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import time
import os
import numpy as np
import gradio as gr
import random
from fastrtc import AdditionalOutputs, WebRTC, ReplyOnPause, get_cloudflare_turn_credentials_async, get_cloudflare_turn_credentials
HF_TOKEN = os.getenv("HF_TOKEN")
async def get_credentials():
return await get_cloudflare_turn_credentials_async(hf_token=HF_TOKEN)
possible_responses = [
"hello",
"hi",
"how's it going?",
"what's up?",
"how's your day?",
"how are you?",
"what's your name?",
"where are you from?",
"what do you do?",
"what's your favorite color?",
"what's your favorite food?",
"what's your favorite movie?",
]
def transcribe(audio: tuple[int, np.ndarray]):
time.sleep(1)
transformers_convo = [
{"role": "assistant", "content": random.choice(possible_responses)}
]
yield AdditionalOutputs(transformers_convo)
with gr.Blocks() as demo:
gr.HTML(
"""
TEST
"""
)
test_state = gr.State()
with gr.Row():
with gr.Column():
audio = WebRTC(
label="Stream",
mode="send-receive",
modality="audio",
rtc_configuration=get_credentials,
server_rtc_configuration=get_cloudflare_turn_credentials(ttl=360_000),
)
with gr.Column():
transcript = gr.Chatbot(label="transcript", type="messages")
audio.stream(
ReplyOnPause(transcribe), inputs=[audio], outputs=[audio], time_limit=180
)
def handle_additional_outputs(outputs):
print(f"outputs: {outputs}")
return outputs
audio.on_additional_outputs(
fn=handle_additional_outputs,
outputs=[test_state],
concurrency_limit=100,
queue=True, #False,
show_progress="hidden",
)
gr.on(test_state.change, inputs=[test_state, transcript], outputs=[transcript])
def state_change(test_state, transcript):
print(f"test_state: {test_state}")
return test_state + transcript
demo.launch(server_name="0.0.0.0", server_port=7860, share=True)
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