Langchain项目使用Pinecone向量存储时遇PineconeArgumentError报错排查

错误原因 #

你调用 pinecone.Index() 时没有传入具体的Pinecone索引名称，该方法要求必须传入字符串类型的索引名，因此触发了参数类型错误。

解决方案 #

1. 在 pinecone.Index() 中补充你在Pinecone控制台创建好的索引名称（字符串格式）
2. 确保该索引的维度与你使用的OpenAIEmbeddings维度匹配（OpenAI的text-embedding-ada-002对应1536维）

修改后的代码 #

const pinecone = new Pinecone();

// 替换为你实际的Pinecone索引名称
const pineconeIndex = pinecone.Index("your-pinecone-index-name");

const docs = [
  new Document({
    metadata: { foo: "bar" },
    pageContent: "pinecone is a vector db",
  }),
  new Document({
    metadata: { foo: "bar" },
    pageContent: "the quick brown fox jumped over the lazy dog",
  }),
  new Document({
    metadata: { baz: "qux" },
    pageContent: "lorem ipsum dolor sit amet",
  }),
  new Document({
    metadata: { baz: "qux" },
    pageContent: "pinecones are the woody fruiting body and of a pine tree",
  }),
];

await PineconeStore.fromDocuments(docs, new OpenAIEmbeddings(), {
  pineconeIndex,
  maxConcurrency: 5, // Maximum number of batch requests to allow at once. Each batch is 1000 vectors.
});

内容的提问来源于stack exchange，提问作者Kingsley