AI Q&A (QRAG)
QRAG stands for Question Retrieval Augmented Generation. Focus on Foundations indexes questions and answers extracted from interviews, meetings, and books in a vector database. Semantic search finds relevant Q&A by meaning, rather than only by matching keywords, and returns quoted source passages with source links. The qrag-search skill retrieves those passages without generating an AI answer. The qrag-ask skill and web chat also give the retrieved passages to an AI model to synthesize an answer, with the direct quotes available for checking. Browse Transcripts to read the source material. An AI answer is a synthesis, not a verbatim statement by the original speaker. QRAG is open source. Point an AI agent to the public repository to ask questions about how it works, with explanations tailored to your background and interests.https://github.com/randalljam/fof-mono-public
Ask questions across the David Deutsch interview corpus, with quoted answers grounded in the sources.
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