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import os | |
from crewai import Agent, Task, Crew, Process | |
from crewai_tools import SerperDevTool | |
from langchain_openai import ChatOpenAI | |
from dotenv import load_dotenv | |
load_dotenv() | |
search_tool = SerperDevTool() | |
# Define agents with roles and goals | |
researcher = Agent( | |
role = "Senior Research Assistant", | |
goal = "Look up the latest Advancements in AI Agents", | |
backstory = """ | |
You work at a leading tech think tank. | |
Your expertise lies in searching Google for AI Agent frameworks. | |
You have a knack for dissecting complex data and presenting actionable insights. | |
""", | |
verbose = True, | |
allow_delegation = False, | |
tools=[search_tool], | |
llm=ChatOpenAI(model_name="gpt-3.5-turbo-0125", temperature=0.2) | |
) | |
writer = Agent( | |
role = "Professional Short-Article Writer", | |
goal = "Summarise the latest advancement in AI agents in a concise artcle", | |
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, | |
llm=ChatOpenAI(model_name="gpt-3.5-turbo-0125", temperature=0.7) | |
) | |
# Create tasks for the agents | |
research = Task( | |
description=""" | |
Conduct a comprehensive analysis of the latest advancements in AI Agents in April of 2024. | |
Identify key trends, breakthrough technologies, and potential industry impacts. | |
""", | |
expected_output="Full analysis in bullet points", | |
agent=researcher | |
) | |
write = Task( | |
description=""" | |
Using the insights provided, write a short article that highlights the most significat AI Agent 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 3 paragraphs", | |
agent=writer | |
) | |
# Instantiate your crew with a sequential process | |
crew = Crew( | |
agents=[researcher,writer], | |
tasks=[research,write], | |
verbose=1 | |
) | |
result = crew.kickoff() | |
print("####") | |
print(result) |