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opea-project
[Feature] Empower ChatQnA UI with Explainable RAG Insights
Priority
P2-High
OS type
Ubuntu
Hardware type
Gaudi2
Running nodes
Single Node
Description
This feature aims to enhance the ChatQnA user interface by providing a fully explainable view of the Retrieval-Augmented Generation (RAG) process. It will enable users to visualize and understand key steps, including embedding generation, retrieval results, reranking, and LLM outputs, all within a cohesive and user-friendly interface.
Key Objectives:
Transparency: Display detailed information about each stage of the RAG pipeline, including intermediate results, scores, and parameters. Customizability: Allow users to configure parameters for embedding, retrieval, and reranking processes, enabling fine-tuned performance. Real-time Feedback: Provide real-time insights into how inputs and configurations impact the final LLM-generated response.
Core Features:
Embedding Visualization: Show embeddings generated for user queries, including vector representations and dimensionality details. Retrieval Insights: List retrieved documents or knowledge chunks, their similarity scores, and metadata. Reranking Analysis: Display the reranked order of results with detailed scoring and filtering logic. LLM Output Breakdown: Provide a clear view of how the LLM constructs responses using retrieved and reranked data. Parameter Configuration: Offer an intuitive interface to adjust RAG-related parameters such as similarity thresholds, maximum retrieval results, reranking weights, etc.
Benefits:
Improves the explainability of AI-driven responses, increasing user trust and adoption. Empowers technical users to diagnose and optimize the RAG workflow for various use cases. Facilitates better decision-making for tuning and deploying ChatQnA in real-world scenarios. This feature will transform the ChatQnA UI into a powerful and transparent tool for leveraging the potential of Retrieval-Augmented Generation while maintaining user control and trust.
Hi @WenjiaoYue please help to consider the feature when new release plan, thank you! [Remind]
