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contextual-retrieval

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Six RAG approaches — vanilla, hybrid, contextual, graph, agentic, and n8n-adaptive — served as OpenAI-compatible endpoints selectable from the Open WebUI model picker on a fully-local Atlas stack, with a reproducible LLM judge-panel harness that measures which approach wins on which kind of question.

  • Updated Jul 8, 2026
  • Python

Slack Q&A bot template — ingests Slack threads + markdown docs into Pinecone, then an n8n workflow retrieves, re-ranks on metadata, and posts answers back in-thread. Includes contextual retrieval and an eval harness.

  • Updated Jun 9, 2026
  • Python

Rigorous evaluation of contextual retrieval techniques on FinanceBench: comparing 5 embedders × 4 chunking strategies with bootstrapped confidence intervals on FinMTEB and FinanceBench.

  • Updated May 12, 2026
  • Jupyter Notebook

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