67 lines
1.9 KiB
TypeScript
67 lines
1.9 KiB
TypeScript
import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
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import { ChatOllama } from '@langchain/community/chat_models/ollama';
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import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
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import { getOllamaApiEndpoint, getOpenaiApiKey } from '../config';
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export const getAvailableProviders = async () => {
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const openAIApiKey = getOpenaiApiKey();
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const ollamaEndpoint = getOllamaApiEndpoint();
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const models = {};
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if (openAIApiKey) {
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try {
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models['openai'] = {
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'gpt-3.5-turbo': new ChatOpenAI({
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openAIApiKey,
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modelName: 'gpt-3.5-turbo',
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temperature: 0.7,
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}),
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'gpt-4': new ChatOpenAI({
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openAIApiKey,
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modelName: 'gpt-4',
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temperature: 0.7,
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}),
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'gpt-4-turbo': new ChatOpenAI({
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openAIApiKey,
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modelName: 'gpt-4-turbo',
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temperature: 0.7,
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}),
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embeddings: new OpenAIEmbeddings({
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openAIApiKey,
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modelName: 'text-embedding-3-large',
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}),
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};
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} catch (err) {
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console.log(`Error loading OpenAI models: ${err}`);
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}
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}
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if (ollamaEndpoint) {
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try {
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const response = await fetch(`${ollamaEndpoint}/api/tags`);
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const { models: ollamaModels } = (await response.json()) as any;
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models['ollama'] = ollamaModels.reduce((acc, model) => {
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acc[model.model] = new ChatOllama({
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baseUrl: ollamaEndpoint,
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model: model.model,
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temperature: 0.7,
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});
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return acc;
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}, {});
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if (Object.keys(models['ollama']).length > 0) {
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models['ollama']['embeddings'] = new OllamaEmbeddings({
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baseUrl: ollamaEndpoint,
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model: models['ollama'][Object.keys(models['ollama'])[0]].model,
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});
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}
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} catch (err) {
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console.log(`Error loading Ollama models: ${err}`);
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}
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}
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return models;
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};
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