mirror of
https://github.com/hwchase17/langchain
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fa5d49f2c1
ran ```bash g grep -l "langchain.vectorstores" | xargs -L 1 sed -i '' "s/langchain\.vectorstores/langchain_community.vectorstores/g" g grep -l "langchain.document_loaders" | xargs -L 1 sed -i '' "s/langchain\.document_loaders/langchain_community.document_loaders/g" g grep -l "langchain.chat_loaders" | xargs -L 1 sed -i '' "s/langchain\.chat_loaders/langchain_community.chat_loaders/g" g grep -l "langchain.document_transformers" | xargs -L 1 sed -i '' "s/langchain\.document_transformers/langchain_community.document_transformers/g" g grep -l "langchain\.graphs" | xargs -L 1 sed -i '' "s/langchain\.graphs/langchain_community.graphs/g" g grep -l "langchain\.memory\.chat_message_histories" | xargs -L 1 sed -i '' "s/langchain\.memory\.chat_message_histories/langchain_community.chat_message_histories/g" gco master libs/langchain/tests/unit_tests/*/test_imports.py gco master libs/langchain/tests/unit_tests/**/test_public_api.py ```
22 lines
486 B
Python
22 lines
486 B
Python
from langchain_community.graphs import Neo4jGraph
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graph = Neo4jGraph()
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# Import sample data
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graph.query(
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"""
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MERGE (m:Movie {name:"Top Gun"})
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WITH m
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UNWIND ["Tom Cruise", "Val Kilmer", "Anthony Edwards", "Meg Ryan"] AS actor
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MERGE (a:Person {name:actor})
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MERGE (a)-[:ACTED_IN]->(m)
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"""
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)
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# Create full text index for entity matching
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# on Person and Movie nodes
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graph.query(
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"CREATE FULLTEXT INDEX entity IF NOT EXISTS"
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" FOR (m:Movie|Person) ON EACH [m.title, m.name]"
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)
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