If the language is set to English, the products will be displayed according to the predictive conversion when you type in the search bar.
However, if the language is set to Japanese, the predictive conversion is not displayed.
I know it is possible to implement this in an application, but I would like to implement it in code only, without implementing an application as much as possible.
To implement predictive text conversion in both English and Japanese without creating a full application, you can leverage existing libraries and APIs. Here’s a general approach using Python
Install Required Libraries:
transformers: For language models.
sentencepiece: For tokenization.
googletrans: For translation (optional).
Python
!pip install transformers sentencepiece googletrans==4.0.0-rc1
Load Pre-trained Models:
Use models from Hugging Face for predictive text.
Python
from transformers import pipeline
en_model = pipeline(‘text-generation’, model=‘gpt-2’)
ja_model = pipeline(‘text-generation’, model=‘rinna/japanese-gpt2-medium’)
Predictive Text Function:
Create a function to generate predictions based on input text.
Python
def generate_predictions(model, text, max_length=50):
predictions = model(text, max_length=max_length, num_return_sequences=1)
return predictions[0][‘generated_text’]
en_text = “The future of AI is”
ja_text = “AIの未来は”
en_prediction = generate_predictions(en_model, en_text)
ja_prediction = generate_predictions(ja_model, ja_text)
print(“English Prediction:”, en_prediction)
print(“Japanese Prediction:”, ja_prediction)