feat: 笔记独立窗口改为多标签，AI 多轮会话与 TXT/MD 阅读
笔记独立窗口从「一窗一条」改为单窗口多标签，与阅读器一致： 标签集在主进程侧为权威，notes:tabsChanged 只能收窄不能新增， 否则渲染层可以谎报持有某条笔记来越权读取。存活编辑器上限 3 并 LRU 回收，回收前序列化未保存内容。笔记没有自动保存，关标签与 关窗都做二次确认，取消关闭必须回报主进程复位 closePending， 否则窗口再也关不掉而看门狗仍会销毁未保存内容。 AI 助手支持多轮会话：会话独立落盘，先取历史再写提问， 历史只发文本不重发图像，失败与取消都保留已流出的残片。 新增 TXT/MD 内置阅读（转内存 EPUB 复用 epub 渲染管线）， 补上渲染层遗漏的可阅读格式白名单：主进程本就放行 txt/md， 但渲染层另有两份白名单漏了，表现为卡片上没有「阅读」按钮。 书库卡片封面改用 contain 完整显示，留白由同图模糊层垫底， 修正不同比例封面被裁切程度不一导致的观感不一致；多选复选框 去掉衬底色块，恢复原生外观。 其余：PDF 画质档位与画布尺寸钳制、原子写入、笔记资源托管、 GitHub Pages 站点。
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lofyer
+93
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@@ -10,8 +10,8 @@ const { fetchWithProxy } = require('../sources/http');
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const MAX_CHARS = 12000;
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const MAX_QUESTION_CHARS = 4000;
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// 上下文按字符数截断。中间挖空而不是尾部截断：
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// 结论性内容常在末尾，只留开头会让模型答非所问。
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// 中间挖空而不是尾部截断：结论性内容常在末尾，只留开头会让模型答非所问。
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// 正文默认不再走这里，只在有明确预算上限的场合（如多轮历史）显式调用。
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function clipContext(text, limit = MAX_CHARS) {
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const s = String(text || '');
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if (s.length <= limit) return s;
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@@ -42,7 +42,7 @@ const TASKS = {
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function buildPromptFromNormalized(task, text, question, visuals) {
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const t = TASKS[task];
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if (!t) throw new Error('不支持的任务类型: ' + task);
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let body = clipContext(text);
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let body = String(text || '');
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const ocr = visuals
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.filter((item) => item.ocr.include)
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.map((item) => item.ocr.text.trim())
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@@ -58,27 +58,60 @@ function buildPromptFromNormalized(task, text, question, visuals) {
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return { system, userText, images };
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}
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function buildMessagesFromNormalized(task, text, question, visuals) {
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// 历史轮只取 role 与 text，其余字段（尤其 images）一律忽略：
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// 视觉模型按图块计费，重发历史图会让长会话费用随轮数累积，用户无从预期。
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function normalizeHistory(history) {
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if (!Array.isArray(history)) return [];
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const items = [];
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for (const entry of history) {
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if (!entry) continue;
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const role = entry.role === 'assistant' ? 'assistant' : 'user';
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const text = String(entry.text || '').trim();
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if (!text) continue;
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const last = items[items.length - 1];
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// 相邻同角色合并而不是丢弃：Anthropic 会直接 400，但丢内容比合并更糟
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if (last && last.role === role) last.text = `${last.text}\n\n${text}`;
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else items.push({ role, text });
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}
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// Anthropic 的 /messages 要求首条必须是 user
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while (items.length && items[0].role === 'assistant') items.shift();
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return items;
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}
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// 当前轮固定是 user，历史末条若也是 user 就会相邻同角色，把它并入当前轮正文。
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function mergeHistory(history, currentText) {
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const items = normalizeHistory(history);
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const tail = items.length && items[items.length - 1].role === 'user' ? items.pop() : null;
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return {
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items,
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currentText: tail ? `${tail.text}\n\n${currentText}` : currentText
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};
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}
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function buildMessagesFromNormalized(task, text, question, visuals, history) {
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const { system, userText, images } = buildPromptFromNormalized(task, text, question, visuals);
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const merged = mergeHistory(history, userText);
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const userContent = images.length
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? [
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{ type: 'text', text: userText },
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{ type: 'text', text: merged.currentText },
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...images.map((item) => ({
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type: 'image_url',
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image_url: { url: imageDataUrl(item.image) }
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}))
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]
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: userText;
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: merged.currentText;
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return [
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{ role: 'system', content: system },
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...merged.items.map((item) => ({ role: item.role, content: item.text })),
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{ role: 'user', content: userContent }
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];
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}
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function buildAnthropicPayload(cfg, prompt) {
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function buildAnthropicPayload(cfg, prompt, history) {
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const merged = mergeHistory(history, prompt.userText);
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const content = prompt.images.length
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? [
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{ type: 'text', text: prompt.userText },
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{ type: 'text', text: merged.currentText },
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...prompt.images.map((item) => ({
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type: 'image',
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source: {
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@@ -88,20 +121,24 @@ function buildAnthropicPayload(cfg, prompt) {
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}
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}))
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]
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: prompt.userText;
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: merged.currentText;
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return {
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model: cfg.model,
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system: prompt.system,
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messages: [{ role: 'user', content }],
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messages: [
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...merged.items.map((item) => ({ role: item.role, content: item.text })),
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{ role: 'user', content }
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],
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temperature: cfg.temperature,
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max_tokens: cfg.maxTokens,
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stream: true
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};
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}
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function buildResponsesPayload(cfg, prompt) {
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function buildResponsesPayload(cfg, prompt, history) {
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const merged = mergeHistory(history, prompt.userText);
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const content = [
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{ type: 'input_text', text: prompt.userText },
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{ type: 'input_text', text: merged.currentText },
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...prompt.images.map((item) => ({
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type: 'input_image',
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image_url: imageDataUrl(item.image)
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@@ -110,7 +147,12 @@ function buildResponsesPayload(cfg, prompt) {
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return {
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model: cfg.model,
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instructions: prompt.system,
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input: [{ role: 'user', content }],
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input: [
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// 纯字符串是 Responses 输入消息的合法简写，同时绕开 input_text/output_text
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// 的角色约束：input_text 不接受 assistant，output_text 只出现在带 id 的输出项里。
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...merged.items.map((item) => ({ role: item.role, content: item.text })),
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{ role: 'user', content }
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],
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temperature: cfg.temperature,
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max_output_tokens: cfg.maxTokens,
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stream: true,
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@@ -118,8 +160,14 @@ function buildResponsesPayload(cfg, prompt) {
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};
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}
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function buildMessages(task, text, question, visualContexts) {
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return buildMessagesFromNormalized(task, text, question, normalizeVisualContexts(visualContexts));
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function buildMessages(task, text, question, visualContexts, history) {
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return buildMessagesFromNormalized(
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task,
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text,
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question,
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normalizeVisualContexts(visualContexts),
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history
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);
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}
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function endpointFor(baseUrl, protocol) {
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@@ -144,24 +192,42 @@ function headersFor(cfg) {
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return headers;
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}
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function payloadFor(cfg, task, text, question, visuals) {
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function payloadFor(cfg, task, text, question, visuals, history) {
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const prompt = buildPromptFromNormalized(task, text, question, visuals);
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if (cfg.protocol === 'anthropic') return buildAnthropicPayload(cfg, prompt);
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if (cfg.protocol === 'openai-responses') return buildResponsesPayload(cfg, prompt);
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if (cfg.protocol === 'anthropic') return buildAnthropicPayload(cfg, prompt, history);
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if (cfg.protocol === 'openai-responses') return buildResponsesPayload(cfg, prompt, history);
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return {
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model: cfg.model,
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messages: buildMessagesFromNormalized(task, text, question, visuals),
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messages: buildMessagesFromNormalized(task, text, question, visuals, history),
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temperature: cfg.temperature,
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max_tokens: cfg.maxTokens,
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stream: true
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};
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}
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// 正文不再由本地截断，超出模型窗口时只能由接口报错。各家措辞不同，
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// 统一识别成一句可操作的中文提示，否则用户只会看到一串英文而不知道该缩小范围。
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const CONTEXT_OVERFLOW_RE = /context[_\s-]?length|context window|maximum context|too many tokens|prompt is too long|reduce the length|input length|exceeds? the (?:maximum|context)/i;
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function isContextOverflow(message, status) {
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// 413 单看状态码就够：请求体过大只可能是上下文塞太多
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if (status === 413) return true;
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if (!CONTEXT_OVERFLOW_RE.test(String(message || ''))) return false;
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return status === undefined || status === 400 || status === 422;
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}
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function overflowHint(message) {
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return `上下文超出模型窗口，请把范围改小（如改用"当前页"或选中片段）或换用更大窗口的模型。接口原文：${message}`;
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}
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function parseErrorBody(text, status) {
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try {
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const j = JSON.parse(text);
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const msg = (j.error && (j.error.message || j.error)) || j.message;
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if (msg) return String(msg);
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if (msg) {
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const s = String(msg);
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return isContextOverflow(s, status) ? overflowHint(s) : s;
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}
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} catch (e) { /* 非 JSON */ }
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if (status === 401 || status === 403) return 'API Key 无效或没有权限';
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if (status === 404) return '接口地址或模型名称不存在';
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@@ -189,8 +255,8 @@ function streamFinished(protocol, event) {
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}
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// onDelta 每收到一段增量就回调一次；返回完整文本。
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// signal 用于用户中途取消。
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async function stream({ task, text, question, visualContexts, signal, onDelta }) {
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// signal 用于用户中途取消。history 是本轮之前的历史轮次，只消费 role 与 text。
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async function stream({ task, text, question, visualContexts, history, signal, onDelta }) {
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const cfg = aiConfig.get();
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const st = aiConfig.status();
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if (!cfg.apiKey && !st.isLocal) throw new Error('尚未配置 API Key，请先在设置中填写');
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@@ -203,7 +269,7 @@ async function stream({ task, text, question, visualContexts, signal, onDelta })
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const res = await fetchWithProxy(endpointFor(cfg.baseUrl, cfg.protocol), {
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method: 'POST',
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headers: headersFor(cfg),
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body: JSON.stringify(payloadFor(cfg, task, text, question, visuals)),
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body: JSON.stringify(payloadFor(cfg, task, text, question, visuals, history)),
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signal
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});
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@@ -231,11 +297,13 @@ async function stream({ task, text, question, visualContexts, signal, onDelta })
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// 部分服务端把错误放在流里返回
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if (j.error || j.type === 'error') {
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const error = j.error || j;
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throw new Error(error.message || String(error));
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const message = error.message || String(error);
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throw new Error(isContextOverflow(message) ? overflowHint(message) : message);
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}
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if (cfg.protocol === 'openai-responses' && ['response.failed', 'response.incomplete'].includes(j.type)) {
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const error = j.response && (j.response.error || j.response.incomplete_details);
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throw new Error((error && (error.message || error.reason)) || 'OpenAI Responses 请求未完成');
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const message = (error && (error.message || error.reason)) || 'OpenAI Responses 请求未完成';
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throw new Error(isContextOverflow(message) ? overflowHint(message) : message);
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}
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const piece = streamDelta(cfg.protocol, j);
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if (piece) {
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