chore(js): update Gemini models in docs and samples

js/ai/src/model-types.ts

@@ -174,7 +174,7 @@ export const GenerationCommonConfigSchema = z
     version: z
       .string()
       .describe(
-        'A specific version of a model family, e.g. `gemini-2.0-flash` ' +
+        'A specific version of a model family, e.g. `gemini-2.5-flash` ' +
           'for the `googleai` family.'
       )
       .optional(),

js/core/src/registry.ts

@@ -88,7 +88,7 @@ interface ParsedRegistryKey {
 /**
  * Parses the registry key into key parts as per the key format convention. Ex:
  *  - mcp-host:tool/my-tool
- *  - /model/googleai/gemini-2.0-flash
+ *  - /model/googleai/gemini-2.5-flash
  *  - /prompt/my-plugin/folder/my-prompt
  *  - /util/generate
  */
@@ -124,7 +124,7 @@ export function parseRegistryKey(
     // Invalid key format
     return undefined;
   }
-  // ex: /model/googleai/gemini-2.0-flash or /prompt/my-plugin/folder/my-prompt
+  // ex: /model/googleai/gemini-2.5-flash or /prompt/my-plugin/folder/my-prompt
   if (tokens.length >= 4) {
     return {
       actionType: tokens[1] as ActionType,

js/doc-snippets/src/dotprompt/index.ts

@@ -153,7 +153,7 @@ function fn09() {
   // [START definePromptTempl]
   const myPrompt = ai.definePrompt({
     name: 'myPrompt',
-    model: 'googleai/gemini-1.5-flash',
+    model: 'googleai/gemini-2.5-flash',
     input: {
       schema: z.object({
         name: z.string(),
@@ -168,7 +168,7 @@ function fn10() {
   // [START definePromptFn]
   const myPrompt = ai.definePrompt({
     name: 'myPrompt',
-    model: 'googleai/gemini-1.5-flash',
+    model: 'googleai/gemini-2.5-flash',
     input: {
       schema: z.object({
         name: z.string(),

js/doc-snippets/src/dotprompt/prompts/ex01.prompt

@@ -1,5 +1,5 @@
 ---
-model: googleai/gemini-1.5-flash
+model: googleai/gemini-2.5-flash
 config:
   temperature: 0.9
 input:

js/doc-snippets/src/dotprompt/prompts/ex02.prompt

@@ -1,4 +1,4 @@
 ---
-model: vertexai/gemini-1.5-flash
+model: vertexai/gemini-2.5-flash
 ---
 You are the world's most welcoming AI assistant. Greet the user and offer your assistance.

js/doc-snippets/src/dotprompt/prompts/ex03.prompt

@@ -1,5 +1,5 @@
 ---
-model: googleai/gemini-1.5-flash
+model: googleai/gemini-2.5-flash
 config:
   temperature: 1.4
   topK: 50

js/doc-snippets/src/dotprompt/prompts/ex04.prompt

@@ -1,5 +1,5 @@
 ---
-model: googleai/gemini-1.5-flash
+model: googleai/gemini-2.5-flash
 input:
   schema:
     theme?: string

js/doc-snippets/src/dotprompt/prompts/ex05.prompt

@@ -1,5 +1,5 @@
 ---
-model: googleai/gemini-1.5-flash
+model: googleai/gemini-2.5-flash
 input:
   schema:
     theme?: string

js/doc-snippets/src/dotprompt/prompts/ex06.prompt

@@ -1,5 +1,5 @@
 ---
-model: vertexai/gemini-1.5-flash
+model: vertexai/gemini-2.5-flash
 input:
   schema:
     userQuestion: string

js/doc-snippets/src/dotprompt/prompts/ex08.prompt

@@ -1,5 +1,5 @@
 ---
-model: vertexai/gemini-1.5-flash
+model: vertexai/gemini-2.5-flash
 input:
   schema:
     photoUrl: string

js/doc-snippets/src/flows/index.ts

@@ -29,7 +29,7 @@ export const menuSuggestionFlow = ai.defineFlow(
   },
   async (restaurantTheme) => {
     const { text } = await ai.generate({
-      model: googleAI.model('gemini-2.0-flash'),
+      model: googleAI.model('gemini-2.5-flash'),
       prompt: `Invent a menu item for a ${restaurantTheme} themed restaurant.`,
     });
     return text;
@@ -51,7 +51,7 @@ export const menuSuggestionFlowWithSchema = ai.defineFlow(
   },
   async (restaurantTheme) => {
     const { output } = await ai.generate({
-      model: googleAI.model('gemini-2.0-flash'),
+      model: googleAI.model('gemini-2.5-flash'),
       prompt: `Invent a menu item for a ${restaurantTheme} themed restaurant.`,
       output: { schema: MenuItemSchema },
     });
@@ -72,7 +72,7 @@ export const menuSuggestionFlowMarkdown = ai.defineFlow(
   },
   async (restaurantTheme) => {
     const { output } = await ai.generate({
-      model: googleAI.model('gemini-2.0-flash'),
+      model: googleAI.model('gemini-2.5-flash'),
       prompt: `Invent a menu item for a ${restaurantTheme} themed restaurant.`,
       output: { schema: MenuItemSchema },
     });
@@ -94,7 +94,7 @@ export const menuSuggestionStreamingFlow = ai.defineFlow(
   },
   async (restaurantTheme, { sendChunk }) => {
     const response = await ai.generateStream({
-      model: googleAI.model('gemini-2.0-flash'),
+      model: googleAI.model('gemini-2.5-flash'),
       prompt: `Invent a menu item for a ${restaurantTheme} themed restaurant.`,
     });
 
@@ -128,7 +128,7 @@ export const complexMenuSuggestionFlow = ai.defineFlow(
     outputSchema: PrixFixeMenuSchema,
   },
   async (theme: string): Promise<z.infer<typeof PrixFixeMenuSchema>> => {
-    const chat = ai.chat({ model: googleAI.model('gemini-2.0-flash') });
+    const chat = ai.chat({ model: googleAI.model('gemini-2.5-flash') });
     await chat.send('What makes a good prix fixe menu?');
     await chat.send(
       'What are some ingredients, seasonings, and cooking techniques that ' +
@@ -178,7 +178,7 @@ Today's menu
       }
     );
     const { text } = await ai.generate({
-      model: googleAI.model('gemini-2.0-flash'),
+      model: googleAI.model('gemini-2.5-flash'),
       system: "Help the user answer questions about today's menu.",
       prompt: input,
       docs: [{ content: [{ text: menu }] }],

js/doc-snippets/src/index.ts

@@ -19,7 +19,7 @@ import { genkit } from 'genkit';
 
 const ai = genkit({
   plugins: [googleAI()],
-  model: googleAI.model('gemini-2.0-flash'),
+  model: googleAI.model('gemini-2.5-flash'),
 });
 
 async function main() {

js/doc-snippets/src/models/index.ts

@@ -19,13 +19,13 @@ import { genkit } from 'genkit';
 
 const ai = genkit({
   plugins: [googleAI()],
-  model: googleAI.model('gemini-2.0-flash'),
+  model: googleAI.model('gemini-2.5-flash'),
 });
 
 async function fn01() {
   // [START ex01]
   const { text } = await ai.generate({
-    model: googleAI.model('gemini-2.0-flash'),
+    model: googleAI.model('gemini-2.5-flash'),
     prompt: 'Invent a menu item for a pirate themed restaurant.',
   });
   // [END ex01]
@@ -34,7 +34,7 @@ async function fn01() {
 async function fn02() {
   // [START ex02]
   const { text } = await ai.generate({
-    model: 'googleai/gemini-2.0-flash-001',
+    model: 'googleai/gemini-2.5-flash-001',
     prompt: 'Invent a menu item for a pirate themed restaurant.',
   });
   // [END ex02]

js/doc-snippets/src/models/minimal.ts

@@ -20,7 +20,7 @@ import { genkit } from 'genkit';
 
 const ai = genkit({
   plugins: [googleAI()],
-  model: googleAI.model('gemini-2.0-flash'),
+  model: googleAI.model('gemini-2.5-flash'),
 });
 
 async function main() {

js/genkit/tests/prompts/badSchemaRef.prompt

@@ -1,9 +1,9 @@
 ---
-model: googleai/gemini-1.5-flash
+model: googleai/gemini-2.5-flash
 input:
   schema: badSchemaRef1
 output:
   schema: badSchemaRef2
 ---
 
-doesn't matter
+doesn't matter

js/genkit/tests/prompts/schemaRef.prompt

@@ -1,9 +1,9 @@
 ---
-model: googleai/gemini-1.5-flash
+model: googleai/gemini-2.5-flash
 input:
   schema: myInputSchema
 output:
   schema: myOutputSchema
 ---
 
-Write a poem about {{foo}}.
+Write a poem about {{foo}}.

js/plugins/google-genai/tests/common/utils_test.ts

@@ -55,15 +55,15 @@ describe('Common Utils', () => {
   describe('extractVersion', () => {
     it('should return version from modelRef if present', () => {
       const ref = modelRef({
-        name: 'vertexai/gemini-1.5-pro',
-        version: 'gemini-1.5-pro-001',
+        name: 'vertexai/gemini-2.5-pro',
+        version: 'gemini-2.5-pro-001',
       });
-      assert.strictEqual(extractVersion(ref), 'gemini-1.5-pro-001');
+      assert.strictEqual(extractVersion(ref), 'gemini-2.5-pro-001');
     });
 
     it('should extract version from name if version field is missing', () => {
-      const ref = modelRef({ name: 'vertexai/gemini-1.5-flash' });
-      assert.strictEqual(extractVersion(ref), 'gemini-1.5-flash');
+      const ref = modelRef({ name: 'vertexai/gemini-2.5-flash' });
+      assert.strictEqual(extractVersion(ref), 'gemini-2.5-flash');
     });
 
     it('should work with embedderRef', () => {
@@ -75,12 +75,12 @@ describe('Common Utils', () => {
   describe('modelName', () => {
     it('extracts model name from a full path', () => {
       assert.strictEqual(
-        modelName('models/googleai/gemini-1.5-pro'),
-        'gemini-1.5-pro'
+        modelName('models/googleai/gemini-2.5-pro'),
+        'gemini-2.5-pro'
       );
       assert.strictEqual(
-        modelName('vertexai/gemini-1.5-flash'),
-        'gemini-1.5-flash'
+        modelName('vertexai/gemini-2.5-flash'),
+        'gemini-2.5-flash'
       );
       assert.strictEqual(modelName('model/foo'), 'foo');
       assert.strictEqual(modelName('embedders/bar'), 'bar');
@@ -102,8 +102,8 @@ describe('Common Utils', () => {
 
   describe('checkModelName', () => {
     it('extracts model name from a full path', () => {
-      const name = 'models/vertexai/gemini-1.5-pro';
-      assert.strictEqual(checkModelName(name), 'gemini-1.5-pro');
+      const name = 'models/vertexai/gemini-2.5-pro';
+      assert.strictEqual(checkModelName(name), 'gemini-2.5-pro');
     });
 
     it('returns name if no prefix', () => {

js/plugins/google-genai/tests/googleai/client_test.ts

@@ -108,12 +108,12 @@ describe('Google AI Client', () => {
 
     it('should build URL with resourceMethod', () => {
       const url = getGoogleAIUrl({
-        resourcePath: 'models/gemini-2.0-pro',
+        resourcePath: 'models/gemini-2.5-pro',
         resourceMethod: 'generateContent',
       });
       assert.strictEqual(
         url,
-        `${defaultBaseUrl}/${defaultApiVersion}/models/gemini-2.0-pro:generateContent`
+        `${defaultBaseUrl}/${defaultApiVersion}/models/gemini-2.5-pro:generateContent`
       );
     });
 
@@ -164,7 +164,7 @@ describe('Google AI Client', () => {
   describe('listModels', () => {
     it('should return a list of models', async () => {
       const mockModels: Model[] = [
-        { name: 'models/gemini-2.0-pro' } as Model,
+        { name: 'models/gemini-2.5-pro' } as Model,
         { name: 'models/gemini-2.5-flash' } as Model,
       ];
       mockFetchResponse({ models: mockModels });
@@ -242,7 +242,7 @@ describe('Google AI Client', () => {
   });
 
   describe('generateContent', () => {
-    const model = 'gemini-2.0-pro';
+    const model = 'gemini-2.5-pro';
     const request: GenerateContentRequest = {
       contents: [{ role: 'user', parts: [{ text: 'hello' }] }],
     };

js/plugins/google-genai/tests/googleai/gemini_test.ts

@@ -105,12 +105,12 @@ describe('Google AI Gemini', () => {
     describe('API Key Handling', () => {
       it('throws if no API key is provided', () => {
         assert.throws(() => {
-          defineModel('gemini-2.0-flash');
+          defineModel('gemini-2.5-flash');
         }, MISSING_API_KEY_ERROR);
       });
 
       it('uses API key from pluginOptions', async () => {
-        const model = defineModel('gemini-2.0-flash', {
+        const model = defineModel('gemini-2.5-flash', {
           apiKey: 'plugin-key',
         });
         mockFetchResponse(defaultApiResponse);
@@ -125,7 +125,7 @@ describe('Google AI Gemini', () => {
 
       it('uses API key from GEMINI_API_KEY env var', async () => {
         process.env.GEMINI_API_KEY = 'gemini-key';
-        const model = defineModel('gemini-2.0-flash');
+        const model = defineModel('gemini-2.5-flash');
         mockFetchResponse(defaultApiResponse);
         await model.run(minimalRequest);
         const fetchOptions = fetchStub.lastCall.args[1];
@@ -136,7 +136,7 @@ describe('Google AI Gemini', () => {
       });
 
       it('throws if apiKey is false and not in call config', async () => {
-        const model = defineModel('gemini-2.0-flash', { apiKey: false });
+        const model = defineModel('gemini-2.5-flash', { apiKey: false });
         await assert.rejects(
           model.run(minimalRequest),
           /GoogleAI plugin was initialized with \{apiKey: false\}/
@@ -145,7 +145,7 @@ describe('Google AI Gemini', () => {
       });
 
       it('uses API key from call config if apiKey is false', async () => {
-        const model = defineModel('gemini-2.0-flash', { apiKey: false });
+        const model = defineModel('gemini-2.5-flash', { apiKey: false });
         mockFetchResponse(defaultApiResponse);
         const request: GenerateRequest<typeof GeminiConfigSchema> = {
           ...minimalRequest,
@@ -289,7 +289,7 @@ describe('Google AI Gemini', () => {
 
     describe('Error Handling', () => {
       it('throws if no candidates are returned', async () => {
-        const model = defineModel('gemini-2.0-flash', defaultPluginOptions);
+        const model = defineModel('gemini-2.5-flash', defaultPluginOptions);
         mockFetchResponse({ candidates: [] });
         await assert.rejects(
           model.run(minimalRequest),
@@ -298,7 +298,7 @@ describe('Google AI Gemini', () => {
       });
 
       it('throws on fetch error', async () => {
-        const model = defineModel('gemini-2.0-flash', defaultPluginOptions);
+        const model = defineModel('gemini-2.5-flash', defaultPluginOptions);
         fetchStub.rejects(new Error('Network error'));
         await assert.rejects(model.run(minimalRequest), /Failed to fetch/);
       });
@@ -317,7 +317,7 @@ describe('Google AI Gemini', () => {
       });
 
       it('API call works with debugTraces: false', async () => {
-        const model = defineModel('gemini-2.0-flash', {
+        const model = defineModel('gemini-2.5-flash', {
           ...defaultPluginOptions,
           experimental_debugTraces: false,
         });
@@ -331,7 +331,7 @@ describe('Google AI Gemini', () => {
 
   describe('gemini() function', () => {
     it('returns a ModelReference for a known model string', () => {
-      const name = 'gemini-2.0-flash';
+      const name = 'gemini-2.5-flash';
       const modelRef = model(name);
       assert.strictEqual(modelRef.name, `googleai/${name}`);
       assert.strictEqual(modelRef.info?.supports?.multiturn, true);