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autogen/website/docs/Examples.md
Nicolas Marchildon 17c51fd2f0
Enable defining new functions after agent creation (#285) 
* Enable defining new functions after agent creation

* Add notebook for function inception example

* format

* 1. fix bug 2. support remove function

* 1. fix bug 2. support remove function

* 1. add example doc 2. change test file 3. change ipynb title

* Update website/docs/Examples.md

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Co-authored-by: Li Jiang <bnujli@gmail.com>
Co-authored-by: “skzhang1” <“shaokunzhang529@gmail.com”>
Co-authored-by: Shaokun Zhang <shaokunzhang529@gmail.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
2023-12-02 01:05:54 +00:00

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Examples

Automated Multi Agent Chat

AutoGen offers conversable agents powered by LLM, tool or human, which can be used to perform tasks collectively via automated chat. This framework allows tool use and human participation via multi-agent conversation. Please find documentation about this feature here.

Links to notebook examples:

  1. Code Generation, Execution, and Debugging

    • Automated Task Solving with Code Generation, Execution & Debugging - View Notebook
    • Auto Code Generation, Execution, Debugging and Human Feedback - View Notebook
    • Automated Code Generation and Question Answering with Retrieval Augmented Agents - View Notebook
    • Automated Code Generation and Question Answering with Qdrant based Retrieval Augmented Agents - View Notebook

  2. Multi-Agent Collaboration (>3 Agents)

    • Automated Task Solving with GPT-4 + Multiple Human Users - View Notebook
    • Automated Task Solving by Group Chat (with 3 group member agents and 1 manager agent) - View Notebook
    • Automated Data Visualization by Group Chat (with 3 group member agents and 1 manager agent) - View Notebook
    • Automated Complex Task Solving by Group Chat (with 6 group member agents and 1 manager agent) - View Notebook
    • Automated Task Solving with Coding & Planning Agents - View Notebook
    • Automated Task Solving with agents divided into 2 groups - View Notebook
    • Automated Task Solving with transition paths specified in a graph - View Notebook

  3. Applications

    • Automated Chess Game Playing & Chitchatting by GPT-4 Agents - View Notebook
    • Automated Continual Learning from New Data - View Notebook
    • OptiGuide - Coding, Tool Using, Safeguarding & Question Anwering for Supply Chain Optimization

  4. Tool Use

    • Web Search: Solve Tasks Requiring Web Info - View Notebook
    • Use Provided Tools as Functions - View Notebook
    • Task Solving with Langchain Provided Tools as Functions - View Notebook
    • RAG: Group Chat with Retrieval Augmented Generation (with 5 group member agents and 1 manager agent) - View Notebook
    • In-depth Guide to OpenAI Utility Functions - View Notebook
    • Function Inception: Enable AutoGen agents to update/remove functions during conversations. - View Notebook

  5. Agent Teaching and Learning

    • Teach Agents New Skills & Reuse via Automated Chat - View Notebook
    • Teach Agents New Facts, User Preferences and Skills Beyond Coding - View Notebook

  6. Multi-Agent Chat with OpenAI Assistants in the loop

  7. Multimodal Agent

Tune GPT Models

AutoGen also offers a cost-effective hyperparameter optimization technique EcoOptiGen for tuning Large Language Models. The research study finds that tuning hyperparameters can significantly improve the utility of them. Please find documentation about this feature here.

Links to notebook examples: