Create app.py

app.py

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+import gradio as gr
+import torch
+import numpy as np
+from soprano import SopranoTTS
+from scipy.io.wavfile import write as wav_write
+import tempfile
+import os
+
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+print(DEVICE)
+
+# Load model once
+model = SopranoTTS(
+    backend="auto",
+    device=DEVICE,
+    cache_size_mb=100,
+    decoder_batch_size=1,
+)
+
+SAMPLE_RATE = 32000
+
+
+def tts_stream(text, temperature, top_p, repetition_penalty, state):
+    if not text.strip():
+        yield None, state
+        return
+
+    chunks = []
+    stream = model.infer_stream(
+        text,
+        chunk_size=1,
+        temperature=temperature,
+        top_p=top_p,
+        repetition_penalty=repetition_penalty,
+    )
+
+    for chunk in stream:
+        if isinstance(chunk, torch.Tensor):
+            audio_np = chunk.detach().cpu().numpy().astype(np.float32)
+            chunks.append(audio_np)
+            # stream partial audio
+            yield (SAMPLE_RATE, audio_np), np.concatenate(chunks)
+
+    if chunks:
+        final_audio = np.concatenate(chunks)
+        yield (SAMPLE_RATE, final_audio), final_audio
+
+
+def save_audio(state):
+    if state is None or len(state) == 0:
+        return None
+    fd, path = tempfile.mkstemp(suffix=".wav")
+    os.close(fd)
+    wav_write(path, SAMPLE_RATE, state)
+    return path
+
+
+with gr.Blocks() as demo:
+    state_audio = gr.State(None)
+
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("## Soprano Demo")
+
+            text_in = gr.Textbox(
+                label="Input Text",
+                placeholder="Enter text to synthesize...",
+                lines=4,
+            )
+
+            with gr.Accordion("Advanced options", open=False):
+                temperature = gr.Slider(
+                    0.0, 1.0, value=0.3, step=0.05, label="Temperature"
+                )
+                top_p = gr.Slider(
+                    0.0, 1.0, value=0.95, step=0.01, label="Top-p"
+                )
+                repetition_penalty = gr.Slider(
+                    0.5, 2.0, value=1.2, step=0.05, label="Repetition penalty"
+                )
+
+            gen_btn = gr.Button("Generate")
+
+        with gr.Column():
+            audio_out = gr.Audio(
+                label="Output Audio",
+                autoplay=True,
+                streaming=True,
+            )
+            download_btn = gr.Button("Download")
+            file_out = gr.File(label="Download file")
+            gr.Markdown(
+                "Usage tips: (placeholder)\n\n"
+                "- Tip 1\n"
+                "- Tip 2\n"
+                "- Tip 3"
+            )
+
+    gen_btn.click(
+        fn=tts_stream,
+        inputs=[text_in, temperature, top_p, repetition_penalty, state_audio],
+        outputs=[audio_out, state_audio],
+    )
+
+    download_btn.click(
+        fn=save_audio,
+        inputs=[state_audio],
+        outputs=[file_out],
+    )
+
+demo.queue()
+demo.launch()