RAG Documentation Search
Enables semantic search through documentation using vector embeddings, allowing AI assistants to retrieve and cite relevant documentation context for user queries.
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What it does
- Search documentation using semantic vector embeddings
- Retrieve relevant context from multiple documentation sources
- Generate embeddings locally with Ollama or via OpenAI
- Process and index documentation automatically
- Augment AI responses with cited documentation sources
Best for
Building documentation-aware AI assistantsDevelopers needing context-aware toolingTeams wanting to search knowledge bases semantically
Local embeddings with Ollama supportMultiple documentation sourcesReal-time context augmentation
