Wire mic through Whisper-compatible transcriptions on LLM_BASE_URL. Photos upload to MinIO and reach the vision model as base64 image_url parts.
48 lines
1.4 KiB
TypeScript
48 lines
1.4 KiB
TypeScript
import { getLlmConfig } from "./config";
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const MAX_AUDIO_BYTES = 25 * 1024 * 1024;
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export async function transcribeAudioFile(file: File | Blob, filename: string): Promise<string> {
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if (file.size > MAX_AUDIO_BYTES) {
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throw new Error("Recording exceeds 25 MB limit");
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}
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const config = getLlmConfig();
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if (config.provider === "mock" || !config.baseUrl) {
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return "add milk to the shopping list";
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}
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const formData = new FormData();
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formData.append("file", file, filename);
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formData.append("model", "whisper-1");
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const url = `${config.baseUrl.replace(/\/$/, "")}/audio/transcriptions`;
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const headers: Record<string, string> = {};
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if (config.apiKey) {
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headers.Authorization = `Bearer ${config.apiKey}`;
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}
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const response = await fetch(url, {
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method: "POST",
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headers,
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body: formData,
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});
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if (!response.ok) {
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const detail = await response.text();
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throw new Error(`Transcription failed (${response.status}): ${detail.slice(0, 400)}`);
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}
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const contentType = response.headers.get("content-type") ?? "";
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if (contentType.includes("application/json")) {
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const payload = (await response.json()) as { text?: string };
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const text = payload.text?.trim();
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if (!text) throw new Error("Transcription returned empty text");
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return text;
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}
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const text = (await response.text()).trim();
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if (!text) throw new Error("Transcription returned empty text");
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return text;
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}
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