/gemini-openai-proxy

A proxy for converting the OpenAI API protocol to the Google Gemini Pro protocol.

Primary LanguageGoMIT LicenseMIT

Gemini-OpenAI-Proxy

Gemini-OpenAI-Proxy is a proxy designed to convert the OpenAI API protocol to the Google Gemini Pro protocol. This enables seamless integration of OpenAI-powered functionalities into applications using the Gemini Pro protocol.

Table of Contents

Build

To build the Gemini-OpenAI-Proxy, follow these steps:

go build -o gemini main.go

Deploy

We recommend deploying Gemini-OpenAI-Proxy using Docker for a straightforward setup. Follow these steps to deploy with Docker:

docker run --restart=always -it -d -p 8080:8080 --name gemini zhu327/gemini-openai-proxy:latest

Adjust the port mapping (e.g., -p 8080:8080) as needed, and ensure that the Docker image version (zhu327/gemini-openai-proxy:latest) aligns with your requirements.

Usage

Gemini-OpenAI-Proxy offers a straightforward way to integrate OpenAI functionalities into any application that supports custom OpenAI API endpoints. Follow these steps to leverage the capabilities of this proxy:

  1. Set Up OpenAI Endpoint: Ensure your application is configured to use a custom OpenAI API endpoint. Gemini-OpenAI-Proxy seamlessly works with any OpenAI-compatible endpoint.

  2. Get Google AI Studio API Key: Before using the proxy, you'll need to obtain an API key from ai.google.dev. Treat this API key as your OpenAI API key when interacting with Gemini-OpenAI-Proxy.

  3. Integrate the Proxy into Your Application: Modify your application's API requests to target the Gemini-OpenAI-Proxy, providing the acquired Google AI Studio API key as if it were your OpenAI API key.

    Example API Request (Assuming the proxy is hosted at http://localhost:8080):

    curl http://localhost:8080/v1/chat/completions \
 -H "Content-Type: application/json" \
 -H "Authorization: Bearer $YOUR_GOOGLE_AI_STUDIO_API_KEY" \
 -d '{
     "model": "gpt-3.5-turbo",
     "messages": [{"role": "user", "content": "Say this is a test!"}],
     "temperature": 0.7
 }'

    Alternatively, use Gemini Pro Vision:

    curl http://localhost:8080/v1/chat/completions \
 -H "Content-Type: application/json" \
 -H "Authorization: Bearer $YOUR_GOOGLE_AI_STUDIO_API_KEY" \
 -d '{
     "model": "gpt-4-vision-preview",
     "messages": [{"role": "user", "content": [
        {"type": "text", "text": "What’s in this image?"},
        {
          "type": "image_url",
          "image_url": {
            "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
          }
        }
     ]}],
     "temperature": 0.7
 }'

    If you already have access to the Gemini 1.5 Pro api, you can use:

    curl http://localhost:8080/v1/chat/completions \
 -H "Content-Type: application/json" \
 -H "Authorization: Bearer $YOUR_GOOGLE_AI_STUDIO_API_KEY" \
 -d '{
     "model": "gpt-4-turbo-preview",
     "messages": [{"role": "user", "content": "Say this is a test!"}],
     "temperature": 0.7
 }'

    Model Mapping:

    • gpt-3.5-turbo -> gemini-1.0-pro-latest
    • gpt-4 -> gemini-1.0-ultra-latest
    • gpt-4-turbo-preview -> gemini-1.5-pro-latest
    • gpt-4-vision-preview -> gemini-1.0-pro-vision-latest

    If you wish to map gpt-4-vision-preview to gemini-1.5-pro-latest, you can configure the environment variable GPT_4_VISION_PREVIEW = gemini-1.5-pro-latest. This is because gemini-1.5-pro-latest now also supports multi-modal data.

  4. Handle Responses: Process the responses from the Gemini-OpenAI-Proxy in the same way you would handle responses from OpenAI.

Now, your application is equipped to leverage OpenAI functionality through the Gemini-OpenAI-Proxy, bridging the gap between OpenAI and applications using the Google Gemini Pro protocol.

Compatibility

License

Gemini-OpenAI-Proxy is licensed under the MIT License - see the LICENSE file for details.