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### What problem does this PR solve? #1594 ### Type of change - [x] New Feature (non-breaking change which adds functionality)
52 lines
2.1 KiB
Python
52 lines
2.1 KiB
Python
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# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import argparse
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import json
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from graphrag import leiden
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from graphrag.community_reports_extractor import CommunityReportsExtractor
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from graphrag.entity_resolution import EntityResolution
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from graphrag.graph_extractor import GraphExtractor
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from graphrag.leiden import add_community_info2graph
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument('-t', '--tenant_id', default=False, help="Tenant ID", action='store', required=True)
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parser.add_argument('-d', '--doc_id', default=False, help="Document ID", action='store', required=True)
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args = parser.parse_args()
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from api.db import LLMType
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from api.db.services.llm_service import LLMBundle
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from api.settings import retrievaler
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ex = GraphExtractor(LLMBundle(args.tenant_id, LLMType.CHAT))
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docs = [d["content_with_weight"] for d in
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retrievaler.chunk_list(args.doc_id, args.tenant_id, max_count=6, fields=["content_with_weight"])]
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graph = ex(docs)
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er = EntityResolution(LLMBundle(args.tenant_id, LLMType.CHAT))
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graph = er(graph.output)
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comm = leiden.run(graph.output, {})
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add_community_info2graph(graph.output, comm)
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# print(json.dumps(nx.node_link_data(graph.output), ensure_ascii=False,indent=2))
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print(json.dumps(comm, ensure_ascii=False, indent=2))
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cr = CommunityReportsExtractor(LLMBundle(args.tenant_id, LLMType.CHAT))
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cr = cr(graph.output)
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print("------------------ COMMUNITY REPORT ----------------------\n", cr.output)
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print(json.dumps(cr.structured_output, ensure_ascii=False, indent=2)) |