2cb2f0e4e8
- Added `vectordb` as a dependency in `package.json`. - Implemented `embedText` function in `src/main/ai/embeddings.ts` to handle text embeddings using GitHub Copilot OAuth token or OpenAI token. - Created `vectordb.ts` for managing LanceDB connection and embedding notes with upsert strategy. - Updated `index.ts` to initialize vector database and migrate existing notes on app ready. - Modified `router/index.ts` to fire-and-forget embedding calls on note creation and updates. - Enhanced `progress.txt` with detailed implementation notes and learnings regarding the integration.
74 lines
2.3 KiB
TypeScript
74 lines
2.3 KiB
TypeScript
import fs from 'node:fs';
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import os from 'node:os';
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import path from 'node:path';
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import { getToken } from './token';
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interface CopilotConfig {
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copilot_tokens?: Record<string, string>;
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}
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/**
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* Read the GitHub Copilot OAuth token from the CLI config file.
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* Stored at ~/.copilot/config.json under copilot_tokens["{host}:{login}"].
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* Returns the first available token, or null if unavailable.
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*/
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function readCopilotToken(): string | null {
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try {
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const raw = fs.readFileSync(
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path.join(os.homedir(), '.copilot', 'config.json'),
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'utf-8',
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);
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const cfg = JSON.parse(raw) as CopilotConfig;
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const vals = Object.values(cfg.copilot_tokens ?? {});
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return vals[0] ?? null;
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} catch {
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return null;
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}
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}
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/**
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* Embed a single text string using the best available credentials.
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*
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* Priority:
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* 1. GitHub Copilot CLI token → OpenAI-compatible embeddings endpoint at
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* https://api.githubcopilot.com
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* 2. Stored OpenAI token → standard OpenAI embeddings API
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*
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* Throws if no credentials are available or the API call fails.
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* Callers must .catch() this and handle the error without rejecting
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* the surrounding tRPC mutation.
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*/
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export async function embedText(text: string): Promise<number[]> {
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const { OpenAIEmbeddings } = await import('@langchain/openai');
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const copilotToken = readCopilotToken();
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let embeddingsInstance;
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if (copilotToken) {
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embeddingsInstance = new OpenAIEmbeddings({
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apiKey: copilotToken,
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model: 'text-embedding-3-small',
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configuration: { baseURL: 'https://api.githubcopilot.com' },
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});
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} else {
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const openaiToken = await getToken('openai');
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if (!openaiToken) {
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throw new Error(
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'[Embeddings] No credentials available. Authenticate with Copilot CLI or add an OpenAI token in Settings.',
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);
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}
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embeddingsInstance = new OpenAIEmbeddings({
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apiKey: openaiToken,
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model: 'text-embedding-3-small',
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});
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}
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// embedDocuments returns number[][] — cast explicitly to satisfy strict TS
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const results = (await embeddingsInstance.embedDocuments([text])) as number[][];
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const vector = results[0] as number[] | undefined;
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if (!vector || vector.length === 0) {
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throw new Error('[Embeddings] Empty vector returned from embedding API');
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}
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return vector;
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}
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