89 lines
2.7 KiB
JavaScript
89 lines
2.7 KiB
JavaScript
const { toChunks } = require("../../helpers");
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class OpenAiEmbedder {
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constructor() {
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const { Configuration, OpenAIApi } = require("openai");
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if (!process.env.OPEN_AI_KEY) throw new Error("No OpenAI API key was set.");
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const config = new Configuration({
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apiKey: process.env.OPEN_AI_KEY,
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});
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const openai = new OpenAIApi(config);
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this.openai = openai;
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this.model = process.env.EMBEDDING_MODEL_PREF || "text-embedding-ada-002";
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// Limit of how many strings we can process in a single pass to stay with resource or network limits
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this.maxConcurrentChunks = 500;
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this.embeddingMaxChunkLength = 1_000;
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}
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async embedTextInput(textInput) {
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const result = await this.embedChunks(textInput);
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return result?.[0] || [];
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}
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async embedChunks(textChunks = []) {
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// Because there is a hard POST limit on how many chunks can be sent at once to OpenAI (~8mb)
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// we concurrently execute each max batch of text chunks possible.
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// Refer to constructor maxConcurrentChunks for more info.
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const embeddingRequests = [];
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for (const chunk of toChunks(textChunks, this.maxConcurrentChunks)) {
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embeddingRequests.push(
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new Promise((resolve) => {
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this.openai
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.createEmbedding({
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model: this.model,
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input: chunk,
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})
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.then((res) => {
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resolve({ data: res.data?.data, error: null });
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})
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.catch((e) => {
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e.type =
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e?.response?.data?.error?.code ||
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e?.response?.status ||
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"failed_to_embed";
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e.message = e?.response?.data?.error?.message || e.message;
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resolve({ data: [], error: e });
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});
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})
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);
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}
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const { data = [], error = null } = await Promise.all(
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embeddingRequests
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).then((results) => {
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// If any errors were returned from OpenAI abort the entire sequence because the embeddings
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// will be incomplete.
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const errors = results
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.filter((res) => !!res.error)
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.map((res) => res.error)
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.flat();
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if (errors.length > 0) {
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let uniqueErrors = new Set();
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errors.map((error) =>
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uniqueErrors.add(`[${error.type}]: ${error.message}`)
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);
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return {
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data: [],
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error: Array.from(uniqueErrors).join(", "),
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};
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}
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return {
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data: results.map((res) => res?.data || []).flat(),
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error: null,
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};
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});
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if (!!error) throw new Error(`OpenAI Failed to embed: ${error}`);
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return data.length > 0 &&
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data.every((embd) => embd.hasOwnProperty("embedding"))
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? data.map((embd) => embd.embedding)
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: null;
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}
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}
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module.exports = {
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OpenAiEmbedder,
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};
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