geminicli2api
A FastAPI proxy that transforms Google's Gemini CLI into OpenAI-compatible and native Gemini API endpoints for easy integration.
What is geminicli2api?
Gemini CLI to API Proxy is a FastAPI-based server that converts Google's Gemini CLI tool into standard API endpoints. It provides both OpenAI-compatible and native Gemini API interfaces, allowing developers to integrate Gemini's AI capabilities into applications using familiar API patterns. The proxy enables access to Google's free Gemini API quota through a standardized interface.
Developers and teams building AI-powered applications who want to use Google's Gemini models through API interfaces compatible with OpenAI's format or direct Gemini API calls.
It provides a drop-in replacement for OpenAI's API while leveraging Google's free Gemini quota, offers both streaming and multimodal support, and is containerized for easy self-hosting. The proxy eliminates the need to adapt tools specifically for Gemini's CLI, enabling broader integration.
Overview
Gemini CLI to API Proxy is a FastAPI-based server that converts the Gemini CLI tool into standard API endpoints. It enables developers to use Google's free Gemini API quota through familiar OpenAI API interfaces or direct Gemini API calls, making it simple to integrate Gemini capabilities into existing applications.
Key Features
- OpenAI-Compatible API — Drop-in replacement for OpenAI's chat completions API, allowing seamless integration with tools expecting OpenAI's format.
- Native Gemini API — Direct proxy to Google's Gemini API, supporting all its endpoints and features.
- Streaming Support — Real-time streaming responses for both API formats, enabling interactive applications.
- Multimodal Support — Handles text and image inputs, leveraging Gemini's multimodal capabilities.
- Authentication Flexibility — Supports multiple auth methods including Bearer tokens, Basic auth, query parameters, and Google API headers.
- Model Variants — Automatically creates model variants with Google Search grounding and thinking/reasoning controls.
- Docker Ready — Containerized for easy deployment and includes Hugging Face Spaces compatibility.
Philosophy
The project aims to bridge the gap between Google's Gemini CLI and the broader ecosystem of AI tools by providing a standardized, easy-to-deploy API layer that maintains compatibility with popular interfaces.
Use Cases
Best For
- Integrating Gemini models into applications that expect OpenAI's API format
- Self-hosting a proxy to use Google's free Gemini API quota
- Adding streaming AI responses to applications using Gemini models
- Building multimodal applications with text and image inputs via API
- Deploying an AI API proxy on Hugging Face Spaces or Docker containers
- Creating a unified API layer for tools that work with both OpenAI and Gemini models
Not Ideal For
- Production systems needing high-throughput, low-latency AI inference without proxy overhead
- Teams using multiple AI providers beyond Google's Gemini models
- Applications requiring advanced API management features like built-in rate limiting or detailed analytics
Pros & Cons
Pros
Acts as a drop-in replacement for OpenAI's chat completions API, enabling seamless integration with existing tools and libraries, as shown in the Python example using the openai client.
Proxies all Gemini API endpoints, allowing use of advanced features like thinking controls and Google Search grounding through model variants like '-search' and '-maxthinking'.
Supports real-time streaming responses and handles text and image inputs, leveraging Gemini's capabilities for interactive and vision-based applications.
Containerized with Docker and configured for Hugging Face Spaces, simplifying setup and scaling across different hosting environments.
Cons
Requires managing Google OAuth credentials or API keys, which adds initial configuration overhead compared to simpler authentication methods and can be error-prone.
Tied exclusively to Google's Gemini models, limiting flexibility if you need to switch to or incorporate other AI providers like OpenAI or Anthropic.
Adds an extra network hop as a proxy layer, which can increase latency and become a bottleneck in high-demand scenarios without built-in clustering or load balancing.
Frequently Asked Questions
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