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In this sample, we will demonstrate how to build simple chat interface that
interacts with an AgentChat
agent or a team, using Chainlit,
and support streaming messages.
To run this sample, you will need to install the following packages:
pip install -U chainlit autogen-agentchat autogen-ext[openai] pyyaml
To use other model providers, you will need to install a different extra
for the autogen-ext package.
See the Models documentation for more information.
Create a configuration file named model_config.yaml to configure the model
you want to use. Use model_config_template.yaml as a template.
The first sample demonstrate how to interact with a single AssistantAgent
from the chat interface.
chainlit run app_agent.py -h
You can use one of the starters. For example, ask "What the weather in Seattle?".
The agent will respond by first using the tools provided and then reflecting
on the result of the tool execution.
The second sample demonstrate how to interact with a team of agents from the
chat interface.
chainlit run app_team.py -h
You can use one of the starters. For example, ask "Write a poem about winter.".
The team is a RoundRobinGroupChat, so each agent will respond in turn.
There are two agents in the team: one is instructed to be generally helpful
and the other one is instructed to be a critic and provide feedback.
The two agents will respond in round-robin fashion until
the 'APPROVE' is mentioned by the critic agent.
The third sample demonstrate how to interact with a team of agents including
a UserProxyAgent
for approval or rejection.
chainlit run app_team_user_proxy.py -h
You can use one of the starters. For example, ask "Write code to reverse a string.".
By default, the UserProxyAgent will request an input action from the user
to approve or reject the response from the team.
When the user approves the response, the UserProxyAgent will send a message
to the team containing the text "APPROVE", and the team will stop responding.
There are a few ways you can extend this example:
This is a mirror of AutoGen from GitHub. AutoGen is a framework that enables the development of LLM applications using multiple agents that can converse with each other to solve tasks.
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