dream-team
This repo helps you to build a team of AI agents with Autogen
Stars: 87
Build your dream team with Autogen is a repository that leverages Microsoft Autogen 0.4, Azure OpenAI, and Streamlit to create an end-to-end multi-agent application. It provides an advanced multi-agent framework based on Magentic One, with features such as a friendly UI, single-line deployment, secure code execution, managed identities, and observability & debugging tools. Users can deploy Azure resources and the app with simple commands, work locally with virtual environments, install dependencies, update configurations, and run the application. The repository also offers resources for learning more about building applications with Autogen.
README:
This repository leverages Microsoft Autogen 0.4, Azure OpenAI and integrates it with Streamlit, to build an end to end multi agents application, this repo makes it easy to build test and deploy an advanced multi agent framework, based on Magentic One
🎉 December 3, 2024: The repo now support one click deployment with Azure Developer CLI, if you would like to run it with the full process localy you can check v0.21
🎉 November 18, 2024: we are porting this repo to Autogen 0.4, A new event driven, asynchronous architecture for AutoGen and Magentic One
Dream Team offers the following key features:
- Advanced multi agent framework: this solution is based on the popular framework Autogen(35K stars) and Magentic One
- Friendly UI: easy way to build and share data apps powered by Streamlit
- Single line deployment: developer-friendly deployment that accelerates your path from a local development environment to Azure with single line of code - azd up.
- Secure code execution: Fast access to secure sandboxed with strong isolation environments that are ideal for running code or applications with Azure Container Apps dynamic sessions.
- Managed Identities: Built in Azure Managed identities to eliminate the need for developers to manage these credentials
- Observability & Debugging: Built-in features and tools for tracking, tracing, and debugging agent interactions and workflows, including PromptFlow tracing.
- Install Azure Developer CLI.
- Ensure you have access to an Azure subscription
- Docker - Follow the official Docker installation instructions
- Python version >= 3.8, < 3.13
- Install UV - optional for running locally
git clone https://github.com/Azure-Samples/dream-team
azd auth login
You need to choose your preferred region (you can start with east us or sweden central or any other available region)
azd up
cd src
Set up a virtual environment (Preferred)
uv venv
Once you’ve created a virtual environment, you may activate it.
On Windows, run:
.venv\Scripts\activate
On Unix or MacOS, run:
source .venv/bin/activate
To deactivate :
deactivate
More information about virtual environments can be found here
uv sync
git clone --depth 1 --branch v0.4.0.dev11 https://github.com/microsoft/autogen.git
cd autogen/python/packages/autogen-magentic-one
uv pip install -e .
- Navigate to src folder
cd ../../../..
playwright install --with-deps chromium
- If you used AZD to deploy the resources just run the code below
azd env get-values > .env
- Alternatively, copy
.env.sample
(under src) into.env
Important: Magentic-One code uses code execution, you need to have Docker installed to run the examples if you use local execution
streamlit run app.py
If your app is ready, you can browse to (typically) http://localhost:8501 to see the app in action.
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