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import { IEmbeddingFunction } from "./IEmbeddingFunction";
export class JinaEmbeddingFunction implements IEmbeddingFunction {
private model_name: string;
private api_url: string;
private headers: { [key: string]: string };
constructor({ jinaai_api_key, model_name }: { jinaai_api_key: string; model_name?: string }) {
this.model_name = model_name || 'jina-embeddings-v2-base-en';
this.api_url = 'https://api.jina.ai/v1/embeddings';
this.headers = {
Authorization: `Bearer ${jinaai_api_key}`,
'Accept-Encoding': 'identity',
'Content-Type': 'application/json',
};
}
public async generate(texts: string[]) {
try {
const response = await fetch(this.api_url, {
method: 'POST',
headers: this.headers,
body: JSON.stringify({
input: texts,
model: this.model_name,
}),
});
const data = (await response.json()) as { data: any[]; detail: string };
if (!data || !data.data) {
throw new Error(data.detail);
}
const embeddings: any[] = data.data;
const sortedEmbeddings = embeddings.sort((a, b) => a.index - b.index);
return sortedEmbeddings.map((result) => result.embedding);
} catch (error) {
if (error instanceof Error) {
throw new Error(`Error calling Jina AI API: ${error.message}`);
} else {
throw new Error(`Error calling Jina AI API: ${error}`);
}
}
}
}
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