Upload app (1).py

app (1).py

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+from transformers import pipeline
+import requests
+import gradio as gr
+
+# Load emotion detection model
+emotion_model = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base", top_k=1)
+
+# Mappings
+mood_mapping = {
+    'joy': 'happy',
+    'neutral': 'calm',
+    'sadness': 'calm',
+    'fear': 'professional',
+    'anger': 'energetic',
+    'surprise': 'energetic',
+    'disgust': 'professional'
+}
+
+ui_styles = {
+    'happy': {
+        'font': 'Comic Neue',
+        'tip': 'Use bright colors, rounded buttons, playful layout.'
+    },
+    'calm': {
+        'font': 'Lato',
+        'tip': 'Use cool tones, white space, soft shadows.'
+    },
+    'energetic': {
+        'font': 'Bebas Neue',
+        'tip': 'Use bold colors, sharp edges, vibrant CTAs.'
+    },
+    'professional': {
+        'font': 'Roboto',
+        'tip': 'Use clean layouts, neutral tones, consistent spacing.'
+    }
+}
+
+# Main Function
+def mood_to_ui(text):
+    result = emotion_model(text)[0][0]
+    emotion = result['label'].lower()
+    mood = mood_mapping.get(emotion, 'calm')
+    style = ui_styles[mood]
+
+    # Colormind API
+    try:
+        color_data = {"model": "default"}
+        color_res = requests.post("http://colormind.io/api/", json=color_data)
+        colors = color_res.json()['result']
+    except:
+        colors = []
+
+    return {
+        "Emotion": emotion,
+        "Mood": mood,
+        "Font": style['font'],
+        "UI Tip": style['tip'],
+        "Color Palette": str(colors)
+    }
+
+# Gradio UI
+iface = gr.Interface(fn=mood_to_ui, inputs="text", outputs="json", title="Mood to UI Generator")
+iface.launch()