Spaces:
Runtime error
Runtime error
add basic text to speech
Browse files- app.py +151 -0
- requirements.txt +13 -0
- sample_utils/__init__.py +0 -0
- sample_utils/__pycache__/__init__.cpython-310.pyc +0 -0
- sample_utils/__pycache__/__init__.cpython-39.pyc +0 -0
- sample_utils/__pycache__/download.cpython-310.pyc +0 -0
- sample_utils/__pycache__/turn.cpython-310.pyc +0 -0
- sample_utils/__pycache__/turn.cpython-39.pyc +0 -0
- sample_utils/download.py +50 -0
- sample_utils/turn.py +32 -0
app.py
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from collections import deque
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import os
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import threading
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import time
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import av
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import numpy as np
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import streamlit as st
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from streamlit_webrtc import WebRtcMode, webrtc_streamer
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import pydub
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# import av
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# import cv2
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from sample_utils.turn import get_ice_servers
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import json
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from typing import List
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from vosk import SetLogLevel, Model, KaldiRecognizer
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SetLogLevel(-1) # mutes vosk verbosity
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from dotenv import load_dotenv
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load_dotenv()
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system_one = {
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"audio_bit_rate": 16000,
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# "audio_bit_rate": 32000,
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# "audio_bit_rate": 48000,
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}
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playing = st.checkbox("Playing", value=True)
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def load_vosk (model='small'):
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# load vosk model
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# get path of current file
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current_file_path = os.path.abspath(__file__)
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current_directory = os.path.dirname(current_file_path)
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_path = os.path.join(current_directory, 'models', 'vosk', model)
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model_voice = Model(_path)
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recognizer = KaldiRecognizer(model_voice, system_one['audio_bit_rate'])
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return recognizer
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vask = load_vosk()
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def handle_audio_frame(frame):
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# if self.vosk.AcceptWaveform(data):
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pass
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def do_work(data: bytearray) -> tuple[str, bool]:
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text = ''
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speaker_finished = False
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if vask.AcceptWaveform(data):
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result = vask.Result()
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result_json = json.loads(result)
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text = result_json['text']
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speaker_finished = True
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else:
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result = vask.PartialResult()
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result_json = json.loads(result)
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text = result_json['partial']
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return text, speaker_finished
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frames_deque_lock = threading.Lock()
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frames_deque: deque = deque([])
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async def queued_audio_frames_callback(
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frames: List[av.AudioFrame],
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) -> av.AudioFrame:
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with frames_deque_lock:
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frames_deque.extend(frames)
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# create frames to be returned.
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new_frames = []
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for frame in frames:
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input_array = frame.to_ndarray()
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new_frame = av.AudioFrame.from_ndarray(
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np.zeros(input_array.shape, dtype=input_array.dtype),
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layout=frame.layout.name,
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)
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new_frame.sample_rate = frame.sample_rate
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new_frames.append(new_frame)
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# TODO: replace with the audio we want to send to the other side.
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return new_frames
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webrtc_ctx = webrtc_streamer(
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key="charles",
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desired_playing_state=playing,
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# audio_receiver_size=4096,
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# audio_frame_callback=process_audio,
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queued_audio_frames_callback=queued_audio_frames_callback,
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mode=WebRtcMode.SENDRECV,
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rtc_configuration={"iceServers": get_ice_servers()},
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async_processing=True,
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)
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system_one_audio_status = st.empty()
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if not webrtc_ctx.state.playing:
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exit
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system_one_audio_status.write("Initializing...")
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system_one_audio_output = st.empty()
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system_one_audio_history = []
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system_one_audio_history_output = st.empty()
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sound_chunk = pydub.AudioSegment.empty()
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while True:
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if webrtc_ctx.state.playing:
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audio_frames = []
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with frames_deque_lock:
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while len(frames_deque) > 0:
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frame = frames_deque.popleft()
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audio_frames.append(frame)
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if len(audio_frames) == 0:
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time.sleep(0.1)
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system_one_audio_status.write("No frame arrived.")
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continue
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system_one_audio_status.write("Running. Say something!")
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for audio_frame in audio_frames:
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sound = pydub.AudioSegment(
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data=audio_frame.to_ndarray().tobytes(),
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sample_width=audio_frame.format.bytes,
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frame_rate=audio_frame.sample_rate,
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channels=len(audio_frame.layout.channels),
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)
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sound = sound.set_channels(1)
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sound = sound.set_frame_rate(system_one['audio_bit_rate'])
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sound_chunk += sound
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if len(sound_chunk) > 0:
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buffer = np.array(sound_chunk.get_array_of_samples())
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text, speaker_finished = do_work(buffer.tobytes())
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system_one_audio_output.markdown(f"**System 1 Audio:** {text}")
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if speaker_finished and len(text) > 0:
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system_one_audio_history.append(text)
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if len(system_one_audio_history) > 10:
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system_one_audio_history = system_one_audio_history[-10:]
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table_content = "| System 1 Audio History |\n| --- |\n"
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table_content += "\n".join([f"| {item} |" for item in reversed(system_one_audio_history)])
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system_one_audio_history_output.markdown(table_content)
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sound_chunk = pydub.AudioSegment.empty()
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else:
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system_one_audio_status.write("Stopped.")
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break
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requirements.txt
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@@ -0,0 +1,13 @@
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vosk
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# scipy
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# sounddevice
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# setuptools-rust
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# git+https://github.com/openai/whisper.git
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opencv-python-headless
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pydub
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streamlit_webrtc
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twilio
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python-dotenv
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watchdog
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pydub
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sample_utils/__init__.py
ADDED
File without changes
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sample_utils/__pycache__/__init__.cpython-310.pyc
ADDED
Binary file (168 Bytes). View file
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sample_utils/__pycache__/__init__.cpython-39.pyc
ADDED
Binary file (166 Bytes). View file
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sample_utils/__pycache__/download.cpython-310.pyc
ADDED
Binary file (1.32 kB). View file
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sample_utils/__pycache__/turn.cpython-310.pyc
ADDED
Binary file (1.29 kB). View file
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sample_utils/__pycache__/turn.cpython-39.pyc
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Binary file (1.29 kB). View file
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sample_utils/download.py
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import urllib.request
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from pathlib import Path
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import streamlit as st
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# This code is based on https://github.com/streamlit/demo-self-driving/blob/230245391f2dda0cb464008195a470751c01770b/streamlit_app.py#L48 # noqa: E501
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def download_file(url, download_to: Path, expected_size=None):
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# Don't download the file twice.
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# (If possible, verify the download using the file length.)
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if download_to.exists():
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if expected_size:
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if download_to.stat().st_size == expected_size:
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return
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else:
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st.info(f"{url} is already downloaded.")
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if not st.button("Download again?"):
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return
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download_to.parent.mkdir(parents=True, exist_ok=True)
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# These are handles to two visual elements to animate.
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weights_warning, progress_bar = None, None
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try:
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weights_warning = st.warning("Downloading %s..." % url)
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progress_bar = st.progress(0)
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with open(download_to, "wb") as output_file:
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with urllib.request.urlopen(url) as response:
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length = int(response.info()["Content-Length"])
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counter = 0.0
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MEGABYTES = 2.0 ** 20.0
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while True:
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data = response.read(8192)
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if not data:
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break
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counter += len(data)
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output_file.write(data)
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# We perform animation by overwriting the elements.
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weights_warning.warning(
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"Downloading %s... (%6.2f/%6.2f MB)"
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% (url, counter / MEGABYTES, length / MEGABYTES)
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)
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progress_bar.progress(min(counter / length, 1.0))
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# Finally, we remove these visual elements by calling .empty().
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finally:
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if weights_warning is not None:
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weights_warning.empty()
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if progress_bar is not None:
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progress_bar.empty()
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sample_utils/turn.py
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import logging
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import os
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import streamlit as st
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from twilio.rest import Client
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logger = logging.getLogger(__name__)
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@st.cache_data
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def get_ice_servers():
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"""Use Twilio's TURN server because Streamlit Community Cloud has changed
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its infrastructure and WebRTC connection cannot be established without TURN server now. # noqa: E501
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We considered Open Relay Project (https://www.metered.ca/tools/openrelay/) too,
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but it is not stable and hardly works as some people reported like https://github.com/aiortc/aiortc/issues/832#issuecomment-1482420656 # noqa: E501
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See https://github.com/whitphx/streamlit-webrtc/issues/1213
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"""
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# Ref: https://www.twilio.com/docs/stun-turn/api
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try:
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account_sid = os.environ["TWILIO_ACCOUNT_SID"]
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auth_token = os.environ["TWILIO_AUTH_TOKEN"]
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except KeyError:
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logger.warning(
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"Twilio credentials are not set. Fallback to a free STUN server from Google." # noqa: E501
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)
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return [{"urls": ["stun:stun.l.google.com:19302"]}]
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client = Client(account_sid, auth_token)
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token = client.tokens.create()
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return token.ice_servers
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