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import gradio as gr
import json
from nameder import init_model_ner, get_entity_results
from speech2text import init_model_trans, transcribe
from translation import translate
from resources import NER_Response, NER_Request, entity_labels_sample, set_start, audit_elapsedtime
def translation_to_english(text: str):
resultado = translate(text)
return resultado
def transcription(audio: bytes):
s2t = init_model_trans()
return transcribe(audio, s2t)
def named_entity_recognition(text: str):
tokenizer, ner = init_model_ner()
# print('NER:',ner)
result = get_entity_results(entities_list=entity_labels_sample,
model=ner,
tokenizer=tokenizer,
text=text)
print('result:',result,type(result))
return result
def get_lead(audio: bytes):
start = set_start()
transcribe = transcription(audio)
translate = translation_to_english(transcribe)
ner = named_entity_recognition(NER_Request(
entities=entity_labels_sample,
text=translate
))
audit_elapsedtime("VoiceLead", start)
return ner
audio_input = gr.Microphone(
label="Record your audio"
)
text_output = gr.Textbox(
label="Labels",
info="",
lines=9,
value=""
)
demo = gr.Interface(
fn=named_entity_recognition,
description= "Get the ",
inputs=[audio_input],
outputs=[text_output],
title="VoiceLead"
)
if __name__ == "__main__":
demo.launch() |