feat(app): create app gui module

src/emotion_analysis/app/__init__.py

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+from .gui import build_gui as build_gui
+from .on_callback import on_classify as on_classify

src/emotion_analysis/app/gui.py

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+from typing import Callable
+
+from gradio import Audio, Blocks, Button, Column, Slider
+
+from ..services import Classifier
+
+
+def build_gui(model: Classifier, on_btn_classify: Callable):
+    with Blocks() as demo:
+        with Column():
+            audio_input = Audio(
+                label="Audio input",
+                sources=["microphone", "upload"],
+                type="filepath",
+            )
+            classify_btn = Button(value="Classify")
+
+        with Column():
+            emotions = [
+                Slider(
+                    label=emotion.capitalize(),
+                    minimum=0,
+                    maximum=1,
+                    precision=0,
+                    interactive=False,
+                )
+                for emotion in model.label2id.keys()
+            ]
+
+        classify_btn.click(
+            fn=on_btn_classify(model), inputs=audio_input, outputs=emotions
+        )
+
+        return demo

src/emotion_analysis/app/on_callback.py

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+from pathlib import Path
+
+from ..services import Classifier
+
+
+def on_classify(model: Classifier):
+    def fn(audio: Path | str):
+        probs: dict[int, float] = model.predict(audio, return_probs=True)  # type: ignore
+        print(probs)
+        return list(probs.values())
+
+    return fn