import streamlit as st
from transformers import pipeline
import logging
from PyPDF2 import PdfReader

# Setup logging
def setup_logging():
    logging.basicConfig(
        level=logging.INFO,
        format='%(asctime)s - %(levelname)s - %(message)s',
        handlers=[
            logging.StreamHandler()
        ]
    )

# Function to extract text from a PDF file
def extract_text_from_pdf(pdf_file):
    pdf_reader = PdfReader(pdf_file)
    text = ""
    for page in pdf_reader.pages:
        text += page.extract_text()
    return text

def main():
    setup_logging()
    logging.info("Starting the Streamlit app.")

    # Initialize the summarization pipeline
    summarizer = pipeline("summarization")

    # Streamlit UI
    st.title("GenAI Lab Report Analyzer")
    st.write("Upload a file, record audio, or type text to generate a summary. Select the appropriate input type and provide the input.")

    input_type = st.radio(
        "Select Input Type:",
        options=["Text", "Text File", "PDF", "DOCX", "Audio"],
        index=0
    )

    file = None
    text = None
    audio = None

    if input_type == "Text":
        text = st.text_area("Enter your text here:", placeholder="Type your text here...")
    elif input_type == "Text File":
        file = st.file_uploader("Upload your text file:", type=["txt"])
    elif input_type == "PDF":
        file = st.file_uploader("Upload your PDF file:", type=["pdf"])
    elif input_type == "DOCX":
        file = st.file_uploader("Upload your DOCX file:", type=["docx"])
    elif input_type == "Audio":
        audio = st.file_uploader("Upload your audio file:", type=["wav", "mp3", "m4a"])

    if st.button("Report Result"):
        try:
            summary = None
            if input_type == "Text" and text:
                logging.info("Processing text input.")
                summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
                logging.info("Text input processed successfully.")
            elif input_type == "Text File" and file:
                logging.info(f"Processing text file: {file.name}")
                text = file.read().decode("utf-8")  # Assuming UTF-8 encoding
                summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
            elif input_type == "PDF" and file:
                logging.info(f"Processing PDF file: {file.name}")
                text = extract_text_from_pdf(file)
                summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
            elif input_type == "Audio" and audio:
                logging.info("Processing audio input.")
                # Add audio processing logic here
                summary = "Audio processing not implemented yet."
            else:
                summary = "Invalid input. Please provide a valid file or text."
                logging.warning("Invalid input type provided.")

            st.text_area("Report Result:", summary[0]['summary_text'] if isinstance(summary, list) else summary, height=200)
        except Exception as e:
            logging.error(f"Error during summarization: {e}")
            st.error("An error occurred during summarization. Please check the logs for more details.")

    logging.info("Closing the Streamlit app.")

if __name__ == "__main__":
    main()