Create app.py

app.py

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+"""PUBLIC
+Simple demo app.
+
+Copyright PolyAI Limited.
+"""
+import time
+from pathlib import Path
+
+import gradio as gr
+
+from transformer_infer import PhemeClient, parse_arguments
+
+# TODO
+VOICE_OPTIONS = [
+        "male_voice",
+        "POD1000000004_S0000246",
+        "POD1000000018_S0000253",
+        "POD1000000048_S0000035",
+        "YOU1000000006_S0000051",
+        "YOU1000000044_S0000798",
+        "empress",
+]
+
+args = parse_arguments()
+model = PhemeClient(args)
+
+
+def inference(
+    text,
+    voice,
+    top_k,
+    temperature
+):
+    with open("PhemeVoice.log", "a") as f:
+        f.write(f"{voice}: {text} \n")
+    start_time = time.time()
+
+    data = model.infer(
+        text, voice, top_k=top_k, temperature=temperature)
+    samplerate = 16_000
+    print("Time taken: ", time.time() - start_time)
+    yield (samplerate, data)
+
+
+def main():
+    title = "Pheme"
+    description = """Model can generate a variety of conversational voices."""
+    text = gr.Textbox(
+        lines=3,
+        value="Our property has several wedding venues.",
+        label="Text",
+    )
+
+    voice = gr.Dropdown(
+        VOICE_OPTIONS, value="empress", label="Select voice:", type="value"
+    )
+    temperature = gr.Slider(minimum=.3, maximum=1.5, value=0.7, step=0.05)
+    top_k = gr.Slider(minimum=10, maximum=250, value=210)
+    output_audio = gr.Audio(label="audio:", autoplay=True)
+    interface = gr.Interface(
+        fn=inference,
+        inputs=[
+            text,
+            voice,
+            top_k,
+            temperature,
+        ],
+        title=title,
+        description=description,
+        outputs=[output_audio],
+    )
+    interface.queue().launch(share=True)
+
+
+if __name__ == "__main__":
+    main()