Create app.py

app.py

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+import gradio as gr
+import torch
+import soundfile as sf
+from qwen_tts import Qwen3TTSModel
+from langdetect import detect
+import os
+
+# Load model - optimized for BF16 to save memory
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model_id = "Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice"
+
+print(f"Loading model to {device}...")
+model = Qwen3TTSModel.from_pretrained(
+    model_id,
+    device_map=device,
+    torch_dtype=torch.bfloat16 if device == "cuda" else torch.float32
+)
+
+def smart_tts(text, voice, instructions, auto_detect):
+    try:
+        # Smart Language Detection
+        lang_map = {
+            'zh': 'Chinese', 'en': 'English', 'jp': 'Japanese', 
+            'ko': 'Korean', 'de': 'German', 'fr': 'French', 
+            'ru': 'Russian', 'pt': 'Portuguese', 'es': 'Spanish', 'it': 'Italian'
+        }
+        
+        detected_lang = "English" # Default
+        if auto_detect:
+            try:
+                raw_lang = detect(text).split('-')[0]
+                detected_lang = lang_map.get(raw_lang, "English")
+            except:
+                pass
+
+        # Generate Audio
+        # The CustomVoice model uses instructions for style/emotion
+        wavs, sr = model.generate_custom_voice(
+            language=detected_lang,
+            speaker=voice,
+            instruct=instructions,
+            text=text
+        )
+        
+        output_path = "output.wav"
+        sf.write(output_path, wavs[0], sr)
+        return output_path, f"Detected Language: {detected_lang}"
+        
+    except Exception as e:
+        return None, str(e)
+
+# UI Layout
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown(f"# 🗣️ Qwen3-TTS Smart Studio")
+    gr.Markdown("Experience natural speech with style control using Qwen3-TTS-12Hz.")
+    
+    with gr.Row():
+        with gr.Column():
+            input_text = gr.Textbox(
+                label="Input Text", 
+                placeholder="Type something here...",
+                lines=4
+            )
+            
+            with gr.Row():
+                voice_select = gr.Dropdown(
+                    choices=["Vivian", "Ryan", "Bella", "Daisy", "George"], 
+                    value="Vivian", 
+                    label="Speaker"
+                )
+                auto_lang = gr.Checkbox(label="Auto-detect Language", value=True)
+            
+            style_instruct = gr.Textbox(
+                label="Style Instruction (e.g., 'Speak with a happy tone')", 
+                placeholder="Angry, Sad, Excited, Whisper...",
+                value="Speak naturally"
+            )
+            
+            generate_btn = gr.Button("Generate Speech", variant="primary")
+            
+        with gr.Column():
+            audio_output = gr.Audio(label="Generated Audio", type="filepath")
+            status_info = gr.Label(label="System Status")
+
+    generate_btn.click(
+        fn=smart_tts,
+        inputs=[input_text, voice_select, style_instruct, auto_lang],
+        outputs=[audio_output, status_info]
+    )
+
+if __name__ == "__main__":
+    demo.launch()