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Light GraphRAG (#4585)
### What problem does this PR solve? #4543 ### Type of change - [x] New Feature (non-breaking change which adds functionality)
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graphrag/light/smoke.py
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58
graphrag/light/smoke.py
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#
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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 api import settings
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import networkx as nx
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from api.db import LLMType
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from api.db.services.document_service import DocumentService
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from api.db.services.knowledgebase_service import KnowledgebaseService
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from api.db.services.llm_service import LLMBundle
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from api.db.services.user_service import TenantService
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from graphrag.general.index import Dealer
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from graphrag.light.graph_extractor import GraphExtractor
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from rag.utils.redis_conn import RedisDistributedLock
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settings.init_settings()
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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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e, doc = DocumentService.get_by_id(args.doc_id)
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if not e:
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raise LookupError("Document not found.")
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kb_id = doc.kb_id
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chunks = [d["content_with_weight"] for d in
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settings.retrievaler.chunk_list(args.doc_id, args.tenant_id, [kb_id], max_count=6,
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fields=["content_with_weight"])]
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chunks = [("x", c) for c in chunks]
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RedisDistributedLock.clean_lock(kb_id)
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_, tenant = TenantService.get_by_id(args.tenant_id)
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llm_bdl = LLMBundle(args.tenant_id, LLMType.CHAT, tenant.llm_id)
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_, kb = KnowledgebaseService.get_by_id(kb_id)
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embed_bdl = LLMBundle(args.tenant_id, LLMType.EMBEDDING, kb.embd_id)
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dealer = Dealer(GraphExtractor, args.tenant_id, kb_id, llm_bdl, chunks, "English", embed_bdl=embed_bdl)
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print(json.dumps(nx.node_link_data(dealer.graph), ensure_ascii=False, indent=2))
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