🔥 MaxKB is an open-source platform for building enterprise-grade agents. 强大易用的开源企业级智能体平台。

🥤 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.

This is the public release of MIRA OS. Discrete memories decay through momentum loss, tools auto-configure when dropped into tools/ folder, and the system prompt composes from modular trinkets. I would like to think I've made an elegant brain-in-box. You load it and send cURL requests - it talks back, learns, and uses tools. Contributions welcome.

Code from tutorials presented on the "Code AI with Rok" YouTube channel

Postgres/pgvector Python Client

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)

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

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

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

An intellligent AI assistant that can do anything!

🧹 An automizable or interactive pruning tool for Open WebUI: clean up orphaned files, old chats, inactive users, stale vector data and more!

MCP-enabled AI conversation engine with MCTS analysis, FastAPI backend, and async operations for building advanced LLM applications

(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

Hierarchical RAG architecture scaling to 693K chunks on consumer hardware (4GB VRAM). Features 3-address routing, hybrid vector+graph fusion, and SetFit classification.

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!