get-convex · Nicolapps · Aug 8, 2025 · Aug 8, 2025 · Aug 8, 2025 · Aug 8, 2025
diff --git a/app/components/DebugPromptView.tsx b/app/components/DebugPromptView.tsx
@@ -2,7 +2,7 @@
 import { useEffect, useCallback, useState } from 'react';
 import { JsonView } from 'react-json-view-lite';
 import 'react-json-view-lite/dist/index.css';
-import type { CoreMessage, FilePart, ToolCallPart, TextPart } from 'ai';
+import type { ModelMessage, FilePart, ToolCallPart, TextPart } from 'ai';
 import { ChevronDownIcon, ChevronRightIcon } from '@heroicons/react/20/solid';
 import { ClipboardIcon, ArrowTopRightOnSquareIcon } from '@heroicons/react/24/outline';
 import { useDebugPrompt } from '~/lib/hooks/useDebugPrompt';
@@ -14,58 +14,58 @@ import { IconButton } from '~/components/ui/IconButton';
  * <DebugAllPromptsForChat initialChatId={}>
  *   <UserPromptGroup>  // A group of LLM calls that were executed without the user typing anything in between
  *     <LlmPromptAndResponseView model="Anthropic's Best">  // A single call to an LLM and the response we received bac
- *       <CoreMessageView role='system'>      // CoreMessage is a Vercel AI SDK type, it's a User or Assistant or System or Tool message.
+ *       <ModelMessageView role='system'>      // ModelMessage is a Vercel AI SDK type, it's a User or Assistant or System or Tool message.
  *         Do a good job.
- *       </CoreMessageView>
- *       <CoreMessageView role='user'>
+ *       </ModelMessageView>
+ *       <ModelMessageView role='user'>
  *         Please make an app!
- *       </CoreMessageView>
- *       <CoreMessageView role='assistant'>
+ *       </ModelMessageView>
+ *       <ModelMessageView role='assistant'>
  *         Will do! Please write these files and run this tool.
- *       </CoreMessageView>
+ *       </ModelMessageView>
  *     </LlmPromptAndResponseView>
  *
  *     --- this represents a new call to /api/chat and a new network request to an LLM provider
  *
  *     <LlmPromptAndResponseView model="Something from AWS">
- *       <CoreMessageView role='system'> // We typically repeat back all these messages
+ *       <ModelMessageView role='system'> // We typically repeat back all these messages
  *         Do a good job.
- *       </CoreMessageView>
- *       <CoreMessageView role='system'> // But we can also add new ones
+ *       </ModelMessageView>
+ *       <ModelMessageView role='system'> // But we can also add new ones
  *         BTW, the user is using Chrome on a Mac.
- *       </CoreMessageView>
- *       <CoreMessageView role='user'>
+ *       </ModelMessageView>
+ *       <ModelMessageView role='user'>
  *         Please make an app!
- *       </CoreMessageView>
- *       <CoreMessageView role='assistant'>
+ *       </ModelMessageView>
+ *       <ModelMessageView role='assistant'>
  *         Will do! Please write these files and run this tool.
- *       </CoreMessageView>
- *       <CoreMessageView role='tool'>
+ *       </ModelMessageView>
+ *       <ModelMessageView role='tool'>
  *         file write done! and also I deployed the app.
- *       </CoreMessageView>
+ *       </ModelMessageView>
  *     </LlmPromptAndResponseView>
  *
  *     --- this represents a new call to /api/chat and a new network request to an LLM provider
  *
  *     <LlmPromptAndResponseView model="Something from AWS">
- *       <CoreMessageView role='system'> // We typically repeat back all these messages
+ *       <ModelMessageView role='system'> // We typically repeat back all these messages
  *         Do a good job.
- *       </CoreMessageView>
- *       <CoreMessageView role='system'> // But we can also add new ones
+ *       </ModelMessageView>
+ *       <ModelMessageView role='system'> // But we can also add new ones
  *         BTW, the user is using Chrome on a Mac.
- *       </CoreMessageView>
- *       <CoreMessageView role='user'>
+ *       </ModelMessageView>
+ *       <ModelMessageView role='user'>
  *         Please make an app!
- *       </CoreMessageView>
- *       <CoreMessageView role='assistant'>
+ *       </ModelMessageView>
+ *       <ModelMessageView role='assistant'>
  *         Will do! Please write these files and run this tool.
- *       </CoreMessageView>
- *       <CoreMessageView role='tool'>
+ *       </ModelMessageView>
+ *       <ModelMessageView role='tool'>
  *         file write done! and also I deployed the app.
- *       </CoreMessageView>
- *       <CoreMessageView role='assistant'>
+ *       </ModelMessageView>
+ *       <ModelMessageView role='assistant'>
  *         OK all done, I made you an app!
- *       </CoreMessageView>
+ *       </ModelMessageView>
  *     </LlmPromptAndResponseView>
  *   </UserPromptGroup>
  *
@@ -107,7 +107,7 @@ function isToolCallPart(part: unknown): part is ToolCallPart {
   return typeof part === 'object' && part !== null && 'type' in part && part.type === 'tool-call';
 }
 
-function getMessageCharCount(message: CoreMessage): number {
+function getMessageCharCount(message: ModelMessage): number {
   if (typeof message.content === 'string') return message.content.length;
   if (Array.isArray(message.content)) {
     return message.content.reduce((sum, part) => {
@@ -145,7 +145,7 @@ function getPreviewClass(text: string) {
   return `preview-${Math.abs(text.split('').reduce((acc, char) => acc + char.charCodeAt(0), 0))}`;
 }
 
-function findLastAssistantMessage(prompt: CoreMessage[]): string {
+function findLastAssistantMessage(prompt: ModelMessage[]): string {
   // The last assistant message in a LLM  of messages is the response.
   // It should generally just be the last message, full stop.
   for (let i = prompt.length - 1; i >= 0; i--) {
@@ -186,7 +186,7 @@ function LlmPromptAndResponseView({ promptAndResponse }: { promptAndResponse: Ll
   const totalInputChars = (prompt || []).reduce((sum, msg) => sum + getMessageCharCount(msg), 0);
   const totalOutputChars = (completion || []).reduce((sum, msg) => sum + getMessageCharCount(msg), 0);
 
-  const getTokenEstimate = (message: CoreMessage) => {
+  const getTokenEstimate = (message: ModelMessage) => {
     const charCount = getMessageCharCount(message);
     return estimateTokenCount(charCount, totalInputChars, promptTokensTotal);
   };
@@ -239,7 +239,7 @@ function LlmPromptAndResponseView({ promptAndResponse }: { promptAndResponse: Ll
             </div>
 
             {prompt.map((message, idx) => (
-              <CoreMessageView
+              <ModelMessageView
                 key={idx}
                 message={message}
                 getTokenEstimate={getTokenEstimate}
@@ -252,7 +252,7 @@ function LlmPromptAndResponseView({ promptAndResponse }: { promptAndResponse: Ll
               {formatNumber(outputTokens)} completion tokens ({formatNumber(totalOutputChars)} chars)
             </div>
             {completion.map((message, idx) => (
-              <CoreMessageView key={idx} message={message} />
+              <ModelMessageView key={idx} message={message} />
             ))}
           </div>
         </div>
@@ -261,13 +261,13 @@ function LlmPromptAndResponseView({ promptAndResponse }: { promptAndResponse: Ll
   );
 }
 
-type CoreMessageViewProps = {
-  message: CoreMessage;
-  getTokenEstimate?: (message: CoreMessage) => number;
+type ModelMessageViewProps = {
+  message: ModelMessage;
+  getTokenEstimate?: (message: ModelMessage) => number;
   totalCompletionTokens?: number;
 };
 
-function getMessagePreview(content: CoreMessage['content']): string {
+function getMessagePreview(content: ModelMessage['content']): string {
   if (typeof content === 'string') {
     return content;
   }
@@ -288,7 +288,7 @@ function getMessagePreview(content: CoreMessage['content']): string {
 }
 
 type MessageContentViewProps = {
-  content: CoreMessage['content'];
+  content: ModelMessage['content'];
   showRawJson?: boolean;
 };
 
@@ -371,7 +371,7 @@ const roleColors = {
   tool: 'bg-purple-50 dark:bg-purple-900/20 border-purple-200 dark:border-purple-800',
 } as const;
 
-function CoreMessageView({ message, getTokenEstimate, totalCompletionTokens }: CoreMessageViewProps) {
+function ModelMessageView({ message, getTokenEstimate, totalCompletionTokens }: ModelMessageViewProps) {
   const [isExpanded, setIsExpanded] = useState(false);
 
   const roleColor = roleColors[message.role as keyof typeof roleColors] || roleColors.user;
@@ -428,7 +428,7 @@ function CoreMessageView({ message, getTokenEstimate, totalCompletionTokens }: C
 
 function findTriggeringUserMessage(promptAndResponses: LlmPromptAndResponse[]): string {
   // Look through all prompt and responses in reverse order.
-  // Generally this should be the final CoreMessage of the prompt.
+  // Generally this should be the final ModelMessage of the prompt.
   for (let i = promptAndResponses.length - 1; i >= 0; i--) {
     const promptAndResponse = promptAndResponses[i];
     // Look through messages in reverse order to find the last user message

diff --git a/app/lib/.server/llm/convex-agent.ts b/app/lib/.server/llm/convex-agent.ts
@@ -2,7 +2,7 @@ import {
   createDataStream,
   streamText,
   type CoreAssistantMessage,
-  type CoreMessage,
+  type ModelMessage,
   type CoreToolMessage,
   type DataStreamWriter,
   type LanguageModelUsage,
@@ -108,7 +108,7 @@ export async function convexAgent(args: {
     tools.edit = editTool;
   }
 
-  const messagesForDataStream: CoreMessage[] = [
+  const messagesForDataStream: ModelMessage[] = [
     {
       role: 'system' as const,
       content: ROLE_SYSTEM_PROMPT,
@@ -124,7 +124,7 @@ export async function convexAgent(args: {
     execute(dataStream) {
       const result = streamText({
         model: provider.model,
-        maxTokens: provider.maxTokens,
+        maxOutputTokens: provider.maxTokens,
         providerOptions: provider.options,
         messages: messagesForDataStream,
         tools,
@@ -139,7 +139,7 @@ export async function convexAgent(args: {
             recordUsageCb,
             toolsDisabledFromRepeatedErrors: shouldDisableTools,
             recordRawPromptsForDebugging,
-            coreMessages: messagesForDataStream,
+            modelMessages: messagesForDataStream,
             modelProvider,
             modelChoice,
             collapsedMessages,
@@ -207,7 +207,7 @@ async function onFinishHandler({
   recordUsageCb,
   toolsDisabledFromRepeatedErrors,
   recordRawPromptsForDebugging,
-  coreMessages,
+  modelMessages,
   modelProvider,
   modelChoice,
   collapsedMessages,
@@ -227,7 +227,7 @@ async function onFinishHandler({
   ) => Promise<void>;
   recordRawPromptsForDebugging: boolean;
   toolsDisabledFromRepeatedErrors: boolean;
-  coreMessages: CoreMessage[];
+  modelMessages: ModelMessage[];
   modelProvider: ModelProvider;
   modelChoice: string | undefined;
   collapsedMessages: boolean;
@@ -327,13 +327,13 @@ async function onFinishHandler({
     await recordUsageCb(messages[messages.length - 1], { usage, providerMetadata });
   }
   if (recordRawPromptsForDebugging) {
-    const responseCoreMessages = result.response.messages as (CoreAssistantMessage | CoreToolMessage)[];
+    const responseModelMessages = result.response.messages as (CoreAssistantMessage | CoreToolMessage)[];
     // don't block the request but keep the request alive in Vercel Lambdas
     waitUntil(
       storeDebugPrompt(
-        coreMessages,
+        modelMessages,
         chatInitialId,
-        responseCoreMessages,
+        responseModelMessages,
         result,
         {
           usage,
@@ -406,9 +406,9 @@ function buildUsageRecord(usage: Usage): UsageRecord {
 }
 
 async function storeDebugPrompt(
-  promptCoreMessages: CoreMessage[],
+  promptModelMessages: ModelMessage[],
   chatInitialId: string,
-  responseCoreMessages: CoreMessage[],
+  responseModelMessages: ModelMessage[],
   result: Omit<StepResult<any>, 'stepType' | 'isContinued'>,
   generation: { usage: LanguageModelUsage; providerMetadata?: ProviderMetadata },
   modelProvider: ModelProvider,
@@ -418,15 +418,15 @@ async function storeDebugPrompt(
     const modelId = result.response.modelId || '';
     const usage = usageFromGeneration(generation);
 
-    const promptMessageData = new TextEncoder().encode(JSON.stringify(promptCoreMessages));
+    const promptMessageData = new TextEncoder().encode(JSON.stringify(promptModelMessages));
     const compressedData = compressWithLz4Server(promptMessageData);
 
     type Metadata = Omit<(typeof internal.debugPrompt.storeDebugPrompt)['_args'], 'promptCoreMessagesStorageId'>;
     const { chefTokens } = calculateChefTokens(usage, modelProvider);
 
     const metadata = {
       chatInitialId,
-      responseCoreMessages,
+      responseCoreMessages: responseModelMessages,
       finishReason,
       modelId,
       usage: buildUsageRecord(usage),

diff --git a/app/lib/hooks/useDebugPrompt.ts b/app/lib/hooks/useDebugPrompt.ts
@@ -1,13 +1,13 @@
 import { useConvex, useMutation, useQuery } from 'convex/react';
 import { useQueries as useReactQueries } from '@tanstack/react-query';
 import { api } from '@convex/_generated/api';
-import type { CoreMessage } from 'ai';
+import type { ModelMessage } from 'ai';
 import { decompressWithLz4 } from '~/lib/compression.client';
 import { queryClientStore } from '~/lib/stores/reactQueryClient';
 import { useEffect, useState } from 'react';
 import { getConvexAuthToken } from '~/lib/stores/sessionId';
 
-async function fetchPromptData(url: string): Promise<CoreMessage[]> {
+async function fetchPromptData(url: string): Promise<ModelMessage[]> {
   const response = await fetch(url);
   if (!response.ok) {
     throw new Error(`Failed to fetch prompt data: ${response.statusText}`);
@@ -17,7 +17,7 @@ async function fetchPromptData(url: string): Promise<CoreMessage[]> {
   const decompressedData = decompressWithLz4(new Uint8Array(compressedData));
   const textDecoder = new TextDecoder();
   const jsonString = textDecoder.decode(decompressedData);
-  return JSON.parse(jsonString) as CoreMessage[];
+  return JSON.parse(jsonString) as ModelMessage[];
 }
 
 export function useAuthToken() {

diff --git a/chef-agent/cleanupAssistantMessages.ts b/chef-agent/cleanupAssistantMessages.ts
@@ -1,4 +1,4 @@
-import { convertToCoreMessages } from 'ai';
+import { convertToModelMessages } from 'ai';
 import type { Message } from 'ai';
 import { EXCLUDED_FILE_PATHS } from './constants.js';
 
@@ -24,7 +24,7 @@ export function cleanupAssistantMessages(messages: Message[]) {
       (message.parts &&
         message.parts.filter((part) => part.type === 'text' || part.type === 'tool-invocation').length > 0),
   );
-  return convertToCoreMessages(processedMessages).filter((message) => message.content.length > 0);
+  return convertToModelMessages(processedMessages).filter((message) => message.content.length > 0);
 }
 
 function cleanMessage(message: string) {

diff --git a/chef-agent/package.json b/chef-agent/package.json
@@ -8,11 +8,11 @@
     "typecheck": "tsc"
   },
   "dependencies": {
-    "ai": "^4.3.2",
+    "ai": "^5.0.8",
     "jose": "^5.9.6",
     "path-browserify": "^1.0.1",
     "typescript": "^5.4.2",
-    "zod": "^3.24.1"
+    "zod": "^3.25.0"
   },
   "devDependencies": {
     "@types/node": "^20.17.30",

diff --git a/package.json b/package.json
@@ -31,13 +31,13 @@
     "node": ">=18.18.0"
   },
   "dependencies": {
-    "@ai-sdk/amazon-bedrock": "^2.2.9",
-    "@ai-sdk/anthropic": "^1.2.12",
-    "@ai-sdk/google": "^1.2.11",
-    "@ai-sdk/google-vertex": "^2.2.24",
-    "@ai-sdk/openai": "^1.3.6",
-    "@ai-sdk/react": "^1.2.5",
-    "@ai-sdk/xai": "^1.2.13",
+    "@ai-sdk/amazon-bedrock": "^2.0.0",
+    "@ai-sdk/anthropic": "^2.0.0",
+    "@ai-sdk/google": "^2.0.0",
+    "@ai-sdk/google-vertex": "^2.0.0",
+    "@ai-sdk/openai": "^2.0.5",
+    "@ai-sdk/react": "^2.0.0",
+    "@ai-sdk/xai": "^2.0.0",
     "@auth0/auth0-react": "^2.3.0",
     "@aws-sdk/credential-providers": "^3.782.0",
     "@aws-sdk/rds-signer": "^3.782.0",
@@ -90,7 +90,7 @@
     "@xterm/addon-fit": "^0.10.0",
     "@xterm/addon-web-links": "^0.11.0",
     "@xterm/xterm": "^5.5.0",
-    "ai": "^4.3.2",
+    "ai": "^5.0.8",
     "allotment": "^1.20.3",
     "chart.js": "^4.4.9",
     "chef-agent": "workspace:*",
@@ -188,18 +188,14 @@
     "vite-plugin-optimize-css-modules": "^1.1.0",
     "vite-tsconfig-paths": "^4.3.2",
     "vitest": "^2.1.9",
-    "zod": "^3.24.1"
+    "zod": "^3.25.0"
   },
   "resolutions": {
     "@typescript-eslint/utils": "^8.0.0-alpha.30"
   },
   "pnpm": {
     "overrides": {
-      "@remix-run/cloudflare": "npm:@remix-run/[email protected]",
-      "@ai-sdk/google": "npm:@convex-dev/[email protected]"
-    },
-    "patchedDependencies": {
-      "@ai-sdk/[email protected]": "patches/@[email protected]"
+      "@remix-run/cloudflare": "npm:@remix-run/[email protected]"
     }
   },
   "packageManager": "[email protected]"