mirror of
https://github.com/hwchase17/langchain
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60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
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from langchain_community.graphs import Neo4jGraph
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# Instantiate connection to Neo4j
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graph = Neo4jGraph()
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# Define unique constraints
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graph.query("CREATE CONSTRAINT IF NOT EXISTS FOR (m:Movie) REQUIRE m.id IS UNIQUE;")
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graph.query("CREATE CONSTRAINT IF NOT EXISTS FOR (u:User) REQUIRE u.id IS UNIQUE;")
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graph.query("CREATE CONSTRAINT IF NOT EXISTS FOR (p:Person) REQUIRE p.name IS UNIQUE;")
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graph.query("CREATE CONSTRAINT IF NOT EXISTS FOR (g:Genre) REQUIRE g.name IS UNIQUE;")
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# Import movie information
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movies_query = """
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LOAD CSV WITH HEADERS FROM
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'https://raw.githubusercontent.com/tomasonjo/blog-datasets/main/movies/movies.csv'
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AS row
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CALL {
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WITH row
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MERGE (m:Movie {id:row.movieId})
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SET m.released = date(row.released),
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m.title = row.title,
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m.imdbRating = toFloat(row.imdbRating)
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FOREACH (director in split(row.director, '|') |
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MERGE (p:Person {name:trim(director)})
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MERGE (p)-[:DIRECTED]->(m))
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FOREACH (actor in split(row.actors, '|') |
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MERGE (p:Person {name:trim(actor)})
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MERGE (p)-[:ACTED_IN]->(m))
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FOREACH (genre in split(row.genres, '|') |
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MERGE (g:Genre {name:trim(genre)})
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MERGE (m)-[:IN_GENRE]->(g))
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} IN TRANSACTIONS
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"""
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graph.query(movies_query)
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# Import rating information
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rating_query = """
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LOAD CSV WITH HEADERS FROM
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'https://raw.githubusercontent.com/tomasonjo/blog-datasets/main/movies/ratings.csv'
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AS row
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CALL {
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WITH row
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MATCH (m:Movie {id:row.movieId})
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MERGE (u:User {id:row.userId})
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MERGE (u)-[r:RATED]->(m)
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SET r.rating = toFloat(row.rating),
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r.timestamp = row.timestamp
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} IN TRANSACTIONS OF 10000 ROWS
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"""
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graph.query(rating_query)
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# Define fulltext indices
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graph.query("CREATE FULLTEXT INDEX movie IF NOT EXISTS FOR (m:Movie) ON EACH [m.title]")
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graph.query(
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"CREATE FULLTEXT INDEX person IF NOT EXISTS FOR (p:Person) ON EACH [p.name]"
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)
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