Update app.py

app.py

@@ -1,42 +1,40 @@
 # app.py
-import json
-import gradio as gr
+import json, gradio as gr
 from transformers import pipeline
 
-# 1) Load base labels from JSON
-with open("labels.json", "r") as f:
-    base_labels = json.load(f)
+# 1) Load taxonomies
+with open("coarse_labels.json") as f:
+    coarse_labels = json.load(f)                                 # :contentReference[oaicite:4]{index=4}
+with open("fine_labels.json") as f:
+    fine_map = json.load(f)                                      # :contentReference[oaicite:5]{index=5}
 
-# 2) Prepare default textbox value
-default_label_str = ", ".join(base_labels)
+# 2) Init classifier
+classifier = pipeline("zero-shot-classification",
+                      model="facebook/bart-large-mnli")
 
-# 3) Initialize zero-shot classifier
-classifier = pipeline(
-    task="zero-shot-classification",
-    model="facebook/bart-large-mnli"
-)
-
-# 4) Interface function that merges runtime labels
-def tag_question(question: str, labels_str: str):
-    # Split & clean the user-supplied string
-    labels = [lbl.strip() for lbl in labels_str.split(",") if lbl.strip()]
-    # Zero-shot classify
-    out = classifier(question, candidate_labels=labels)
-    # Return top-3 labels with scores
-    return {lbl: round(score,3) for lbl, score in zip(out["labels"], out["scores"])}
+# 3) Tagging fn
+def hierarchical_tag(question):
+    # Stage 1: pick coarse subject
+    coarse_out = classifier(question, candidate_labels=coarse_labels)
+    chosen = coarse_out["labels"][0]
+    # Stage 2: fine-grained tags within that subject
+    fine_labels = fine_map.get(chosen, [])
+    fine_out = classifier(question, candidate_labels=fine_labels)
+    # Return both
+    return {
+      "Subject": chosen,
+      **{lbl: round(score,3) 
+         for lbl, score in zip(fine_out["labels"], fine_out["scores"])}
+    }
 
-# 5) Build the Gradio UI
+# 4) Build UI
 iface = gr.Interface(
-    fn=tag_question,
-    inputs=[
-        gr.Textbox(lines=3, label="Question"),
-        gr.Textbox(lines=2, label="Candidate Labels (comma-separated)",
-                   value=default_label_str)
-    ],
-    outputs=gr.Label(num_top_classes=3),
-    title="Hybrid Zero-Shot Question Tagger",
-    description="Loaded labels from `labels.json`, editable at runtime."
+    fn=hierarchical_tag,
+    inputs=gr.Textbox(lines=3, label="Enter your question"),
+    outputs=gr.JSON(label="Hierarchical Tags"),
+    title="Two-Stage Zero-Shot Question Tagger",
+    description="Stage 1: classify subject; Stage 2: classify topic within subject."
 )
 
-if __name__ == "__main__":
+if __name__=="__main__":
     iface.launch()