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Merge pull request #4 from itaybar/removed-transformers
removed transformers dependency
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,52 +1,52 @@ | ||
| import type { Tensor, Pipeline } from "@xenova/transformers"; | ||
| import { pipeline, dot } from "@xenova/transformers"; | ||
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| // see here: https://github.com/nmslib/hnswlib/blob/359b2ba87358224963986f709e593d799064ace6/README.md?plain=1#L34 | ||
| function innerProduct(tensor1: Tensor, tensor2: Tensor) { | ||
| return 1.0 - dot(tensor1.data, tensor2.data); | ||
| } | ||
|
|
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| // Use the Singleton pattern to enable lazy construction of the pipeline. | ||
| class PipelineSingleton { | ||
| static modelId = "Xenova/gte-small"; | ||
| static instance: Promise<Pipeline> | null = null; | ||
| static async getInstance() { | ||
| if (this.instance === null) { | ||
| this.instance = pipeline("feature-extraction", this.modelId); | ||
| } | ||
| return this.instance; | ||
| } | ||
| } | ||
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| // see https://huggingface.co/thenlper/gte-small/blob/d8e2604cadbeeda029847d19759d219e0ce2e6d8/README.md?code=true#L2625 | ||
| // import type { Tensor, Pipeline } from "@xenova/transformers"; | ||
| // import { pipeline, dot } from "@xenova/transformers"; | ||
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| // // see here: https://github.com/nmslib/hnswlib/blob/359b2ba87358224963986f709e593d799064ace6/README.md?plain=1#L34 | ||
| // function innerProduct(tensor1: Tensor, tensor2: Tensor) { | ||
| // return 1.0 - dot(tensor1.data, tensor2.data); | ||
| // } | ||
|
|
||
| // // Use the Singleton pattern to enable lazy construction of the pipeline. | ||
| // class PipelineSingleton { | ||
| // static modelId = "Xenova/gte-small"; | ||
| // static instance: Promise<Pipeline> | null = null; | ||
| // static async getInstance() { | ||
| // if (this.instance === null) { | ||
| // this.instance = pipeline("feature-extraction", this.modelId); | ||
| // } | ||
| // return this.instance; | ||
| // } | ||
| // } | ||
|
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||
| // // see https://huggingface.co/thenlper/gte-small/blob/d8e2604cadbeeda029847d19759d219e0ce2e6d8/README.md?code=true#L2625 | ||
| export const MAX_SEQ_LEN = 512 as const; | ||
|
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||
| export async function findSimilarSentences( | ||
| query: string, | ||
| sentences: string[], | ||
| { topK = 5 }: { topK: number } | ||
| ) { | ||
| const input = [query, ...sentences]; | ||
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| const extractor = await PipelineSingleton.getInstance(); | ||
| const output: Tensor = await extractor(input, { pooling: "mean", normalize: true }); | ||
|
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| const queryTensor: Tensor = output[0]; | ||
| const sentencesTensor: Tensor = output.slice([1, input.length - 1]); | ||
|
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| const distancesFromQuery: { distance: number; index: number }[] = [...sentencesTensor].map( | ||
| (sentenceTensor: Tensor, index: number) => { | ||
| return { | ||
| distance: innerProduct(queryTensor, sentenceTensor), | ||
| index: index, | ||
| }; | ||
| } | ||
| ); | ||
|
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| distancesFromQuery.sort((a, b) => { | ||
| return a.distance - b.distance; | ||
| }); | ||
|
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| // Return the indexes of the closest topK sentences | ||
| return distancesFromQuery.slice(0, topK).map((item) => item.index); | ||
| } | ||
| // export async function findSimilarSentences( | ||
| // query: string, | ||
| // sentences: string[], | ||
| // { topK = 5 }: { topK: number } | ||
| // ) { | ||
| // const input = [query, ...sentences]; | ||
|
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||
| // const extractor = await PipelineSingleton.getInstance(); | ||
| // const output: Tensor = await extractor(input, { pooling: "mean", normalize: true }); | ||
|
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| // const queryTensor: Tensor = output[0]; | ||
| // const sentencesTensor: Tensor = output.slice([1, input.length - 1]); | ||
|
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| // const distancesFromQuery: { distance: number; index: number }[] = [...sentencesTensor].map( | ||
| // (sentenceTensor: Tensor, index: number) => { | ||
| // return { | ||
| // distance: innerProduct(queryTensor, sentenceTensor), | ||
| // index: index, | ||
| // }; | ||
| // } | ||
| // ); | ||
|
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| // distancesFromQuery.sort((a, b) => { | ||
| // return a.distance - b.distance; | ||
| // }); | ||
|
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| // // Return the indexes of the closest topK sentences | ||
| // return distancesFromQuery.slice(0, topK).map((item) => item.index); | ||
| // } |