add chainlit sample (microsoft#4749)

* add chainlit sample

* readme updates

* put team inside run to avoid problems

* simplify example and add readme

* inform user team is reset

---------

Co-authored-by: Hussein Mozannar <[email protected]>

python/samples/agentchat_chainlit/.gitignore

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+build
+dist
+
+*.egg-info
+
+.env
+
+*.files
+
+venv
+.venv
+.DS_Store
+
+.chainlit
+!cypress/e2e/**/*/.chainlit/*
+chainlit.md
+
+cypress/screenshots
+cypress/videos
+cypress/downloads
+
+__pycache__
+
+.ipynb_checkpoints
+
+*.db
+
+.mypy_cache
+
+chat_files
+
+.chroma
+
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+dist
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?
+
+.aider*
+.coverage
+
+backend/README.md
+backend/.dmypy.json

python/samples/agentchat_chainlit/README.md

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+# Building a Multi-Agent Application with AutoGen and Chainlit
+
+In this sample, we will build a simple chat interface that interacts with a `RoundRobinGroupChat` team built using the [AutoGen AgentChat](https://microsoft.github.io/autogen/dev/user-guide/agentchat-user-guide/index.html) api.
+
+![AgentChat](docs/chainlit_autogen.png).
+
+## High-Level Description
+
+The `app.py` script sets up a Chainlit chat interface that communicates with the AutoGen team. When a chat starts, it
+
+- Initializes an AgentChat team.
+
+```python
+
+async def get_weather(city: str) -> str:
+    return f"The weather in {city} is 73 degrees and Sunny."
+
+assistant_agent = AssistantAgent(
+    name="assistant_agent",
+    tools=[get_weather],
+    model_client=OpenAIChatCompletionClient(
+        model="gpt-4o-2024-08-06"))
+
+
+termination = TextMentionTermination("TERMINATE") | MaxMessageTermination(10)
+team = RoundRobinGroupChat(
+    participants=[assistant_agent], termination_condition=termination)
+
+```
+
+- As users interact with the chat, their queries are sent to the team which responds.
+- As agents respond/act, their responses are streamed back to the chat interface.
+
+## Quickstart
+
+To get started, ensure you have setup an API Key. We will be using the OpenAI API for this example.
+
+1. Ensure you have an OPENAPI API key. Set this key in your environment variables as `OPENAI_API_KEY`.
+
+2. Install the required Python packages by running:
+
+```shell
+pip install -r requirements.txt
+```
+
+3. Run the `app.py` script to start the Chainlit server.
+
+```shell
+chainlit run app.py -h
+```
+
+4. Interact with the Agent Team Chainlit interface. The chat interface will be available at `http://localhost:8000` by default.
+
+### Function Definitions
+
+- `start_chat`: Initializes the chat session
+- `run_team`: Sends the user's query to the team streams the agent responses back to the chat interface.
+- `chat`: Receives messages from the user and passes them to the `run_team` function.
+
+
+## Adding a UserProxyAgent
+
+We can add a `UserProxyAgent` to the team so that the user can interact with the team directly with the input box in the chat interface. This requires defining a function for input that uses the Chainlit input box instead of the terminal.
+
+```python
+from typing import Optional
+from autogen_core import CancellationToken
+from autogen_agentchat.agents import AssistantAgent, UserProxyAgent
+from autogen_agentchat.conditions import TextMentionTermination, MaxMessageTermination
+from autogen_agentchat.teams import RoundRobinGroupChat
+from autogen_ext.models.openai import OpenAIChatCompletionClient
+
+async def chainlit_input_func(prompt: str, cancellation_token: Optional[CancellationToken] = None) -> str:
+    try:
+        response = await cl.AskUserMessage(
+            content=prompt,
+            author="System",
+        ).send()
+        return response["output"]
+
+    except Exception as e:
+        raise RuntimeError(f"Failed to get user input: {str(e)}") from e
+
+user_proxy_agent = UserProxyAgent(
+    name="user_proxy_agent",
+    input_func=chainlit_input_func,
+)
+assistant_agent = AssistantAgent(
+    name="assistant_agent",
+    model_client=OpenAIChatCompletionClient(
+        model="gpt-4o-2024-08-06"))
+
+termination = TextMentionTermination("TERMINATE") | MaxMessageTermination(10)
+
+team = RoundRobinGroupChat(
+    participants=[user_proxy_agent, assistant_agent],
+    termination_condition=termination)
+```
+
+
+
+## Next Steps (Extra Credit)
+
+In this example, we created a basic AutoGen team with a single agent in a RoundRobinGroupChat team. There are a few ways you can extend this example:
+
+- Add more [agents](https://microsoft.github.io/autogen/dev/user-guide/agentchat-user-guide/tutorial/agents.html) to the team.
+- Explor custom agents that sent multimodal messages
+- Explore more [team](https://microsoft.github.io/autogen/dev/user-guide/agentchat-user-guide/tutorial/teams.html) types beyond the `RoundRobinGroupChat`.

python/samples/agentchat_chainlit/app.py

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+import chainlit as cl
+from autogen_agentchat.agents import AssistantAgent
+from autogen_agentchat.conditions import TextMentionTermination, MaxMessageTermination
+from autogen_agentchat.teams import RoundRobinGroupChat
+from autogen_ext.models.openai import OpenAIChatCompletionClient
+from autogen_agentchat.base import TaskResult
+
+
+async def get_weather(city: str) -> str:
+    return f"The weather in {city} is 73 degrees and Sunny."
+
+
+@cl.on_chat_start
+async def start_chat():
+    cl.user_session.set(
+        "prompt_history",
+        "",
+    )
+
+
+async def run_team(query: str):
+    assistant_agent = AssistantAgent(
+        name="assistant_agent", tools=[get_weather], model_client=OpenAIChatCompletionClient(model="gpt-4o-2024-08-06")
+    )
+
+    termination = TextMentionTermination("TERMINATE") | MaxMessageTermination(10)
+    team = RoundRobinGroupChat(participants=[assistant_agent], termination_condition=termination)
+
+    response_stream = team.run_stream(task=query)
+    async for msg in response_stream:
+        if hasattr(msg, "content"):
+            msg = cl.Message(content=msg.content, author="Agent Team")
+            await msg.send()
+        if isinstance(msg, TaskResult):
+            msg = cl.Message(content="Termination condition met. Team and Agents are reset.", author="Agent Team")
+            await msg.send()
+
+
+@cl.on_message
+async def chat(message: cl.Message):
+    await run_team(message.content)

python/samples/agentchat_chainlit/requirements.txt

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+chainlit
+autogen-agentchat==0.4.0.dev11