crew.py

import os

from crewai import LLM, Agent, Crew, Process, Task
from crewai.project import CrewBase, agent, crew, task
from dotenv import load_dotenv
from models import *

load_dotenv()

@CrewBase
class SizzleReelCrew:
    """Sizzle Reel Script Generation Crew"""
    
    def __init__(self, inputs, *args, **kwargs):
        super().__init__(*args, **kwargs)
        # Get OpenAI API key from environment
        openai_api_key = os.getenv('OPENAI_API_KEY')
        if not openai_api_key:
            raise ValueError("OpenAI API Key is not set. Please set the OPENAI_API_KEY environment variable.")
        
        # Configure LLM with explicit provider
        self.llm = LLM(
            model="openai/gpt-4.1-nano",
            temperature=0.7,
            api_key=openai_api_key
        )
        self.inputs = inputs
        
        # self.llm = LLM(
        # model="gemini/gemini-2.0-flash-lite",
        # temperature=0.7,
        # api_key=os.getenv('GEMINI_API_KEY')
        # )

    @agent
    def hero_research_specialist(self) -> Agent:
        return Agent(
            config=self.agents_config['hero_research_specialist'],
            verbose=True,
            llm=self.llm  # Use the configured LLM
        )

    @agent
    def content_strategist(self) -> Agent:
        return Agent(
            config=self.agents_config['content_strategist'],
            verbose=True,
            llm=self.llm  # Use the configured LLM
        )

    @agent
    def narrative_scriptwriter(self) -> Agent:
        return Agent(
            config=self.agents_config['narrative_scriptwriter'],
            verbose=True,
            llm=self.llm  # Use the configured LLM
        )

    @task
    def hero_research_task(self) -> Task:
        return Task(
            description=f"""Identify the hero user and their primary use case. Understand why they would use the app and what problem it solves for them.
            Identify the hero-user, hero-usecase, and hero user journey from app name {self.inputs['app_name']}.
            App Description: {self.inputs['customer_idea']}""",
            expected_output="""Outline the steps the hero user takes in their journey within the app, from start to finish.""",
            agent=self.hero_research_specialist(),
            output_pydantic=HeroResearchOutput
        )

    @task
    def content_plan_task(self) -> Task:
        return Task(
            description=f"""Generate a detailed content plan for the sizzle reel for App {self.inputs['app_name']}""",
            expected_output="""A detailed content plan for the sizzle reel""",
            agent=self.content_strategist(),
            context=[self.hero_research_task()]
        )

    @task
    def script_generation_task(self) -> Task:
        return Task(
            description=f"""Develop the final script for the sizzle reel for app: '{self.inputs['app_name']}', including engaging narrations and screen actions for each step in the hero's journey.""",
            expected_output="""A detailed script with narrations and screen actions.""",
            agent=self.narrative_scriptwriter(),
            output_pydantic=ScriptOutput,
            context=[self.hero_research_task(), self.content_plan_task()]
        )

    @crew
    def crew(self) -> Crew:
        return Crew(
            agents=self.agents,
            tasks=self.tasks,
            process=Process.sequential,
            verbose=True,
            llm=self.llm  # Use the configured LLM for the entire crew
        )