feat(agent): add Docs RAG Agent for documentation Q&A #12
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- Add docs-rag-agent using createVectorQueryTool from @mastra/rag - Add ingestion script to clone runpod/docs and generate embeddings - Use LibSQL vector store with network volume support for persistence - Add @mastra/rag, ai, simple-git, tiktoken dependencies - Update README with RAG agent documentation and setup instructions - Vector DB auto-detects /runpod-volume for persistent storage Closes CSE-787
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Summary
Adds a RAG (Retrieval Augmented Generation) agent that answers questions about Runpod documentation using semantic search over vector embeddings.
Changes
docs-rag-agent.tsusingcreateVectorQueryToolfrom@mastra/ragscripts/ingest-docs.tsclones runpod/docs, chunks markdown, generates embeddings@mastra/rag,ai,simple-git,tiktokenHow It Works
OPENAI_API_KEY=xxx npx tsx scripts/ingest-docs.tsPersistence
/runpod-volume/vector.dbTesting
Tested locally with Docker - agent successfully answers questions about serverless, pods, network volumes, and handlers.
Closes CSE-787