import os
import logging
from langchain_openai import OpenAI
from langchain_core.prompts import PromptTemplate
from langchain_core.runnables import RunnableSequence
import time

def summarize_text(text):
    """Summarizes the given text using LangChain with OpenAI."""
    prompt_template = PromptTemplate(
        input_variables=["text"],
        template="Please summarize the following text:\n\n{text}"
    )

    llm = OpenAI(temperature=0.7)  # Adjust the temperature for creativity
    summarization_chain = RunnableSequence(prompt_template | llm)

    max_retries = 3
    for attempt in range(max_retries):
        try:
            summary = summarization_chain.invoke({"text": text})
            return summary
        except Exception as e:
            if 'insufficient_quota' in str(e) and attempt < max_retries - 1:
                print(f'Quota exceeded. Retrying in {2 ** attempt} seconds...')
                time.sleep(2 ** attempt)  # Exponential backoff
            else:
                logging.error(f'An error occurred: {e}')
                raise e

if __name__ == "__main__":
    # Ensure the blogs folder exists
    if not os.path.exists('blogs'):
        os.makedirs('blogs')

    # Get the transcription file path from the user
    transcription_file_path = input("Enter the path to the transcription file: ")

    # Read the transcription text
    try:
        with open(transcription_file_path, 'r') as file:
            transcription_text = file.read()

        # Summarize the transcription text
        summary = summarize_text(transcription_text)

        # Save the summary to a text file in the blogs folder
        summary_file_path = os.path.join('blogs', os.path.basename(transcription_file_path).replace('.txt', '_summary.txt'))
        with open(summary_file_path, 'w') as summary_file:
            summary_file.write(summary)

        print(f"Summary saved to: {summary_file_path}")
    except Exception as e:
        logging.error(f'An error occurred while processing the transcription file: {e}')