File size: 2,214 Bytes
dabe589 f4abbca 8786bb1 f4abbca 8786bb1 f4abbca 8786bb1 f4abbca 8786bb1 4832d73 f4abbca 8786bb1 f4abbca 8786bb1 f4abbca 8786bb1 bf32783 f4abbca 8786bb1 bf32783 8786bb1 f4abbca 8786bb1 f4abbca 8786bb1 f4abbca 8786bb1 f4abbca 8786bb1 f4abbca dabe589 6fd068e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 |
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_Request, entity_labels_sample, set_start, audit_elapsedtime
import ast
import numpy as np
def translation_to_english(text: str):
resultado = translate(text)
return resultado
def transcription(audio):
s2t = init_model_trans()
sr, y = audio
y = y.astype(np.float32)
y /= np.max(np.abs(y))
return transcribe({"sampling_rate": sr, "raw": y}, s2t)
def named_entity_recognition(req: NER_Request):
ner = init_model_ner()
result = get_entity_results(entities_list=req.entities,#entity_labels_sample,
model=ner,
text=req.text)
print('result:',result,type(result))
return json.dumps(result)
def get_lead(audio: bytes, labels: str, input_text: str):
print("audio",audio,type(audio))
print("input text:",input_text)
print("labels:",labels)
start = set_start()
labels_list = ast.literal_eval(labels)
if audio == None:
text = input_text
else:
transcribe = transcription(audio)
text = translation_to_english(transcribe)
lead_input.value = text
ner = named_entity_recognition(NER_Request(
entities=labels_list,
text=text
))
audit_elapsedtime("VoiceLead", start)
return ner
audio_input = gr.Audio(
label="Record your audio"
)
labels_input = gr.Textbox(
label="Labels",
info="Choose your labels",
value=entity_labels_sample
)
lead_input = gr.Textbox(
label="Lead",
info="[Optional] Input your lead",
lines=9,
value="I have a lead that Salesforce needs 3 developers for 600 euros a day, for 6 months"
)
text_output = gr.Textbox(
label="Labels",
info="",
lines=9,
value=""
)
ui = gr.Interface(
fn=get_lead,
description= "Voice your lead",
inputs=[audio_input, labels_input, lead_input],
outputs=[text_output],
title="VoiceLead"
)
if __name__ == "__main__":
ui.launch() |