gemini-rotate 0.1.1

A lightweight Python library for Google Gemini API key rotation and model fallback.

Gemini Rotate

A lightweight Async Python library for Google Gemini API key rotation, valid model selection, and automatic fallback to "Lite" models on server errors.

🚀 Features

• ✅ Automatic Key Rotation: Seamlessly rotates through a list of API keys when quota is exhausted (429), permission denied (403), or any other API error occurs.
• 🔄 Smart Model Fallback: Automatically downgrades specific models (e.g., gemini-2.0-flash -> gemini-2.0-flash-lite) if server errors (5xx) persist.
• ⚡ Async First: Built on top of the google-genai async client for high-performance non-blocking applications.
• 🛡️ Robust Error Handling: Implements exponential backoff before rotating keys or switching models.
• 📝 Concise Logging: Logs only essential success/failure information (e.g., 400 INVALID_ARGUMENT) to keep your console clean.

📦 Installation

pip install gemini-rotate

⚡ Quick Start

1. Configure Environment: Create a .env file.

   GEMINI_API_KEY_1="AIzaSy..."
   GEMINI_API_KEY_2="AI3yhj..."
   GEMINI_API_KEY_3="AIdf56..."
   

2. Run Code:

   import asyncio
   from gemini_rotate import GeminiRotationClient
   
   async def main():
       client = GeminiRotationClient()
       response = await client.generate_content("Hello, Gemini!")
       print(response.text)
   
   asyncio.run(main())
   

📖 Usage Guide

Initialization

The client automatically loads API keys from your environment variables (GEMINI_API_KEY_1, GEMINI_API_KEY_2, etc.).

client = GeminiRotationClient()

Generating Content

The generate_content method wraps the standard google-genai call but adds rotation and fallback logic.

1. Basic Text Generation

import asyncio
from gemini_rotate import GeminiRotationClient
from dotenv import load_dotenv

load_dotenv()

async def generate_text():
    client = GeminiRotationClient()
    try:
        response = await client.generate_content(
            contents="Explain quantum computing in 50 words."
        )
        print(f"Generated text: {response.text}")
    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    asyncio.run(generate_text())

2. Advanced: Tool Calling & Structured Output

You can pass tools and response_schema (or response_mime_type) via the config parameter.

import asyncio
from google import genai
from gemini_rotate import GeminiRotationClient
from pydantic import BaseModel
from dotenv import load_dotenv

load_dotenv()

# Define a schema for structured output
class Recipe(BaseModel):
    title: str
    ingredients: list[str]
    instructions: list[str]

async def generate_recipe():
    client = GeminiRotationClient()

    try:
        response = await client.generate_content(
            contents="Give me a recipe for chocolate cake.",
            config={
                "response_mime_type": "application/json",
                "response_schema": Recipe,
            }
        )
        
        # Parse result directly into Pydantic model
        recipe = response.parsed
        print(f"Title: {recipe.title}")
        print(f"Ingredients: {recipe.ingredients}")
        
    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    asyncio.run(generate_recipe())

Parameters

Parameter	Type	Description
contents	str | list	The prompt or content to send.
model	str	(Optional) The specific model to use. Defaults to first in priority list.
config	dict	(Optional) Generation config (temperature, tools, schema) passed to google.genai.

⚙️ Configuration

1. API Keys (Required)

Define your keys in .env or environment variables using the pattern GEMINI_API_KEY_n.

GEMINI_API_KEY_1="key_one..."
GEMINI_API_KEY_2="key_two..."
GEMINI_API_KEY_3="key_three..."

(Note: A single GEMINI_API_KEY is also supported, but using the numbered pattern allows for rotation.)

2. Model Priority (Optional)

You can customize the order in which models are attempted by setting GEMINI_MODELS in .env. The library processes models in Primary -> Secondary pairs.

Default Behavior (if not set):

1. gemini-flash-latest -> gemini-flash-lite-latest
2. gemini-3-flash-preview -> gemini-2.5-flash
3. gemini-2.5-flash-lite -> gemini-2.0-flash
4. gemini-2.0-flash-lite -> (None)

Custom Configuration:

GEMINI_MODELS='["gemini-2.5-flash", "gemini-2.5-flash-lite", "gemini-2.0-flash"]'

🔍 How it Works

graph TD
    Start[Start Request] --> LoopPairs{Loop Model Pairs}
    LoopPairs -->|Primary, Secondary| LoopClients{Loop API Clients}
    
    LoopClients -->|Next Client| AttemptPrimary[Attempt Primary Model]
    
    AttemptPrimary -->|Success| ReturnResponse[Return Response]
    AttemptPrimary -->|Failure| CheckSecondary{Has Secondary Model?}
    
    CheckSecondary -->|Yes| AttemptSecondary[Attempt Secondary Model]
    CheckSecondary -->|No| NextClient[Next Client]
    
    AttemptSecondary -->|Success| ReturnResponse
    AttemptSecondary -->|Failure| NextClient
    
    NextClient -->|Clients Exhausted| NextPair[Next Pair]
    NextPair -->|Pairs Exhausted| RaiseError[Raise AllClientsFailed]
    
    style Start fill:#f9f,stroke:#333,stroke-width:2px
    style ReturnResponse fill:#9f9,stroke:#333,stroke-width:2px
    style RaiseError fill:#f99,stroke:#333,stroke-width:2px

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.