Intial commit

.gitignore

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+__pycache__

README.md

@@ -1,10 +1,11 @@
 ---
-title: Dut Recipe Generator
-emoji: 🚀
-colorFrom: red
-colorTo: gray
+title: DUT Recipe Generator
+emoji: 🍲
+colorFrom: pink
+colorTo: green
 sdk: gradio
-sdk_version: 4.44.0
+sdk_version: 4.42.0
+python_version: 3.11
 app_file: app.py
 pinned: false
 license: bigscience-bloom-rail-1.0

app.py

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+import json
+
+import gradio as gr
+import spaces
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+
+from format.format_output import format_output
+from validate.validate_ingredients import validate_ingredients
+from device.get_device_id import get_device_id
+
+tokenizer = AutoTokenizer.from_pretrained("Ashikan/dut-recipe-generator")
+model = AutoModelForCausalLM.from_pretrained("Ashikan/dut-recipe-generator")
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=get_device_id())
+
+
+@spaces.GPU
+def perform_model_inference(ingredients_list):
+    for ingredient_index in range(len(ingredients_list)):
+        ingredients_list[ingredient_index] = ingredients_list[ingredient_index].strip()
+
+    input_text = '{"prompt": ' + json.dumps(ingredients_list)
+
+    output = pipe(input_text, max_length=1024, temperature=0.1, do_sample=True, truncation=True)[0]["generated_text"]
+
+    return format_output(output)
+
+
+def generate_recipe(ingredients):
+    ingredients_list = ingredients.lower().split(',')
+    is_ingredients_valid = validate_ingredients(ingredients_list)
+
+    if is_ingredients_valid:
+        generated_text = perform_model_inference(ingredients_list)
+
+        return {
+            generated_recipe: gr.Markdown(value=generated_text, label="Generated Recipe",
+                                          elem_id="recipe-container", visible=True)
+        }
+    else:
+        error_text = "## Invalid ingredients. Please include at least 2 ingredients in a comma separated list. e.g. brown rice, onions, garlic"
+
+        return {
+            generated_recipe: gr.Markdown(value=error_text, elem_id="recipe-container", visible=True)
+        }
+
+
+with gr.Blocks(css="./css/styles.css") as recipegen:
+    gr.Image("./assets/dut.png", interactive=False, show_share_button=False, show_download_button=False,
+             show_fullscreen_button=False, show_label=False, elem_id="dut-logo", height=256)
+    gr.Markdown("# Durban University Of Technology Recipe Generator", elem_id="header")
+    gr.Markdown("### An AI Model Attempting To Produce Healthier, Diabetic-Friendly Recipes",
+                elem_id="header-sub-heading")
+    gr.Markdown("Start by entering a comma-separated list of ingredients below.", elem_id="header-instructions")
+    with gr.Column() as column:
+        user_ingredients = gr.Textbox(label="Ingredients", autofocus=True, max_lines=1, elem_id="ingredients-input")
+        generate_button = gr.Button(value="Generate")
+    with gr.Column():
+        generated_recipe = gr.Markdown(visible=True)
+    examples = gr.Examples(
+        elem_id="examples",
+        examples=[
+            "sweet potato, mushrooms, cheese, garlic",
+            "chicken breast, chili, onion, tomato, parmesan cheese",
+            "strawberries, vanilla, honey, rolled oats, almonds, butter",
+            "hake, spring onion, lemon"
+        ],
+        inputs=[user_ingredients]
+    )
+
+    generate_button.click(
+        fn=generate_recipe,
+        inputs=[user_ingredients],
+        outputs=[generated_recipe]
+    )
+
+recipegen.launch(share=True)

css/styles.css

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+#dut-logo {
+    padding: 1em;
+}
+
+#header {
+    text-align: center;
+}
+
+#header-sub-heading {
+    text-align: center;
+}
+
+#header-instructions {
+    text-align: center;
+}
+
+#ingredients-input input {
+    font-size: 12pt;
+}
+
+#recipe-container {
+    padding: 1em !important;
+    border: 1px solid #e5e7eb !important;
+    border-radius: 5px !important;
+}
+
+#examples button div{
+    padding-left: 1.5em;
+    padding-right: 1.5em;
+}

device/get_device_id.py

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+import torch
+
+def get_device_id():
+    if torch.cuda.is_available():
+        return 0
+
+    return -1

format/format_output.py

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+import json
+
+
+def format_output(raw_response):
+    response_object = json.loads(raw_response)
+
+    title_block = __get_title_block(response_object["title"])
+    ingredients_block = __get_ingredients_block(response_object["ingredients"])
+    method_block = __get_method_block(response_object["method"])
+
+    return title_block + ingredients_block + method_block
+
+
+def __get_title_block(title):
+    return f"# <ins>{title.title()}</ins>\n\n"
+
+
+def __get_ingredients_block(ingredients):
+    ingredients_block = "## Ingredients:\n"
+
+    for ingredient in ingredients:
+        ingredients_block += f"- {ingredient.capitalize()}\n"
+
+    return f"{ingredients_block}\n\n"
+
+
+def __get_method_block(method):
+    method_block = "## Method:\n"
+
+    for step in method:
+        sentences = step.split(".")
+
+        formatted_sentences = []
+
+        for sentence in sentences:
+            formatted_sentences.append(sentence.strip().capitalize())
+
+        joined_sentences = ". ".join(formatted_sentences)
+
+        method_block += f"- {joined_sentences}\n"
+
+    return f"{method_block}\n\n"

requirements.txt

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+transformers
+accelerate
+gradio
+spaces
+torch

validate/validate_ingredients.py

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+def validate_ingredients(ingredients_list):
+    return len(ingredients_list) > 1