Upgrade to AI sdk with codemod (#1000)

e2e-tests/snapshots/ollama.spec.ts_send-message-to-ollama-1.aria.yml

 - paragraph: hi
-- paragraph: ollamachunkollamachunk
+- img
+- text: file1.txt
+- img
+- text: file1.txt
+- paragraph: More EOM
 - button "Retry":
   - img
\ No newline at end of file

package.json

@@ -84,17 +84,18 @@
     "vitest": "^3.1.1"
   },
   "dependencies": {
-    "@ai-sdk/anthropic": "^1.2.8",
-    "@ai-sdk/google": "^1.2.19",
-    "@ai-sdk/openai": "^1.3.24",
-    "@ai-sdk/openai-compatible": "^0.2.13",
+    "@ai-sdk/anthropic": "^2.0.4",
+    "@ai-sdk/google": "^2.0.6",
+    "@ai-sdk/openai": "^2.0.15",
+    "@ai-sdk/openai-compatible": "^1.0.8",
+    "@ai-sdk/provider-utils": "^3.0.3",
     "@biomejs/biome": "^1.9.4",
     "@dyad-sh/supabase-management-js": "v1.0.0",
     "@lexical/react": "^0.33.1",
     "@monaco-editor/react": "^4.7.0-rc.0",
     "@neondatabase/api-client": "^2.1.0",
     "@neondatabase/serverless": "^1.0.1",
-    "@openrouter/ai-sdk-provider": "^0.4.5",
+    "@openrouter/ai-sdk-provider": "^1.1.2",
     "@radix-ui/react-accordion": "^1.2.4",
     "@radix-ui/react-alert-dialog": "^1.1.13",
     "@radix-ui/react-checkbox": "^1.3.2",
@@ -118,7 +119,7 @@
     "@types/uuid": "^10.0.0",
     "@vercel/sdk": "^1.10.0",
     "@vitejs/plugin-react": "^4.3.4",
-    "ai": "^4.3.4",
+    "ai": "^5.0.15",
     "better-sqlite3": "^11.9.1",
     "class-variance-authority": "^0.7.1",
     "clsx": "^2.1.1",
@@ -140,7 +141,6 @@
     "lexical-beautiful-mentions": "^0.1.47",
     "lucide-react": "^0.487.0",
     "monaco-editor": "^0.52.2",
-    "ollama-ai-provider": "^1.2.0",
     "openai": "^4.91.1",
     "posthog-js": "^1.236.3",
     "react": "^19.0.0",
@@ -158,7 +158,8 @@
     "tree-kill": "^1.2.2",
     "tw-animate-css": "^1.2.5",
     "update-electron-app": "^3.1.1",
-    "uuid": "^11.1.0"
+    "uuid": "^11.1.0",
+    "zod": "^3.25.76"
   },
   "lint-staged": {
     "**/*.{js,mjs,cjs,jsx,ts,mts,cts,tsx,vue,astro,svelte}": "oxlint",

src/ipc/handlers/chat_stream_handlers.ts

 import { v4 as uuidv4 } from "uuid";
 import { ipcMain } from "electron";
 import {
-  CoreMessage,
+  ModelMessage,
   TextPart,
   ImagePart,
   streamText,
@@ -134,14 +134,14 @@ async function processStreamChunks({
         chunk = "</think>";
         inThinkingBlock = false;
       }
-      chunk += part.textDelta;
-    } else if (part.type === "reasoning") {
+      chunk += part.text;
+    } else if (part.type === "reasoning-delta") {
       if (!inThinkingBlock) {
         chunk = "<think>";
         inThinkingBlock = true;
       }
 
-      chunk += escapeDyadTags(part.textDelta);
+      chunk += escapeDyadTags(part.text);
     }
 
     if (!chunk) {
@@ -603,7 +603,7 @@ This conversation includes one or more image attachments. When the user uploads
             ] as const)
           : [];
 
-        let chatMessages: CoreMessage[] = [
+        let chatMessages: ModelMessage[] = [
           ...codebasePrefix,
           ...otherCodebasePrefix,
           ...limitedMessageHistory.map((msg) => ({
@@ -647,7 +647,7 @@ This conversation includes one or more image attachments. When the user uploads
               content:
                 "Summarize the following chat: " +
                 formatMessagesForSummary(previousChat?.messages ?? []),
-            } satisfies CoreMessage,
+            } satisfies ModelMessage,
           ];
         }
 
@@ -655,7 +655,7 @@ This conversation includes one or more image attachments. When the user uploads
           chatMessages,
           modelClient,
         }: {
-          chatMessages: CoreMessage[];
+          chatMessages: ModelMessage[];
           modelClient: ModelClient;
         }) => {
           const dyadRequestId = uuidv4();
@@ -668,7 +668,7 @@ This conversation includes one or more image attachments. When the user uploads
             logger.log("sending AI request");
           }
           return streamText({
-            maxTokens: await getMaxTokens(settings.selectedModel),
+            maxOutputTokens: await getMaxTokens(settings.selectedModel),
             temperature: await getTemperature(settings.selectedModel),
             maxRetries: 2,
             model: modelClient.model,
@@ -798,7 +798,7 @@ This conversation includes one or more image attachments. When the user uploads
                   break;
                 }
                 if (part.type !== "text-delta") continue; // ignore reasoning for continuation
-                fullResponse += part.textDelta;
+                fullResponse += part.text;
                 fullResponse = cleanFullResponse(fullResponse);
                 fullResponse = await processResponseChunkUpdate({
                   fullResponse,
@@ -825,7 +825,7 @@ This conversation includes one or more image attachments. When the user uploads
 
               let autoFixAttempts = 0;
               const originalFullResponse = fullResponse;
-              const previousAttempts: CoreMessage[] = [];
+              const previousAttempts: ModelMessage[] = [];
               while (
                 problemReport.problems.length > 0 &&
                 autoFixAttempts < 2 &&
@@ -1161,9 +1161,9 @@ async function replaceTextAttachmentWithContent(
 
 // Helper function to convert traditional message to one with proper image attachments
 async function prepareMessageWithAttachments(
-  message: CoreMessage,
+  message: ModelMessage,
   attachmentPaths: string[],
-): Promise<CoreMessage> {
+): Promise<ModelMessage> {
   let textContent = message.content;
   // Get the original text content
   if (typeof textContent !== "string") {

src/ipc/handlers/local_model_ollama_handler.ts

@@ -37,7 +37,9 @@ export function parseOllamaHost(host?: string): string {
   return `http://${host}:11434`;
 }
 
-const OLLAMA_API_URL = parseOllamaHost(process.env.OLLAMA_HOST);
+export function getOllamaApiUrl(): string {
+  return parseOllamaHost(process.env.OLLAMA_HOST);
+}
 
 interface OllamaModel {
   name: string;
@@ -55,7 +57,7 @@ interface OllamaModel {
 
 export async function fetchOllamaModels(): Promise<LocalModelListResponse> {
   try {
-    const response = await fetch(`${OLLAMA_API_URL}/api/tags`);
+    const response = await fetch(`${getOllamaApiUrl()}/api/tags`);
     if (!response.ok) {
       throw new Error(`Failed to fetch model: ${response.statusText}`);
     }

src/ipc/utils/get_model_client.ts

-import { LanguageModelV1 } from "ai";
 import { createOpenAI } from "@ai-sdk/openai";
 import { createGoogleGenerativeAI as createGoogle } from "@ai-sdk/google";
 import { createAnthropic } from "@ai-sdk/anthropic";
 import { createOpenRouter } from "@openrouter/ai-sdk-provider";
-import { createOllama } from "ollama-ai-provider";
 import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
 import type { LargeLanguageModel, UserSettings } from "../../lib/schemas";
 import { getEnvVar } from "./read_env";
@@ -13,6 +11,9 @@ import { LanguageModelProvider } from "../ipc_types";
 import { createDyadEngine } from "./llm_engine_provider";
 
 import { LM_STUDIO_BASE_URL } from "./lm_studio_utils";
+import { LanguageModel } from "ai";
+import { createOllamaProvider } from "./ollama_provider";
+import { getOllamaApiUrl } from "../handlers/local_model_ollama_handler";
 
 const dyadEngineUrl = process.env.DYAD_ENGINE_URL;
 const dyadGatewayUrl = process.env.DYAD_GATEWAY_URL;
@@ -33,7 +34,7 @@ const AUTO_MODELS = [
 ];
 
 export interface ModelClient {
-  model: LanguageModelV1;
+  model: LanguageModel;
   builtinProviderId?: string;
 }
 
@@ -168,7 +169,10 @@ function getRegularModelClient(
   model: LargeLanguageModel,
   settings: UserSettings,
   providerConfig: LanguageModelProvider,
-) {
+): {
+  modelClient: ModelClient;
+  backupModelClients: ModelClient[];
+} {
   // Get API key for the specific provider
   const apiKey =
     settings.providerSettings?.[model.provider]?.apiKey?.value ||
@@ -220,13 +224,11 @@ function getRegularModelClient(
       };
     }
     case "ollama": {
-      // Ollama typically runs locally and doesn't require an API key in the same way
-      const provider = createOllama({
-        baseURL: process.env.OLLAMA_HOST,
-      });
+      const provider = createOllamaProvider({ baseURL: getOllamaApiUrl() });
       return {
         modelClient: {
           model: provider(model.name),
+          builtinProviderId: providerId,
         },
         backupModelClients: [],
       };

src/ipc/utils/llm_engine_provider.ts

-import {
-  LanguageModelV1,
-  LanguageModelV1ObjectGenerationMode,
-} from "@ai-sdk/provider";
+import { LanguageModel } from "ai";
 import { OpenAICompatibleChatLanguageModel } from "@ai-sdk/openai-compatible";
 import {
   FetchFunction,
@@ -9,7 +6,6 @@ import {
   withoutTrailingSlash,
 } from "@ai-sdk/provider-utils";
 
-import { OpenAICompatibleChatSettings } from "@ai-sdk/openai-compatible";
 import log from "electron-log";
 import { getExtraProviderOptions } from "./thinking_utils";
 import type { UserSettings } from "../../lib/schemas";
@@ -18,7 +14,7 @@ const logger = log.scope("llm_engine_provider");
 
 export type ExampleChatModelId = string & {};
 
-export interface ExampleChatSettings extends OpenAICompatibleChatSettings {
+export interface ExampleChatSettings {
   files?: { path: string; content: string }[];
 }
 export interface ExampleProviderSettings {
@@ -56,10 +52,7 @@ export interface DyadEngineProvider {
   /**
 Creates a model for text generation.
 */
-  (
-    modelId: ExampleChatModelId,
-    settings?: ExampleChatSettings,
-  ): LanguageModelV1;
+  (modelId: ExampleChatModelId, settings?: ExampleChatSettings): LanguageModel;
 
   /**
 Creates a chat model for text generation.
@@ -67,7 +60,7 @@ Creates a chat model for text generation.
   chatModel(
     modelId: ExampleChatModelId,
     settings?: ExampleChatSettings,
-  ): LanguageModelV1;
+  ): LanguageModel;
 }
 
 export function createDyadEngine(
@@ -113,13 +106,13 @@ export function createDyadEngine(
     settings: ExampleChatSettings = {},
   ) => {
     // Extract files from settings to process them appropriately
-    const { files, ...restSettings } = settings;
+    const { files } = settings;
 
     // Create configuration with file handling
     const config = {
       ...getCommonModelConfig(),
-      defaultObjectGenerationMode:
-        "tool" as LanguageModelV1ObjectGenerationMode,
+      // defaultObjectGenerationMode:
+      //   "tool" as LanguageModelV1ObjectGenerationMode,
       // Custom fetch implementation that adds files to the request
       fetch: (input: RequestInfo | URL, init?: RequestInit) => {
         // Use default fetch if no init or body
@@ -181,7 +174,7 @@ export function createDyadEngine(
       },
     };
 
-    return new OpenAICompatibleChatLanguageModel(modelId, restSettings, config);
+    return new OpenAICompatibleChatLanguageModel(modelId, config);
   };
 
   const provider = (

src/ipc/utils/ollama_provider.ts

+import { LanguageModel } from "ai";
+import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
+import type { FetchFunction } from "@ai-sdk/provider-utils";
+import { withoutTrailingSlash } from "@ai-sdk/provider-utils";
+import type {} from "@ai-sdk/provider";
+
+type OllamaChatModelId = string;
+
+export interface OllamaProviderOptions {
+  /**
+   * Base URL for the Ollama API. For real Ollama, use e.g. http://localhost:11434/api
+   * The provider will POST to `${baseURL}/chat`.
+   * If undefined, defaults to http://localhost:11434/api
+   */
+  baseURL?: string;
+  headers?: Record<string, string>;
+  fetch?: FetchFunction;
+}
+
+export interface OllamaChatSettings {}
+
+export interface OllamaProvider {
+  (modelId: OllamaChatModelId, settings?: OllamaChatSettings): LanguageModel;
+}
+
+export function createOllamaProvider(
+  options?: OllamaProviderOptions,
+): OllamaProvider {
+  const base = withoutTrailingSlash(
+    options?.baseURL ?? "http://localhost:11434",
+  )!;
+  const v1Base = (base.endsWith("/v1") ? base : `${base}/v1`) as string;
+  const provider = createOpenAICompatible({
+    name: "ollama",
+    baseURL: v1Base,
+    headers: options?.headers,
+  });
+  return (modelId: OllamaChatModelId) => provider(modelId);
+}

testing/fake-llm-server/index.ts

@@ -94,51 +94,6 @@ app.get("/ollama/api/tags", (req, res) => {
   res.json(ollamaModels);
 });
 
-app.post("/ollama/chat", (req, res) => {
-  // Tell the client we're going to stream NDJSON
-  res.setHeader("Content-Type", "application/x-ndjson");
-  res.setHeader("Cache-Control", "no-cache");
-
-  // Chunk #1 – partial answer
-  const firstChunk = {
-    model: "llama3.2",
-    created_at: "2023-08-04T08:52:19.385406455-07:00",
-    message: {
-      role: "assistant",
-      content: "ollamachunk",
-      images: null,
-    },
-    done: false,
-  };
-
-  // Chunk #2 – final answer + metrics
-  const secondChunk = {
-    model: "llama3.2",
-    created_at: "2023-08-04T19:22:45.499127Z",
-    message: {
-      role: "assistant",
-      content: "",
-    },
-    done: true,
-    total_duration: 4883583458,
-    load_duration: 1334875,
-    prompt_eval_count: 26,
-    prompt_eval_duration: 342546000,
-    eval_count: 282,
-    eval_duration: 4535599000,
-  };
-
-  // Send the first object right away
-  res.write(JSON.stringify(firstChunk) + "\n");
-  res.write(JSON.stringify(firstChunk) + "\n");
-
-  // …and the second one a moment later to mimic streaming
-  setTimeout(() => {
-    res.write(JSON.stringify(secondChunk) + "\n");
-    res.end(); // Close the HTTP stream
-  }, 300); // 300 ms delay – tweak as you like
-});
-
 // LM Studio specific endpoints
 app.get("/lmstudio/api/v0/models", (req, res) => {
   const lmStudioModels = {
@@ -182,7 +137,7 @@ app.get("/lmstudio/api/v0/models", (req, res) => {
   res.json(lmStudioModels);
 });
 
-["lmstudio", "gateway", "engine"].forEach((provider) => {
+["lmstudio", "gateway", "engine", "ollama"].forEach((provider) => {
   app.post(
     `/${provider}/v1/chat/completions`,
     createChatCompletionHandler(provider),