# 500-项目合集 **Repository Path**: chais-flying-up/500-project-collection ## Basic Information - **Project Name**: 500-项目合集 - **Description**: No description available - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-12-10 - **Last Updated**: 2025-12-10 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # 🌟 500+ AI Agent Projects / UseCases [![500-AI-Agents-Projects - UseCase](https://img.shields.io/badge/500--AI--Agents--Projects-UseCase-2ea44f?logo=https%3A%2F%2Fstatic-00.iconduck.com%2Fassets.00%2Frobot-emoji-2048x2044-kay057lt.png&logoColor=2ea44f)](https://github.com/ashishpatel26/500-AI-Agents-Projects) ![img](images/AIAgentUseCase.jpg) A curated collection of AI agent use cases across industries, showcasing practical applications and linking to open-source projects for implementation. Explore how AI agents are transforming industries like healthcare, finance, education, and more! 🤖✨ --- ## 📋 Table of Contents - [Introduction](#introduction) - [Industry Usecase](#-industry-usecase-mindmap) - [Use Case Table](#use-case-table) - [Framework Wise UseCase](#framework-wise-usecases) - [CrewAI UseCase](#framework-name-crewai) - [AutoGen UseCase](#framework-name-autogen) - [Agno UseCase](#framework-name-agno) - [Langgraph UseCase](#framework-name-langgraph) - [Contributing](#contributing) - [License](#license) --- ## 🧠 Introduction Artificial Intelligence (AI) agents are revolutionizing the way industries operate. From personalized learning to financial trading bots, AI agents bring efficiency, innovation, and scalability. This repository provides: - A categorized list of industries where AI agents are making an impact. - Detailed use cases with links to open-source projects for implementation. Whether you're a developer, researcher, or business enthusiast, this repository is your go-to resource for AI agent inspiration and learning. --- ## 🏭 Industry UseCase MindMap ![](images/industry_usecase1.png) --- ## 🧩 Use Case Table | Use Case | Industry | Description | Code Github | | ------------------------------------------- | ---------------- | -------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **HIA (Health Insights Agent)** | Healthcare | analyses medical reports and provide health insights. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/harshhh28/hia.git) | | **AI Health Assistant** | Healthcare | Diagnoses and monitors diseases using patient data. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/ahmadvh/AI-Agents-for-Medical-Diagnostics.git) | | **Automated Trading Bot** | Finance | Automates stock trading with real-time market analysis. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/MingyuJ666/Stockagent.git) | | **Virtual AI Tutor** | Education | Provides personalized education tailored to users. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/hqanhh/EduGPT.git) | | **24/7 AI Chatbot** | Customer Service | Handles customer queries around the clock. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/NirDiamant/GenAI_Agents/blob/main/all_agents_tutorials/customer_support_agent_langgraph.ipynb) | | **Product Recommendation Agent** | Retail | Suggests products based on user preferences and history. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/microsoft/RecAI) | | **Self-Driving Delivery Agent** | Transportation | Optimizes routes and autonomously delivers packages. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/sled-group/driVLMe) | | **Factory Process Monitoring Agent** | Manufacturing | Monitors production lines and ensures quality control. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/yuchenxia/llm4ias) | | **Property Pricing Agent** | Real Estate | Analyzes market trends to determine property prices. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/AleksNeStu/ai-real-estate-assistant) | | **Smart Farming Assistant** | Agriculture | Provides insights on crop health and yield predictions. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/mohammed97ashraf/LLM_Agri_Bot) | | **Energy Demand Forecasting Agent** | Energy | Predicts energy usage to optimize grid management. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/yecchen/MIRAI) | | **Content Personalization Agent** | Entertainment | Recommends personalized media based on preferences. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/crosleythomas/MirrorGPT) | | **Legal Document Review Assistant** | Legal | Automates document review and highlights key clauses. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/firica/legalai) | | **Recruitment Recommendation Agent** | Human Resources | Suggests best-fit candidates for job openings. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/sentient-engineering/jobber) | | **Virtual Travel Assistant** | Hospitality | Plans travel itineraries based on preferences. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/nirbar1985/ai-travel-agent) | | **AI Game Companion Agent** | Gaming | Enhances player experience with real-time assistance. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/onjas-buidl/LLM-agent-game) | | **Real-Time Threat Detection Agent** | Cybersecurity | Identifies potential threats and mitigates attacks. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/NVISOsecurity/cyber-security-llm-agents) | | **E-commerce Personal Shopper Agent** | E-commerce | Helps customers find products they’ll love. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/Hoanganhvu123/ShoppingGPT) | | **Logistics Optimization Agent** | Supply Chain | Plans efficient delivery routes and manages inventory. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/microsoft/OptiGuide) | | **Vibe Hacking Agent** | Cybersecurity | Autonomous Multi-Agent Based Red Team Testing Service. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/PurpleAILAB/Decepticon) | | **MediSuite-Ai-Agent** | Health insurance | A medical ai agent that helps automating the process of hospitals / insurance claiming workflow. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/MahmoudRabea13/MediSuite-Ai-Agent) | | **Lina-Egyptian-Medical-Chatbot** | Health insurance | A medical ai agent that helps automating the process of hospitals / insurance claiming workflow. | [![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/MahmoudRabea13/MediSuite-Ai-Agent) | ## Framework wise Usecases --- ### **Framework Name**: **CrewAI** | Use Case | Industry | Description | GitHub | | -------------------------------- | ----------------------- | -------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------- | | 📧 Email Auto Responder Flow | 🗣️ Communication | Automates email responses based on predefined criteria to enhance communication efficiency. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/email_auto_responder_flow) | | 📝 Meeting Assistant Flow | 🛠️ Productivity | Assists in organizing and managing meetings, including scheduling and agenda preparation. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/meeting_assistant_flow) | | 🔄 Self Evaluation Loop Flow | 👥 Human Resources | Facilitates self-assessment processes within an organization, aiding in performance reviews. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/self_evaluation_loop_flow) | | 📈 Lead Score Flow | 💼 Sales | Evaluates and scores potential leads to prioritize outreach in sales strategies. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/lead-score-flow) | | 📊 Marketing Strategy Generator | 📢 Marketing | Develops marketing strategies by analyzing market trends and audience data. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/marketing_strategy) | | 📝 Job Posting Generator | 🧑‍💼 Recruitment | Creates job postings by analyzing job requirements, aiding in recruitment processes. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/job-posting) | | 🔄 Recruitment Workflow | 🧑‍💼 Recruitment | Streamlines the recruitment process by automating various tasks involved in hiring. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/recruitment) | | 🔍 Match Profile to Positions | 🧑‍💼 Recruitment | Matches candidate profiles to suitable job positions to enhance recruitment efficiency. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/match_profile_to_positions) | | 📸 Instagram Post Generator | 📱 Social Media | Generates and schedules Instagram posts automatically, streamlining social media management. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/instagram_post) | | 🌐 Landing Page Generator | 💻 Web Development | Automates the creation of landing pages for websites, facilitating web development tasks. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/landing_page_generator) | | 🎮 Game Builder Crew | 🎮 Game Development | Assists in the development of games by automating certain aspects of game creation. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/game-builder-crew) | | 💹 Stock Analysis Tool | 💰 Finance | Provides tools for analyzing stock market data to assist in financial decision-making. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/stock_analysis) | | 🗺️ Trip Planner | ✈️ Travel | Assists in planning trips by organizing itineraries and managing travel details. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/trip_planner) | | 🎁 Surprise Trip Planner | ✈️ Travel | Plans surprise trips by selecting destinations and activities based on user preferences. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/surprise_trip) | | 📚 Write a Book with Flows | ✍️ Creative Writing | Assists authors in writing books by providing structured workflows and writing assistance. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/write_a_book_with_flows) | | 🎬 Screenplay Writer | ✍️ Creative Writing | Aids in writing screenplays by offering templates and guidance for script development. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/screenplay_writer) | | ✅ Markdown Validator | 📄 Documentation | Validates Markdown files to ensure proper formatting and adherence to standards. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/markdown_validator) | | 🧠 Meta Quest Knowledge | 📚 Knowledge Management | Manages and organizes knowledge related to Meta Quest, facilitating information retrieval. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/meta_quest_knowledge) | | 🤖 NVIDIA Models Integration | 🤖 AI Integration | Integrates NVIDIA AI models into workflows to enhance computational capabilities. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/integrations/nvidia_models) | | 🗂️ Prep for a Meeting | 🛠️ Productivity | Assists in preparing for meetings by organizing materials and setting agendas. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/prep-for-a-meeting) | | 🛠️Starter Template | 🛠️ Development | Provides a starter template for new projects to streamline the setup process. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/starter_template) | | 🔗CrewAI + LangGraph Integration | 🤖 AI Integration | Demonstrates integration between CrewAI and LangGraph for enhanced workflow automation. | [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/crewAIInc/crewAI-examples/tree/main/integrations/CrewAI-LangGraph) | ### **Framework Name**: **Autogen** > **Code Generation, Execution, and Debugging** | Use Case | Industry | Description | Notebook | | --------------------------------------------------------------------------------------- | ----------------------- | --------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | 🤖 Automated Task Solving with Code Generation, Execution & Debugging | 💻 Software Development | Demonstrates automated task-solving by generating, executing, and debugging code. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_auto_feedback_from_code_execution) | | 🧑‍💻 Automated Code Generation and Question Answering with Retrieval Augmented Agents | 💻 Software Development | Generates code and answers questions using retrieval-augmented methods. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_RetrieveChat) | | 🧠 Automated Code Generation and Question Answering with Qdrant-based Retrieval | 💻 Software Development | Utilizes Qdrant for enhanced retrieval-augmented agent performance. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_RetrieveChat_qdrant) | > **Multi-Agent Collaboration (>3 Agents)** | Use Case | Industry | Description | Notebook | | :----------------------------------------------------------------------- | :-------------------------- | :------------------------------------------------------------------ | :------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | 🤝 Automated Task Solving by Group Chat (3 members, 1 manager) | 🤝 Collaboration | Demonstrates group task-solving via multi-agent collaboration. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat) | | 📊 Automated Data Visualization by Group Chat (3 members, 1 manager) | 📊 Data Analysis | Uses multi-agent collaboration to create data visualizations. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat_vis) | | 🧩 Automated Complex Task Solving by Group Chat (6 members, 1 manager) | 🤝 Collaboration | Solves complex tasks collaboratively with a larger group of agents. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat_research) | | 🧑‍💻 Automated Task Solving with Coding & Planning Agents | 🛠️ Planning & Development | Combines coding and planning agents for solving tasks effectively. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_planning.ipynb) | | 📐 Automated Task Solving with Transition Paths Specified in a Graph | 🤝 Collaboration | Uses predefined transition paths in a graph for solving tasks. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/docs/notebooks/agentchat_groupchat_finite_state_machine) | | 🧠 Running a Group Chat as an Inner-Monologue via the SocietyOfMindAgent | 🧠 Cognitive Sciences | Simulates inner-monologue for problem-solving using group chats. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_society_of_mind) | | 🔧 Running a Group Chat with Custom Speaker Selection Function | 🤝 Collaboration | Implements a custom function for speaker selection in group chats. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat_customized) | > **Sequential Multi-Agent Chats** | Use Case | Industry | Description | Notebook | | :--------------------------------------------------------------------------------- | :--------------------- | :------------------------------------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------- | | 🔄 Solving Multiple Tasks in a Sequence of Chats Initiated by a Single Agent | 🔄 Workflow Automation | Automates sequential task-solving with a single initiating agent. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_multi_task_chats) | | ⏳ Async-solving Multiple Tasks in a Sequence of Chats Initiated by a Single Agent | 🔄 Workflow Automation | Handles asynchronous task-solving in a sequence of chats initiated by one agent. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_multi_task_async_chats) | | 🤝 Solving Multiple Tasks in a Sequence of Chats Initiated by Different Agents | 🔄 Workflow Automation | Facilitates sequential task-solving with different agents initiating each chat. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchats_sequential_chats) | > **Nested Chats** | Use Case | Industry | Description | Notebook | | :----------------------------------------------------------------------------- | :--------------------------- | :------------------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------- | | 🧠 Solving Complex Tasks with Nested Chats | 🧠 Problem Solving | Uses nested chats to solve hierarchical and complex problems. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nestedchat) | | 🔄 Solving Complex Tasks with A Sequence of Nested Chats | 🧠 Problem Solving | Demonstrates sequential task-solving using nested chats. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nested_sequential_chats) | | 🏭 OptiGuide for Solving a Supply Chain Optimization Problem with Nested Chats | 🏭 Supply Chain Optimization | Showcases how to solve supply chain optimization problems using nested chats, a coding agent, and a safeguard agent. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nestedchat_optiguide) | | ♟️ Conversational Chess with Nested Chats and Tool Use | 🎮 Gaming | Explores the use of nested chats for playing conversational chess with integrated tools. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nested_chats_chess) | > **Application** | Use Case | Industry | Description | Notebook | | :------------------------------------------------------------------------------------------------- | :--------------------------- | :------------------------------------------------------------------------------------------------ | :------------------------------------------------------------------------------------------------------------------------------------------------------------ | | 🔄 Automated Continual Learning from New Data | 📊 Machine Learning | Continuously learns from new data inputs for adaptive AI. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_stream.ipynb) | | 🏭 OptiGuide - Coding, Tool Using, Safeguarding & Question Answering for Supply Chain Optimization | 🏭 Supply Chain Optimization | Highlights a solution combining coding, tool use, and safeguarding for supply chain optimization. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nestedchat_optiguide) | | 🤖 AutoAnny - A Discord bot built using AutoGen | 💬 Communication Tools | Showcases the development of a Discord bot using AutoGen for enhanced interaction. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/tree/main/samples/apps/auto-anny) | > **Tools** | Use Case | Industry | Description | Notebook | | :--------------------------------------------------------------------- | :----------------------------- | :------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | 🌐 Web Search: Solve Tasks Requiring Web Info | 🔍 Information Retrieval | Searches the web to gather information required for completing tasks. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_web_info.ipynb) | | 🔧 Use Provided Tools as Functions | 🛠️ Tool Integration | Demonstrates how to use pre-provided tools as callable functions in AutoGen. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_function_call_currency_calculator) | | 🔗 Use Tools via Sync and Async Function Calling | 🛠️ Tool Integration | Illustrates synchronous and asynchronous tool usage within AutoGen workflows. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_function_call_async) | | 🧩 Task Solving with Langchain Provided Tools as Functions | 🔍 Language Processing | Leverages Langchain tools for task-solving within AutoGen. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_langchain.ipynb) | | 📚 RAG: Group Chat with Retrieval Augmented Generation | 🤝 Collaboration | Enables group chat with Retrieval Augmented Generation (RAG) to support information sharing. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat_RAG) | | ⚙️ Function Inception: Update/Remove Functions During Conversations | 🔧 Development Tools | Allows AutoGen agents to modify their functions dynamically during conversations. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_inception_function.ipynb) | | 🔊 Agent Chat with Whisper | 🎙️ Audio Processing | Demonstrates AI agent capabilities for transcription and translation using Whisper. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_video_transcript_translate_with_whisper) | | 📏 Constrained Responses via Guidance | 💡 Natural Language Processing | Shows how to use guidance to constrain responses generated by agents. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_guidance.ipynb) | | 🌍 Browse the Web with Agents | 🌐 Information Retrieval | Explains how to configure agents to browse and retrieve information from the web. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_surfer.ipynb) | | 📊 SQL: Natural Language Text to SQL Query Using Spider Benchmark | 💾 Database Management | Converts natural language inputs into SQL queries using the Spider benchmark. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_sql_spider.ipynb) | | 🕸️ Web Scraping with Apify | 🌐 Data Gathering | Illustrates web scraping techniques with Apify using AutoGen. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_webscraping_with_apify) | | 🕷️ Web Crawling: Crawl Entire Domain with Spider API | 🌐 Data Gathering | Explains how to crawl entire domains using the Spider API. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_webcrawling_with_spider) | | 💻 Write a Software App Task by Task with Specially Designed Functions | 💻 Software Development | Builds a software application step-by-step using designed functions. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_function_call_code_writing.ipynb) | > **Human Development** | Use Case | Industry | Description | Notebook | | :--------------------------------------------------------------- | :---------------------- | :------------------------------------------------------------------------------------------------ | :------------------------------------------------------------------------------------------------------------------------------------------------------------ | | 💬 Simple Example in ChatGPT Style | 🧠 Conversational AI | Demonstrates a simple conversational example in the style of ChatGPT. | [![Example](https://img.shields.io/badge/View-Example-blue?logo=openai)](https://github.com/microsoft/autogen/blob/0.2/samples/simple_chat.py) | | 🤖 Auto Code Generation, Execution, Debugging and Human Feedback | 💻 Software Development | Showcases code generation, execution, debugging with human feedback integrated into the workflow. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_human_feedback.ipynb) | | 👥 Automated Task Solving with GPT-4 + Multiple Human Users | 🤝 Collaboration | Enables task solving with multiple human users collaborating with GPT-4. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_two_users.ipynb) | | 🔄 Agent Chat with Async Human Inputs | 🧠 Conversational AI | Supports asynchronous human input during agent conversations. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/Async_human_input.ipynb) | > **Agent Teaching and Learning** | Use Case | Industry | Description | Notebook | | :------------------------------------------------------------------- | :-------------------------- | :--------------------------------------------------------------------------------------- | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | 📘 Teach Agents New Skills & Reuse via Automated Chat | 🎓 Education & Training | Demonstrates teaching new skills to agents and enabling their reuse in automated chats. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_teaching) | | 🧠 Teach Agents New Facts, User Preferences and Skills Beyond Coding | 🎓 Education & Training | Shows how to teach agents new facts, user preferences, and non-coding skills. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_teachability) | | 🤖 Teach OpenAI Assistants Through GPTAssistantAgent | 💻 AI Assistant Development | Illustrates how to enhance OpenAI assistants' capabilities using GPTAssistantAgent. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_teachable_oai_assistants.ipynb) | | 🔄 Agent Optimizer: Train Agents in an Agentic Way | 🛠️ Optimization | Explains how to train agents effectively in an agentic manner using the Agent Optimizer. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_agentoptimizer.ipynb) | > **Multi-Agent Chat with OpenAI Assistants in the loop** | Use Case | Industry | Description | Notebook | | :-------------------------------------------------------- | :----------------------- | :---------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | 🌟 Hello-World Chat with OpenAI Assistant in AutoGen | 🤖 Conversational AI | A basic example of chatting with OpenAI Assistant using AutoGen. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_oai_assistant_twoagents_basic.ipynb) | | 🔧 Chat with OpenAI Assistant using Function Call | 🔧 Development Tools | Illustrates how to use function calls with OpenAI Assistant in chats. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_oai_assistant_function_call.ipynb) | | 🧠 Chat with OpenAI Assistant with Code Interpreter | 💻 Software Development | Demonstrates the use of OpenAI Assistant as a code interpreter in chats. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_oai_code_interpreter.ipynb) | | 🔍 Chat with OpenAI Assistant with Retrieval Augmentation | 📚 Information Retrieval | Enables retrieval-augmented conversations with OpenAI Assistant. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_oai_assistant_retrieval.ipynb) | | 🤝 OpenAI Assistant in a Group Chat | 🤝 Collaboration | Shows how OpenAI Assistant can collaborate with other agents in a group chat. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_oai_assistant_groupchat.ipynb) | | 🛠️ GPTAssistantAgent based Multi-Agent Tool Use | 🔧 Development Tools | Explains how to use GPTAssistantAgent for multi-agent tool usage. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/gpt_assistant_agent_function_call.ipynb) | > **Non-OpenAI Models** | Use Case | Industry | Description | Notebook | | :------------------------------------------------ | :-------- | :---------------------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | ♟️ Conversational Chess using Non-OpenAI Models | 🎮 Gaming | Explores conversational chess implemented with non-OpenAI models. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nested_chats_chess_altmodels) | > **Multimodal Agent** | Use Case | Industry | Description | Notebook | | :--------------------------------------------- | :------------------ | :-------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------- | | 🎨 Multimodal Agent Chat with DALLE and GPT-4V | 🖼️ Multimedia AI | Combines DALLE and GPT-4V for multimodal agent communication. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_dalle_and_gpt4v.ipynb) | | 🖌️ Multimodal Agent Chat with Llava | 📷 Image Processing | Uses Llava for enabling multimodal agent conversations with image processing. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_lmm_llava.ipynb) | | 🖼️ Multimodal Agent Chat with GPT-4V | 🖼️ Multimedia AI | Leverages GPT-4V for visual and conversational interactions in multimodal agents. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_lmm_gpt-4v.ipynb) | > **Long Context Handling** | Use Case | Industry | Description | Notebook | | :--------------------------------------- | :--------------- | :--------------------------------------------------------------------------------- | :---------------------------------------------------------------------------------------------------------------------------------------------------------- | | 📜 Long Context Handling as A Capability | 🧠 AI Capability | Demonstrates techniques for handling long context effectively within AI workflows. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_transform_messages) | > **Evaluation and Assessment** | Use Case | Industry | Description | Notebook | | :----------------------------------------------------------------------------------- | :------------------------ | :------------------------------------------------------------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------- | | 📊 AgentEval: A Multi-Agent System for Assessing Utility of LLM-Powered Applications | 📈 Performance Evaluation | Introduces AgentEval for evaluating and assessing the performance of LLM-based applications. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agenteval_cq_math.ipynb) | > **Automatic Agent Building** | Use Case | Industry | Description | Notebook | | :------------------------------------------------------------ | :---------------- | :------------------------------------------------------------------------------------ | :----------------------------------------------------------------------------------------------------------------------------------------------------------- | | 🏗️ Automatically Build Multi-agent System with AgentBuilder | 🤖 AI Development | Explains how to automatically build multi-agent systems using the AgentBuilder tool. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/autobuild_basic.ipynb) | | 📚 Automatically Build Multi-agent System from Agent Library | 🤖 AI Development | Shows how to construct multi-agent systems by leveraging a pre-defined agent library. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/autobuild_agent_library.ipynb) | > **Observability** | Use Case | Industry | Description | Notebook | | :---------------------------------------------------------------- | :------------------------ | :----------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------ | | 📊 Track LLM Calls, Tool Usage, Actions and Errors using AgentOps | 📈 Monitoring & Analytics | Demonstrates how to monitor LLM interactions, tool usage, and errors using AgentOps. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_agentops.ipynb) | > **Enhanced Inferences** | Use Case | Industry | Description | Notebook | | :--------------------------------------------------------------------- | :----------------- | :----------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | 🔗 API Unification | 🔧 API Management | Explains how to unify API usage with documentation and code examples. | [![Documentation](https://img.shields.io/badge/View-Documentation-blue?logo=readthedocs)](https://microsoft.github.io/autogen/docs/Use-Cases/enhanced_inference/#api-unification) | | ⚙️ Utility Functions to Help Managing API Configurations Effectively | 🔧 API Management | Demonstrates utility functions to manage API configurations more effectively. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://microsoft.github.io/autogen/0.2/docs/topics/llm_configuration) | | 💰 Cost Calculation | 📈 Cost Management | Introduces methods for tracking token usage and estimating costs for LLM interactions. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_cost_token_tracking.ipynb) | | ⚡ Optimize for Code Generation | 📊 Optimization | Highlights cost-effective optimization techniques for improving code generation with LLMs. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/oai_completion.ipynb) | | 📐 Optimize for Math | 📊 Optimization | Explains techniques to optimize LLM performance for solving mathematical problems. | [![Notebook](https://img.shields.io/badge/View-Notebook-blue?logo=jupyter)](https://github.com/microsoft/autogen/blob/0.2/notebook/oai_chatgpt_gpt4.ipynb) | ### **Framework Name**: **Agno** > **UseCase** | Use Case | Industry | Description | Notebook | | :--------------------------------- | :----------------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | 🤖 Support Agent | 💻 Software Development / AI / Framework Support | The Agno Support Agent helps developers with the Agno framework by providing real-time answers, explanations, and code examples. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/agno_support_agent.py) | | 🎥 YouTube Agent | 📺 Media & Content | An intelligent agent that analyzes YouTube videos by generating detailed summaries, timestamps, themes, and content breakdowns using AI tools. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/youtube_agent.py) | | 📊 Finance Agent | 💼 Finance | An advanced AI-powered market analyst that delivers real-time stock market insights, analyst recommendations, financial deep-dives, and sector-specific trends. Supports prompts for detailed analysis of companies like AAPL, TSLA, NVDA, etc. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/thinking_finance_agent.py) | | 📚 Study Partner | 🎓 Education | Assists users in learning by finding resources, answering questions, and creating study plans. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/study_partner.py) | | 🛍️ Shopping Partner Agent | 🏬 E-commerce | A product recommender agent that helps users find matching products based on preferences from trusted platforms like Amazon, Flipkart, etc. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/shopping_partner.py) | | 🎓 Research Scholar Agent | 🧠 Education / Research | An AI-powered academic assistant that performs advanced academic searches, analyzes recent publications, synthesizes findings across disciplines, and writes well-structured academic reports with proper citations. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/research_agent_exa.py) | | 🧠 Research Agent | 🗞️ Media & Journalism | A research agent that combines web search and professional journalistic writing. It performs deep investigations and produces NYT-style reports. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/research_agent.py) | | 🍳 Recipe Creator | 🍽️ Food & Culinary | An AI-powered recipe recommendation agent that provides personalized recipes based on ingredients, preferences, and time constraints. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/recipe_creator.py) | | 🗞️ Finance Agent | 💼 Finance | A powerful financial analyst agent combining real-time stock data, analyst insights, company fundamentals, and market news. Ideal for analyzing companies like Apple, Tesla, NVIDIA, and sectors like semiconductors or automotive. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/finance_agent.py) | | 🧠 Financial Reasoning Agent | 📈 Finance | Uses a Claude-3.5 Sonnet-based agent to analyze stocks like NVDA using tools for reasoning and Yahoo Finance data. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/reasoning_finance_agent.py) | | 🤖 Readme Generator Agent | 💻 Software Dev | Agent generates high-quality READMEs for GitHub repositories using repo metadata. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/readme_generator.py) | | 🎬 Movie Recommendation Agent | 🎥 Entertainment | An intelligent agent that gives personalized movie recommendations using Exa and GPT-4o, analyzing genres, themes, and latest ratings. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/movie_recommedation.py) | | 🔍 Media Trend Analysis Agent | 📰 Media & News | Analyzes emerging trends, patterns, and influencers from digital platforms using AI-powered agents and scraping. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/media_trend_analysis_agent.py) | | ⚖️ Legal Document Analysis Agent | 🏛️ Legal Tech | An AI agent that analyzes legal documents from PDF URLs and provides legal insights based on a knowledge base using vector embeddings and GPT-4o. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/legal_consultant.py) | | 🤔 DeepKnowledge | 🧠 Research | This agent performs iterative searches through its knowledge base, breaking down complex queries into sub-questions and synthesizing comprehensive answers. It uses Agno docs for demonstration and is designed for deep reasoning and exploration. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/deep_knowledge.py) | | 📚 Book Recommendation Agent | 🧠 Publishing & Media | An intelligent agent that provides personalized book suggestions using literary data, reader preferences, reviews, and release info. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/book_recommendation.py) | | 🏠 MCP Airbnb Agent | 🛎️ Hospitality | Create an AI Agent using MCP and Llama 4 to search Airbnb listings with filters like workspace & transport proximity. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/airbnb_mcp.py) | | 🤖 Assist Agent | 🧠 AI Framework | An AI agent using GPT-4o to answer questions about the Agno framework with hybrid search and embedded knowledge. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/agno_assist.py) | ### **Framework Name**: **Langgraph** > **UseCase** | Use Case | Industry | Description | Notebook | | :------------------------------------ | :---------------------------- | :----------------------------------------------------------- | :----------------------------------------------------------- | | 🤖 Chatbot Simulation Evaluation | 💻 💬 AI / Quality Assurance | Simulate user interactions to evaluate chatbot performance, ensuring robustness and reliability in real-world scenarios. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb) | | 🧠 Information Gathering via Prompting | 🧠 AI / Research & Development | This tutorial demonstrates how to design a LangGraph workflow that utilizes prompting techniques to gather information effectively. It showcases how to structure prompts and manage the flow of information to build intelligent agents. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/chatbots/information-gather-prompting.ipynb) | | 🧠 Code Assistant with LangGraph | 💻 Software Development | This tutorial demonstrates how to build a resilient code assistant using LangGraph. It guides you through creating a graph-based agent that can handle code generation, error checking, and iterative refinement, ensuring robust and accurate coding assistance. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/code_assistant/langgraph_code_assistant.ipynb) | | 🧑‍💼 Customer Support Agent | 🧑‍💼 Customer Support Agent | This tutorial demonstrates how to build a customer support agent using LangGraph. It guides you through creating a graph-based agent that can handle customer inquiries, providing automated support and enhancing user experience. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/customer-support/customer-support.ipynb) | | 🔁 Extraction with Retries | 🧠 AI / Data Extraction | This tutorial demonstrates how to implement retry mechanisms in LangGraph workflows, ensuring robust data extraction processes that can handle transient errors and improve reliability. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/extraction/retries.ipynb) | | 🧠 Multi-Agent Workflow | 🧠 AI / Workflow Orchestration | This tutorial demonstrates how to build a multi-agent system using LangGraph's agent supervisor. It guides you through creating a supervisor agent that orchestrates multiple specialized agents, managing task delegation and communication flow. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/agent_supervisor.ipynb) | | 🧠 Hierarchical Agent Teams | 🧠 AI / Workflow Orchestration | This tutorial demonstrates how to build a hierarchical agent system using LangGraph. It guides you through creating a top-level supervisor agent that delegates tasks to specialized sub-agents, enabling complex workflows with clear task delegation and communication. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/hierarchical_agent_teams.ipynb) | | 🤝 Multi-Agent Collaboration | 🧠 AI / Workflow Orchestration | This tutorial demonstrates how to implement multi-agent collaboration using LangGraph. It guides you through creating multiple specialized agents that work together to accomplish a complex task, showcasing the power of agent collaboration in AI workflows. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/multi-agent-collaboration.ipynb) | | 🧠 Plan-and-Execute Agent | 🧠 AI / Workflow Orchestration | This tutorial demonstrates how to build a "Plan-and-Execute" style agent using LangGraph. It guides you through creating an agent that first generates a multi-step plan and then executes each step sequentially, revisiting and modifying the plan as necessary. This approach is inspired by the Plan-and-Solve paper and the Baby-AGI project, aiming to enhance long-term planning and task execution in AI workflows. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/plan-and-execute/plan-and-execute.ipynb) | | 🧠 SQL Agent | 🧠 AI / Database Interaction | This tutorial demonstrates how to build an agent that can answer questions about a SQL database. The agent fetches available tables, determines relevance to the question, retrieves schemas, generates a query, checks for errors, executes it, and formulates a response. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/sql-agent.ipynb) | | 🧠 Reflection Agent | 🧠 AI / Workflow Orchestration | This tutorial demonstrates how to build a reflection agent using LangGraph. It guides you through creating an agent that can critique and revise its own outputs, enhancing the quality and reliability of generated content. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/reflection/reflection.ipynb)| | 🧠 Reflexion Agent | 🧠 AI / Workflow Orchestration | This tutorial demonstrates how to build a reflexion agent using LangGraph. It guides you through creating an agent that can reflect on its actions and outcomes, enabling iterative improvement and more accurate decision-making in complex workflows. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/reflexion/reflexion.ipynb)| | **LangGraph Agentic RAG** | | | | | 🧠 **Adaptive RAG** | 🧠 AI / Information Retrieval | This tutorial demonstrates how to build an Adaptive RAG system using LangGraph. It guides you through creating a dynamic retrieval process that adjusts based on query complexity, enhancing the efficiency and accuracy of information retrieval. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_adaptive_rag.ipynb) | | 🧠 **Adaptive RAG (Local)** | 🧠 AI / Information Retrieval | This tutorial focuses on implementing Adaptive RAG with local models, allowing for offline retrieval and generation, which is crucial for environments with limited internet access or privacy concerns. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_adaptive_rag_local.ipynb) | | 🤖 **Agentic RAG** | 🤖 AI / Intelligent Agents | Learn to build an Agentic RAG system where an agent determines the best retrieval strategy before generating a response, improving the relevance and accuracy of answers. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_agentic_rag.ipynb) | | 🤖 **Agentic RAG (Local)** | 🤖 AI / Intelligent Agents | This tutorial extends Agentic RAG to local environments, enabling the use of local models and data sources for retrieval and generation tasks. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_agentic_rag_local.ipynb) | | 🧠 **Corrective RAG (CRAG)** | 🧠 AI / Information Retrieval | Implement a Corrective RAG system that evaluates and refines retrieved documents before passing them to the generator, ensuring higher-quality outputs. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_crag.ipynb) | | 🧠 **Corrective RAG (Local)** | 🧠 AI / Information Retrieval | This tutorial focuses on building a Corrective RAG system using local resources, allowing for offline document evaluation and refinement processes. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_crag_local.ipynb) | | 🧠 **Self-RAG** | 🧠 AI / Information Retrieval | Learn to implement Self-RAG, where the system reflects on its responses and retrieves additional information if necessary, enhancing the accuracy and relevance of generated content. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_self_rag.ipynb) | | 🧠 **Self-RAG (Local)** | 🧠 AI / Information Retrieval | This tutorial demonstrates how to implement Self-RAG using local models and data sources, enabling offline reflection and retrieval processes. | [![AI Agent Code - Python](https://img.shields.io/static/v1?label=AI+Agent+Code&message=Python&color=%23244cd1)](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_self_rag_local.ipynb) | --- ## 🤝 Contributing Contributions are welcome! 🎉 Here's how you can help: 1. Fork the repository. 2. Add a new use case or improve an existing one. 3. Submit a pull request with your changes. Please follow our [Contributing Guidelines](CONTRIBUTING.md) for more details. --- ## 📜 License This repository is licensed under the MIT License. See the [LICENSE](LICENSE) file for more information. --- ## 🚀 Let's Build Together! Feel free to share this repository with your network and star ⭐ it if you find it useful. Let’s collaborate to create the ultimate resource for AI agent use cases!