Spaces:
Runtime error
Runtime error
File size: 3,595 Bytes
16d35dc cda6806 3caa7d1 cda6806 16d35dc 0e00791 cda6806 16d35dc cda6806 16d35dc ff44154 cda6806 16d35dc cda6806 8752186 16d35dc cda6806 16d35dc ff44154 cda6806 16d35dc cda6806 b270fe6 cda6806 16d35dc ff44154 16d35dc cda6806 |
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 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 |
import tempfile
import gradio as gr
from neon_tts_plugin_coqui import CoquiTTS
LANGUAGES = list(CoquiTTS.langs.keys())
default_lang = "en"
# ChatGPT
from pyChatGPT import ChatGPT
import whisper
whisper_model = whisper.load_model("small")
import os
session_token = os.environ.get('SessionToken')
title = "Speech to ChatGPT to Speech"
#info = "more info at [Neon Coqui TTS Plugin](https://github.com/NeonGeckoCom/neon-tts-plugin-coqui), [Coqui TTS](https://github.com/coqui-ai/TTS)"
#badge = "https://visitor-badge-reloaded.herokuapp.com/badge?page_id=neongeckocom.neon-tts-plugin-coqui"
coquiTTS = CoquiTTS()
# ChatGPT
def chat_hf(audio, custom_token, language):
try:
whisper_text = translate(audio)
api = ChatGPT(session_token)
resp = api.send_message(whisper_text)
api.refresh_auth() # refresh the authorization token
api.reset_conversation() # reset the conversation
gpt_response = resp['message']
except:
whisper_text = translate(audio)
api = ChatGPT(custom_token)
resp = api.send_message(whisper_text)
api.refresh_auth() # refresh the authorization token
api.reset_conversation() # reset the conversation
gpt_response = resp['message']
# to voice
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
coquiTTS.get_tts(gpt_response, fp, speaker = {"language" : language})
return whisper_text, gpt_response, fp.name
# whisper
def translate(audio):
print("""
—
Sending audio to Whisper ...
—
""")
audio = whisper.load_audio(audio)
audio = whisper.pad_or_trim(audio)
mel = whisper.log_mel_spectrogram(audio).to(whisper_model.device)
_, probs = whisper_model.detect_language(mel)
transcript_options = whisper.DecodingOptions(task="transcribe", fp16 = False)
transcription = whisper.decode(whisper_model, mel, transcript_options)
print("language spoken: " + transcription.language)
print("transcript: " + transcription.text)
print("———————————————————————————————————————————")
return transcription.text
with gr.Blocks() as blocks:
gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>"
+ title
+ "</h1>")
#gr.Markdown(description)
with gr.Row(equal_height=True):# equal_height=False
with gr.Column():# variant="panel"
audio_file = gr.inputs.Audio(source="microphone", type="filepath")
custom_token = gr.Textbox(label='If it fails, use your own session token', placeholder="your own session token")
radio = gr.Radio(
label="Language",
choices=LANGUAGES,
value=default_lang
)
with gr.Row():# mobile_collapse=False
submit = gr.Button("Submit", variant="primary")
with gr.Column():
text1 = gr.Textbox(label="Speech to Text")
text2 = gr.Textbox(label="chatGPT response")
audio = gr.Audio(label="Output", interactive=False)
#gr.Markdown(info)
#gr.Markdown("<center>"
# +f'<img src={badge} alt="visitors badge"/>'
# +"</center>")
# actions
submit.click(
chat_hf,
[audio_file, custom_token, radio],
[text1, text2, audio],
)
radio.change(lambda lang: CoquiTTS.langs[lang]["sentence"], radio, text2)
blocks.launch(debug=True)
|