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75 lines
2.3 KiB
TypeScript
75 lines
2.3 KiB
TypeScript
import axios from 'axios';
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import options from "../../services/options.js";
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import log from "../../services/log.js";
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import type { Request, Response } from "express";
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/**
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* List available models from OpenAI
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*/
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async function listModels(req: Request, res: Response) {
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try {
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const { baseUrl } = req.body;
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// Use provided base URL or default from options
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const openaiBaseUrl = baseUrl || await options.getOption('openaiBaseUrl') || 'https://api.openai.com/v1';
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const apiKey = await options.getOption('openaiApiKey');
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if (!apiKey) {
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throw new Error('OpenAI API key is not configured');
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}
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// Call OpenAI API to get models
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const response = await axios.get(`${openaiBaseUrl}/models`, {
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headers: {
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${apiKey}`
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},
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timeout: 10000
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});
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// Filter and categorize models
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const allModels = response.data.data || [];
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// Separate models into chat models and embedding models
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const chatModels = allModels
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.filter((model: any) =>
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// Include GPT models for chat
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model.id.includes('gpt') ||
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// Include Claude models via Azure OpenAI
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model.id.includes('claude')
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)
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.map((model: any) => ({
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id: model.id,
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name: model.id,
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type: 'chat'
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}));
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const embeddingModels = allModels
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.filter((model: any) =>
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// Only include embedding-specific models
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model.id.includes('embedding') ||
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model.id.includes('embed')
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)
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.map((model: any) => ({
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id: model.id,
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name: model.id,
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type: 'embedding'
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}));
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// Return the models list
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return {
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success: true,
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chatModels,
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embeddingModels
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};
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} catch (error: any) {
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log.error(`Error listing OpenAI models: ${error.message || 'Unknown error'}`);
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// Properly throw the error to be handled by the global error handler
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throw new Error(`Failed to list OpenAI models: ${error.message || 'Unknown error'}`);
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}
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}
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export default {
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listModels
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}; |