Delete app.py

app.py

@@ -1,71 +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 PyPDF2
-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
-
-# Ensure API key is available
-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):
-    """Extract text from a PDF file."""
-    text = ""
-    reader = PyPDF2.PdfReader(pdf_file)
-    for page in reader.pages:
-        page_text = page.extract_text()
-        if page_text:
-            text += page_text + "\n"
-    return text
-
-def summarize_text(text):
-    """Summarize the text"""
-    prompt = f"Summarize the following document:\n\n{text[:10000]}"  # Limit input size
-    response = llm.predict(prompt)
-    return response
-
-def process_pdf(file):
-    """Extract text and summarize PDF using Mistral-8x7B."""
-    if file is None:
-        return "No file uploaded."
-
-    # Read file bytes and process it using PyPDF2
-    pdf_reader = PyPDF2.PdfReader(file)
-    text = ""
-    for page in pdf_reader.pages:
-        page_text = page.extract_text()
-        if page_text:
-            text += page_text + "\n"
-
-    # Limit text size for API efficiency
-    text = text[:10000] if len(text) > 10000 else text
-
-    # Summarize
-    summary = summarize_text(text)
-    return summary
-
-# Create Gradio Interface
-interface = gr.Interface(
-    fn=process_pdf,
-    inputs=gr.File(label="Upload a PDF"),
-    outputs="text",
-    title="📄 PDF Summarizer",
-    description="Upload a PDF file and get a summary"
-)
-
-# Run the app
-interface.launch()