Update app.py

app.py

@@ -1,26 +1,22 @@
 import gradio as gr
+from transformers import pipeline
 
-# Define chatbot behavior
+# Load a small, free AI model from Hugging Face
+generator = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.2")
+
+# Define chatbot logic
 def fruit_health_bot(message, history=[]):
-    responses = {
-        "apple": "Apples are great for heart health and rich in fiber.",
-        "banana": "Bananas are rich in potassium and good for energy.",
-        "orange": "Oranges boost your immune system with Vitamin C.",
-        "mango": "Mangoes are rich in antioxidants and support skin health."
-    }
-    message_lower = message.lower().strip()
-    for fruit in responses:
-        if fruit in message_lower:
-            return responses[fruit]
-    return "Hi there! 🍎 I'm FruitHealthGPT. Ask me about the health benefits of any fruit!"
+    prompt = f"You are FruitHealthGPT, a friendly expert on fruits and health benefits. Be concise and helpful.\nUser: {message}\nFruitHealthGPT:"
+    response = generator(prompt, max_new_tokens=100, do_sample=True, temperature=0.7)
+    answer = response[0]["generated_text"].split("FruitHealthGPT:")[-1].strip()
+    return answer
 
-# Create a simple chat interface
+# Create the chat UI
 iface = gr.ChatInterface(
     fn=fruit_health_bot,
-    title="🍇 FruitHealthGPT",
-    description="Ask me about the health benefits of fruits!"
+    title="🍎 FruitHealthGPT",
+    description="Ask me about the health benefits of any fruit!"
 )
 
 iface.launch()
 
-