mirror of
https://github.com/Mintplex-Labs/anything-llm.git
synced 2024-11-09 00:10:10 +01:00
70 lines
2.0 KiB
JavaScript
70 lines
2.0 KiB
JavaScript
function getVectorDbClass() {
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const vectorSelection = process.env.VECTOR_DB || "pinecone";
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switch (vectorSelection) {
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case "pinecone":
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const { Pinecone } = require("../vectorDbProviders/pinecone");
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return Pinecone;
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case "chroma":
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const { Chroma } = require("../vectorDbProviders/chroma");
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return Chroma;
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case "lancedb":
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const { LanceDb } = require("../vectorDbProviders/lance");
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return LanceDb;
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case "weaviate":
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const { Weaviate } = require("../vectorDbProviders/weaviate");
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return Weaviate;
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case "qdrant":
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const { QDrant } = require("../vectorDbProviders/qdrant");
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return QDrant;
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default:
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throw new Error("ENV: No VECTOR_DB value found in environment!");
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}
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}
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function getLLMProvider() {
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const vectorSelection = process.env.LLM_PROVIDER || "openai";
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switch (vectorSelection) {
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case "openai":
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const { OpenAiLLM } = require("../AiProviders/openAi");
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return new OpenAiLLM();
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case "azure":
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const { AzureOpenAiLLM } = require("../AiProviders/azureOpenAi");
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return new AzureOpenAiLLM();
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case "anthropic":
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const { AnthropicLLM } = require("../AiProviders/anthropic");
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const embedder = getEmbeddingEngineSelection();
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return new AnthropicLLM(embedder);
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default:
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throw new Error("ENV: No LLM_PROVIDER value found in environment!");
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}
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}
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function getEmbeddingEngineSelection() {
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const engineSelection = process.env.EMBEDDING_ENGINE;
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switch (engineSelection) {
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case "openai":
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const { OpenAiEmbedder } = require("../EmbeddingEngines/openAi");
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return new OpenAiEmbedder();
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case "azure":
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const {
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AzureOpenAiEmbedder,
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} = require("../EmbeddingEngines/azureOpenAi");
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return new AzureOpenAiEmbedder();
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default:
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return null;
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}
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}
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function toChunks(arr, size) {
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return Array.from({ length: Math.ceil(arr.length / size) }, (_v, i) =>
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arr.slice(i * size, i * size + size)
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);
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}
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module.exports = {
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getEmbeddingEngineSelection,
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getVectorDbClass,
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getLLMProvider,
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toChunks,
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};
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