Spaces:
Running
on
Zero
Running
on
Zero
Add download button
Browse files
app.py
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import os
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# Disable PyTorch dynamo/inductor globally
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os.environ["TORCHDYNAMO_DISABLE"] = "1"
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@@ -14,6 +15,7 @@ import torch
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import spaces
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import gradio as gr
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import numpy as np
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from voxtream.generator import SpeechGenerator, SpeechGeneratorConfig
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@@ -76,6 +78,11 @@ def float32_to_int16(audio_float32: np.ndarray) -> np.ndarray:
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return audio_int16
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@spaces.GPU
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def synthesize_fn(prompt_audio_path, prompt_text, target_text):
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if next(speech_generator.model.parameters()).device.type == "cpu":
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@@ -87,7 +94,8 @@ def synthesize_fn(prompt_audio_path, prompt_text, target_text):
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speech_generator.device = "cuda"
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if not prompt_audio_path or not target_text:
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return None
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stream = speech_generator.generate_stream(
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prompt_text=prompt_text,
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prompt_audio_path=Path(prompt_audio_path),
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buffer = []
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buffer_len = 0
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for frame, _ in stream:
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buffer.append(frame)
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buffer_len += frame.shape[0]
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if buffer_len >= CHUNK_SIZE:
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audio = np.concatenate(buffer)
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yield (config.mimi_sr, float32_to_int16(audio))
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# Reset buffer and length
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buffer = []
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if nfade > 0:
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fade = np.linspace(1.0, 0.0, nfade, dtype=np.float32)
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final[-nfade:] *= fade
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yield (config.mimi_sr, float32_to_int16(final))
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def main():
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interactive=False,
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streaming=True,
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autoplay=True,
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)
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with gr.Row():
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outputs=[validation_msg, submit_btn],
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)
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#
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submit_btn.click(
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fn=lambda a, p, t: None,
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inputs=[prompt_audio, prompt_text, target_text],
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outputs=output_audio,
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show_progress="hidden",
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).then(
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fn=synthesize_fn,
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inputs=[prompt_audio, prompt_text, target_text],
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outputs=output_audio,
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)
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clear_btn.click(
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fn=lambda: (
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inputs=[],
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outputs=[prompt_audio, prompt_text, target_text, output_audio, validation_msg, submit_btn],
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)
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# --- Add Examples ---
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gr.Markdown("### Examples")
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gr.Examples(
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examples=[
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[
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"assets/app/male.wav",
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],
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],
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inputs=[prompt_audio, prompt_text, target_text],
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outputs=output_audio,
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fn=synthesize_fn,
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cache_examples=
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)
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demo.launch()
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import os
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import uuid
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# Disable PyTorch dynamo/inductor globally
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os.environ["TORCHDYNAMO_DISABLE"] = "1"
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import spaces
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import gradio as gr
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import numpy as np
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import soundfile as sf
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from voxtream.generator import SpeechGenerator, SpeechGeneratorConfig
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return audio_int16
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def _clear_outputs():
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# clears the player + hides file (download btn mirrors file via .change)
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return None, gr.update(value=None, visible=False)
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@spaces.GPU
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def synthesize_fn(prompt_audio_path, prompt_text, target_text):
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if next(speech_generator.model.parameters()).device.type == "cpu":
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speech_generator.device = "cuda"
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if not prompt_audio_path or not target_text:
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return None, gr.update(value=None, visible=False)
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stream = speech_generator.generate_stream(
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prompt_text=prompt_text,
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prompt_audio_path=Path(prompt_audio_path),
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buffer = []
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buffer_len = 0
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total_buffer = []
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for frame, _ in stream:
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buffer.append(frame)
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total_buffer.append(frame)
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buffer_len += frame.shape[0]
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if buffer_len >= CHUNK_SIZE:
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audio = np.concatenate(buffer)
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yield (config.mimi_sr, float32_to_int16(audio)), None
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# Reset buffer and length
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buffer = []
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if nfade > 0:
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fade = np.linspace(1.0, 0.0, nfade, dtype=np.float32)
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final[-nfade:] *= fade
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yield (config.mimi_sr, float32_to_int16(final)), None
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# Save the full audio to a file for download
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if len(total_buffer) > 0:
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full_audio = np.concatenate(total_buffer)
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nfade = min(int(config.mimi_sr * FADE_OUT_SEC), full_audio.shape[0])
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if nfade > 0:
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fade = np.linspace(1.0, 0.0, nfade, dtype=np.float32)
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full_audio[-nfade:] *= fade
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file_path = f"/tmp/voxtream_{uuid.uuid4().hex}.wav"
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sf.write(file_path, float32_to_int16(full_audio), config.mimi_sr)
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yield None, gr.update(value=file_path, visible=True)
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else:
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yield None, gr.update(value=None, visible=False)
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def main():
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interactive=False,
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streaming=True,
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autoplay=True,
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show_download_button=False,
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show_share_button=False,
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)
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# appears only when file is ready
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download_btn = gr.DownloadButton(
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"Download audio",
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visible=False,
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)
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with gr.Row():
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outputs=[validation_msg, submit_btn],
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)
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# clear outputs before streaming
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submit_btn.click(
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fn=lambda a, p, t: (None, gr.update(value=None, visible=False)),
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inputs=[prompt_audio, prompt_text, target_text],
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outputs=[output_audio, download_btn],
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show_progress="hidden",
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).then(
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fn=synthesize_fn,
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inputs=[prompt_audio, prompt_text, target_text],
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outputs=[output_audio, download_btn],
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)
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clear_btn.click(
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fn=lambda: (
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None, "", "", # inputs
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None, # output_audio
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gr.update(value=None, visible=False), # download_btn
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gr.update(visible=False, value=""), # validation_msg
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gr.update(interactive=False), # submit_btn
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),
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inputs=[],
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outputs=[prompt_audio, prompt_text, target_text, output_audio, download_btn, validation_msg, submit_btn],
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)
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# --- Add Examples ---
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gr.Markdown("### Examples")
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ex = gr.Examples(
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examples=[
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[
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"assets/app/male.wav",
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],
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],
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inputs=[prompt_audio, prompt_text, target_text],
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outputs=[output_audio, download_btn],
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fn=synthesize_fn,
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cache_examples=False,
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)
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ex.dataset.click(
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fn=_clear_outputs,
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inputs=[],
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outputs=[output_audio, download_btn],
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queue=False,
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)
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demo.launch()
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gradio_cached_examples/16/Synthesized audio/95f83d950a0400b268bd/tmppmcwrg5n
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version https://git-lfs.github.com/spec/v1
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oid sha256:ac85b968e44a98af1e2f344ed56f68c700cd2b99a3c114d2552c66b2b6c2e957
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size 326444
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gradio_cached_examples/16/Synthesized audio/b5933b8060d980ce1ea1/tmp339_glws
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:7a15baf860116573dd4985238c7a05fe3120f3732b43bef7d8c8aa22e07b5fbd
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-
size 322604
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gradio_cached_examples/16/log.csv
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Synthesized audio,flag,username,timestamp
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"{""path"": ""gradio_cached_examples/16/Synthesized audio/95f83d950a0400b268bd/tmppmcwrg5n"", ""url"": null, ""size"": null, ""orig_name"": null, ""mime_type"": null, ""is_stream"": false, ""meta"": {""_type"": ""gradio.FileData""}}",,,2025-09-28 16:43:00.957637
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"{""path"": ""gradio_cached_examples/16/Synthesized audio/b5933b8060d980ce1ea1/tmp339_glws"", ""url"": null, ""size"": null, ""orig_name"": null, ""mime_type"": null, ""is_stream"": false, ""meta"": {""_type"": ""gradio.FileData""}}",,,2025-09-28 16:43:06.729484
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