multi_agents.py

import asyncio
import sys
import traceback

from beeai_framework.backend import ChatModel
from beeai_framework.emitter import EmitterOptions
from beeai_framework.errors import FrameworkError
from beeai_framework.tools.search.wikipedia import WikipediaTool
from beeai_framework.tools.weather import OpenMeteoTool
from beeai_framework.workflows.agent import AgentWorkflow, AgentWorkflowInput
from examples.helpers.io import ConsoleReader


async def main() -> None:
    llm = ChatModel.from_name("ollama:llama3.1")
    workflow = AgentWorkflow(name="Smart assistant")

    workflow.add_agent(
        name="Researcher",
        role="A diligent researcher.",
        instructions="You look up and provide information about a specific topic.",
        tools=[WikipediaTool()],
        llm=llm,
    )

    workflow.add_agent(
        name="WeatherForecaster",
        role="A weather reporter.",
        instructions="You provide detailed weather reports.",
        tools=[OpenMeteoTool()],
        llm=llm,
    )

    workflow.add_agent(
        name="DataSynthesizer",
        role="A meticulous and creative data synthesizer",
        instructions="You can combine disparate information into a final coherent summary.",
        llm=llm,
    )

    reader = ConsoleReader()

    reader.write("Assistant 🤖 : ", "What location do you want to learn about?")
    for prompt in reader:
        await (
            workflow.run(
                inputs=[
                    AgentWorkflowInput(prompt="Provide a short history of the location.", context=prompt),
                    AgentWorkflowInput(
                        prompt="Provide a comprehensive weather summary for the location today.",
                        expected_output="Essential weather details such as chance of rain, temperature and wind. Only report information that is available.",  # noqa: E501
                    ),
                    AgentWorkflowInput(
                        prompt="Summarize the historical and weather data for the location.",
                        expected_output="A paragraph that describes the history of the location, followed by the current weather conditions.",  # noqa: E501
                    ),
                ]
            )
            .on(
                # Event Matcher -> match agent's 'success' events
                lambda event: isinstance(event.creator, ChatModel) and event.name == "success",
                # log data to the console
                lambda data, event: reader.write(
                    "->Got response from the LLM",
                    "  \n->".join([str(message.content[0].model_dump()) for message in data.value.messages]),
                ),
                EmitterOptions(match_nested=True),
            )
            .on(
                "success",
                lambda data, event: reader.write(
                    f"->Step '{data.step}' has been completed with the following outcome."
                    f"\n\n{data.state.final_answer}\n\n",
                    data.model_dump(exclude={"data"}),
                ),
            )
        )
        reader.write("Assistant 🤖 : ", "What location do you want to learn about?")


if __name__ == "__main__":
    try:
        asyncio.run(main())
    except FrameworkError as e:
        traceback.print_exc()
        sys.exit(e.explain())