Developer builds RAGEval API for RAG system evaluation

The developer details the creation of RAGEval, a platform designed to evaluate and debug retrieval-augmented generation (RAG) systems. Facing issues with LLMs confidently providing incorrect information, the developer built a foundational API using FastAPI and LiteLLM to ensure reliable LLM calls, error handling, and real-time streaming responses. This robust foundation, developed over two days, supports multiple LLM providers and includes essential features like a health check and a streaming completion endpoint. AI

IMPACT Enables more robust evaluation and debugging of RAG systems, improving their reliability and performance.

RANK_REASON The item describes the development of a specific tool (RAGEval) for evaluating RAG systems, detailing the technical implementation and dependencies.

Read on dev.to — LLM tag →

• FastAPI
• GitHub
• Groq
• httpx
• LiteLLM
• OpenAI
• pydantic
• pytest
• pytest-asyncio
• python-dotenv
• RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework
• retrieval-augmented generation
• uvicorn

• product
• infra

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