From 92c0e3c420c9c1c15584ffe7f66340897eb9701e Mon Sep 17 00:00:00 2001 From: foxhui Date: Tue, 16 Dec 2025 17:50:29 +0800 Subject: [PATCH] =?UTF-8?q?feat:=20=E5=88=9D=E6=AD=A5=E6=94=AF=E6=8C=81?= =?UTF-8?q?=E6=96=87=E6=9C=AC=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- scripts/verify_parsing.js | 90 +++++++ server.js | 8 +- src/backend/adapter/lmarena_text.js | 295 +++++++++++++++++++++ src/backend/index.js | 12 + src/backend/pool/PoolManager.js | 12 + src/backend/pool/Worker.js | 21 ++ src/backend/registry.js | 22 +- src/server/http/routes.js | 3 + src/server/parseChat.js | 177 +++++++++++-- src/server/queue.js | 3 + src/utils/config.js | 9 +- 升级.md | 395 ++++++++++++++++++++++++++++ 12 files changed, 1014 insertions(+), 33 deletions(-) create mode 100644 scripts/verify_parsing.js create mode 100644 src/backend/adapter/lmarena_text.js create mode 100644 升级.md diff --git a/scripts/verify_parsing.js b/scripts/verify_parsing.js new file mode 100644 index 0000000..6a56527 --- /dev/null +++ b/scripts/verify_parsing.js @@ -0,0 +1,90 @@ + +import { parseRequest } from '../src/server/parseChat.js'; + +// Mock options +const mockOptions = { + tempDir: './data/temp', + imageLimit: 5, + backendName: 'test-backend', + resolveModelId: (id) => id === 'gpt-4-text' ? 'resolved-gpt-4' : null, + getImagePolicy: () => 'optional', + getModelType: (id) => id === 'gpt-4-text' ? 'text' : 'image', + requestId: 'test-req-id', + logger: { info: console.log, error: console.error, warn: console.warn, debug: console.log } +}; + +async function testTextParsing() { + console.log('--- Testing Text Model Parsing ---'); + const requestData = { + model: 'gpt-4-text', + stream: true, + messages: [ + { role: 'system', content: 'You are a cat.' }, + { role: 'user', content: 'Hello' }, + { role: 'assistant', content: 'Meow' }, + { + role: 'user', content: [ + { type: 'text', text: 'Look at this ' }, + { type: 'image_url', image_url: { url: 'https://example.com/image.png' } } + ] + } + ] + }; + + const result = await parseRequest(requestData, mockOptions); + + if (result.success) { + console.log('Success!'); + console.log('Prompt:\n' + result.data.prompt); + console.log('Image Paths:', result.data.imagePaths); + + if (result.data.prompt.includes('=== 系统指令') && result.data.prompt.includes('User: Look at this')) { + console.log('✅ Text Parsing Verification PASSED'); + } else { + console.error('❌ Text Parsing Verification FAILED'); + } + + } else { + console.error('Failed:', result.error); + } +} + +async function testImageParsing() { + console.log('\n--- Testing Image Model Parsing (Legacy) ---'); + const requestData = { + model: 'some-image-model', + stream: false, + messages: [ + { role: 'user', content: 'Draw a cat' } + ] + }; + + const options = { + ...mockOptions, + resolveModelId: (id) => 'resolved-image-model', + getModelType: () => 'image' + }; + + const result = await parseRequest(requestData, options); + + if (result.success) { + console.log('Success!'); + console.log('Prompt:', result.data.prompt); + if (result.data.prompt === 'Draw a cat') { + console.log('✅ Image Parsing Verification PASSED'); + } else { + console.error('❌ Image Parsing Verification FAILED'); + } + } else { + console.error('Failed:', result.error); + } +} + +(async () => { + try { + await testTextParsing(); + await testImageParsing(); + } catch (e) { + console.error(e); + } +})(); diff --git a/server.js b/server.js index eb12e67..82b21ee 100644 --- a/server.js +++ b/server.js @@ -58,7 +58,8 @@ const { TEMP_DIR, resolveModelId, getModels, - getImagePolicy + getImagePolicy, + getModelType } = backend; /** @type {number} 服务器端口 */ @@ -102,16 +103,13 @@ const queueManager = createQueueManager( : null } ); - -/** - * 路由处理器：负责 API 路由分发和鉴权 - */ const handleRequest = createRouter({ authToken: AUTH_TOKEN, backendName, getModels, resolveModelId, getImagePolicy, + getModelType, tempDir: TEMP_DIR, imageLimit: IMAGE_LIMIT, queueManager diff --git a/src/backend/adapter/lmarena_text.js b/src/backend/adapter/lmarena_text.js new file mode 100644 index 0000000..53dd1bc --- /dev/null +++ b/src/backend/adapter/lmarena_text.js @@ -0,0 +1,295 @@ +/** + * @fileoverview LMArena 适配器 + */ + +import { + sleep, + safeClick, + pasteImages +} from '../../browser/utils.js'; +import { + fillPrompt, + submit, + waitApiResponse, + normalizePageError, + normalizeHttpError, + + moveMouseAway, + waitForInput, + gotoWithCheck +} from '../utils/index.js'; +import { logger } from '../../utils/logger.js'; + +// --- 配置常量 --- +const TARGET_URL = 'https://lmarena.ai/c/new?mode=direct'; + + + + +/** + * 执行生图任务 + * @param {object} context - 浏览器上下文 { page, client } + * @param {string} prompt - 提示词 + * @param {string[]} imgPaths - 图片路径数组 + * @param {string} [modelId] - 指定的模型 ID (可选) + * @param {object} [meta={}] - 日志元数据 + * @returns {Promise<{image?: string, text?: string, error?: string}>} 生成结果 + */ +async function generateImage(context, prompt, imgPaths, modelId, meta = {}) { + const { page, config } = context; + const textareaSelector = 'textarea'; + + try { + logger.info('适配器', '开启新会话...', meta); + const gotoResult = await gotoWithCheck(page, TARGET_URL); + if (gotoResult.error) return gotoResult; + + // 1. 等待输入框加载 + await waitForInput(page, textareaSelector, { click: false }); + await sleep(1500, 2500); + + // 2. 上传图片 (uploadImages) + if (imgPaths && imgPaths.length > 0) { + await pasteImages(page, textareaSelector, imgPaths); + } + + // 3. 填写提示词 (fillPrompt) + await safeClick(page, textareaSelector, { bias: 'input' }); + await fillPrompt(page, textareaSelector, prompt, meta); + + // 4. 配置请求拦截 (用于修改模型 ID) + await page.unroute('**/*').catch(() => { }); + + if (modelId) { + logger.debug('适配器', `准备拦截请求`, meta); + await page.route(url => url.href.includes('/nextjs-api/stream'), async (route) => { + const request = route.request(); + if (request.method() !== 'POST') return route.continue(); + + try { + const postData = request.postDataJSON(); + if (postData && postData.modelAId) { + logger.info('适配器', `已拦截请求并修改模型: ${postData.modelAId} -> ${modelId}`, meta); + postData.modelAId = modelId; + await route.continue({ postData: JSON.stringify(postData) }); + return; + } + } catch (e) { + logger.error('适配器', '拦截处理异常', { ...meta, error: e.message }); + } + await route.continue(); + }); + } + + // 5. 提交表单 (submit) + logger.debug('适配器', '点击发送...', meta); + await submit(page, { + btnSelector: 'button[type="submit"]', + inputTarget: textareaSelector, + meta + }); + + logger.info('适配器', '等待生成结果...', meta); + + // 6. 等待 API 响应 (waitApiResponse) + let response; + try { + response = await waitApiResponse(page, { + urlMatch: '/nextjs-api/stream', + method: 'POST', + timeout: 120000, + meta + }); + } catch (e) { + // 使用公共错误处理 + const pageError = normalizePageError(e, meta); + if (pageError) return pageError; + throw e; + } + + // 7. 解析响应结果 + const content = await response.text(); + + // 8. 检查 HTTP 错误 + const httpError = normalizeHttpError(response, content); + if (httpError) { + logger.error('适配器', `请求生成时返回错误: ${httpError.error}`, meta); + return { error: `请求生成时返回错误: ${httpError.error}` }; + } + + // 9. 解析文本流 + // 格式示例: + // a0:"Hello" + // a0:" World" + // d:{"finishReason":"stop"} + let fullText = ''; + const lines = content.split('\n'); + + for (const line of lines) { + if (line.startsWith('a0:')) { + try { + // 尝试解析 JSON 字符串内容 + // line.substring(3) 应该是 JSON 字符串，如 "Hello" + const textPart = JSON.parse(line.substring(3)); + fullText += textPart; + } catch (e) { + // 如果解析失败，可能是原生文本或其他格式 + logger.warn('适配器', `解析文本块失败: ${line}`, meta); + } + } + } + + if (fullText) { + logger.info('适配器', `获取文本成功，长度: ${fullText.length}`, meta); + return { text: fullText }; + } else { + logger.warn('适配器', '未解析到有效文本内容', { ...meta, preview: content.substring(0, 150) }); + // 如果没解析到 a0，尝试直接返回原始内容防空 + return { error: '未解析到有效文本内容' }; + } + + } catch (err) { + // 顶层错误处理 + const pageError = normalizePageError(err, meta); + if (pageError) return pageError; + + logger.error('适配器', '生成任务失败', { ...meta, error: err.message }); + return { error: `生成任务失败: ${err.message}` }; + } finally { + // 清理拦截器 + if (modelId) await page.unroute('**/*').catch(() => { }); + + // 任务结束，将鼠标移至安全区域 + await moveMouseAway(page); + } +} + +/** + * 适配器 manifest + */ +export const manifest = { + id: 'lmarena_text', + displayName: 'LMArena Text', + + // 入口 URL + getTargetUrl(config, workerConfig) { + return TARGET_URL; + }, + + // 模型列表（从 models.js 迁移） + models: [ + { id: 'claude-opus-4-5-20251101-thinking-32k', codeName: '019ab8b2-9bcf-79b5-9fb5-149a7c67b7c0', imagePolicy: 'forbidden', type: 'text' }, + { id: 'claude-opus-4-5-20251101', 'codeName': '019adbec-8396-71cc-87d5-b47f8431a6a6', 'imagePolicy': 'forbidden', "type": "text" }, + { id: 'gemini-3-pro', codeName: '019a98f7-afcd-779f-8dcb-856cc3b3f078', imagePolicy: 'optional', type: 'text' }, + { id: 'grok-4.1-thinking', codeName: '019a9389-a9d3-77a8-afbb-4fe4dd3d8630', imagePolicy: 'forbidden', type: 'text' }, + { id: 'grok-4.1', codeName: '019a9389-a4d8-748d-9939-b4640198302e', imagePolicy: 'forbidden', type: 'text' }, + { id: 'gpt-5.1-high', codeName: '019a8548-a2b1-70ce-b1be-eba096d41f58', imagePolicy: 'optional', type: 'text' }, + { id: 'gemini-2.5-pro', codeName: '0199f060-b306-7e1f-aeae-0ebb4e3f1122', imagePolicy: 'optional', type: 'text' }, + { id: 'claude-sonnet-4-5-20250929-thinking-32k', codeName: 'b0ea1407-2f92-4515-b9cc-b22a6d6c14f2', imagePolicy: 'forbidden', type: 'text' }, + { id: 'claude-opus-4-1-20250805-thinking-16k', codeName: 'f1a2eb6f-fc30-4806-9e00-1efd0d73cbc4', imagePolicy: 'forbidden', type: 'text' }, + { id: 'claude-sonnet-4-5-20250929', codeName: '019a2d13-28a5-7205-908c-0a58de904617', imagePolicy: 'forbidden', type: 'text' }, + { id: 'claude-opus-4-1-20250805', codeName: '96ae95fd-b70d-49c3-91cc-b58c7da1090b', imagePolicy: 'forbidden', type: 'text' }, + { id: 'chatgpt-4o-latest-20250326', codeName: '0199c1e0-3720-742d-91c8-787788b0a19b', imagePolicy: 'optional', type: 'text' }, + { id: 'gpt-5.1', codeName: '019a7ebf-0f3f-7518-8899-fca13e32d9dc', imagePolicy: 'optional', type: 'text' }, + { id: 'gpt-5-high', codeName: '983bc566-b783-4d28-b24c-3c8b08eb1086', imagePolicy: 'optional', type: 'text' }, + { id: 'o3-2025-04-16', codeName: 'cb0f1e24-e8e9-4745-aabc-b926ffde7475', imagePolicy: 'optional', type: 'text' }, + { id: 'qwen3-max-preview', codeName: '812c93cc-5f88-4cff-b9ca-c11a26599b0e', imagePolicy: 'forbidden', type: 'text' }, + { id: 'grok-4-1-fast-reasoning', codeName: '019aa41a-0a13-714a-beb1-be4a918a4b56', imagePolicy: 'forbidden', type: 'text' }, + { id: 'ernie-5.0-preview-1103', codeName: '019a4ca9-720d-75f5-9012-883ce8ff61df', imagePolicy: 'forbidden', type: 'text' }, + { id: 'kimi-k2-thinking-turbo', codeName: '019a59bc-8bb8-7933-92eb-fe143770c211', imagePolicy: 'forbidden', type: 'text' }, + { id: 'gpt-5-chat', codeName: '4b11c78c-08c8-461c-938e-5fc97d56a40d', imagePolicy: 'optional', type: 'text' }, + { id: 'glm-4.6', codeName: 'f595e6f1-6175-4880-a9eb-377e390819e4', imagePolicy: 'forbidden', type: 'text' }, + { id: 'qwen3-max-2025-09-23', codeName: '98ad8b8b-12cd-46cd-98de-99edde7e03eb', imagePolicy: 'forbidden', type: 'text' }, + { id: 'claude-opus-4-20250514-thinking-16k', codeName: '3b5e9593-3dc0-4492-a3da-19784c4bde75', imagePolicy: 'forbidden', type: 'text' }, + { id: 'qwen3-235b-a22b-instruct-2507', codeName: 'ee7cb86e-8601-4585-b1d0-7c7380f8f6f4', imagePolicy: 'forbidden', type: 'text' }, + { id: 'grok-4-fast-chat', codeName: 'grok-4-fast-chat', imagePolicy: 'forbidden', type: 'text' }, + { id: 'deepseek-v3.2-thinking', codeName: '019adb32-bb7a-77eb-882f-b8e3aaa2b2fd', imagePolicy: 'forbidden', type: 'text' }, + { id: 'kimi-k2-0905-preview', codeName: 'b88e983b-9459-473d-8bf1-753932f1679a', imagePolicy: 'forbidden', type: 'text' }, + { id: 'kimi-k2-0711-preview', codeName: '7a3626fc-4e64-4c9e-821f-b449a4b43b6a', imagePolicy: 'forbidden', type: 'text' }, + { id: 'deepseek-v3.2', codeName: '019adb32-b716-7591-9a2f-c6882973e340', imagePolicy: 'forbidden', type: 'text' }, + { id: 'qwen3-vl-235b-a22b-instruct', codeName: '716aa8ca-d729-427f-93ab-9579e4a13e98', imagePolicy: 'optional', type: 'text' }, + { id: 'mistral-large-3', codeName: '019acbac-df7c-73dc-9716-ebe040daaa4e', imagePolicy: 'forbidden', type: 'text' }, + { id: 'gpt-4.1-2025-04-14', codeName: '14e9311c-94d2-40c2-8c54-273947e208b0', imagePolicy: 'optional', type: 'text' }, + { id: 'claude-opus-4-20250514', codeName: 'ee116d12-64d6-48a8-88e5-b2d06325cdd2', imagePolicy: 'forbidden', type: 'text' }, + { id: 'mistral-medium-2508', codeName: '27035fb8-a25b-4ec9-8410-34be18328afd', imagePolicy: 'optional', type: 'text' }, + { id: 'grok-4-0709', codeName: 'b9edb8e9-4e98-49e7-8aaf-ae67e9797a11', imagePolicy: 'optional', type: 'text' }, + { id: 'glm-4.5', codeName: 'd079ef40-3b20-4c58-ab5e-243738dbada5', imagePolicy: 'forbidden', type: 'text' }, + { id: 'gemini-2.5-flash', codeName: '0199f059-3877-7cfe-bc80-e01b1a4a83de', imagePolicy: 'optional', type: 'text' }, + { id: 'gemini-2.5-flash-preview-09-2025', codeName: 'fc700d46-c4c1-4fec-88b5-f086876ae0bb', imagePolicy: 'optional', type: 'text' }, + { id: 'claude-haiku-4-5-20251001', codeName: '0199e8e9-01ed-73e0-96ba-cf43b286bf10', imagePolicy: 'forbidden', type: 'text' }, + { id: 'grok-4-fast-reasoning', codeName: '19b3730a-0369-49ba-ad9c-09e7337937f0', imagePolicy: 'forbidden', type: 'text' }, + { id: 'qwen3-next-80b-a3b-instruct', codeName: '351fe482-eb6c-4536-857b-909e16c0bf52', imagePolicy: 'forbidden', type: 'text' }, + { id: 'longcat-flash-chat', codeName: '6fcbe051-f521-4dc7-8986-c429eb6191bf', imagePolicy: 'forbidden', type: 'text' }, + { id: 'qwen3-235b-a22b-no-thinking', codeName: '1a400d9a-f61c-4bc2-89b4-a9b7e77dff12', imagePolicy: 'forbidden', type: 'text' }, + { id: 'qwen3-235b-a22b-thinking-2507', codeName: '16b8e53a-cc7b-4608-a29a-20d4dac77cf2', imagePolicy: 'forbidden', type: 'text' }, + { id: 'qwen3-vl-235b-a22b-thinking', codeName: '03c511f5-0d35-4751-aae6-24f918b0d49e', imagePolicy: 'optional', type: 'text' }, + { id: 'gpt-5-mini-high', codeName: '5fd3caa8-fe4c-41a5-a22c-0025b58f4b42', imagePolicy: 'optional', type: 'text' }, + { id: 'deepseek-v3-0324', codeName: '2f5253e4-75be-473c-bcfc-baeb3df0f8ad', imagePolicy: 'forbidden', type: 'text' }, + { id: 'hunyuan-vision-1.5-thinking', codeName: '6a3a1e04-050e-4cb4-9052-b9ac4bec0c38', imagePolicy: 'optional', type: 'text' }, + { id: 'o4-mini-2025-04-16', codeName: 'f1102bbf-34ca-468f-a9fc-14bcf63f315b', imagePolicy: 'optional', type: 'text' }, + { id: 'claude-sonnet-4-20250514', codeName: 'ac44dd10-0666-451c-b824-386ccfea7bcc', imagePolicy: 'forbidden', type: 'text' }, + { id: 'claude-3-7-sonnet-20250219-thinking-32k', codeName: 'be98fcfd-345c-4ae1-9a82-a19123ebf1d2', imagePolicy: 'forbidden', type: 'text' }, + { id: 'qwen3-coder-480b-a35b-instruct', codeName: 'af033cbd-ec6c-42cc-9afa-e227fc12efe8', imagePolicy: 'forbidden', type: 'text' }, + { id: 'hunyuan-t1-20250711', codeName: 'ba8c2392-4c47-42af-bfee-c6c057615a91', imagePolicy: 'forbidden', type: 'text' }, + { id: 'mistral-medium-2505', codeName: '27b9f8c6-3ee1-464a-9479-a8b3c2a48fd4', imagePolicy: 'optional', type: 'text' }, + { id: 'qwen3-30b-a3b-instruct-2507', codeName: 'a8d1d310-e485-4c50-8f27-4bff18292a99', imagePolicy: 'forbidden', type: 'text' }, + { id: 'gpt-4.1-mini-2025-04-14', codeName: '6a5437a7-c786-467b-b701-17b0bc8c8231', imagePolicy: 'optional', type: 'text' }, + { id: 'gemini-2.5-flash-lite-preview-09-2025-no-thinking', codeName: '75555628-8c14-402a-8d6e-43c19cb40116', imagePolicy: 'optional', type: 'text' }, + { id: 'gemini-2.5-flash-lite-preview-06-17-thinking', codeName: '04ec9a17-c597-49df-acf0-963da275c246', imagePolicy: 'optional', type: 'text' }, + { id: 'qwen3-235b-a22b', codeName: '2595a594-fa54-4299-97cd-2d7380d21c80', imagePolicy: 'forbidden', type: 'text' }, + { id: 'claude-3-5-sonnet-20241022', codeName: 'f44e280a-7914-43ca-a25d-ecfcc5d48d09', imagePolicy: 'forbidden', type: 'text' }, + { id: 'claude-3-7-sonnet-20250219', codeName: 'c5a11495-081a-4dc6-8d9a-64a4fd6f7bbc', imagePolicy: 'forbidden', type: 'text' }, + { id: 'glm-4.5-air', codeName: '7bfb254a-5d32-4ce2-b6dc-2c7faf1d5fe8', imagePolicy: 'forbidden', type: 'text' }, + { id: 'qwen3-next-80b-a3b-thinking', codeName: '73cf8705-98c8-4b75-8d04-e3746e1c1565', imagePolicy: 'forbidden', type: 'text' }, + { id: 'minimax-m1', codeName: '87e8d160-049e-4b4e-adc4-7f2511348539', imagePolicy: 'forbidden', type: 'text' }, + { id: 'gemma-3-27b-it', codeName: '789e245f-eafe-4c72-b563-d135e93988fc', imagePolicy: 'optional', type: 'text' }, + { id: 'grok-3-mini-high', codeName: '149619f1-f1d5-45fd-a53e-7d790f156f20', imagePolicy: 'forbidden', type: 'text' }, + { id: 'gemini-2.0-flash-001', codeName: '7a55108b-b997-4cff-a72f-5aa83beee918', imagePolicy: 'optional', type: 'text' }, + { id: 'grok-3-mini-beta', codeName: '7699c8d4-0742-42f9-a117-d10e84688dab', imagePolicy: 'forbidden', type: 'text' }, + { id: 'mistral-small-2506', codeName: 'bbad1d17-6aa5-4321-949c-d11fb6289241', imagePolicy: 'optional', type: 'text' }, + { id: 'gpt-oss-120b', codeName: '6ee9f901-17b5-4fbe-9cc2-13c16497c23b', imagePolicy: 'forbidden', type: 'text' }, + { id: 'glm-4.5v', codeName: '9dab0475-a0cc-4524-84a2-3fd25aa8c768', imagePolicy: 'optional', type: 'text' }, + { id: 'command-a-03-2025', codeName: '0f785ba1-efcb-472d-961e-69f7b251c7e3', imagePolicy: 'forbidden', type: 'text' }, + { id: 'amazon-nova-experimental-chat-10-20', codeName: '019a4c75-256c-790b-9088-4694cc63c507', imagePolicy: 'forbidden', type: 'text' }, + { id: 'intellect-3', codeName: '019aebfd-af0e-7f0c-8f0d-96c588e4cd3b', imagePolicy: 'forbidden', type: 'text' }, + { id: 'o3-mini', codeName: 'c680645e-efac-4a81-b0af-da16902b2541', imagePolicy: 'forbidden', type: 'text' }, + { id: 'ling-flash-2.0', codeName: '71f96ca9-4cf8-4be7-bac2-2231613930a6', imagePolicy: 'forbidden', type: 'text' }, + { id: 'minimax-m2', codeName: '019a27e0-e7d8-7b0b-877c-a2106c6eb87d', imagePolicy: 'forbidden', type: 'text' }, + { id: 'step-3', codeName: '1ea13a81-93a7-4804-bcdd-693cd72e302d', imagePolicy: 'forbidden', type: 'text' }, + { id: 'gpt-5-nano-high', codeName: '2dc249b3-98da-44b4-8d1e-6666346a8012', imagePolicy: 'optional', type: 'text' }, + { id: 'nova-2-lite', codeName: '019ae300-83b7-7717-a1e0-31accd1ff6fa', imagePolicy: 'forbidden', type: 'text' }, + { id: 'qwq-32b', codeName: '885976d3-d178-48f5-a3f4-6e13e0718872', imagePolicy: 'forbidden', type: 'text' }, + { id: 'llama-4-maverick-17b-128e-instruct', codeName: 'b5ad3ab7-fc56-4ecd-8921-bd56b55c1159', imagePolicy: 'optional', type: 'text' }, + { id: 'qwen3-30b-a3b', codeName: '9a066f6a-7205-4325-8d0b-d81cc4b049c0', imagePolicy: 'forbidden', type: 'text' }, + { id: 'claude-3-5-haiku-20241022', codeName: 'claude-3-5-haiku-20241022', imagePolicy: 'forbidden', type: 'text' }, + { id: 'ring-flash-2.0', codeName: '11ad4114-c868-4fed-b6e7-d535dc9c62f8', imagePolicy: 'forbidden', type: 'text' }, + { id: 'llama-3.3-70b-instruct', codeName: 'dcbd7897-5a37-4a34-93f1-76a24c7bb028', imagePolicy: 'forbidden', type: 'text' }, + { id: 'gemma-3n-e4b-it', codeName: '896a3848-ae03-4651-963b-7d8f54b61ae8', imagePolicy: 'forbidden', type: 'text' }, + { id: 'gpt-oss-20b', codeName: 'ec3beb4b-7229-4232-bab9-670ee52dd711', imagePolicy: 'forbidden', type: 'text' }, + { id: 'mercury', codeName: '019a6f77-e20d-7c1d-a7cd-8bd926e7395d', imagePolicy: 'forbidden', type: 'text' }, + { id: 'olmo-3-32b-think', codeName: '019ac2ef-27e1-769f-8258-d131f79e28ef', imagePolicy: 'forbidden', type: 'text' }, + { id: 'magistral-medium-2506', codeName: '6337f479-2fc8-4311-a76b-8c957765cd68', imagePolicy: 'forbidden', type: 'text' }, + { id: 'mistral-small-3.1-24b-instruct-2503', codeName: '69f5d38a-45f5-4d3a-9320-b866a4035ed9', imagePolicy: 'optional', type: 'text' }, + { id: 'ibm-granite-h-small', codeName: '4ddb69f5-391a-4f78-af92-7d7328c18ab1', imagePolicy: 'forbidden', type: 'text' }, + { id: 'qwen3-vl-8b-thinking', codeName: '0199e3d1-a308-77b9-a650-41453e8ef2fb', imagePolicy: 'optional', type: 'text' }, + { id: 'qwen3-vl-8b-instruct', codeName: '0199e3d1-a713-7de2-a5dd-a1583cad9532', imagePolicy: 'optional', type: 'text' }, + { id: 'amazon.nova-pro-v1:0', codeName: 'a14546b5-d78d-4cf6-bb61-ab5b8510a9d6', imagePolicy: 'optional', type: 'text' }, + { id: 'glm-4.6v', codeName: '019b151a-7c3b-72a2-8811-0bf9317c2ef5', imagePolicy: 'optional', type: 'text' }, + { id: 'gpt-5.2-high', codeName: '019b1448-dafa-7f92-90c3-50e159c2263c', imagePolicy: 'optional', type: 'text' }, + { id: 'gpt-5.2', codeName: '019b1448-d548-78f4-8b98-788d72cbd057', imagePolicy: 'foptional', type: 'text' }, + { id: 'glm-4.6v-flash', codeName: '019b1536-49c0-73b2-8d45-403b8571568d', imagePolicy: 'optional', type: 'text' }, + { id: 'qwen3-omni-flash', codeName: '0199c9dc-e157-7458-bd49-5942363be215', imagePolicy: 'optional', type: 'text' } + ], + + // 模型 ID 解析 + resolveModelId(modelKey) { + const model = this.models.find(m => m.id === modelKey); + return model ? model.codeName : null; + }, + + // 无需导航处理器 + navigationHandlers: [], + + // 核心生图方法 + generateImage +}; diff --git a/src/backend/index.js b/src/backend/index.js index 88b77e7..ae15fee 100644 --- a/src/backend/index.js +++ b/src/backend/index.js @@ -110,6 +110,18 @@ export function getBackend() { return poolManager.getImagePolicy(modelKey); }, + /** + * 获取模型类型 + * @param {string} modelKey - 模型 key + * @returns {string} 'text' | 'image' + */ + getModelType: (modelKey) => { + if (!poolManager) { + return 'image'; + } + return poolManager.getModelType(modelKey); + }, + /** * 获取 Cookies * @param {string} [workerName] - Worker 名称 diff --git a/src/backend/pool/PoolManager.js b/src/backend/pool/PoolManager.js index 5cb6bf8..818bac4 100644 --- a/src/backend/pool/PoolManager.js +++ b/src/backend/pool/PoolManager.js @@ -249,6 +249,18 @@ export class PoolManager { return 'optional'; } + /** + * 获取模型类型 + */ + getModelType(modelKey) { + for (const worker of this.workers) { + if (worker.supports(modelKey)) { + return worker.getModelType(modelKey); + } + } + return 'image'; + } + /** * 获取指定实例的 Cookies */ diff --git a/src/backend/pool/Worker.js b/src/backend/pool/Worker.js index 5b5b16e..353dac7 100644 --- a/src/backend/pool/Worker.js +++ b/src/backend/pool/Worker.js @@ -421,6 +421,27 @@ export class Worker { } } + /** + * 获取模型类型 + */ + getModelType(modelKey) { + if (this.type === 'merge') { + if (modelKey.includes('/')) { + const [specifiedType, actualModel] = modelKey.split('/', 2); + if (this.mergeTypes.includes(specifiedType)) { + return registry.getModelType(specifiedType, actualModel); + } + } + for (const type of this.mergeTypes) { + const realId = registry.resolveModelId(type, modelKey); + if (realId) return registry.getModelType(type, modelKey); + } + return 'image'; + } else { + return registry.getModelType(this.type, modelKey); + } + } + /** * 导航到监控页面（空闲时） */ diff --git a/src/backend/registry.js b/src/backend/registry.js index 885583f..71253a2 100644 --- a/src/backend/registry.js +++ b/src/backend/registry.js @@ -197,7 +197,8 @@ class AdapterRegistry { object: 'model', created: Math.floor(Date.now() / 1000), owned_by: id, - image_policy: m.imagePolicy + image_policy: m.imagePolicy, + type: m.type || 'image' // Default to image if not specified })); return { object: 'list', data }; @@ -243,6 +244,22 @@ class AdapterRegistry { return model?.imagePolicy || IMAGE_POLICY.OPTIONAL; } + /** + * 获取模型的类型 + * @param {string} adapterId - 适配器 ID + * @param {string} modelKey - 模型 key + * @returns {string} 'text' | 'image' + */ + getModelType(adapterId, modelKey) { + const adapter = this.getAdapter(adapterId); + if (!adapter || !adapter.models) { + return 'image'; + } + + const model = adapter.models.find(m => m.id === modelKey); + return model?.type || 'image'; + } + /** * 聚合所有适配器的模型列表 * @returns {object} @@ -258,7 +275,8 @@ class AdapterRegistry { object: 'model', created: Math.floor(Date.now() / 1000), owned_by: id, - image_policy: m.imagePolicy + image_policy: m.imagePolicy, + type: m.type || 'image' }); } } diff --git a/src/server/http/routes.js b/src/server/http/routes.js index 12c625d..dd82995 100644 --- a/src/server/http/routes.js +++ b/src/server/http/routes.js @@ -28,6 +28,7 @@ function checkAuth(req, authToken) { * @param {Function} context.getModels - 获取模型列表函数 * @param {Function} context.resolveModelId - 解析模型 ID 函数 * @param {Function} context.getImagePolicy - 获取图片策略函数 + * @param {Function} context.getModelType - 获取模型类型函数 * @param {string} context.tempDir - 临时目录 * @param {number} context.imageLimit - 图片数量限制 * @param {object} context.queueManager - 队列管理器 @@ -40,6 +41,7 @@ export function createRouter(context) { getModels, resolveModelId, getImagePolicy, + getModelType, tempDir, imageLimit, queueManager @@ -138,6 +140,7 @@ export function createRouter(context) { backendName, resolveModelId, getImagePolicy, + getModelType, requestId, logger }); diff --git a/src/server/parseChat.js b/src/server/parseChat.js index d8c0594..887227b 100644 --- a/src/server/parseChat.js +++ b/src/server/parseChat.js @@ -56,6 +56,7 @@ function parseError(code, customMessage) { * @param {string} options.backendName - 后端名称 * @param {Function} options.resolveModelId - 模型 ID 解析函数 * @param {Function} options.getImagePolicy - 获取图片策略函数 + * @param {Function} options.getModelType - 获取模型类型函数 * @param {string} options.requestId - 请求 ID * @param {Function} options.logger - 日志函数 * @returns {Promise} 解析结果 @@ -67,6 +68,7 @@ export async function parseRequest(data, options) { backendName, resolveModelId, getImagePolicy, + getModelType, requestId, logger } = options; @@ -79,6 +81,156 @@ export async function parseRequest(data, options) { return parseError(ERROR_CODES.NO_MESSAGES); } + // 1. 解析模型参数与类型 + let modelKey = null; + let isTextMode = false; + + if (data.model) { + const resolved = resolveModelId(data.model); + if (resolved) { + modelKey = data.model; + logger.info('服务器', `触发模型: ${data.model}`, { id: requestId }); + + // 判定是否为文本模式 + const type = getModelType ? getModelType(data.model) : 'image'; + isTextMode = type === 'text'; + + if (isTextMode) { + logger.info('服务器', '解析模式: 文本对话 (虚拟上下文构建)', { id: requestId }); + } else { + logger.info('服务器', '解析模式: 图像生成 (仅取最后一条)', { id: requestId }); + } + + } else { + return parseError(ERROR_CODES.INVALID_MODEL, `模型无效/后端 ${backendName} 不支持: ${data.model}`); + } + } else { + logger.info('服务器', '未指定模型，使用网页默认', { id: requestId }); + } + + // ============================================================ + // 分支 A: 文本模型解析 (构建虚拟上下文) + // ============================================================ + if (isTextMode) { + return await parseTextRequest(messages, tempDir, imageLimit, modelKey, isStreaming); + } + + // ============================================================ + // 分支 B: 生图模型解析 (原有逻辑) + // ============================================================ + return await parseImageRequest(messages, tempDir, imageLimit, modelKey, isStreaming, getImagePolicy); +} + +/** + * 解析文本请求 (构建虚拟上下文) + */ +async function parseTextRequest(messages, tempDir, imageLimit, modelId, isStreaming) { + let systemPrompt = ''; + let historyPrompt = ''; + let currentPrompt = ''; + + const imagePaths = []; + let globalImageCount = 0; + + // 辅助函数：处理单条消息内容 + async function processContent(content) { + let textBuffer = ''; + if (typeof content === 'string') { + textBuffer += content; + } else if (Array.isArray(content)) { + for (const item of content) { + if (item.type === 'text') { + textBuffer += item.text; + } else if (item.type === 'image_url' && item.image_url?.url) { + globalImageCount++; + + // 图片数量限制检查 + if (imageLimit > 0 && globalImageCount > imageLimit) { + textBuffer += `[图片${globalImageCount} (已忽略:超过限制)]`; + continue; + } + + const url = item.image_url.url; + if (url.startsWith('data:image')) { + const imagePath = await saveBase64Image(url, tempDir); + if (imagePath) { + imagePaths.push(imagePath); + // 插入占位符 + textBuffer += `[图片${globalImageCount}]`; + } else { + textBuffer += `[图片${globalImageCount} (上传失败)]`; + } + } else { + textBuffer += `[图片${globalImageCount} (无效链接)]`; + } + } + } + } + return textBuffer; + } + + // 1. 提取 System Prompt + const systemMsg = messages.find(m => m.role === 'system'); + if (systemMsg) { + const content = await processContent(systemMsg.content); + if (content) { + systemPrompt = `=== 系统指令 (永远置顶) ===\n${content}\n\n`; + } + } + + // 2. 区分历史和当前消息 + // 找到最后一条 user 消息的索引 + let lastUserIndex = -1; + for (let i = messages.length - 1; i >= 0; i--) { + if (messages[i].role === 'user') { + lastUserIndex = i; + break; + } + } + + if (lastUserIndex === -1) { + return parseError(ERROR_CODES.NO_USER_MESSAGES); + } + + // 3. 构建历史对话 (不包含 system 和 最后一条 user) + const historyMessages = messages.filter((m, index) => { + return m.role !== 'system' && index < lastUserIndex; + }); + + if (historyMessages.length > 0) { + historyPrompt += `=== 历史对话 (滑动窗口或摘要) ===\n`; + for (const msg of historyMessages) { + const roleName = msg.role === 'user' ? 'User' : 'AI'; + const content = await processContent(msg.content); + historyPrompt += `${roleName}: ${content}\n`; + } + historyPrompt += `\n`; + } + + // 4. 构建当前输入 + const lastUserMsg = messages[lastUserIndex]; + const currentContent = await processContent(lastUserMsg.content); + currentPrompt = `=== 当前输入 ===\nUser: ${currentContent}`; + + // 5. 合并最终 Prompt + const finalPrompt = systemPrompt + historyPrompt + currentPrompt; + + return { + success: true, + data: { + prompt: finalPrompt, + imagePaths, + modelId, + modelName: modelId, + isStreaming + } + }; +} + +/** + * 解析生图请求 (原有逻辑) + */ +async function parseImageRequest(messages, tempDir, imageLimit, modelId, isStreaming, getImagePolicy) { // 筛选用户消息 const userMessages = messages.filter(m => m.role === 'user'); if (userMessages.length === 0) { @@ -127,31 +279,16 @@ export async function parseRequest(data, options) { prompt = prompt.trim(); - // 解析模型参数 - let modelKey = null; - if (data.model) { - // 只校验模型是否支持，不解析 - const resolved = resolveModelId(data.model); - if (resolved) { - modelKey = data.model; // 保留原始 modelKey，由 PoolManager 自行解析 - logger.info('服务器', `触发模型: ${data.model}`, { id: requestId }); - } else { - return parseError(ERROR_CODES.INVALID_MODEL, `模型无效/后端 ${backendName} 不支持: ${data.model}`); - } - } else { - logger.info('服务器', '未指定模型，使用网页默认', { id: requestId }); - } - // 图片策略校验 const hasImage = imagePaths.length > 0; - const policy = data.model ? getImagePolicy(data.model) : IMAGE_POLICY.OPTIONAL; + const policy = modelId ? getImagePolicy(modelId) : IMAGE_POLICY.OPTIONAL; if (policy === IMAGE_POLICY.REQUIRED && !hasImage) { - return parseError(ERROR_CODES.IMAGE_REQUIRED, `模型 ${data.model} 需要参考图`); + return parseError(ERROR_CODES.IMAGE_REQUIRED, `模型 ${modelId} 需要参考图`); } if (policy === IMAGE_POLICY.FORBIDDEN && hasImage) { - return parseError(ERROR_CODES.IMAGE_FORBIDDEN, `模型 ${data.model} 不支持图片输入`); + return parseError(ERROR_CODES.IMAGE_FORBIDDEN, `模型 ${modelId} 不支持图片输入`); } return { @@ -159,8 +296,8 @@ export async function parseRequest(data, options) { data: { prompt, imagePaths, - modelId: modelKey, // 返回原始 modelKey - modelName: data.model || null, + modelId, + modelName: modelId, isStreaming } }; diff --git a/src/server/queue.js b/src/server/queue.js index 31f7512..d9d62a5 100644 --- a/src/server/queue.js +++ b/src/server/queue.js @@ -135,13 +135,16 @@ export function createQueueManager(queueConfig, callbacks) { } // 发送成功响应 + logger.info('服务器', '准备发送响应...', { id, isStreaming, contentLength: finalContent.length }); if (isStreaming) { const chunk = buildChatCompletionChunk(finalContent, modelName); sendSse(res, chunk); sendSseDone(res); + logger.info('服务器', '流式响应已结束', { id }); } else { const response = buildChatCompletion(finalContent, modelName); sendJson(res, 200, response); + logger.info('服务器', 'JSON 响应已发送', { id }); } } catch (err) { diff --git a/src/utils/config.js b/src/utils/config.js index 3438731..c6c8d03 100644 --- a/src/utils/config.js +++ b/src/utils/config.js @@ -19,9 +19,6 @@ const EXAMPLE_CONFIG_PATH = path.join(process.cwd(), 'config.example.yaml'); // 模块级缓存：确保配置只从磁盘读取一次 let cachedConfig = null; -// 有效的适配器类型 -const VALID_ADAPTER_TYPES = ['lmarena', 'gemini', 'gemini_biz', 'nanobananafree_ai', 'zai_is', 'merge']; - /** * 解析用户数据目录路径 * @param {string|undefined} userDataMark - 用户数据标记 @@ -84,9 +81,9 @@ function validateWorker(worker, instanceName, index) { if (!worker.type) { throw new Error(`instances[${instanceName}].workers[${index}] (${worker.name}) 缺少必需字段: type`); } - if (!VALID_ADAPTER_TYPES.includes(worker.type)) { - throw new Error(`Worker "${worker.name}" 的 type "${worker.type}" 无效。有效值: ${VALID_ADAPTER_TYPES.join(', ')}`); - } + // 移除对 type 的硬编码校验，允许动态加载新适配器 + // if (!VALID_ADAPTER_TYPES.includes(worker.type)) { ... } + if (worker.type === 'merge') { if (!worker.mergeTypes || !Array.isArray(worker.mergeTypes) || worker.mergeTypes.length === 0) { throw new Error(`Worker "${worker.name}" 类型为 merge，但缺少有效的 mergeTypes 数组`); diff --git a/升级.md b/升级.md new file mode 100644 index 0000000..899ac41 --- /dev/null +++ b/升级.md @@ -0,0 +1,395 @@ +这是一个非常好的架构升级思路。为了支持文本模型（Chat Model）并构建“虚拟上下文”，我们需要重构 `src/server/parseChat.js`，让它具备根据模型类型（图片 vs 文本）采用不同解析策略的能力。 + +以下是具体的修改方案： + +### 修改思路 + +1. **区分模型类型**：我们需要知道当前请求的模型是“生图模型”还是“文本模型”。 + * *方案*：在 `registry.js` 中为模型定义增加 `type` 字段（如 `type: 'text'`），或者在 `parseChat.js` 中简单地通过判断模型 ID 是否包含特定关键字（如 `gpt-4`, `claude`）来区分。为了演示方便，我将在代码中添加一个简单的判断逻辑。 +2. **文本模型解析逻辑**： + * 不再只取最后一条消息。 + * 遍历 `messages` 数组。 + * 提取 `system` 消息作为“系统指令”。 + * 提取之前的 `user` 和 `assistant` 消息作为“历史对话”。 + * 提取最后一条 `user` 消息作为“当前输入”。 + * **图片处理**：在遍历过程中，遇到图片不仅要保存文件，还要在文本中插入 `[图片1]` 占位符，并将图片路径收集到 `imagePaths` 数组中。 + +### 修改代码 + +你需要修改 `src/server/parseChat.js`。 + +#### 1\. 新增辅助函数 `buildTextContext` + +这个函数负责将 OpenAI 格式的 `messages` 数组转换为你要求的“虚拟上下文”字符串格式。 + +#### 2\. 改造 `parseRequest` 主函数 + +增加分支逻辑：如果是文本模型走新逻辑，如果是生图模型走原有逻辑（只取最后一条）。 + +以下是完整的修改后的 `src/server/parseChat.js` 代码： + +```javascript +/** + * @fileoverview 请求解析模块 + * @description 负责解析聊天请求、提取提示词和处理图片 + */ + +import fs from 'fs'; +import path from 'path'; +import sharp from 'sharp'; +import { IMAGE_POLICY } from '../backend/registry.js'; +import { ERROR_CODES, getErrorMessage } from './errors.js'; + +/** + * 构造解析错误结果 + */ +function parseError(code, customMessage) { + return { + success: false, + error: { + code, + error: customMessage || getErrorMessage(code) + } + }; +} + +/** + * 判断是否为文本模型 (根据模型ID特征简单判断，你可以根据 registry 里的配置来判断) + * @param {string} modelId + * @returns {boolean} + */ +function isTextModel(modelId) { + if (!modelId) return false; + // 这里可以根据实际情况修改，比如检查 registry.getModelType(modelId) + // 示例：如果 ID 包含 gpt, claude, llama, qwen 且不是 image 模型，则认为是文本模型 + // 现有的图片模型通常有 image 关键字，或者在 registry 中明确定义。 + // 为了简单起见，假设除了已知的生图模型外，其他都是文本模型，或者你可以维护一个列表。 + const textKeywords = ['gpt-4', 'claude', 'llama', 'qwen', 'deepseek', 'gemini-pro']; + // 注意：gemini-3-pro-image-preview 是生图的，需排除 + if (modelId.includes('image') || modelId.includes('flux') || modelId.includes('seedream')) return false; + + return textKeywords.some(k => modelId.includes(k)); +} + +/** + * 解析聊天请求 + */ +export async function parseRequest(data, options) { + const { + tempDir, + imageLimit, + backendName, + resolveModelId, + getImagePolicy, + requestId, + logger + } = options; + + const messages = data.messages; + const isStreaming = data.stream === true; + + // 验证 messages + if (!messages || messages.length === 0) { + return parseError(ERROR_CODES.NO_MESSAGES); + } + + // 1. 解析模型参数 + let modelKey = null; + let isTextMode = false; + + if (data.model) { + const resolved = resolveModelId(data.model); + if (resolved) { + modelKey = data.model; + logger.info('服务器', `触发模型: ${data.model}`, { id: requestId }); + + // 判定是否为文本模式 (你需要根据实际情况实现 isTextModel 或传入 getModelType) + // 这里假设如果不包含特定生图关键词就是文本模型，或者你可以扩展 options 传入判断函数 + isTextMode = isTextModel(data.model); + if (isTextMode) { + logger.info('服务器', '解析模式: 文本对话 (虚拟上下文构建)', { id: requestId }); + } else { + logger.info('服务器', '解析模式: 图像生成 (仅取最后一条)', { id: requestId }); + } + + } else { + return parseError(ERROR_CODES.INVALID_MODEL, `模型无效/后端 ${backendName} 不支持: ${data.model}`); + } + } else { + logger.info('服务器', '未指定模型，使用网页默认', { id: requestId }); + } + + // ============================================================ + // 分支 A: 文本模型解析 (构建虚拟上下文) + // ============================================================ + if (isTextMode) { + return await parseTextRequest(messages, tempDir, imageLimit, modelKey, isStreaming); + } + + // ============================================================ + // 分支 B: 生图模型解析 (原有逻辑，只取最后一条 User 消息) + // ============================================================ + return await parseImageRequest(messages, tempDir, imageLimit, modelKey, isStreaming, getImagePolicy); +} + +/** + * 解析文本请求 (构建虚拟上下文) + */ +async function parseTextRequest(messages, tempDir, imageLimit, modelId, isStreaming) { + let systemPrompt = ''; + let historyPrompt = ''; + let currentPrompt = ''; + + const imagePaths = []; + let globalImageCount = 0; + + // 辅助函数：处理单条消息内容 + async function processContent(content) { + let textBuffer = ''; + if (typeof content === 'string') { + textBuffer += content; + } else if (Array.isArray(content)) { + for (const item of content) { + if (item.type === 'text') { + textBuffer += item.text; + } else if (item.type === 'image_url' && item.image_url?.url) { + globalImageCount++; + + // 图片数量限制检查 + if (imageLimit > 0 && globalImageCount > imageLimit) { + textBuffer += `[图片${globalImageCount} (已忽略:超过限制)]`; + continue; + } + + const url = item.image_url.url; + if (url.startsWith('data:image')) { + const imagePath = await saveBase64Image(url, tempDir); + if (imagePath) { + imagePaths.push(imagePath); + // 插入占位符 + textBuffer += `[图片${globalImageCount}]`; + } else { + textBuffer += `[图片${globalImageCount} (上传失败)]`; + } + } else { + textBuffer += `[图片${globalImageCount} (无效链接)]`; + } + } + } + } + return textBuffer; + } + + // 1. 提取 System Prompt + const systemMsg = messages.find(m => m.role === 'system'); + if (systemMsg) { + const content = await processContent(systemMsg.content); + if (content) { + systemPrompt = `=== 系统指令 (永远置顶) ===\n${content}\n\n`; + } + } + + // 2. 区分历史和当前消息 + // 找到最后一条 user 消息的索引 + let lastUserIndex = -1; + for (let i = messages.length - 1; i >= 0; i--) { + if (messages[i].role === 'user') { + lastUserIndex = i; + break; + } + } + + if (lastUserIndex === -1) { + return parseError(ERROR_CODES.NO_USER_MESSAGES); + } + + // 3. 构建历史对话 (不包含 system 和 最后一条 user) + const historyMessages = messages.filter((m, index) => { + return m.role !== 'system' && index < lastUserIndex; + }); + + if (historyMessages.length > 0) { + historyPrompt += `=== 历史对话 (滑动窗口或摘要) ===\n`; + for (const msg of historyMessages) { + const roleName = msg.role === 'user' ? 'User' : 'AI'; + const content = await processContent(msg.content); + historyPrompt += `${roleName}: ${content}\n`; + } + historyPrompt += `\n`; + } + + // 4. 构建当前输入 + const lastUserMsg = messages[lastUserIndex]; + const currentContent = await processContent(lastUserMsg.content); + currentPrompt = `=== 当前输入 ===\nUser: ${currentContent}`; + + // 5. 合并最终 Prompt + // 注意：这里我们告诉浏览器上传了 imagePaths 里的所有图片 + // 并且在 prompt 文本中已经用 [图片N] 标记了它们的位置 + const finalPrompt = systemPrompt + historyPrompt + currentPrompt; + + return { + success: true, + data: { + prompt: finalPrompt, + imagePaths, // 包含历史和当前的图片路径，按顺序排列 + modelId, + modelName: modelId, + isStreaming + } + }; +} + +/** + * 解析生图请求 (原有逻辑保持不变) + */ +async function parseImageRequest(messages, tempDir, imageLimit, modelId, isStreaming, getImagePolicy) { + // 筛选用户消息 + const userMessages = messages.filter(m => m.role === 'user'); + if (userMessages.length === 0) { + return parseError(ERROR_CODES.NO_USER_MESSAGES); + } + + const lastMessage = userMessages[userMessages.length - 1]; + + let prompt = ''; + const imagePaths = []; + let imageCount = 0; + + // 解析内容 + if (Array.isArray(lastMessage.content)) { + for (const item of lastMessage.content) { + if (item.type === 'text') { + prompt += item.text + ' '; + } else if (item.type === 'image_url' && item.image_url?.url) { + imageCount++; + + // 图片数量检查 + if (imageLimit <= 10) { + if (imageCount > imageLimit) { + return parseError(ERROR_CODES.TOO_MANY_IMAGES, `图片数量超过限制（最大 ${imageLimit} 张）`); + } + } else { + if (imageCount > 10) continue; + } + + // 处理 data URL + const url = item.image_url.url; + if (url.startsWith('data:image')) { + const imagePath = await saveBase64Image(url, tempDir); + if (imagePath) { + imagePaths.push(imagePath); + } + } + } + } + } else { + prompt = lastMessage.content; + } + + prompt = prompt.trim(); + + // 图片策略校验 + const hasImage = imagePaths.length > 0; + const policy = modelId ? getImagePolicy(modelId) : IMAGE_POLICY.OPTIONAL; + + if (policy === IMAGE_POLICY.REQUIRED && !hasImage) { + return parseError(ERROR_CODES.IMAGE_REQUIRED, `模型 ${modelId} 需要参考图`); + } + + if (policy === IMAGE_POLICY.FORBIDDEN && hasImage) { + return parseError(ERROR_CODES.IMAGE_FORBIDDEN, `模型 ${modelId} 不支持图片输入`); + } + + return { + success: true, + data: { + prompt, + imagePaths, + modelId, + modelName: modelId, + isStreaming + } + }; +} + +/** + * 保存 Base64 图片到临时文件 + */ +async function saveBase64Image(dataUrl, tempDir) { + const matches = dataUrl.match(/^data:([A-Za-z-+\/]+);base64,(.+)$/); + if (!matches || matches.length !== 3) { + return null; + } + + try { + const buffer = Buffer.from(matches[2], 'base64'); + // 压缩图片 + const processedBuffer = await sharp(buffer) + .jpeg({ quality: 90 }) + .toBuffer(); + + const filename = `img_${Date.now()}_${Math.random().toString(36).substring(7)}.jpg`; + const filePath = path.join(tempDir, filename); + fs.writeFileSync(filePath, processedBuffer); + return filePath; + } catch (e) { + return null; + } +} +``` + +### 配套修改建议 + +1. **修改 `src/backend/registry.js` (可选，推荐)**: + 在 `models` 数组中添加 `type: 'text'` 或 `type: 'image'` 字段，然后在 `getModelsForAdapter` 中暴露出来。这样 `parseChat.js` 就可以通过 `registry.getModelType(id)` 来精准判断，而不是靠猜。 + +2. **修改适配器代码**: + 目前的适配器（如 `gemini_biz.js`, `zai_is.js`）的 `generateImage` 函数接收的是： + + ```javascript + async function generateImage(context, prompt, imgPaths, modelId, meta = {}) + ``` + + 对于文本模型，`prompt` 现在将是一个包含了系统指令、历史对话和当前输入的**长字符串**。`imgPaths` 将包含**所有**涉及到的图片。 + + * 适配器的逻辑通常是：先上传所有 `imgPaths`，然后在输入框填入 `prompt`，最后发送。 + * **注意**：你现有的 `gemini_biz.js` 和 `zai_is.js` 适配器逻辑是先 `pasteImages` 然后 `fillPrompt`。 + * 这对于新的文本逻辑**正好适用**！因为图片占位符 `[图片1]` 已经在 `prompt` 文本里了，而实际的图片文件通过 `imgPaths` 传给适配器上传，适配器上传后，输入框里会有图片缩略图，加上我们输入的带有 `[图片1]` 的长文本，AI 就能理解这个对应关系（或者至少作为上下文）。 + +### 效果预期 + +当客户端发送如下请求时： + +```json +{ + "model": "gpt-4-text", + "messages": [ + {"role": "system", "content": "你是一个猫娘"}, + {"role": "user", "content": "你好"}, + {"role": "assistant", "content": "喵~"}, + {"role": "user", "content": ["看看这个", {"type": "image_url", "url": "..."}]} + ] +} +``` + +服务器会解析为： + +**prompt (传递给适配器输入框的文本):** + +```text +=== 系统指令 (永远置顶) === +你是一个猫娘 + +=== 历史对话 (滑动窗口或摘要) === +User: 你好 +AI: 喵~ + +=== 当前输入 === +User: 看看这个[图片1] +``` + +**imagePaths (传递给适配器上传的文件):** +`['/tmp/img_xxx.jpg']` + +这样你就成功地在一个单轮对话的网页接口上，模拟出了带上下文和多模态理解的多轮对话体验。 \ No newline at end of file