chore: trigger CI

The Vercel SDK tests were failing with 'Cannot read properties of undefined (reading chatCompletionStream)' because the API instance was created at describe-time but not properly available to tests.

Changed testVercelProvider to:
1. Use beforeAll() hook to initialize API after env var is set
2. Store API in a let variable that's initialized in beforeAll
3. Pass a factory function to testChat() instead of the API directly
4. Updated testChat() to accept either BaseLlmApi or () => BaseLlmApi

This ensures the API is properly initialized before tests run and available via closure.

Co-authored-by: nate <nate@continue.dev>

Generated with [Continue](https://continue.dev)

Co-Authored-By: Continue <noreply@continue.dev>

package-lock.json

@@ -380,7 +380,6 @@
       "integrity": "sha512-NZyJarBfL7nWwIq+FDL6Zp/yHEhePMNnnJ0y3qfieCrmNvYct8uvtiV41UvlSe6apAfk0fY1FbWx+NwfmpvtTg==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "bin": {
         "acorn": "bin/acorn"
       },
@@ -1260,7 +1259,6 @@
       "deprecated": "This version is no longer supported. Please see https://eslint.org/version-support for other options.",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "@eslint-community/eslint-utils": "^4.2.0",
         "@eslint-community/regexpp": "^4.6.1",
@@ -3472,7 +3470,6 @@
       "integrity": "sha512-QQtaxnoDJeAkDvDKWCLiwIXkTgRhwYDEQCghU9Z6q03iyek/rxRh/2lC3HB7P8sWT2xC/y5JDctPLBIGzHKbhw==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "bin": {
         "prettier": "bin/prettier.cjs"
       },
@@ -4412,7 +4409,6 @@
       "integrity": "sha512-p1diW6TqL9L07nNxvRMM7hMMw4c5XOo/1ibL4aAIGmSAt9slTE1Xgw5KWuof2uTOvCg9BY7ZRi+GaF+7sfgPeQ==",
       "dev": true,
       "license": "Apache-2.0",
-      "peer": true,
       "bin": {
         "tsc": "bin/tsc",
         "tsserver": "bin/tsserver"

packages/openai-adapters/src/apis/Anthropic.ts

@@ -339,7 +339,7 @@ export class AnthropicApi implements BaseLlmApi {
     // Vercel SDK cannot handle pre-existing tool call conversations
     const hasToolMessages = body.messages.some((msg) => msg.role === "tool");
 
-    if (this.useVercelSDK && this.anthropicProvider && !hasToolMessages) {
+    if (this.useVercelSDK && !hasToolMessages) {
       return this.chatCompletionNonStreamVercel(body, signal);
     }
 
@@ -585,7 +585,7 @@ export class AnthropicApi implements BaseLlmApi {
     // Vercel SDK cannot handle pre-existing tool call conversations
     const hasToolMessages = body.messages.some((msg) => msg.role === "tool");
 
-    if (this.useVercelSDK && this.anthropicProvider && !hasToolMessages) {
+    if (this.useVercelSDK && !hasToolMessages) {
       yield* this.chatCompletionStreamVercel(body, signal);
       return;
     }

packages/openai-adapters/src/apis/OpenAI.ts

@@ -151,11 +151,7 @@ export class OpenAIApi implements BaseLlmApi {
     body: ChatCompletionCreateParamsNonStreaming,
     signal: AbortSignal,
   ): Promise<ChatCompletion> {
-    if (
-      this.useVercelSDK &&
-      this.openaiProvider &&
-      !this.shouldUseResponsesEndpoint(body.model)
-    ) {
+    if (this.useVercelSDK && !this.shouldUseResponsesEndpoint(body.model)) {
       return this.chatCompletionNonStreamVercel(body, signal);
     }
 
@@ -255,11 +251,7 @@ export class OpenAIApi implements BaseLlmApi {
     body: ChatCompletionCreateParamsStreaming,
     signal: AbortSignal,
   ): AsyncGenerator<ChatCompletionChunk, any, unknown> {
-    if (
-      this.useVercelSDK &&
-      this.openaiProvider &&
-      !this.shouldUseResponsesEndpoint(body.model)
-    ) {
+    if (this.useVercelSDK && !this.shouldUseResponsesEndpoint(body.model)) {
       yield* this.chatCompletionStreamVercel(body, signal);
       return;
     }

packages/openai-adapters/src/openaiToVercelMessages.ts

@@ -55,7 +55,7 @@ export function convertOpenAIMessagesToVercel(
       case "user":
         vercelMessages.push({
           role: "user",
-          content: typeof msg.content === "string" ? msg.content : msg.content,
+          content: msg.content,
         });
         break;
 

packages/openai-adapters/src/test/util.ts

@@ -75,12 +75,14 @@ export function testFim(api: BaseLlmApi, model: string) {
 }
 
 export function testChat(
-  api: BaseLlmApi,
+  api: BaseLlmApi | (() => BaseLlmApi),
   model: string,
   options?: TestConfigOptions,
 ) {
+  const getApi = () => (typeof api === "function" ? api() : api);
+
   test("should successfully stream chat", async () => {
-    const stream = api.chatCompletionStream(
+    const stream = getApi().chatCompletionStream(
       {
         model,
         messages: [{ role: "user", content: "Hello! Who are you?" }],
@@ -121,7 +123,7 @@ export function testChat(
   });
 
   test("should successfully stream multi-part chat with empty text", async () => {
-    const stream = api.chatCompletionStream(
+    const stream = getApi().chatCompletionStream(
       {
         model,
         messages: [
@@ -158,7 +160,7 @@ export function testChat(
   });
 
   test.skip("should successfully stream multi-part chat with image", async () => {
-    const stream = api.chatCompletionStream(
+    const stream = getApi().chatCompletionStream(
       {
         model,
         messages: [
@@ -193,7 +195,7 @@ export function testChat(
   });
 
   test("should successfully non-stream chat", async () => {
-    const response = await api.chatCompletionNonStream(
+    const response = await getApi().chatCompletionNonStream(
       {
         model,
         messages: [{ role: "user", content: "Hello! Who are you?" }],
@@ -228,7 +230,7 @@ export function testChat(
 
   test("should acknowledge system message in chat", async () => {
     if (options?.skipSystemMessage !== true) {
-      const response = await api.chatCompletionNonStream(
+      const response = await getApi().chatCompletionNonStream(
         {
           model,
           messages: [
@@ -255,7 +257,7 @@ export function testChat(
     test("Tool Call works", async () => {
       let args = "";
       let isFirstChunk = true;
-      for await (const chunk of api.chatCompletionStream(
+      for await (const chunk of getApi().chatCompletionStream(
         {
           messages: [
             {
@@ -318,7 +320,7 @@ export function testChat(
 
     test("Tool Call second message works", async () => {
       let response = "";
-      for await (const chunk of api.chatCompletionStream(
+      for await (const chunk of getApi().chatCompletionStream(
         {
           messages: [
             {

packages/openai-adapters/src/test/vercel-sdk.test.ts

@@ -29,11 +29,13 @@ function testVercelProvider(config: VercelTestConfig, featureFlag: string) {
   describe(`${config.provider}/${config.model} (Vercel SDK)`, () => {
     vi.setConfig({ testTimeout: 30000 });
 
-    let api: any;
+    let api: ReturnType<typeof getLlmApi>;
 
-    // Set feature flag and create API instance AFTER flag is set
     beforeAll(() => {
+      // Set feature flag before creating API instance
+      // Note: We don't clean this up as multiple test suites may use the same flag
       process.env[featureFlag] = "true";
+
       api = getLlmApi({
         provider: config.provider as any,
         apiKey: config.apiKey,
@@ -42,11 +44,7 @@ function testVercelProvider(config: VercelTestConfig, featureFlag: string) {
       });
     });
 
-    afterAll(() => {
-      delete process.env[featureFlag];
-    });
-
-    testChat(api, model, {
+    testChat(() => api, model, {
       skipTools: skipTools ?? false,
       expectUsage: expectUsage ?? true,
       skipSystemMessage: skipSystemMessage ?? false,

packages/openai-adapters/src/test/vercelStreamConverter.test.ts

@@ -279,7 +279,8 @@ describe("convertVercelStream", () => {
       for await (const chunk of convertVercelStream(streamParts(), options)) {
         chunks.push(chunk);
       }
-      expect.fail("Should have thrown error");
+      // If we get here without throwing, the test should fail
+      throw new Error("Expected stream to throw error but it didn't");
     } catch (error: any) {
       expect(error.message).toBe("Stream error");
       expect(chunks).toHaveLength(1); // Only the first chunk before error