mirror of
https://github.com/TriliumNext/Notes.git
synced 2025-07-27 10:02:59 +08:00
rip out openai custom implementation in favor of sdk
This commit is contained in:
parent
f71351db6a
commit
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46
package-lock.json
generated
46
package-lock.json
generated
@ -69,6 +69,7 @@
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"normalize-strings": "1.1.1",
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"normalize.css": "8.0.1",
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"ollama": "0.5.14",
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"openai": "4.93.0",
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"rand-token": "1.0.1",
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"safe-compare": "1.1.4",
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"sanitize-filename": "1.6.3",
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@ -16035,6 +16036,51 @@
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"dev": true,
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"license": "MIT"
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},
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"node_modules/openai": {
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"version": "4.93.0",
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"resolved": "https://registry.npmjs.org/openai/-/openai-4.93.0.tgz",
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"integrity": "sha512-2kONcISbThKLfm7T9paVzg+QCE1FOZtNMMUfXyXckUAoXRRS/mTP89JSDHPMp8uM5s0bz28RISbvQjArD6mgUQ==",
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"license": "Apache-2.0",
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"dependencies": {
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"@types/node": "^18.11.18",
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"@types/node-fetch": "^2.6.4",
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"abort-controller": "^3.0.0",
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"agentkeepalive": "^4.2.1",
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"form-data-encoder": "1.7.2",
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"formdata-node": "^4.3.2",
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"node-fetch": "^2.6.7"
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},
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"bin": {
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"openai": "bin/cli"
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},
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"peerDependencies": {
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"ws": "^8.18.0",
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"zod": "^3.23.8"
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},
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"peerDependenciesMeta": {
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"ws": {
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"optional": true
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},
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"zod": {
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"optional": true
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}
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}
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},
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"node_modules/openai/node_modules/@types/node": {
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"version": "18.19.86",
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"resolved": "https://registry.npmjs.org/@types/node/-/node-18.19.86.tgz",
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"integrity": "sha512-fifKayi175wLyKyc5qUfyENhQ1dCNI1UNjp653d8kuYcPQN5JhX3dGuP/XmvPTg/xRBn1VTLpbmi+H/Mr7tLfQ==",
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"license": "MIT",
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"dependencies": {
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"undici-types": "~5.26.4"
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}
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},
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"node_modules/openai/node_modules/undici-types": {
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"version": "5.26.5",
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"resolved": "https://registry.npmjs.org/undici-types/-/undici-types-5.26.5.tgz",
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"integrity": "sha512-JlCMO+ehdEIKqlFxk6IfVoAUVmgz7cU7zD/h9XZ0qzeosSHmUJVOzSQvvYSYWXkFXC+IfLKSIffhv0sVZup6pA==",
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"license": "MIT"
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},
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"node_modules/openapi-types": {
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"version": "12.1.3",
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"resolved": "https://registry.npmjs.org/openapi-types/-/openapi-types-12.1.3.tgz",
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@ -131,6 +131,7 @@
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"normalize-strings": "1.1.1",
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"normalize.css": "8.0.1",
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"ollama": "0.5.14",
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"openai": "4.93.0",
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"rand-token": "1.0.1",
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"safe-compare": "1.1.4",
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"sanitize-filename": "1.6.3",
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@ -1,7 +1,7 @@
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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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import OpenAI from "openai";
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/**
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* @swagger
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@ -69,39 +69,39 @@ async function listModels(req: Request, res: Response) {
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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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// Initialize OpenAI client with the API key and base URL
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const openai = new OpenAI({
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apiKey,
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baseURL: openaiBaseUrl
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});
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// Call OpenAI API to get models using the SDK
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const response = await openai.models.list();
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// Filter and categorize models
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const allModels = response.data.data || [];
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const allModels = response.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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.filter((model) =>
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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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.map((model) => ({
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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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.filter((model) =>
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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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.map((model) => ({
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id: model.id,
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name: model.id,
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type: 'embedding'
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@ -4,15 +4,30 @@ import type { EmbeddingConfig } from "../embeddings_interface.js";
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import { NormalizationStatus } from "../embeddings_interface.js";
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import { LLM_CONSTANTS } from "../../constants/provider_constants.js";
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import type { EmbeddingModelInfo } from "../../interfaces/embedding_interfaces.js";
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import OpenAI from "openai";
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/**
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* OpenAI embedding provider implementation
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* OpenAI embedding provider implementation using the official SDK
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*/
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export class OpenAIEmbeddingProvider extends BaseEmbeddingProvider {
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name = "openai";
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private client: OpenAI | null = null;
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constructor(config: EmbeddingConfig) {
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super(config);
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this.initClient();
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}
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/**
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* Initialize the OpenAI client
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*/
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private initClient() {
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if (this.apiKey) {
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this.client = new OpenAI({
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apiKey: this.apiKey,
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baseURL: this.baseUrl
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});
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}
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}
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/**
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@ -21,6 +36,11 @@ export class OpenAIEmbeddingProvider extends BaseEmbeddingProvider {
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async initialize(): Promise<void> {
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const modelName = this.config.model || "text-embedding-3-small";
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try {
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// Initialize client if needed
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if (!this.client && this.apiKey) {
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this.initClient();
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}
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// Detect model capabilities
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const modelInfo = await this.getModelInfo(modelName);
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@ -37,46 +57,35 @@ export class OpenAIEmbeddingProvider extends BaseEmbeddingProvider {
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* Fetch model information from the OpenAI API
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*/
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private async fetchModelCapabilities(modelName: string): Promise<EmbeddingModelInfo | null> {
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if (!this.apiKey) {
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if (!this.client) {
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return null;
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}
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try {
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// First try to get model details from the models API
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const response = await fetch(`${this.baseUrl}/models/${modelName}`, {
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method: 'GET',
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headers: {
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"Authorization": `Bearer ${this.apiKey}`,
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"Content-Type": "application/json"
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},
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signal: AbortSignal.timeout(10000)
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});
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if (!response.ok) {
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throw new Error(`HTTP error! status: ${response.status}`);
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}
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// Get model details using the SDK
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const model = await this.client.models.retrieve(modelName);
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const data = await response.json();
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if (data) {
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if (model) {
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// Different model families may have different ways of exposing context window
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let contextWindow = 0;
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let dimension = 0;
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// Extract context window if available
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if (data.context_window) {
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contextWindow = data.context_window;
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} else if (data.limits && data.limits.context_window) {
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contextWindow = data.limits.context_window;
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} else if (data.limits && data.limits.context_length) {
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contextWindow = data.limits.context_length;
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// Extract context window if available from the response
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const modelData = model as any;
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if (modelData.context_window) {
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contextWindow = modelData.context_window;
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} else if (modelData.limits && modelData.limits.context_window) {
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contextWindow = modelData.limits.context_window;
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} else if (modelData.limits && modelData.limits.context_length) {
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contextWindow = modelData.limits.context_length;
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}
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// Extract embedding dimensions if available
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if (data.dimensions) {
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dimension = data.dimensions;
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} else if (data.embedding_dimension) {
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dimension = data.embedding_dimension;
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if (modelData.dimensions) {
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dimension = modelData.dimensions;
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} else if (modelData.embedding_dimension) {
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dimension = modelData.embedding_dimension;
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}
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// If we didn't get all the info, use defaults for missing values
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@ -188,27 +197,21 @@ export class OpenAIEmbeddingProvider extends BaseEmbeddingProvider {
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return new Float32Array(this.config.dimension);
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}
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const response = await fetch(`${this.baseUrl}/embeddings`, {
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method: 'POST',
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headers: {
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"Content-Type": "application/json",
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"Authorization": `Bearer ${this.apiKey}`
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},
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body: JSON.stringify({
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input: text,
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model: this.config.model || "text-embedding-3-small",
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encoding_format: "float"
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})
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});
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if (!response.ok) {
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throw new Error(`HTTP error! status: ${response.status}`);
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if (!this.client) {
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this.initClient();
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if (!this.client) {
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throw new Error("OpenAI client initialization failed");
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}
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}
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const response = await this.client.embeddings.create({
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model: this.config.model || "text-embedding-3-small",
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input: text,
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encoding_format: "float"
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});
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const data = await response.json();
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if (data && data.data && data.data[0] && data.data[0].embedding) {
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return new Float32Array(data.data[0].embedding);
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if (response && response.data && response.data[0] && response.data[0].embedding) {
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return new Float32Array(response.data[0].embedding);
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} else {
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throw new Error("Unexpected response structure from OpenAI API");
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}
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@ -243,30 +246,24 @@ export class OpenAIEmbeddingProvider extends BaseEmbeddingProvider {
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return [];
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}
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const response = await fetch(`${this.baseUrl}/embeddings`, {
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method: 'POST',
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headers: {
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"Content-Type": "application/json",
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"Authorization": `Bearer ${this.apiKey}`
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},
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body: JSON.stringify({
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input: texts,
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model: this.config.model || "text-embedding-3-small",
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encoding_format: "float"
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})
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});
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if (!response.ok) {
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throw new Error(`HTTP error! status: ${response.status}`);
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if (!this.client) {
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this.initClient();
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if (!this.client) {
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throw new Error("OpenAI client initialization failed");
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}
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}
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const response = await this.client.embeddings.create({
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model: this.config.model || "text-embedding-3-small",
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input: texts,
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encoding_format: "float"
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});
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const data = await response.json();
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if (data && data.data) {
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if (response && response.data) {
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// Sort the embeddings by index to ensure they match the input order
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const sortedEmbeddings = data.data
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.sort((a: any, b: any) => a.index - b.index)
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.map((item: any) => new Float32Array(item.embedding));
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const sortedEmbeddings = response.data
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.sort((a, b) => a.index - b.index)
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.map(item => new Float32Array(item.embedding));
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return sortedEmbeddings;
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} else {
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@ -1,7 +1,6 @@
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import type { Message } from "../ai_interface.js";
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// These imports need to be added for the factory to work
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import { OpenAIMessageFormatter } from "../formatters/openai_formatter.js";
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import { AnthropicMessageFormatter } from "../formatters/anthropic_formatter.js";
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import { OllamaMessageFormatter } from "../formatters/ollama_formatter.js";
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/**
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@ -76,7 +75,8 @@ export class MessageFormatterFactory {
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this.formatters[providerKey] = new OpenAIMessageFormatter();
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break;
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case 'anthropic':
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this.formatters[providerKey] = new AnthropicMessageFormatter();
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console.warn('Anthropic formatter not available, using OpenAI formatter as fallback');
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this.formatters[providerKey] = new OpenAIMessageFormatter();
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break;
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case 'ollama':
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this.formatters[providerKey] = new OllamaMessageFormatter();
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|
@ -1,11 +1,12 @@
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import options from '../../options.js';
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import { BaseAIService } from '../base_ai_service.js';
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import type { ChatCompletionOptions, ChatResponse, Message } from '../ai_interface.js';
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import { PROVIDER_CONSTANTS } from '../constants/provider_constants.js';
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import type { OpenAIOptions } from './provider_options.js';
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import { getOpenAIOptions } from './providers.js';
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import OpenAI from 'openai';
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export class OpenAIService extends BaseAIService {
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private openai: OpenAI | null = null;
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constructor() {
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super('OpenAI');
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}
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@ -14,6 +15,16 @@ export class OpenAIService extends BaseAIService {
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return super.isAvailable() && !!options.getOption('openaiApiKey');
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}
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private getClient(apiKey: string, baseUrl?: string): OpenAI {
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if (!this.openai) {
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this.openai = new OpenAI({
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apiKey,
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baseURL: baseUrl
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});
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}
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return this.openai;
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}
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async generateChatCompletion(messages: Message[], opts: ChatCompletionOptions = {}): Promise<ChatResponse> {
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if (!this.isAvailable()) {
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throw new Error('OpenAI service is not available. Check API key and AI settings.');
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@ -21,6 +32,9 @@ export class OpenAIService extends BaseAIService {
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// Get provider-specific options from the central provider manager
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const providerOptions = getOpenAIOptions(opts);
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// Initialize the OpenAI client
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const client = this.getClient(providerOptions.apiKey, providerOptions.baseUrl);
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const systemPrompt = this.getSystemPrompt(providerOptions.systemPrompt || options.getOption('aiSystemPrompt'));
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@ -31,20 +45,10 @@ export class OpenAIService extends BaseAIService {
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: [{ role: 'system', content: systemPrompt }, ...messages];
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try {
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// Fix endpoint construction - ensure we don't double up on /v1
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const normalizedBaseUrl = providerOptions.baseUrl.replace(/\/+$/, '');
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const endpoint = normalizedBaseUrl.includes('/v1')
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? `${normalizedBaseUrl}/chat/completions`
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: `${normalizedBaseUrl}/v1/chat/completions`;
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// Create request body directly from provider options
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const requestBody: any = {
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// Create params object for the OpenAI SDK
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const params: OpenAI.Chat.ChatCompletionCreateParams = {
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model: providerOptions.model,
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messages: messagesWithSystem,
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};
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// Extract API parameters from provider options
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const apiParams = {
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messages: messagesWithSystem as OpenAI.Chat.ChatCompletionMessageParam[],
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temperature: providerOptions.temperature,
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max_tokens: providerOptions.max_tokens,
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stream: providerOptions.stream,
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@ -53,51 +57,138 @@ export class OpenAIService extends BaseAIService {
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presence_penalty: providerOptions.presence_penalty
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};
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|
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// Merge API parameters, filtering out undefined values
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Object.entries(apiParams).forEach(([key, value]) => {
|
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if (value !== undefined) {
|
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requestBody[key] = value;
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||||
}
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});
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|
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// Add tools if enabled
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if (providerOptions.enableTools && providerOptions.tools && providerOptions.tools.length > 0) {
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requestBody.tools = providerOptions.tools;
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params.tools = providerOptions.tools as OpenAI.Chat.ChatCompletionTool[];
|
||||
}
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if (providerOptions.tool_choice) {
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requestBody.tool_choice = providerOptions.tool_choice;
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params.tool_choice = providerOptions.tool_choice as OpenAI.Chat.ChatCompletionToolChoiceOption;
|
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}
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|
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const response = await fetch(endpoint, {
|
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method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
'Authorization': `Bearer ${providerOptions.apiKey}`
|
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},
|
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body: JSON.stringify(requestBody)
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});
|
||||
// If streaming is requested
|
||||
if (providerOptions.stream) {
|
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params.stream = true;
|
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|
||||
const stream = await client.chat.completions.create(params);
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||||
let fullText = '';
|
||||
|
||||
// If a direct callback is provided, use it
|
||||
if (providerOptions.streamCallback) {
|
||||
// Process the stream with the callback
|
||||
try {
|
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// The stream is an AsyncIterable
|
||||
if (Symbol.asyncIterator in stream) {
|
||||
for await (const chunk of stream as AsyncIterable<OpenAI.Chat.ChatCompletionChunk>) {
|
||||
const content = chunk.choices[0]?.delta?.content || '';
|
||||
if (content) {
|
||||
fullText += content;
|
||||
await providerOptions.streamCallback(content, false, chunk);
|
||||
}
|
||||
|
||||
// If this is the last chunk
|
||||
if (chunk.choices[0]?.finish_reason) {
|
||||
await providerOptions.streamCallback('', true, chunk);
|
||||
}
|
||||
}
|
||||
} else {
|
||||
console.error('Stream is not iterable, falling back to non-streaming response');
|
||||
|
||||
// If we get a non-streaming response somehow
|
||||
if ('choices' in stream) {
|
||||
const content = stream.choices[0]?.message?.content || '';
|
||||
fullText = content;
|
||||
if (providerOptions.streamCallback) {
|
||||
await providerOptions.streamCallback(content, true, stream);
|
||||
}
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error processing stream:', error);
|
||||
throw error;
|
||||
}
|
||||
|
||||
return {
|
||||
text: fullText,
|
||||
model: params.model,
|
||||
provider: this.getName(),
|
||||
usage: {} // Usage stats aren't available with streaming
|
||||
};
|
||||
} else {
|
||||
// Use the more flexible stream interface
|
||||
return {
|
||||
text: '', // Initial empty text, will be filled by stream processing
|
||||
model: params.model,
|
||||
provider: this.getName(),
|
||||
usage: {}, // Usage stats aren't available with streaming
|
||||
stream: async (callback) => {
|
||||
let completeText = '';
|
||||
|
||||
try {
|
||||
// The stream is an AsyncIterable
|
||||
if (Symbol.asyncIterator in stream) {
|
||||
for await (const chunk of stream as AsyncIterable<OpenAI.Chat.ChatCompletionChunk>) {
|
||||
const content = chunk.choices[0]?.delta?.content || '';
|
||||
const isDone = !!chunk.choices[0]?.finish_reason;
|
||||
|
||||
if (content) {
|
||||
completeText += content;
|
||||
}
|
||||
|
||||
// Call the provided callback with the StreamChunk interface
|
||||
await callback({
|
||||
text: content,
|
||||
done: isDone
|
||||
});
|
||||
|
||||
if (isDone) {
|
||||
break;
|
||||
}
|
||||
}
|
||||
} else {
|
||||
console.warn('Stream is not iterable, falling back to non-streaming response');
|
||||
|
||||
// If we get a non-streaming response somehow
|
||||
if ('choices' in stream) {
|
||||
const content = stream.choices[0]?.message?.content || '';
|
||||
completeText = content;
|
||||
await callback({
|
||||
text: content,
|
||||
done: true
|
||||
});
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error processing stream:', error);
|
||||
throw error;
|
||||
}
|
||||
|
||||
return completeText;
|
||||
}
|
||||
};
|
||||
}
|
||||
} else {
|
||||
// Non-streaming response
|
||||
params.stream = false;
|
||||
|
||||
const completion = await client.chat.completions.create(params);
|
||||
|
||||
if (!('choices' in completion)) {
|
||||
throw new Error('Unexpected response format from OpenAI API');
|
||||
}
|
||||
|
||||
if (!response.ok) {
|
||||
const errorBody = await response.text();
|
||||
throw new Error(`OpenAI API error: ${response.status} ${response.statusText} - ${errorBody}`);
|
||||
return {
|
||||
text: completion.choices[0].message.content || '',
|
||||
model: completion.model,
|
||||
provider: this.getName(),
|
||||
usage: {
|
||||
promptTokens: completion.usage?.prompt_tokens,
|
||||
completionTokens: completion.usage?.completion_tokens,
|
||||
totalTokens: completion.usage?.total_tokens
|
||||
},
|
||||
tool_calls: completion.choices[0].message.tool_calls
|
||||
};
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
|
||||
return {
|
||||
text: data.choices[0].message.content,
|
||||
model: data.model,
|
||||
provider: this.getName(),
|
||||
usage: {
|
||||
promptTokens: data.usage?.prompt_tokens,
|
||||
completionTokens: data.usage?.completion_tokens,
|
||||
totalTokens: data.usage?.total_tokens
|
||||
},
|
||||
tool_calls: data.choices[0].message.tool_calls
|
||||
};
|
||||
} catch (error) {
|
||||
console.error('OpenAI service error:', error);
|
||||
throw error;
|
||||
|
@ -53,6 +53,8 @@ export interface OpenAIOptions extends ProviderConfig {
|
||||
|
||||
// Internal control flags (not sent directly to API)
|
||||
enableTools?: boolean;
|
||||
// Streaming callback handler
|
||||
streamCallback?: (text: string, isDone: boolean, originalChunk?: any) => Promise<void> | void;
|
||||
}
|
||||
|
||||
/**
|
||||
@ -76,6 +78,8 @@ export interface AnthropicOptions extends ProviderConfig {
|
||||
|
||||
// Internal parameters (not sent directly to API)
|
||||
formattedMessages?: { messages: any[], system: string };
|
||||
// Streaming callback handler
|
||||
streamCallback?: (text: string, isDone: boolean, originalChunk?: any) => Promise<void> | void;
|
||||
}
|
||||
|
||||
/**
|
||||
@ -105,6 +109,8 @@ export interface OllamaOptions extends ProviderConfig {
|
||||
preserveSystemPrompt?: boolean;
|
||||
expectsJsonResponse?: boolean;
|
||||
toolExecutionStatus?: any[];
|
||||
// Streaming callback handler
|
||||
streamCallback?: (text: string, isDone: boolean, originalChunk?: any) => Promise<void> | void;
|
||||
}
|
||||
|
||||
/**
|
||||
@ -134,6 +140,10 @@ export function createOpenAIOptions(
|
||||
// Internal configuration
|
||||
systemPrompt: opts.systemPrompt,
|
||||
enableTools: opts.enableTools,
|
||||
// Pass through streaming callback
|
||||
streamCallback: opts.streamCallback,
|
||||
// Include provider metadata
|
||||
providerMetadata: opts.providerMetadata,
|
||||
};
|
||||
}
|
||||
|
||||
@ -164,6 +174,10 @@ export function createAnthropicOptions(
|
||||
|
||||
// Internal configuration
|
||||
systemPrompt: opts.systemPrompt,
|
||||
// Pass through streaming callback
|
||||
streamCallback: opts.streamCallback,
|
||||
// Include provider metadata
|
||||
providerMetadata: opts.providerMetadata,
|
||||
};
|
||||
}
|
||||
|
||||
@ -198,5 +212,9 @@ export function createOllamaOptions(
|
||||
preserveSystemPrompt: opts.preserveSystemPrompt,
|
||||
expectsJsonResponse: opts.expectsJsonResponse,
|
||||
toolExecutionStatus: opts.toolExecutionStatus,
|
||||
// Pass through streaming callback
|
||||
streamCallback: opts.streamCallback,
|
||||
// Include provider metadata
|
||||
providerMetadata: opts.providerMetadata,
|
||||
};
|
||||
}
|
||||
|
Loading…
x
Reference in New Issue
Block a user