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Feat/support multimodal embedding (#29115)

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Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
This commit is contained in:
Jyong
2025-12-09 14:41:46 +08:00
committed by GitHub
parent 77cf8f6c27
commit 9affc546c6
78 changed files with 3230 additions and 713 deletions
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24
api/tasks/add_document_to_index_task.py
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@@ -4,9 +4,10 @@ import time
import click
from celery import shared_task
from core.rag.index_processor.constant.index_type import IndexType
from core.rag.index_processor.constant.doc_type import DocType
from core.rag.index_processor.constant.index_type import IndexStructureType
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from core.rag.models.document import ChildDocument, Document
from core.rag.models.document import AttachmentDocument, ChildDocument, Document
from extensions.ext_database import db
from extensions.ext_redis import redis_client
from libs.datetime_utils import naive_utc_now
@@ -55,6 +56,7 @@ def add_document_to_index_task(dataset_document_id: str):
)
documents = []
multimodal_documents = []
for segment in segments:
document = Document(
page_content=segment.content,
@@ -65,7 +67,7 @@ def add_document_to_index_task(dataset_document_id: str):
"dataset_id": segment.dataset_id,
},
)
if dataset_document.doc_form == IndexType.PARENT_CHILD_INDEX:
if dataset_document.doc_form == IndexStructureType.PARENT_CHILD_INDEX:
child_chunks = segment.get_child_chunks()
if child_chunks:
child_documents = []
@@ -81,11 +83,25 @@ def add_document_to_index_task(dataset_document_id: str):
)
child_documents.append(child_document)
document.children = child_documents
if dataset.is_multimodal:
for attachment in segment.attachments:
multimodal_documents.append(
AttachmentDocument(
page_content=attachment["name"],
metadata={
"doc_id": attachment["id"],
"doc_hash": "",
"document_id": segment.document_id,
"dataset_id": segment.dataset_id,
"doc_type": DocType.IMAGE,
},
)
)
documents.append(document)
index_type = dataset.doc_form
index_processor = IndexProcessorFactory(index_type).init_index_processor()
index_processor.load(dataset, documents)
index_processor.load(dataset, documents, multimodal_documents=multimodal_documents)
# delete auto disable log
db.session.query(DatasetAutoDisableLog).where(DatasetAutoDisableLog.document_id == dataset_document.id).delete()