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feat: Add summary index for knowledge. (#31625)

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Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: Jyong <76649700+JohnJyong@users.noreply.github.com>
Co-authored-by: zxhlyh <jasonapring2015@outlook.com>
Co-authored-by: Yansong Zhang <916125788@qq.com>
Co-authored-by: hj24 <mambahj24@gmail.com>
Co-authored-by: CodingOnStar <hanxujiang@dify.ai>
Co-authored-by: CodingOnStar <hanxujiang@dify.com>
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FFXN
2026-01-29 13:47:35 +08:00
committed by GitHub
parent 5ce3a04a2c
commit c2473d85dc
51 changed files with 3797 additions and 60 deletions
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140
api/core/rag/datasource/retrieval_service.py
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@ -24,7 +24,13 @@ from core.rag.rerank.rerank_type import RerankMode
from core.rag.retrieval.retrieval_methods import RetrievalMethod
from core.tools.signature import sign_upload_file
from extensions.ext_database import db
from models.dataset import ChildChunk, Dataset, DocumentSegment, SegmentAttachmentBinding
from models.dataset import (
ChildChunk,
Dataset,
DocumentSegment,
DocumentSegmentSummary,
SegmentAttachmentBinding,
)
from models.dataset import Document as DatasetDocument
from models.model import UploadFile
from services.external_knowledge_service import ExternalDatasetService
@ -389,15 +395,15 @@ class RetrievalService:
.all()
}
records = []
include_segment_ids = set()
segment_child_map = {}
valid_dataset_documents = {}
image_doc_ids: list[Any] = []
child_index_node_ids = []
index_node_ids = []
doc_to_document_map = {}
summary_segment_ids = set() # Track segments retrieved via summary
summary_score_map: dict[str, float] = {} # Map original_chunk_id to summary score
# First pass: collect all document IDs and identify summary documents
for document in documents:
document_id = document.metadata.get("document_id")
if document_id not in dataset_documents:
@ -408,16 +414,39 @@ class RetrievalService:
continue
valid_dataset_documents[document_id] = dataset_document
doc_id = document.metadata.get("doc_id") or ""
doc_to_document_map[doc_id] = document
# Check if this is a summary document
is_summary = document.metadata.get("is_summary", False)
if is_summary:
# For summary documents, find the original chunk via original_chunk_id
original_chunk_id = document.metadata.get("original_chunk_id")
if original_chunk_id:
summary_segment_ids.add(original_chunk_id)
# Save summary's score for later use
summary_score = document.metadata.get("score")
if summary_score is not None:
try:
summary_score_float = float(summary_score)
# If the same segment has multiple summary hits, take the highest score
if original_chunk_id not in summary_score_map:
summary_score_map[original_chunk_id] = summary_score_float
else:
summary_score_map[original_chunk_id] = max(
summary_score_map[original_chunk_id], summary_score_float
)
except (ValueError, TypeError):
# Skip invalid score values
pass
continue # Skip adding to other lists for summary documents
if dataset_document.doc_form == IndexStructureType.PARENT_CHILD_INDEX:
doc_id = document.metadata.get("doc_id") or ""
doc_to_document_map[doc_id] = document
if document.metadata.get("doc_type") == DocType.IMAGE:
image_doc_ids.append(doc_id)
else:
child_index_node_ids.append(doc_id)
else:
doc_id = document.metadata.get("doc_id") or ""
doc_to_document_map[doc_id] = document
if document.metadata.get("doc_type") == DocType.IMAGE:
image_doc_ids.append(doc_id)
else:
@ -433,6 +462,7 @@ class RetrievalService:
attachment_map: dict[str, list[dict[str, Any]]] = {}
child_chunk_map: dict[str, list[ChildChunk]] = {}
doc_segment_map: dict[str, list[str]] = {}
segment_summary_map: dict[str, str] = {} # Map segment_id to summary content
with session_factory.create_session() as session:
attachments = cls.get_segment_attachment_infos(image_doc_ids, session)
@ -447,6 +477,7 @@ class RetrievalService:
doc_segment_map[attachment["segment_id"]].append(attachment["attachment_id"])
else:
doc_segment_map[attachment["segment_id"]] = [attachment["attachment_id"]]
child_chunk_stmt = select(ChildChunk).where(ChildChunk.index_node_id.in_(child_index_node_ids))
child_index_nodes = session.execute(child_chunk_stmt).scalars().all()
@ -470,6 +501,7 @@ class RetrievalService:
index_node_segments = session.execute(document_segment_stmt).scalars().all() # type: ignore
for index_node_segment in index_node_segments:
doc_segment_map[index_node_segment.id] = [index_node_segment.index_node_id]
if segment_ids:
document_segment_stmt = select(DocumentSegment).where(
DocumentSegment.enabled == True,
@ -481,6 +513,40 @@ class RetrievalService:
if index_node_segments:
segments.extend(index_node_segments)
# Handle summary documents: query segments by original_chunk_id
if summary_segment_ids:
summary_segment_ids_list = list(summary_segment_ids)
summary_segment_stmt = select(DocumentSegment).where(
DocumentSegment.enabled == True,
DocumentSegment.status == "completed",
DocumentSegment.id.in_(summary_segment_ids_list),
)
summary_segments = session.execute(summary_segment_stmt).scalars().all() # type: ignore
segments.extend(summary_segments)
# Add summary segment IDs to segment_ids for summary query
for seg in summary_segments:
if seg.id not in segment_ids:
segment_ids.append(seg.id)
# Batch query summaries for segments retrieved via summary (only enabled summaries)
if summary_segment_ids:
summaries = (
session.query(DocumentSegmentSummary)
.filter(
DocumentSegmentSummary.chunk_id.in_(list(summary_segment_ids)),
DocumentSegmentSummary.status == "completed",
DocumentSegmentSummary.enabled == True, # Only retrieve enabled summaries
)
.all()
)
for summary in summaries:
if summary.summary_content:
segment_summary_map[summary.chunk_id] = summary.summary_content
include_segment_ids = set()
segment_child_map: dict[str, dict[str, Any]] = {}
records: list[dict[str, Any]] = []
for segment in segments:
child_chunks: list[ChildChunk] = child_chunk_map.get(segment.id, [])
attachment_infos: list[dict[str, Any]] = attachment_map.get(segment.id, [])
@ -489,30 +555,44 @@ class RetrievalService:
if ds_dataset_document and ds_dataset_document.doc_form == IndexStructureType.PARENT_CHILD_INDEX:
if segment.id not in include_segment_ids:
include_segment_ids.add(segment.id)
# Check if this segment was retrieved via summary
# Use summary score as base score if available, otherwise 0.0
max_score = summary_score_map.get(segment.id, 0.0)
if child_chunks or attachment_infos:
child_chunk_details = []
max_score = 0.0
for child_chunk in child_chunks:
document = doc_to_document_map[child_chunk.index_node_id]
child_document: Document | None = doc_to_document_map.get(child_chunk.index_node_id)
if child_document:
child_score = child_document.metadata.get("score", 0.0)
else:
child_score = 0.0
child_chunk_detail = {
"id": child_chunk.id,
"content": child_chunk.content,
"position": child_chunk.position,
"score": document.metadata.get("score", 0.0) if document else 0.0,
"score": child_score,
}
child_chunk_details.append(child_chunk_detail)
max_score = max(max_score, document.metadata.get("score", 0.0) if document else 0.0)
max_score = max(max_score, child_score)
for attachment_info in attachment_infos:
file_document = doc_to_document_map[attachment_info["id"]]
max_score = max(
max_score, file_document.metadata.get("score", 0.0) if file_document else 0.0
)
file_document = doc_to_document_map.get(attachment_info["id"])
if file_document:
max_score = max(max_score, file_document.metadata.get("score", 0.0))
map_detail = {
"max_score": max_score,
"child_chunks": child_chunk_details,
}
segment_child_map[segment.id] = map_detail
else:
# No child chunks or attachments, use summary score if available
summary_score = summary_score_map.get(segment.id)
if summary_score is not None:
segment_child_map[segment.id] = {
"max_score": summary_score,
"child_chunks": [],
}
record: dict[str, Any] = {
"segment": segment,
}
@ -520,14 +600,23 @@ class RetrievalService:
else:
if segment.id not in include_segment_ids:
include_segment_ids.add(segment.id)
max_score = 0.0
segment_document = doc_to_document_map.get(segment.index_node_id)
if segment_document:
max_score = max(max_score, segment_document.metadata.get("score", 0.0))
# Check if this segment was retrieved via summary
# Use summary score if available (summary retrieval takes priority)
max_score = summary_score_map.get(segment.id, 0.0)
# If not retrieved via summary, use original segment's score
if segment.id not in summary_score_map:
segment_document = doc_to_document_map.get(segment.index_node_id)
if segment_document:
max_score = max(max_score, segment_document.metadata.get("score", 0.0))
# Also consider attachment scores
for attachment_info in attachment_infos:
file_doc = doc_to_document_map.get(attachment_info["id"])
if file_doc:
max_score = max(max_score, file_doc.metadata.get("score", 0.0))
record = {
"segment": segment,
"score": max_score,
@ -576,9 +665,16 @@ class RetrievalService:
else None
)
# Extract summary if this segment was retrieved via summary
summary_content = segment_summary_map.get(segment.id)
# Create RetrievalSegments object
retrieval_segment = RetrievalSegments(
segment=segment, child_chunks=child_chunks_list, score=score, files=files
segment=segment,
child_chunks=child_chunks_list,
score=score,
files=files,
summary=summary_content,
)
result.append(retrieval_segment)