magentic_ui 0.1.6
A research prototype of a human-centered interface powered by a multi-agent system
Requires Python: >=3.10
Keywords: agents, ai-assistant, browser-use, multi-agent, playwright, web-automation

<div align="center">
<img src="docs/img/magui-readme-logo.svg" alt="Magentic-UI Logo">


_Automate your web tasks while you stay in control_

[![image](https://img.shields.io/pypi/v/magentic_ui.svg)](https://pypi.python.org/pypi/magentic_ui)
[![image](https://img.shields.io/pypi/l/magentic_ui.svg)](https://pypi.python.org/pypi/magentic_ui)
![Python Versions](https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue)
[![arXiv](https://img.shields.io/badge/arXiv-2507.22358-b31b1b.svg)](https://arxiv.org/abs/2507.22358)

</div>

---

Magentic-UI is a **research prototype** human-centered AI agent that solves complex web and coding tasks that may require monitoring. Unlike other black-box agents, the system reveals its plan before executions, lets you guide its actions, and requests approval for sensitive operations while browsing websites, executing code, and analyzing files.
*Check out the [demo section](#demos) for inspiration on what tasks you can accomplish.*

## ✨ What's New

Microsoft latest agentic model [Fara-7B](https://www.microsoft.com/en-us/research/blog/fara-7b-an-efficient-agentic-model-for-computer-use/) is now integrated in Magentic-UI, read how to launch in <a href="#Magentic-UI with Fara-7B">Fara-7B guide</a>.


- **"Tell me When"**: Automate monitoring tasks and repeatable workflows that require web or API access that span minutes to days. *Learn more [here](https://www.microsoft.com/en-us/research/blog/tell-me-when-building-agents-that-can-wait-monitor-and-act/).*
- **File Upload Support**: Upload any file through the UI for analysis or modification
- **MCP Agents**: Extend capabilities with your favorite MCP servers
- **Easier Installation**: We have uploaded our docker containers to GHCR so you no longer need to build any containers! Installation time now is much quicker.


## 🚀 Quick Start

Here's how you can get started with Magentic-UI:

```bash
# 1. Setup environment
python3 -m venv .venv
source .venv/bin/activate
pip install magentic-ui --upgrade

# 2. Set your API key
export OPENAI_API_KEY="your-api-key-here"

# 3. Launch Magentic-UI
magentic-ui --port 8081
```

Then open <http://localhost:8081> in your browser to interact with Magentic-UI!

> **Prerequisites**: Requires Docker and Python 3.10+. Windows users should use WSL2. See [detailed installation](#️-installation) for more info.

## Alternative Usage Options

**Without Docker** (limited functionality: no code execution):
```bash
magentic-ui --run-without-docker --port 8081
```

**Command Line Interface**:
```bash
magentic-cli --work-dir PATH/TO/STORE/DATA
```

**Custom LLM Clients**:
```bash
# Azure
pip install magentic-ui[azure]

# Ollama (local models)
pip install magentic-ui[ollama]
```

You can then pass a config file to the `magentic-ui` command (<a href="#model-client-configuration"> client config</a>) or change the model client inside the UI settings.

For further details on installation please read the   <a href="#️-installation">🛠️ Installation</a> section. For common installation issues and their solutions, please refer to the [troubleshooting document](TROUBLESHOOTING.md). See advanced usage instructions with the command `magentic-ui --help`. 

## Quick Navigation:
<p align="center">
  <a href="#demos">🎬 Demos</a> &nbsp;|&nbsp;
  <a href="#how-it-works">🟪 How it Works</a> &nbsp;|&nbsp;
  <a href="#️installation">🛠️ Installation</a> &nbsp;|&nbsp;
  <a href="#troubleshooting">⚠️ Troubleshooting</a> &nbsp;|&nbsp; 
  <a href="#contributing">🤝 Contributing</a> &nbsp;|&nbsp;
  <a href="#license">📄 License</a>
</p>

---

## Demos

<table>
<tr>
<td width="33%" align="center">

**🍕 Pizza Ordering**  
*Web automation with human-in-the-loop*

<video src="https://github.com/user-attachments/assets/dc95cf5f-c4b4-4fe0-b708-158ff071e5a9" width="100%" style="max-height: 300px;">
</video>

</td>
<td width="33%" align="center">

**🏠 Airbnb Price Analysis**  
*MCP agent integration*

<video src="https://github.com/user-attachments/assets/c19ed8c2-e06f-43b7-bee3-5e2ffc4c5e02" width="100%" style="max-height: 300px;">
</video>

</td>
<td width="33%" align="center">

**⭐ Star Monitoring**  
*Long-running monitoring task*

<video src="https://github.com/user-attachments/assets/d2a463ca-7a94-4414-932d-a69f30fff63b" width="100%" style="max-height: 300px;">
</video>

</td>
</tr>
</table>



## How it Works
<p align="center">
  <img src="./docs/img/magenticui_running.png" alt="Magentic-UI" height="400">
</p>

Magentic-UI is especially useful for web tasks that require actions on the web (e.g., filling a form, customizing a food order), deep navigation through websites not indexed by search engines (e.g., filtering flights, finding a link from a personal site) or tasks that need web navigation and code execution (e.g., generate a chart from online data).

What differentiates Magentic-UI from other browser use offerings is its transparent and controllable interface that allows for efficient human-in-the-loop involvement. Magentic-UI is built using [AutoGen](https://github.com/microsoft/autogen) and provides a platform to study human-agent interaction and experiment with web agents. Key features include:

- 🧑‍🤝‍🧑 **Co-Planning**: Collaboratively create and approve step-by-step plans using chat and the plan editor.
- 🤝 **Co-Tasking**: Interrupt and guide the task execution using the web browser directly or through chat. Magentic-UI can also ask for clarifications and help when needed.
- 🛡️ **Action Guards**: Sensitive actions are only executed with explicit user approvals.
- 🧠 **Plan Learning and Retrieval**: Learn from previous runs to improve future task automation and save them in a plan gallery. Automatically or manually retrieve saved plans in future tasks.
- 🔀 **Parallel Task Execution**: You can run multiple tasks in parallel and session status indicators will let you know when Magentic-UI needs your input or has completed the task.

<div align="center">
  <a href="https://www.youtube.com/watch?v=wOs-5SR8xOc" target="_blank">
    <img src="https://img.youtube.com/vi/wOs-5SR8xOc/maxresdefault.jpg" alt="Watch the demo video" width="600"/>
  </a>
  <br>
  ▶️ <em> Click to watch a video and learn more about Magentic-UI </em>
</div>


### Autonomous Evaluation

To evaluate its autonomous capabilities, Magentic-UI has been tested against several benchmarks when running with o4-mini: [GAIA](https://huggingface.co/datasets/gaia-benchmark/GAIA) test set (42.52%), which assesses general AI assistants across reasoning, tool use, and web interaction tasks ; [AssistantBench](https://huggingface.co/AssistantBench) test set (27.60%), focusing on realistic, time-consuming web tasks; [WebVoyager](https://github.com/MinorJerry/WebVoyager) (82.2%), measuring end-to-end web navigation in real-world scenarios; and [WebGames](https://webgames.convergence.ai/) (45.5%), evaluating general-purpose web-browsing agents through interactive challenges.
To reproduce these experimental results, please see the following [instructions](experiments/eval/README.md).



If you're interested in reading more checkout our [technical report](https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/magentic-ui-report.pdf) and [blog post](https://www.microsoft.com/en-us/research/blog/magentic-ui-an-experimental-human-centered-web-agent/).


## 🛠️ Installation
### Pre-Requisites

**Note**: If you're using Windows, we highly recommend using [WSL2](https://docs.microsoft.com/en-us/windows/wsl/install) (Windows Subsystem for Linux).

1. If running on **Windows** or **Mac** you should use [Docker Desktop](https://www.docker.com/products/docker-desktop/) or if inside WSL2 you can install Docker directly inside WSL [docker in WSL2 guide](https://gist.github.com/dehsilvadeveloper/c3bdf0f4cdcc5c177e2fe9be671820c7). If running on **Linux**, you should use [Docker Engine](https://docs.docker.com/engine/install/). 

If using Docker Desktop, make sure it is set up to use WSL2:
    - Go to Settings > Resources > WSL Integration
    - Enable integration with your development distro You can find more detailed instructions about this step [here](https://docs.microsoft.com/en-us/windows/wsl/tutorials/wsl-containers).



2. During the Installation step, you will need to set up your `OPENAI_API_KEY`. To use other models, review the [Model Client Configuration](#model-client-configuration) section below.

3. You need at least [Python 3.10](https://www.python.org/downloads/) installed.


If you are on Windows, we recommend to run Magentic-UI inside [WSL2](https://docs.microsoft.com/en-us/windows/wsl/install) (Windows Subsystem for Linux) for correct Docker and file path compatibility.



### PyPI Installation

Magentic-UI is available on PyPI. We recommend using a virtual environment to avoid conflicts with other packages.

```bash
python3 -m venv .venv
source .venv/bin/activate
pip install magentic-ui
```

Alternatively, if you use [`uv`](https://docs.astral.sh/uv/getting-started/installation/) for dependency management, you can install Magentic-UI with:

```bash
uv venv --python=3.12 .venv
. .venv/bin/activate
uv pip install magentic-ui
```


### Running Magentic-UI

To run Magentic-UI, make sure that Docker is running, then run the following command:

```bash
magentic-ui --port 8081
```

>**Note**: Running this command for the first time will pull two docker images required for the Magentic-UI agents. If you encounter problems, you can build them directly with the following command:
```bash
cd docker
sh build-all.sh
```

If you face issues with Docker, please refer to the [TROUBLESHOOTING.md](TROUBLESHOOTING.md) document.

Once the server is running, you can access the UI at <http://localhost:8081>.



### Magentic-UI with Fara-7B

1) First install magentic-ui with the fara extras:

```bash
```bash
python3 -m venv .venv
source .venv/bin/activate
pip install magentic-ui[fara]
```

2) In a seperate process, serve the Fara-7B model using vLLM:

```bash
vllm serve "microsoft/Fara-7B" --port 5000 --dtype auto 
```

3) First create a `fara_config.yaml` file with the following content:

```yaml
model_config_local_surfer: &client_surfer
  provider: OpenAIChatCompletionClient
  config:
    model: "microsoft/Fara-7B"
    base_url: http://localhost:5000/v1
    api_key: not-needed
    model_info:
      vision: true
      function_calling: true
      json_output: false
      family: "unknown" 
      structured_output: false
      multiple_system_messages: false

orchestrator_client: *client_surfer
coder_client: *client_surfer
web_surfer_client: *client_surfer
file_surfer_client: *client_surfer
action_guard_client: *client_surfer
model_client: *client_surfer
```
Note: if you are hosting vLLM on a different port or host, change the `base_url` accordingly.


Then launch Magentic-UI with the fara agent:

```bash
magentic-ui --fara --port 8081 --config fara_config.yaml 
```

Finally, navigate to <http://localhost:8081> to access the interface!

### Configuration

#### Model Client Configuration

If you want to use a different OpenAI key, or if you want to configure use with Azure OpenAI or Ollama, you can do so inside the UI by navigating to settings (top right icon) and changing model configuration. Another option is to pass a yaml config file when you start Magentic-UI which will override any settings in the UI:

```bash
magentic-ui --port 8081 --config config.yaml
```

Where the `config.yaml` should look as follows with an AutoGen model client configuration:

```yaml
gpt4o_client: &gpt4o_client
    provider: OpenAIChatCompletionClient
    config:
      model: gpt-4o-2024-08-06
      api_key: null
      base_url: null
      max_retries: 5

orchestrator_client: *gpt4o_client
coder_client: *gpt4o_client
web_surfer_client: *gpt4o_client
file_surfer_client: *gpt4o_client
action_guard_client: *gpt4o_client
plan_learning_client: *gpt4o_client
```
You can change the client for each of the agents using the config file and use AzureOpenAI (`AzureOpenAIChatCompletionClient`), Ollama and other clients.

#### MCP Server Configuration

You can also extend Magentic-UI's capabilities by adding custom "McpAgents" to the multi-agent team. Each McpAgent can have access to one or more MCP Servers. You can specify these agents via the `mcp_agent_configs` parameter in your `config.yaml`.

For example, here's an agent called "airbnb_surfer" that has access to the OpenBnb MCP Server running locally via Stdio.

```yaml
mcp_agent_configs:
  - name: airbnb_surfer
    description: "The airbnb_surfer has direct access to AirBnB."
    model_client: 
      provider: OpenAIChatCompletionClient
      config:
        model: gpt-4.1-2025-04-14
      max_retries: 10
    system_message: |-
      You are AirBnb Surfer, a helpful digital assistant that can help users acces AirBnB.

      You have access to a suite of tools provided by the AirBnB API. Use those tools to satisfy the users requests.
    reflect_on_tool_use: false
    mcp_servers:
      - server_name: AirBnB
        server_params:
          type: StdioServerParams
          command: npx
          args:
            - -y
            - "@openbnb/mcp-server-airbnb"
            - --ignore-robots-txt
```

Under the hood, each `McpAgent` is just a `autogen_agentchat.agents.AssistantAgent` with the set of MCP Servers exposed as an `AggregateMcpWorkbench` which is simply a named collection of `autogen_ext.tools.mcp.McpWorkbench` objects (one per MCP Server).

Currently the supported MCP Server types are `autogen_ext.tools.mcp.StdioServerParams` and `autogen_ext.tools.mcp.SseServerParams`.

### Building Magentic-UI from source

This step is primarily for users seeking to make modifications to the code, are having trouble with the pypi installation or want the latest code before a pypi version release.

#### 1. Make sure the above prerequisites are installed, and that Docker is running.

#### 2. Clone the repository to your local machine:

```bash
git clone https://github.com/microsoft/magentic-ui.git
cd magentic-ui
```

#### 3. Install Magentic-UI's dependencies with uv or your favorite package manager:

```bash
# install uv through https://docs.astral.sh/uv/getting-started/installation/
uv venv --python=3.12 .venv
uv sync --all-extras
source .venv/bin/activate
```

#### 4. Build the frontend:

First make sure to install node:

```bash
# install nvm to install node
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.40.1/install.sh | bash
nvm install node
```

Then install the frontend:

```bash
cd frontend
npm install -g gatsby-cli
npm install --global yarn
yarn install
yarn build
```

#### 5. Run Magentic-UI, as usual.

```bash
magentic-ui --port 8081
```


#### Running the UI from source

If you are making changes to the source code of the UI, you can run the frontend in development mode so that it will automatically update when you make changes for faster development.

1. Open a separate terminal and change directory to the frontend

```bash
cd frontend
```

2. Create a `.env.development` file.

```bash
cp .env.default .env.development
```

3. Launch frontend server

```bash
npm run start
```

4. Then run the UI:

```bash
magentic-ui --port 8081
```

The frontend from source will be available at <http://localhost:8000>, and the compiled frontend will be available at <http://localhost:8081>.




## Troubleshooting


If you were unable to get Magentic-UI running, do not worry! The first step is to make sure you have followed the steps outlined above, particularly with the [pre-requisites](#pre-requisites).

For common issues and their solutions, please refer to the [TROUBLESHOOTING.md](TROUBLESHOOTING.md) file in this repository. If you do not see your problem there, please open a `GitHub Issue`. 

## Contributing

This project welcomes contributions and suggestions. For information about contributing to Magentic-UI, please see our [CONTRIBUTING.md](CONTRIBUTING.md) guide, which includes current issues to be resolved and other forms of contributing.

This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). For more information, see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.


## Citation

Please cite our paper if you use our work in your research:

```
@article{mozannar2025magentic,
  title={Magentic-UI: Towards Human-in-the-loop Agentic Systems},
  author={Mozannar, Hussein and Bansal, Gagan and Tan, Cheng and Fourney, Adam and Dibia, Victor and Chen, Jingya and Gerrits, Jack and Payne, Tyler and Maldaner, Matheus Kunzler and Grunde-McLaughlin, Madeleine and others},
  journal={arXiv preprint arXiv:2507.22358},
  year={2025}
}
```

## License

Microsoft, and any contributors, grant you a license to any code in the repository under the [MIT License](https://opensource.org/licenses/MIT). See the [LICENSE](LICENSE) file.

Microsoft, Windows, Microsoft Azure, and/or other Microsoft products and services referenced in the documentation
may be either trademarks or registered trademarks of Microsoft in the United States and/or other countries.
The licenses for this project do not grant you rights to use any Microsoft names, logos, or trademarks.
Microsoft's general trademark guidelines can be found at <http://go.microsoft.com/fwlink/?LinkID=254653>.

Any use of third-party trademarks or logos are subject to those third-party's policies.

Privacy information can be found at <https://go.microsoft.com/fwlink/?LinkId=521839>

Microsoft and any contributors reserve all other rights, whether under their respective copyrights, patents, or trademarks, whether by implication, estoppel, or otherwise.