Quick Start Guide
Get up and running with ragleaf in minutes. Follow these simple steps to integrate our RAG quality helper into your existing pipeline.
Installation
Install ragleaf using your preferred package manager:
pip install ragleaf
Or using npm for JavaScript projects:
npm install ragleaf
Basic Usage
Here's a simple example to get you started with Python:
from ragleaf import RAGQualityChecker
# Initialize the checker with your API key
checker = RAGQualityChecker(api_key="your_api_key")
# Verify citations in your RAG response
result = checker.verify_citations(
query="What is machine learning?",
response="Machine learning is...",
sources=[doc1, doc2, doc3]
)
print(result.accuracy_score)
Configuration
Configure ragleaf with your specific requirements:
checker = RAGQualityChecker(
api_key="your_api_key",
threshold=0.85,
enable_visualization=True
)
Next Steps
Now that you have ragleaf installed, explore these resources:
- API Reference - Complete documentation of all methods
- Tutorials - Step-by-step guides for common use cases
- SDK & Libraries - Language-specific SDKs
Need Help?
If you encounter any issues or have questions, reach out to us at support@ragleaf.dev or visit our contact page.