Upload MarketingPostGeneratorAgent.py
Browse files- MarketingPostGeneratorAgent.py +153 -0
MarketingPostGeneratorAgent.py
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from typing import List
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from crewai import Agent, Crew, Process, Task
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from crewai.project import CrewBase, agent, crew, task
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from crewai_tools import SerperDevTool, ScrapeWebsiteTool
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from pydantic import BaseModel, Field
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import os
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# Model options
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llm_models = [
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"gemini/gemini-1.5-flash",
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"gemini/gemini-1.5-pro",
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"gemini/gemini-pro"
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]
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selected_model = llm_models[0]
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def set_model(selected_model_name):
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global selected_model
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selected_model = selected_model_name
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def configure_api_keys(gemini_api_key):
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if not gemini_api_key:
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raise ValueError("Gemini API key is required")
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os.environ['GEMINI_API_KEY'] = gemini_api_key
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# Pydantic models for output validation
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class MarketStrategy(BaseModel):
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"""Market strategy model"""
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name: str = Field(..., description="Name of the market strategy")
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tatics: List[str] = Field(..., description="List of tactics to be used in the market strategy")
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channels: List[str] = Field(..., description="List of channels to be used in the market strategy")
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KPIs: List[str] = Field(..., description="List of KPIs to be used in the market strategy")
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class CampaignIdea(BaseModel):
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"""Campaign idea model"""
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name: str = Field(..., description="Name of the campaign idea")
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description: str = Field(..., description="Description of the campaign idea")
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audience: str = Field(..., description="Audience of the campaign idea")
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channel: str = Field(..., description="Channel of the campaign idea")
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class Copy(BaseModel):
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"""Copy model"""
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title: str = Field(..., description="Title of the copy")
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body: str = Field(..., description="Body of the copy")
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@CrewBase
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class MarketingPostsCrew:
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"""MarketingPosts crew"""
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agents_config = 'config/MarketingPostGeneratorAgent/agents.yaml'
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tasks_config = 'config/MarketingPostGeneratorAgent/tasks.yaml'
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@agent
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def lead_market_analyst(self) -> Agent:
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return Agent(
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config=self.agents_config['lead_market_analyst'],
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tools=[SerperDevTool(), ScrapeWebsiteTool()],
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verbose=True,
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memory=False,
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llm=selected_model
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)
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@agent
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def chief_marketing_strategist(self) -> Agent:
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return Agent(
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config=self.agents_config['chief_marketing_strategist'],
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tools=[SerperDevTool(), ScrapeWebsiteTool()],
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verbose=True,
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memory=False,
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llm=selected_model
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)
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@agent
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def creative_content_creator(self) -> Agent:
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return Agent(
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config=self.agents_config['creative_content_creator'],
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verbose=True,
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memory=False,
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llm=selected_model
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)
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@task
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def research_task(self) -> Task:
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return Task(
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config=self.tasks_config['research_task'],
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agent=self.lead_market_analyst()
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)
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@task
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def project_understanding_task(self) -> Task:
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return Task(
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config=self.tasks_config['project_understanding_task'],
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agent=self.chief_marketing_strategist()
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)
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@task
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def marketing_strategy_task(self) -> Task:
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return Task(
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config=self.tasks_config['marketing_strategy_task'],
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agent=self.chief_marketing_strategist(),
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output_json=MarketStrategy
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)
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@task
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def campaign_idea_task(self) -> Task:
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return Task(
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config=self.tasks_config['campaign_idea_task'],
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agent=self.creative_content_creator(),
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output_json=CampaignIdea
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)
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@task
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def copy_creation_task(self) -> Task:
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return Task(
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config=self.tasks_config['copy_creation_task'],
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agent=self.creative_content_creator(),
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context=[self.marketing_strategy_task(), self.campaign_idea_task()],
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output_json=Copy
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)
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@crew
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def crew(self) -> Crew:
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"""Creates the MarketingPosts crew"""
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return Crew(
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agents=self.agents, # Automatically created by the @agent decorator
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tasks=self.tasks, # Automatically created by the @task decorator
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process=Process.sequential,
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verbose=True,
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)
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def run_crew_mpga(gemini_api_key, inputs):
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"""
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Run the MarketingPosts crew using the provided Gemini API key and inputs.
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Args:
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gemini_api_key (str): The Gemini API key to configure the environment.
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inputs (dict): Input parameters required by the tasks (e.g., customer_domain, project_description).
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Returns:
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The final output from the crew kickoff.
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"""
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try:
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configure_api_keys(gemini_api_key)
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crew_instance = MarketingPostsCrew().crew()
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result = crew_instance.kickoff(inputs=inputs)
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return result
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except Exception as e:
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return f"Error: {str(e)}"
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