Spaces:
Running on Zero
Running on Zero
update example
Browse files- app.py +135 -0
- asset/reference_02_s1.wav +3 -0
- asset/reference_02_s2.wav +3 -0
app.py
CHANGED
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@@ -39,6 +39,66 @@ DEFAULT_ATTN_IMPLEMENTATION = "auto"
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DEFAULT_MAX_NEW_TOKENS = 2000
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MIN_SPEAKERS = 1
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MAX_SPEAKERS = 5
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def resolve_attn_implementation(requested: str, device: torch.device, dtype: torch.dtype) -> str | None:
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@@ -212,6 +272,59 @@ def update_speaker_panels(speaker_count: int):
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return [gr.update(visible=(idx < count)) for idx in range(MAX_SPEAKERS)]
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def _merge_consecutive_speaker_tags(text: str) -> str:
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segments = re.split(r"(?=\[S\d+\])", text)
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if not segments:
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@@ -609,12 +722,34 @@ def build_demo(args: argparse.Namespace):
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output_audio = gr.Audio(label="Output Audio", type="numpy", elem_id="output_audio")
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gr.HTML("", elem_id="output_audio_spacer")
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status = gr.Textbox(label="Status", lines=4, interactive=False, elem_id="output_status")
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speaker_count.change(
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fn=update_speaker_panels,
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inputs=[speaker_count],
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outputs=speaker_panels,
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)
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run_btn.click(
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fn=run_inference,
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DEFAULT_MAX_NEW_TOKENS = 2000
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MIN_SPEAKERS = 1
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MAX_SPEAKERS = 5
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PRESET_REF_AUDIO_S1 = "asset/reference_02_s1.wav"
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PRESET_REF_AUDIO_S2 = "asset/reference_02_s2.wav"
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PRESET_PROMPT_TEXT_S1 = (
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"[S1] In short, we embarked on a mission to make America great again for all Americans."
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)
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PRESET_PROMPT_TEXT_S2 = (
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"[S2] NVIDIA reinvented computing for the first time after 60 years. In fact, Erwin at IBM knows quite "
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"well that the computer has largely been the same since the 60s."
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)
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PRESET_DIALOGUE_TEXT = (
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"[S1] Listen, let's talk business. China. I'm hearing things.\n"
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"People are saying they're catching up. Fast. What's the real scoop?\n"
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"Their AI, is it a threat?\n"
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"[S2] Well, the pace of innovation there is extraordinary, honestly.\n"
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"They have the researchers, and they have the drive.\n"
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"[S1] Extraordinary? I don't like that. I want us to be extraordinary.\n"
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"Are they winning?\n"
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"[S2] I wouldn't say winning, but their progress is very promising.\n"
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"They are building massive clusters. They're very determined.\n"
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"[S1] Promising. There it is. I hate that word.\n"
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"When China is promising, it means we're losing.\n"
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"It's a disaster, Jensen. A total disaster."
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)
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PRESET_EXAMPLES = [
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{
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"name": "Quick Start | reference_02_s1/s2",
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"speaker_count": 2,
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"s1_audio": PRESET_REF_AUDIO_S1,
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"s1_prompt": PRESET_PROMPT_TEXT_S1,
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"s2_audio": PRESET_REF_AUDIO_S2,
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"s2_prompt": PRESET_PROMPT_TEXT_S2,
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"dialogue_text": PRESET_DIALOGUE_TEXT,
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}
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]
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PRESET_DISPLAY_FIELDS = [
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("Speaker Count", "speaker_count"),
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("S1 Reference Audio (Optional)", "s1_audio"),
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("S1 Prompt Text (Required with reference audio)", "s1_prompt"),
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("S2 Reference Audio (Optional)", "s2_audio"),
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("S2 Prompt Text (Required with reference audio)", "s2_prompt"),
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("Dialogue Text", "dialogue_text"),
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]
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def _build_preset_table_rows():
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rows = []
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row_to_preset = []
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for preset_idx, preset in enumerate(PRESET_EXAMPLES):
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for field_name, field_key in PRESET_DISPLAY_FIELDS:
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value = str(preset.get(field_key, ""))
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if field_key == "dialogue_text":
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value = value.replace("\n", " ").strip()
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if len(value) > 120:
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value = value[:120] + " ..."
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rows.append([field_name, value])
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row_to_preset.append(preset_idx)
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return rows, row_to_preset
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PRESET_TABLE_ROWS, PRESET_TABLE_ROW_TO_PRESET = _build_preset_table_rows()
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def resolve_attn_implementation(requested: str, device: torch.device, dtype: torch.dtype) -> str | None:
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return [gr.update(visible=(idx < count)) for idx in range(MAX_SPEAKERS)]
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def apply_preset_selection(evt: gr.SelectData):
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if evt is None or evt.index is None:
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return (
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gr.update(),
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gr.update(),
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gr.update(),
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gr.update(),
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gr.update(),
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gr.update(),
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*[gr.update() for _ in range(MAX_SPEAKERS)],
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)
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if isinstance(evt.index, (tuple, list)):
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row_idx = int(evt.index[0])
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else:
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row_idx = int(evt.index)
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if row_idx < 0 or row_idx >= len(PRESET_TABLE_ROW_TO_PRESET):
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return (
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gr.update(),
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gr.update(),
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gr.update(),
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gr.update(),
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gr.update(),
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gr.update(),
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*[gr.update() for _ in range(MAX_SPEAKERS)],
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)
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preset_idx = PRESET_TABLE_ROW_TO_PRESET[row_idx]
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if preset_idx < 0 or preset_idx >= len(PRESET_EXAMPLES):
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return (
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gr.update(),
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gr.update(),
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gr.update(),
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gr.update(),
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gr.update(),
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gr.update(),
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*[gr.update() for _ in range(MAX_SPEAKERS)],
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)
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preset = PRESET_EXAMPLES[preset_idx]
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panel_updates = update_speaker_panels(int(preset["speaker_count"]))
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return (
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gr.update(value=int(preset["speaker_count"])),
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gr.update(value=str(preset["s1_audio"])),
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gr.update(value=str(preset["s1_prompt"])),
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gr.update(value=str(preset["s2_audio"])),
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gr.update(value=str(preset["s2_prompt"])),
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gr.update(value=str(preset["dialogue_text"])),
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*panel_updates,
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)
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def _merge_consecutive_speaker_tags(text: str) -> str:
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segments = re.split(r"(?=\[S\d+\])", text)
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if not segments:
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output_audio = gr.Audio(label="Output Audio", type="numpy", elem_id="output_audio")
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gr.HTML("", elem_id="output_audio_spacer")
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status = gr.Textbox(label="Status", lines=4, interactive=False, elem_id="output_status")
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preset_examples = gr.Dataframe(
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headers=["Field", "Value (click any row to fill inputs)"],
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value=PRESET_TABLE_ROWS,
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datatype=["str", "str"],
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row_count=(len(PRESET_TABLE_ROWS), "fixed"),
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col_count=(2, "fixed"),
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interactive=False,
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wrap=True,
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label="Preset Examples",
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)
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speaker_count.change(
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fn=update_speaker_panels,
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inputs=[speaker_count],
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outputs=speaker_panels,
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)
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preset_examples.select(
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fn=apply_preset_selection,
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outputs=[
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speaker_count,
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speaker_refs[0],
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speaker_prompts[0],
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speaker_refs[1],
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speaker_prompts[1],
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dialogue_text,
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*speaker_panels,
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],
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)
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run_btn.click(
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fn=run_inference,
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asset/reference_02_s1.wav
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:1816ab428334ba2de49dcb8b0a10e17eb1835f7f1f7bcda13504e88f46bed1e8
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size 249284
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asset/reference_02_s2.wav
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:0a407b1cba86ee320849208f4de0a437a0cb6ab4dbc52a595d99fbffda98aa35
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size 2268548
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