youngkingdom/dify
1
0
Fork 0
mirror of https://github.com/langgenius/dify.git synced 2026-05-05 01:48:04 +08:00
Code Issues Packages Projects Releases Wiki Activity

fix: fix summary index bug.

Browse Source
This commit is contained in:
FFXN
2026-01-23 19:03:06 +08:00
parent 9841b8c5b5
commit b953e4fe9b
2 changed files with 22 additions and 21 deletions
Download Patch File Download Diff File Expand all files Collapse all files

34
api/services/dataset_service.py
View File

@ -3257,14 +3257,10 @@ class SegmentService:
VectorService.update_segment_vector(args.keywords, segment, dataset)
# update summary index if summary is provided and has changed
if args.summary is not None:
# Check if summary index is enabled
has_summary_index = (
dataset.indexing_technique == "high_quality"
and dataset.summary_index_setting
and dataset.summary_index_setting.get("enable") is True
)
if has_summary_index:
# When user manually provides summary, allow saving even if summary_index_setting doesn't exist
# summary_index_setting is only needed for LLM generation, not for manual summary vectorization
# Vectorization uses dataset.embedding_model, which doesn't require summary_index_setting
if dataset.indexing_technique == "high_quality":
# Query existing summary from database
from models.dataset import DocumentSegmentSummary
@ -3363,12 +3359,7 @@ class SegmentService:
# update segment vector index
VectorService.update_segment_vector(args.keywords, segment, dataset)
# Handle summary index when content changed
has_summary_index = (
dataset.indexing_technique == "high_quality"
and dataset.summary_index_setting
and dataset.summary_index_setting.get("enable") is True
)
if has_summary_index:
if dataset.indexing_technique == "high_quality":
from models.dataset import DocumentSegmentSummary
existing_summary = (
@ -3382,7 +3373,12 @@ class SegmentService:
if args.summary is None:
# User didn't provide summary, auto-regenerate if segment previously had summary
if existing_summary:
# Auto-regeneration only happens if summary_index_setting exists and enable is True
if (
existing_summary
and dataset.summary_index_setting
and dataset.summary_index_setting.get("enable") is True
):
# Segment previously had summary, regenerate it with new content
from services.summary_index_service import SummaryIndexService
@ -3398,6 +3394,7 @@ class SegmentService:
# Don't fail the entire update if summary regeneration fails
else:
# User provided summary, check if it has changed
# Manual summary updates are allowed even if summary_index_setting doesn't exist
existing_summary_content = existing_summary.summary_content if existing_summary else None
if existing_summary_content != args.summary:
# Summary has changed, use user-provided summary
@ -3413,7 +3410,12 @@ class SegmentService:
# Don't fail the entire update if summary update fails
else:
# Summary hasn't changed, regenerate based on new content
if existing_summary:
# Auto-regeneration only happens if summary_index_setting exists and enable is True
if (
existing_summary
and dataset.summary_index_setting
and dataset.summary_index_setting.get("enable") is True
):
from services.summary_index_service import SummaryIndexService
try:

9
api/services/summary_index_service.py
View File

@ -681,16 +681,15 @@ class SummaryIndexService:
summary_content: New summary content
Returns:
Updated DocumentSegmentSummary instance, or None if summary index is not enabled
Updated DocumentSegmentSummary instance, or None if indexing technique is not high_quality
"""
# Only update summary index for high_quality indexing technique
if dataset.indexing_technique != "high_quality":
return None
# Check if summary index is enabled
summary_index_setting = dataset.summary_index_setting
if not summary_index_setting or not summary_index_setting.get("enable"):
return None
# When user manually provides summary, allow saving even if summary_index_setting doesn't exist
# summary_index_setting is only needed for LLM generation, not for manual summary vectorization
# Vectorization uses dataset.embedding_model, which doesn't require summary_index_setting
# Skip qa_model documents
if segment.document and segment.document.doc_form == "qa_model":