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52 lines
1.3 KiB
Python
52 lines
1.3 KiB
Python
import os
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import asyncio
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from lightrag.kg.postgres_impl import PGGraphStorage
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from lightrag.llm.ollama import ollama_embedding
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from lightrag.utils import EmbeddingFunc
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#########
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# Uncomment the below two lines if running in a jupyter notebook to handle the async nature of rag.insert()
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# import nest_asyncio
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# nest_asyncio.apply()
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#########
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WORKING_DIR = "./local_neo4jWorkDir"
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if not os.path.exists(WORKING_DIR):
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os.mkdir(WORKING_DIR)
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# AGE
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os.environ["AGE_GRAPH_NAME"] = "dickens"
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os.environ["POSTGRES_HOST"] = "localhost"
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os.environ["POSTGRES_PORT"] = "15432"
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os.environ["POSTGRES_USER"] = "rag"
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os.environ["POSTGRES_PASSWORD"] = "rag"
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os.environ["POSTGRES_DATABASE"] = "rag"
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async def main():
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graph_db = PGGraphStorage(
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namespace="dickens",
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embedding_func=EmbeddingFunc(
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embedding_dim=1024,
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max_token_size=8192,
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func=lambda texts: ollama_embedding(
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texts, embed_model="bge-m3", host="http://localhost:11434"
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),
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),
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global_config={},
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)
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await graph_db.initialize()
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labels = await graph_db.get_all_labels()
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print("all labels", labels)
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res = await graph_db.get_knowledge_graph("FEZZIWIG")
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print("knowledge graphs", res)
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await graph_db.finalize()
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if __name__ == "__main__":
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asyncio.run(main())
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