timescale/private-rag-example
Private RAG app sample using Llama3, Ollama and PostgreSQL
Implements vector embeddings and semantic search within PostgreSQL using pgai and pgvector extensions, enabling efficient document retrieval without external embedding services. The pipeline orchestrates local LLM inference through Ollama, document chunking, and vector storage entirely within a containerized environment. Supports swappable models (Llama3.2, Mistral) and includes pgai for in-database AI operations, eliminating dependency on cloud-based RAG platforms.
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Nov 06, 2024
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