Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+from sentiment3d import Sentiment3D
+
+s3d = Sentiment3D()
+
+TITLE = "COMPASS Pathways 3D Sentiment Model"
+EXAMPLES = [
+    "This is so awesome!",
+    "You're driving me up the wall!",
+    "I'm so lonely I could cry.",
+    "I'm not feeling very sad at all.",
+    "You're slapping your father in the face, aren't you?",
+    "Yes, that's how I feel [laughing].",
+    "Yes, that's how I feel [sobbing].",
+    "Now I hear what you're sayin' 😀",
+    "Now I hear what you're sayin' 🙁",
+]
+
+
+def sentiment(text, state):
+    valence, arousal, confidence = s3d(text)
+    res = dict(text=text, valence=valence, arousal=arousal, confidence=confidence, words=len(text.split()))
+    #if clear_history:
+    #    state = []
+    if state == None:
+        state = []
+    state.append(res)
+    df = pd.DataFrame(state)
+    res_txt = [
+        f"{r['text']}: valence={r['valence']:0.3f}, arousal={r['arousal']:0.3f}, confidence=arousal={r['confidence']:0.3f}"
+        for r in state
+    ]
+    return "\n".join(res_txt), df, state
+
+
+iface = gr.Interface(
+    fn=sentiment,
+    inputs=[gr.Textbox(lines=1, placeholder="Text for 3d sentiment..."), "state"],
+    outputs=[
+        gr.Textbox(lines=5, max_lines=5, label="Results"),
+        gr.ScatterPlot(
+            x="valence",
+            y="arousal",
+            z="confidence",
+            tooltip="text",
+            size="words",
+            size_legend_position="none",
+            interactive=False,
+            x_lim=[-1.05, 1.05],
+            y_lim=[-1.05, 1.05],
+            z_lim=[-1.05, 1.05],
+        ),
+        "state",
+    ],
+    titel=TITLE,
+    examples=EXAMPLES,
+)
+iface.launch()