Create app.py

app.py

@@ -0,0 +1,25 @@
+import streamlit as st
+from keras.models import load_model
+
+st.set_page_config(page_title="Fine-tuned Gemma Chatbot", layout="centered")
+
+# Load the Keras model
+@st.cache_resource
+def load_keras_model():
+    model = load_model("gemma_finetuned.keras")
+    return model
+
+model = load_keras_model()
+
+# UI
+st.title("💬 Fine-tuned Gemma Code Generator")
+prompt = st.text_area("Enter your instruction", value="Write a Python function to reverse a string")
+
+if st.button("Generate"):
+    # Simple inference logic - you may need to adapt this based on how your model generates text
+    sampler = keras_nlp.samplers.TopKSampler(k=5, seed=2)
+    model.compile(sampler=sampler)
+    response = model.generate(prompt, max_length=256)
+
+    st.subheader("Response:")
+    st.code(response, language="python")