Recommend health check packages based on user information.

CDoc lets you chat with your documents using local LLMs, combining Ollama, ChromaDB, and LangChain for offline, secure, and efficient information extraction. Perfect for researchers, developers, and professionals seeking quick insights from their documents.

AI-powered LeetCode analytics platform — syncs your solving history and uses RAG (Gemini + ChromaDB) to answer personalized questions about your strengths, weaknesses, and growth areas. Built as a Turborepo monorepo with real-time SSE sync, BullMQ background jobs, and full observability (Prometheus/Loki/Grafana)

A fully local AI nursing assistant for elderly care institutions, supporting resident EHR management, medical record OCR, hybrid RAG retrieval, local LLM reasoning, nursing task cards, SBAR handover, and decision memory.

一款支持私有化部署的沉浸式 AI 角色扮演全栈系统。提供支持打包为移动端 App 的跨平台前端，支持多分支世界线剧情探索、多版本候选回复切换与好感度联动；集成智能情感配音（TTS）与动作过滤，兼容 SillyTavern 角色卡与独立世界书百科；具备长期向量记忆与图谱增强检索（RAG），可根据日常需要定制专属私密 AI 聊天。

一个支持多用户的知识图谱系统，整合 Neo4j 图数据库和 ChromaDB 向量数据库，实现文档知识管理、可视化检索和 RAG 智能问答。

This repository houses a collection of projects built using LangChain, focusing on Retrieval Augmented Generation (RAG) systems and AI chatbots. Explore various implementations, from basic RAG models to more sophisticated chatbot interactions.

Domain-specific AI research assistant with hybrid RAG (ChromaDB + BM25 + RRF), NLI-based hallucination detection, and multi-paper knowledge graph. 100% free, fully local — no API keys required.

Production-style RAG chatbot with PDF Q&A, built with Groq LLM and ChromaDB

Smart Decision Support Assistant for KOBIS (Kocaeli Bicycle System) built with RAG architecture. Powered by Llama-3.3, LangChain, and ChromaDB for data-driven insights. 🚲🤖

A Retrieval-Augmented Generation (RAG) application that enables users to upload PDF documents and ask questions about their content, powered by locally-run AI models.

Multimodal RAG-based AI consultant tool that processes videos end-to-end audio transcription, keyframe extraction, OCR, and visual analysis, then answers questions strictly from video content with source citations and timestamps. Built with Groq, ChromaDB, sentence-transformers, and Streamlit.

using ollama, langchain, and chromadb

30-day sprint from LLM basics to production AI systems — LangGraph multi-agent orchestration, RAG pipelines, HITL workflows, LangSmith observability, CrewAI, FastAPI deployment & SSE streaming. Built with Python, Gemini, ChromaDB.

A Retrieval Augmented Generation (RAG) application allowing users to upload PDF documents and ask questions about their content. Built with Python, Streamlit, LangChain, and Google Gemini AI models.

AI-powered research paper assistant using RAG, LangChain, and LLMs to extract insights from PDFs

RAG Q&A System with LangChain, OpenAI & Agents

AI-powered B2B cold email generator with automated lead sourcing, quality scoring, and batch processing.