Delete app (1).py

app (1).py

@@ -1,84 +0,0 @@
-# -*- coding: utf-8 -*-
-"""app.ipynb
-
-Automatically generated by Colab.
-
-Original file is located at
-    https://colab.research.google.com/drive/1XblbxoRxB4XOHixjGij789FPD9KjKdhi
-"""
-
-import os
-import pdfplumber
-import gradio as gr
-from langchain_groq.chat_models import ChatGroq
-
-# Set Groq API key securely
-GROQ_API_KEY = os.getenv("GROQ_API_KEY")  # Fetch from environment variables
-if not GROQ_API_KEY:
-    raise ValueError("GROQ_API_KEY is not set. Add it in Hugging Face Secrets.")
-
-# Initialize LLM (llama-3.3-70b-versatile)
-llm = ChatGroq(model_name="llama-3.3-70b-versatile")
-
-def extract_text_from_pdf(pdf_file):
-    """Extracts clean text from a text-based PDF while handling edge cases."""
-    text = ""
-    try:
-        with pdfplumber.open(pdf_file) as pdf:
-            for page in pdf.pages:
-                page_text = page.extract_text()
-                if page_text:
-                    text += page_text.strip() + "\n\n"  # Keep formatting clean
-    except Exception as e:
-        return f"Error extracting text: {str(e)}"
-
-    if not text.strip():
-        return "⚠️ No readable text found. This might be a scanned or image-based PDF."
-
-    return text.strip()
-
-def summarize_text(text, length, style):
-    """Summarizes extracted text using Mistral-8x7B with structured formatting."""
-    prompt = (
-        f"""
-        Read the following document and summarize it in {style.lower()} format.
-        Keep the summary {length.lower()}.
-        Follow this structured reasoning:
-        1. Identify key sections & main topics.
-        2. Extract essential points from each section.
-        3. Remove redundant information.
-        4. Ensure accuracy without hallucination.
-
-        Document:
-        {text[:10000]}  # Limit input to 10,000 characters for efficiency
-        """
-    )
-    response = llm.predict(prompt)
-    return response.strip()
-
-def process_pdf(file, length, style):
-    """Extracts text and summarizes PDF with customization options."""
-    if not file:
-        return "⚠️ No file uploaded. Please upload a PDF."
-
-    text = extract_text_from_pdf(file.name)
-    if text.startswith("⚠️") or text.startswith("Error"):
-        return text  # Return error messages directly
-
-    return summarize_text(text, length, style)
-
-# Create Gradio Interface
-interface = gr.Interface(
-    fn=process_pdf,
-    inputs=[
-        gr.File(label="📄 Upload a PDF"),
-        gr.Radio(["Short", "Medium", "Long"], label="📏 Summary Length", value="Medium"),
-        gr.Radio(["Bullets", "Key Takeaways", "Concise Paragraph"], label="📌 Summary Style", value="Key Takeaways"),
-    ],
-    outputs="text",
-    title="📄 PDF Summarizer (Text-Based PDFs Only)",
-    description="Upload a PDF file (text-based only) and get a structured summary. Not for scanned/image PDFs.",
-)
-
-# Run the app
-interface.launch()