mirror of
https://github.com/langgenius/dify.git
synced 2026-04-20 02:37:20 +08:00
fix: fix session problem.
This commit is contained in:
FFXN
@ -147,6 +147,8 @@ class SummaryIndexService:
|
||||
|
||||
# Always regenerate hash (in case summary content changed)
|
||||
summary_content = summary_record.summary_content
|
||||
if not summary_content or not summary_content.strip():
|
||||
raise ValueError(f"Summary content is empty for segment {segment.id}, cannot vectorize")
|
||||
summary_hash = helper.generate_text_hash(summary_content)
|
||||
|
||||
# Delete old vector only if we're reusing the same index_node_id (to overwrite)
|
||||
@ -219,17 +221,26 @@ class SummaryIndexService:
|
||||
session.query(DocumentSegmentSummary).filter_by(id=summary_record_id).first()
|
||||
)
|
||||
if summary_record_in_session:
|
||||
# Update all fields including summary_content (in case it was updated in outer session)
|
||||
# Update all fields including summary_content
|
||||
# Always use the summary_content from the parameter (which is the latest from outer session)
|
||||
# rather than relying on what's in the database, in case outer session hasn't committed yet
|
||||
summary_record_in_session.summary_index_node_id = summary_index_node_id
|
||||
summary_record_in_session.summary_index_node_hash = summary_hash
|
||||
summary_record_in_session.tokens = embedding_tokens # Save embedding tokens
|
||||
summary_record_in_session.status = "completed"
|
||||
# Ensure summary_content is preserved (use the latest from summary_record parameter)
|
||||
# This is critical: use the parameter value, not the database value
|
||||
summary_record_in_session.summary_content = summary_content
|
||||
# Explicitly update updated_at to ensure it's refreshed even if other fields haven't changed
|
||||
summary_record_in_session.updated_at = datetime.now(UTC).replace(tzinfo=None)
|
||||
session.add(summary_record_in_session)
|
||||
session.commit()
|
||||
logger.info(
|
||||
"Successfully vectorized summary for segment %s, index_node_id=%s, tokens=%s",
|
||||
segment.id,
|
||||
summary_index_node_id,
|
||||
embedding_tokens,
|
||||
)
|
||||
# Update the original object for consistency
|
||||
summary_record.summary_index_node_id = summary_index_node_id
|
||||
summary_record.summary_index_node_hash = summary_hash
|
||||
@ -237,6 +248,13 @@ class SummaryIndexService:
|
||||
summary_record.status = "completed"
|
||||
summary_record.summary_content = summary_content
|
||||
summary_record.updated_at = summary_record_in_session.updated_at
|
||||
else:
|
||||
logger.error(
|
||||
"Summary record not found in database for segment %s (id=%s) after vectorization",
|
||||
segment.id,
|
||||
summary_record_id,
|
||||
)
|
||||
raise ValueError(f"Summary record not found for segment {segment.id} after vectorization")
|
||||
# Success, exit function
|
||||
return
|
||||
|
||||
@ -450,14 +468,23 @@ class SummaryIndexService:
|
||||
# Pass the session-managed record to vectorize_summary
|
||||
# vectorize_summary will update status to "completed" and tokens in its own session
|
||||
# vectorize_summary will also ensure summary_content is preserved
|
||||
SummaryIndexService.vectorize_summary(summary_record_in_session, segment, dataset)
|
||||
|
||||
# Refresh the object from database to get the updated status and tokens from vectorize_summary
|
||||
session.refresh(summary_record_in_session)
|
||||
# Commit the session (summary_record_in_session should have status="completed" and tokens from refresh)
|
||||
session.commit()
|
||||
logger.info("Successfully generated and vectorized summary for segment %s", segment.id)
|
||||
return summary_record_in_session
|
||||
try:
|
||||
SummaryIndexService.vectorize_summary(summary_record_in_session, segment, dataset)
|
||||
# Refresh the object from database to get the updated status and tokens from vectorize_summary
|
||||
session.refresh(summary_record_in_session)
|
||||
# Commit the session
|
||||
# (summary_record_in_session should have status="completed" and tokens from refresh)
|
||||
session.commit()
|
||||
logger.info("Successfully generated and vectorized summary for segment %s", segment.id)
|
||||
return summary_record_in_session
|
||||
except Exception as vectorize_error:
|
||||
# If vectorization fails, update status to error in current session
|
||||
logger.exception("Failed to vectorize summary for segment %s", segment.id)
|
||||
summary_record_in_session.status = "error"
|
||||
summary_record_in_session.error = f"Vectorization failed: {str(vectorize_error)}"
|
||||
session.add(summary_record_in_session)
|
||||
session.commit()
|
||||
raise
|
||||
|
||||
except Exception as e:
|
||||
logger.exception("Failed to generate summary for segment %s", segment.id)
|
||||
@ -859,6 +886,8 @@ class SummaryIndexService:
|
||||
|
||||
# Re-vectorize summary (this will update status to "completed" and tokens in its own session)
|
||||
# vectorize_summary will also ensure summary_content is preserved
|
||||
# Note: vectorize_summary may take time due to embedding API calls, but we need to complete it
|
||||
# to ensure the summary is properly indexed
|
||||
try:
|
||||
SummaryIndexService.vectorize_summary(summary_record, segment, dataset)
|
||||
# Refresh the object from database to get the updated status and tokens from vectorize_summary
|
||||
@ -869,11 +898,15 @@ class SummaryIndexService:
|
||||
return summary_record
|
||||
except Exception as e:
|
||||
# If vectorization fails, update status to error in current session
|
||||
# Don't raise the exception - just log it and return the record with error status
|
||||
# This allows the segment update to complete even if vectorization fails
|
||||
summary_record.status = "error"
|
||||
summary_record.error = f"Vectorization failed: {str(e)}"
|
||||
session.commit()
|
||||
logger.exception("Failed to vectorize summary for segment %s", segment.id)
|
||||
raise
|
||||
# Return the record with error status instead of raising
|
||||
# The caller can check the status if needed
|
||||
return summary_record
|
||||
else:
|
||||
# Create new summary record if doesn't exist
|
||||
summary_record = SummaryIndexService.create_summary_record(
|
||||
@ -901,8 +934,13 @@ class SummaryIndexService:
|
||||
error_record.status = "error"
|
||||
error_record.error = f"Vectorization failed: {str(e)}"
|
||||
error_session.commit()
|
||||
# Update the returned record
|
||||
summary_record.status = "error"
|
||||
summary_record.error = error_record.error
|
||||
logger.exception("Failed to vectorize summary for segment %s", segment.id)
|
||||
raise
|
||||
# Return the record with error status instead of raising
|
||||
# This allows the segment update to complete even if vectorization fails
|
||||
return summary_record
|
||||
|
||||
except Exception as e:
|
||||
logger.exception("Failed to update summary for segment %s", segment.id)
|
||||
|
||||
@ -48,6 +48,16 @@ def generate_summary_index_task(dataset_id: str, document_id: str, segment_ids:
|
||||
logger.error(click.style(f"Document not found: {document_id}", fg="red"))
|
||||
return
|
||||
|
||||
# Check if document needs summary
|
||||
if not document.need_summary:
|
||||
logger.info(
|
||||
click.style(
|
||||
f"Skipping summary generation for document {document_id}: need_summary is False",
|
||||
fg="cyan",
|
||||
)
|
||||
)
|
||||
return
|
||||
|
||||
# Only generate summary index for high_quality indexing technique
|
||||
if dataset.indexing_technique != "high_quality":
|
||||
logger.info(
|
||||
|
||||
Reference in New Issue
Block a user