OracleVS 集成

export ORACLE_USER=testuser
export ORACLE_PASSWORD=testuser
export ORACLE_DSN="localhost:1521/free"

import oracledb from "oracledb";
import { OracleEmbeddings, OracleVS } from "@oracle/langchain-oracledb";
import { Document } from "@langchain/core/documents";

const connection = await oracledb.getConnection({
  user: process.env.ORACLE_USER,
  password: process.env.ORACLE_PASSWORD,
  connectionString: process.env.ORACLE_DSN,
});

const embeddings = new OracleEmbeddings(connection, {
  provider: "database",
  model: "DEMO_MODEL",
});

const vectorStore = new OracleVS(embeddings, {
  client: connection,
  tableName: "DEMO_VECTORS",
  query: "Find documents about Oracle RAG patterns.",
  distanceStrategy: "DOT",
});
await vectorStore.initialize();

const docs: Document[] = [
  {
    pageContent: "LangChain works great with Oracle Database.",
    metadata: {
      doc_id: "doc-1",
      title: "RAG overview",
      status: "release",
      tags: ["AI", "rag"],
      category: "books",
      price: 18,
    },
  },
];

await vectorStore.addDocuments(docs);

// 在应用程序关闭钩子中关闭连接或池以避免泄漏。
// await connection.close();

const pool = await oracledb.createPool({
  user: process.env.ORACLE_USER,
  password: process.env.ORACLE_PASSWORD,
  connectString: process.env.ORACLE_DSN,
  poolIncrement: 1,
  poolMax: 4,
  poolMin: 0,
  poolPingInterval: 60,
});

const vectorStoreFromPool = new OracleVS(embeddings, {
  client: pool,
  tableName: "DEMO_VECTORS",
  query: "Find documents about Oracle RAG patterns.",
  distanceStrategy: "DOT",
});
await vectorStoreFromPool.initialize();

// 在关闭期间释放资源。
// await pool.close(0);

const results = await vectorStore.similaritySearch("oracle rag", 3, {
  $and: [
    { status: "release" },
    { tags: { $in: ["AI"] } },
    { price: { $between: [10, 25] } },
  ],
});

// 或者请求文档及其分数。
const scored = await vectorStore.similaritySearchWithScore(
  "oracle rag",
  3,
  { status: "release" },
);

console.log(results[0]?.pageContent);
console.log(scored[0]?.[1]); // 相似性分数

const complexFilter = {
  $or: [
    { status: "draft" },
    {
      $and: [
        { category: "books" },
        { price: { $lte: 20 } },
      ],
    },
  ],
};

import { createIndex } from "@oracle/langchain-oracledb";

// 重用设置部分中的 vectorStore 和 connection，
// 或使用 OracleVS.fromDocuments / initialize() 创建一个。
await createIndex(connection, vectorStore, {
  idxName: "demo_hnsw_idx",
  neighbors: 48,
  efConstruction: 400,
  accuracy: 95,
  parallel: 16,
});

import { createIndex } from "@oracle/langchain-oracledb";

await createIndex(connection, vectorStore, {
  idxName: "demo_ivf_idx",
  idxType: "IVF",
  neighborPart: 64,
  accuracy: 90,
  parallel: 8,
});