mirror of
https://git.mirrors.martin98.com/https://github.com/infiniflow/ragflow.git
synced 2025-04-22 06:00:00 +08:00
dd0ebbea35
### What problem does this PR solve? #4543 ### Type of change - [x] New Feature (non-breaking change which adds functionality)
198 lines
8.4 KiB
Python
198 lines
8.4 KiB
Python
#
|
|
# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
#
|
|
import json
|
|
import logging
|
|
from functools import reduce, partial
|
|
import networkx as nx
|
|
|
|
from api import settings
|
|
from graphrag.general.community_reports_extractor import CommunityReportsExtractor
|
|
from graphrag.entity_resolution import EntityResolution
|
|
from graphrag.general.extractor import Extractor
|
|
from graphrag.general.graph_extractor import DEFAULT_ENTITY_TYPES
|
|
from graphrag.utils import graph_merge, set_entity, get_relation, set_relation, get_entity, get_graph, set_graph, \
|
|
chunk_id, update_nodes_pagerank_nhop_neighbour
|
|
from rag.nlp import rag_tokenizer, search
|
|
from rag.utils.redis_conn import RedisDistributedLock
|
|
|
|
|
|
class Dealer:
|
|
def __init__(self,
|
|
extractor: Extractor,
|
|
tenant_id: str,
|
|
kb_id: str,
|
|
llm_bdl,
|
|
chunks: list[tuple[str, str]],
|
|
language,
|
|
entity_types=DEFAULT_ENTITY_TYPES,
|
|
embed_bdl=None,
|
|
callback=None
|
|
):
|
|
docids = list(set([docid for docid,_ in chunks]))
|
|
self.llm_bdl = llm_bdl
|
|
self.embed_bdl = embed_bdl
|
|
ext = extractor(self.llm_bdl, language=language,
|
|
entity_types=entity_types,
|
|
get_entity=partial(get_entity, tenant_id, kb_id),
|
|
set_entity=partial(set_entity, tenant_id, kb_id, self.embed_bdl),
|
|
get_relation=partial(get_relation, tenant_id, kb_id),
|
|
set_relation=partial(set_relation, tenant_id, kb_id, self.embed_bdl)
|
|
)
|
|
ents, rels = ext(chunks, callback)
|
|
self.graph = nx.Graph()
|
|
for en in ents:
|
|
self.graph.add_node(en["entity_name"], entity_type=en["entity_type"])#, description=en["description"])
|
|
|
|
for rel in rels:
|
|
self.graph.add_edge(
|
|
rel["src_id"],
|
|
rel["tgt_id"],
|
|
weight=rel["weight"],
|
|
#description=rel["description"]
|
|
)
|
|
|
|
with RedisDistributedLock(kb_id, 60*60):
|
|
old_graph, old_doc_ids = get_graph(tenant_id, kb_id)
|
|
if old_graph is not None:
|
|
logging.info("Merge with an exiting graph...................")
|
|
self.graph = reduce(graph_merge, [old_graph, self.graph])
|
|
update_nodes_pagerank_nhop_neighbour(tenant_id, kb_id, self.graph, 2)
|
|
if old_doc_ids:
|
|
docids.extend(old_doc_ids)
|
|
docids = list(set(docids))
|
|
set_graph(tenant_id, kb_id, self.graph, docids)
|
|
|
|
|
|
class WithResolution(Dealer):
|
|
def __init__(self,
|
|
tenant_id: str,
|
|
kb_id: str,
|
|
llm_bdl,
|
|
embed_bdl=None,
|
|
callback=None
|
|
):
|
|
self.llm_bdl = llm_bdl
|
|
self.embed_bdl = embed_bdl
|
|
|
|
with RedisDistributedLock(kb_id, 60*60):
|
|
self.graph, doc_ids = get_graph(tenant_id, kb_id)
|
|
if not self.graph:
|
|
logging.error(f"Faild to fetch the graph. tenant_id:{kb_id}, kb_id:{kb_id}")
|
|
if callback:
|
|
callback(-1, msg="Faild to fetch the graph.")
|
|
return
|
|
|
|
if callback:
|
|
callback(msg="Fetch the existing graph.")
|
|
er = EntityResolution(self.llm_bdl,
|
|
get_entity=partial(get_entity, tenant_id, kb_id),
|
|
set_entity=partial(set_entity, tenant_id, kb_id, self.embed_bdl),
|
|
get_relation=partial(get_relation, tenant_id, kb_id),
|
|
set_relation=partial(set_relation, tenant_id, kb_id, self.embed_bdl))
|
|
reso = er(self.graph)
|
|
self.graph = reso.graph
|
|
logging.info("Graph resolution is done. Remove {} nodes.".format(len(reso.removed_entities)))
|
|
if callback:
|
|
callback(msg="Graph resolution is done. Remove {} nodes.".format(len(reso.removed_entities)))
|
|
update_nodes_pagerank_nhop_neighbour(tenant_id, kb_id, self.graph, 2)
|
|
set_graph(tenant_id, kb_id, self.graph, doc_ids)
|
|
|
|
settings.docStoreConn.delete({
|
|
"knowledge_graph_kwd": "relation",
|
|
"kb_id": kb_id,
|
|
"from_entity_kwd": reso.removed_entities
|
|
}, search.index_name(tenant_id), kb_id)
|
|
settings.docStoreConn.delete({
|
|
"knowledge_graph_kwd": "relation",
|
|
"kb_id": kb_id,
|
|
"to_entity_kwd": reso.removed_entities
|
|
}, search.index_name(tenant_id), kb_id)
|
|
settings.docStoreConn.delete({
|
|
"knowledge_graph_kwd": "entity",
|
|
"kb_id": kb_id,
|
|
"entity_kwd": reso.removed_entities
|
|
}, search.index_name(tenant_id), kb_id)
|
|
|
|
|
|
class WithCommunity(Dealer):
|
|
def __init__(self,
|
|
tenant_id: str,
|
|
kb_id: str,
|
|
llm_bdl,
|
|
embed_bdl=None,
|
|
callback=None
|
|
):
|
|
|
|
self.community_structure = None
|
|
self.community_reports = None
|
|
self.llm_bdl = llm_bdl
|
|
self.embed_bdl = embed_bdl
|
|
|
|
with RedisDistributedLock(kb_id, 60*60):
|
|
self.graph, doc_ids = get_graph(tenant_id, kb_id)
|
|
if not self.graph:
|
|
logging.error(f"Faild to fetch the graph. tenant_id:{kb_id}, kb_id:{kb_id}")
|
|
if callback:
|
|
callback(-1, msg="Faild to fetch the graph.")
|
|
return
|
|
if callback:
|
|
callback(msg="Fetch the existing graph.")
|
|
|
|
cr = CommunityReportsExtractor(self.llm_bdl,
|
|
get_entity=partial(get_entity, tenant_id, kb_id),
|
|
set_entity=partial(set_entity, tenant_id, kb_id, self.embed_bdl),
|
|
get_relation=partial(get_relation, tenant_id, kb_id),
|
|
set_relation=partial(set_relation, tenant_id, kb_id, self.embed_bdl))
|
|
cr = cr(self.graph, callback=callback)
|
|
self.community_structure = cr.structured_output
|
|
self.community_reports = cr.output
|
|
set_graph(tenant_id, kb_id, self.graph, doc_ids)
|
|
|
|
if callback:
|
|
callback(msg="Graph community extraction is done. Indexing {} reports.".format(len(cr.structured_output)))
|
|
|
|
settings.docStoreConn.delete({
|
|
"knowledge_graph_kwd": "community_report",
|
|
"kb_id": kb_id
|
|
}, search.index_name(tenant_id), kb_id)
|
|
|
|
for stru, rep in zip(self.community_structure, self.community_reports):
|
|
obj = {
|
|
"report": rep,
|
|
"evidences": "\n".join([f["explanation"] for f in stru["findings"]])
|
|
}
|
|
chunk = {
|
|
"docnm_kwd": stru["title"],
|
|
"title_tks": rag_tokenizer.tokenize(stru["title"]),
|
|
"content_with_weight": json.dumps(obj, ensure_ascii=False),
|
|
"content_ltks": rag_tokenizer.tokenize(obj["report"] +" "+ obj["evidences"]),
|
|
"knowledge_graph_kwd": "community_report",
|
|
"weight_flt": stru["weight"],
|
|
"entities_kwd": stru["entities"],
|
|
"important_kwd": stru["entities"],
|
|
"kb_id": kb_id,
|
|
"source_id": doc_ids,
|
|
"available_int": 0
|
|
}
|
|
chunk["content_sm_ltks"] = rag_tokenizer.fine_grained_tokenize(chunk["content_ltks"])
|
|
#try:
|
|
# ebd, _ = self.embed_bdl.encode([", ".join(community["entities"])])
|
|
# chunk["q_%d_vec" % len(ebd[0])] = ebd[0]
|
|
#except Exception as e:
|
|
# logging.exception(f"Fail to embed entity relation: {e}")
|
|
settings.docStoreConn.insert([{"id": chunk_id(chunk), **chunk}], search.index_name(tenant_id))
|
|
|