sk_presidential_votes.py

from langchain_community.llms import OpenAI
from langchain_community.tools import DuckDuckGoSearchRun
from dotenv import load_dotenv
load_dotenv()
search_tool = DuckDuckGoSearchRun()

import os
from crewai import Agent, Task, Crew, Process

# Define your agents with roles and goals
researcher = Agent(
  role='Senior Research Analyst',
  goal='Manage latest news on political events',
  backstory="""You work as editor-in-chief of a large newspaper publishing house.
  Your expertise lies in identifying emerging trends.
  You have a knack for dissecting complex data and presenting plain sample facts.""",
  verbose=True,
  allow_delegation=False,
  tools=[search_tool]

)
writer = Agent(
  role='Content Publisher',
  goal='Craft bulletpoint content on the politics',
  backstory="""You are a renowned Content writer, known for your insightful and engaging articles.
  You transform recived events in comprehensible bulletpoints.""",
  verbose=True,
  allow_delegation=True
)

# Create tasks for your agents
task1 = Task(
  description="""Conduct a comprehensive analysis of the latest presidential votes in Slovakia.
  Identify key trends, breakthrough events, and potential impacts to the future politics.""",
  expected_output="Full analysis report in bullet points",
  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.""",
  expected_output="Full blog post of at least 4 paragraphs",
  agent=writer
)

# Instantiate your crew with a sequential process
crew = Crew(
  agents=[researcher, writer],
  tasks=[task1],
  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)