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import streamlit as st
from dotenv import load_dotenv
import os
# Load environment variables
load_dotenv()
os.environ['SERPER_API_KEY'] = os.getenv('SERPER_API_KEY')
os.environ['GOOGLE_API_KEY'] = os.getenv('GOOGLE_API_KEY')
# Import necessary modules from crewai
from crewai_tools import SerperDevTool
from crewai import Agent, Task, Crew, Process
from langchain_google_genai import ChatGoogleGenerativeAI
# Initialize the tool for internet searching capabilities
tool = SerperDevTool()
# Call the Gemini models
llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash", verbose=True, temperature=0.5, google_api_key=os.getenv("GOOGLE_API_KEY"))
# Creating a senior researcher agent with memory and verbose mode
news_researcher = Agent(
role="Senior Researcher",
goal='Uncover groundbreaking technologies in {topic}',
verbose=True,
memory=True,
backstory=(
"Driven by curiosity, you're at the forefront of innovation, eager to explore and share knowledge that could change the world."
),
tools=[tool],
llm=llm,
allow_delegation=True
)
# Creating a writer agent with custom tools responsible for writing news blog
news_writer = Agent(
role='Writer',
goal='Narrate compelling tech stories about {topic}',
verbose=True,
memory=True,
backstory=(
"With a flair for simplifying complex topics, you craft engaging narratives that captivate and educate, bringing new discoveries to light in an accessible manner."
),
tools=[tool],
llm=llm,
allow_delegation=False
)
# Research task
research_task = Task(
description=(
"Identify the next big trend in {topic}. Focus on identifying pros and cons and the overall narrative. Your final report should clearly articulate the key points, its market opportunities, and potential risks."
),
expected_output='A comprehensive 3 paragraphs long report on the latest AI trends.',
tools=[tool],
agent=news_researcher,
)
# Writing task with language model configuration
write_task = Task(
description=(
"Compose an insightful article on {topic}. Focus on the latest trends and how it's impacting the industry. This article should be easy to understand, engaging, and positive."
),
expected_output='A 4 paragraph article on {topic} advancements formatted as markdown.',
tools=[tool],
agent=news_writer,
async_execution=False,
output_file='new-blog-post.md'
)
# Forming the tech-focused crew with some enhanced configuration
crew = Crew(
agents=[news_researcher, news_writer],
tasks=[research_task, write_task],
process=Process.sequential,
)
# Streamlit app
def main():
st.title("AI News Generation")
# Input for the topic
topic = st.text_input("Enter the topic for research", "AI in healthcare")
if st.button("Generate Report and Article"):
result = crew.kickoff(inputs={'topic': topic})
st.success("Task execution completed!")
st.subheader("Research Report")
st.write(result.get(research_task))
st.subheader("News Article")
st.write(result.get(write_task))
# Display the content of the generated markdown file (if it exists)
if os.path.exists('new-blog-post.md'):
with open('new-blog-post.md', 'r') as file:
st.markdown(file.read())
if __name__ == "__main__":
main()
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