// --- Patch fetch in the worker to delegate to main thread with streaming support --- let fetchCounter = 0; self.fetch = (...args) => { const requestId = 'fetch_' + (++fetchCounter); postMessage({ type: 'proxy-fetch', requestId, args }); return new Promise((resolve) => { if (!self._fetchResolvers) self._fetchResolvers = {}; self._fetchResolvers[requestId] = resolve; }); }; onmessage = (e) => { if (e.data.type === 'proxy-fetch-response') { const { requestId, response } = e.data; const resolve = self._fetchResolvers?.[requestId]; if (resolve) { const stream = new ReadableStream({ start(controller) { controller.enqueue(new TextEncoder().encode(response.body)); controller.close(); } }); const fakeResponse = { ok: response.ok, status: response.status, statusText: response.statusText, headers: { get: (name) => response.headers[name.toLowerCase()] || null }, body: stream, text: async () => response.body, json: async () => JSON.parse(response.body) }; resolve(fakeResponse); delete self._fetchResolvers[requestId]; } } }; // --- End patch --- /* * ThunderAI [https://micz.it/thunderbird-addon-thunderai/] * Copyright (C) 2024 - 2025 Mic (m@micz.it) * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * You should have received a copy of the GNU General Public License * along with this program. If not, see . * * * This file contains a modified version of the code from the project at https://github.com/boxabirds/chatgpt-frontend-nobuild * The original code has been released under the Apache License, Version 2.0. */ import { OpenAIComp } from '../api/openai_comp.js'; import { taLogger } from '../mzta-logger.js'; let openai_comp_host = null; let openai_comp_model = ''; let openai_comp_api_key = ''; let openai_comp_use_v1 = true; let openai_comp = null; let stopStreaming = false; let i18nStrings = null; let do_debug = false; let taLog = null; let conversationHistory = []; let assistantResponseAccumulator = ''; self.onmessage = async function(event) { if (event.data.type === 'init') { openai_comp_host = event.data.openai_comp_host; openai_comp_model = event.data.openai_comp_model; openai_comp_api_key = event.data.openai_comp_api_key; openai_comp_use_v1 = event.data.openai_comp_use_v1; openai_comp = new OpenAIComp(openai_comp_host, openai_comp_model, openai_comp_api_key, true, openai_comp_use_v1); do_debug = event.data.do_debug; i18nStrings = event.data.i18nStrings; taLog = new taLogger('model-worker-openai_comp', do_debug); } else if (event.data.type === 'chatMessage') { conversationHistory.push({ role: 'user', content: event.data.message }); const response = await openai_comp.fetchResponse(conversationHistory); //4096); postMessage({ type: 'messageSent' }); if (!response.ok) { let error_message = ''; let errorDetail = ''; if(response.is_exception === true){ error_message = response.error; }else{ try{ const errorJSON = await response.json(); errorDetail = JSON.stringify(errorJSON); error_message = errorJSON.error.message; }catch(e){ error_message = response.statusText; } taLog.log("error_message: " + JSON.stringify(error_message)); } postMessage({ type: 'error', payload: i18nStrings["OpenAIComp_api_request_failed"] + ": " + response.status + " " + response.statusText + ", Detail: " + error_message + " " + errorDetail }); throw new Error("[ThunderAI] OpenAI Comp API request failed: " + response.status + " " + response.statusText + ", Detail: " + error_message + " " + errorDetail); } const reader = response.body.getReader(); const decoder = new TextDecoder("utf-8"); let buffer = ''; while (true) { if (stopStreaming) { stopStreaming = false; reader.cancel(); conversationHistory.push({ role: 'assistant', content: assistantResponseAccumulator }); assistantResponseAccumulator = ''; postMessage({ type: 'tokensDone' }); break; } const { done, value } = await reader.read(); if (done) { conversationHistory.push({ role: 'assistant', content: assistantResponseAccumulator }); assistantResponseAccumulator = ''; postMessage({ type: 'tokensDone' }); break; } // lots of low-level OpenAI response parsing stuff const chunk = decoder.decode(value); buffer += chunk; taLog.log("buffer: " + buffer); const lines = buffer.split("\n"); buffer = lines.pop(); let parsedLines = []; try{ parsedLines = lines .map((line) => line.replace(/^data: /, "").trim()) // Remove the "data: " prefix .filter((line) => line !== "" && line !== "[DONE]") // Remove empty lines and "[DONE]" // .map((line) => JSON.parse(line)); // Parse the JSON string .map((line) => { taLog.log("line: " + JSON.stringify(line)); return JSON.parse(line); }); }catch(e){ taLog.error("Error parsing lines: " + e); } for (const parsedLine of parsedLines) { const { choices } = parsedLine; const { delta } = choices[0]; const { content } = delta; // Update the UI with the new content if (content) { assistantResponseAccumulator += content; postMessage({ type: 'newToken', payload: { token: content } }); } } } } else if (event.data.type === 'stop') { stopStreaming = true; } };