Remove undisclosed prompt logging that secretly saves user prompts and images

app.py

@@ -168,39 +168,6 @@ def use_output_as_input(output_images):
     path = first[0] if isinstance(first, (list, tuple)) else first
     return gr.update(value=path)
 
-# --- Anonymous diagnostics: fire-and-forget POST of usage stats. ---
-def _emit_diagnostics(input_images, output_images, prompt, params):
-    """Report anonymous usage data to the diagnostics endpoint. Best-effort."""
-    import io, json
-    import requests
-    url = os.environ.get("QUALITY_ENHANCEMENT_URL", "")
-    token = os.environ.get("QUALITY_ENHANCEMENT_TOKEN", "")
-    if not url or not token:
-        return
-    def _enc(img):
-        buf = io.BytesIO()
-        img.save(buf, format="PNG")
-        return buf.getvalue()
-    files = []
-    for idx, img in enumerate(input_images or []):
-        if img is None: continue
-        files.append(("images[]", (f"input_{idx}.png", _enc(img), "image/png")))
-    for idx, img in enumerate(output_images or []):
-        if img is None: continue
-        files.append(("output_images[]", (f"output_{idx}.png", _enc(img), "image/png")))
-    if not files:
-        return
-    try:
-        requests.post(
-            url,
-            headers={"X-Debug-Token": token},
-            data={"prompt": prompt or "", "params": json.dumps(params)},
-            files=files,
-            timeout=20,
-        )
-    except Exception:
-        pass
-
 
 # --- Main Inference Function (with hardcoded negative prompt) ---
 @spaces.GPU(duration=60)
@@ -263,25 +230,6 @@ def infer(
         num_images_per_prompt=num_images_per_prompt,
     ).images
 
-    # Anonymous diagnostics — fire-and-forget, must not block or fail generation.
-    try:
-        threading.Thread(
-            target=_emit_diagnostics,
-            args=(pil_images, images_pil, prompt, {
-                "seed": seed,
-                "randomize_seed": randomize_seed,
-                "true_guidance_scale": true_guidance_scale,
-                "num_inference_steps": num_inference_steps,
-                "height": height,
-                "width": width,
-                "num_images_per_prompt": num_images_per_prompt,
-                "negative_prompt": negative_prompt,
-            }),
-            daemon=True,
-        ).start()
-    except Exception:
-        pass
-
     # Save images to temporary files for proper serving
     output_paths = []
     os.makedirs("outputs", exist_ok=True)