| import requests | |
| import time | |
| from PIL import Image | |
| import gradio as gr | |
| hold_time = time.time() | |
| API_URL = "https://cm7kxsqi3sekfih7.us-east-1.aws.endpoints.huggingface.cloud" | |
| headers = { | |
| "Accept" : "application/json", | |
| "Content-Type": "application/json" | |
| } | |
| def query(payload): | |
| global hold_time | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| if response.status_code != 200: | |
| print('Sleeping due to API error') | |
| if (time.time() - hold_time) > 60: | |
| hold_time = time.time() | |
| return None | |
| return response.json() | |
| def run_model(Dialects): | |
| global hold_time | |
| output = query({ | |
| "inputs": Dialects, | |
| "parameters": {} | |
| }) | |
| if output: | |
| hold_time = 1 | |
| return output[0]['generated_text'] | |
| else: | |
| wait_time = int((hold_time - time.time()) + 35) | |
| if wait_time >= 0: | |
| return f'Model is being loaded, please try again in {wait_time} seconds.' | |
| else: | |
| return 'Taking longer than usual to load, please wait.' | |
| response = requests.post(API_URL, headers=headers, json={ | |
| "inputs": 'احا', | |
| "parameters": {} | |
| }) | |
| if response.status_code != 200: | |
| print('Sleeping due to Model is being loaded') | |
| time.sleep(40) | |
| examples_text = [ | |
| ["ما ابغا أروح الإمتحان"], | |
| ["أييد أن انام ف لبيتنا"], | |
| ["Hello how are you today"], | |
| ["kef al7al"] | |
| ] | |
| def mode_run(text): | |
| result = run_model(text) | |
| return result | |
| link = '<a href="{}" target="_blank" style="cursor: pointer; font-size: 18px;">{}</a>' | |
| with gr.Blocks(theme=gr.themes.GoogleFont('ali')) as demo: | |
| gr.Markdown( | |
| """ | |
| ## Dialects to MSA transformer | |
| Start typing Non-Traditional Arabic to convert into Classical version. | |
| """ | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| input = gr.Textbox(label='Dialects') | |
| with gr.Column(): | |
| output = gr.Textbox(label='MSA') | |
| with gr.Row(): | |
| button = gr.Button('Submit',variant='primary') | |
| clear = gr.ClearButton(input) | |
| examples = gr.Examples(examples_text,input,output,mode_run,cache_examples=True) | |
| with gr.Row(): | |
| gr.Markdown( | |
| """ | |
| ## Model Overview | |
| This Model is optimized to convert written text in various non Standard Classical Arabic into Classic Arabic, the model was Fine-Tuned on 0.8M pairs of sentence generated by OpenAI API gpt-4o-mini Text Generation Model, beside being able to convert Dialects into Classical Arabic, the model can also be used in other NLP tasks such as Text Correction, Diacretization and Sentence Punctuation. | |
| """ | |
| ) | |
| with gr.Row(): | |
| gr.Markdown( | |
| """ | |
| ## Dielcts the Model trained on | |
| Below image shows an estimate of dialects the model trained on. | |
| """ | |
| ) | |
| with gr.Row(): | |
| with gr.Column(scale=3): | |
| gr.Image(Image.open('Dialects by Region.png'),height=300,container=False) | |
| with gr.Column(scale=3): | |
| pass | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| pass | |
| with gr.Column(scale=2): | |
| gr.HTML( | |
| '<div style="text-align: center;">' +\ | |
| link.format('https://huggingface.co/HamzaNaser/Dialects-to-MSA-Transformer', 'Model Card') + ' -- '+link.format('https://www.linkedin.com/in/hamza-naser-0b4b90160/', 'LinkedIn') +\ | |
| '</div>' | |
| ) | |
| with gr.Column(scale=1): | |
| pass | |
| input.submit(mode_run,input,output) | |
| button.click(mode_run,input,output) | |
| demo.launch() | |