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import gradio as gr |
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from transformers import TextIteratorStreamer |
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from threading import Thread |
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from unsloth import FastLanguageModel |
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load_in_4bit = True |
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recipe_model_id = "ID2223JR/recipe_model" |
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lora_model_id = "ID2223JR/lora_model" |
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recipe_model, recipe_tokenizer = FastLanguageModel.from_pretrained( |
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model_name=recipe_model_id, |
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load_in_4bit=load_in_4bit, |
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) |
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FastLanguageModel.for_inference(recipe_model) |
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lora_model, lora_tokenizer = FastLanguageModel.from_pretrained( |
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model_name=lora_model_id, |
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load_in_4bit=load_in_4bit, |
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) |
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FastLanguageModel.for_inference(lora_model) |
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ingredients_list = [] |
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def add_ingredient(ingredient, quantity): |
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if ingredient and int(quantity) > 0: |
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ingredients_list.append(f"{ingredient}, {quantity} grams") |
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return ( |
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"\n".join(ingredients_list), |
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gr.update(value="", interactive=True), |
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gr.update(value=None, interactive=True), |
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) |
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def validate_inputs(ingredient, quantity): |
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if ingredient and int(quantity) > 0: |
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return gr.update(interactive=True) |
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return gr.update(interactive=False) |
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def submit_to_model(selected_model): |
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if not ingredients_list: |
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return "Ingredients list is empty! Please add ingredients first." |
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if selected_model == "Recipe Model": |
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model = recipe_model |
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tokenizer = recipe_tokenizer |
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elif selected_model == "LoRA Model": |
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model = lora_model |
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tokenizer = lora_tokenizer |
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else: |
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return "Invalid model selected!" |
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prompt = f"Using the following ingredients, suggest a recipe:\n\n" + "\n".join( |
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ingredients_list |
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) |
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ingredients_list.clear() |
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messages = [ |
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{"role": "user", "content": prompt}, |
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] |
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inputs = tokenizer.apply_chat_template( |
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messages, |
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tokenize=True, |
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add_generation_prompt=True, |
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return_tensors="pt", |
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).to("cuda") |
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text_streamer = TextIteratorStreamer(tokenizer, skip_prompt=True) |
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generation_kwargs = dict(inputs=inputs, streamer=text_streamer, use_cache=True, temperature=0.3, min_p=0.1) |
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thread = Thread(target=model.generate, kwargs=generation_kwargs) |
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thread.start() |
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content = "" |
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for text in text_streamer: |
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print(text) |
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content += text |
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if content.endswith("<|eot_id|>"): |
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content = content.replace("<|eot_id|>", "") |
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yield content |
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def app(): |
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with gr.Blocks() as demo: |
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with gr.Row(): |
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ingredient_input = gr.Textbox( |
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label="Ingredient", placeholder="Enter ingredient name" |
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) |
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quantity_input = gr.Number(label="Quantity (grams)", value=None) |
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add_button = gr.Button("Add Ingredient", interactive=False) |
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output = gr.Textbox(label="Ingredients List", lines=10, interactive=False) |
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with gr.Row(): |
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submit_button = gr.Button("Give me a meal!") |
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model_dropdown = gr.Dropdown( |
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label="Choose Model", |
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choices=["Recipe Model", "LoRA Model"], |
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value="Recipe Model" |
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) |
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with gr.Row(): |
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model_output = gr.Textbox( |
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label="Recipe Suggestion", lines=10, interactive=False |
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) |
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ingredient_input.change( |
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validate_inputs, [ingredient_input, quantity_input], add_button |
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) |
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quantity_input.change( |
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validate_inputs, [ingredient_input, quantity_input], add_button |
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) |
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add_button.click( |
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add_ingredient, |
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[ingredient_input, quantity_input], |
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[output, ingredient_input, quantity_input], |
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) |
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submit_button.click( |
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submit_to_model, |
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inputs=model_dropdown, |
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outputs=model_output, |
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) |
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return demo |
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demo = app() |
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demo.launch() |
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