Create app.py

app.py

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+import gradio as gr
+from outetts.v0_1.interface import InterfaceHF
+
+interface = InterfaceHF("OuteAI/OuteTTS-0.1-350M")
+
+def generate_tts(text, temperature, repetition_penalty, reference_audio, reference_text):
+
+    if reference_audio and reference_text:
+        speaker = interface.create_speaker(reference_audio, reference_text)
+    else:
+        speaker = None
+
+    output = interface.generate(
+        text=text,
+        speaker=speaker,
+        temperature=temperature,
+        repetition_penalty=repetition_penalty
+    )
+    output.save("output.wav")
+    return "output.wav"
+
+with gr.Blocks() as demo:
+    gr.Markdown("# OuteTTS-0.1-350M Text-to-Speech Demo")
+
+    with gr.Row():
+        with gr.Column():
+            text_input = gr.Textbox(label="Text to Synthesize", placeholder="Enter text here...")
+            temperature = gr.Slider(0.1, 1.0, value=0.1, label="Temperature")
+            repetition_penalty = gr.Slider(0.5, 2.0, value=1.1, label="Repetition Penalty")
+
+            gr.Markdown("""
+**Note**: For voice cloning, both a reference audio file and its corresponding transcription must be provided.
+If either the audio file or transcription is missing, the model will generate audio with random characteristics.""")
+            reference_audio = gr.Audio(label="Reference Audio (for voice cloning)", type="filepath")
+            reference_text = gr.Textbox(label="Reference Transcription Text (matching the audio)", placeholder="Enter reference text here if using voice cloning")
+            submit_button = gr.Button("Generate Speech")
+        with gr.Column():
+            audio_output = gr.Audio(label="Generated Audio", type="filepath")
+
+    submit_button.click(
+        fn=generate_tts,
+        inputs=[text_input, temperature, repetition_penalty, reference_audio, reference_text],
+        outputs=audio_output
+    )
+
+demo.launch()