import streamlit as st
from crewai import Crew, Agent, Process
from tools import tool
from dotenv import load_dotenv
import os

# Load environment variables
load_dotenv()

# Initialize Google Generative AI model
from langchain_google_genai import ChatGoogleGenerativeAI
llm = ChatGoogleGenerativeAI(
    model="gemini-1.5-flash",
    verbose=True,
    temperature=0.5,
    google_api_key= "AIzaSyDy02GtpV6-VcdeCZNLJT-c4kWuPxBRbrI"
)

# Define agents
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
)

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
)

# Define tasks
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,
)

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'  # Example of output customization
)

# Define Crew
crew = Crew(
    agents=[news_researcher, news_writer],
    tasks=[research_task, write_task],
    process=Process.sequential,
)

# Streamlit UI
st.set_page_config(
    page_title="Tech Research and Writing",
    page_icon="🔬",
    layout="wide",
    menu_items={"About": "# Made by Prathamesh Khade"}
)

st.title("Tech Research and Writing")

topic = st.text_input("Enter a topic to research and write about:")

if st.button("Start Task"):
    if topic:
        result = crew.kickoff(inputs={'topic': topic})
        st.write("Task Results:")
        st.write(result)
    else:
        st.error("Please enter a topic.")