Evaluation is the key to building robust Retrieval-Augmented Generation (RAG) systems. Leveraging Dria’s Persona Pipeline alongside custom workflows, this approach offers a comprehensive method to assess AI agents using context-specific data and diverse personas.
###The Process
This workflow demonstrates how to evaluate your RAG pipeline by combining persona-driven question generation, contextual data scraping, and performance evaluation across multiple models. Here’s how it works:
- Generate Personas with Dria’s Persona Pipeline: Start by creating detailed personas tailored to your evaluation needs. These personas define the tone, focus, and perspective of the questions to be generated.
- Scrape Contextual Data: Use tools like Firecrawl to scrape relevant content from specific URLs or entire domains. This data serves as the foundation for generating nuanced, contextually rich questions.
- Generate Questions: Combine the generated personas with the scraped context to create targeted and diverse questions. These questions are crafted to evaluate the RAG pipeline’s ability to retrieve and reason effectively.
- Generate Answers: Use AI models to produce answers for the generated questions. These responses simulate real-world scenarios, offering insights into the performance of different RAG configurations.
- Evaluate Performance:
Assess the generated answers using Promptfoo across multiple RAG configurations:
- Simple RAG
- RAG with Jina Reranker
- RAG with Cohere Reranker
###Why It Matters
This approach ensures a robust evaluation by testing multiple dimensions of your RAG system: • Contextual Relevance: Ensures the system retrieves and generates accurate, context-aware responses. • Model Comparison: Highlights strengths and weaknesses across different RAG configurations. • Scalable Evaluation: Allows for iterative testing and refinement at scale.
###Get Started
Whether you’re a seasoned developer or just getting started, Dria’s tools make RAG evaluation accessible, efficient, and impactful. https://github.com/sertacafsari/dria-cookbook