import torch
import gradio as gr
from transformers import pipeline
from PyPDF2 import PdfReader  # Alternative for PDF handling
from docx import Document  # For handling .docx files

model_path = ("../Models/models--deepset--roberta-base-squad2/snapshots"
              "/cbf50ba81465d4d8676b8bab348e31835147541b")

question_answer = pipeline("question-answering",
                           model="deepset/roberta-base-squad2")

def read_file_content(file_obj):
    try:
        # Determine the file extension
        file_extension = file_obj.name.split('.')[-1].lower()

        if file_extension == 'txt':
            # Reading text files
            with open(file_obj.name, 'r', encoding='utf-8') as file:
                context = file.read()

        elif file_extension == 'pdf':
            # Reading PDF files using PyPDF2
            reader = PdfReader(file_obj.name)
            context = ""
            for page in reader.pages:
                context += page.extract_text()

        elif file_extension == 'docx':
            # Reading Word documents using python-docx
            doc = Document(file_obj.name)
            context = "\n".join([para.text for para in doc.paragraphs])

        else:
            return "Unsupported file format. Please upload a .txt, .pdf, or .docx file."

        return context

    except Exception as e:
        return f"An error occurred: {e}"

def get_answer(file, question):
    context = read_file_content(file)
    if "An error occurred" in context or "Unsupported" in context:
        return context  # Return error message directly if present
    answer = question_answer(question=question, context=context)
    return answer["answer"]

demo = gr.Interface(
    fn=get_answer,
    inputs=[
        gr.File(label="Upload your file"),
        gr.Textbox(label="Input your question", lines=1)
    ],
    outputs=[gr.Textbox(label="Answer text", lines=1)],
    title="Explore Documents",
    description="THIS APPLICATION WILL BE USED TO ANSWER QUESTIONS BASED ON CONTEXT PROVIDED."
)

demo.launch()