coding_pub_sub.py: a code execution example with two agents, one for calling tool and one for executing the tool, to demonstrate tool use and reflection on tool use. This example uses broadcast communication.
coding_direct_with_intercept.py: an example showing human-in-the-loop for approving or denying tool execution.
mixture_of_agents.py: An example of how to create a mixture of agents.
multi_agent_debate.py: An example of how to create a sparse multi-agent debate pattern.
assistant.py: a demonstration of how to use the OpenAI Assistant API to create a ChatGPT agent.
chest_game.py: an example with two chess player agents that executes its own tools to demonstrate tool use and reflection on tool use.
slow_human_in_loop.py: an example showing human-in-the-loop which waits for human input before making the tool call.

Running the examples

Prerequisites

First, you need a shell with AutoGen core and required dependencies installed.

Using Azure OpenAI API

For Azure OpenAI API, you need to set the following environment variables:

export OPENAI_API_TYPE=azure
export AZURE_OPENAI_API_ENDPOINT=your_azure_openai_endpoint
export AZURE_OPENAI_API_VERSION=your_azure_openai_api_version

By default, we use Azure Active Directory (AAD) for authentication. You need to run az login first to authenticate with Azure. You can also use API key authentication by setting the following environment variables:

export AZURE_OPENAI_API_KEY=your_azure_openai_api_key

This requires azure-identity installation:

pip install azure-identity

Using OpenAI API

For OpenAI API, you need to set the following environment variables.

export OPENAI_API_TYPE=openai
export OPENAI_API_KEY=your_openai_api_key

Running

To run an example, just run the corresponding Python script. For example:

hatch shell
python core/one_agent_direct.py

Or simply:

hatch run python core/one_agent_direct.py