return prompt analysis without generating images
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@ -1662,6 +1662,56 @@ function buildAutoModeFallbackMessage(params: {
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].join("\n");
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}
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function sanitizePromptOnlyUserIntent(text: string): string {
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return String(text || "")
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.replace(/先?分析(?:一下)?(?:这张)?(?:图片|图像|这张图)?/g, "")
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.replace(/帮我|给我|先给我|只给我|仅给我/g, "")
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.replace(/优化(?:一下)?提示词|提示词优化|提示词|prompt/gi, "")
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.replace(/不要生图|先别生图|不需要生图|不要生成|别生成|不直接生成/g, "")
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.replace(/[，。；：,.!！?？]/g, " ")
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.replace(/\s+/g, " ")
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.trim();
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}
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function buildPromptOnlyOptimizationSeed(params: {
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text: string;
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imageSummary?: string;
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}): string {
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const cleanedIntent = sanitizePromptOnlyUserIntent(params.text);
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const summary = String(params.imageSummary || "").replace(/\s+/g, " ").trim();
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if (cleanedIntent && summary) {
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return `${cleanedIntent}。参考图关键特征：${summary}`;
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}
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if (summary) {
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return `基于参考图生成一段可直接复现核心主体、场景、风格与光线特征的中文提示词。参考图关键特征：${summary}`;
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}
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if (cleanedIntent) {
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return cleanedIntent;
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}
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return "基于当前参考图整理一段可直接使用的中文提示词。";
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}
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function buildPromptOnlyReply(params: {
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userText: string;
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imageSummary?: string;
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optimizedPrompt: string;
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}): string {
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const demand = sanitizePromptOnlyUserIntent(params.userText) || "你希望我先分析这张图并整理可直接使用的提示词";
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const summary = String(params.imageSummary || "").replace(/\s+/g, " ").trim();
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return [
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"【需求理解】",
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`- ${demand}`,
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"【图片分析】",
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summary ? `- ${summary}` : "- 我已基于当前图片梳理主体、场景、风格与光线特征。",
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"【优化后提示词】",
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`- ${params.optimizedPrompt.replace(/\s+/g, " ").trim()}`,
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"【使用建议】",
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"- 本轮仅输出优化后的提示词，不直接执行生图。",
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].join("\n");
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}
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function hasStructuredAgentSections(message?: string): boolean {
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if (!message) return false;
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return /(?:###\s*需求理解|【\s*需求理解\s*】|###\s*图片分析|【\s*图片分析\s*】|###\s*执行计划|【\s*执行计划\s*】|###\s*优化后提示词|【\s*优化后提示词\s*】)/.test(
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@ -4042,6 +4092,133 @@ export async function POST(request: Request) {
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const streamId = generateUUID();
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await createStreamId({ streamId, chatId: id });
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const wantsPromptOnlyFromCurrentImage =
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shouldRunAgentConversation &&
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!smartAutoNeedsClarification &&
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requestResolvedMediaInput.currentMessageImageUrls.length > 0 &&
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(
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await import("@/lib/ai/smart-analyzer")
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).isExplicitPromptOptimizationRequest(requestTextContent);
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if (wantsPromptOnlyFromCurrentImage) {
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let promptOnlyImageSummary = "";
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try {
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const { summarizeImageForExecutionReport } = await import("@/lib/ai/smart-analyzer");
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const summaryTimeoutMs = getBudgetedTimeout({
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startedAt: requestStartedAt,
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preferredMs: SMART_AUTO_IMAGE_SUMMARY_TIMEOUT_MS,
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minimumMs: 6_000,
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});
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if (summaryTimeoutMs) {
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const summaryAssetIds = Array.from(
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new Set([
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...extractMessageImageAssetIds(message.parts as any[]),
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...((contextPayload?.selectedAssetIds || []).filter(Boolean) as string[]),
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]),
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);
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const summary = await withOperationTimeout(
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summarizeImageForExecutionReport({
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text: requestTextContent,
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imageUrls: requestResolvedMediaInput.currentMessageImageUrls.slice(0, 4),
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context: typeof autoContext === "string" ? autoContext : undefined,
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preferredModelId: preferredAgentModelId,
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assetIds: summaryAssetIds,
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}),
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"promptOnlyImageSummary",
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summaryTimeoutMs,
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);
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if (summary?.trim()) {
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promptOnlyImageSummary = summary.trim();
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}
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}
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} catch (promptOnlySummaryError) {
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console.warn("[Chat API] Prompt-only image summary failed:", promptOnlySummaryError);
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}
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let promptOnlyOptimizedPrompt = smartAutoOptimizedPrompt?.trim() || "";
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if (!promptOnlyOptimizedPrompt) {
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try {
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const { optimizePromptWithLLM, optimizePrompt } = await import("@/lib/ai/prompt-optimizer");
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const promptSeed = buildPromptOnlyOptimizationSeed({
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text: requestTextContent,
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imageSummary: promptOnlyImageSummary,
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});
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const optimizedResult = await optimizePromptWithLLM({
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originalPrompt: promptSeed,
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intent: "image_gen",
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historyMessages: smartAutoHistoryMessagesFromDb,
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context: typeof autoContext === "string" ? autoContext : undefined,
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}).catch(() =>
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optimizePrompt({
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originalPrompt: promptSeed,
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intent: "image_gen",
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}),
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);
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promptOnlyOptimizedPrompt = String(optimizedResult?.optimizedPrompt || "").trim();
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} catch (promptOnlyOptimizeError) {
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console.warn("[Chat API] Prompt-only optimization failed:", promptOnlyOptimizeError);
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}
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}
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if (!promptOnlyOptimizedPrompt) {
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promptOnlyOptimizedPrompt = buildPromptOnlyOptimizationSeed({
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text: requestTextContent,
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imageSummary: promptOnlyImageSummary,
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});
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}
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const promptOnlyMessage = buildPromptOnlyReply({
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userText: requestTextContent,
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imageSummary: promptOnlyImageSummary,
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optimizedPrompt: promptOnlyOptimizedPrompt,
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});
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const promptOnlyStream = createUIMessageStream({
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execute: async ({ writer }) => {
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const messageId = generateUUID();
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writeAssistantTextChunk(writer, promptOnlyMessage, "prompt-only:reply", messageId);
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await saveMessages({
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messages: [
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{
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id: messageId,
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chatId: id,
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role: "assistant",
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parts: [{ type: "text", text: promptOnlyMessage }],
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attachments: [],
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createdAt: new Date(),
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videoStorageStatus: null,
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temporaryVideoUrl: null,
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permanentVideoUrl: null,
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archivedAt: null,
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videoMetadata: null,
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},
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],
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});
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try {
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await upsertConversationWorkingState({
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userId: session.user.id,
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chatId: id,
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projectId: contextPayload?.projectId || null,
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currentIntent: "vision",
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lastMessageId: messageId,
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lastTurnSummary: {
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text: requestTextContent.slice(0, 500),
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resolutionMode: "prompt_only",
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confidence: 90,
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optimizedPrompt: promptOnlyOptimizedPrompt.slice(0, 1000),
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},
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});
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} catch (promptOnlyMemoryError) {
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console.warn("[Chat API] Failed to persist prompt-only response state:", promptOnlyMemoryError);
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}
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},
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});
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return createSseResponse(promptOnlyStream);
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}
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if (shouldRunAgentConversation && smartAutoNeedsClarification) {
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const hasCurrentImageInput = message.parts.some((part: any) =>
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part?.type === "file" || part?.type === "image" || part?.type === "image_url"
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@ -46,6 +46,26 @@ function isLikelyAdvisoryOrPlanningRequest(text: string): boolean {
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);
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}
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export function isExplicitPromptOptimizationRequest(text: string): boolean {
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const normalizedText = normalizeCompactText(text);
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if (!normalizedText) return false;
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const asksPrompt =
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/提示词|prompt|文生图提示|出图提示|描述词|咒语|关键词/.test(normalizedText);
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if (!asksPrompt) return false;
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const asksAnalysis =
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/分析|看图|看看|识别|拆解|提炼|整理|归纳|总结|描述|写出|给我|输出|优化|改写/.test(
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normalizedText,
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);
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const blocksExecution =
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/不要生图|先别生图|不需要生图|不要生成|别生成|仅给|只给|先给我|先出提示词|先分析/.test(
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normalizedText,
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);
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return asksAnalysis || blocksExecution;
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}
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function isExplicitVideoGenerationRequest(text: string): boolean {
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const normalizedText = normalizeCompactText(text);
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const hasStrongVideoMarkers =
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@ -112,6 +132,8 @@ function applyDirectExecutionPolicy(
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hasAnyRequestText && isLikelyAdvisoryOrPlanningRequest(params.text);
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const likelyVisionRequest = hasAnyRequestText && isLikelyVisionRequest(params.text);
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const likelyGeneralChatTurn = hasAnyRequestText && isLikelyGeneralChatTurn(params.text);
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const promptOptimizationOnlyRequest =
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hasAnyRequestText && isExplicitPromptOptimizationRequest(params.text);
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if (explicitVideoGenerationRequest) {
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return {
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@ -130,6 +152,19 @@ function applyDirectExecutionPolicy(
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}
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if (!hasUsableImage) {
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if (promptOptimizationOnlyRequest) {
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return {
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...result,
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intent: "chat",
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subIntent: undefined,
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confidence: Math.max(result.confidence, 0.82),
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needsClarification: false,
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clarifyingQuestions: [],
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conversationalReply:
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result.conversationalReply || "收到，我先按你的要求整理提示词，不直接执行生成。",
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};
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}
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if (!explicitImageGenerationRequest && !explicitVideoGenerationRequest) {
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if (likelyAdvisoryRequest || likelyGeneralChatTurn || result.intent === "chat") {
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return {
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@ -174,6 +209,19 @@ function applyDirectExecutionPolicy(
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const keepClarification = Boolean(result.needsClarification);
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const explicitEditRequest = hasAnyRequestText && isLikelyImageEditRequest(params.text);
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if (promptOptimizationOnlyRequest) {
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return {
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...baseResult,
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intent: "vision",
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subIntent: undefined,
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confidence: Math.max(baseResult.confidence, 0.88),
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needsClarification: false,
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clarifyingQuestions: [],
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conversationalReply:
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baseResult.conversationalReply || "收到，我先分析这张图并整理可直接使用的优化提示词，不会直接生图。",
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};
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}
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if (!hasAnyRequestText) {
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return {
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...baseResult,
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@ -2102,6 +2150,14 @@ export function fallbackKeywordAnalysis(
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// === 图片编辑场景（需要有图片） ===
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if (hasImage) {
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if (isExplicitPromptOptimizationRequest(text)) {
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return {
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intent: "vision",
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confidence: 0.92,
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conversationalReply: "收到，我先分析这张图并给你整理优化后的提示词，不直接生图。",
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};
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}
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// 视频生成（图生视频/首尾帧等）
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if (isExplicitVideoGenerationRequest(text)) {
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return {
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