README.md

---
title: Chef Transformer
emoji: 🍲
colorFrom: blue
colorTo: red
sdk: streamlit
app_file: app.py
pinned: false
---

# Chef Transformer (T5) 
> This is part of the [Flax/Jax Community Week](https://discuss.huggingface.co/t/recipe-generation-model/7475), organized by [HuggingFace](https://huggingface.co/) and TPU usage sponsored by Google.

Want to give it a try? Then what's the wait, head over to the demo [here](https://share.streamlit.io/chef-transformer/chef-transformer/main/app.py).


## Team Members
- Mehrdad Farahani ([m3hrdadfi](https://huggingface.co/m3hrdadfi))
- Kartik Godawat ([dk-crazydiv](https://huggingface.co/dk-crazydiv))
- Haswanth Aekula ([hassiahk](https://huggingface.co/hassiahk))
- Deepak Pandian ([rays2pix](https://huggingface.co/rays2pix))
- Nicholas Broad ([nbroad](https://huggingface.co/nbroad))

## Dataset

[RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation](https://recipenlg.cs.put.poznan.pl/). This dataset contains **2,231,142** cooking recipes (>2 millions) with size of **2.14 GB**. It's processed in more careful way.

### Example

```json
{
    "NER": [
        "oyster crackers",
        "salad dressing",
        "lemon pepper",
        "dill weed",
        "garlic powder",
        "salad oil"
    ],
    "directions": [
        "Combine salad dressing mix and oil.",
        "Add dill weed, garlic powder and lemon pepper.",
        "Pour over crackers; stir to coat.",
        "Place in warm oven.",
        "Use very low temperature for 15 to 20 minutes."
    ],
    "ingredients": [
        "12 to 16 oz. plain oyster crackers",
        "1 pkg. Hidden Valley Ranch salad dressing mix",
        "1/4 tsp. lemon pepper",
        "1/2 to 1 tsp. dill weed",
        "1/4 tsp. garlic powder",
        "3/4 to 1 c. salad oil"
    ],
    "link": "www.cookbooks.com/Recipe-Details.aspx?id=648947",
    "source": "Gathered",
    "title": "Hidden Valley Ranch Oyster Crackers"
}
```

## How To Use

```bash
# Installing requirements
pip install transformers
```

```python
from transformers import FlaxAutoModelForSeq2SeqLM
from transformers import AutoTokenizer

MODEL_NAME_OR_PATH = "flax-community/t5-recipe-generation"
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME_OR_PATH, use_fast=True)
model = FlaxAutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME_OR_PATH)

prefix = "items: "
# generation_kwargs = {
#     "max_length": 1024,
#     "min_length": 128,
#     "no_repeat_ngram_size": 3,
#     "do_sample": True,
#     "top_k": 60,
#     "top_p": 0.95
# }
generation_kwargs = {
    "max_length": 512,
    "min_length": 64,
    "no_repeat_ngram_size": 3,
    "early_stopping": True,
    "num_beams": 5,
    "length_penalty": 1.5,
}

special_tokens = tokenizer.all_special_tokens
tokens_map = {
    "<sep>": "--",
    "<section>": "\n"
}
def skip_special_tokens(text, special_tokens):
    for token in special_tokens:
        text = text.replace(token, "")

    return text

def target_postprocessing(texts, special_tokens):
    if not isinstance(texts, list):
        texts = [texts]
    
    new_texts = []
    for text in texts:
        text = skip_special_tokens(text, special_tokens)

        for k, v in tokens_map.items():
            text = text.replace(k, v)

        new_texts.append(text)

    return new_texts

def generation_function(texts):
    _inputs = texts if isinstance(texts, list) else [texts]
    inputs = [prefix + inp for inp in _inputs]
    inputs = tokenizer(
        inputs, 
        max_length=256, 
        padding="max_length", 
        truncation=True, 
        return_tensors="jax"
    )

    input_ids = inputs.input_ids
    attention_mask = inputs.attention_mask

    output_ids = model.generate(
        input_ids=input_ids, 
        attention_mask=attention_mask,
        **generation_kwargs
    )
    generated = output_ids.sequences
    generated_recipe = target_postprocessing(
        tokenizer.batch_decode(generated, skip_special_tokens=False),
        special_tokens
    )
    return generated_recipe
```

```python
items = [
    "macaroni, butter, salt, bacon, milk, flour, pepper, cream corn",
    "provolone cheese, bacon, bread, ginger"
]
generated = generation_function(items)
for text in generated:
    sections = text.split("\n")
    for section in sections:
        section = section.strip()
        if section.startswith("title:"):
            section = section.replace("title:", "")
            headline = "TITLE"
        elif section.startswith("ingredients:"):
            section = section.replace("ingredients:", "")
            headline = "INGREDIENTS"
        elif section.startswith("directions:"):
            section = section.replace("directions:", "")
            headline = "DIRECTIONS"
        
        if headline == "TITLE":
            print(f"[{headline}]: {section.strip().capitalize()}")
        else:
            section_info = [f"  - {i+1}: {info.strip().capitalize()}" for i, info in enumerate(section.split("--"))]
            print(f"[{headline}]:")
            print("\n".join(section_info))

    print("-" * 130)
```

Output:
```text
[TITLE]: Macaroni and corn
[INGREDIENTS]:
  - 1: 2 c. macaroni
  - 2: 2 tbsp. butter
  - 3: 1 tsp. salt
  - 4: 4 slices bacon
  - 5: 2 c. milk
  - 6: 2 tbsp. flour
  - 7: 1/4 tsp. pepper
  - 8: 1 can cream corn
[DIRECTIONS]:
  - 1: Cook macaroni in boiling salted water until tender.
  - 2: Drain.
  - 3: Melt butter in saucepan.
  - 4: Blend in flour, salt and pepper.
  - 5: Add milk all at once.
  - 6: Cook and stir until thickened and bubbly.
  - 7: Stir in corn and bacon.
  - 8: Pour over macaroni and mix well.
----------------------------------------------------------------------------------------------------------------------------------
[TITLE]: Grilled provolone and bacon sandwich
[INGREDIENTS]:
  - 1: 2 slices provolone cheese
  - 2: 2 slices bacon
  - 3: 2 slices sourdough bread
  - 4: 2 slices pickled ginger
[DIRECTIONS]:
  - 1: Place a slice of provolone cheese on one slice of bread.
  - 2: Top with a slice of bacon.
  - 3: Top with a slice of pickled ginger.
  - 4: Top with the other slice of bread.
  - 5: Heat a skillet over medium heat.
  - 6: Place the sandwich in the skillet and cook until the cheese is melted and the bread is golden brown.
----------------------------------------------------------------------------------------------------------------------------------
```

## Evaluation

The following table summarizes the scores obtained by the **Chef Transformer**. Those marked as (*) are the baseline models.

|      Model      |  WER  | COSIM | ROUGE-2 |
| :-------------: | :---: | :---: | :-----: |
|   Recipe1M+ *   | 0.786 | 0.589 |    -    |
|   RecipeNLG *   | 0.751 | 0.666 |    -    |
| ChefTransformer | 0.709 | 0.714 |  0.290  |

## Streamlit demo

```bash
streamlit run app.py
```

## Looking to contribute?
Then follow the steps mentioned in this [contributing guide](CONTRIBUTING.md) and you are good to go.

## Copyright

Special thanks to those who provided these fantastic materials.
- [Anatomy](https://www.flaticon.com/free-icon)
- [Chef Hat](https://www.vecteezy.com/members/jellyfishwater)
- [Moira Nazzari](https://pixabay.com/photos/food-dessert-cake-eggs-butter-3048440/)
- [Instagram Post](https://www.freepik.com/free-psd/recipes-ad-social-media-post-template_11520617.htm)