🤖 fix: correctly classify (and not retry) model not found errors

src/services/streamManager.ts

@@ -899,41 +899,11 @@ export class StreamManager extends EventEmitter {
 
       let errorType = this.categorizeError(actualError);
 
-      // Detect and enhance model-not-found errors
-      if (APICallError.isInstance(actualError)) {
-        const apiError = actualError;
-
-        // Type guard for error data structure
-        const hasErrorProperty = (
-          data: unknown
-        ): data is { error: { code?: string; type?: string } } => {
-          return (
-            typeof data === "object" &&
-            data !== null &&
-            "error" in data &&
-            typeof data.error === "object" &&
-            data.error !== null
-          );
-        };
-
-        // OpenAI: 400 with error.code === 'model_not_found'
-        const isOpenAIModelError =
-          apiError.statusCode === 400 &&
-          hasErrorProperty(apiError.data) &&
-          apiError.data.error.code === "model_not_found";
-
-        // Anthropic: 404 with error.type === 'not_found_error'
-        const isAnthropicModelError =
-          apiError.statusCode === 404 &&
-          hasErrorProperty(apiError.data) &&
-          apiError.data.error.type === "not_found_error";
-
-        if (isOpenAIModelError || isAnthropicModelError) {
-          errorType = "model_not_found";
-          // Extract model name from model string (e.g., "anthropic:sonnet-1m" -> "sonnet-1m")
-          const [, modelName] = streamInfo.model.split(":");
-          errorMessage = `Model '${modelName || streamInfo.model}' does not exist or is not available. Please check your model selection.`;
-        }
+      // Enhance model-not-found error messages
+      if (errorType === "model_not_found") {
+        // Extract model name from model string (e.g., "anthropic:sonnet-1m" -> "sonnet-1m")
+        const [, modelName] = streamInfo.model.split(":");
+        errorMessage = `Model '${modelName || streamInfo.model}' does not exist or is not available. Please check your model selection.`;
       }
 
       // If we detect API key issues in the error message, override the type
@@ -1044,6 +1014,36 @@ export class StreamManager extends EventEmitter {
       if (error.statusCode === 429) return "rate_limit";
       if (error.statusCode && error.statusCode >= 500) return "server_error";
 
+      // Check for model_not_found errors (OpenAI and Anthropic)
+      // Type guard for error data structure
+      const hasErrorProperty = (
+        data: unknown
+      ): data is { error: { code?: string; type?: string } } => {
+        return (
+          typeof data === "object" &&
+          data !== null &&
+          "error" in data &&
+          typeof data.error === "object" &&
+          data.error !== null
+        );
+      };
+
+      // OpenAI: 400 with error.code === 'model_not_found'
+      const isOpenAIModelError =
+        error.statusCode === 400 &&
+        hasErrorProperty(error.data) &&
+        error.data.error.code === "model_not_found";
+
+      // Anthropic: 404 with error.type === 'not_found_error'
+      const isAnthropicModelError =
+        error.statusCode === 404 &&
+        hasErrorProperty(error.data) &&
+        error.data.error.type === "not_found_error";
+
+      if (isOpenAIModelError || isAnthropicModelError) {
+        return "model_not_found";
+      }
+
       // Check for Anthropic context exceeded errors
       if (error.message.includes("prompt is too long:")) {
         return "context_exceeded";

tests/ipcMain/anthropic1MContext.test.ts

@@ -20,13 +20,6 @@ describeIntegration("IpcMain anthropic 1M context integration tests", () => {
     jest.retryTimes(3, { logErrorsBeforeRetry: true });
   }
 
-  // Load tokenizer modules once before all tests (takes ~14s)
-  // This ensures accurate token counts for API calls without timing out individual tests
-  beforeAll(async () => {
-    const { loadTokenizerModules } = await import("../../src/utils/main/tokenizer");
-    await loadTokenizerModules();
-  }, 30000); // 30s timeout for tokenizer loading
-
   test.concurrent(
     "should handle larger context with 1M flag enabled vs standard limits",
     async () => {

tests/ipcMain/forkWorkspace.test.ts

@@ -32,13 +32,6 @@ describeIntegration("IpcMain fork workspace integration tests", () => {
     jest.retryTimes(3, { logErrorsBeforeRetry: true });
   }
 
-  // Load tokenizer modules once before all tests (takes ~14s)
-  // This ensures accurate token counts for API calls without timing out individual tests
-  beforeAll(async () => {
-    const { loadTokenizerModules } = await import("../../src/utils/main/tokenizer");
-    await loadTokenizerModules();
-  }, 30000); // 30s timeout for tokenizer loading
-
   test.concurrent(
     "should fail to fork workspace with invalid name",
     async () => {

tests/ipcMain/modelNotFound.test.ts

@@ -0,0 +1,98 @@
+import { setupWorkspace, shouldRunIntegrationTests, validateApiKeys } from "./setup";
+import { sendMessageWithModel, createEventCollector, waitFor } from "./helpers";
+import { IPC_CHANNELS } from "../../src/constants/ipc-constants";
+import type { Result } from "../../src/types/result";
+import type { SendMessageError } from "../../src/types/errors";
+import type { StreamErrorMessage } from "../../src/types/ipc";
+
+// Skip all tests if TEST_INTEGRATION is not set
+const describeIntegration = shouldRunIntegrationTests() ? describe : describe.skip;
+
+// Validate API keys before running tests
+if (shouldRunIntegrationTests()) {
+  validateApiKeys(["ANTHROPIC_API_KEY", "OPENAI_API_KEY"]);
+}
+
+describeIntegration("IpcMain model_not_found error handling", () => {
+  // Enable retries in CI for flaky API tests
+  if (process.env.CI && typeof jest !== "undefined" && jest.retryTimes) {
+    jest.retryTimes(3, { logErrorsBeforeRetry: true });
+  }
+
+  test.concurrent(
+    "should classify Anthropic 404 as model_not_found (not retryable)",
+    async () => {
+      const { env, workspaceId, cleanup } = await setupWorkspace("anthropic");
+      try {
+        // Send a message with a non-existent model
+        // Anthropic returns 404 with error.type === 'not_found_error'
+        void sendMessageWithModel(
+          env.mockIpcRenderer,
+          workspaceId,
+          "Hello",
+          "anthropic",
+          "invalid-model-that-does-not-exist-xyz123"
+        );
+
+        // Collect events to verify error classification
+        const collector = createEventCollector(env.sentEvents, workspaceId);
+        await waitFor(() => {
+          collector.collect();
+          return collector.getEvents().some((e) => "type" in e && e.type === "stream-error");
+        }, 10000);
+
+        const events = collector.getEvents();
+        const errorEvent = events.find((e) => "type" in e && e.type === "stream-error") as
+          | StreamErrorMessage
+          | undefined;
+
+        expect(errorEvent).toBeDefined();
+
+        // Bug: Error should be classified as 'model_not_found', not 'api' or 'unknown'
+        // This ensures it's marked as non-retryable in retryEligibility.ts
+        expect(errorEvent?.errorType).toBe("model_not_found");
+      } finally {
+        await cleanup();
+      }
+    },
+    30000 // 30s timeout
+  );
+
+  test.concurrent(
+    "should classify OpenAI 400 model_not_found as model_not_found (not retryable)",
+    async () => {
+      const { env, workspaceId, cleanup } = await setupWorkspace("openai");
+      try {
+        // Send a message with a non-existent model
+        // OpenAI returns 400 with error.code === 'model_not_found'
+        void sendMessageWithModel(
+          env.mockIpcRenderer,
+          workspaceId,
+          "Hello",
+          "openai",
+          "gpt-nonexistent-model-xyz123"
+        );
+
+        // Collect events to verify error classification
+        const collector = createEventCollector(env.sentEvents, workspaceId);
+        await waitFor(() => {
+          collector.collect();
+          return collector.getEvents().some((e) => "type" in e && e.type === "stream-error");
+        }, 10000);
+
+        const events = collector.getEvents();
+        const errorEvent = events.find((e) => "type" in e && e.type === "stream-error") as
+          | StreamErrorMessage
+          | undefined;
+
+        expect(errorEvent).toBeDefined();
+
+        // Bug: Error should be classified as 'model_not_found', not 'api' or 'unknown'
+        expect(errorEvent?.errorType).toBe("model_not_found");
+      } finally {
+        await cleanup();
+      }
+    },
+    30000 // 30s timeout
+  );
+});

tests/ipcMain/openai-web-search.test.ts

@@ -15,13 +15,6 @@ describeIntegration("OpenAI web_search integration tests", () => {
     jest.retryTimes(3, { logErrorsBeforeRetry: true });
   }
 
-  // Load tokenizer modules once before all tests (takes ~14s)
-  // This ensures accurate token counts for API calls without timing out individual tests
-  beforeAll(async () => {
-    const { loadTokenizerModules } = await import("../../src/utils/main/tokenizer");
-    await loadTokenizerModules();
-  }, 30000); // 30s timeout for tokenizer loading
-
   test.concurrent(
     "should handle reasoning + web_search without itemId errors",
     async () => {

tests/ipcMain/resumeStream.test.ts

@@ -20,13 +20,6 @@ describeIntegration("IpcMain resumeStream integration tests", () => {
     jest.retryTimes(3, { logErrorsBeforeRetry: true });
   }
 
-  // Load tokenizer modules once before all tests (takes ~14s)
-  // This ensures accurate token counts for API calls without timing out individual tests
-  beforeAll(async () => {
-    const { loadTokenizerModules } = await import("../../src/utils/main/tokenizer");
-    await loadTokenizerModules();
-  }, 30000); // 30s timeout for tokenizer loading
-
   test.concurrent(
     "should resume interrupted stream without new user message",
     async () => {

tests/ipcMain/sendMessage.test.ts

@@ -48,12 +48,6 @@ describeIntegration("IpcMain sendMessage integration tests", () => {
     jest.retryTimes(3, { logErrorsBeforeRetry: true });
   }
 
-  // Load tokenizer modules once before all tests (takes ~14s)
-  // This ensures accurate token counts for API calls without timing out individual tests
-  beforeAll(async () => {
-    const { loadTokenizerModules } = await import("../../src/utils/main/tokenizer");
-    await loadTokenizerModules();
-  }, 30000); // 30s timeout for tokenizer loading
   // Run tests for each provider concurrently
   describe.each(PROVIDER_CONFIGS)("%s:%s provider tests", (provider, model) => {
     test.concurrent(

tests/ipcMain/streamErrorRecovery.test.ts

@@ -220,13 +220,6 @@ describeIntegration("Stream Error Recovery (No Amnesia)", () => {
     jest.retryTimes(3, { logErrorsBeforeRetry: true });
   }
 
-  // Load tokenizer modules once before all tests (takes ~14s)
-  // This ensures accurate token counts for API calls without timing out individual tests
-  beforeAll(async () => {
-    const { loadTokenizerModules } = await import("../../src/utils/main/tokenizer");
-    await loadTokenizerModules();
-  }, 30000); // 30s timeout for tokenizer loading
-
   test.concurrent(
     "should preserve exact prefix and continue from exact point after stream error",
     async () => {

tests/ipcMain/truncate.test.ts

@@ -24,13 +24,6 @@ describeIntegration("IpcMain truncate integration tests", () => {
     jest.retryTimes(3, { logErrorsBeforeRetry: true });
   }
 
-  // Load tokenizer modules once before all tests (takes ~14s)
-  // This ensures accurate token counts for API calls without timing out individual tests
-  beforeAll(async () => {
-    const { loadTokenizerModules } = await import("../../src/utils/main/tokenizer");
-    await loadTokenizerModules();
-  }, 30000); // 30s timeout for tokenizer loading
-
   test.concurrent(
     "should truncate 50% of chat history and verify context is updated",
     async () => {