A robust wrapper for LiteLLM with retry logic and rate limiting
Project description
LiteLLM Retry Wrapper
A robust Python wrapper for LiteLLM that provides retry mechanisms, rate limiting, and error handling for LLM API calls.
Features
- 🔄 Automatic retry mechanism with exponential backoff
- ⏱️ Built-in rate limiting
- 🎯 Configurable parameters for retries and rate limits
- 📝 Comprehensive logging
- 🛡️ Error handling and exception management
- 🔧 Easy to customize and extend
Installation
uv pip install litellm-retry-wrapper
Quick Start
from call_litellm_with_retry import LiteLLMCaller
# Initialize the caller
llm_caller = LiteLLMCaller(
model_name="gemini/gemini-2.0-flash",
rpm=2000,
max_retries=3
)
# Prepare your messages
messages = [
{
"role": "user",
"content": "Write a short poem about artificial intelligence."
}
]
# Make the API call
response = llm_caller.complete(
messages=messages,
temperature=0.7,
max_tokens=100
)
print(response.choices[0].message.content)
Configuration
The LiteLLMCaller class accepts the following parameters:
model_name: The name of the LLM model to use (default: "gemini/gemini-2.0-flash")rpm: Rate limit in requests per minute (default: 2000)max_retries: Maximum number of retry attempts (default: 3)min_retry_wait: Minimum wait time between retries in seconds (default: 4)max_retry_wait: Maximum wait time between retries in seconds (default: 10)
Environment Variables
Create a .env file with your API keys:
GEMINI_API_KEY=your_api_key_here
Development
To set up the development environment:
# Clone the repository
git clone https://github.com/sanjeed5/litellm-retry-wrapper.git
cd litellm-retry-wrapper
# Install dependencies
uv venv
source .venv/bin/activate
uv sync
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
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