Angular2Guy/AIDocumentLibraryChat
A project to show howto use SpringAI with OpenAI to chat with the documents in a library. Documents are stored in a normal/vector database. The AI is used to create embeddings from documents that are stored in the vector database. The vector database is used to query for the nearest document. That document is used by the AI to generate the answer.
Extends RAG capabilities beyond document search to include image similarity queries using local LLava embeddings, SQL generation from natural language with table/column metadata embeddings, and MCP protocol integration for decoupled tool services. Built on Spring Boot with PostgreSQL vector extensions (pgvector) and supports both OpenAI and local Ollama models, enabling offline inference with GPU acceleration when available. Frontend uses Angular Material with dynamic table rendering for multi-modal search results and generated SQL query outputs.
Stars
32
Forks
14
Language
Java
License
Apache-2.0
Category
Last pushed
Dec 28, 2025
Commits (30d)
0
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