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### 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.