Unraid-CrewAI-Sample.py

### This is the code sample from crewai's readme.md file. If you haven't you'll need to run pip install crewai and pip install duckduckgo-search

import os
from crewai import Agent, Task, Crew

### Remove the comment below and add your key if your OPENAI_API_KEY is not set in your environment variables
#os.environ["OPENAI_API_KEY"] = "YOUR KEY" 

from langchain_community.tools import DuckDuckGoSearchRun ### langchain.tools was depracated so I updated the import to langchain_community.tools
search_tool = DuckDuckGoSearchRun()

# Define your agents with roles and goals
researcher = Agent(
  role='Senior Research Analyst',
  goal='Uncover cutting-edge developments in AI and data science',
  backstory='You work at a leading tech think tank. Your expertise lies in identifying emerging trends. You have a knack for dissecting complex data and presenting actionable insights.',
  verbose=True,
  allow_delegation=False,
  tools=[search_tool]
)
writer = Agent(
  role='Tech Content Strategist',
  goal='Craft compelling content on tech advancements',
  backstory='You are a renowned Content Strategist, known for your insightful and engaging articles. You transform complex concepts into compelling narratives.',
  verbose=True,
  allow_delegation=True,
)

# Create tasks for your agents
task1 = Task(
  description='Conduct a comprehensive analysis of the latest advancements in AI in 2024. Identify key trends, breakthrough technologies, and potential industry impacts. Your final answer MUST be a full analysis report',
  agent=researcher
)

task2 = Task(
  description='Using the insights provided, develop an engaging blog post that highlights the most significant AI advancements. Your post should be informative yet accessible, catering to a tech-savvy audience. Make it sound cool, avoid complex words so it doesn\'t sound like AI. Your final answer MUST be the full blog post of at least 4 paragraphs.',
  agent=writer
)

# Instantiate your crew with a sequential process
crew = Crew(
  agents=[researcher, writer],
  tasks=[task1, task2],
  verbose=2, # You can set it to 1 or 2 to different logging levels
)

# Get your crew to work!
result = crew.kickoff()

print("######################")
print(result)