autogenra 0.0.10a0

Autogen Assistant UI

AutoGen Assistant

AutoGen Assistant is an Autogen-powered AI app (user interface) that can converse with you to help you conduct research, write and execute code, run saved skills, create new skills (explicitly and by demonstration), and adapt in response to your interactions.

Capabilities / Roadmap

Some of the capabilities supported by the app frontend include the following:

• Select fron a list of agents (current support for two agent workflows - UserProxyAgent and AssistantAgent)
• Modify agent configuration (e.g. temperature, model, agent system message, model etc) and chat with updated agent configurations.
• View agent messages and output files in the UI from agent runs.
• Support for more complex agent workflows (e.g. GroupChat workflows)
• Improved user experience (e.g., streaming intermediate model output, better summarization of agent responses, etc)

Project Structure:

• autogenra/ code for the backend classes and web api (FastAPI)
• frontend/ code for the webui, built with Gatsby and Tailwind

Installation

1. Install from PyPi

   We recommend using a virtual environment (e.g., conda) to avoid conflicts with existing Python packages. With Python 3.10 or newer active in your virtual environment, use pip to install AutoGen Assistant:

   pip install autogenra
   

2. Install from Source

   Note: This approach requires some familiarity with building interfaces in React.

   If you prefer to install from source, ensure you have Python 3.10+ and Node.js (version above 14.15.0) installed. Here's how you get started:

   • Clone the AutoGen Assistant repository and install its Python dependencies:

     pip install -e .
     

   • Navigate to the samples/apps/autogen-assistant/frontend directory, install dependencies, and build the UI:

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

   For Windows users, to build the frontend, you may need alternative commands to build the frontend.

   ```bash
   
   gatsby clean && rmdir /s /q ..\\autogenra\\web\\ui && (set \"PREFIX_PATH_VALUE=\" || ver>nul) && gatsby build --prefix-paths && xcopy /E /I /Y public ..\\autogenra\\web\\ui
   
   ````
   

Running the Application

Once installed, run the web UI by entering the following in your terminal:

autogenra ui --port 8081

This will start the application on the specified port. Open your web browser and go to http://localhost:8081/ to begin using AutoGen Assistant.

Now that you have AutoGen Assistant installed and running, you are ready to explore its capabilities, including defining and modifying agent workflows, interacting with agents and sessions, and expanding agent skills.

Capabilities

This demo focuses on the research assistant use case with some generalizations:

• Skills: The agent is provided with a list of skills that it can leverage while attempting to address a user's query. Each skill is a python function that may be in any file in a folder made availabe to the agents. We separate the concept of global skills available to all agents backend/files/global_utlis_dir and user level skills backend/files/user/<user_hash>/utils_dir, relevant in a multi user environment. Agents are aware skills as they are appended to the system message. A list of example skills is available in the backend/global_utlis_dir folder. Modify the file or create a new file with a function in the same directory to create new global skills.

• Conversation Persistence: Conversation history is persisted in an sqlite database database.sqlite.

• Default Agent Workflow: The default a sample workflow with two agents - a user proxy agent and an assistant agent.

Example Usage

Let us use a simple query demonstrating the capabilities of the research assistant.

Plot a chart of NVDA and TESLA stock price YTD. Save the result to a file named nvda_tesla.png

The agents responds by writing and executing code to create a python program to generate the chart with the stock prices.

Note than there could be multiple turns between the AssistantAgent and the UserProxyAgent to produce and execute the code in order to complete the task.

Note: You can also view the debug console that generates useful information to see how the agents are interacting in the background.

FAQ

Q: How can I add more skills to the AutoGen Assistant? A: You can extend the capabilities of your agents by adding new Python functions. The AutoGen Assistant interface also lets you directly paste functions that can be reused in the agent workflow.

Q: Where can I adjust the agent configurations and settings? A: You can modify agent configurations directly from the UI or by editing the default configurations in the utils.py file under the get_default_agent_config() method (assuming you are building your own UI).

Q: If I want to reset the conversation with an agent, how do I go about it? A: To reset your conversation history, you can delete the database.sqlite file. If you need to clear user-specific data, remove the relevant autogenra/web/files/user/<user_id_md5hash> folder.

Q: Is it possible to view the output and messages generated by the agents during interactions? A: Yes, you can view the generated messages in the debug console of the web UI, providing insights into the agent interactions. Alternatively, you can inspect the database.sqlite file for a comprehensive record of messages.

Acknowledgements

AutoGen assistant is Based on the AutoGen project. It is adapted in October 2023 from a research prototype (original credits: Gagan Bansal, Adam Fourney, Victor Dibia, Piali Choudhury, Saleema Amershi, Ahmed Awadallah, Chi Wang)