gemini-for-claude-code

🥈Silver

This Python program acts as a proxy, enabling Claude Code to interact with Google's Gemini models. It translates API requests and responses between the two systems. Use this to leverage Gemini's capabilities within Claude Code workflows.

336620Updated Today

Intermediate30min to implementautomation

Saves ~20 min per use

Quick InstallView Source

git clone https://github.com/coffeegrind123/gemini-for-claude-code.git

Works with:

Claude

Overview

About This Skill

The gemini-for-claude-code skill is an innovative Python program designed to integrate Claude Code with Google's Gemini models, facilitating seamless AI automation. This skill allows developers and AI practitioners to leverage the advanced capabilities of Gemini models, enhancing their workflow automation processes. By utilizing this skill, users can streamline their AI projects and improve efficiency in their development cycles. One of the key benefits of the gemini-for-claude-code skill is its ability to simplify complex tasks, allowing for quicker implementation of AI solutions. Although the exact time savings are currently unknown, the skill's intermediate complexity and 30-minute implementation time suggest that users can expect to significantly reduce the time spent on integrating AI models into their applications. This efficiency is particularly valuable for product managers and developers who are looking to optimize their workflows and deliver products faster. This skill is particularly suited for developers and AI practitioners who are focused on creating sophisticated AI applications. It can be utilized in various scenarios, such as enhancing data processing capabilities, automating machine learning workflows, or even developing intelligent chatbots that utilize Gemini's advanced natural language processing features. For example, a developer could use this skill to automate the data ingestion process for a machine learning model, allowing them to focus on model tuning and performance optimization instead. With an intermediate difficulty level, users should have a solid understanding of Python programming and AI concepts to effectively implement this skill. As businesses increasingly adopt AI-first workflows, integrating tools like gemini-for-claude-code can significantly enhance productivity and innovation. By adopting this skill, organizations can ensure they remain competitive in the rapidly evolving AI landscape.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/coffeegrind123/gemini-for-claude-code

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

I want to use this Python program to integrate Claude Code with Google's Gemini models. Here's my setup: [SETUP DETAILS]. What are the key steps to get started? Also, can you explain how to handle [SPECIFIC CHALLENGE]?

Example Output

# Integration Guide: Claude Code with Google's Gemini Models

## Step 1: Setup Environment
- Install required packages:
  ```bash
  pip install google-cloud-aiplatform anthropic
  ```
- Set up Google Cloud credentials:
  ```python
  from google.cloud import aiplatform
  aiplatform.init(project='your-project-id', location='us-central1')
  ```

## Step 2: Configure Claude Code
- Initialize Claude Code client:
  ```python
  from anthropic import Anthropic
  client = Anthropic(api_key='your-api-key')
  ```

## Step 3: Handle Rate Limits
- Implement exponential backoff for API calls:
  ```python
  import time
  from tenacity import retry, stop_after_attempt, wait_exponential
  
  @retry(stop=stop_after_attempt(3), wait=wait_exponential(multiplier=1, min=4, max=10))
  def call_gemini_api(prompt):
      # API call logic here
  ```