Spaces:
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Sleeping
| import gradio as gr | |
| import spaces | |
| from huggingface_hub import InferenceClient | |
| from transformers import pipeline | |
| LOCAL_MODEL = "Qwen/Qwen2.5-0.5B-Instruct" | |
| REMOTE_MODEL = "meta-llama/Llama-3.1-8B-Instruct" | |
| max_tokens = 900 | |
| temperature = 0.7 | |
| top_p = 0.95 | |
| pipe = pipeline( | |
| "text-generation", | |
| model=LOCAL_MODEL, | |
| dtype="auto", | |
| device="cuda", | |
| ) | |
| fancy_css = """ | |
| .gradio-container { | |
| width: 96% !important; | |
| max-width: none !important; | |
| background: url("/gradio_api/file=cute_kitchen_background.png") center / cover fixed !important; | |
| } | |
| #app-title, | |
| #app-subtitle, | |
| #model-note { | |
| background: var(--block-background-fill); | |
| color: var(--body-text-color); | |
| padding: var(--block-padding); | |
| border-radius: var(--block-radius); | |
| } | |
| #app-title, | |
| #app-subtitle { | |
| text-align: center; | |
| } | |
| @media (max-width: 768px) { | |
| .gradio-container { | |
| width: 98% !important; | |
| } | |
| } | |
| """ | |
| def local_generate( | |
| messages, | |
| max_tokens, | |
| temperature, | |
| top_p, | |
| ): | |
| outputs = pipe( | |
| messages, | |
| max_new_tokens=max_tokens, | |
| do_sample=True, | |
| temperature=temperature, | |
| top_p=top_p, | |
| ) | |
| return outputs[0]["generated_text"][-1]["content"] | |
| def respond( | |
| message, | |
| history: list[dict[str, str]], | |
| system_message, | |
| time_required, | |
| pantry_staples, | |
| use_local_model, | |
| hf_token: gr.OAuthToken, | |
| ): | |
| messages = [{"role": "system", "content": system_message}] | |
| messages.extend(history) | |
| pantry_text = ", ".join(pantry_staples) if pantry_staples else "None selected" | |
| messages.append( | |
| { | |
| "role": "user", | |
| "content": ( | |
| f"{message}\n\n" | |
| f"Time Required: {time_required}\n" | |
| f"Pantry Staples Available: {pantry_text}" | |
| ), | |
| } | |
| ) | |
| if use_local_model: | |
| print("[MODE] local") | |
| response = local_generate( | |
| messages, | |
| max_tokens, | |
| temperature, | |
| top_p, | |
| ) | |
| yield response | |
| return | |
| print("[MODE] api") | |
| if hf_token is None or not getattr(hf_token, "token", None): | |
| yield "⚠️ Please log in with your Hugging Face account first." | |
| return | |
| client = InferenceClient( | |
| token=hf_token.token, | |
| model=REMOTE_MODEL, | |
| ) | |
| response = "" | |
| for chunk in client.chat_completion( | |
| messages, | |
| max_tokens=max_tokens, | |
| stream=True, | |
| temperature=temperature, | |
| top_p=top_p, | |
| ): | |
| choices = chunk.choices | |
| token = "" | |
| if len(choices) and choices[0].delta.content: | |
| token = choices[0].delta.content | |
| response += token | |
| yield response | |
| with gr.Blocks() as demo: | |
| with gr.Sidebar(): | |
| gr.LoginButton() | |
| gr.Markdown( | |
| "# 🍽️ What's For Dinner?", | |
| elem_id="app-title", | |
| ) | |
| gr.Markdown( | |
| "**Don't know what to make for dinner? Plan your meals with our chatbot. Select the time you have and input your ingredients or special requests.**", | |
| elem_id="app-subtitle", | |
| ) | |
| time_required = gr.Dropdown( | |
| choices=["20 minutes", "30 minutes", "1 hour", "2 hours"], | |
| value=None, | |
| label="How Much Time Do You Have?", | |
| elem_id="time-required", | |
| ) | |
| pantry_staples = gr.CheckboxGroup( | |
| choices=[ | |
| "Salt", | |
| "Pepper", | |
| "Olive Oil", | |
| "Butter", | |
| "Garlic", | |
| "Onions", | |
| "Peppers", | |
| "Rice", | |
| "Pasta", | |
| "Eggs", | |
| "Flour", | |
| "Sugar", | |
| "Milk", | |
| "Cheese", | |
| "Tomatoes", | |
| "Bread", | |
| "Vinegar" | |
| ], | |
| label="Which Pantry Staples Do You Have?", | |
| elem_id="pantry-staples", | |
| ) | |
| system_message = gr.Textbox( | |
| value="You are a recipe assistant Chatbot. Use the user's input ingredients, checked pantry staples, and cooking time to suggest 1 recipe that can be made within the amount of time specified. If you suggest ingredients that the user does not explictly have, list these as optional.", | |
| label="System message", | |
| render=False, | |
| ) | |
| use_local_model = gr.Checkbox( | |
| label="Use Local Model", | |
| value=False, | |
| render=False, | |
| ) | |
| with gr.Column(elem_id="chat-container"): | |
| chatbot = gr.ChatInterface( | |
| fn=respond, | |
| additional_inputs=[ | |
| system_message, | |
| time_required, | |
| pantry_staples, | |
| use_local_model, | |
| ], | |
| ) | |
| gr.Markdown( | |
| "**Use Additional inputs to switch between the API model and the locally executed model.**", | |
| elem_id="model-note", | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch( | |
| theme=gr.themes.Soft(), | |
| css=fancy_css, | |
| allowed_paths=["cute_kitchen_background.png"], | |
| ) | |