feat(moderation): enhance JSON extraction and validation in moderation analysis
This commit is contained in:
MythEclipse
@@ -55,11 +55,9 @@ interface RawModerationResponse {
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}
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/**
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* Helper to extract a JSON object from a potentially conversational or markdown-wrapped string.
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* It first scans for markdown json code blocks, then falls back to trying all start/end brace pairs from largest to smallest.
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* Helper to extract JSON from a potentially conversational or markdown-wrapped string.
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*/
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export function extractJson(content: string): any {
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// 1. Try to find markdown json code blocks: ```json ... ``` or ``` ... ```
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const codeBlockRegex = /```(?:json)?\s*([\s\S]*?)\s*```/g;
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const matches = content.matchAll(codeBlockRegex);
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for (const match of matches) {
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@@ -69,32 +67,53 @@ export function extractJson(content: string): any {
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if (parsed && typeof parsed === "object") {
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return parsed;
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}
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} catch (e) {
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// Continue to next code block
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}
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} catch (_) {}
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}
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// 2. If no code blocks parse successfully, try scanning for {...} pairs
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const openBraces: number[] = [];
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const closeBraces: number[] = [];
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for (let i = 0; i < content.length; i++) {
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if (content[i] === "{") openBraces.push(i);
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if (content[i] === "}") closeBraces.push(i);
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}
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for (let start = 0; start < content.length; start++) {
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const firstChar = content[start];
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if (firstChar !== "{" && firstChar !== "[") continue;
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// Try pairs from largest span to smallest
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for (const start of openBraces) {
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for (let j = closeBraces.length - 1; j >= 0; j--) {
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const end = closeBraces[j];
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if (end > start) {
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const candidate = content.substring(start, end + 1);
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try {
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const parsed = JSON.parse(candidate);
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if (parsed && typeof parsed === "object") {
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return parsed;
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}
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} catch (e) {
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// ignore and try next
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const stack = [firstChar];
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let inString = false;
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let escaped = false;
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for (let i = start + 1; i < content.length; i++) {
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const char = content[i];
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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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continue;
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}
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if (char === "{" || char === "[") {
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stack.push(char);
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continue;
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}
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const last = stack[stack.length - 1];
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if ((char === "}" && last === "{") || (char === "]" && last === "[")) {
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stack.pop();
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if (stack.length === 0) {
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const candidate = content.slice(start, i + 1);
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try {
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const parsed = JSON.parse(candidate);
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if (parsed && typeof parsed === "object") {
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return parsed;
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}
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} catch (_) {}
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break;
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}
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}
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}
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@@ -447,111 +466,152 @@ Return ONLY valid JSON, no other text.`;
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})
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.slice(0, 8); // Cap at 8 to prevent LLM API limits (e.g. Nemotron/Omni models 8-image limit)
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let messageContent:
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type MessageContent =
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| string
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| Array<{ type: string; text?: string; image_url?: { url: string } }>;
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let imageParts: Array<{
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type: string;
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text?: string;
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image_url?: { url: string };
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}> = [];
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if (imageAttachments.length > 0) {
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const imageParts = await Promise.all(
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imageAttachments.map(async (att) => {
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try {
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const urlToUse = getAttachmentImageUrl(att);
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if (!urlToUse) return [];
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log.info(
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{ attachmentId: att.id, url: urlToUse },
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"Downloading attachment for base64 encoding",
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);
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const res = await fetch(urlToUse);
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if (!res.ok) {
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imageParts = (
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await Promise.all(
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imageAttachments.map(async (att) => {
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try {
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const urlToUse = getAttachmentImageUrl(att);
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if (!urlToUse) return [];
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log.info(
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{ attachmentId: att.id, url: urlToUse },
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"Downloading attachment for base64 encoding",
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);
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const res = await fetch(urlToUse);
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if (!res.ok) {
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log.warn(
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{ attachmentId: att.id, status: res.status },
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"Failed to fetch attachment image",
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);
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return [];
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}
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const buffer = await res.arrayBuffer();
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const base64Str = Buffer.from(buffer).toString("base64");
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const dataUrl = `data:${att.type};base64,${base64Str}`;
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return [
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{
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type: "image_url",
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image_url: {
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url: dataUrl,
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},
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},
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{
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type: "text",
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text: `\n[Image Attachment for Message ID: ${att.message_id}, Filename: ${att.filename}]`,
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},
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];
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} catch (err) {
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log.warn(
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{ attachmentId: att.id, status: res.status },
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"Failed to fetch attachment image",
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{
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attachmentId: att.id,
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error: err instanceof Error ? err.message : String(err),
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},
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"Error base64 encoding attachment",
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);
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return [];
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}
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const buffer = await res.arrayBuffer();
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const base64Str = Buffer.from(buffer).toString("base64");
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const dataUrl = `data:${att.type};base64,${base64Str}`;
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return [
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{
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type: "image_url",
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image_url: {
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url: dataUrl,
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},
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},
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{
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type: "text",
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text: `\n[Image Attachment for Message ID: ${att.message_id}, Filename: ${att.filename}]`,
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},
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];
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} catch (err) {
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log.warn(
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{
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attachmentId: att.id,
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error: err instanceof Error ? err.message : String(err),
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},
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"Error base64 encoding attachment",
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);
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return [];
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}
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}),
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);
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messageContent = [
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...imageParts.flat(),
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{
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type: "text",
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text: moderationPrompt,
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},
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];
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} else {
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messageContent = moderationPrompt;
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}),
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)
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).flat();
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}
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const result = await retryWithBackoff(
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() =>
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openai.chat.completions.create({
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model: config.AI_LLM_MODEL,
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messages: [
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{
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role: "user",
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content: messageContent,
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},
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],
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temperature: 0.2,
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top_p: 0.95,
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max_tokens: 65536,
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response_format: { type: "json_object" },
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stream: false,
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chat_template_kwargs: { enable_thinking: false },
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reasoning_budget: 0,
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} as OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming),
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{
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retries: 3,
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minTimeout: 1000,
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maxTimeout: 10000,
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logger: log,
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},
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);
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let lastParseError: string | null = null;
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let lastInvalidContent: string | null = null;
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const buildMessageContent = (): MessageContent => {
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const correctionPrompt = lastParseError
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? `${moderationPrompt}\n\nPrevious response failed validation. Error: ${lastParseError}\nInvalid response preview:\n${lastInvalidContent?.slice(0, 1000) ?? "<empty>"}\n\nRetry with corrected output. Return ONLY one valid JSON object matching the required schema.`
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: moderationPrompt;
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// Extract content from response
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if (!result.choices || !Array.isArray(result.choices) || !result.choices[0]) {
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throw new Error("Invalid LLM response structure");
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}
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if (imageParts.length > 0) {
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return [
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...imageParts,
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{
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type: "text",
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text: correctionPrompt,
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},
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];
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}
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const content = result.choices[0].message?.content;
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if (!content) {
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throw new Error("No content in LLM response");
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}
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return correctionPrompt;
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};
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// Parse and validate
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let parsed: AnalysisResult[];
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let result: OpenAI.Chat.Completions.ChatCompletion | null = null;
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try {
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parsed = parseModerationResponse(content, targetIds);
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const analysis = await retryWithBackoff(
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async () => {
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const completion = await openai.chat.completions.create({
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model: config.AI_LLM_MODEL,
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messages: [
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{
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role: "user",
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content: buildMessageContent(),
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},
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],
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temperature: 0.2,
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top_p: 0.95,
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max_tokens: 65536,
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response_format: { type: "json_object" },
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stream: false,
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chat_template_kwargs: { enable_thinking: false },
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reasoning_budget: 0,
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} as OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming);
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if (
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!completion.choices ||
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!Array.isArray(completion.choices) ||
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!completion.choices[0]
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) {
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throw new Error("Invalid LLM response structure");
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}
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const content = completion.choices[0].message?.content;
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if (!content) {
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throw new Error("No content in LLM response");
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}
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try {
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return {
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parsed: parseModerationResponse(content, targetIds),
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result: completion,
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};
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} catch (parseError) {
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lastParseError =
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parseError instanceof Error
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? parseError.message
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: String(parseError);
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lastInvalidContent = content;
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throw parseError;
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}
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},
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{
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retries: 3,
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minTimeout: 1000,
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maxTimeout: 10000,
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logger: log,
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},
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);
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parsed = analysis.parsed;
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result = analysis.result;
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} catch (parseError) {
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if (!lastInvalidContent) {
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throw parseError;
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}
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const errorMsg =
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parseError instanceof Error ? parseError.message : String(parseError);
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const content: string = lastInvalidContent;
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const salvaged = salvageMalformedModerationResponse(content, targetIds);
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if (salvaged) {
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log.warn(
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