Update app.py

app.py

@@ -1,35 +1,44 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
-import spaces
 
-model_id = "tiiuae/falcon-rw-1b"
+model_id = "microsoft/phi-2"
 
-# Load tokenizer and model for CPU
+# Load model and tokenizer (CPU + float32)
 tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float32)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.float32
+).to("cpu")
 
-# Chat logic
-@spaces.GPU
+# Chat function
 def chat_with_bot(user_input, history):
     history = history or []
     prompt = ""
     for user, bot in history:
-        prompt += f"{user}\n{bot}\n"
-    prompt += f"{user_input}\n"
+        prompt += f"User: {user}\nAssistant: {bot}\n"
+    prompt += f"User: {user_input}\nAssistant:"
 
     inputs = tokenizer(prompt, return_tensors="pt").to("cpu")
-    outputs = model.generate(**inputs, max_new_tokens=200, do_sample=True)
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=256,
+        do_sample=True,
+        temperature=0.7,
+        top_p=0.95,
+        eos_token_id=tokenizer.eos_token_id,
+    )
+
     decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    response = decoded[len(prompt):].strip().split("\n")[0]
 
-    response = decoded[len(prompt):].strip()
     history.append((user_input, response))
     return response, history
 
 # Gradio UI
 gr.ChatInterface(
     fn=chat_with_bot,
-    title="Chatbot (CPU-Friendly)",
+    title="Phi-2 Chatbot (ZeroGPU Safe)",
     theme="soft",
-    examples=["What's Falcon?", "Tell me something about space.", "What is time travel?"]
+    examples=["What is AI?", "Summarize the French Revolution.", "Tell me a space fact."]
 ).launch(share=True)