https://github.com/ashishpatel26/500-AI-Agents-Projects
The 500 AI Agents Projects is a curated collection of AI agent use cases across various industries. It showcases practical applications and provides links to open-source projects for implementation, illustrating how AI agents are transforming sectors such as healthcare, finance, education, retail, and more.
https://github.com/ashishpatel26/500-AI-Agents-Projects
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The 500 AI Agents Projects is a curated collection of AI agent use cases across various industries. It showcases practical applications and provides links to open-source projects for implementation, illustrating how AI agents are transforming sectors such as healthcare, finance, education, retail, and more.
- Host: GitHub
- URL: https://github.com/ashishpatel26/500-AI-Agents-Projects
- Owner: ashishpatel26
- Created: 2024-12-20T13:37:15.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-01-13T05:35:49.000Z (5 months ago)
- Last Synced: 2025-01-13T06:19:32.215Z (5 months ago)
- Topics: ai-agents, genai
- Homepage: https://github.com/ashishpatel26/500-AI-Agents-Projects
- Size: 1.63 MB
- Stars: 19
- Watchers: 2
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🌟 500+ AI Agent Projects / UseCases
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)
- [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
---
## 🧩 Use Case Table
| Use Case | Industry | Description | Code Github |
| ------------------------------------------- | ---------------- | -------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **AI Health Assistant** | Healthcare | Diagnoses and monitors diseases using patient data. | [](https://github.com/ahmadvh/AI-Agents-for-Medical-Diagnostics.git) |
| **Automated Trading Bot** | Finance | Automates stock trading with real-time market analysis. | [](https://github.com/MingyuJ666/Stockagent.git) |
| **Virtual AI Tutor** | Education | Provides personalized education tailored to users. | [](https://github.com/hqanhh/EduGPT.git) |
| **24/7 AI Chatbot** | Customer Service | Handles customer queries around the clock. | [](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. | [](https://github.com/microsoft/RecAI) |
| **Self-Driving Delivery Agent** | Transportation | Optimizes routes and autonomously delivers packages. | [](https://github.com/sled-group/driVLMe) |
| **Factory Process Monitoring Agent** | Manufacturing | Monitors production lines and ensures quality control. | [](https://github.com/yuchenxia/llm4ias) |
| **Property Pricing Agent** | Real Estate | Analyzes market trends to determine property prices. | [](https://github.com/AleksNeStu/ai-real-estate-assistant) |
| **Smart Farming Assistant** | Agriculture | Provides insights on crop health and yield predictions. | [](https://github.com/mohammed97ashraf/LLM_Agri_Bot) |
| **Energy Demand Forecasting Agent** | Energy | Predicts energy usage to optimize grid management. | [](https://github.com/yecchen/MIRAI) |
| **Content Personalization Agent** | Entertainment | Recommends personalized media based on preferences. | [](https://github.com/crosleythomas/MirrorGPT) |
| **Legal Document Review Assistant** | Legal | Automates document review and highlights key clauses. | [](https://github.com/firica/legalai) |
| **Recruitment Recommendation Agent** | Human Resources | Suggests best-fit candidates for job openings. | [](https://github.com/sentient-engineering/jobber) |
| **Virtual Travel Assistant** | Hospitality | Plans travel itineraries based on preferences. | [](https://github.com/nirbar1985/ai-travel-agent) |
| **AI Game Companion Agent** | Gaming | Enhances player experience with real-time assistance. | [](https://github.com/onjas-buidl/LLM-agent-game) |
| **Real-Time Threat Detection Agent** | Cybersecurity | Identifies potential threats and mitigates attacks. | [](https://github.com/NVISOsecurity/cyber-security-llm-agents) |
| **E-commerce Personal Shopper Agent** | E-commerce | Helps customers find products they’ll love. | [](https://github.com/Hoanganhvu123/ShoppingGPT) |
| **Logistics Optimization Agent** | Supply Chain | Plans efficient delivery routes and manages inventory. | [](https://github.com/microsoft/OptiGuide) |
## 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. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/email_auto_responder_flow) |
| 📝 Meeting Assistant Flow | 🛠️ Productivity | Assists in organizing and managing meetings, including scheduling and agenda preparation. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/meeting_assistant_flow) |
| 🔄 Self Evaluation Loop Flow | 👥 Human Resources | Facilitates self-assessment processes within an organization, aiding in performance reviews. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/self_evaluation_loop_flow) |
| 📈 Lead Score Flow | 💼 Sales | Evaluates and scores potential leads to prioritize outreach in sales strategies. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/lead-score-flow) |
| 📊 Marketing Strategy Generator| 📢 Marketing | Develops marketing strategies by analyzing market trends and audience data. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/marketing_strategy) |
| 📝 Job Posting Generator | 🧑💼 Recruitment | Creates job postings by analyzing job requirements, aiding in recruitment processes. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/job-posting) |
| 🔄 Recruitment Workflow | 🧑💼 Recruitment | Streamlines the recruitment process by automating various tasks involved in hiring. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/recruitment) |
| 🔍 Match Profile to Positions | 🧑💼 Recruitment | Matches candidate profiles to suitable job positions to enhance recruitment efficiency. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/match_profile_to_positions) |
| 📸 Instagram Post Generator | 📱 Social Media | Generates and schedules Instagram posts automatically, streamlining social media management. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/instagram_post) |
| 🌐 Landing Page Generator | 💻 Web Development | Automates the creation of landing pages for websites, facilitating web development tasks. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/landing_page_generator) |
| 🎮 Game Builder Crew | 🎮 Game Development | Assists in the development of games by automating certain aspects of game creation. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/game-builder-crew) |
| 💹 Stock Analysis Tool | 💰 Finance | Provides tools for analyzing stock market data to assist in financial decision-making. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/stock_analysis) |
| 🗺️ Trip Planner | ✈️ Travel | Assists in planning trips by organizing itineraries and managing travel details. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/trip_planner) |
| 🎁 Surprise Trip Planner | ✈️ Travel | Plans surprise trips by selecting destinations and activities based on user preferences. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/surprise_trip) |
| 📚 Write a Book with Flows | ✍️ Creative Writing | Assists authors in writing books by providing structured workflows and writing assistance. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/write_a_book_with_flows) |
| 🎬 Screenplay Writer | ✍️ Creative Writing | Aids in writing screenplays by offering templates and guidance for script development. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/screenplay_writer) |
| ✅ Markdown Validator | 📄 Documentation | Validates Markdown files to ensure proper formatting and adherence to standards. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/markdown_validator) |
| 🧠 Meta Quest Knowledge | 📚 Knowledge Management| Manages and organizes knowledge related to Meta Quest, facilitating information retrieval. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/meta_quest_knowledge) |
| 🤖 NVIDIA Models Integration | 🤖 AI Integration | Integrates NVIDIA AI models into workflows to enhance computational capabilities. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/nvidia_models) |
| 🗂️ Prep for a Meeting | 🛠️ Productivity | Assists in preparing for meetings by organizing materials and setting agendas. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/prep-for-a-meeting) |
| 🛠️Starter Template | 🛠️ Development | Provides a starter template for new projects to streamline the setup process. | [](https://github.com/crewAIInc/crewAI-examples/tree/main/starter_template) |
| 🔗CrewAI + LangGraph Integration| 🤖 AI Integration | Demonstrates integration between CrewAI and LangGraph for enhanced workflow automation.
### **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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](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. | [](https://github.com/microsoft/autogen/blob/0.2/notebook/oai_chatgpt_gpt4.ipynb) |
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## 🤝 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.
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## 📜 License
This repository is licensed under the MIT License. See the [LICENSE](LICENSE) file for more information.
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## 🚀 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!