Upload app.py

app.py

@@ -0,0 +1,84 @@
+# -*- 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 (Mistral-8x7B)
+llm = ChatGroq(model_name="mixtral-8x7b-32768")
+
+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()