WeKnora

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1. Oct 31
   Agentic RAG Struggles to Find All Evidence for a Topic

   The ai-study-helper-v2 project tested prompts, query expansion, corpus-grounded facets, auditing, reranking, and section routing for exhaustive topic coverage in Agentic RAG. Adding more tools, turns, and queries did not reliably reveal every semantic facet, while a term-by-term full-text search recovered all three regression probes but retrieved 511 of 526 blocks. The project is therefore preserving block retrieval and moving toward precompiled, source-traceable LLM Wiki evidence maps as a possible way to organize and complete topic coverage.

   掘金 · 人工智能 · 🔥 0

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WeKnora: An open-source, LLM-powered knowledge framework for enterprise document understanding, semantic retrieval and reasoning.

What problem it solves Teams need to bring documents together so they can be searched, reasoned over and kept up to date. They also need a way to move from source-grounded retrieval to multi-step tasks while maintaining organized, current knowledge. Key features Three knowledge workflows — RAG supports lookup, an agent handles multi-step tasks, and a wiki organizes knowledge. All three operate on …

github.comhttps://github.com/Tencent/WeKnora