Update app.py

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 
-# 1. Load YOUR Model (The one currently training)
+# 1. Load YOUR Model
 MODEL_NAME = "himu1780/ai-python-model"
 
 print(f"Loading {MODEL_NAME}...")
@@ -17,33 +17,30 @@ generator = pipeline(
 )
 
 def chat_function(user_message, history):
-    # 2. Format the prompt exactly like the training data
-    # This teaches the model: "Hey, I am giving you an Instruction, now give me the Response."
+    # 2. Format the prompt
     prompt = f"### Instruction:\n{user_message}\n\n### Response:\n"
     
     # 3. Generate the answer
     response = generator(
         prompt,
-        max_new_tokens=200,    # Max length of answer
-        temperature=0.6,       # Creativity (Low = better for code)
+        max_new_tokens=200,
+        temperature=0.6,
         do_sample=True,
         pad_token_id=tokenizer.eos_token_id
     )
     
-    # 4. Clean up the text (Remove the prompt so we only see the answer)
+    # 4. Clean up the text
     full_text = response[0]['generated_text']
-    # Split by "### Response:" and take the second part
     answer = full_text.split("### Response:")[-1].strip()
     
     return answer
 
-# 5. Launch the Chat UI
+# 5. Launch the Chat UI (Fixed: Removed 'theme' argument)
 demo = gr.ChatInterface(
     fn=chat_function,
     title="🐍 AI Python Assistant",
     description="Ask me to write Python code!",
-    examples=["Write a function to calculate area of circle", "Create a list of numbers 1 to 10"],
-    theme="soft"
+    examples=["Write a function to calculate area of circle", "Create a list of numbers 1 to 10"]
 )
 
 demo.launch()