summarize_and_question.ipynb

{
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  {
   "cell_type": "code",
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   "source": [
    "import tkinter as tk\n",
    "from tkinter import filedialog, simpledialog, messagebox\n",
    "import docx\n",
    "import pdfplumber\n",
    "from transformers import pipeline, T5Tokenizer\n",
    "import threading\n",
    "import torch\n",
    "import textwrap\n",
    "\n",
    "def read_document(file_path):\n",
    "    \"\"\"Reads text from a Word or PDF document and returns it as a string.\"\"\"\n",
    "    if file_path.endswith(\".docx\"):\n",
    "        document = docx.Document(file_path)\n",
    "        paragraphs = document.paragraphs\n",
    "        text = \"\"\n",
    "        for paragraph in paragraphs:\n",
    "            text += paragraph.text + \"\\n\"\n",
    "        return text\n",
    "    elif file_path.endswith(\".pdf\"):\n",
    "        with pdfplumber.open(file_path) as pdf:\n",
    "            text = \"\"\n",
    "            for page in pdf.pages:\n",
    "                text += page.extract_text() + \"\\n\"\n",
    "            return text\n",
    "    else:\n",
    "        return None\n",
    "\n",
    "def split_text_into_chunks(text, max_chunk_length):\n",
    "    \"\"\"Splits a text into smaller chunks of the specified length.\"\"\"\n",
    "    paragraphs = text.split(\"\\n\")\n",
    "    chunks = []\n",
    "    current_chunk = \"\"\n",
    "\n",
    "    for paragraph in paragraphs:\n",
    "        if len(current_chunk) + len(paragraph) < max_chunk_length:\n",
    "            current_chunk += paragraph + \"\\n\"\n",
    "        else:\n",
    "            chunks.append(current_chunk.strip())\n",
    "            current_chunk = paragraph + \"\\n\"\n",
    "\n",
    "    if current_chunk:\n",
    "        chunks.append(current_chunk.strip())\n",
    "\n",
    "    return chunks\n",
    "\n",
    "def summarize_document():\n",
    "    if uploaded_file_path:\n",
    "        threading.Thread(target=background_summarize, args=(uploaded_file_path,)).start()\n",
    "        progress_label.config(text=\"Summarizing...\", fg=\"blue\")\n",
    "    else:\n",
    "        progress_label.config(text=\"Please upload a Word or PDF document.\", fg=\"red\")\n",
    "\n",
    "def background_summarize(file_path):\n",
    "    document_text = read_document(file_path)\n",
    "\n",
    "    if document_text:\n",
    "        summarizer = pipeline(\"summarization\", model=\"t5-base\", tokenizer=\"t5-base\")\n",
    "\n",
    "        # Split the text into chunks\n",
    "        text_chunks = split_text_into_chunks(document_text, max_chunk_length=1500)\n",
    "        summarized_chunks = []\n",
    "\n",
    "        for chunk in text_chunks:\n",
    "            # Manually set max_length to a lower value\n",
    "            max_len = 115  # Adjust as needed\n",
    "            summary = summarizer(chunk, max_length=max_len, min_length=100, do_sample=True, top_k=50, top_p=0.95)\n",
    "            summarized_chunks.append(summary[0]['summary_text'])\n",
    "\n",
    "        # Join the summarized chunks\n",
    "        summarized_text = \"\\n\".join(summarized_chunks)\n",
    "\n",
    "        # Display the summary in the tkinter interface\n",
    "        result_text.delete(1.0, tk.END)\n",
    "        result_text.insert(tk.END, summarized_text)\n",
    "\n",
    "        progress_label.config(text=\"Summarize\", fg=\"black\")\n",
    "        show_checkmark()\n",
    "    else:\n",
    "        progress_label.config(text=\"Unsupported document type.\", fg=\"red\")\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def max_length(input_length):\n",
    "    \"\"\"Creates a summary with a maximum length of 30% of the input text.\n",
    "\n",
    "    Args:\n",
    "        input_length (str): The input text.\n",
    "\n",
    "    Returns:\n",
    "        int: The maximum length of the summary.\n",
    "    \"\"\"\n",
    "    input_length = len(input_length)\n",
    "    if not isinstance(input_length, int):\n",
    "        input_length = int(input_length)\n",
    "\n",
    "    return int(input_length * 0.3)\n",
    "\n",
    "def upload_word_document():\n",
    "    # Opens a file selection dialog and selects the Word document\n",
    "    global uploaded_file_path\n",
    "    uploaded_file_path = filedialog.askopenfilename(filetypes=[(\"Word Document\", \"*.docx\"), (\"PDF Document\", \"*.pdf\"), (\"All Files\", \"*.*\")])\n",
    "    \n",
    "    if uploaded_file_path:\n",
    "        show_checkmark()  # Displays a green checkmark\n",
    "\n",
    "def ask_question():\n",
    "    # Provides a warning to the user if they have not uploaded a file\n",
    "    if not uploaded_file_path:\n",
    "        progress_label.config(text=\"Please upload a Word document.\", fg=\"red\")\n",
    "        return\n",
    "\n",
    "    # Opens a dialog to ask the user a question about the uploaded text\n",
    "    question = simpledialog.askstring(\"Ask a Question!\", \"Ask a question about the uploaded text:\")\n",
    "    if question:\n",
    "        # Initiates the question-answering process in a separate thread\n",
    "        threading.Thread(target=background_answer_question, args=(uploaded_file_path, question)).start()\n",
    "\n",
    "def background_answer_question(file_path, question):\n",
    "    # Provides feedback to the user while the question-answering process is running\n",
    "    progress_label.config(text=\"Answering...\", fg=\"blue\")\n",
    "\n",
    "    # Retrieves the answer to the question\n",
    "    answer = answer_question(file_path, question)\n",
    "\n",
    "    # Displays the answer on the screen\n",
    "    result_text.delete(1.0, tk.END)  # Clears the previous content\n",
    "    result_text.insert(tk.END, \"Question: \" + question + \"\\nAnswer: \" + answer)\n",
    "\n",
    "    # Resets the progress label and shows a green checkmark when the process is complete\n",
    "    progress_label.config(text=\"Answered\", fg=\"black\")\n",
    "    show_checkmark()\n",
    "\n",
    "def answer_question(file_path, question):\n",
    "    # Retrieves the text from the file path\n",
    "    document_text = read_document(file_path)\n",
    "    question_answerer = pipeline(\"question-answering\", model='distilbert-base-cased-distilled-squad')\n",
    "    \n",
    "    # Uses the model to find the answer to the question\n",
    "    answer = question_answerer(context=document_text, question=question)\n",
    "    \n",
    "    return answer[\"answer\"]\n",
    "\n",
    "def show_checkmark():\n",
    "    # Displays a green checkmark (large and next to it)\n",
    "    checkmark_label.config(text=\"✓\", fg=\"green\", font=(\"Arial\", 24))  # Large and green checkmark\n",
    "\n",
    "# Create a tkinter window\n",
    "root = tk.Tk()\n",
    "root.title(\"Word Document Summarizer\")\n",
    "\n",
    "# Upload file button\n",
    "upload_file_button = tk.Button(root, text=\"Upload Document\", command=upload_word_document)\n",
    "upload_file_button.pack(side=tk.LEFT, padx=10)\n",
    "\n",
    "# Summarize button\n",
    "summarize_button = tk.Button(root, text=\"Summarize Document\", command=summarize_document)\n",
    "summarize_button.pack(side=tk.LEFT, padx=10)\n",
    "\n",
    "# Uploaded file path (initially empty)\n",
    "uploaded_file_path = None\n",
    "\n",
    "# Ask a question button\n",
    "question_button = tk.Button(root, text=\"Ask a Question!\", command=ask_question, bg=\"red\", fg=\"white\", font=(\"Arial\", 11))\n",
    "question_button.pack(side=tk.BOTTOM, padx=5, pady=5)\n",
    "\n",
    "# Text box to display the summarized text\n",
    "result_text = tk.Text(root, wrap=tk.WORD, width=40, height=10)\n",
    "result_text.pack(padx=10, pady=10)\n",
    "\n",
    "# Label to display progress during processing\n",
    "progress_label = tk.Label(root, text=\"\", fg=\"black\")\n",
    "progress_label.pack()\n",
    "\n",
    "# Label to display a green checkmark\n",
    "checkmark_label = tk.Label(root, text=\"\", fg=\"green\")\n",
    "checkmark_label.pack()\n",
    "\n",
    "root.mainloop()\n"
   ]
  }
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