Spring AI RAG with PGVector and Ollama Integration#70
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smadil997 wants to merge 1 commit intospring-projects:mainfrom
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Spring AI RAG with PGVector and Ollama Integration#70smadil997 wants to merge 1 commit intospring-projects:mainfrom
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Signed-off-by: Mohdadil alisnagina@gmail.com
Signed-off-by: adil <alisnagina@gmail.com>
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Hi @tzolov please have look on this? |
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This PR introduces a complete example of a Retrieval-Augmented Generation (RAG) pipeline using:
Spring AI
PGVector (running via Docker)
Ollama for embedding and chat models
Instead of installing a local PGVector DB manually, this setup runs it using Docker Compose (compose.yaml). Please ensure the database is running before starting the Spring Boot application.
⚙️ Key Features
Uses Ollama locally for LLM (gemma:3b) and embedding (nomic-embed-text:latest) models
PDF file upload endpoint at POST /upload for document ingestion
Validates PDFs for table of contents (TOC) – required by default reader
Embeds paragraphs from the PDF and stores them in a vector store using PGVector
Auto-creates vector_store table if not specified
Uses initialize-schema: true in application.yaml to recreate the schema on every app run (can be customized)