Upload 2 files

app.py

@@ -1,36 +1,57 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load a text generation model
-generator = pipeline("text-generation", model="gpt2")
+# Load GPT-2 generator
+generator = pipeline("text-generation", model="gpt2", max_length=200)
 
-# Function to handle each new user message
+# Chat function
 def chat(user_message, history):
-    # Combine history to make a context
+    # Build context string
     context = ""
     for turn in history:
         context += f"User: {turn[0]}\nBot: {turn[1]}\n"
     context += f"User: {user_message}\nBot:"
 
-    # Generate response
-    response = generator(context, max_length=200, do_sample=True, temperature=0.7)[0]['generated_text']
-    # Keep only new part after last "Bot:"
-    reply = response.split("Bot:")[-1].strip().split("\n")[0]
-    
-    # Append to chat history
+    # Print context for debugging (will also be in trace box)
+    print("----- TRACE: Prompt to LLM -----")
+    print(context)
+    print("---------------------------------")
+
+    # Generate raw output
+    raw_output = generator(context, max_length=len(context.split()) + 50, do_sample=True, temperature=0.7)[0]['generated_text']
+
+    print("----- TRACE: Raw LLM output -----")
+    print(raw_output)
+    print("---------------------------------")
+
+    # Extract final reply
+    if "Bot:" in raw_output:
+        reply = raw_output.split("Bot:")[-1].split("\n")[0].strip()
+    else:
+        reply = raw_output[len(context):].strip()
+
+    # Build trace text
+    trace_text = (
+        f"📄 Prompt sent to LLM:\n\n{context}\n\n"
+        f"⚡ Raw LLM output:\n\n{raw_output}\n\n"
+        f"✅ Final extracted reply:\n\n{reply}"
+    )
+
+    # Update history
     history.append((user_message, reply))
-    return history, history
+    return history, history, trace_text
 
 with gr.Blocks() as demo:
-    gr.Markdown("<h1 style='text-align: center;'>💬 Conversational Agent Chatbot</h1>")
+    gr.Markdown("<h1 style='text-align: center;'>💬 Conversational Agent with Trace</h1>")
 
     chatbot = gr.Chatbot()
-    msg = gr.Textbox(placeholder="Type your question and press Enter...")
+    msg = gr.Textbox(placeholder="Type your message and press Enter...")
+
+    trace_box = gr.Textbox(label="🧐 Trace Logs (for debugging)", lines=15)
 
     clear = gr.Button("Clear Chat")
 
-    # Bind events
-    msg.submit(chat, [msg, chatbot], [chatbot, chatbot])
-    clear.click(lambda: None, None, chatbot, queue=False)
+    msg.submit(chat, [msg, chatbot], [chatbot, chatbot, trace_box])
+    clear.click(lambda: ([], [], ""), None, [chatbot, chatbot, trace_box], queue=False)
 
 demo.launch()