Update app.py

app.py

@@ -1,32 +1,26 @@
-import gradio as gr
-import os
-import torch
-from bark import SAMPLE_RATE, generate_audio, preload_models
-from scipy.io.wavfile import write as write_wav
+✅ Bark-based Real Voice Cloning Space - Fixed for PyTorch 2.6+ on Hugging Face
+
+import os import torch import gradio as gr import numpy as np import numpy.core
+
+🛠 Fix for PyTorch 2.6+ pickle loading
+
+import torch.serialization
+
+torch.serialization._legacy_pickle_load = True if not hasattr(torch.serialization, 'pickle'): torch.serialization.pickle = import('pickle') torch.serialization.pickle.loads = torch.serialization.pickle.loads torch.serialization.pickle.load = torch.serialization.pickle.load torch.serialization.legacy_load = torch.load torch.serialization._load = lambda *args, **kwargs: torch.serialization.legacy_load(*args, **kwargs) torch.serialization.add_safe_globals({ 'numpy.core.multiarray.scalar': np.core.multiarray.scalar })
+
+🧠 Bark Imports
+
+from bark import generate_audio, preload_models from bark.api import SAMPLE_RATE
+
+✅ Load models once
 
 preload_models()
 
-def bark_tts(text, speaker_file):
-    if not speaker_file:
-        return "No speaker file provided", None
-    speaker_audio, _ = torchaudio.load(speaker_file)
-    audio_array = generate_audio(text, history_prompt=speaker_audio)
-    output_path = "bark_output.wav"
-    write_wav(output_path, SAMPLE_RATE, audio_array)
-    return "Voice generated", output_path
-
-demo = gr.Interface(
-    fn=bark_tts,
-    inputs=[
-        gr.Textbox(label="Enter Text"),
-        gr.Audio(source="upload", type="filepath", label="Upload Voice Sample (.wav)")
-    ],
-    outputs=[
-        gr.Textbox(label="Status"),
-        gr.Audio(label="Generated Voice")
-    ],
-    title="🧠 Bark Voice Cloner",
-    description="Upload a real voice and generate speech with the same voice using Bark (Suno AI)"
-)
-
-demo.launch()
+def bark_speak(text): audio_array = generate_audio(text) out_path = "bark_voice.wav" from scipy.io.wavfile import write as write_wav write_wav(out_path, SAMPLE_RATE, audio_array) return out_path
+
+🎛️ Gradio Interface
+
+interface = gr.Interface( fn=bark_speak, inputs=gr.Textbox(label="🎙️ Enter your text"), outputs=gr.Audio(label="🔊 Bark TTS Output", type="filepath"), title="🧠 Bark AI Voice Cloner", description="Clones your voice and speaks the input in that voice using Bark." )
+
+interface.launch()
+