Update app.py

app.py

@@ -1,50 +1,65 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
-import os
-
-# Make sure you set your HF token as an environment variable in your Space:
-# Settings → Variables → Add HF_TOKEN
-client = InferenceClient(
-    "mistralai/Mistral-7B-Instruct-v0.3",
-    token=os.environ.get("HF_TOKEN")
-)
-
-def respond(message, history, system_message, max_tokens, temperature, top_p):
-    # Ensure history is in the role/content format
-    messages = [{"role": "system", "content": system_message}]
-    for msg in history:
-        messages.append({"role": "user", "content": msg[0]})
-        messages.append({"role": "assistant", "content": msg[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    # Call the model
-    completion = client.chat_completion(
-        messages=messages,
-        max_tokens=max_tokens,
-        temperature=temperature,
-        top_p=top_p
+
+# ✅ This model supports chat completions through the free Inference API
+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"
+    }
+]
+
+def find_recipes(budget, have_items, allergies):
+    results = []
+    for recipe in recipes:
+        if recipe["budget"] != budget:
+            continue
+        if any(a in recipe["allergies"] for a in allergies):
+            continue
+        if not all(item in have_items for item in recipe["ingredients"]):
+            continue
+        results.append(recipe["name"])
+    return results or ["No matching recipes found."]
+
+def chatbot(message, history, budget, have_items, allergies):
+    recipes_found = find_recipes(budget, have_items.split(","), allergies.split(","))
+    system_prompt = (
+        f"You are a friendly cooking assistant. The user has budget '{budget}', "
+        f"these ingredients: {have_items}, and allergies: {allergies}. "
+        f"Suggest recipes from this list: {recipes_found}."
     )
 
-    reply = completion.choices[0].message["content"]
-    history.append((message, reply))
-    return history, history  # return chatbot state & UI
+    msgs = [{"role": "system", "content": system_prompt}]
+    for user_msg, bot_msg in history:
+        msgs.append({"role": "user", "content": user_msg})
+        msgs.append({"role": "assistant", "content": bot_msg})
+    msgs.append({"role": "user", "content": message})
+
+    response_text = ""
+    for resp in client.chat_completion(messages=msgs, stream=True):
+        token = resp.choices[0].delta.content or ""
+        response_text += token
+        return response_text
 
 with gr.Blocks() as demo:
-    gr.Markdown("## 🍳 Recipe Assistant Chatbot")
-    chatbot = gr.Chatbot(type="messages", height=400)
-    system_message = gr.Textbox(value="You are a helpful recipe assistant.", label="System Message")
-    msg = gr.Textbox(label="Your message")
-    max_tokens = gr.Slider(50, 500, value=200, step=10, label="Max Tokens")
-    temperature = gr.Slider(0, 1, value=0.7, step=0.1, label="Temperature")
-    top_p = gr.Slider(0, 1, value=0.9, step=0.1, label="Top P")
-
-    state = gr.State([])
-
-    msg.submit(
-        respond,
-        [msg, state, system_message, max_tokens, temperature, top_p],
-        [chatbot, state]
-    )
+    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: chatbot(msg, hist, budget.value, have_items.value, allergies.value))
 
 demo.launch()