLIProxyAPI.git
   cd CLIProxyAPI
   

2. Build the application:

   go build -o cli-proxy-api ./cmd/server
   

Usage

Authentication

Before using the API, you need to authenticate with your Google account:

./cli-proxy-api --login

If you are an old gemini code user, you may need to specify a project ID:

./cli-proxy-api --login --project_id <your_project_id>

Starting the Server

Once authenticated, start the server:

./cli-proxy-api

By default, the server runs on port 8317.

API Endpoints

List Models

GET http://localhost:8317/v1/models

Chat Completions

POST http://localhost:8317/v1/chat/completions

Request body example:

{
  "model": "gemini-2.5-pro",
  "messages": [
    {
      "role": "user",
      "content": "Hello, how are you?"
    }
  ],
  "stream": true
}

Using with OpenAI Libraries

You can use this proxy with any OpenAI-compatible library by setting the base URL to your local server:

Python (with OpenAI library)

from openai import OpenAI

client = OpenAI(
    api_key="dummy",  # Not used but required
    base_url="http://localhost:8317/v1"
)

response = client.chat.completions.create(
    model="gemini-2.5-pro",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)

print(response.choices[0].message.content)

JavaScript/TypeScript

import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: 'dummy', // Not used but required
  baseURL: 'http://localhost:8317/v1',
});

const response = await openai.chat.completions.create({
  model: 'gemini-2.5-pro',
  messages: [
    { role: 'user', content: 'Hello, how are you?' }
  ],
});

console.log(response.choices[0].message.content);

Supported Models

• gemini-2.5-pro
• gemini-2.5-flash
• And various preview versions

Configuration

The server uses a YAML configuration file (config.yaml) located in the project root directory by default. You can specify a different configuration file path using the --config flag:

./cli-proxy --config /path/to/your/config.yaml

Configuration Options

Parameter	Type	Default	Description
port	integer	8317	The port number on which the server will listen
auth_dir	string	"~/.cli-proxy-api"	Directory where authentication tokens are stored. Supports using ~ for home directory
proxy-url	string	""	Proxy url, support socks5/http/https protocol, example: socks5://user:pass@192.168.1.1:1080/
debug	boolean	false	Enable debug mode for verbose logging
api_keys	string[]	[]	List of API keys that can be used to authenticate requests

Example Configuration File

# Server port
port: 8317

# Authentication directory (supports ~ for home directory)
auth_dir: "~/.cli-proxy-api"

# Enable debug logging
debug: false

# API keys for authentication
api_keys:
  - "your-api-key-1"
  - "your-api-key-2"

Authentication Directory

The auth_dir parameter specifies where authentication tokens are stored. When you run the login command, the application will create JSON files in this directory containing the authentication tokens for your Google accounts. Multiple accounts can be used for load balancing.

API Keys

The api_keys parameter allows you to define a list of API keys that can be used to authenticate requests to your proxy server. When making requests to the API, you can include one of these keys in the Authorization header:

Authorization: Bearer your-api-key-1

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.