fix: canvas image/video download - fix data URL parsing in cvDownloadPreview (v1.5.21, hot 1.5.23)

2026-07-20 08:48:56 +08:00
parent 42e23663ee
commit aadd2b04ae
28 changed files with 5881 additions and 329 deletions
@@ -0,0 +1,162 @@
+// prompt-analysis.js —— 图片反推生图提示词（移植自「提示词提取」项目）
+// LLM 通道走本应用的 router 分组（直接读中转分组列表），与 team.js 同模式。
+"use strict";
+const router = require("./router");
+const { SYSTEM_PROMPT, USER_INSTRUCTION } = require("./team-prompt");
+
+// ============================================================================
+//  以下 <CORE> 自 提示词提取/server.js 原样提取（extractJson / callChat），未改动逻辑。
+// ============================================================================
+
+function extractJson(text) {
+  if (!text) throw new Error('模型返回为空');
+  let t = text.trim();
+  const fence = t.match(/```(?:json)?\s*([\s\S]*?)```/i);
+  if (fence) t = fence[1].trim();
+  const start = t.indexOf('{');
+  const end = t.lastIndexOf('}');
+  if (start !== -1 && end !== -1 && end > start) t = t.slice(start, end + 1);
+
+  const tryParse = (s) => { try { return JSON.parse(s); } catch (_) { return undefined; } };
+  let r = tryParse(t);
+  if (r !== undefined) return r;
+  r = tryParse(t.replace(/,\s*([}\]])/g, '$1'));
+  if (r !== undefined) return r;
+  throw new Error('模型输出的 JSON 格式有误，请重试');
+}
+
+// 流式调用：空闲超时——120 秒收不到任何数据就判定挂起并中止
+const CHAT_IDLE_MS = 120000;
+function chatTimeoutError() {
+  return Object.assign(new Error('模型长时间无响应（可能渠道不稳或模型太慢），请重试或换个更快的模型'), { status: 504 });
+}
+async function callChat(gwBase, apiKey, model, messages, maxTokens) {
+  const ctrl = new AbortController();
+  let idle;
+  const resetIdle = () => { clearTimeout(idle); idle = setTimeout(() => ctrl.abort(), CHAT_IDLE_MS); };
+  resetIdle();
+
+  let upstream;
+  try {
+    upstream = await fetch(`${gwBase}/chat/completions`, {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json', Authorization: `Bearer ${apiKey}` },
+      body: JSON.stringify({ model, temperature: 0.4, max_tokens: maxTokens, messages, stream: true }),
+      signal: ctrl.signal,
+    });
+  } catch (e) {
+    clearTimeout(idle);
+    if (e.name === 'AbortError') throw chatTimeoutError();
+    throw e;
+  }
+  if (!upstream.ok) {
+    clearTimeout(idle);
+    const detail = await upstream.text().catch(() => '');
+    const err = new Error(`上游模型调用失败 (${upstream.status})`);
+    err.status = upstream.status === 401 ? 401 : 502;
+    err.detail = detail.slice(0, 300);
+    throw err;
+  }
+
+  const reader = upstream.body.getReader();
+  const decoder = new TextDecoder();
+  let buf = '';
+  let content = '';
+  try {
+    while (true) {
+      const { done, value } = await reader.read();
+      if (done) break;
+      resetIdle();
+      buf += decoder.decode(value, { stream: true });
+      let nl;
+      while ((nl = buf.indexOf('\n')) >= 0) {
+        const line = buf.slice(0, nl).trim();
+        buf = buf.slice(nl + 1);
+        if (!line.startsWith('data:')) continue;
+        const data = line.slice(5).trim();
+        if (!data || data === '[DONE]') continue;
+        try {
+          const j = JSON.parse(data);
+          const delta = j.choices?.[0]?.delta;
+          if (delta?.content) content += delta.content;
+          else if (j.choices?.[0]?.message?.content) content += j.choices[0].message.content;
+        } catch (_) { /* 跳过 keep-alive / 非 JSON 行 */ }
+      }
+    }
+  } catch (e) {
+    if (e.name === 'AbortError') throw chatTimeoutError();
+    throw e;
+  } finally {
+    clearTimeout(idle);
+  }
+  if (!content) throw new Error('模型未返回内容（可能超时或渠道异常）');
+  return content;
+}
+
+// ============================================================================
+//  适配层：LLM 走 router 分组
+// ============================================================================
+
+// 把分组 baseUrl 归一成「+ /chat/completions 即正确」的基址（对齐 team.js）
+function chatBase(baseUrl) {
+  const base = String(baseUrl || "").replace(/\/+$/, "");
+  if (/\/chat\/completions$/.test(base)) return base.replace(/\/chat\/completions$/, "");
+  if (/\/v\d+$/.test(base)) return base;
+  return base + "/v1";
+}
+
+// 取分组：优先按 id，否则用默认 LLM 分组
+function resolveGroup(groupId) {
+  let g = null;
+  if (groupId != null && groupId !== "" && typeof router.groupById === "function") {
+    g = router.groupById(groupId);
+  }
+  if (!g && typeof router.llmGroup === "function") g = router.llmGroup();
+  if (!g) throw new Error("没有可用的中转分组，请先在「路由」里配置好带 baseUrl 和密钥的分组");
+  if (!g.baseUrl || !g.key) throw new Error(`分组「${g.name || g.id}」缺少 baseUrl 或密钥`);
+  return g;
+}
+
+// 获取所有可用分组列表（给前端下拉用）
+function listGroups() {
+  try {
+    return router.usableGroups().map((g) => ({
+      id: g.id,
+      name: g.name || g.id,
+      host: (() => { try { return new (require("url").URL)(g.baseUrl).host; } catch (_) { return ""; } })(),
+      mode: g.mode || "chat",
+    }));
+  } catch (_) {
+    return [];
+  }
+}
+
+// 拉取指定分组的模型列表
+async function listModels(groupId) {
+  const g = resolveGroup(groupId);
+  const models = await router.fetchModels(g.baseUrl, g.key);
+  return models;
+}
+
+// 核心：图片 → 提示词分析
+async function analyze({ image, model, groupId } = {}) {
+  if (!image || typeof image !== "string") throw new Error("缺少图片数据");
+  if (!model) throw new Error("未选择模型");
+  const g = resolveGroup(groupId);
+  const gwBase = chatBase(g.baseUrl);
+
+  const content = await callChat(gwBase, g.key, model, [
+    { role: "system", content: SYSTEM_PROMPT },
+    {
+      role: "user",
+      content: [
+        { type: "text", text: USER_INSTRUCTION },
+        { type: "image_url", image_url: { url: image } },
+      ],
+    },
+  ], 2000);
+
+  return { result: extractJson(content), model };
+}
+
+module.exports = { analyze, listGroups, listModels };