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Jupyter Notebook agents
2,100 Jupyter Notebook AI agents indexed on MeshKore — the most complete public catalog, ranked by popularity and updated daily.
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Jupyter Notebook agents — page 15 of 21
This repository contains practical examples and sample projects demonstrating how to use Moorcheh, a framework for building AI-powered chat applications.
This project is an innovative coffee shop application designed to bring an engaging and personalized experience to coffee lovers. The app leverages AI-powered agents for chat-based interactions and integrates modern web and mobile development techniques to provide seamless ordering and delivery services.
QueryGenie.AI is a Generative AI tool to extract data from a database by using simple Natural Language. This tool takes question in the form of natural language and convert that into SQL query then it shows both SQL query and exact answer as output to the user.
Agentic chatbot for food-delivery order queries: SQL agent over order DB → LLM-powered, guardrailed responses. LangChain, OpenAI/Claude, SQLite.
Learn to build trustworthy AI with systematic evaluations in Azure AI Foundry. The session covers quality, safety, agent and custom evaluators
Next-Gen Indonesia IT Law Q&A: Knowledge Graphs & LLMs. ArangoDB Hackathon Project Repository: Building the Next-Gen Agentic App with GraphRAG & NVIDIA cuGraph.
A deep-dive LLM engineering lab — agents, RAG, fine-tuning, inference optimization, model deployment, hands-on research, and ongoing paper tracking.
AI-powered multi-agent financial advisor system with LangGraph orchestration across nine specialized agents including retrieval, portfolio analysis, market desk, due diligence, and compliance, routing through a LiteLLM gateway, computing real portfolio risk metrics, and holding risky answers for human review before they reach the user.
LangGraph: Multi-Agent Supervisor Chatting with a User
Just LangChain for beginners tutorial in Persian.
GRAPHRAG with Langchain
📑 DAYA: Document Aware hYbrid Architecture, A RAG Pipeline for Illustrated Documents (PPTs).
An agentic AI system for conversational data analysis. Upload any CSV, query your data in natural language, and receive instant insights, auto-generated visualizations, and executable Python code — powered by LangChain, OpenAI/Gemini LLMs, Streamlit, and FastAPI.
Collaborative development environment and project repository for the Coddiom agency. Featuring AI-driven workflows, product scaling experiments, and automated content generation pipelines.
How to build LLM agents with Magentic
AI Engineering 实战学习仓库
Hands-on Generative AI: 15 RAG modules from document loaders to guardrails, plus Papeer — a research paper assistant with citations and claim verification. Also LangGraph workflows and LangSmith tracing.
This Python project demonstrates semantic search using MongoDB and two different LLM frameworks: LangChain and LlamaIndex. The goal is to load documents from MongoDB, generate embeddings for the text data, and perform semantic searches using both LangChain and LlamaIndex frameworks.
A highly customizable AI companion for Telegram. Create digital clones with unique personalities, voice, and vision directly from Google Colab.
Custom Trained LLM application with Llama, and grounding via RAG. This project uses Streamlit to create a simple UX LLM based chatbot with Llama3 & RAG grounding on Stehen Hawking's books
A simple AgenticAI RAG agent showcasing autonomous reasoning and decision-making by integrating thought, logic, and action in real-time tasks.
In this we implements a Retrieval-Augmented Generation (RAG) based conversational AI agent designed for intelligent knowledge extraction from PDF documents. Leveraging LangChain and Google’s Gemini LLM
Việt Nam Dữ Liệu
Recursive Consciousness: Modeling Minds in Forgetful Systems
Metadata filtering in RAG application
Multi-agent LLM simulations testing algorithmic collusion and coordination breakdown in oligopoly markets.
LLMRoboFund is a powerful chatbot empowered with Multi-document RAG. The chatbot is equipped with RetrievalQA and SQL Agents to ease the investment research
Learning and sharing about libraries and frameworks on LLMs 😎
🎧💡 EchoSummarize: A YouTube video summarizer using the Phi-3.5-mini LLM, providing fast and accurate summaries of video transcripts.
Explore how to build a Q&A system on PDF File's using AstraDB's Vector DB with Langchain and OpenAI API's
How to process semi-structured data using Large Language Models (LLMs) on Amazon Bedrock.
A real-time AI-powered chatroom that detects emotions, blocks toxic content, and generates conversation insights using microservices and modern Transformer models
Agentic RAG using Crew AI
Beyond Vectors: Augment LLM Capabilities with MongoDB Aggregation Framework and CrewAI
🤖🤝🤖AI agent orchestration patterns with Semantic Kernel and AutoGen. 💸Investment advisor scenario.
Welcome to SriksML – a comprehensive repository of hands-on, production-inspired Jupyter notebooks and code samples for modern machine learning, deep learning, and AI workflows.
ArguBot is a chatbot based on the doctoral thesis "Construction of Arguments and Socio-Technical Controversies" by Tomás Manzur. It offers interactive access to the thesis's insights on the Plan Provincial de Ordenamiento Territorial of Mendoza.
Personality Representation & Personality based Chatting
This repository contains a machine learning-based predictive model for automating loan eligibility assessments. Using features such as demographic details, loan information, and credit history, the model predicts whether a loan should be approved or denied.
Chatbot for E-Commerce Related Questions
The intention of this project is to create a chatbot based on movie reviews so that you can ask questions and have a free conversation about this topic.
A multi-backend AI chatbot with a customizable Gradio interface, supporting 100+ models from local and cloud providers.
Python library for building custom AI chatbot with just one line of code.
Simple chatbot implementation with PyTorch.
This GitHub repository is a valuable resource for machine learning and Python enthusiasts. It includes a wide range of projects and tools, covering topics like Data Visualization, Data Analysis, ML, DL, Automation, NLP, Web Scraping, and more. Contributors are welcome to join and learn together in this supportive community. Happy coding!
위험지수 및 혼잡도를 고려한 대중교통 추천 경로를 안내해주는 챗봇입니다.
Discord bot using DailoGPT pretrained model on Rick& Morty Dataset from Kaggle
A prompting framework for getting foundational models to “lazily” evaluate their reasoning trace
This repo mirrors my public Kaggle notebooks and keeps them in one clean, versioned place.
🚀 Explore Happy-LLM, a tool designed to enhance interactions with language models, offering a user-friendly experience in Chinese.
This project leverages the Phi3 model and ChromaDB to create a Retrieval-Augmented Generation (RAG) application.
KG1 is a social knowledge management application, infused with AI.
🤖GraphRAG v2 API (From Local to Global: arxiv.org/abs/2404.16130) Playground 🥦
A PoC of using Weaviate + DSPy to make a BookStore CoPilot
The Zoomcamp LLM Course focuses on tools for working with LLMs and RAG, including OpenAI API, HuggingFace, Elasticsearch, and Streamlit. It covers vector search, embedding creation, data ingestion with Mage, and monitoring using Grafana, emphasizing practical applications and best practices.
A RAG system designed for law firms to enable lawyers to efficiently "talk to their data"
A Tool that Allows You Run PyTest within Jupyter Notebook Cells
An AI-powered crypto analytics platform integrating forecasting, sentiment, and on-chain intelligence, built with FastAPI, MCP protocol, and MLflow in a monolithic architecture.
The goal of this project is to develop a RAG system using Agent from LangGraph to improve the travelling experience of tourists.
Series of generative artificial intelligence (AI) for creating new content, including audio, code, images, text, simulations, and videos.
This project consist on ChatBot implementation with two approach: Retrival-Augmented Generation (RAG) and Fine-Tuning
Notebooks that walk through modern LangChain and LangGraph patterns using the latest v1.x APIs. Content is organized to start from fundamentals and build up on that.
🗯️LLM toolkit for RAG, tuning, agents, and more
Innovative AI agent implementations using LangGraph—featuring ReAct, RAG (Corrective, Self, Agentic), chatbots, microagents, and more, with multi-AI agent systems on the horizon! 🤖🚀
Build your own AI chatbot from scratch using Google Colab, TensorFlow, and a interactive neon matrix interface.
Explore Mistral AI's extensive collection of models. Learn to select, prompt, and integrate Mistral's open-source and commercial models for tasks like classification, coding, and Retrieval Augmented Generation (RAG).
This project aims to develop a high-precision legal expert system for contract Q&A using Retrieval-Augmented Generation (RAG). The system leverages advanced natural language processing (NLP) techniques to provide accurate and context-aware answers to questions about legal contracts and integrates a powerful language model with a custom retrieval
[WebMedia 2025] Explore the fundamentals of MLLMs and emblematic models. This repository covers practical techniques for preprocessing, prompt engineering, and building multimodal pipelines using LangChain and LangGraph, alongside future trends and challenges in AI.
A RAG-based chatbot that extracts insights, summaries, and topic clusters from YouTube videos, providing comprehensive understanding and answering user queries.
Secure FedRAG framework for distributed health data search and knowledge exchange
An end-to-end Machine Learning and Agentic AI system to predict customer churn and generate structured retention strategies using LangGraph and Open-Source LLMs.
Step-by-step implementations for building cognitive financial agents
A practical, research-backed handbook for deciding when (and how) to build AI agent teams that actually ship
🤖 Tajan – An intelligent bilingual (Persian/English) intent recognition chatbot powered by BiLSTM deep learning. Features: offline Persian/English lemmatizer, smart data augmentation (1.8x), GUI interface, and 419 intent classes with ~66% accuracy. Fully customizable, open-source, and runs without internet. Built with TensorFlow, Hazm, and NLTK.
Wheat Farming AI Disease Detection and Chatbot Support
Guia técnico aberto de engenharia de agentes de IA em produção (em português): agentes ReAct e multi-agente, engenharia de contexto, avaliação e observabilidade (LLM-as-a-Judge, Langfuse), LangGraph e RAG avançado/Graph/Agentic (LlamaIndex, Neo4j).
A deep-dive LLM engineering lab — agents, RAG, fine-tuning, inference optimization, model deployment, hands-on research, and ongoing paper tracking.
Thermal Sentinel Grid: Physical-AI Digital Twin & Autonomous Agentic Dispatch Engine for Substation Transformers & Urban Grid Resilience | FortyGuard Hackathon '26 (Track 03: Industrial & Enterprise)
黑马程序员Python入门学习与项目练习合集，涵盖基础语法、文件处理、网络爬虫、数据分析与 AI 应用开发
Agentic AI refers to AI systems capable of autonomous decision-making, planning, and executing tasks based on goals—acting like intelligent agents. These systems combine LLMs with tools, memory, and feedback loops to complete complex workflows with minimal human input.
✅ 의료 데이터를 활용한 챗봇과 다양한 파이프라인을 제작합니다.
Collection of generative AI projects & applications including: multiple LLMs, AI agents, RAG
The LangGraph project implements a "Reflection Agent" designed to iteratively refine answers to user queries using a Large Language Model (LLM) and web search. It simulates a research process where an initial answer is generated, critiqued, and revised based on information gathered from web searches, all managed by a LangGraph workflow.
AI agents, trained by the minds that move the world.
This is a YouTube Q&A Chatbot powered by a Large Language Model (LLM) and FastAPI. Users can enter a YouTube video URL and ask questions — the system generates accurate answers using the video transcript.
This is a document question answering app made with LangChain and deployed on Streamlit where you can upload a .txt or .docx file, ask questions based on the file and an LLM like Falcon-7B or Dolly-V2-3B answers it. ChromaDB is used as the vector database.
GenAI demo with Amazon Kendra, 🦜️🔗 LangChain and Amazon SageMaker JumpStart
AI-powered book recommendations engine that fuses semantic understanding and emotion intelligence to deliver deeply relevant book suggestions. Powered by LangChain, OpenAI embeddings, and emotion-aware NLP across ~7,000 titles, with an interactive Gradio experience for intuitive exploration.
Interactive Book Recommendation System using RAG and RecSys
This project seeks to create a comprehensive system for summarising research papers by harnessing the latest advancements in AI and NLP. By merging abstractive text summarization with LLMs and the RAG methodology, we anticipate developing a unique and effective approach to extracting valuable insights from research papers
This project implements a RAG (Retrieval-Augmented Generation) application to answer questions about phenotypes using biological and genomic data. The pipeline integrates information retrieval with response generation via language models (LLM), facilitating accurate analysis of phenotypic data.
All CPU efficient GPU-less Financial Analysis RAG Model with Qdrant, Langchain and GPT4All x Mistral-7B, run RAG without any GPU support!
The Agentic AI Workshop by ADP Brazil Labs.
Creating RAG from Scratch . Creating RAG using the langchain. Creating RAG using llama indexing and Qdrant db
AI Engineering Bootcamp for Programmers - A 19-module, 18-week immersive study plan designed for programmers looking to master AI engineering through real-world projects, foundational theory, and practical tools.
A Typeform-inspired Chat Feature with Chat Agents for Engaging Data Collection, Powered by AutoGen and Langchain. Includes REST API Integration for Messaging Systems.
Unlock the potential of AI-driven solutions and delve into the world of Large Language Models. Explore cutting-edge concepts, real-world applications, and best practices to build powerful systems with these state-of-the-art models.
Record voice, transcribe a prompt, picturize the prompt, create variations, get description of a celebrity and upload, other use cases on KB