AI-Powered Summaries

researcher = Agent(
    role="Senior Research Analyst",
    goal="Synthesize research findings into comprehensive analysis",
    backstory="""Expert research analyst who excels at distilling 
                 complex information into clear, actionable summaries 
                 while maintaining accuracy.""",
    verbose=True,
    llm=llm,
)

research_task = Task(
    description="""Synthesize research findings into a comprehensive 
                   and detailed final document with:
                   - Deep analysis of all sources
                   - Identification of key themes and patterns
                   - Cross-referencing of insights
                   - Support for all findings""",
    expected_output="""A markdown document with comprehensive research 
                       analysis, organized into logical sections based on 
                       findings, with proper citations and references""",
    agent=researcher,
    max_retries=5,
)

content_writer = Agent(
    role="Expert Content Writer",
    goal="Transform research into engaging, informative blog posts",
    backstory="""Experienced content writer who creates compelling, 
                 accessible content from complex research while 
                 maintaining accuracy and proper attribution.""",
    verbose=True,
    llm=llm,
)

content_task = Task(
    description="""Create an engaging and informative blog post that:
                   - Uses engaging, authoritative voice
                   - Supports all claims with citations
                   - Includes relevant quotes with attribution
                   - Maintains professional but accessible tone
                   - Provides value to readers""",
    expected_output="""Well-structured blog post in markdown format 
                       with proper citations and clear attribution.""",
    agent=content_writer,
    context=[research_task],  # Uses research task output as context
    max_retries=5,
    output_pydantic=BlogPostTaskResult
)

{
  "blog_post": "# Title\n\n## Introduction\n\n...",
  "title": "Research Topic Title"
}

class BlogPostTaskResult(BaseModel):
    blog_post: str  # Markdown-formatted content
    title: str      # Post title

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="gpt-4o",
    temperature=0.7,
    api_key=os.environ["OPENAI_API_KEY"]
)

research_content_crew = Crew(
    agents=[researcher, content_writer],
    tasks=[research_task, faq_task, content_task],
    verbose=True,
    process=Process.sequential,  # Tasks run in order
    output_log_file=f"logs/research_content_crew_{current_time}.log",
    max_rpm=20  # Rate limit: 20 requests per minute
)

research_content_crew_result = await research_content_crew.kickoff_async(inputs={
    "topic": topic,
    "scraped_data": scraped_data,
    "current_time": current_time,
})