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refactor: Use lazy import for CheckpointService

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- Move CheckpointService import inside run_raptor_with_checkpoint function
- Prevents module-level import that could cause initialization issues
- Improves modularity and reduces coupling

Note: task_executor.py has pre-existing NLTK dependencies from resume module
that may require NLTK data in test environments. This is unrelated to checkpoint feature.
This commit is contained in:
hsparks.codes 2025-12-03 09:51:28 +01:00
parent 811e8e0561
commit 3ff57771c6
1 changed files with 3 additions and 1 deletions
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4
rag/svr/task_executor.py
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@ -27,7 +27,6 @@ import json_repair
from api.db import PIPELINE_SPECIAL_PROGRESS_FREEZE_TASK_TYPES from api.db import PIPELINE_SPECIAL_PROGRESS_FREEZE_TASK_TYPES
from api.db.services.knowledgebase_service import KnowledgebaseService from api.db.services.knowledgebase_service import KnowledgebaseService
from api.db.services.pipeline_operation_log_service import PipelineOperationLogService from api.db.services.pipeline_operation_log_service import PipelineOperationLogService
from api.db.services.checkpoint_service import CheckpointService
from common.connection_utils import timeout from common.connection_utils import timeout
from rag.utils.base64_image import image2id from rag.utils.base64_image import image2id
from common.log_utils import init_root_logger from common.log_utils import init_root_logger
@ -650,6 +649,9 @@ async def run_raptor_with_checkpoint(task, row, kb_parser_config, chat_mdl, embd
- Failure isolation - Failure isolation
- Automatic retry - Automatic retry
""" """
# Lazy import to avoid initialization issues
from api.db.services.checkpoint_service import CheckpointService
task_id = task["id"] task_id = task["id"]
raptor_config = kb_parser_config.get("raptor", {}) raptor_config = kb_parser_config.get("raptor", {})