Upload Gradio app for mental health analysis

app.py

@@ -16,15 +16,42 @@
 #     title="Mindscape AI Therapist"
 # ).launch()
 
+# import gradio as gr
+# from transformers import pipeline
+
+# classifier = pipeline("text-classification", model="coldnasser/depression-anxiety-mindscape")
+
+# def predict(text):
+#     try:
+#         return classifier(text)
+#     except Exception as e:
+#         return f"Error: {str(e)}"
+
+# gr.Interface(fn=predict, inputs="text", outputs="text", title="Mindscape").launch()
 import gradio as gr
 from transformers import pipeline
 
+# Define the mapping from label to human-readable status
+label_mapping = {
+    "LABEL_0": "Normal",
+    "LABEL_1": "Depression",
+    "LABEL_2": "Anxiety"
+}
+
 classifier = pipeline("text-classification", model="coldnasser/depression-anxiety-mindscape")
 
 def predict(text):
     try:
-        return classifier(text)
+        result = classifier(text)[0]  # Get the first result
+        label = result['label']
+        score = result['score']
+        
+        # Map the label to a human-readable value
+        human_label = label_mapping.get(label, label)
+        
+        return {"label": human_label, "score": score}
     except Exception as e:
         return f"Error: {str(e)}"
 
-gr.Interface(fn=predict, inputs="text", outputs="text", title="Mindscape").launch()
+gr.Interface(fn=predict, inputs="text", outputs="json", title="Mindscape").launch()
+