mazzasaverio/fastapi-langchain-rag
(Let's start with a) Scalable question-answering system utilizing FastAPI, LangChain (LCEL), and PGVector, featuring an ingestion pipeline. Deployed on GCP Cloud Run via Terraform.
This project helps developers quickly set up a scalable question-answering system using their own documents. You put PDF files in a folder, and the system processes them, allowing users to ask questions and get answers through an API. This is for backend developers or ML engineers who need to deploy a custom RAG solution.
No commits in the last 6 months.
Use this if you are a developer looking for a pre-configured, serverless architecture to deploy a RAG-based Q&A system from PDF documents.
Not ideal if you are an end-user looking for a ready-to-use Q&A application without any coding or infrastructure setup.
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Language
Python
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Last pushed
Apr 14, 2024
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