History

Eric Zhu 025490a1bd Use class hierarchy to organize AgentChat message types and introduce StructuredMessage type (#5998 ) This PR refactored `AgentEvent` and `ChatMessage` union types to abstract base classes. This allows for user-defined message types that subclass one of the base classes to be used in AgentChat. To support a unified interface for working with the messages, the base classes added abstract methods for: - Convert content to string - Convert content to a `UserMessage` for model client - Convert content for rendering in console. - Dump into a dictionary - Load and create a new instance from a dictionary This way, all agents such as `AssistantAgent` and `SocietyOfMindAgent` can utilize the unified interface to work with any built-in and user-defined message type. This PR also introduces a new message type, `StructuredMessage` for AgentChat (Resolves #5131), which is a generic type that requires a user-specified content type. You can create a `StructuredMessage` as follow: ```python class MessageType(BaseModel): data: str references: List[str] message = StructuredMessage[MessageType](content=MessageType(data="data", references=["a", "b"]), source="user") # message.content is of type `MessageType`. ``` This PR addresses the receving side of this message type. To produce this message type from `AssistantAgent`, the work continue in #5934. Added unit tests to verify this message type works with agents and teams.		2025-03-26 16:19:52 -07:00
..
.gitignore	adding streamlit sample app (#5306 )	2025-01-31 12:19:16 -08:00
README.md	adding streamlit sample app (#5306 )	2025-01-31 12:19:16 -08:00
agent.py	Use class hierarchy to organize AgentChat message types and introduce StructuredMessage type (#5998 )	2025-03-26 16:19:52 -07:00
main.py	fix: type issues in streamlit sample and add streamlit to dev dependencies (#5309 )	2025-01-31 14:06:59 -08:00

README.md

Streamlit AgentChat Sample Application

This is a sample AI chat assistant built with Streamlit

Setup

Install the streamlit package with the following command:

pip install streamlit

To use Azure OpenAI models or models hosted on OpenAI-compatible API endpoints, you need to install the autogen-ext[openai,azure] package. You can install it with the following command:

pip install "autogen-ext[openai,azure]"
# pip install "autogen-ext[openai]" for OpenAI models

Create a new file named model_config.yml in the the same directory as the script to configure the model you want to use.

For example, to use gpt-4o-mini model from Azure OpenAI, you can use the following configuration:

provider: autogen_ext.models.openai.AzureOpenAIChatCompletionClient
config:
  azure_deployment: "gpt-4o-mini"
  model: gpt-4o-mini
  api_version: REPLACE_WITH_MODEL_API_VERSION
  azure_endpoint: REPLACE_WITH_MODEL_ENDPOINT
  api_key: REPLACE_WITH_MODEL_API_KEY

For more information on how to configure the model and use other providers, please refer to the Models documentation.

Run

Run the following command to start the web application:

streamlit run main.py