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.

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Table of Contents

• Gemini-OpenAI-Proxy
  • Table of Contents
  • Build
  • Deploy
  • Usage
  • Compatibility
  • License

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Build

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

go build -o gemini main.go

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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.

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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

• zhu327#4

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License

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