Jupyter Notebook agents

🚀 Build a production-ready Agentic RAG system with LangGraph using minimal code and streamline your AI development process.

A ChatBot powered by OpenAI GPT-3.5 which can answer questions on E-commerce data

This repository contains various techniques for Retrieval-Augmented Generation (RAG) systems.

A practical guide to getting started with local 🤖 Large Language Models using Python, Ollama, & Streamlit. Includes basic chatbot setup, RAG-enabled PDF querying, & vectorstore visualization. Ideal for experimenting with LLMs on your own machine—no cloud req. 🦙

Extracting Product Insights from Unstructured text data using LLMs with LangChain

The LLM Dataset Generator is an open source tool for generating text data compatible with various language models supported by LangChain. You can customize it to meet your specific needs, making it a valuable resource for researchers, developers, and organizations working on NLP applications.

Automate complex business workflows with our Multi-AI-Agent Systems using crewAI. This framework leverages autonomous, role-specific AI agents to collaboratively perform multi-step tasks, enhancing efficiency and accuracy across various domains. Ideal for applications in resume tailoring, website design, research, customer support, and more.

Gemini Pro LLM and Pinecone Vector Database for fast and performant Retrieval Augmented Generation (RAG) with LlamaIndex

GROQ LPU Powered LLM chat engine

Techniques and workflows for building an LLM-powered RAG application using LlamaIndex.

【🔥🔥NLP-LLM-Agent🔥🔥】: projects, analysis, source code, model training and testing.

AI and Data Science Course

Agentic Framework examples for SAP Gen AI Hub via LiteLLM

Agentic Search Engine For Real-Time IoT Data

Labs for agentic AI — covering Azure AI Foundry, Foundry Agent Service, Microsoft Agent Framework, AI Agents, RAG, Azure AI Search, and Azure Container Apps(ACA)

This repository documents my hackathon solution, hands-on experiments, and technical notes from the IEEE YP Agentic AI Summit Dec 2025

Use LLM/AI agent for Web scraping (collection data) and analysis data with deep research

LLM App to demystify and summarize Terms and Conditions agreements

Implementation of "Building Agentic RAG with LlamaIndex" offered by DeepLearning.AI focusing on developing intelligent research agents using the Retrieval-Augmented Generation (RAG) framework.

A Retrieval-Augmented Generation (RAG) application for querying legal documents. It uses PostgreSQL, Elasticsearch, and LLM to provide summaries and suggestions based on user queries. Features data ingestion with Airflow, real-time monitoring with Grafana, and a Streamlit interface.

RAG pipeline with Agents for multiround conversation consistancy

This project is a Document Retrieval application that utilizes Retrieval-Augmented Generation (RAG) techniques to enable users to interact with uploaded PDF documents. By leveraging a Large Language Model (LLM), users can ask questions about the content of the documents and receive accurate answers based on the information retrieved.

A simple Docker based playground that brings together popular open source data and AI tools to help others get started with data lakehouse architecture and GenAI development on their local machines.

Loreer is wise AI assistance that has the vast knowledge of all lores, whether that is movie, series, game, or book related. Powered by LLMs and AI.

SAIRA Project, Generative Artificial Intelligence, Fall 2023, Innopolis University

Unlock the power of vector databases with the "Vector Databases: from Embeddings to Applications" course! A journey that will equip you with essential skills to leverage vector databases for various applications.

RAG/LLM-based movie recommendation system with

llm_works

An implementation of Retrieval-Augmented Generation (RAG) indexing using Rust and LanceDB. It leverages the power of Rust for efficient and safe performance, combined with LanceDB for advanced indexing capabilities.

AI-driven financial analyst system utilizing LangChain and Ollama for real-time stock analysis, market trends, and financial insights.

关于 LangChain 的深度学习与实践教程仓库，涵盖了从基础入门到高级 Agent 架构的多个阶段。本项目旨在通过实际的代码示例和 Notebook 教程，帮助开发者掌握 LangChain 生态系统的核心概念与最新特性。

Explore Functions, Tools and Agents with LangChain along with LangChain Expression Language

A collection of beginner to intermediate-level Data Science & Machine Learning projects using Python, Pandas, Scikit-learn, Tensorflow, and more.

Winning solution of Capital One Launchpad Hackathon 2025

Structured approach in AI and ML. Fundamentals and Advanced topics. RAG, Scoring & Profiling, LangChain & LangGraph, Certified Azure AI Engineer materials.

Sustainable Hydroponic domain-specific LLM developed to improve sustainable farming.

Intelligent Document Reranking RAG System

Demo building Restaurant Recommendation Chatbot based on Yelp Public Data

LLM / AI data science agent, using Anthropic's Claude and PANDAS

The goal of this projest is to present 3 different approaches for text classification (trained ML model, zer-shot transformer, RAG).

The repo underpins a codelab, demonstrating how to use Gemini File Search to enable RAG in your Agentic Application. Use the Gemini File Search to ingest and index documents without having to worry about the details of chunking, embedding or vector database.

🎓 AI-powered academic tutor using RAG to provide contextual answers from course textbooks across multiple subjects with intelligent query enhancement 🤖✨

AI-powered Smart Water Leak Detection system using Machine Learning and IoT sensor data. Includes a Streamlit dashboard for real-time leak prediction, geo-visualization, batch analysis, and AI-driven insights.

This repository features a collection of generative AI applications designed to showcase the capabilities of AI across various domains.

BENCHMARKS WITHOUT BORDERS

AI agents, trained by the minds that move the world.

Agentic AI for Cold-Chain Sustainability: LSTM-Based Predictive Logistics

MCP tool for cocktail recommendations using RAG (Retrieval-Augmented Generation).

A hands-on tutorial exploring six agent architecture patterns with the OpenAI Agents SDK, featuring Python examples, architecture diagrams, and notebooks for local Jupyter and Google Colab.

Teaching material of the HPI AI Service Centre for the RAG workshop series (RAG II and III): marimo notebooks on chunking, embeddings, retrieval metrics, document types, OCR and RAGAS evaluation

All-in-one repository of Production-ready tutorials on languages and frameworks with 40+ projects. Anyone can lookup on these and follow my roadmap to become a full-stack engineer.

Hands-on LangGraph tutorials: 6 agentic design patterns + Agentic RAG, with runnable notebooks and the official diagrams.

A Streamlit app for document question answering and text summarization.

Educational Tutor AI Assistant using Google's Gemini language model. The assistant will include features like generating quizzes, creating flashcards, providing grammar corrections, and offering project guidance.

🎓 RAG Agent: Intelligent University Policy Assistant

【WWW2024】The MMO Economist: AI Empowers Robust, Healthy, and Sustainable P2W MMO Economies

AI Agent for Real estate recommendation system

LangChain Documentation based practice

This repository provides a LangChain-powered chatbot for customer support, enabling businesses to deliver efficient and personalized support experiences to their customers. Leverage the power of natural language processing (NLP) to handle customer inquiries, resolve issues promptly, and enhance overall customer satisfaction.

Intelligent cooking companion that finds recipes based on your ingredients using advanced AI. Built for Google's Gen AI Intensive Course 2025Q1, showcasing 8 AI capabilities: LangGraph agents, RAG with ChromaDB, voice commands, nutrition API integration, Google Search grounding, and more.

A curated list of prediction market APIs, tools, datasets, and resources for developers and AI agents

AI Engineering Bootcamp

This repository is packed with practical, beginner-friendly codelabs that bring AI and coding concepts to life. From extracting job applicant details with OpenAI’s Function Calling (think resume parsing into JSON) to automating real-world tasks, you’ll find working code, sample datasets, and step-by-step guides here.

🤖 Build and explore powerful AI agents that solve real-world tasks using tools, memory, and reasoning within a collaborative hub.

Using LLMs to detect bias in news articles.

Using Pinecone, LangChain + OpenAI for Generative Q&A with Retrieval Augmented Generation (RAG).

Using FineTune Models for Document Q/A and Chatbots

This is a personalized chatbot that uses context from the whatsapp chat history to behave like a specific individual

Chat with AI

AI & RAG Based Personalized Writing Assistant

Build your own ESG chatbot

🚀Information Retrieval & Question Answering 🔥LLMs 🌐Streamlit

My first RAG question-answering app that answers questions based on files uploaded. The app has been deployed on streamlit

A playbook and Colab-based demo for helping engineering teams adopt Generative AI. Includes a working RAG pipeline using LangChain + Chroma, OpenAI GPT-4o embeddings, prompt engineering best practices, and automated LLM evaluations with Ragas.

🦜🔗 LangChain-Tutorials is an amazing GitHub repository that provides an array of friendly and interactive tutorials for LangChain enthusiasts. Scripts are coded in Python

Tutorials for LangChain

In this project I have built a RAG pipeline to showcase how we can augment LLM knowledge with additional data.

Optimizing a Retrieval-Augmented Generation (RAG) system on the CNN/Daily Mail dataset using LangChain, with performance benchmarking and analysis via RAGAS.

Learn about LangGraph’s components and how they enable the development, debugging, and maintenance of AI agents.

An accessible, reliable, and efficient platform for medical information and support using LLMs

Creating Knowledge Graphs and Productionalizing your RAG model with using Dagworks, FalkorDB, Langchain and OpenAI

LangChain integration for advertools

A web site crawler for semantic search.

This project leverages Langchain and Groq to analyze conversations between recovery agents and borrowers. The analysis includes summarization, key actions identification, sentiment analysis, named entity recognition (NER), and non-compliance checks.

retreival augmented generation based chatbot using langchain and google's gemini which reduces hallucination and gets the latest data ensuring privacy and concise answers

Revise your subjects with studybot using RAG

The Camel Quickstart Assistant helps you build Camel applications using a LLM backed agent that draws on documentation for Camel Quarkus and Camel Springboot.

Generative AI projects using openAI, llama, langchain, vectordb

A practice repository implementing examples from the official LangChain documentation

Implementing Retrieval Augmented Generation (RAG) via using GPT-3.5-Turbo as the LLM model and Langchain to simplify the implementation, with the data being feed is in the form of list to make it easier to understand.

How to convert GPT text prompts to text prompts for Large Language Models (LLMs) on Amazon Bedrock.

Multi-model knowledge assistant/QA-Bot based on Langchain, leveraging LLMs, RAG, FastAPI and Gradio

An LLM challenge to (i) fine-tune pre-trained HuggingFace transformer model to build a Code Generation language model, and (ii) build a retrieval-augmented generation (RAG) application using LangChain

Retrieval-augmented generation (RAG) system for medical Q&A using the Merck Manual of Diagnosis and Therapy (19th Edition). Semantic search via ChromaDB and GTE-large embeddings; answer generation with Mistral 7B (GGUF). Runs fully locally for privacy, with optional GPU acceleration.

Applied AI and Agentic AI project repository from the IIIT Bangalore PGP program, focusing on LLMs, agentic workflows, automation, and real-world AI system design.

My LangGraph Exercises 🦜🕸️

Semantic book recommendation system using LLM embeddings, zero-shot classification, and emotion scoring with a Gradio dashboard.

This repository contains a case study of the use of Large Language Models to serve as a customer service chatbot based off of Home Depot's website using the Langchain framework, Slack API, and Open AI API. The Langchain agent used is a database agent that can perform SQL queries on any database.