fix: address project review bugs
This commit is contained in:
@@ -1,8 +1,5 @@
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import { buildApiUrl, buildAuthHeaders } from "./serverConnection";
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const TEXT_MODELS = ["qwen-max", "qwen-plus", "qwen-turbo"];
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const VISION_MODELS = ["qwen3.7-plus", "qwen-vl-plus", "qwen-vl-max"];
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type AbortSignalConstructorWithAny = typeof AbortSignal & {
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any?: (signals: AbortSignal[]) => AbortSignal;
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};
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@@ -110,11 +107,45 @@ export interface ComplianceCheck {
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allow_video_generation: boolean;
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}
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function findJsonSlice(raw: string): string {
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const start = raw.search(/[\[{]/);
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if (start < 0) return raw;
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const stack: string[] = [];
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let inString = false;
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let escaped = false;
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for (let index = start; index < raw.length; index += 1) {
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const char = raw[index];
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if (inString) {
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if (escaped) {
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escaped = false;
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} else if (char === "\\") {
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escaped = true;
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} else if (char === "\"") {
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inString = false;
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}
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continue;
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}
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if (char === "\"") {
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inString = true;
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} else if (char === "{" || char === "[") {
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stack.push(char === "{" ? "}" : "]");
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} else if (char === "}" || char === "]") {
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if (stack.pop() !== char) break;
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if (stack.length === 0) return raw.slice(start, index + 1);
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}
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}
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return raw.slice(start);
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}
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function extractJson(text: string): unknown {
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const fenced = text.match(/```(?:json)?\s*([\s\S]*?)```/);
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const raw = fenced ? fenced[1].trim() : text.trim();
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const start = raw.search(/[[{]/);
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const slice = start >= 0 ? raw.slice(start) : raw;
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const slice = findJsonSlice(raw);
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try {
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return JSON.parse(slice);
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} catch {
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@@ -122,9 +153,16 @@ function extractJson(text: string): unknown {
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}
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}
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type ChatContent =
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| string
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| Array<
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| { type: "image_url"; image_url: { url: string } }
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| { type: "text"; text: string }
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>;
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interface ChatMessage {
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role: "system" | "user";
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content: string;
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content: ChatContent;
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}
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const MAX_RETRIES = 3;
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@@ -171,43 +209,32 @@ async function chat(
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userContent: string,
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options?: { model?: string; signal?: AbortSignal },
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): Promise<string> {
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const candidateModels = options?.model ? [options.model] : TEXT_MODELS;
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let lastError: Error | null = null;
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return retryOnTransient(async () => {
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const messages: ChatMessage[] = [
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{ role: "system", content: systemPrompt },
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{ role: "user", content: userContent },
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];
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const timeoutSignal = AbortSignal.timeout(CHAT_TIMEOUT_MS);
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const combinedSignal = combineAbortSignals(options?.signal, timeoutSignal);
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const body: Record<string, unknown> = { messages, stream: false, temperature: 0.4 };
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if (options?.model) body.model = options.model;
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for (const model of candidateModels) {
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try {
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return await retryOnTransient(async () => {
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const messages: ChatMessage[] = [
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{ role: "system", content: systemPrompt },
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{ role: "user", content: userContent },
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];
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const timeoutSignal = AbortSignal.timeout(CHAT_TIMEOUT_MS);
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const combinedSignal = combineAbortSignals(options?.signal, timeoutSignal);
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const res = await fetch(buildApiUrl("ai/chat"), {
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method: "POST",
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headers: buildAuthHeaders(),
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body: JSON.stringify({ model, messages, stream: false, temperature: 0.4 }),
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signal: combinedSignal,
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});
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if (!res.ok) {
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const errBody = await res.text().catch(() => "");
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throw new Error(`AI 调用失败 (${res.status})${errBody ? `: ${errBody.slice(0, 120)}` : ""}`);
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}
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const payload = await res.json();
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const content: string =
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payload?.content ?? payload?.choices?.[0]?.message?.content ?? payload?.text ?? "";
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if (!content) throw new Error("模型未返回有效内容");
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return content;
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}, options?.signal);
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} catch (err) {
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lastError = err instanceof Error ? err : new Error(String(err));
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if (options?.signal?.aborted) throw lastError;
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// If user pinned a specific model, don't fall back to others
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if (options?.model) throw lastError;
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// Try next model in fallback chain
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const res = await fetch(buildApiUrl("ai/chat"), {
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method: "POST",
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headers: buildAuthHeaders(),
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body: JSON.stringify(body),
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signal: combinedSignal,
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});
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if (!res.ok) {
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const errBody = await res.text().catch(() => "");
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throw new Error(`AI 调用失败 (${res.status})${errBody ? `: ${errBody.slice(0, 120)}` : ""}`);
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}
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}
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throw lastError ?? new Error("所有候选模型均不可用");
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const payload = await res.json();
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const content: string =
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payload?.content ?? payload?.choices?.[0]?.message?.content ?? payload?.text ?? "";
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if (!content) throw new Error("模型未返回有效内容");
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return content;
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}, options?.signal);
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}
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async function visionChat(
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@@ -216,50 +243,36 @@ async function visionChat(
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imageUrls: string[],
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signal?: AbortSignal,
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): Promise<string> {
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const content = [
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...imageUrls.map((url) => ({ type: "image_url", image_url: { url } })),
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const content: ChatContent = [
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...imageUrls.map((url) => ({ type: "image_url" as const, image_url: { url } })),
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{ type: "text", text },
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];
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const messages = [
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{ role: "system", content: systemPrompt },
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{ role: "user", content },
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];
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] satisfies ChatMessage[];
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let lastError: Error | null = null;
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for (const model of VISION_MODELS) {
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return retryOnTransient(async () => {
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const timeoutSignal = AbortSignal.timeout(CHAT_TIMEOUT_MS);
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const combinedSignal = combineAbortSignals(signal, timeoutSignal);
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try {
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const out = await retryOnTransient(async () => {
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const res = await fetch(buildApiUrl("ai/chat"), {
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method: "POST",
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headers: buildAuthHeaders(),
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body: JSON.stringify({ model, messages, stream: false, temperature: 0.3 }),
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signal: combinedSignal,
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});
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if (!res.ok) {
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const errBody = await res.text().catch(() => "");
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if (errBody.includes("image format")) throw new Error("IMAGE_FORMAT_FALLBACK");
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throw new Error(`图片理解调用失败 (${res.status})${errBody ? `: ${errBody.slice(0, 120)}` : ""}`);
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}
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const payload = await res.json();
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const result: string =
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payload?.content ?? payload?.choices?.[0]?.message?.content ?? payload?.text ?? "";
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if (!result) throw new Error("图片理解未返回有效内容");
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return result;
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}, signal);
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return out;
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} catch (err) {
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lastError = err instanceof Error ? err : new Error(String(err));
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if (signal?.aborted) throw lastError;
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// Continue trying next vision model on transient failures, image format errors, or upstream errors
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if (lastError.message === "IMAGE_FORMAT_FALLBACK") continue;
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if (lastError.message.includes("图片理解调用失败")) continue;
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if (isTransientError(lastError)) continue;
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throw lastError;
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const res = await fetch(buildApiUrl("ai/chat"), {
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method: "POST",
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headers: buildAuthHeaders(),
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body: JSON.stringify({ messages, stream: false, temperature: 0.3 }),
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signal: combinedSignal,
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});
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if (!res.ok) {
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const errBody = await res.text().catch(() => "");
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if (errBody.includes("image format")) throw new Error("图片格式不受支持,请更换图片后重试");
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throw new Error(`图片理解调用失败 (${res.status})${errBody ? `: ${errBody.slice(0, 120)}` : ""}`);
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}
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}
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throw lastError ?? new Error("图片理解调用失败,所有模型均不可用");
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const payload = await res.json();
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const result: string =
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payload?.content ?? payload?.choices?.[0]?.message?.content ?? payload?.text ?? "";
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if (!result) throw new Error("图片理解未返回有效内容");
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return result;
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}, signal);
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}
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const IMAGE_UNDERSTANDING_PROMPT = `你是电商产品图片分析专家。请分析用户提供的产品图片,识别产品主体、外观、颜色、材质、形状、尺寸感、品牌标识、关键部件、可视化卖点和适合展示的镜头角度。请用简洁的中文段落描述,不要编造图片中看不到的信息。`;
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