app.py

import gradio as gr
from huggingface_hub import InferenceClient

# ✅ 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"
    }
]

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")

    slider = gr.Slider(
        minimum=0,     # lowest value
        maximum=100,   # highest value
        value=50,      # default starting value
        step=1,        # increment step
        label="Select a number"
    )
    
    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()