mirror of
https://github.com/DayuanJiang/next-ai-draw-io.git
synced 2026-01-02 14:22:28 +08:00
chore: add Biome for formatting and linting (#116)
- Add Biome as formatter and linter (replaces Prettier) - Configure Husky + lint-staged for pre-commit hooks - Add VS Code settings for format on save - Ignore components/ui/ (shadcn generated code) - Remove semicolons, use 4-space indent - Reformat all files to new style
This commit is contained in:
Dayuan Jiang
@@ -1,247 +1,299 @@
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import { streamText, convertToModelMessages, createUIMessageStream, createUIMessageStreamResponse } from 'ai';
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import { getAIModel } from '@/lib/ai-providers';
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import { findCachedResponse } from '@/lib/cached-responses';
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import { setTraceInput, setTraceOutput, getTelemetryConfig, wrapWithObserve } from '@/lib/langfuse';
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import { getSystemPrompt } from '@/lib/system-prompts';
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import { z } from "zod";
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import {
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convertToModelMessages,
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createUIMessageStream,
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createUIMessageStreamResponse,
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streamText,
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} from "ai"
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import { z } from "zod"
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import { getAIModel } from "@/lib/ai-providers"
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import { findCachedResponse } from "@/lib/cached-responses"
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import {
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getTelemetryConfig,
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setTraceInput,
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setTraceOutput,
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wrapWithObserve,
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} from "@/lib/langfuse"
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import { getSystemPrompt } from "@/lib/system-prompts"
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export const maxDuration = 300;
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export const maxDuration = 300
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// File upload limits (must match client-side)
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const MAX_FILE_SIZE = 2 * 1024 * 1024; // 2MB
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const MAX_FILES = 5;
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const MAX_FILE_SIZE = 2 * 1024 * 1024 // 2MB
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const MAX_FILES = 5
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// Helper function to validate file parts in messages
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function validateFileParts(messages: any[]): { valid: boolean; error?: string } {
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const lastMessage = messages[messages.length - 1];
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const fileParts = lastMessage?.parts?.filter((p: any) => p.type === 'file') || [];
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function validateFileParts(messages: any[]): {
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valid: boolean
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error?: string
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} {
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const lastMessage = messages[messages.length - 1]
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const fileParts =
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lastMessage?.parts?.filter((p: any) => p.type === "file") || []
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if (fileParts.length > MAX_FILES) {
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return { valid: false, error: `Too many files. Maximum ${MAX_FILES} allowed.` };
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}
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for (const filePart of fileParts) {
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// Data URLs format: data:image/png;base64,<data>
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// Base64 increases size by ~33%, so we check the decoded size
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if (filePart.url && filePart.url.startsWith('data:')) {
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const base64Data = filePart.url.split(',')[1];
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if (base64Data) {
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const sizeInBytes = Math.ceil((base64Data.length * 3) / 4);
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if (sizeInBytes > MAX_FILE_SIZE) {
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return { valid: false, error: `File exceeds ${MAX_FILE_SIZE / 1024 / 1024}MB limit.` };
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if (fileParts.length > MAX_FILES) {
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return {
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valid: false,
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error: `Too many files. Maximum ${MAX_FILES} allowed.`,
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}
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}
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}
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}
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return { valid: true };
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for (const filePart of fileParts) {
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// Data URLs format: data:image/png;base64,<data>
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// Base64 increases size by ~33%, so we check the decoded size
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if (filePart.url && filePart.url.startsWith("data:")) {
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const base64Data = filePart.url.split(",")[1]
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if (base64Data) {
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const sizeInBytes = Math.ceil((base64Data.length * 3) / 4)
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if (sizeInBytes > MAX_FILE_SIZE) {
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return {
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valid: false,
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error: `File exceeds ${MAX_FILE_SIZE / 1024 / 1024}MB limit.`,
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}
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}
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}
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}
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}
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return { valid: true }
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}
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// Helper function to check if diagram is minimal/empty
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function isMinimalDiagram(xml: string): boolean {
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const stripped = xml.replace(/\s/g, '');
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return !stripped.includes('id="2"');
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const stripped = xml.replace(/\s/g, "")
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return !stripped.includes('id="2"')
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}
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// Helper function to create cached stream response
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function createCachedStreamResponse(xml: string): Response {
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const toolCallId = `cached-${Date.now()}`;
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const toolCallId = `cached-${Date.now()}`
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const stream = createUIMessageStream({
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execute: async ({ writer }) => {
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writer.write({ type: 'start' });
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writer.write({ type: 'tool-input-start', toolCallId, toolName: 'display_diagram' });
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writer.write({ type: 'tool-input-delta', toolCallId, inputTextDelta: xml });
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writer.write({ type: 'tool-input-available', toolCallId, toolName: 'display_diagram', input: { xml } });
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writer.write({ type: 'finish' });
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},
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});
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const stream = createUIMessageStream({
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execute: async ({ writer }) => {
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writer.write({ type: "start" })
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writer.write({
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type: "tool-input-start",
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toolCallId,
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toolName: "display_diagram",
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})
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writer.write({
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type: "tool-input-delta",
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toolCallId,
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inputTextDelta: xml,
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})
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writer.write({
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type: "tool-input-available",
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toolCallId,
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toolName: "display_diagram",
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input: { xml },
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})
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writer.write({ type: "finish" })
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},
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})
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return createUIMessageStreamResponse({ stream });
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return createUIMessageStreamResponse({ stream })
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}
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// Inner handler function
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async function handleChatRequest(req: Request): Promise<Response> {
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// Check for access code
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const accessCodes = process.env.ACCESS_CODE_LIST?.split(',').map(code => code.trim()).filter(Boolean) || [];
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if (accessCodes.length > 0) {
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const accessCodeHeader = req.headers.get('x-access-code');
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if (!accessCodeHeader || !accessCodes.includes(accessCodeHeader)) {
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return Response.json(
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{ error: 'Invalid or missing access code. Please configure it in Settings.' },
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{ status: 401 }
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);
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// Check for access code
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const accessCodes =
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process.env.ACCESS_CODE_LIST?.split(",")
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.map((code) => code.trim())
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.filter(Boolean) || []
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if (accessCodes.length > 0) {
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const accessCodeHeader = req.headers.get("x-access-code")
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if (!accessCodeHeader || !accessCodes.includes(accessCodeHeader)) {
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return Response.json(
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{
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error: "Invalid or missing access code. Please configure it in Settings.",
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},
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{ status: 401 },
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)
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}
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}
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}
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const { messages, xml, sessionId } = await req.json();
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const { messages, xml, sessionId } = await req.json()
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// Get user IP for Langfuse tracking
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const forwardedFor = req.headers.get('x-forwarded-for');
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const userId = forwardedFor?.split(',')[0]?.trim() || 'anonymous';
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// Get user IP for Langfuse tracking
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const forwardedFor = req.headers.get("x-forwarded-for")
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const userId = forwardedFor?.split(",")[0]?.trim() || "anonymous"
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// Validate sessionId for Langfuse (must be string, max 200 chars)
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const validSessionId = sessionId && typeof sessionId === 'string' && sessionId.length <= 200
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? sessionId
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: undefined;
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// Validate sessionId for Langfuse (must be string, max 200 chars)
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const validSessionId =
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sessionId && typeof sessionId === "string" && sessionId.length <= 200
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? sessionId
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: undefined
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// Extract user input text for Langfuse trace
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const currentMessage = messages[messages.length - 1];
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const userInputText = currentMessage?.parts?.find((p: any) => p.type === 'text')?.text || '';
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// Extract user input text for Langfuse trace
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const currentMessage = messages[messages.length - 1]
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const userInputText =
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currentMessage?.parts?.find((p: any) => p.type === "text")?.text || ""
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// Update Langfuse trace with input, session, and user
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setTraceInput({
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input: userInputText,
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sessionId: validSessionId,
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userId: userId,
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});
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// Update Langfuse trace with input, session, and user
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setTraceInput({
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input: userInputText,
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sessionId: validSessionId,
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userId: userId,
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})
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// === FILE VALIDATION START ===
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const fileValidation = validateFileParts(messages);
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if (!fileValidation.valid) {
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return Response.json({ error: fileValidation.error }, { status: 400 });
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}
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// === FILE VALIDATION END ===
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// === CACHE CHECK START ===
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const isFirstMessage = messages.length === 1;
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const isEmptyDiagram = !xml || xml.trim() === '' || isMinimalDiagram(xml);
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if (isFirstMessage && isEmptyDiagram) {
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const lastMessage = messages[0];
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const textPart = lastMessage.parts?.find((p: any) => p.type === 'text');
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const filePart = lastMessage.parts?.find((p: any) => p.type === 'file');
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const cached = findCachedResponse(textPart?.text || '', !!filePart);
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if (cached) {
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console.log('[Cache] Returning cached response for:', textPart?.text);
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return createCachedStreamResponse(cached.xml);
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// === FILE VALIDATION START ===
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const fileValidation = validateFileParts(messages)
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if (!fileValidation.valid) {
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return Response.json({ error: fileValidation.error }, { status: 400 })
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}
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}
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// === CACHE CHECK END ===
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// === FILE VALIDATION END ===
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// Get AI model from environment configuration
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const { model, providerOptions, headers, modelId } = getAIModel();
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// === CACHE CHECK START ===
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const isFirstMessage = messages.length === 1
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const isEmptyDiagram = !xml || xml.trim() === "" || isMinimalDiagram(xml)
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// Get the appropriate system prompt based on model (extended for Opus/Haiku 4.5)
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const systemMessage = getSystemPrompt(modelId);
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if (isFirstMessage && isEmptyDiagram) {
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const lastMessage = messages[0]
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const textPart = lastMessage.parts?.find((p: any) => p.type === "text")
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const filePart = lastMessage.parts?.find((p: any) => p.type === "file")
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const lastMessage = messages[messages.length - 1];
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const cached = findCachedResponse(textPart?.text || "", !!filePart)
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// Extract text from the last message parts
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const lastMessageText = lastMessage.parts?.find((part: any) => part.type === 'text')?.text || '';
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if (cached) {
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console.log(
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"[Cache] Returning cached response for:",
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textPart?.text,
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)
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return createCachedStreamResponse(cached.xml)
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}
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}
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// === CACHE CHECK END ===
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// Extract file parts (images) from the last message
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const fileParts = lastMessage.parts?.filter((part: any) => part.type === 'file') || [];
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// Get AI model from environment configuration
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const { model, providerOptions, headers, modelId } = getAIModel()
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// User input only - XML is now in a separate cached system message
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const formattedUserInput = `User input:
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// Get the appropriate system prompt based on model (extended for Opus/Haiku 4.5)
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const systemMessage = getSystemPrompt(modelId)
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const lastMessage = messages[messages.length - 1]
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// Extract text from the last message parts
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const lastMessageText =
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lastMessage.parts?.find((part: any) => part.type === "text")?.text || ""
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// Extract file parts (images) from the last message
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const fileParts =
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lastMessage.parts?.filter((part: any) => part.type === "file") || []
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// User input only - XML is now in a separate cached system message
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const formattedUserInput = `User input:
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"""md
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${lastMessageText}
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"""`;
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"""`
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// Convert UIMessages to ModelMessages and add system message
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const modelMessages = convertToModelMessages(messages);
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// Convert UIMessages to ModelMessages and add system message
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const modelMessages = convertToModelMessages(messages)
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// Filter out messages with empty content arrays (Bedrock API rejects these)
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// This is a safety measure - ideally convertToModelMessages should handle all cases
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let enhancedMessages = modelMessages.filter((msg: any) =>
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msg.content && Array.isArray(msg.content) && msg.content.length > 0
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);
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// Filter out messages with empty content arrays (Bedrock API rejects these)
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// This is a safety measure - ideally convertToModelMessages should handle all cases
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let enhancedMessages = modelMessages.filter(
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(msg: any) =>
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msg.content && Array.isArray(msg.content) && msg.content.length > 0,
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)
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// Update the last message with user input only (XML moved to separate cached system message)
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if (enhancedMessages.length >= 1) {
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const lastModelMessage = enhancedMessages[enhancedMessages.length - 1];
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if (lastModelMessage.role === 'user') {
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// Build content array with user input text and file parts
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const contentParts: any[] = [
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{ type: 'text', text: formattedUserInput }
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];
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// Update the last message with user input only (XML moved to separate cached system message)
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if (enhancedMessages.length >= 1) {
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const lastModelMessage = enhancedMessages[enhancedMessages.length - 1]
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if (lastModelMessage.role === "user") {
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// Build content array with user input text and file parts
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const contentParts: any[] = [
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{ type: "text", text: formattedUserInput },
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]
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|
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// Add image parts back
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for (const filePart of fileParts) {
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contentParts.push({
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type: 'image',
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image: filePart.url,
|
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mimeType: filePart.mediaType
|
||||
});
|
||||
}
|
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// Add image parts back
|
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for (const filePart of fileParts) {
|
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contentParts.push({
|
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type: "image",
|
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image: filePart.url,
|
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mimeType: filePart.mediaType,
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})
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}
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|
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enhancedMessages = [
|
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...enhancedMessages.slice(0, -1),
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{ ...lastModelMessage, content: contentParts }
|
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];
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enhancedMessages = [
|
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...enhancedMessages.slice(0, -1),
|
||||
{ ...lastModelMessage, content: contentParts },
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Add cache point to the last assistant message in conversation history
|
||||
// This caches the entire conversation prefix for subsequent requests
|
||||
// Strategy: system (cached) + history with last assistant (cached) + new user message
|
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if (enhancedMessages.length >= 2) {
|
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// Find the last assistant message (should be second-to-last, before current user message)
|
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for (let i = enhancedMessages.length - 2; i >= 0; i--) {
|
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if (enhancedMessages[i].role === 'assistant') {
|
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enhancedMessages[i] = {
|
||||
...enhancedMessages[i],
|
||||
providerOptions: {
|
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bedrock: { cachePoint: { type: 'default' } },
|
||||
},
|
||||
};
|
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break; // Only cache the last assistant message
|
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}
|
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// Add cache point to the last assistant message in conversation history
|
||||
// This caches the entire conversation prefix for subsequent requests
|
||||
// Strategy: system (cached) + history with last assistant (cached) + new user message
|
||||
if (enhancedMessages.length >= 2) {
|
||||
// Find the last assistant message (should be second-to-last, before current user message)
|
||||
for (let i = enhancedMessages.length - 2; i >= 0; i--) {
|
||||
if (enhancedMessages[i].role === "assistant") {
|
||||
enhancedMessages[i] = {
|
||||
...enhancedMessages[i],
|
||||
providerOptions: {
|
||||
bedrock: { cachePoint: { type: "default" } },
|
||||
},
|
||||
}
|
||||
break // Only cache the last assistant message
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// System messages with multiple cache breakpoints for optimal caching:
|
||||
// - Breakpoint 1: Static instructions (~1500 tokens) - rarely changes
|
||||
// - Breakpoint 2: Current XML context - changes per diagram, but constant within a conversation turn
|
||||
// This allows: if only user message changes, both system caches are reused
|
||||
// if XML changes, instruction cache is still reused
|
||||
const systemMessages = [
|
||||
// Cache breakpoint 1: Instructions (rarely change)
|
||||
{
|
||||
role: 'system' as const,
|
||||
content: systemMessage,
|
||||
providerOptions: {
|
||||
bedrock: { cachePoint: { type: 'default' } },
|
||||
},
|
||||
},
|
||||
// Cache breakpoint 2: Current diagram XML context
|
||||
{
|
||||
role: 'system' as const,
|
||||
content: `Current diagram XML:\n"""xml\n${xml || ''}\n"""\nWhen using edit_diagram, COPY search patterns exactly from this XML - attribute order matters!`,
|
||||
providerOptions: {
|
||||
bedrock: { cachePoint: { type: 'default' } },
|
||||
},
|
||||
},
|
||||
];
|
||||
// System messages with multiple cache breakpoints for optimal caching:
|
||||
// - Breakpoint 1: Static instructions (~1500 tokens) - rarely changes
|
||||
// - Breakpoint 2: Current XML context - changes per diagram, but constant within a conversation turn
|
||||
// This allows: if only user message changes, both system caches are reused
|
||||
// if XML changes, instruction cache is still reused
|
||||
const systemMessages = [
|
||||
// Cache breakpoint 1: Instructions (rarely change)
|
||||
{
|
||||
role: "system" as const,
|
||||
content: systemMessage,
|
||||
providerOptions: {
|
||||
bedrock: { cachePoint: { type: "default" } },
|
||||
},
|
||||
},
|
||||
// Cache breakpoint 2: Current diagram XML context
|
||||
{
|
||||
role: "system" as const,
|
||||
content: `Current diagram XML:\n"""xml\n${xml || ""}\n"""\nWhen using edit_diagram, COPY search patterns exactly from this XML - attribute order matters!`,
|
||||
providerOptions: {
|
||||
bedrock: { cachePoint: { type: "default" } },
|
||||
},
|
||||
},
|
||||
]
|
||||
|
||||
const allMessages = [...systemMessages, ...enhancedMessages];
|
||||
const allMessages = [...systemMessages, ...enhancedMessages]
|
||||
|
||||
const result = streamText({
|
||||
model,
|
||||
messages: allMessages,
|
||||
...(providerOptions && { providerOptions }),
|
||||
...(headers && { headers }),
|
||||
// Langfuse telemetry config (returns undefined if not configured)
|
||||
...(getTelemetryConfig({ sessionId: validSessionId, userId }) && {
|
||||
experimental_telemetry: getTelemetryConfig({ sessionId: validSessionId, userId }),
|
||||
}),
|
||||
onFinish: ({ text, usage, providerMetadata }) => {
|
||||
console.log('[Cache] Full providerMetadata:', JSON.stringify(providerMetadata, null, 2));
|
||||
console.log('[Cache] Usage:', JSON.stringify(usage, null, 2));
|
||||
// Pass usage to Langfuse (Bedrock streaming doesn't auto-report tokens to telemetry)
|
||||
// AI SDK uses inputTokens/outputTokens, Langfuse expects promptTokens/completionTokens
|
||||
setTraceOutput(text, {
|
||||
promptTokens: usage?.inputTokens,
|
||||
completionTokens: usage?.outputTokens,
|
||||
});
|
||||
},
|
||||
tools: {
|
||||
// Client-side tool that will be executed on the client
|
||||
display_diagram: {
|
||||
description: `Display a diagram on draw.io. Pass the XML content inside <root> tags.
|
||||
const result = streamText({
|
||||
model,
|
||||
messages: allMessages,
|
||||
...(providerOptions && { providerOptions }),
|
||||
...(headers && { headers }),
|
||||
// Langfuse telemetry config (returns undefined if not configured)
|
||||
...(getTelemetryConfig({ sessionId: validSessionId, userId }) && {
|
||||
experimental_telemetry: getTelemetryConfig({
|
||||
sessionId: validSessionId,
|
||||
userId,
|
||||
}),
|
||||
}),
|
||||
onFinish: ({ text, usage, providerMetadata }) => {
|
||||
console.log(
|
||||
"[Cache] Full providerMetadata:",
|
||||
JSON.stringify(providerMetadata, null, 2),
|
||||
)
|
||||
console.log("[Cache] Usage:", JSON.stringify(usage, null, 2))
|
||||
// Pass usage to Langfuse (Bedrock streaming doesn't auto-report tokens to telemetry)
|
||||
// AI SDK uses inputTokens/outputTokens, Langfuse expects promptTokens/completionTokens
|
||||
setTraceOutput(text, {
|
||||
promptTokens: usage?.inputTokens,
|
||||
completionTokens: usage?.outputTokens,
|
||||
})
|
||||
},
|
||||
tools: {
|
||||
// Client-side tool that will be executed on the client
|
||||
display_diagram: {
|
||||
description: `Display a diagram on draw.io. Pass the XML content inside <root> tags.
|
||||
|
||||
VALIDATION RULES (XML will be rejected if violated):
|
||||
1. All mxCell elements must be DIRECT children of <root> - never nested
|
||||
@@ -276,12 +328,14 @@ Notes:
|
||||
- For AWS diagrams, use **AWS 2025 icons**.
|
||||
- For animated connectors, add "flowAnimation=1" to edge style.
|
||||
`,
|
||||
inputSchema: z.object({
|
||||
xml: z.string().describe("XML string to be displayed on draw.io")
|
||||
})
|
||||
},
|
||||
edit_diagram: {
|
||||
description: `Edit specific parts of the current diagram by replacing exact line matches. Use this tool to make targeted fixes without regenerating the entire XML.
|
||||
inputSchema: z.object({
|
||||
xml: z
|
||||
.string()
|
||||
.describe("XML string to be displayed on draw.io"),
|
||||
}),
|
||||
},
|
||||
edit_diagram: {
|
||||
description: `Edit specific parts of the current diagram by replacing exact line matches. Use this tool to make targeted fixes without regenerating the entire XML.
|
||||
CRITICAL: Copy-paste the EXACT search pattern from the "Current diagram XML" in system context. Do NOT reorder attributes or reformat - the attribute order in draw.io XML varies and you MUST match it exactly.
|
||||
IMPORTANT: Keep edits concise:
|
||||
- COPY the exact mxCell line from the current XML (attribute order matters!)
|
||||
@@ -289,33 +343,48 @@ IMPORTANT: Keep edits concise:
|
||||
- Break large changes into multiple smaller edits
|
||||
- Each search must contain complete lines (never truncate mid-line)
|
||||
- First match only - be specific enough to target the right element`,
|
||||
inputSchema: z.object({
|
||||
edits: z.array(z.object({
|
||||
search: z.string().describe("EXACT lines copied from current XML (preserve attribute order!)"),
|
||||
replace: z.string().describe("Replacement lines")
|
||||
})).describe("Array of search/replace pairs to apply sequentially")
|
||||
})
|
||||
},
|
||||
},
|
||||
temperature: 0,
|
||||
});
|
||||
inputSchema: z.object({
|
||||
edits: z
|
||||
.array(
|
||||
z.object({
|
||||
search: z
|
||||
.string()
|
||||
.describe(
|
||||
"EXACT lines copied from current XML (preserve attribute order!)",
|
||||
),
|
||||
replace: z
|
||||
.string()
|
||||
.describe("Replacement lines"),
|
||||
}),
|
||||
)
|
||||
.describe(
|
||||
"Array of search/replace pairs to apply sequentially",
|
||||
),
|
||||
}),
|
||||
},
|
||||
},
|
||||
temperature: 0,
|
||||
})
|
||||
|
||||
return result.toUIMessageStreamResponse();
|
||||
return result.toUIMessageStreamResponse()
|
||||
}
|
||||
|
||||
// Wrap handler with error handling
|
||||
async function safeHandler(req: Request): Promise<Response> {
|
||||
try {
|
||||
return await handleChatRequest(req);
|
||||
} catch (error) {
|
||||
console.error('Error in chat route:', error);
|
||||
return Response.json({ error: 'Internal server error' }, { status: 500 });
|
||||
}
|
||||
try {
|
||||
return await handleChatRequest(req)
|
||||
} catch (error) {
|
||||
console.error("Error in chat route:", error)
|
||||
return Response.json(
|
||||
{ error: "Internal server error" },
|
||||
{ status: 500 },
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
// Wrap with Langfuse observe (if configured)
|
||||
const observedHandler = wrapWithObserve(safeHandler);
|
||||
const observedHandler = wrapWithObserve(safeHandler)
|
||||
|
||||
export async function POST(req: Request) {
|
||||
return observedHandler(req);
|
||||
return observedHandler(req)
|
||||
}
|
||||
|
||||
@@ -1,9 +1,12 @@
|
||||
import { NextResponse } from "next/server";
|
||||
import { NextResponse } from "next/server"
|
||||
|
||||
export async function GET() {
|
||||
const accessCodes = process.env.ACCESS_CODE_LIST?.split(',').map(code => code.trim()).filter(Boolean) || [];
|
||||
const accessCodes =
|
||||
process.env.ACCESS_CODE_LIST?.split(",")
|
||||
.map((code) => code.trim())
|
||||
.filter(Boolean) || []
|
||||
|
||||
return NextResponse.json({
|
||||
accessCodeRequired: accessCodes.length > 0,
|
||||
});
|
||||
return NextResponse.json({
|
||||
accessCodeRequired: accessCodes.length > 0,
|
||||
})
|
||||
}
|
||||
|
||||
@@ -1,103 +1,112 @@
|
||||
import { getLangfuseClient } from '@/lib/langfuse';
|
||||
import { randomUUID } from 'crypto';
|
||||
import { z } from 'zod';
|
||||
import { randomUUID } from "crypto"
|
||||
import { z } from "zod"
|
||||
import { getLangfuseClient } from "@/lib/langfuse"
|
||||
|
||||
const feedbackSchema = z.object({
|
||||
messageId: z.string().min(1).max(200),
|
||||
feedback: z.enum(['good', 'bad']),
|
||||
sessionId: z.string().min(1).max(200).optional(),
|
||||
});
|
||||
messageId: z.string().min(1).max(200),
|
||||
feedback: z.enum(["good", "bad"]),
|
||||
sessionId: z.string().min(1).max(200).optional(),
|
||||
})
|
||||
|
||||
export async function POST(req: Request) {
|
||||
const langfuse = getLangfuseClient();
|
||||
if (!langfuse) {
|
||||
return Response.json({ success: true, logged: false });
|
||||
}
|
||||
|
||||
// Validate input
|
||||
let data;
|
||||
try {
|
||||
data = feedbackSchema.parse(await req.json());
|
||||
} catch {
|
||||
return Response.json({ success: false, error: 'Invalid input' }, { status: 400 });
|
||||
}
|
||||
|
||||
const { messageId, feedback, sessionId } = data;
|
||||
|
||||
// Get user IP for tracking
|
||||
const forwardedFor = req.headers.get('x-forwarded-for');
|
||||
const userId = forwardedFor?.split(',')[0]?.trim() || 'anonymous';
|
||||
|
||||
try {
|
||||
// Find the most recent chat trace for this session to attach the score to
|
||||
const tracesResponse = await langfuse.api.trace.list({
|
||||
sessionId,
|
||||
limit: 1,
|
||||
});
|
||||
|
||||
const traces = tracesResponse.data || [];
|
||||
const latestTrace = traces[0];
|
||||
|
||||
if (!latestTrace) {
|
||||
// No trace found for this session - create a standalone feedback trace
|
||||
const traceId = randomUUID();
|
||||
const timestamp = new Date().toISOString();
|
||||
|
||||
await langfuse.api.ingestion.batch({
|
||||
batch: [
|
||||
{
|
||||
type: 'trace-create',
|
||||
id: randomUUID(),
|
||||
timestamp,
|
||||
body: {
|
||||
id: traceId,
|
||||
name: 'user-feedback',
|
||||
sessionId,
|
||||
userId,
|
||||
input: { messageId, feedback },
|
||||
metadata: { source: 'feedback-button', note: 'standalone - no chat trace found' },
|
||||
timestamp,
|
||||
},
|
||||
},
|
||||
{
|
||||
type: 'score-create',
|
||||
id: randomUUID(),
|
||||
timestamp,
|
||||
body: {
|
||||
id: randomUUID(),
|
||||
traceId,
|
||||
name: 'user-feedback',
|
||||
value: feedback === 'good' ? 1 : 0,
|
||||
comment: `User gave ${feedback} feedback`,
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
} else {
|
||||
// Attach score to the existing chat trace
|
||||
const timestamp = new Date().toISOString();
|
||||
|
||||
await langfuse.api.ingestion.batch({
|
||||
batch: [
|
||||
{
|
||||
type: 'score-create',
|
||||
id: randomUUID(),
|
||||
timestamp,
|
||||
body: {
|
||||
id: randomUUID(),
|
||||
traceId: latestTrace.id,
|
||||
name: 'user-feedback',
|
||||
value: feedback === 'good' ? 1 : 0,
|
||||
comment: `User gave ${feedback} feedback`,
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
const langfuse = getLangfuseClient()
|
||||
if (!langfuse) {
|
||||
return Response.json({ success: true, logged: false })
|
||||
}
|
||||
|
||||
return Response.json({ success: true, logged: true });
|
||||
} catch (error) {
|
||||
console.error('Langfuse feedback error:', error);
|
||||
return Response.json({ success: false, error: 'Failed to log feedback' }, { status: 500 });
|
||||
}
|
||||
// Validate input
|
||||
let data
|
||||
try {
|
||||
data = feedbackSchema.parse(await req.json())
|
||||
} catch {
|
||||
return Response.json(
|
||||
{ success: false, error: "Invalid input" },
|
||||
{ status: 400 },
|
||||
)
|
||||
}
|
||||
|
||||
const { messageId, feedback, sessionId } = data
|
||||
|
||||
// Get user IP for tracking
|
||||
const forwardedFor = req.headers.get("x-forwarded-for")
|
||||
const userId = forwardedFor?.split(",")[0]?.trim() || "anonymous"
|
||||
|
||||
try {
|
||||
// Find the most recent chat trace for this session to attach the score to
|
||||
const tracesResponse = await langfuse.api.trace.list({
|
||||
sessionId,
|
||||
limit: 1,
|
||||
})
|
||||
|
||||
const traces = tracesResponse.data || []
|
||||
const latestTrace = traces[0]
|
||||
|
||||
if (!latestTrace) {
|
||||
// No trace found for this session - create a standalone feedback trace
|
||||
const traceId = randomUUID()
|
||||
const timestamp = new Date().toISOString()
|
||||
|
||||
await langfuse.api.ingestion.batch({
|
||||
batch: [
|
||||
{
|
||||
type: "trace-create",
|
||||
id: randomUUID(),
|
||||
timestamp,
|
||||
body: {
|
||||
id: traceId,
|
||||
name: "user-feedback",
|
||||
sessionId,
|
||||
userId,
|
||||
input: { messageId, feedback },
|
||||
metadata: {
|
||||
source: "feedback-button",
|
||||
note: "standalone - no chat trace found",
|
||||
},
|
||||
timestamp,
|
||||
},
|
||||
},
|
||||
{
|
||||
type: "score-create",
|
||||
id: randomUUID(),
|
||||
timestamp,
|
||||
body: {
|
||||
id: randomUUID(),
|
||||
traceId,
|
||||
name: "user-feedback",
|
||||
value: feedback === "good" ? 1 : 0,
|
||||
comment: `User gave ${feedback} feedback`,
|
||||
},
|
||||
},
|
||||
],
|
||||
})
|
||||
} else {
|
||||
// Attach score to the existing chat trace
|
||||
const timestamp = new Date().toISOString()
|
||||
|
||||
await langfuse.api.ingestion.batch({
|
||||
batch: [
|
||||
{
|
||||
type: "score-create",
|
||||
id: randomUUID(),
|
||||
timestamp,
|
||||
body: {
|
||||
id: randomUUID(),
|
||||
traceId: latestTrace.id,
|
||||
name: "user-feedback",
|
||||
value: feedback === "good" ? 1 : 0,
|
||||
comment: `User gave ${feedback} feedback`,
|
||||
},
|
||||
},
|
||||
],
|
||||
})
|
||||
}
|
||||
|
||||
return Response.json({ success: true, logged: true })
|
||||
} catch (error) {
|
||||
console.error("Langfuse feedback error:", error)
|
||||
return Response.json(
|
||||
{ success: false, error: "Failed to log feedback" },
|
||||
{ status: 500 },
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,65 +1,71 @@
|
||||
import { getLangfuseClient } from '@/lib/langfuse';
|
||||
import { randomUUID } from 'crypto';
|
||||
import { z } from 'zod';
|
||||
import { randomUUID } from "crypto"
|
||||
import { z } from "zod"
|
||||
import { getLangfuseClient } from "@/lib/langfuse"
|
||||
|
||||
const saveSchema = z.object({
|
||||
filename: z.string().min(1).max(255),
|
||||
format: z.enum(['drawio', 'png', 'svg']),
|
||||
sessionId: z.string().min(1).max(200).optional(),
|
||||
});
|
||||
filename: z.string().min(1).max(255),
|
||||
format: z.enum(["drawio", "png", "svg"]),
|
||||
sessionId: z.string().min(1).max(200).optional(),
|
||||
})
|
||||
|
||||
export async function POST(req: Request) {
|
||||
const langfuse = getLangfuseClient();
|
||||
if (!langfuse) {
|
||||
return Response.json({ success: true, logged: false });
|
||||
}
|
||||
|
||||
// Validate input
|
||||
let data;
|
||||
try {
|
||||
data = saveSchema.parse(await req.json());
|
||||
} catch {
|
||||
return Response.json({ success: false, error: 'Invalid input' }, { status: 400 });
|
||||
}
|
||||
|
||||
const { filename, format, sessionId } = data;
|
||||
|
||||
try {
|
||||
const timestamp = new Date().toISOString();
|
||||
|
||||
// Find the most recent chat trace for this session to attach the save flag
|
||||
const tracesResponse = await langfuse.api.trace.list({
|
||||
sessionId,
|
||||
limit: 1,
|
||||
});
|
||||
|
||||
const traces = tracesResponse.data || [];
|
||||
const latestTrace = traces[0];
|
||||
|
||||
if (latestTrace) {
|
||||
// Add a score to the existing trace to flag that user saved
|
||||
await langfuse.api.ingestion.batch({
|
||||
batch: [
|
||||
{
|
||||
type: 'score-create',
|
||||
id: randomUUID(),
|
||||
timestamp,
|
||||
body: {
|
||||
id: randomUUID(),
|
||||
traceId: latestTrace.id,
|
||||
name: 'diagram-saved',
|
||||
value: 1,
|
||||
comment: `User saved diagram as ${filename}.${format}`,
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
const langfuse = getLangfuseClient()
|
||||
if (!langfuse) {
|
||||
return Response.json({ success: true, logged: false })
|
||||
}
|
||||
// If no trace found, skip logging (user hasn't chatted yet)
|
||||
|
||||
return Response.json({ success: true, logged: !!latestTrace });
|
||||
} catch (error) {
|
||||
console.error('Langfuse save error:', error);
|
||||
return Response.json({ success: false, error: 'Failed to log save' }, { status: 500 });
|
||||
}
|
||||
// Validate input
|
||||
let data
|
||||
try {
|
||||
data = saveSchema.parse(await req.json())
|
||||
} catch {
|
||||
return Response.json(
|
||||
{ success: false, error: "Invalid input" },
|
||||
{ status: 400 },
|
||||
)
|
||||
}
|
||||
|
||||
const { filename, format, sessionId } = data
|
||||
|
||||
try {
|
||||
const timestamp = new Date().toISOString()
|
||||
|
||||
// Find the most recent chat trace for this session to attach the save flag
|
||||
const tracesResponse = await langfuse.api.trace.list({
|
||||
sessionId,
|
||||
limit: 1,
|
||||
})
|
||||
|
||||
const traces = tracesResponse.data || []
|
||||
const latestTrace = traces[0]
|
||||
|
||||
if (latestTrace) {
|
||||
// Add a score to the existing trace to flag that user saved
|
||||
await langfuse.api.ingestion.batch({
|
||||
batch: [
|
||||
{
|
||||
type: "score-create",
|
||||
id: randomUUID(),
|
||||
timestamp,
|
||||
body: {
|
||||
id: randomUUID(),
|
||||
traceId: latestTrace.id,
|
||||
name: "diagram-saved",
|
||||
value: 1,
|
||||
comment: `User saved diagram as ${filename}.${format}`,
|
||||
},
|
||||
},
|
||||
],
|
||||
})
|
||||
}
|
||||
// If no trace found, skip logging (user hasn't chatted yet)
|
||||
|
||||
return Response.json({ success: true, logged: !!latestTrace })
|
||||
} catch (error) {
|
||||
console.error("Langfuse save error:", error)
|
||||
return Response.json(
|
||||
{ success: false, error: "Failed to log save" },
|
||||
{ status: 500 },
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user