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100 lines
3.0 KiB
Python
100 lines
3.0 KiB
Python
import datetime
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import logging
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import time
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import click
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from celery import shared_task
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from llama_index.data_structs import Node
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from llama_index.data_structs.node_v2 import DocumentRelationship
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from werkzeug.exceptions import NotFound
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from core.index.keyword_table_index import KeywordTableIndex
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from core.index.vector_index import VectorIndex
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from extensions.ext_database import db
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from extensions.ext_redis import redis_client
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from models.dataset import DocumentSegment, Document
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@shared_task
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def add_document_to_index_task(document_id: str):
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"""
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Async Add document to index
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:param document_id:
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Usage: add_document_to_index.delay(document_id)
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"""
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logging.info(click.style('Start add document to index: {}'.format(document_id), fg='green'))
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start_at = time.perf_counter()
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document = db.session.query(Document).filter(Document.id == document_id).first()
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if not document:
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raise NotFound('Document not found')
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if document.indexing_status != 'completed':
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return
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indexing_cache_key = 'document_{}_indexing'.format(document.id)
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try:
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segments = db.session.query(DocumentSegment).filter(
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DocumentSegment.document_id == document.id,
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DocumentSegment.enabled == True
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) \
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.order_by(DocumentSegment.position.asc()).all()
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nodes = []
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previous_node = None
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for segment in segments:
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relationships = {
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DocumentRelationship.SOURCE: document.id
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}
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if previous_node:
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relationships[DocumentRelationship.PREVIOUS] = previous_node.doc_id
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previous_node.relationships[DocumentRelationship.NEXT] = segment.index_node_id
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node = Node(
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doc_id=segment.index_node_id,
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doc_hash=segment.index_node_hash,
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text=segment.content,
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extra_info=None,
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node_info=None,
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relationships=relationships
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)
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previous_node = node
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nodes.append(node)
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dataset = document.dataset
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if not dataset:
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raise Exception('Document has no dataset')
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vector_index = VectorIndex(dataset=dataset)
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keyword_table_index = KeywordTableIndex(dataset=dataset)
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# save vector index
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if dataset.indexing_technique == "high_quality":
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vector_index.add_nodes(
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nodes=nodes,
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duplicate_check=True
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)
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# save keyword index
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keyword_table_index.add_nodes(nodes)
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end_at = time.perf_counter()
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logging.info(
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click.style('Document added to index: {} latency: {}'.format(document.id, end_at - start_at), fg='green'))
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except Exception as e:
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logging.exception("add document to index failed")
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document.enabled = False
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document.disabled_at = datetime.datetime.utcnow()
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document.status = 'error'
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document.error = str(e)
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db.session.commit()
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finally:
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redis_client.delete(indexing_cache_key)
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