refactor: streamline trigger event node metadata handling and update async workflow service for JSON serialization

- Removed unnecessary input data from the TriggerEventNode's metadata.
- Updated AsyncWorkflowService to use model_dump_json() for trigger metadata serialization.
- Added a comment in WorkflowAppService to address the large size of the workflow_app_log table and the use of an additional details field.

api/services/async_workflow_service.py

@@ -111,6 +111,7 @@ class AsyncWorkflowService:
             app_id=trigger_data.app_id,
             workflow_id=workflow.id,
             root_node_id=trigger_data.root_node_id,
+            trigger_metadata=trigger_data.trigger_metadata.model_dump_json(),
             trigger_type=trigger_data.trigger_type,
             trigger_data=trigger_data.model_dump_json(),
             inputs=json.dumps(dict(trigger_data.inputs)),

api/services/workflow/entities.py

@@ -19,6 +19,12 @@ class AsyncTriggerStatus(StrEnum):
     TIMEOUT = "timeout"
 
 
+class TriggerMetadata(BaseModel):
+    """Trigger metadata"""
+
+    pass
+
+
 class TriggerData(BaseModel):
     """Base trigger data model for async workflow execution"""
 
@@ -30,6 +36,7 @@ class TriggerData(BaseModel):
     files: Sequence[Mapping[str, Any]] = Field(default_factory=list)
     trigger_type: AppTriggerType
     trigger_from: WorkflowRunTriggeredFrom
+    trigger_metadata: TriggerMetadata = Field(default_factory=TriggerMetadata)
 
     model_config = ConfigDict(use_enum_values=True)
 
@@ -48,6 +55,17 @@ class ScheduleTriggerData(TriggerData):
     trigger_from: WorkflowRunTriggeredFrom = WorkflowRunTriggeredFrom.SCHEDULE
 
 
+class PluginTriggerMetadata(TriggerMetadata):
+    """Plugin trigger metadata"""
+
+    plugin_id: str
+    endpoint_id: str
+    plugin_unique_identifier: str
+    provider_id: str
+    icon_url: str
+    icon_dark_url: str
+
+
 class PluginTriggerData(TriggerData):
     """Plugin webhook trigger data"""
 

api/services/workflow_app_service.py

@@ -1,3 +1,4 @@
+import json
 import uuid
 from datetime import datetime
 
@@ -7,6 +8,35 @@ from sqlalchemy.orm import Session
 from core.workflow.enums import WorkflowExecutionStatus
 from models import Account, App, EndUser, WorkflowAppLog, WorkflowRun
 from models.enums import CreatorUserRole
+from models.trigger import WorkflowTriggerLog
+
+
+# Since the workflow_app_log table has exceeded 100 million records, we use an additional details field to extend it
+class LogView:
+    """Lightweight wrapper for WorkflowAppLog with computed details.
+
+    - Exposes `details_` for marshalling to `details` in API response
+    - Proxies all other attributes to the underlying `WorkflowAppLog`
+    """
+
+    def __init__(self, log: WorkflowAppLog, details: dict | None):
+        self.log = log
+        self.details_ = details
+
+    def __getattr__(self, name):
+        return getattr(self.log, name)
+
+
+# Helpers
+def _safe_json_loads(val):
+    if not val:
+        return None
+    if isinstance(val, str):
+        try:
+            return json.loads(val)
+        except Exception:
+            return None
+    return val
 
 
 class WorkflowAppService:
@@ -21,6 +51,7 @@ class WorkflowAppService:
         created_at_after: datetime | None = None,
         page: int = 1,
         limit: int = 20,
+        detail: bool = False,
         created_by_end_user_session_id: str | None = None,
         created_by_account: str | None = None,
     ):
@@ -34,6 +65,7 @@ class WorkflowAppService:
         :param created_at_after: filter logs created after this timestamp
         :param page: page number
         :param limit: items per page
+        :param detail: whether to return detailed logs
         :param created_by_end_user_session_id: filter by end user session id
         :param created_by_account: filter by account email
         :return: Pagination object
@@ -43,8 +75,24 @@ class WorkflowAppService:
             WorkflowAppLog.tenant_id == app_model.tenant_id, WorkflowAppLog.app_id == app_model.id
         )
 
+        if detail:
+            # Correlated scalar subquery: fetch latest trigger_metadata per workflow_run_id
+            meta_expr = (
+                select(WorkflowTriggerLog.trigger_metadata)
+                .where(
+                    WorkflowTriggerLog.workflow_run_id == WorkflowAppLog.workflow_run_id,
+                    WorkflowTriggerLog.app_id == app_model.id,
+                    WorkflowTriggerLog.tenant_id == app_model.tenant_id,
+                )
+                .order_by(WorkflowTriggerLog.created_at.desc())
+                .limit(1)
+                .scalar_subquery()
+            )
+            stmt = stmt.add_columns(meta_expr)
+
         if keyword or status:
             stmt = stmt.join(WorkflowRun, WorkflowRun.id == WorkflowAppLog.workflow_run_id)
+            # Join to workflow run for filtering when needed.
 
         if keyword:
             keyword_like_val = f"%{keyword[:30].encode('unicode_escape').decode('utf-8')}%".replace(r"\u", r"\\u")
@@ -108,9 +156,14 @@ class WorkflowAppService:
         # Apply pagination limits
         offset_stmt = stmt.offset((page - 1) * limit).limit(limit)
 
-        # Execute query and get items
-        items = list(session.scalars(offset_stmt).all())
+        # wrapper moved to module scope as `LogView`
 
+        # Execute query and get items
+        if detail:
+            rows = session.execute(offset_stmt).all()
+            items = [LogView(log, {"trigger_metadata": _safe_json_loads(meta_val)}) for log, meta_val in rows]
+        else:
+            items = [LogView(log, None) for log in session.scalars(offset_stmt).all()]
         return {
             "page": page,
             "limit": limit,