fix: unified_search + ai_proactive get API key from DB, fix model names for Ollama Cloud

- query_understanding.py: get API key/base_url/provider_type from ai_providers DB
- embedding.py: get API key from DB, pass db+tenant_id through call chain
- routes.py: pass db+tenant_id to llm_analyze_query and llm_aggregate_results
- search_engine.py: pass db+tenant_id to generate_embedding
- unified_search/jobs.py: pass db+tenant_id to generate_embedding
- Fix all default model names: ollama/deepseek-v4 -> ollama/deepseek-v4-flash
- Ollama Cloud has no embedding endpoint; embedding calls fail gracefully

app/plugins/builtins/ai_proactive/services.py

@@ -113,7 +113,7 @@ async def get_user_settings(
             suggestion_categories=["mail", "tasks", "contacts", "companies", "insights"],
             confidence_threshold=0.5,
             rate_limit_seconds=10,
-            model="ollama/deepseek-v4",
+            model="ollama/deepseek-v4-flash",
         )
         db.add(settings)
         await db.flush()
@@ -395,7 +395,7 @@ async def generate_suggestion(
     Returns dict with suggestion_type, title, content, confidence, actions
     or None on failure.
     """
-    model = settings.model or "ollama/deepseek-v4"
+    model = settings.model or "ollama/deepseek-v4-flash"
 
     # Get API key from DB (like ai_assistant does) or fall back to env
     api_key = None
@@ -407,7 +407,7 @@ async def generate_suggestion(
         api_key = os.environ.get('API_KEY_OLLAMA_CLOUD', '') or None
 
     # Build model string with provider prefix (like ai_assistant build_litellm_params)
-    model = settings.model or "ollama/deepseek-v4"
+    model = settings.model or "ollama/deepseek-v4-flash"
     if provider_type:
         model_parts = model.split("/", 1)
         model = f"{provider_type}/{model_parts[-1]}"