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remove unwanted comments
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1 changed files with 1 additions and 10 deletions
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@ -220,7 +220,6 @@ class OpenAIVectorStoreMixin(ABC):
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current_time = int(time.time())
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cleanup_interval = 24 * 60 * 60 # 1 day in seconds
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# Check if enough time has passed since last cleanup
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if current_time - self._last_cleanup_time >= cleanup_interval:
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logger.info("Running throttled cleanup of expired file batches")
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await self._cleanup_expired_file_batches()
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@ -238,9 +237,7 @@ class OpenAIVectorStoreMixin(ABC):
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"""Load existing OpenAI vector stores and file batches into the in-memory cache."""
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self.openai_vector_stores = await self._load_openai_vector_stores()
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self.openai_file_batches = await self._load_openai_vector_store_file_batches()
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# Resume any incomplete file batches
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await self._resume_incomplete_batches()
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# Initialize last cleanup time
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self._last_cleanup_time = 0
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@abstractmethod
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@ -947,7 +944,7 @@ class OpenAIVectorStoreMixin(ABC):
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# Start background processing of files
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asyncio.create_task(self._process_file_batch_async(batch_id, batch_info))
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# Run cleanup if needed (throttled to once every 7 days)
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# Run cleanup if needed (throttled to once every 1 day)
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asyncio.create_task(self._cleanup_expired_file_batches_if_needed())
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return batch_object
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@ -994,7 +991,6 @@ class OpenAIVectorStoreMixin(ABC):
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else:
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batch_info["status"] = "completed" # Partial success counts as completed
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# Save final batch status to persistent storage (keep completed batches like vector stores)
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await self._save_openai_vector_store_file_batch(batch_id, batch_info)
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logger.info(f"File batch {batch_id} processing completed with status: {batch_info['status']}")
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@ -1064,7 +1060,6 @@ class OpenAIVectorStoreMixin(ABC):
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) -> VectorStoreFileBatchObject:
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"""Retrieve a vector store file batch."""
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batch_info = self._get_and_validate_batch(batch_id, vector_store_id)
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# Convert dict back to Pydantic model for API response
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return VectorStoreFileBatchObject(**batch_info)
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async def openai_list_files_in_vector_store_file_batch(
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@ -1120,17 +1115,13 @@ class OpenAIVectorStoreMixin(ABC):
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"""Cancel a vector store file batch."""
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batch_info = self._get_and_validate_batch(batch_id, vector_store_id)
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# Only allow cancellation if batch is in progress
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if batch_info["status"] not in ["in_progress"]:
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raise ValueError(f"Cannot cancel batch {batch_id} with status {batch_info['status']}")
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# Update batch with cancelled status
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batch_info["status"] = "cancelled"
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# Save cancelled batch status to persistent storage (keep cancelled batches like vector stores)
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await self._save_openai_vector_store_file_batch(batch_id, batch_info)
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# Create updated batch object for API response
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updated_batch = VectorStoreFileBatchObject(**batch_info)
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return updated_batch
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