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app.py

@@ -1,160 +1,27 @@
 import os
-os.environ.setdefault("CHATTERBOX_FLASH_ENGINE", "torch")
 os.environ.setdefault("NUMBA_DISABLE_CUDA", "1")
 
 import spaces
 import torch
-import numpy as np
-import gradio as gr
-
-# Install chatterbox-tts and chatterbox-flash with --no-deps to avoid
-# the torch==2.6.0 / gradio==6.8.0 pins (incompatible with ZeroGPU).
-# Their real deps are listed in requirements.txt.
-import subprocess
-import sys
+print(f"After import spaces: cuda_available={torch.cuda.is_available()}")
 
+# Install chatterbox packages
+import subprocess, sys
 subprocess.run(
     [sys.executable, "-m", "pip", "install", "--no-deps",
      "chatterbox-tts==0.1.7", "chatterbox-flash==0.1.0"],
     check=True,
 )
+print(f"After pip install: cuda_available={torch.cuda.is_available()}")
 
 from chatterbox_flash import ChatterboxFlashTTS
+print(f"After chatterbox import: cuda_available={torch.cuda.is_available()}")
 
-MODEL_ID = "ResembleAI/chatterbox-flash"
-DEVICE = "cuda"
-
-print(f"Loading Chatterbox-Flash from {MODEL_ID}...")
-tts = ChatterboxFlashTTS.from_pretrained(
-    MODEL_ID, device=DEVICE, dtype=torch.bfloat16,
-)
-print("Model loaded successfully.")
-
-
-@spaces.GPU(duration=120)
-def generate_tts(
-    text_input: str,
-    audio_prompt_path: str | None = None,
-    exaggeration: float = 0.5,
-    temperature: float = 0.6,
-    cfg_scale: float = 1.0,
-    num_steps: int = 10,
-    seed_num: int = 0,
-):
-    """Generate speech from text using Chatterbox-Flash block-diffusion TTS.
-
-    Zero-shot voice cloning: provide a short reference audio clip to clone
-    the speaker's voice, or leave it empty to use the default voice.
-
-    Args:
-        text_input: Text to synthesize (max 300 characters).
-        audio_prompt_path: Reference audio file for voice cloning (optional).
-        exaggeration: Controls speech expressiveness (0.25-2.0, 0.5=neutral).
-        temperature: Controls randomness in generation (0.05-5.0, higher=more varied).
-        cfg_scale: Classifier-free guidance scale (0.2-1.0).
-        num_steps: Number of block-diffusion denoising steps (default 10).
-        seed_num: Random seed for reproducibility (0=random).
-    """
-    if seed_num != 0:
-        torch.manual_seed(int(seed_num))
-        torch.cuda.manual_seed(int(seed_num))
-        np.random.seed(int(seed_num))
-
-    generate_kwargs = {
-        "exaggeration": exaggeration,
-        "temperature": temperature,
-        "cfg_scale": cfg_scale,
-        "num_steps": num_steps,
-        "backend": "torch",
-    }
-
-    if audio_prompt_path:
-        generate_kwargs["audio_prompt_path"] = audio_prompt_path
-
-    wav = tts.generate(text_input[:300], **generate_kwargs)
-    return (tts.sr, wav.squeeze(0).numpy())
-
-
-CSS = """
-#col-container { max-width: 1100px; margin: 0 auto; }
-.dark .gradio-container { color: var(--body-text-color); }
-"""
-
-with gr.Blocks() as demo:
-    gr.Markdown(
-        """
-        # Chatterbox-Flash TTS
-        Prior-calibrated block-diffusion zero-shot TTS by Resemble AI.
-        Provide a reference audio clip to clone a voice, or generate with the default voice.
-
-        [Paper](https://huggingface.co/papers/2605.30748) · [Model](https://huggingface.co/ResembleAI/chatterbox-flash) · [GitHub](https://github.com/resemble-ai/chatterbox-flash)
-        """
-    )
-
-    with gr.Row(elem_id="col-container"):
-        with gr.Column(scale=3):
-            text = gr.Textbox(
-                value="Sometimes it's better to just let things slide, you know?",
-                label="Text to synthesize (max 300 chars)",
-                max_lines=5,
-            )
-            ref_wav = gr.Audio(
-                sources=["upload", "microphone"],
-                type="filepath",
-                label="Reference Audio (optional — for voice cloning)",
-            )
-
-            with gr.Accordion("Advanced settings", open=False):
-                exaggeration = gr.Slider(
-                    0.25, 2.0, step=0.05,
-                    label="Exaggeration (0.5=neutral, higher=more expressive)",
-                    value=0.5,
-                )
-                temperature = gr.Slider(
-                    0.05, 2.0, step=0.05,
-                    label="Temperature",
-                    value=0.6,
-                )
-                cfg_scale = gr.Slider(
-                    0.2, 1.0, step=0.05,
-                    label="CFG Scale",
-                    value=1.0,
-                )
-                num_steps = gr.Slider(
-                    1, 30, step=1,
-                    label="Denoising Steps",
-                    value=10,
-                )
-                seed_num = gr.Number(
-                    value=0, label="Seed (0=random)", precision=0,
-                )
-
-            run_btn = gr.Button("Generate", variant="primary")
-
-        with gr.Column(scale=2):
-            audio_output = gr.Audio(label="Output Audio")
-
-    gr.Examples(
-        examples=[
-            ["Sometimes it's better to just let things slide, you know?"],
-            ["The quick brown fox jumps over the lazy dog. Pack my box with five dozen liquor jugs."],
-            ["In the depths of winter, I finally learned that within me lay an invincible summer."],
-        ],
-        inputs=[text],
-        outputs=[audio_output],
-        fn=generate_tts,
-        cache_examples=True,
-        cache_mode="lazy",
-    )
+import gradio as gr
 
-    run_btn.click(
-        fn=generate_tts,
-        inputs=[
-            text, ref_wav, exaggeration,
-            temperature, cfg_scale, num_steps, seed_num,
-        ],
-        outputs=[audio_output],
-        api_name="generate",
-    )
+@spaces.GPU(duration=60)
+def test_gpu():
+    return f"CUDA available: {torch.cuda.is_available()}, device count: {torch.cuda.device_count()}"
 
-demo.launch(mcp_server=True, theme=gr.themes.Citrus(), css=CSS)
+demo = gr.Interface(fn=test_gpu, inputs=gr.Textbox(value="test"), outputs=gr.Textbox())
+demo.launch(mcp_server=True)