如何构建知识图谱
在本指南中，我们将介绍构建基于非结构化文本的知识图谱的基本方法。构建的图谱随后可用作 RAG 应用程序中的知识库。从高层次来看，从文本构建知识图谱的步骤如下：
- 从文本中提取结构化信息：模型用于从文本中提取结构化的图谱信息。
- 存储到图数据库：将提取的结构化图谱信息存储到图数据库，从而实现下游 RAG 应用程序。
设置
安装依赖项
提示
- npm
- yarn
- pnpm
npm i langchain @langchain/community @langchain/openai neo4j-driver zod
yarn add langchain @langchain/community @langchain/openai neo4j-driver zod
pnpm add langchain @langchain/community @langchain/openai neo4j-driver zod
设置环境变量
我们将在本示例中使用 OpenAI
OPENAI_API_KEY=your-api-key
# Optional, use LangSmith for best-in-class observability
LANGSMITH_API_KEY=your-api-key
LANGCHAIN_TRACING_V2=true
# Reduce tracing latency if you are not in a serverless environment
# LANGCHAIN_CALLBACKS_BACKGROUND=true
接下来，我们需要定义 Neo4j 凭据。请按照 这些安装步骤 设置 Neo4j 数据库。
NEO4J_URI="bolt://localhost:7687"
NEO4J_USERNAME="neo4j"
NEO4J_PASSWORD="password"
以下示例将创建与 Neo4j 数据库的连接。
import "neo4j-driver";
import { Neo4jGraph } from "@langchain/community/graphs/neo4j_graph";
const url = Deno.env.get("NEO4J_URI");
const username = Deno.env.get("NEO4J_USER");
const password = Deno.env.get("NEO4J_PASSWORD");
const graph = await Neo4jGraph.initialize({ url, username, password });
LLM 图谱转换器
从文本中提取图谱数据使非结构化信息能够转换为结构化格式，从而便于深入了解和更有效地浏览复杂的关系和模式。LLMGraphTransformer 通过利用 LLM 来解析和分类实体及其关系，将文本文档转换为结构化的图谱文档。LLM 模型的选择会显着影响输出，因为它决定了提取的图谱数据的准确性和细微差别。
import { ChatOpenAI } from "@langchain/openai";
import { LLMGraphTransformer } from "@langchain/community/experimental/graph_transformers/llm";
const model = new ChatOpenAI({
temperature: 0,
model: "gpt-4-turbo-preview",
});
const llmGraphTransformer = new LLMGraphTransformer({
llm: model,
});
现在，我们可以传入示例文本并检查结果。
import { Document } from "@langchain/core/documents";
let text = `
Marie Curie, was a Polish and naturalised-French physicist and chemist who conducted pioneering research on radioactivity.
She was the first woman to win a Nobel Prize, the first person to win a Nobel Prize twice, and the only person to win a Nobel Prize in two scientific fields.
Her husband, Pierre Curie, was a co-winner of her first Nobel Prize, making them the first-ever married couple to win the Nobel Prize and launching the Curie family legacy of five Nobel Prizes.
She was, in 1906, the first woman to become a professor at the University of Paris.
`;
const result = await llmGraphTransformer.convertToGraphDocuments([
new Document({ pageContent: text }),
]);
console.log(`Nodes: ${result[0].nodes.length}`);
console.log(`Relationships:${result[0].relationships.length}`);
Nodes: 8
Relationships:7
请注意，由于我们使用的是 LLM，因此图谱构建过程是非确定性的。因此，您每次执行可能会得到略有不同的结果。查看以下图像以更好地了解生成的知识图谱的结构。
此外，您可以根据您的需求灵活定义要提取的特定类型的节点和关系。
const llmGraphTransformerFiltered = new LLMGraphTransformer({
llm: model,
allowedNodes: ["PERSON", "COUNTRY", "ORGANIZATION"],
allowedRelationships: ["NATIONALITY", "LOCATED_IN", "WORKED_AT", "SPOUSE"],
strictMode: false,
});
const result_filtered =
await llmGraphTransformerFiltered.convertToGraphDocuments([
new Document({ pageContent: text }),
]);
console.log(`Nodes: ${result_filtered[0].nodes.length}`);
console.log(`Relationships:${result_filtered[0].relationships.length}`);
Nodes: 6
Relationships:4
为了更好地了解生成的图谱，我们可以再次将其可视化。
存储到图数据库
可以使用 addGraphDocuments 方法将生成的图谱文档存储到图数据库。
await graph.addGraphDocuments(result_filtered);