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# | |
# 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 argparse | |
import json | |
from graphrag import leiden | |
from graphrag.community_reports_extractor import CommunityReportsExtractor | |
from graphrag.entity_resolution import EntityResolution | |
from graphrag.graph_extractor import GraphExtractor | |
from graphrag.leiden import add_community_info2graph | |
if __name__ == "__main__": | |
parser = argparse.ArgumentParser() | |
parser.add_argument('-t', '--tenant_id', default=False, help="Tenant ID", action='store', required=True) | |
parser.add_argument('-d', '--doc_id', default=False, help="Document ID", action='store', required=True) | |
args = parser.parse_args() | |
from api.db import LLMType | |
from api.db.services.llm_service import LLMBundle | |
from api.settings import retrievaler | |
ex = GraphExtractor(LLMBundle(args.tenant_id, LLMType.CHAT)) | |
docs = [d["content_with_weight"] for d in | |
retrievaler.chunk_list(args.doc_id, args.tenant_id, max_count=6, fields=["content_with_weight"])] | |
graph = ex(docs) | |
er = EntityResolution(LLMBundle(args.tenant_id, LLMType.CHAT)) | |
graph = er(graph.output) | |
comm = leiden.run(graph.output, {}) | |
add_community_info2graph(graph.output, comm) | |
# print(json.dumps(nx.node_link_data(graph.output), ensure_ascii=False,indent=2)) | |
print(json.dumps(comm, ensure_ascii=False, indent=2)) | |
cr = CommunityReportsExtractor(LLMBundle(args.tenant_id, LLMType.CHAT)) | |
cr = cr(graph.output) | |
print("------------------ COMMUNITY REPORT ----------------------\n", cr.output) | |
print(json.dumps(cr.structured_output, ensure_ascii=False, indent=2)) |