Create app.py

app.py

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+import gradio as gr
+from sentence_transformers import SentenceTransformer, util
+import torch
+import json
+
+model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
+
+# In-memory label store (can be replaced by DB)
+LABEL_STORE = {
+    "chat": ["say hello", "casual talk", "how are you"],
+    "image_generation": ["generate an image", "draw a picture", "create artwork"],
+    "action": ["set a timer", "create a reminder"]
+}
+
+def classify(text, label_json):
+    if not text.strip():
+        return {"error": "Empty input"}
+
+    try:
+        labels = json.loads(label_json)
+    except Exception as e:
+        return {"error": "Invalid label JSON"}
+
+    label_embeddings = {}
+    for label, examples in labels.items():
+        if not examples:
+            continue
+        emb = model.encode(examples, convert_to_tensor=True)
+        label_embeddings[label] = emb.mean(dim=0)
+
+    if not label_embeddings:
+        return {"error": "No valid labels"}
+
+    text_emb = model.encode(text, convert_to_tensor=True)
+
+    scores = {}
+    for label, emb in label_embeddings.items():
+        scores[label] = float(util.cos_sim(text_emb, emb))
+
+    top_intent = max(scores, key=scores.get)
+
+    return {
+        "text": text,
+        "top_intent": top_intent,
+        "scores": scores
+    }
+
+with gr.Blocks() as demo:
+    gr.Markdown("## ⚡ Semantic Intent Router Builder")
+
+    user_input = gr.Textbox(label="User Input")
+
+    label_editor = gr.JSON(
+        value=LABEL_STORE,
+        label="Labels & Examples (edit freely, add/remove)"
+    )
+
+    output = gr.JSON(label="Routing Result")
+
+    classify_btn = gr.Button("Classify")
+
+    classify_btn.click(
+        classify,
+        inputs=[user_input, label_editor],
+        outputs=output
+    )
+
+demo.launch(
+    share=True,
+    show_api=True,
+    enable_queue=False
+)