import asyncio
import streamlit as st
from pydantic_ai import Agent
from pydantic_ai.models.groq import GroqModel
import nest_asyncio
import pdfplumber
import os

api_key = os.getenv("API_KEY")
data = []

#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

model = GroqModel('llama-3.1-70b-versatile', api_key = api_key)

async def ppt_content(data):
    agent = Agent(model,system_prompt=(
        "You are an expert in making power-point perssentation",
        "Convert the content of the attached PDF into PowerPoint slides",
        "Title Slide: Include the document's title, subtitle, author, and date.",
        "Methodology Slide: Summarize the methodology in bullet points",
        "Results Slide: Present key findings using tables or charts.",
        "Discussion Slide: Summarize the implications and limitations.",
        "Conclusion Slide: State the overall conclusion.",
        "Reference Slide: Include all citations used."
    ))
    result_1 = agent.run_sync(user_prompt=data)
    print(result_1.data)

def ai_ppt(data):
    asyncio.run(ppt_content(data=data))


def extract_data(feed):
    
    with pdfplumber.open(feed) as pdf:
        pages = pdf.pages
        for p in pages:
            data.append(p.extract_text())
    return None 

uploaded_file = st.file_uploader('Choose your .pdf file', type="pdf")
if uploaded_file is not None:
    df = extract_data(uploaded_file)

if data is not None:
    st.caption(data)
    ai_ppt(data=data)

# if __name__ == '__main__':
#     import asyncio
#     nest_asyncio.apply()
#     asyncio.run(ppt_content())