Create App.py

App.py

@@ -0,0 +1,49 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+
+# 1. Load YOUR Model (The one currently training)
+MODEL_NAME = "himu1780/ai-python-model"
+
+print(f"Loading {MODEL_NAME}...")
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
+
+# Create a text generation pipeline
+generator = pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    device=-1 # Use CPU
+)
+
+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."
+    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)
+        do_sample=True,
+        pad_token_id=tokenizer.eos_token_id
+    )
+    
+    # 4. Clean up the text (Remove the prompt so we only see the answer)
+    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
+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"
+)
+
+demo.launch()