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import os
from pathlib import Path
import pandas as pd
import torchaudio
import torch
import numpy as np
import gradio as gr
from dotenv import load_dotenv
from fastrtc import (
get_cloudflare_turn_credentials_async,
get_cloudflare_turn_credentials,
WebRTC,
ReplyOnPause,
)
from transformers import AutoProcessor, SeamlessM4Tv2Model
load_dotenv(override=True)
parent_dir = Path(__file__).parents[1]
config_path = Path(parent_dir, "configs")
processor = AutoProcessor.from_pretrained("facebook/seamless-m4t-v2-large")
model = SeamlessM4Tv2Model.from_pretrained("facebook/seamless-m4t-v2-large")
default_sampling_rate = 16_000
HF_TOKEN = os.getenv("HF_TOKEN")
async def get_credentials():
return await get_cloudflare_turn_credentials_async(hf_token=HF_TOKEN)
def translate_audio(
audio: tuple[int, np.ndarray], tgt_language: str
) -> tuple[int, np.ndarray]:
"""Translate the audio that is captured through the streaming component.
Source language of the audio has to be one of the supported languages to be successful.
:param audio: the captured audio
:type audio: tuple[int, np.ndarray]
:param tgt_language: the target language for translation
:type tgt_language: str
:yield: the tuple containing the sampling rate and the audio array
:rtype: tuple[int, np.ndarray]
"""
orig_freq, np_array = audio
waveform = torch.from_numpy(np_array)
waveform = waveform.to(torch.float32)
waveform = waveform / 32768.0 # normalize int16 to [-1, 1]
audio = torchaudio.functional.resample(
waveform, orig_freq=orig_freq, new_freq=default_sampling_rate
) # must be a 16 kHz waveform array
audio_inputs = processor(
audios=audio,
return_tensors="pt",
sampling_rate=default_sampling_rate,
)
audio_array_from_audio = (
model.generate(**audio_inputs, tgt_lang=tgt_language)[0].cpu().numpy().squeeze()
)
yield (default_sampling_rate, audio_array_from_audio)
# Supported target languages for speech
supported_langs_df = pd.read_excel(Path(config_path, "supported_languages.xlsx"))
supported_speech_langs_df = supported_langs_df[
supported_langs_df["Target"].str.contains("Sp")
]
# Labels and values for supported speech languages dropdown
supported_speech_langs = list(
zip(supported_speech_langs_df["language"], supported_speech_langs_df["code"])
)
# Sort by the first element of the tuple (full language name)
supported_speech_langs.sort()
css = """
#componentsContainer {
width: 70%;
display: block;
margin-left: auto;
margin-right: auto;
}
#langDropdown .container .wrap {
width: 230px;
}
.audio-container {
padding-bottom: 2rem !important;
margin-bottom: 2rem !important;
}
.vspace-sm { margin-bottom: 20px !important; }
.vspace-md { margin-bottom: 40px !important; }
.vspace-lg { margin-bottom: 60px !important; }
.tagline {
color: #4a5568;
}
.tagline-emphasis {
font-family: 'Playfair Display', serif;
font-style: italic;
color: #718096;
position: relative;
display: inline-block;
}
.tagline-emphasis:after {
content: "";
position: absolute;
bottom: -5px;
left: 0;
width: 100%;
height: 2px;
background: linear-gradient(90deg, transparent, #6a11cb, transparent);
}
.gradio-footer {
position: fixed;
bottom: 0;
left: 0;
right: 0;
text-align: center;
padding: 12px;
background: var(--background-fill-secondary);
border-top: 1px solid var(--border-color-primary);
font-size: 0.9em;
z-index: 100;
display: flex;
justify-content: center;
align-items: center;
gap: 6px;
}
.gradio-footer a {
display: inline-flex;
align-items: center;
gap: 4px;
color: var(--link-text-color);
text-decoration: none;
}
.fastrtc-icon {
height: 24px;
width: 24px;
}
"""
with gr.Blocks(
theme=gr.themes.Glass(),
css=css,
) as demo:
gr.HTML(
"""
<div style='display: flex; align-items: center; justify-content: center; gap: 20px'>
<div style="background-color: var(--block-background-fill); border-radius: 8px">
<img src="https://images.icon-icons.com/3975/PNG/512/translation_language_translator_icon_251869.png" style="width: 100px; height: 100px;">
</div>
<div>
<h1>TalkGlobe</h1>
<p class="tagline">
Break language barriers in real-time <span class="globe-icon">🌍</span><br>
<span class="tagline-emphasis">no more lost in translation</span> <span class="globe-icon">✨</span>
</p>
</div>
</div>
""",
elem_classes="vspace-sm",
)
# The main components (translation language dropdown and streaming capture component)
with gr.Group(elem_id="componentsContainer"):
with gr.Row(equal_height=True, min_height="11rem"):
with gr.Column(scale=5, elem_id="langCol"):
target_lang = gr.Dropdown(
choices=supported_speech_langs,
value="eng",
label="Supported Languages",
info="Select one of the supported languages for translation",
elem_id="langDropdown",
)
with gr.Column(scale=5, elem_id="micCol"):
audio = WebRTC(
modality="audio",
mode="send-receive",
label="Audio Stream",
rtc_configuration=get_credentials,
server_rtc_configuration=get_cloudflare_turn_credentials(
ttl=360_000
),
)
# Trigger on pause
audio.stream(
ReplyOnPause(translate_audio),
inputs=[audio, target_lang],
outputs=[audio],
concurrency_limit=5,
time_limit=60,
)
# Sticky footer (will stay at bottom on all screen sizes)
gr.HTML(
"""
<div class="gradio-footer">
Powered by
<a href="https://gradio.app/" target="_blank">
Gradio <img class="gradio-icon" src="https://www.gradio.app/_app/immutable/assets/gradio.CHB5adID.svg" alt="GradioIcon" style="height:24px; width:auto;">
</a>
•
<a href="https://freddyaboulton.github.io/gradio-webrtc/" target="_blank">
FastRTC <img class="fastrtc-icon" src="https://fastrtc.org/fastrtc_logo.png" alt="FastRTCIcon">
</a>
</div>
"""
)
demo.launch()
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