chromedb

Production-grade RAG system enforcing source grounding, page-level citations, and zero-hallucination document intelligence using FastAPI, ChromaDB, and Groq.

🧳 智能旅行规划 Agent | LangGraph 编排 + FastAPI + Vue3 | MCP 多工具自主调用 | ChromaDB RAG 知识库 | 用户长期记忆 | Redis 分布式会话 | LangFuse 全链路追踪 | 自我反思质检 | CI/CD 自动化 | 支持流式 SSE 与多方案对比

Personal AI with persistent memory. Turns any LLM into an entity that remembers who you are, learns from your conversations, and grows over time. Local, private, yours.

Sovereign-RAG is a Private Local Intelligence Engine. It allows you to talk to your PDF documents without ever sending that data to the internet. It uses Retrieval-Augmented Generation (RAG), which means the AI "reads" your specific files to give accurate answers instead of guessing.

Enterprise Hybrid RAG system over RBI and SEBI financial regulations combining ChromaDB dense search with BM25, cross-encoder reranking, and quantitative Ragas evaluation.

Local-first Agentic RAG copilot with hybrid retrieval, cross-encoder reranking, page-aware citations, deterministic guardrails, and multi-agent self-correction.

RAG-based Question Answering system using LangChain, Groq LLM, and ChromaDB that processes PDFs and retrieves context-aware answers with source references.

I understood in practical way and tried to explain same.

An autonomous AI trading agent that uses a multi-agent LLM debate to produce BUY/SELL/HOLD decisions, then executes them as options trades on Alpaca's paper market. Runs on local Qwen — no cloud API keys required for the reasoning layer.

Offline-first, multilingual clinical AI for Community Health Workers in Africa — Gemma 4 + RAG over WHO & MSF guidelines

A local RAG app that answers questions about your documents using ChromaDB, Sentence Transformers, and a Gemma GGUF model no external APIs. Built with Python and Streamlit.

Production-grade RAG assistant for technical notes using Hybrid Search (BM25 + ChromaDB Vectors), Reciprocal Rank Fusion (RRF), Cross-Encoder Re-Ranking, and a Streamlit UI with citation grounding.

Production RAG system using LangChain, ChromaDB, and GPT-3.5

An AI-powered coding mentor built with Django, React, LangGraph, and Gemini. Provides intelligent coding assistance, debugging support, and context-aware responses through an agentic AI workflow.

TN Scheme Navigator AI is a citizen-friendly Streamlit app for finding and verifying Tamil Nadu Government schemes. It combines ChromaDB Vector RAG, NetworkX, optional Neo4j Graph RAG, and OpenAI to deliver accurate answers in Tamil, English, or bilingual format.

AI-powered RAG document assistant for PDF & Markdown Q&A with source citations, persistent conversations, and document-grounded answers. #Next.js #FastAPI #LangChain #ChromaDB #embeddings #Ollama #citation-aware PDF/Markdown Q&A.

A minimal, fully local Retrieval-Augmented Generation pipeline built from scratch. Covers document chunking, embedding with sentence-transformers, vector storage via ChromaDB, and LLM generation through Ollama.

A multilingual and multimodal Retrieval-Augmented Generation (RAG) system that enables organizations to query internal documents using AI while keeping data secure. The system processes text, tables, and images from documents and generates grounded answers with citations using modern LLMs.

A cost-efficient RAG app using ChromeDB and local LLMs

Agentic trend analysis system for app reviews using local vector embeddings and semantic deduplication.