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| import os | |
| import gradio as gr | |
| #HF_TOKEN = os.environ.get("HF_TOKEN") | |
| #print("is none?", HF_TOKEN is None) | |
| def get_record(language,text,record): | |
| # Save text and its corresponding record to flag | |
| text =text.strip() | |
| #output_string = "<html> <body> <div class='output'>"+f'Record for text {text} successfully saved to dataset! Thank You.'+"</div> </body> </html>" | |
| output_string = f'Record for text - {text} - successfully saved to dataset! Thank You.' | |
| return output_string | |
| title = 'African Crowdsource Speech' | |
| description = 'A platform to contribute to your African language by recording your voice' | |
| markdown = """# African Crowdsource Speech | |
| A platform to contribute to your African language by recording your voice | |
| """ | |
| # Get a dropdown of all African languages | |
| # Interface design begins | |
| #import pdb; pdb.set_trace() | |
| iface = gr.Interface(fn=get_record, | |
| inputs=[gr.inputs.Textbox(placeholder='Choose your language'), | |
| gr.inputs.Textbox(placeholder='Write your text'), | |
| gr.inputs.Audio(source="microphone",label='Record your voice') | |
| ], | |
| outputs = "text", | |
| title=title, | |
| description=description, | |
| theme='huggingface' | |
| ) | |
| iface.launch() |