Create app.py

copied from thingy

app.py

@@ -0,0 +1,49 @@
+import gradio as gr
+from huggingface_hub import InferenceClient
+
+# model!
+MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
+
+client = InferenceClient(model=MODEL_NAME)
+
+# Example fake recipe database
+recipes = [
+    {
+        "name": "Veggie Pasta",
+        "ingredients": ["pasta", "tomato", "garlic", "olive oil"],
+        "allergies": ["gluten"],
+        "budget": "low"
+    },
+    {
+        "name": "Chicken Stir Fry",
+        "ingredients": ["chicken", "soy sauce", "broccoli", "garlic"],
+        "allergies": ["soy"],
+        "budget": "medium"
+    }
+]
+
+client = InferenceClient("microsoft/phi-4")
+
+def respond(message, history):
+    messages = [{"role": "system", "content": "You are a friendly chatbot"}]
+    if history:
+        messages.extend(history)
+    messages.append({"role": "user", "content": message})
+
+    response = client.chat_completion(
+        messages,
+        max_tokens=100
+    )
+
+    return response['choices'][0]['message']['content'].strip()
+    
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 🍳 Recipe Suggestion Chatbot")
+
+    budget = gr.Dropdown(["low", "medium", "high"], label="Budget", value="low")
+    have_items = gr.Textbox(label="Ingredients you have (comma separated)", placeholder="pasta,tomato,garlic")
+    allergies = gr.Textbox(label="Allergies (comma separated)", placeholder="gluten,soy")
+    chatbot_ui = gr.ChatInterface(fn=lambda msg, hist: respond(msg, hist))
+
+demo.launch()