fix: return full record in get_ingestion_log (#16120)

### What problem does this PR solve?

The `get_ingestion_log` endpoint (both Python
`dataset_api_service.get_ingestion_log` and Go
`DatasetService.GetIngestionLog`) was returning only the
**dataset-level** field set, which omits critical fields such as `dsl`,
`document_id`, `parser_id`, `document_name`, `pipeline_id`, etc.

This caused the front-end **dataflow-result page** to be unable to
render the pipeline timeline and chunks when viewing a single ingestion
log, regardless of whether the log was a dataset-level operation
(graph/raptor/mindmap) or a per-file parse.

### Background

`PipelineOperationLogService` provides two field sets:

| Method | Fields |
|---|---|
| `get_dataset_logs_fields` | Minimal set (progress, status, timestamps,
etc.) |
| `get_file_logs_fields` | Superset — includes `document_id`, `dsl`,
`parser_id`, `document_name`, `pipeline_id`, … |

When listing logs, the API correctly distinguishes dataset-level vs
file-level logs and uses the appropriate converter. However, when
**fetching a single log by ID**, both the Python and Go implementations
were hardcoded to the dataset-level set, dropping the extra fields that
the front-end needs.

api/apps/services/dataset_api_service.py

@@ -781,7 +781,11 @@ def get_ingestion_log(dataset_id: str, tenant_id: str, log_id: str):
 
     from api.db.services.pipeline_operation_log_service import PipelineOperationLogService
 
-    fields = PipelineOperationLogService.get_dataset_logs_fields()
+    # Return the full record (including `dsl`) so the front-end dataflow-result
+    # page can render the pipeline timeline and chunks. The file-level field set
+    # is a superset of the dataset-level fields, so it is valid for both
+    # dataset-level (graph/raptor/mindmap) and per-file logs.
+    fields = PipelineOperationLogService.get_file_logs_fields()
     log = PipelineOperationLogService.model.select(*fields).where((PipelineOperationLogService.model.id == log_id) & (PipelineOperationLogService.model.kb_id == dataset_id)).first()
     if not log:
         return False, "Log not found"