# Gemini CLI OpenAI API Proxy

This project provides a lightweight proxy server that translates OpenAI API requests to the Google Gemini API, utilizing the `@google/gemini-cli` for authentication and request handling.

## Features

* **OpenAI API Compatibility:**  Acts as a drop-in replacement for services that use the OpenAI API format.
* **Google Gemini Integration:** Leverages the power of Google's Gemini models.
* **Authentication:** Uses `gemini-cli` for secure OAuth2 authentication with Google.
* **Docker Support:** Includes `Dockerfile` and `docker-compose.yml` for easy containerized deployment.
* **Hugging Face Spaces Ready:** Can be easily deployed as a Hugging Face Space.

## Support the Project

If you find this project useful, consider supporting its development:

[![Donate using Liberapay][liberapay-logo]][liberapay-link]

[liberapay-logo]: https://liberapay.com/assets/widgets/donate.svg "Liberapay Logo"
[liberapay-link]: https://liberapay.com/sfiorini/donate

## Prerequisites

Before you begin, ensure you have the following installed:

* [Node.js](https://nodejs.org/) (v18 or higher)
* [npm](https://www.npmjs.com/)
* [Docker](https://www.docker.com/) (for containerized deployment)
* [Git](https://git-scm.com/)

## Local Installation and Setup

1. **Clone the repository:**

    ```bash
    git clone https://github.com/your-username/gemini-cli-openai-api.git
    cd gemini-cli-openai-api
    ```

2. **Install project dependencies:**

    ```bash
    npm install
    ```

3. **Install the Gemini CLI and Authenticate:**

    This is a crucial step to authenticate with your Google account and generate the necessary credentials.

    ```bash
    npm install -g @google/gemini-cli
    gemini auth login
    ```

    Follow the on-screen instructions to log in with your Google account. This will create a file at `~/.gemini/oauth_creds.json` containing your authentication tokens.

4. **Configure Environment Variables:**

    Create a `.env` file by copying the example file:

    ```bash
    cp .env.example .env
    ```

    Open the `.env` file and set the following variables:

    * `PORT`: The port the server will run on (default: `11434`).
    * `API_KEY`: A secret key to protect your API endpoint. You can generate a strong random string for this.

## Running the Project

### Development Mode

To run the server in development mode with hot-reloading:

```bash
npm run dev
```

The server will be accessible at `http://localhost:11434` (or the port you specified).

### Production Mode

To build and run the server in production mode:

```bash
npm run build
npm start
```

## Docker Deployment

### Using Docker Compose

The easiest way to deploy the project with Docker is by using the provided `docker-compose.yml` file.

1. **Authentication:**

    The Docker container needs access to your OAuth credentials. You have two options:

    * **Option A (Recommended): Mount the credentials file.**
        Uncomment the `volumes` section in `docker-compose.yml` to mount your local `oauth_creds.json` file into the container.

        ```yaml
        volumes:
          - ~/.gemini/oauth_creds.json:/root/.gemini/oauth_creds.json
        ```

    * **Option B: Use environment variables.**
        If you cannot mount the file, you can set the `ACCESS_TOKEN`, `REFRESH_TOKEN`, and `EXPIRY_DATE` environment variables in the `docker-compose.yml` file. You can get these values from your `~/.gemini/oauth_creds.json` file.

2. **Configure `docker-compose.yml`:**

    Open `docker-compose.yml` and set the `API_KEY` and other environment variables as needed.

3. **Start the container:**

    ```bash
    docker-compose up -d
    ```

    The server will be running on the port specified in the `ports` section of the `docker-compose.yml` file (e.g., `4343`).

### Building the Docker Image Manually

If you need to build the Docker image yourself:

```bash
docker build -t gemini-cli-openai-api .
```

Then you can run the container with the appropriate environment variables and volume mounts.

## Hugging Face Spaces Deployment

You can deploy this project as a Docker Space on Hugging Face.

1. **Create a new Space:**
    * Go to [huggingface.co/new-space](https://huggingface.co/new-space).
    * Choose a name for your space.
    * Select "Docker" as the Space SDK.
    * Choose "From scratch".
    * Create the space.

2. **Upload the project files:**
    * Upload all the project files (including the `Dockerfile`) to your new Hugging Face Space repository. You can do this via the web interface or by cloning the space's repository and pushing the files.

3. **Configure Secrets:**
    * In your Space's settings, go to the "Secrets" section.
    * Add the following secrets. You can get the values for the first three from your `~/.gemini/oauth_creds.json` file.
        * `ACCESS_TOKEN`: Your Google OAuth access token.
        * `REFRESH_TOKEN`: Your Google OAuth refresh token.
        * `EXPIRY_DATE`: The expiry date of your access token.
        * `API_KEY`: The secret API key you want to use to protect your endpoint.
        * `PORT`: The port the application should run on inside the container (e.g., `7860`, which is a common default for Hugging Face Spaces).

4. **Update Dockerfile (if necessary):**
    * The provided `Dockerfile` exposes port `4343`. If Hugging Face requires a different port (like `7860`), you may need to update the `EXPOSE` instruction in the `Dockerfile`.

5. **Deploy:**
    * Hugging Face Spaces will automatically build and deploy your Docker container when you push changes to the repository. Check the "Logs" to monitor the build and deployment process.

Your Gemini-powered OpenAI proxy will now be running on your Hugging Face Space!