mirror of
https://github.com/Mintplex-Labs/langchain-python.git
synced 2026-07-25 04:26:41 -04:00
Simon Cheung
81eebc4070
[Apache HugeGraph](https://github.com/apache/incubator-hugegraph) is a convenient, efficient, and adaptable graph database, compatible with the Apache TinkerPop3 framework and the Gremlin query language. In this PR, the HugeGraph and HugeGraphQAChain provide the same functionality as the existing integration with Neo4j and enables query generation and question answering over HugeGraph database. The difference is that the graph query language supported by HugeGraph is not cypher but another very popular graph query language [Gremlin](https://tinkerpop.apache.org/gremlin.html). A notebook example and a simple test case have also been added. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
from typing import Any, Dict, List
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class HugeGraph:
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"""HugeGraph wrapper for graph operations"""
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def __init__(
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self,
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username: str = "default",
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password: str = "default",
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address: str = "127.0.0.1",
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port: int = 8081,
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graph: str = "hugegraph",
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) -> None:
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"""Create a new HugeGraph wrapper instance."""
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try:
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from hugegraph.connection import PyHugeGraph
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except ImportError:
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raise ValueError(
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"Please install HugeGraph Python client first: "
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"`pip3 install hugegraph-python`"
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)
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self.username = username
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self.password = password
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self.address = address
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self.port = port
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self.graph = graph
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self.client = PyHugeGraph(
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address, port, user=username, pwd=password, graph=graph
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)
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self.schema = ""
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# Set schema
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try:
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self.refresh_schema()
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except Exception as e:
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raise ValueError(f"Could not refresh schema. Error: {e}")
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@property
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def get_schema(self) -> str:
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"""Returns the schema of the HugeGraph database"""
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return self.schema
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def refresh_schema(self) -> None:
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"""
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Refreshes the HugeGraph schema information.
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"""
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schema = self.client.schema()
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vertex_schema = schema.getVertexLabels()
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edge_schema = schema.getEdgeLabels()
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relationships = schema.getRelations()
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self.schema = (
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f"Node properties: {vertex_schema}\n"
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f"Edge properties: {edge_schema}\n"
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f"Relationships: {relationships}\n"
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)
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def query(self, query: str) -> List[Dict[str, Any]]:
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g = self.client.gremlin()
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res = g.exec(query)
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return res["data"]
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