Create app.py

app.py

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+# 1. Import necessary libraries
+import gradio as gr
+from transformers import pipeline
+
+# 2. Load the pre-trained AI model
+# We are using a model fine-tuned to recognize multiple emotions.
+# This is more nuanced than a simple positive/negative classifier.
+emotion_classifier = pipeline(
+    "text-classification",
+    model="SamLowe/roberta-base-go_emotions",
+    top_k=None # This ensures we see the scores for all emotions
+)
+
+# 3. Define the function that will process the input and return the output
+def predict_emotions(text_input):
+    """
+    This function takes text, passes it to the AI model,
+    and then formats the results for display.
+    """
+    # Get the raw predictions from the model
+    predictions = emotion_classifier(text_input)
+
+    # The model returns a list of lists. We only need the first element.
+    emotions = predictions[0]
+
+    # We will focus on key indicators for stress and depression
+    key_indicators = ['sadness', 'fear', 'anger', 'disappointment', 'nervousness']
+
+    # Create a dictionary to hold the scores for our key indicators
+    formatted_results = {}
+    for emotion in emotions:
+        if emotion['label'] in key_indicators:
+            formatted_results[emotion['label']] = round(emotion['score'], 3)
+
+    return formatted_results
+
+# 4. Create the Gradio web interface
+app_interface = gr.Interface(
+    fn=predict_emotions,
+    inputs=gr.Textbox(
+        lines=8,
+        label="Social Media Post",
+        placeholder="Type or paste a social media post here to analyze its emotional content..."
+    ),
+    outputs=gr.Label(
+        num_top_classes=5,
+        label="Key Emotional Indicators"
+    ),
+    title="Student Wellness Analyzer 🧠",
+    description="""
+    **Disclaimer:** This is an AI demo and **not a medical diagnostic tool**.
+    This model analyzes text for emotional indicators often associated with stress and depression.
+    If you are struggling, please seek help from a qualified professional.
+    """,
+    examples=[
+        ["I'm so behind on all my assignments and the exams are next week. I don't know how I'm going to manage all this pressure."],
+        ["Feeling completely isolated and lonely on campus. It seems like everyone else has their friend group figured out."],
+        ["I failed a midterm I studied really hard for. I just feel like a total disappointment and can't get motivated anymore."]
+    ]
+)
+
+# 5. Launch the app
+app_interface.launch()