README.md

RAGnarok

RAGnarok: Unleash the power of truth in your Retrieval-Augmented Generation systems!

RAGnarok

RAGnarok is an open-source framework for verifying and enhancing the accuracy of Retrieval-Augmented Generation (RAG) systems. It uses advanced NLP techniques and efficient similarity search to provide comprehensive assessments of RAG-generated responses.

Features

• Semantic similarity checking using FAISS HNSW for efficient vector search
• Accuracy assessment combining keyword matching and semantic similarity
• Consistency checking against retrieved documents
• Relevance assessment to the original question
• Issue identification for potential problems in responses
• Overall scoring system for quick quality assessment

Installation

pip install ragnarok

Note: RAGnarok requires Python 3.7+.

Dependencies

RAGnarok depends on the following libraries:

• sentence-transformers
• faiss-cpu (or faiss-gpu for GPU support)
• numpy

You can install these dependencies using:

pip install sentence-transformers faiss-cpu numpy

Usage

Here's a basic example of how to use RAGnarok:

from ragnarok import RAGnarok

checker = RAGnarok()
result = checker.verify(rag_response, context)
print(f"Overall Score: {result.overall_score:.2f}")

Configuration

RAGnarok can be configured by passing a configuration dictionary when initializing:

from ragnarok import RAGnarok

checker = RAGnarok()
rag_response = "The capital of France is Paris. It is known for the Eiffel Tower."
context = {
    "question": "What is the capital of France?",
    "retrieved_docs": [
        "Paris is the capital and most populous city of France.",
        "France is a country in Western Europe with several overseas regions and territories.",
        "The Eiffel Tower is a wrought-iron lattice tower on the Champ de Mars in Paris."
    ]
}

result = checker.verify(rag_response, context)

print(f"Overall Score: {result.overall_score:.2f}")
print(f"Accuracy Score: {result.accuracy_score:.2f}")
print(f"Consistency Score: {result.consistency_score:.2f}")
print(f"Relevance Score: {result.relevance_score:.2f}")
print(f"Semantic Similarity Score: {result.semantic_similarity_score:.2f}")
print(f"Confidence Score: {result.confidence_score:.2f}")
print(f"Issues Found: {result.issues}")

Contributing

We welcome contributions! Please see our Contributing Guide for more details.

License

RAGnarok is released under the MIT License. See the LICENSE file for more details.

Citation

If you use RAGnarok in your research, please cite:

@software{ragnarok,
  title = {RAGnarok: A Framework for Verifying Retrieval-Augmented Generation},
  author = {Your Name},
  year = {2024},
  url = {https://github.com/yourusername/ragnarok}
}

Contact

For any questions or feedback, please open an issue on GitHub or contact KnightOwl.