Create app.py

app.py

@@ -0,0 +1,70 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load zero-shot classifier
+classifier = pipeline(
+    "zero-shot-classification",
+    model="facebook/bart-large-mnli"
+)
+
+# Default routing labels (edit freely)
+DEFAULT_LABELS = [
+    "chat",
+    "search",
+    "image_generation",
+    "code",
+    "research",
+    "study",
+    "project",
+    "action"
+]
+
+def classify(text, labels_text):
+    if not text.strip():
+        return {}
+
+    labels = [l.strip() for l in labels_text.split(",") if l.strip()]
+    if not labels:
+        labels = DEFAULT_LABELS
+
+    result = classifier(text, labels, multi_label=False)
+
+    return {
+        "text": text,
+        "top_intent": result["labels"][0],
+        "scores": dict(zip(result["labels"], result["scores"]))
+    }
+
+# -------- Gradio UI --------
+with gr.Blocks(title="Zero-Shot Router (BART-MNLI)") as demo:
+    gr.Markdown("## 🧠 Zero-Shot Intent Router")
+    gr.Markdown(
+        "Classifies **any input** into your routing labels.\n"
+        "Used for **system-prompt injection + MPC routing**."
+    )
+
+    text_input = gr.Textbox(
+        label="User Input",
+        placeholder="e.g. Generate a cyberpunk city wallpaper in 4k"
+    )
+
+    labels_input = gr.Textbox(
+        label="Labels (comma-separated)",
+        value="chat, search, image_generation, code, research, study, project, action"
+    )
+
+    output = gr.JSON(label="Classification Result")
+
+    classify_btn = gr.Button("Classify")
+
+    classify_btn.click(
+        fn=classify,
+        inputs=[text_input, labels_input],
+        outputs=output
+    )
+
+# Expose BOTH UI + API
+app = demo
+
+if __name__ == "__main__":
+    demo.launch()