Update app.py

app.py

@@ -1,25 +1,22 @@
-import streamlit as st
 import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM
-from peft import PeftModel
-
-# Load base model & tokenizer
-base_model_name = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
-adapter_path = "lora_adapter"  # path to your LoRA adapter directory
+import streamlit as st
 
-@st.cache_resource
-def load_model():
-    tokenizer = AutoTokenizer.from_pretrained(base_model_name)
-    base_model = AutoModelForCausalLM.from_pretrained(base_model_name, device_map="auto")
-    model = PeftModel.from_pretrained(base_model, adapter_path)
-    model.eval()
-    return tokenizer, model
+# Load base + LoRA model
+base_model = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
+adapter_path = "./lora_adapter"  # your uploaded LoRA adapter
 
-tokenizer, model = load_model()
+tokenizer = AutoTokenizer.from_pretrained(base_model)
+model = AutoModelForCausalLM.from_pretrained(
+    base_model,
+    device_map="auto",
+    torch_dtype=torch.float32
+)
+model.load_adapter(adapter_path)
+model.eval()
 
-# Prompt formatting
+# ---- Prompt template ----
 def format_prompt(user_input):
-    return def format_prompt(user_input):
     return f"""You are PythonGPT, an expert tutor that ONLY answers questions about Python programming.
 
 If the user asks anything unrelated to Python (like greetings, jokes, math problems, or general trivia), respond strictly with:
@@ -41,24 +38,28 @@ A: Sorry, I can only answer Python-related questions.
 Q: {user_input}
 A:"""
 
-### Response:"""
-
-def chat(instruction):
-    prompt = format_prompt(instruction)
+# ---- Chat generation ----
+def get_response(user_input):
+    prompt = format_prompt(user_input)
     inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
-    output = model.generate(**inputs, max_new_tokens=150, do_sample=True, temperature=0.7)
-    response = tokenizer.decode(output[0], skip_special_tokens=True)
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=200,
+        do_sample=True,
+        temperature=0.7,
+        pad_token_id=tokenizer.eos_token_id
+    )
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return response.split("A:")[-1].strip()
 
-
-# Streamlit UI
+# ---- Streamlit App ----
+st.set_page_config(page_title="🧑‍🏫 Python Tutor Chatbot")
 st.title("🧑‍🏫 Python Tutor Chatbot")
 st.write("Ask me anything about Python programming!")
 
-user_input = st.text_area("Your Question", height=150)
-if st.button("Ask"):
-    if user_input.strip():
-        with st.spinner("Thinking..."):
-            answer = chat(user_input)
-        st.markdown("### 💡 Answer:")
-        st.write(answer)
+user_query = st.text_input("Your Question", "")
+
+if user_query:
+    with st.spinner("Thinking..."):
+        response = get_response(user_query)
+        st.markdown(f"💡 **Answer:**\n\n{response}")