💬 MaxKB is an open-source AI assistant for enterprise. It seamlessly integrates RAG pipelines, supports robust workflows, and provides MCP tool-use capabilities.
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Updated
Jun 26, 2025 - Python
💬 MaxKB is an open-source AI assistant for enterprise. It seamlessly integrates RAG pipelines, supports robust workflows, and provides MCP tool-use capabilities.
🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL
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.
Opinionated sample on how to build/deploy a RAG web app on AWS powered by Amazon Bedrock and PGVector (on Amazon RDS)
Prototype app enabling job description search using natural language description of a job seeker.
Pip-installable, embedded-like postgres server for your python app
An intellligent AI assistant that can do anything!
Extensible API and framework to build your Retrieval Augmented Generation (RAG) and Information Extraction (IE) applications with LLMs
An application that enable the users to upload PDF files and ask questions regarding their content using Retrieval Augmented Generation (RAG)
Knowledge base Q&A program using LangChain for retrieval-augmented prompting and PGVector as vector store.
Question Answering application with Large Language Models (LLMs) and Amazon Postgresql using pgvector
Integrates Supabase with Crawl4AI and AI Chat to create a powerful web crawling and semantic search solution. Streamlit supabase data visualization. Run all in Docker. API and more!
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