common: Contains common implementations and utilities used by the examples.
core: Contains examples that illustrate the core concepts of AGNext.
tool-use: Contains examples that illustrate tool use in AGNext.
patterns: Contains examples that illustrate how multi-agent patterns can be implemented in AGNext.
demos: Contains interactive demos that showcase applications that can be built using AGNext.

See Running the examples for instructions on how to run the examples.

Core examples

We provide examples to illustrate the core concepts of AGNext: agents, runtime, and message passing.

one_agent_direct.py: A simple example of how to create a single agent powered by ChatCompletion model client. Communicate with the agent using direct communication.
inner_outer_direct.py: A simple example of how to create an agent that calls an inner agent using direct communication.
two_agents_pub_sub.py: An example of how to create two agents that communicate using broadcast communication (i.e., pub/sub).

Tool use examples

We provide examples to illustrate how to use tools in AGNext:

coding_one_agent_direct.py: a code execution example with one agent that calls and executes tools to demonstrate tool use and reflection on tool use. This example uses direct communication.
coding_two_agent_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.
custom_function_tool_one_agent_direct.py: a custom function tool example with one agent that calls and executes tools to demonstrate tool use and reflection on tool use. This example uses direct communication.

We provide examples to illustrate how multi-agent patterns can be implemented in AGNext:

coder_executor.py: An example of how to create a coder-executor reflection pattern. This example creates a plot of stock prices using the Yahoo Finance API.
coder_reviewer.py: An example of how to create a coder-reviewer reflection pattern.
group_chat.py: An example of how to create a round-robin group chat among three agents.
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.

We provide interactive demos that showcase applications that can be built using AGNext:

assistant.py: a demonstration of how to use the OpenAI Assistant API to create a ChatGPT agent.
chat_room.py: An example of how to create a chat room of custom agents without a centralized orchestrator.
illustrator_critics.py: a demo that uses an illustrator, critics and descriptor agent to implement the reflection pattern for image generation.
software_consultancy.py: a demonstration of multi-agent interaction using the group chat pattern.
chest_game.py: an example with two chess player agents that executes its own tools to demonstrate tool use and reflection on tool use.

First, you need a shell with AGNext and the examples dependencies installed. To do this, in the example directory, run:

hatch shell

Then, you need to set the OPENAI_API_KEY environment variable to your OpenAI API key.

export OPENAI_API_KEY=your_openai_api_key

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

export AZURE_OPENAI_API_KEY=your_azure_openai_api_key
export AZURE_OPENAI_ENDPOINT=your_azure_openai_endpoint

By default, OpenAI API is used. To use Azure OpenAI API, set the OPENAI_API_TYPE environment variable to azure.

export OPENAI_API_TYPE=azure

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