Sophora - AI Reasoning, Function-calling & Knowledge Retrieval

Stateful AI Agent for Knowledge Extraction

PromptWeaver: RAG Edition helps design effective prompts for Traditional, Hybrid, and Agentic RAG systems. It offers templates, system prompts, and best practices to improve accuracy, context use, and LLM reasoning.

Notebook examples for using OpenAI's Assistants API with the file search (knowledge retrieval) functionality.

A local Retrieval-Augmented Generation (RAG) system for answering questions about TouchDesigner using wiki pages, tutorials, and other structured or semi-structured content. Powered by FAISS and local LLMs via Ollama.

Code to make any AI have unlimited context persistent memory. In the example, a software for any AI to read the Uniform Commercial Code of Michigan. A document of 220,000 tokens

⚡️ Local RAG API using FastAPI + LangChain + Ollama | Upload PDFs, DOCX, CSVs, XLSX and ask questions using your own documents — fully offline!

Advanced multi-agent Medical AI Assistant powered by LangGraph that delivers empathetic, doctor-like responses using a hybrid pipeline of LLM reasoning, RAG from medical PDFs, and intelligent fallback tools. Features Long-term memory with SQLite, dynamic tool routing, and state reasoning for reliable, context-aware consultation.

OllamaMulti-RAG 🚀 is a multimodal AI chat app combining Whisper AI for audio, LLaVA for images, and Chroma DB for PDFs, enhanced with Ollama and OpenAI API. 📄 Built for AI enthusiasts, it welcomes contributions—features, bug fixes, or optimizations—to advance practical multimodal AI research and development collaboratively.

Scientific Agent: A Retrieval-Augmented Generation (RAG) System for Domain-Aware Literature Review Automation

QueryVault is a robust RAG system for structured Q&A data. It ingests JSON files, embeds content via ChromaDB, and serves context-aware answers using FastAPI and Google Gemini. With a modular design and CLI tools, it's built for scalable, secure AI-powered knowledge retrieval.

Local Retrieval-Augmented Generation (RAG) system built with FastAPI, integrating vector search, Elasticsearch, and optional web search to power LLM-based intelligent question answering using models like Mistral or GPT-4.

An end-to-end multi-source knowledge retrieval system using LangChain, FAISS, and OpenAI embeddings. This Retrieval-Augmented Generation (RAG) pipeline intelligently searches across Wikipedia, arXiv, and custom websites, optimizing source selection and delivering precise, real-time results based on query relevance.

🚀 Revolutionize your data interaction with a cutting-edge chatbot built on Retrieval-Augmented Generation (RAG) and OpenAI’s GPT-4. Upload documents, create custom knowledge bases, and get precise, contextual answers. Ideal for research, business operations, customer support, and more!

AI-powered support copilot for ticket classification and query resolution. RAG, Chroma DB, Streamlit. Atlan AI Engineer Internship.

CareConnect uses state-of-the-art large language models (LLMs) to provide rapid, reliable medical guidance. This project addresses increasing wait times and health misinformation, offering timely assistance and supporting informed decision-making to alleviate the burden on the healthcare system.

A Streamlit-based application that leverages Retrieval Augmented Generation (RAG) to provide accurate answers from Wikipedia content.

🤖 RAG-based chatbot for answering queries from 📄 customer support PDFs using 🧠 LLMs, 🔍 OCR, and 📚 FAISS vector search.