Update app.py

app.py

@@ -1,249 +1,148 @@
 import gradio as gr
 import PyPDF2
 import io
-import time
 import os
 from together import Together
-import textwrap
-import tempfile
 
 def extract_text_from_pdf(pdf_file):
-    """Extract text from a PDF file"""
     text = ""
     try:
-        # Check if the pdf_file is already in bytes format or needs conversion
         if hasattr(pdf_file, 'read'):
-            # If it's a file-like object (from gradio upload)
             pdf_content = pdf_file.read()
-            # Reset the file pointer for potential future reads
             if hasattr(pdf_file, 'seek'):
                 pdf_file.seek(0)
         else:
-            # If it's already bytes
             pdf_content = pdf_file
             
-        # Read the PDF file
         pdf_reader = PyPDF2.PdfReader(io.BytesIO(pdf_content))
-        
-        # Extract text from each page
         for page_num in range(len(pdf_reader.pages)):
             page_text = pdf_reader.pages[page_num].extract_text()
-            if page_text:  # Check if text extraction worked
+            if page_text:
                 text += page_text + "\n\n"
             else:
                 text += f"[Page {page_num+1} - No extractable text found]\n\n"
         
         if not text.strip():
             return "No text could be extracted from the PDF. The document may be scanned or image-based."
-            
         return text
     except Exception as e:
         return f"Error extracting text from PDF: {str(e)}"
 
-def format_chat_history(history):
-    """Format the chat history for display"""
-    formatted_history = []
-    for user_msg, bot_msg in history:
-        formatted_history.append((user_msg, bot_msg))
-    return formatted_history
-
 def chat_with_pdf(api_key, pdf_text, user_question, history):
-    """Chat with the PDF using Together API"""
     if not api_key.strip():
-        return history + [(user_question, "Error: Please enter your Together API key.")], history
-    
+        return history + [{"role": "user", "content": user_question}, {"role": "assistant", "content": "Error: Please enter your Together API key."}], history
+
     if not pdf_text.strip() or pdf_text.startswith("Error") or pdf_text.startswith("No text"):
-        return history + [(user_question, "Error: Please upload a valid PDF file with extractable text first.")], history
-    
+        return history + [{"role": "user", "content": user_question}, {"role": "assistant", "content": "Error: Please upload a valid PDF file with extractable text first."}], history
+
     if not user_question.strip():
-        return history + [(user_question, "Error: Please enter a question.")], history
-    
+        return history + [{"role": "user", "content": user_question}, {"role": "assistant", "content": "Error: Please enter a question."}], history
+
     try:
-        # Initialize Together client with the API key
         client = Together(api_key=api_key)
-        
-        # Create the system message with PDF context
-        # Truncate the PDF text if it's too long (model context limit handling)
-        max_context_length = 10000 #10000
-        
+
+        max_context_length = 10000
         if len(pdf_text) > max_context_length:
-            # More sophisticated truncation that preserves beginning and end
             half_length = max_context_length // 2
             pdf_context = pdf_text[:half_length] + "\n\n[...Content truncated due to length...]\n\n" + pdf_text[-half_length:]
         else:
             pdf_context = pdf_text
-        
+
         system_message = f"""You are an intelligent assistant designed to read, understand, and extract information from PDF documents. 
 Based on any question or query the user asks—whether it's about content, summaries, data extraction, definitions, insights, or interpretation—you will 
 analyze the following PDF content and provide an accurate, helpful response grounded in the document. Always respond with clear, concise, and context-aware information.
 PDF CONTENT:
 {pdf_context}
 Answer the user's questions only based on the PDF content above. If the answer cannot be found in the PDF, politely state that the information is not available in the provided document."""
-        
-        # Prepare message history for Together API
-        messages = [
-            {"role": "system", "content": system_message},
-        ]
-        
-        # Add chat history
-        for h_user, h_bot in history:
-            messages.append({"role": "user", "content": h_user})
-            messages.append({"role": "assistant", "content": h_bot})
-        
-        # Add the current user question
+
+        messages = [{"role": "system", "content": system_message}]
+        for msg in history:
+            messages.append(msg)
+
         messages.append({"role": "user", "content": user_question})
-        
-        # Call the Together API
+
         response = client.chat.completions.create(
             model="meta-llama/Llama-3.3-70B-Instruct-Turbo-Free",
             messages=messages,
-            max_tokens=5000, #5000
+            max_tokens=5000,
             temperature=0.7,
         )
-        
-        # Extract the assistant's response
+
         assistant_response = response.choices[0].message.content
-        
-        # Update the chat history
-        new_history = history + [(user_question, assistant_response)]
-        
+        new_history = history + [
+            {"role": "user", "content": user_question},
+            {"role": "assistant", "content": assistant_response}
+        ]
+
         return new_history, new_history
-    
+
     except Exception as e:
-        error_message = f"Error: {str(e)}"
-        return history + [(user_question, error_message)], history
+        return history + [{"role": "user", "content": user_question}, {"role": "assistant", "content": f"Error: {str(e)}"}], history
 
 def process_pdf(pdf_file, api_key_input):
-    """Process the uploaded PDF file"""
     if pdf_file is None:
         return "Please upload a PDF file.", "", []
-    
+
     try:
-        # Get the file name
         file_name = os.path.basename(pdf_file.name) if hasattr(pdf_file, 'name') else "Uploaded PDF"
-        
-        # Extract text from the PDF
         pdf_text = extract_text_from_pdf(pdf_file)
-        
-        # Check if there was an error in extraction
+
         if pdf_text.startswith("Error extracting text from PDF"):
             return f"❌ {pdf_text}", "", []
-        
+
         if not pdf_text.strip() or pdf_text.startswith("No text could be extracted"):
             return f"⚠️ {pdf_text}", "", []
-        
-        # Count words for information
+
         word_count = len(pdf_text.split())
-        
-        # Return a message with the file name and text content
         status_message = f"✅ Successfully processed PDF: {file_name} ({word_count} words extracted)"
-        
-        # Also return an empty history
         return status_message, pdf_text, []
     except Exception as e:
         return f"❌ Error processing PDF: {str(e)}", "", []
 
 def validate_api_key(api_key):
-    """Simple validation for API key format"""
     if not api_key or not api_key.strip():
         return "❌ API Key is required"
-    
     if len(api_key.strip()) < 10:
         return "❌ API Key appears to be too short"
-    
     return "✓ API Key format looks valid (not verified with server)"
-# ✅ Clear function
+
+def update_preview(text):
+    if not text or text.startswith("Error") or text.startswith("No text"):
+        return text
+    preview = text[:500]
+    if len(text) > 500:
+        preview += "...\n[Text truncated for preview. Full text will be used for chat.]"
+    return preview
+
 def clear_all():
     return "", "", "", "", [], "", ""
 
-    
-# Create the Gradio interface
+# 🚀 Gradio Interface
 with gr.Blocks(title="ChatPDF with Together AI", theme=gr.themes.Ocean()) as app:
     gr.Markdown("# 📄 ChatPDF with Together AI")
     gr.Markdown("Upload a PDF and chat with it using the Llama-3.3-70B model.")
-    
+
     with gr.Row():
         with gr.Column(scale=1):
-            # API Key input
-            api_key_input = gr.Textbox(
-                label="Together API Key",
-                placeholder="Enter your Together API key here...",
-                type="password"
-            )
-            
-            # API key validation
-            api_key_status = gr.Textbox(
-                label="API Key Status",
-                interactive=False
-            )
-            
-            # PDF upload
-            pdf_file = gr.File(
-                label="Upload PDF",
-                file_types=[".pdf"],
-                type="binary"  # Ensure we get binary data
-            )
-            
-            # Process PDF button
+            api_key_input = gr.Textbox(label="Together API Key", placeholder="Enter your Together API key here...", type="password")
+            api_key_status = gr.Textbox(label="API Key Status", interactive=False)
+            pdf_file = gr.File(label="Upload PDF", file_types=[".pdf"], type="binary")
             process_button = gr.Button("Process PDF")
-            
-            # Status message
-            status_message = gr.Textbox(
-                label="Status",
-                interactive=False
-            )
-            
-            # Hidden field to store the PDF text
+            status_message = gr.Textbox(label="Status", interactive=False)
             pdf_text = gr.Textbox(visible=False)
-            
-            # Optional: Show PDF preview
+
             with gr.Accordion("PDF Content Preview", open=False):
-                pdf_preview = gr.Textbox(
-                    label="Extracted Text Preview",
-                    interactive=False,
-                    max_lines=10,
-                    show_copy_button=True
-                )
-        
+                pdf_preview = gr.Textbox(label="Extracted Text Preview", interactive=False, max_lines=10, show_copy_button=True)
+
         with gr.Column(scale=2):
-            # Chat interface
-            chatbot = gr.Chatbot(
-                label="Chat with PDF",
-                height=500,
-                show_copy_button=True
-            )
-            
-            # Question input
-            question = gr.Textbox(
-                label="Ask a question about the PDF",
-                placeholder="What is the main topic of this document?",
-                lines=2
-            )
-            
-            # Submit button
+            chatbot = gr.Chatbot(label="Chat with PDF", height=500, show_copy_button=True, type="messages")
+            question = gr.Textbox(label="Ask a question about the PDF", placeholder="What is the main topic of this document?", lines=2)
             submit_button = gr.Button("Submit Question")
-            # clear button
-            
-    
-    # Event handlers
-    def update_preview(text):
-        """Update the preview with the first few lines of the PDF text"""
-        if not text or text.startswith("Error") or text.startswith("No text"):
-            return text
-        
-        # Get the first ~500 characters for preview
-        preview = text[:500]
-        if len(text) > 500:
-            preview += "...\n[Text truncated for preview. Full text will be used for chat.]"
-        return preview
-    
-    # API key validation event
-    api_key_input.change(
-        fn=validate_api_key,
-        inputs=[api_key_input],
-        outputs=[api_key_status]
-    )
-    
+            clear_button = gr.Button("Clear Chat & Reset", variant="stop")  # ✅ CLEAR BUTTON
+
+    # 🔄 Events
+    api_key_input.change(fn=validate_api_key, inputs=[api_key_input], outputs=[api_key_status])
+
     process_button.click(
         fn=process_pdf,
         inputs=[pdf_file, api_key_input],
@@ -253,7 +152,7 @@ with gr.Blocks(title="ChatPDF with Together AI", theme=gr.themes.Ocean()) as app
         inputs=[pdf_text],
         outputs=[pdf_preview]
     )
-    
+
     submit_button.click(
         fn=chat_with_pdf,
         inputs=[api_key_input, pdf_text, question, chatbot],
@@ -262,7 +161,7 @@ with gr.Blocks(title="ChatPDF with Together AI", theme=gr.themes.Ocean()) as app
         fn=lambda: "",
         outputs=question
     )
-    
+
     question.submit(
         fn=chat_with_pdf,
         inputs=[api_key_input, pdf_text, question, chatbot],
@@ -272,7 +171,6 @@ with gr.Blocks(title="ChatPDF with Together AI", theme=gr.themes.Ocean()) as app
         outputs=question
     )
 
-    # ✅ Clear Button Handler
     clear_button.click(
         fn=clear_all,
         outputs=[
@@ -286,7 +184,5 @@ with gr.Blocks(title="ChatPDF with Together AI", theme=gr.themes.Ocean()) as app
         ]
     )
 
-# Launch the app
 if __name__ == "__main__":
     app.launch(share=True)
-