Create app.py

app.py

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+"""
+app.py
+A simple Gradio front-end to demo the multi-model safety analyzer.
+Push to a Hugging Face Space (runtime: python) and ensure required models are accessible.
+"""
+
+import gradio as gr
+import json
+from classifier import analyze_text, MODEL_HANDLES, load_models
+
+# Try to ensure models are loaded (load_models is called at import but re-call gracefully)
+try:
+    load_models()
+except Exception:
+    pass
+
+def pretty_result(text: str):
+    res = analyze_text(text or "")
+    # build human-readable output
+    out_lines = []
+    out_lines.append("Normalized:\n" + (res.get("normalized") or ""))
+    out_lines.append(f"\nEntropy: {res.get('entropy', 0.0):.2f}\n")
+    if res.get("heuristic_flags"):
+        out_lines.append("Heuristic flags:")
+        for h in res["heuristic_flags"]:
+            out_lines.append(f"- {h.get('type')}: {h.get('explain')}")
+            if "matches" in h:
+                out_lines.append(f"  matches: {h['matches']}")
+    if res.get("model_flags"):
+        out_lines.append("\nModel flags:")
+        for m in res["model_flags"]:
+            model = m.get("model", "unknown")
+            label = m.get("label", "")
+            score = m.get("score", None)
+            out_lines.append(f"- {m.get('type')} | {model} | {label} | score={score}")
+            out_lines.append(f"  explain: {m.get('explain')}")
+    if not res.get("heuristic_flags") and not res.get("model_flags"):
+        out_lines.append("\nNo flags detected (no guarantees).")
+    out_lines.append("\nNotes: " + res.get("notes", ""))
+    return "\n".join(out_lines), json.dumps(res, indent=2, ensure_ascii=False)
+
+demo_description = """
+# Text Safety Analyzer (multi-model)
+Paste text or a prompt below. The system runs heuristics + multiple models (toxicity/harm + URL detection) and returns
+explainable flags. This is a detection tool—human review recommended for any enforcement action.
+"""
+
+with gr.Blocks() as demo:
+    gr.Markdown(demo_description)
+    txt = gr.Textbox(lines=8, placeholder="Paste text, prompt, or suspicious content here...")
+    analyze_btn = gr.Button("Analyze")
+    out_text = gr.Textbox(lines=14, label="Result (human readable)")
+    out_json = gr.Textbox(lines=20, label="Raw JSON result")
+    analyze_btn.click(fn=pretty_result, inputs=txt, outputs=[out_text, out_json])
+
+if __name__ == "__main__":
+    demo.launch()