Workflows in LlamaIndex - Tutorial to Build Complex AI Applications with Events

 This video shows how to install and use LlamaIndex Workflows which is a mechanism for orchestrating actions in the increasingly complex AI application.

Code:

conda create -n workflow python=3.11 -y && conda activate workflow

pip install llama-index

pip install llama-index-llms-openai

conda install jupyter -y

pip uninstall charset_normalizer -y

pip install charset_normalizer

jupyter notebook

from llama_index.core.workflow import (

    Event,

    StartEvent,

    StopEvent,

    Workflow,

    step,

)

from llama_index.llms.openai import OpenAI

class WeatherEvent(Event):

    location: str

    forecast: str | None

class WeatherFlow(Workflow):

    llm = OpenAI()

    @step()

    async def get_location(self, ev: StartEvent) -> WeatherEvent:

        location = "Sydney"

        forecast = ""  # or some default value

        return WeatherEvent(location=location, forecast=forecast)

    @step()

    async def get_forecast(self, ev: WeatherEvent) -> WeatherEvent:

        location = ev.location

        prompt = f"Get the current weather forecast for {location}."

        response = await self.llm.acomplete(prompt)

        return WeatherEvent(location=location, forecast=str(response))

    @step()

    async def format_forecast(self, ev: WeatherEvent) -> StopEvent:

        location = ev.location

        forecast = ev.forecast

        formatted_forecast = f"Weather in {location}: {forecast}"

        return StopEvent(result=formatted_forecast)

w = WeatherFlow(timeout=60, verbose=False)

result = await w.run()

print(str(result))