import streamlit as st
from crewai import Agent, Task, Crew
from crewai_tools import YoutubeChannelSearchTool
from langchain_google_genai import ChatGoogleGenerativeAI
from dotenv import load_dotenv
import os
import nest_asyncio

# Load environment variables
load_dotenv()

# Apply nest_asyncio to allow nested event loops
nest_asyncio.apply()

# Initialize Google Gemini AI
llm = ChatGoogleGenerativeAI(
    api_key=os.getenv('GOOGLE_API_KEY'),
    model="models/gemini-pro"  # Replace with the correct model name
)

# Initialize the YoutubeChannelSearchTool without OpenAI dependency
# (Assuming it can be configured to not use OpenAI, or you might need to create a custom search tool)
yt_tool = YoutubeChannelSearchTool(youtube_channel_handle='@krishnaik06', use_openai=False)

# Define Agents
blog_researcher = Agent(
    role='Blog Researcher from Youtube Videos',
    goal='Get the relevant video transcription for the topic {topic} from the provided YT channel',
    backstory=(
        "Expert in understanding videos in AI, Data Science, Machine Learning, and Gen AI and providing suggestions."
    ),
    llm=llm,
    tools=[yt_tool],
    allow_delegation=True,
    verbose=True,
    memory=True
)

blog_writer = Agent(
    role='Blog Writer',
    goal='Narrate compelling tech stories about the video {topic} from YT video',
    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."
    ),
    llm=llm,
    tools=[yt_tool],
    allow_delegation=False,
    verbose=True,
    memory=True
)

# Define Tasks
research_task = Task(
    description=(
        "Identify the video {topic}. "
        "Get detailed information about the video from the channel video."
    ),
    expected_output='A comprehensive 3 paragraphs long report based on the {topic} of video content.',
    agent=blog_researcher,
    tools=[yt_tool]
)

write_task = Task(
    description=(
        "Get the info from the YouTube channel on the topic {topic}."
    ),
    expected_output='Summarize the info from the YouTube channel video on the topic {topic} and create the content for the blog',
    agent=blog_writer,
    tools=[yt_tool],
    async_execution=False,
    output_file='new-blog-post.md'
)

# Define Crew
crew = Crew(
    agents=[blog_researcher, blog_writer],
    tasks=[research_task, write_task],
    verbose=2,
    memory=True,
    cache=True,
    max_rpm=100,
    share_crew=True
)

# Streamlit App
def main():
    st.set_page_config(page_title="AI Blog Generator", page_icon="📝")

    st.title("AI Blog Generator")
    st.write("Enter a topic to generate a blog post based on YouTube videos.")
    
    topic = st.text_input("Topic", "")
    if st.button("Generate Blog Post"):
        if topic:
            with st.spinner("Generating blog post..."):
                try:
                    result = crew.kickoff(inputs={'topic': topic})
                    with open('new-blog-post.md', 'r') as file:
                        blog_content = file.read()
                    st.markdown(blog_content)
                except Exception as e:
                    st.error(f"An error occurred: {e}")
        else:
            st.error("Please enter a topic to continue.")

if __name__ == "__main__":
    main()