AI Vision: multi-provider config, model testing, per-client AI preferences

Backend:
- Add ai_provider + ai_model columns to APIClient model
- New admin_ai router: GET /admin/api/ai/status + POST /admin/api/ai/test
- Update ai_vision.py: provider_override + model_override support
- Update pipeline: load client AI prefs for image processing
- ClientUpdate/ClientResponse schemas include ai_provider/ai_model

Frontend:
- New AIConfigSection component: provider list, model dropdowns,
  test button with live results (no page refresh needed)
- AI types (ai.types.ts) + API (api/ai.ts)
- APIClient types extended with ai_provider/ai_model

app/services/pipeline.py

@@ -181,9 +181,25 @@ async def process_image_pipeline(
     try:
         logger.info("pipeline.step.start", extra={"image_id": image_id, "step": "ai", "step_num": "3/3"})
         t0 = time.time()
+
+        # Charger les préférences AI du client
+        provider_override = None
+        model_override = None
+        if image.client_id:
+            from app.models.client import APIClient
+            client_result = await db.execute(
+                select(APIClient).where(APIClient.id == image.client_id)
+            )
+            owner = client_result.scalar_one_or_none()
+            if owner:
+                provider_override = owner.ai_provider
+                model_override = owner.ai_model
+
         ai = await analyze_image(
             file_path=file_path,
             ocr_hint=image.ocr_text,
+            provider_override=provider_override,
+            model_override=model_override,
         )
 
         image.ai_description   = ai.get("description")