Add model parameter to InvokeLLM for per-call model selection

src/modules/integrations.types.ts

@@ -23,7 +23,7 @@ export type IntegrationEndpointFunction = (
  * ```typescript
  * await base44.integrations.Core.InvokeLLM({
  *   prompt: 'Explain quantum computing',
- *   model: 'gpt-4'
+ *   model: 'gpt_5'
  * });
  * ```
  *
@@ -46,6 +46,11 @@ export type IntegrationPackage = {
 export interface InvokeLLMParams {
   /** The prompt text to send to the model */
   prompt: string;
+  /** Optionally specify a model to override the app-level model setting for this specific call.
+   *
+   * Options: `"gpt_5_mini"`, `"gemini_3_flash"`, `"gpt_5"`, `"gemini_3_pro"`, `"claude_sonnet_4_6"`, `"claude_opus_4_6"`
+   */
+  model?: 'gpt_5_mini' | 'gemini_3_flash' | 'gpt_5' | 'gemini_3_pro' | 'claude_sonnet_4_6' | 'claude_opus_4_6';
   /** If set to `true`, the LLM will use Google Search, Maps, and News to gather real-time context before answering.
    * @default false
    */
@@ -393,7 +398,7 @@ export type IntegrationsModule = {
    * ```typescript
    * const response = await base44.integrations.Core.InvokeLLM({
    *   prompt: 'Explain quantum computing',
-   *   model: 'gpt-4'
+   *   model: 'gpt_5'
    * });
    * ```
    */
@@ -423,7 +428,7 @@ export type IntegrationsModule = {
    * ```typescript
    * const response = await base44.integrations.Core.InvokeLLM({
    *   prompt: 'Explain quantum computing',
-   *   model: 'gpt-4'
+   *   model: 'gpt_5'
    * });
    * ```
    *

tests/unit/integrations.test.ts

@@ -0,0 +1,75 @@
+import { describe, test, expect, beforeEach, afterEach } from 'vitest';
+import nock from 'nock';
+import { createClient } from '../../src/index.ts';
+
+describe('Core Integrations - InvokeLLM', () => {
+  let base44: ReturnType<typeof createClient>;
+  let scope: nock.Scope;
+  const appId = 'test-app-id';
+  const serverUrl = 'https://base44.app';
+
+  beforeEach(() => {
+    base44 = createClient({
+      serverUrl,
+      appId,
+    });
+
+    scope = nock(serverUrl);
+  });
+
+  afterEach(() => {
+    nock.cleanAll();
+  });
+
+  test('InvokeLLM should pass model parameter to the API', async () => {
+    const params = {
+      prompt: 'Explain quantum computing',
+      model: 'gpt_5',
+    };
+
+    scope
+      .post(`/api/apps/${appId}/integration-endpoints/Core/InvokeLLM`, params)
+      .reply(200, 'Quantum computing uses qubits...');
+
+    const result = await base44.integrations.Core.InvokeLLM(params);
+    expect(result).toBe('Quantum computing uses qubits...');
+    expect(scope.isDone()).toBe(true);
+  });
+
+  test('InvokeLLM should work without model parameter', async () => {
+    const params = {
+      prompt: 'Explain quantum computing',
+    };
+
+    scope
+      .post(`/api/apps/${appId}/integration-endpoints/Core/InvokeLLM`, params)
+      .reply(200, 'Quantum computing uses qubits...');
+
+    const result = await base44.integrations.Core.InvokeLLM(params);
+    expect(result).toBe('Quantum computing uses qubits...');
+    expect(scope.isDone()).toBe(true);
+  });
+
+  test('InvokeLLM should pass model alongside other optional parameters', async () => {
+    const params = {
+      prompt: 'Analyze this text',
+      model: 'claude_sonnet_4_6' as const,
+      response_json_schema: {
+        type: 'object',
+        properties: {
+          sentiment: { type: 'string' },
+        },
+      },
+    };
+
+    const mockResponse = { sentiment: 'positive' };
+
+    scope
+      .post(`/api/apps/${appId}/integration-endpoints/Core/InvokeLLM`, params)
+      .reply(200, mockResponse);
+
+    const result = await base44.integrations.Core.InvokeLLM(params);
+    expect(result).toEqual(mockResponse);
+    expect(scope.isDone()).toBe(true);
+  });
+});