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add openai embedding function to nodejs client (#107)
- openai is an optional dependency for lancedb - added an example to show how to use it
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28
node/src/embedding/embedding_function.ts
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28
node/src/embedding/embedding_function.ts
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// Copyright 2023 Lance Developers.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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/**
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* An embedding function that automatically creates vector representation for a given column.
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*/
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export interface EmbeddingFunction<T> {
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/**
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* The name of the column that will be used as input for the Embedding Function.
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*/
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sourceColumn: string
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/**
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* Creates a vector representation for the given values.
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*/
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embed: (data: T[]) => Promise<number[][]>
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}
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51
node/src/embedding/openai.ts
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node/src/embedding/openai.ts
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// Copyright 2023 Lance Developers.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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import { type EmbeddingFunction } from '../index'
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export class OpenAIEmbeddingFunction implements EmbeddingFunction<string> {
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private readonly _openai: any
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private readonly _modelName: string
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constructor (sourceColumn: string, openAIKey: string, modelName: string = 'text-embedding-ada-002') {
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let openai
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try {
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// eslint-disable-next-line @typescript-eslint/no-var-requires
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openai = require('openai')
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} catch {
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throw new Error('please install openai using npm install openai')
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}
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this.sourceColumn = sourceColumn
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const configuration = new openai.Configuration({
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apiKey: openAIKey
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})
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this._openai = new openai.OpenAIApi(configuration)
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this._modelName = modelName
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}
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async embed (data: string[]): Promise<number[][]> {
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const response = await this._openai.createEmbedding({
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model: this._modelName,
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input: data
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})
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const embeddings: number[][] = []
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for (let i = 0; i < response.data.data.length; i++) {
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embeddings.push(response.data.data[i].embedding as number[])
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}
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return embeddings
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}
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sourceColumn: string
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}
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