Update app.py

app.py

@@ -1 +1,66 @@
 pip install gradio openai pdfplumber
+import gradio as gr
+import pdfplumber
+import openai
+import os
+
+# Set your OpenAI API key here
+openai.api_key = "YOUR_OPENAI_API_KEY"
+
+# Function to extract text from uploaded PDF
+def extract_text_from_pdf(pdf_file):
+    text = ""
+    with pdfplumber.open(pdf_file) as pdf:
+        for page in pdf.pages:
+            text += page.extract_text() + "\n"
+    return text
+
+# Function to generate critique using OpenAI LLM
+def generate_critique(file):
+    if file is None:
+        return "Please upload a PDF file."
+
+    # Extract text from PDF
+    extracted_text = extract_text_from_pdf(file)
+
+    # Truncate if too long for API (adjust depending on model token limit)
+    if len(extracted_text) > 6000:
+        extracted_text = extracted_text[:6000]
+
+    # Prompt for LLM
+    prompt = f"""
+Analyze the following research paper and provide:
+
+1. Section-wise summaries (Abstract, Introduction, Methodology, Results, Conclusion).
+2. Identify potential research gaps or areas lacking clarity.
+3. Suggest improvements to enhance the research quality.
+
+Research Paper Content:
+{extracted_text}
+"""
+
+    try:
+        # Call OpenAI API
+        response = openai.ChatCompletion.create(
+            model="gpt-4",  # or "gpt-3.5-turbo" if you're on the free tier
+            messages=[{"role": "user", "content": prompt}],
+            max_tokens=1500,
+            temperature=0.7
+        )
+
+        return response['choices'][0]['message']['content']
+    
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=generate_critique,
+    inputs=gr.File(label="Upload Research Paper (.pdf)", file_types=[".pdf"]),
+    outputs=gr.Textbox(label="LLM Critique Output", lines=30),
+    title="📄 Research Paper Critique Generator",
+    description="Upload a research paper in PDF format. This tool will summarize each section, highlight research gaps, and suggest improvements using GPT-4."
+)
+
+# Launch on Hugging Face / Local
+iface.launch()