ChatWeb can crawl web pages, read PDF, DOCX, TXT, and extract the main content, then answer your questions based on the content, or summarize the key points.

ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector

A RAG app to ask questions about rows in a database table. Deployable on Azure Container Apps with PostgreSQL Flexible Server.

A web UI Project In order to learn the large language model. This project includes features such as chat, quantization, fine-tuning, prompt engineering templates, and multimodality.

Postgres/pgvector Python Client

Prototype app enabling job description search using natural language description of a job seeker.

Opinionated sample on how to build/deploy a RAG web app on AWS powered by Amazon Bedrock and PGVector (on Amazon RDS)

An intellligent AI assistant that can do anything!

Pip-installable, embedded-like postgres server for your python app

Learning journey to develop a scalable and modular backend to manage your data and solve your problems

(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.

Extensible API and framework to build your Retrieval Augmented Generation (RAG) and Information Extraction (IE) applications with LLMs

Knowledge base Q&A program using LangChain for retrieval-augmented prompting and PGVector as vector store.

🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with PostgreSQL or SQLite

pgvector + embeddings API

An application that enable the users to upload PDF files and ask questions regarding their content using Retrieval Augmented Generation (RAG)

Examples of vector DB indexing and query with various vector databases.

Question Answering application with Large Language Models (LLMs) and Amazon Aurora Postgresql using pgvector

Question Answering application with Large Language Models (LLMs) and Amazon Postgresql using pgvector

Code Labyrinth is a tool for using LLM chatbots in coding workflows. It uses Langchain and PGVector to provide context about the working codebase and relevant libraries.