mirror of
https://github.com/DayuanJiang/next-ai-draw-io.git
synced 2026-09-02 01:20:23 +08:00
6c6cf98019
* fix: merge system messages for custom OpenAI endpoints (fixes #734) When using the OpenAI provider with a custom base URL (e.g., vLLM, LMStudio), the app sends two system messages to the API. Open-source model chat templates (Qwen, Llama, etc.) enforce that system messages must appear at the beginning and reject multiple system message blocks, causing the error: 'System message must be at the beginning.' Treat custom OpenAI endpoints (client-provided base URL or OPENAI_BASE_URL env var) the same as other known single-system providers by merging both system messages into one before sending. * fix: also detect custom OpenAI endpoint from serverModelConfig.baseUrlEnv --------- Co-authored-by: dayuan.jiang <jdy.toh@gmail.com>
870 lines
34 KiB
TypeScript
870 lines
34 KiB
TypeScript
import {
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APICallError,
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convertToModelMessages,
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createUIMessageStream,
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createUIMessageStreamResponse,
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InvalidToolInputError,
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LoadAPIKeyError,
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stepCountIs,
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streamText,
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} from "ai"
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import fs from "fs/promises"
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import { jsonrepair } from "jsonrepair"
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import path from "path"
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import { z } from "zod"
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import {
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getAIModel,
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SINGLE_SYSTEM_PROVIDERS,
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supportsImageInput,
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supportsPromptCaching,
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} from "@/lib/ai-providers"
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import { findCachedResponse } from "@/lib/cached-responses"
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import {
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isMinimalDiagram,
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replaceHistoricalToolInputs,
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validateFileParts,
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} from "@/lib/chat-helpers"
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import {
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checkAndIncrementRequest,
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isQuotaEnabled,
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recordTokenUsage,
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} from "@/lib/dynamo-quota-manager"
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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 { findServerModelById } from "@/lib/server-model-config"
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import { getSystemPrompt } from "@/lib/system-prompts"
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import { getUserIdFromRequest } from "@/lib/user-id"
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export const maxDuration = 120
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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 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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}
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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 =
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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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const body = await req.json()
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const { messages, xml, previousXml, sessionId } = body
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const customSystemMessage =
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typeof body.customSystemMessage === "string"
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? body.customSystemMessage.slice(0, 5000)
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: ""
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// Get user ID for Langfuse tracking and quota
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const userId = getUserIdFromRequest(req)
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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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// Find the last USER message, not just the last message (which could be assistant in multi-step tool flows)
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const lastUserMessage = [...messages]
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.reverse()
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.find((m: any) => m.role === "user")
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const userInputText =
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lastUserMessage?.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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// === SERVER-SIDE QUOTA CHECK START ===
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// Quota is opt-in: only enabled when DYNAMODB_QUOTA_TABLE env var is set
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const hasOwnApiKey = !!(
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req.headers.get("x-ai-provider") &&
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(req.headers.get("x-ai-api-key") ||
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req.headers.get("x-aws-access-key-id") ||
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req.headers.get("x-vertex-api-key"))
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)
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// Skip quota check if: quota disabled, user has own API key, or is anonymous
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if (isQuotaEnabled() && !hasOwnApiKey && userId !== "anonymous") {
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const quotaCheck = await checkAndIncrementRequest(userId, {
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requests: Number(process.env.DAILY_REQUEST_LIMIT) || 10,
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tokens: Number(process.env.DAILY_TOKEN_LIMIT) || 200000,
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tpm: Number(process.env.TPM_LIMIT) || 20000,
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})
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if (!quotaCheck.allowed) {
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return Response.json(
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{
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error: quotaCheck.error,
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type: quotaCheck.type,
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used: quotaCheck.used,
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limit: quotaCheck.limit,
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},
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{ status: 429 },
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)
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}
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}
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// === SERVER-SIDE QUOTA CHECK END ===
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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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return createCachedStreamResponse(cached.xml)
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}
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}
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// === CACHE CHECK END ===
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// Read client AI provider overrides from headers
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const provider = req.headers.get("x-ai-provider")
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let baseUrl = req.headers.get("x-ai-base-url")
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const selectedModelId = req.headers.get("x-selected-model-id")
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// For EdgeOne provider, construct full URL from request origin
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// because createOpenAI needs absolute URL, not relative path
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if (provider === "edgeone" && !baseUrl) {
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const origin = req.headers.get("origin") || new URL(req.url).origin
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baseUrl = `${origin}/api/edgeai`
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}
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// Get cookie header for EdgeOne authentication (eo_token, eo_time)
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const cookieHeader = req.headers.get("cookie")
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// Check if this is a server model with custom env var names
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let serverModelConfig: {
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apiKeyEnv?: string | string[]
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baseUrlEnv?: string
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provider?: string
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} = {}
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if (selectedModelId?.startsWith("server:")) {
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const serverModel = await findServerModelById(selectedModelId)
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console.log(
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`[Server Model Lookup] ID: ${selectedModelId}, Found: ${!!serverModel}, Provider: ${serverModel?.provider}`,
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)
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if (serverModel) {
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serverModelConfig = {
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apiKeyEnv: serverModel.apiKeyEnv,
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baseUrlEnv: serverModel.baseUrlEnv,
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// Use actual provider from config (client header may have incorrect value due to ID format change)
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provider: serverModel.provider,
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}
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}
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}
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const clientOverrides = {
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// Server model provider takes precedence over client header
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provider: serverModelConfig.provider || provider,
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baseUrl,
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apiKey: req.headers.get("x-ai-api-key"),
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modelId: req.headers.get("x-ai-model"),
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// AWS Bedrock credentials
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awsAccessKeyId: req.headers.get("x-aws-access-key-id"),
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awsSecretAccessKey: req.headers.get("x-aws-secret-access-key"),
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awsRegion: req.headers.get("x-aws-region"),
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awsSessionToken: req.headers.get("x-aws-session-token"),
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// Server model custom env var names
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...serverModelConfig,
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// Vertex AI credentials (Express Mode)
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vertexApiKey: req.headers.get("x-vertex-api-key"),
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// Pass cookies for EdgeOne Pages authentication
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...(provider === "edgeone" &&
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cookieHeader && {
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headers: { cookie: cookieHeader },
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}),
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}
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// Read minimal style preference from header
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const minimalStyle = req.headers.get("x-minimal-style") === "true"
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console.log(
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`[Client Overrides] provider: ${clientOverrides.provider}, modelId: ${clientOverrides.modelId}`,
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)
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// Get AI model with optional client overrides
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const {
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model,
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providerOptions,
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headers,
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modelId,
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provider: resolvedProvider,
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} = getAIModel(clientOverrides)
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// Check if model supports prompt caching
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const shouldCache = supportsPromptCaching(modelId)
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console.log(
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`[Prompt Caching] ${shouldCache ? "ENABLED" : "DISABLED"} for model: ${modelId}`,
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)
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// Get the appropriate system prompt based on model (extended for Opus/Haiku 4.5)
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const systemMessage = getSystemPrompt(modelId, minimalStyle)
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const finalSystemMessage = customSystemMessage
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? `${systemMessage}\n\n## Custom Instructions\n${customSystemMessage}`
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: systemMessage
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// Extract file parts (images) from the last user message
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const fileParts =
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lastUserMessage?.parts?.filter((part: any) => part.type === "file") ||
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[]
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// Check if user is sending images to a model that doesn't support them
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// AI SDK silently drops unsupported parts, so we need to catch this early
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if (fileParts.length > 0 && !supportsImageInput(modelId)) {
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return Response.json(
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{
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error: `The model "${modelId}" does not support image input. Please use a vision-capable model (e.g., GPT-4o, Claude, Gemini) or remove the image.`,
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},
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{ status: 400 },
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)
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}
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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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${userInputText}
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"""`
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// Convert UIMessages to ModelMessages and add system message
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const modelMessages = await convertToModelMessages(messages)
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// DEBUG: Log incoming messages structure
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console.log("[route.ts] Incoming messages count:", messages.length)
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messages.forEach((msg: any, idx: number) => {
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console.log(
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`[route.ts] Message ${idx} role:`,
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msg.role,
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"parts count:",
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msg.parts?.length,
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)
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if (msg.parts) {
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msg.parts.forEach((part: any, partIdx: number) => {
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if (
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part.type === "tool-invocation" ||
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part.type === "tool-result"
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) {
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console.log(`[route.ts] Part ${partIdx}:`, {
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type: part.type,
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toolName: part.toolName,
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hasInput: !!part.input,
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inputType: typeof part.input,
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inputKeys:
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part.input && typeof part.input === "object"
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? Object.keys(part.input)
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: null,
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})
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}
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})
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}
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})
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// Replace historical tool call XML with placeholders to reduce tokens
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// Disabled by default - some models (e.g. minimax) copy placeholders instead of generating XML
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const enableHistoryReplace =
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process.env.ENABLE_HISTORY_XML_REPLACE === "true"
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const placeholderMessages = enableHistoryReplace
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? replaceHistoricalToolInputs(modelMessages)
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: modelMessages
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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 = placeholderMessages.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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// Filter out tool-calls with invalid inputs (from failed repair or interrupted streaming)
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// Bedrock API rejects messages where toolUse.input is not a valid JSON object
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enhancedMessages = enhancedMessages
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.map((msg: any) => {
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if (msg.role !== "assistant" || !Array.isArray(msg.content)) {
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return msg
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}
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const filteredContent = msg.content.filter((part: any) => {
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if (part.type === "tool-call") {
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// Check if input is a valid object (not null, undefined, or empty)
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if (
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!part.input ||
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typeof part.input !== "object" ||
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Object.keys(part.input).length === 0
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) {
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console.warn(
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`[route.ts] Filtering out tool-call with invalid input:`,
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{ toolName: part.toolName, input: part.input },
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)
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return false
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}
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}
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return true
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})
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return { ...msg, content: filteredContent }
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})
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.filter((msg: any) => msg.content && msg.content.length > 0)
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// DEBUG: Log modelMessages structure (what's being sent to AI)
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console.log("[route.ts] Model messages count:", enhancedMessages.length)
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enhancedMessages.forEach((msg: any, idx: number) => {
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console.log(
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`[route.ts] ModelMsg ${idx} role:`,
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msg.role,
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"content count:",
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msg.content?.length,
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)
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if (msg.content) {
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msg.content.forEach((part: any, partIdx: number) => {
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if (part.type === "tool-call" || part.type === "tool-result") {
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console.log(`[route.ts] Content ${partIdx}:`, {
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type: part.type,
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toolName: part.toolName,
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hasInput: !!part.input,
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inputType: typeof part.input,
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inputValue:
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part.input === undefined
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? "undefined"
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: part.input === null
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? "null"
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: "object",
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})
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}
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})
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}
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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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// 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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enhancedMessages = [
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...enhancedMessages.slice(0, -1),
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{ ...lastModelMessage, content: contentParts },
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]
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}
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}
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// Add cache point to the last assistant message in conversation history
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// This caches the entire conversation prefix for subsequent requests
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// Strategy: system (cached) + history with last assistant (cached) + new user message
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if (shouldCache && 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] = {
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...enhancedMessages[i],
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providerOptions: {
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bedrock: { cachePoint: { type: "default" } },
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},
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}
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break // Only cache the last assistant message
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}
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}
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}
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// System messages with multiple cache breakpoints for optimal caching:
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// - Breakpoint 1: System instructions + custom instructions - changes when user updates custom system message
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// - Breakpoint 2: Current XML context - changes per diagram, but constant within a conversation turn
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// Some providers (e.g. MiniMax) don't support multiple system messages
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// Merge them into a single system message for compatibility
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// Also merge for OpenAI-compatible providers with custom base URLs (e.g. vLLM, LMStudio)
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// because open-source model chat templates (Qwen, Llama, etc.) typically reject multiple system messages
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const isCustomOpenAIEndpoint =
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resolvedProvider === "openai" &&
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!!(
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baseUrl ||
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process.env.OPENAI_BASE_URL ||
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(serverModelConfig.baseUrlEnv &&
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process.env[serverModelConfig.baseUrlEnv])
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)
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const isSingleSystemProvider =
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SINGLE_SYSTEM_PROVIDERS.has(resolvedProvider) || isCustomOpenAIEndpoint
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const xmlContext = `${
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previousXml
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? `Previous diagram XML (before user's last message):
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"""xml
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${previousXml}
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"""
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|
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`
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: ""
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}Current diagram XML (AUTHORITATIVE - the source of truth):
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"""xml
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${xml || ""}
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"""
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|
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IMPORTANT: The "Current diagram XML" is the SINGLE SOURCE OF TRUTH for what's on the canvas right now. The user can manually add, delete, or modify shapes directly in draw.io. Always count and describe elements based on the CURRENT XML, not on what you previously generated. If both previous and current XML are shown, compare them to understand what the user changed. When using edit_diagram, COPY search patterns exactly from the CURRENT XML - attribute order matters!`
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|
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const systemMessages = isSingleSystemProvider
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? [
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{
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role: "system" as const,
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content: `${finalSystemMessage}\n\n${xmlContext}`,
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},
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]
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: [
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// Cache breakpoint 1: Instructions (+ optional custom instructions)
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|
{
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role: "system" as const,
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content: finalSystemMessage,
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|
...(shouldCache && {
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providerOptions: {
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bedrock: { cachePoint: { type: "default" } },
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},
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}),
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},
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// Cache breakpoint 2: Previous and Current diagram XML context
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|
{
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role: "system" as const,
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content: xmlContext,
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...(shouldCache && {
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providerOptions: {
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bedrock: { cachePoint: { type: "default" } },
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},
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}),
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},
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]
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const allMessages = [...systemMessages, ...enhancedMessages]
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|
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const result = streamText({
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model,
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abortSignal: req.signal,
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|
...(process.env.MAX_OUTPUT_TOKENS && {
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|
maxOutputTokens: parseInt(process.env.MAX_OUTPUT_TOKENS, 10),
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}),
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|
stopWhen: stepCountIs(5),
|
|
// Repair truncated tool calls when maxOutputTokens is reached mid-JSON
|
|
experimental_repairToolCall: async ({ toolCall, error }) => {
|
|
// DEBUG: Log what we're trying to repair
|
|
console.log(`[repairToolCall] Tool: ${toolCall.toolName}`)
|
|
console.log(
|
|
`[repairToolCall] Error: ${error.name} - ${error.message}`,
|
|
)
|
|
console.log(`[repairToolCall] Input type: ${typeof toolCall.input}`)
|
|
console.log(`[repairToolCall] Input value:`, toolCall.input)
|
|
|
|
// Only attempt repair for invalid tool input (broken JSON from truncation)
|
|
if (
|
|
error instanceof InvalidToolInputError ||
|
|
error.name === "AI_InvalidToolInputError"
|
|
) {
|
|
try {
|
|
// Pre-process to fix common LLM JSON errors that jsonrepair can't handle
|
|
let inputToRepair = toolCall.input
|
|
if (typeof inputToRepair === "string") {
|
|
// Fix `:=` instead of `: ` (LLM sometimes generates this)
|
|
inputToRepair = inputToRepair.replace(/:=/g, ": ")
|
|
// Fix `= "` instead of `: "`
|
|
inputToRepair = inputToRepair.replace(/=\s*"/g, ': "')
|
|
// Fix inconsistent quote escaping in XML attributes within JSON strings
|
|
// Pattern: attribute="value\" where opening quote is unescaped but closing is escaped
|
|
// Example: y="-20\" should be y=\"-20\"
|
|
inputToRepair = inputToRepair.replace(
|
|
/(\w+)="([^"]*?)\\"/g,
|
|
'$1=\\"$2\\"',
|
|
)
|
|
}
|
|
// Use jsonrepair to fix truncated JSON
|
|
const repairedInput = jsonrepair(inputToRepair)
|
|
console.log(
|
|
`[repairToolCall] Repaired truncated JSON for tool: ${toolCall.toolName}`,
|
|
)
|
|
return { ...toolCall, input: repairedInput }
|
|
} catch (repairError) {
|
|
console.warn(
|
|
`[repairToolCall] Failed to repair JSON for tool: ${toolCall.toolName}`,
|
|
repairError,
|
|
)
|
|
// Return a placeholder input to avoid API errors in multi-step
|
|
// The tool will fail gracefully on client side
|
|
if (toolCall.toolName === "edit_diagram") {
|
|
return {
|
|
...toolCall,
|
|
input: {
|
|
operations: [],
|
|
_error: "JSON repair failed - no operations to apply",
|
|
},
|
|
}
|
|
}
|
|
if (toolCall.toolName === "display_diagram") {
|
|
return {
|
|
...toolCall,
|
|
input: {
|
|
xml: "",
|
|
_error: "JSON repair failed - empty diagram",
|
|
},
|
|
}
|
|
}
|
|
return null
|
|
}
|
|
}
|
|
// Don't attempt to repair other errors (like NoSuchToolError)
|
|
return null
|
|
},
|
|
messages: allMessages,
|
|
...(providerOptions && { providerOptions }), // This now includes all reasoning configs
|
|
...(headers && { headers }),
|
|
// Langfuse telemetry config (returns undefined if not configured)
|
|
...(getTelemetryConfig({ sessionId: validSessionId, userId }) && {
|
|
experimental_telemetry: getTelemetryConfig({
|
|
sessionId: validSessionId,
|
|
userId,
|
|
}),
|
|
}),
|
|
onFinish: ({ text, totalUsage }) => {
|
|
// AI SDK 6 telemetry auto-reports token usage on its spans
|
|
setTraceOutput(text)
|
|
|
|
// Record token usage for server-side quota tracking (if enabled)
|
|
// Use totalUsage (cumulative across all steps) instead of usage (final step only)
|
|
// Include all 4 token types: input, output, cache read, cache write
|
|
if (
|
|
isQuotaEnabled() &&
|
|
!hasOwnApiKey &&
|
|
userId !== "anonymous" &&
|
|
totalUsage
|
|
) {
|
|
const totalTokens =
|
|
(totalUsage.inputTokens || 0) +
|
|
(totalUsage.outputTokens || 0) +
|
|
(totalUsage.cachedInputTokens || 0) +
|
|
(totalUsage.inputTokenDetails?.cacheWriteTokens || 0)
|
|
recordTokenUsage(userId, totalTokens)
|
|
}
|
|
},
|
|
tools: {
|
|
// Client-side tool that will be executed on the client
|
|
display_diagram: {
|
|
description: `Display a diagram on draw.io. Pass ONLY the mxCell elements - wrapper tags and root cells are added automatically.
|
|
|
|
VALIDATION RULES (XML will be rejected if violated):
|
|
1. Generate ONLY mxCell elements - NO wrapper tags (<mxfile>, <mxGraphModel>, <root>)
|
|
2. Do NOT include root cells (id="0" or id="1") - they are added automatically
|
|
3. All mxCell elements must be siblings - never nested
|
|
4. Every mxCell needs a unique id (start from "2")
|
|
5. Every mxCell needs a valid parent attribute (use "1" for top-level)
|
|
6. Escape special chars in values: < > & "
|
|
|
|
Example (generate ONLY this - no wrapper tags):
|
|
<mxCell id="lane1" value="Frontend" style="swimlane;" vertex="1" parent="1">
|
|
<mxGeometry x="40" y="40" width="200" height="200" as="geometry"/>
|
|
</mxCell>
|
|
<mxCell id="step1" value="Step 1" style="rounded=1;" vertex="1" parent="lane1">
|
|
<mxGeometry x="20" y="60" width="160" height="40" as="geometry"/>
|
|
</mxCell>
|
|
<mxCell id="lane2" value="Backend" style="swimlane;" vertex="1" parent="1">
|
|
<mxGeometry x="280" y="40" width="200" height="200" as="geometry"/>
|
|
</mxCell>
|
|
<mxCell id="step2" value="Step 2" style="rounded=1;" vertex="1" parent="lane2">
|
|
<mxGeometry x="20" y="60" width="160" height="40" as="geometry"/>
|
|
</mxCell>
|
|
<mxCell id="edge1" style="edgeStyle=orthogonalEdgeStyle;endArrow=classic;" edge="1" parent="1" source="step1" target="step2">
|
|
<mxGeometry relative="1" as="geometry"/>
|
|
</mxCell>
|
|
|
|
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 the current diagram by ID-based operations (update/add/delete cells).
|
|
|
|
Operations:
|
|
- update: Replace an existing cell by its id. Provide cell_id and complete new_xml.
|
|
- add: Add a new cell. Provide cell_id (new unique id) and new_xml.
|
|
- delete: Remove a cell. Cascade is automatic: children AND edges (source/target) are auto-deleted. Only specify ONE cell_id.
|
|
|
|
For update/add, new_xml must be a complete mxCell element including mxGeometry.
|
|
|
|
⚠️ JSON ESCAPING: Every " inside new_xml MUST be escaped as \\". Example: id=\\"5\\" value=\\"Label\\"
|
|
|
|
Example - Add a rectangle:
|
|
{"operations": [{"operation": "add", "cell_id": "rect-1", "new_xml": "<mxCell id=\\"rect-1\\" value=\\"Hello\\" style=\\"rounded=0;\\" vertex=\\"1\\" parent=\\"1\\"><mxGeometry x=\\"100\\" y=\\"100\\" width=\\"120\\" height=\\"60\\" as=\\"geometry\\"/></mxCell>"}]}
|
|
|
|
Example - Delete container (children & edges auto-deleted):
|
|
{"operations": [{"operation": "delete", "cell_id": "2"}]}`,
|
|
inputSchema: z.object({
|
|
operations: z
|
|
.array(
|
|
z.object({
|
|
operation: z
|
|
.enum(["update", "add", "delete"])
|
|
.describe(
|
|
"Operation to perform: add, update, or delete",
|
|
),
|
|
cell_id: z
|
|
.string()
|
|
.describe(
|
|
"The id of the mxCell. Must match the id attribute in new_xml.",
|
|
),
|
|
new_xml: z
|
|
.string()
|
|
.optional()
|
|
.describe(
|
|
"Complete mxCell XML element (required for update/add)",
|
|
),
|
|
}),
|
|
)
|
|
.describe("Array of operations to apply"),
|
|
}),
|
|
},
|
|
append_diagram: {
|
|
description: `Continue generating diagram XML when previous display_diagram output was truncated due to length limits.
|
|
|
|
WHEN TO USE: Only call this tool after display_diagram was truncated (you'll see an error message about truncation).
|
|
|
|
CRITICAL INSTRUCTIONS:
|
|
1. Do NOT include any wrapper tags - just continue the mxCell elements
|
|
2. Continue from EXACTLY where your previous output stopped
|
|
3. Complete the remaining mxCell elements
|
|
4. If still truncated, call append_diagram again with the next fragment
|
|
|
|
Example: If previous output ended with '<mxCell id="x" style="rounded=1', continue with ';" vertex="1">...' and complete the remaining elements.`,
|
|
inputSchema: z.object({
|
|
xml: z
|
|
.string()
|
|
.describe(
|
|
"Continuation XML fragment to append (NO wrapper tags)",
|
|
),
|
|
}),
|
|
},
|
|
get_shape_library: {
|
|
description: `Get draw.io shape/icon library documentation with style syntax and shape names.
|
|
|
|
Available libraries:
|
|
- Cloud: aws4, azure2, gcp2, alibaba_cloud, openstack, salesforce
|
|
- Networking: cisco19, network, kubernetes, vvd, rack
|
|
- Business: bpmn, lean_mapping
|
|
- General: flowchart, basic, arrows2, infographic, sitemap
|
|
- UI/Mockups: android, material_design
|
|
- Enterprise: citrix, sap, mscae, atlassian
|
|
- Engineering: fluidpower, electrical, pid, cabinets, floorplan
|
|
- Icons: webicons
|
|
|
|
Call this tool to get shape names and usage syntax for a specific library.`,
|
|
inputSchema: z.object({
|
|
library: z
|
|
.string()
|
|
.describe(
|
|
"Library name (e.g., 'aws4', 'kubernetes', 'flowchart')",
|
|
),
|
|
}),
|
|
execute: async ({ library }) => {
|
|
// Sanitize input - prevent path traversal attacks
|
|
const sanitizedLibrary = library
|
|
.toLowerCase()
|
|
.replace(/[^a-z0-9_-]/g, "")
|
|
|
|
if (sanitizedLibrary !== library.toLowerCase()) {
|
|
return `Invalid library name "${library}". Use only letters, numbers, underscores, and hyphens.`
|
|
}
|
|
|
|
const baseDir = path.join(
|
|
process.cwd(),
|
|
"docs/shape-libraries",
|
|
)
|
|
const filePath = path.join(
|
|
baseDir,
|
|
`${sanitizedLibrary}.md`,
|
|
)
|
|
|
|
// Verify path stays within expected directory
|
|
const resolvedPath = path.resolve(filePath)
|
|
if (!resolvedPath.startsWith(path.resolve(baseDir))) {
|
|
return `Invalid library path.`
|
|
}
|
|
|
|
try {
|
|
const content = await fs.readFile(filePath, "utf-8")
|
|
return content
|
|
} catch (error) {
|
|
if (
|
|
(error as NodeJS.ErrnoException).code === "ENOENT"
|
|
) {
|
|
return `Library "${library}" not found. Available: aws4, azure2, gcp2, alibaba_cloud, cisco19, kubernetes, network, bpmn, flowchart, basic, arrows2, vvd, salesforce, citrix, sap, mscae, atlassian, fluidpower, electrical, pid, cabinets, floorplan, webicons, infographic, sitemap, android, material_design, lean_mapping, openstack, rack`
|
|
}
|
|
console.error(
|
|
`[get_shape_library] Error loading "${library}":`,
|
|
error,
|
|
)
|
|
return `Error loading library "${library}". Please try again.`
|
|
}
|
|
},
|
|
},
|
|
},
|
|
...(process.env.TEMPERATURE !== undefined && {
|
|
temperature: parseFloat(process.env.TEMPERATURE),
|
|
}),
|
|
})
|
|
|
|
return result.toUIMessageStreamResponse({
|
|
sendReasoning: true,
|
|
messageMetadata: ({ part }) => {
|
|
if (part.type === "finish") {
|
|
const usage = (part as any).totalUsage
|
|
// AI SDK 6 provides totalTokens directly
|
|
return {
|
|
totalTokens: usage?.totalTokens ?? 0,
|
|
finishReason: (part as any).finishReason,
|
|
}
|
|
}
|
|
return undefined
|
|
},
|
|
})
|
|
}
|
|
|
|
// Helper to categorize errors and return appropriate response
|
|
function handleError(error: unknown): Response {
|
|
console.error("Error in chat route:", error)
|
|
|
|
const isDev = process.env.NODE_ENV === "development"
|
|
|
|
// Check for specific AI SDK error types
|
|
if (APICallError.isInstance(error)) {
|
|
return Response.json(
|
|
{
|
|
error: error.message,
|
|
...(isDev && {
|
|
details: error.responseBody,
|
|
stack: error.stack,
|
|
}),
|
|
},
|
|
{ status: error.statusCode || 500 },
|
|
)
|
|
}
|
|
|
|
if (LoadAPIKeyError.isInstance(error)) {
|
|
return Response.json(
|
|
{
|
|
error: "Authentication failed. Please check your API key.",
|
|
...(isDev && {
|
|
stack: error.stack,
|
|
}),
|
|
},
|
|
{ status: 401 },
|
|
)
|
|
}
|
|
|
|
// Fallback for other errors with safety filter
|
|
const message =
|
|
error instanceof Error ? error.message : "An unexpected error occurred"
|
|
const status = (error as any)?.statusCode || (error as any)?.status || 500
|
|
|
|
// Prevent leaking API keys, tokens, or other sensitive data
|
|
const lowerMessage = message.toLowerCase()
|
|
const safeMessage =
|
|
lowerMessage.includes("key") ||
|
|
lowerMessage.includes("token") ||
|
|
lowerMessage.includes("sig") ||
|
|
lowerMessage.includes("signature") ||
|
|
lowerMessage.includes("secret") ||
|
|
lowerMessage.includes("password") ||
|
|
lowerMessage.includes("credential")
|
|
? "Authentication failed. Please check your credentials."
|
|
: message
|
|
|
|
return Response.json(
|
|
{
|
|
error: safeMessage,
|
|
...(isDev && {
|
|
details: message,
|
|
stack: error instanceof Error ? error.stack : undefined,
|
|
}),
|
|
},
|
|
{ status },
|
|
)
|
|
}
|
|
|
|
// Wrap handler with error handling
|
|
async function safeHandler(req: Request): Promise<Response> {
|
|
try {
|
|
return await handleChatRequest(req)
|
|
} catch (error) {
|
|
return handleError(error)
|
|
}
|
|
}
|
|
|
|
// Wrap with Langfuse observe (if configured)
|
|
const observedHandler = wrapWithObserve(safeHandler)
|
|
|
|
export async function POST(req: Request) {
|
|
return observedHandler(req)
|
|
}
|