puerari/ingestion_and_semantic_search_with_langchain_and_postgresql
This project is the implementation of a technical challenge from the MBA in Software Engineering with AI at FullCycle College. It consists of a RAG (Retrieval‑Augmented Generation) system using LangChain, PostgreSQL with pgvector for vector storage, and Google Gemini or OpenAI GPT for embeddings and answer generation.
Stars
—
Forks
—
Language
Python
License
—
Category
Last pushed
Mar 06, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/puerari/ingestion_and_semantic_search_with_langchain_and_postgresql"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Bbs1412/rag-with-gemma3
This project is a modular Retrieval-Augmented Generation (RAG) system built with Google...
ImadSaddik/RAG_With_Gemini
Providing useful context by using Retrieval Augmented Generation (RAG) to Gemini
falconlee236/rag-from-scratch-with-gemini
This Repository is Google Gemini version of rag-from-scratch with langchain
spashx/abyss.site
website for abyss
ImadSaddik/DoCamp
RAG (Retrieval Augmented Generation) on Android