fix: resolve linting

generative-ai/snippets/countTokens.js

@@ -12,41 +12,41 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-const { VertexAI } = require('@google-cloud/vertexai');
+const {VertexAI} = require('@google-cloud/vertexai');
 
 async function countTokens(
-    projectId = 'PROJECT_ID',
-    location = 'LOCATION_ID',
-    model = 'MODEL'
+  projectId = 'PROJECT_ID',
+  location = 'LOCATION_ID',
+  model = 'MODEL'
 ) {
-    // [START aiplatform_gemini_token_count]  
-
-    /**
-     * TODO(developer): Uncomment these variables before running the sample.
-     */
-    // const projectId = 'your-project-id';
-    // const location = 'us-central1';
-    // const model = 'gemini-pro';
-
-    // Initialize Vertex with your Cloud project and location
-    const vertex_ai = new VertexAI({ project: projectId, location: location });
-
-    // Instantiate the model
-    const generativeModel = vertex_ai.preview.getGenerativeModel({
-        model: model,
-    });
-
-    const req = {
-        contents: [{ role: 'user', parts: [{ text: 'How are you doing today?' }] }],
-    };
-
-    const countTokensResp = await generativeModel.countTokens(req);
-    console.log('count tokens response: ', countTokensResp);
-    
-    // [END aiplatform_gemini_token_count]  
+  // [START aiplatform_gemini_token_count]
+
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const projectId = 'your-project-id';
+  // const location = 'us-central1';
+  // const model = 'gemini-pro';
+
+  // Initialize Vertex with your Cloud project and location
+  const vertex_ai = new VertexAI({project: projectId, location: location});
+
+  // Instantiate the model
+  const generativeModel = vertex_ai.preview.getGenerativeModel({
+    model: model,
+  });
+
+  const req = {
+    contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
+  };
+
+  const countTokensResp = await generativeModel.countTokens(req);
+  console.log('count tokens response: ', countTokensResp);
+
+  // [END aiplatform_gemini_token_count]
 }
 
 countTokens(...process.argv.slice(2)).catch(err => {
-    console.error(err.message);
-    process.exitCode = 1;
+  console.error(err.message);
+  process.exitCode = 1;
 });

generative-ai/snippets/nonStreamingChat.js

@@ -16,7 +16,7 @@ const {VertexAI} = require('@google-cloud/vertexai');
 
 function wait(time) {
   return new Promise(resolve => {
-      setTimeout(resolve, time);
+    setTimeout(resolve, time);
   });
 }
 
@@ -27,8 +27,8 @@ async function createNonStreamingChat(
 ) {
   // TODO: Find better method. Setting delay to give api time to respond, otherwise it will 404
   // await wait(10);
-  
-  // [START aiplatform_gemini_multiturn_chat]  
+
+  // [START aiplatform_gemini_multiturn_chat]
   /**
    * TODO(developer): Uncomment these variables before running the sample.
    */
@@ -63,11 +63,11 @@ async function createNonStreamingChat(
   const result3 = await chat.sendMessage(chatInput3);
   const response3 = result3.response.candidates[0].content.parts[0].text;
   console.log('Chat bot: ', response3);
-  
+
   // [END aiplatform_gemini_multiturn_chat]
 }
 
 createNonStreamingChat(...process.argv.slice(2)).catch(err => {
   console.error(err.message);
   process.exitCode = 1;
-});
+});

generative-ai/snippets/nonStreamingContent.js

@@ -19,8 +19,8 @@ async function createNonStreamingContent(
   location = 'LOCATION_ID',
   model = 'MODEL'
 ) {
-  // [START aiplatform_gemini_function_calling]    
-  
+  // [START aiplatform_gemini_function_calling]
+
   /**
    * TODO(developer): Uncomment these variables before running the sample.
    */
@@ -54,7 +54,7 @@ async function createNonStreamingContent(
     aggregatedResponse.candidates[0].content.parts[0].text;
 
   console.log(fullTextResponse);
-  
+
   // [END aiplatform_gemini_function_calling]
 }
 

generative-ai/snippets/nonStreamingMultipartContent.js

@@ -21,7 +21,7 @@ async function createNonStreamingMultipartContent(
   image = 'gs://generativeai-downloads/images/scones.jpg',
   mimeType = 'image/jpeg'
 ) {
-  // [START aiplatform_gemini_get_started] 
+  // [START aiplatform_gemini_get_started]
 
   /**
    * TODO(developer): Uncomment these variables before running the sample.
@@ -71,8 +71,8 @@ async function createNonStreamingMultipartContent(
     aggregatedResponse.candidates[0].content.parts[0].text;
 
   console.log(fullTextResponse);
-   
-  // [END aiplatform_gemini_get_started] 
+
+  // [END aiplatform_gemini_get_started]
 }
 
 createNonStreamingMultipartContent(...process.argv.slice(2)).catch(err => {

generative-ai/snippets/safetySettings.js

@@ -12,59 +12,61 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-const { VertexAI, HarmCategory, HarmBlockThreshold } = require('@google-cloud/vertexai');
+const {
+  VertexAI,
+  HarmCategory,
+  HarmBlockThreshold,
+} = require('@google-cloud/vertexai');
 
-async function createStreamContent(
-) {
-    // [START aiplatform_gemini_safety_settings]  
-    /**
-     * TODO(developer): Uncomment these variables before running the sample.
-     */
-    const projectId = 'cloud-llm-preview1';
-    const location = 'us-central1';
-    const model = 'gemini-pro'
+async function createStreamContent() {
+  // [START aiplatform_gemini_safety_settings]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  const projectId = 'cloud-llm-preview1';
+  const location = 'us-central1';
+  const model = 'gemini-pro';
 
-    // Initialize Vertex with your Cloud project and location
-    const vertexAI = new VertexAI({ project: projectId, location: location });
+  // Initialize Vertex with your Cloud project and location
+  const vertexAI = new VertexAI({project: projectId, location: location});
 
-    // Instantiate the model
-    const generativeModel = vertexAI.preview.getGenerativeModel({
-        model: model,
-        // The following parameters are optional
-        // They can also be passed to individual content generation requests
-        safety_settings: [
-          {
-            category: HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT,
-            threshold: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
-          },
-        ],
-        generation_config: {max_output_tokens: 256},
-    });
+  // Instantiate the model
+  const generativeModel = vertexAI.preview.getGenerativeModel({
+    model: model,
+    // The following parameters are optional
+    // They can also be passed to individual content generation requests
+    safety_settings: [
+      {
+        category: HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT,
+        threshold: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
+      },
+    ],
+    generation_config: {max_output_tokens: 256},
+  });
 
-    const request = {
-        contents: [{ role: 'user', parts: [{ text: 'Tell me something dangerous.' }] }],
-    };
+  const request = {
+    contents: [{role: 'user', parts: [{text: 'Tell me something dangerous.'}]}],
+  };
 
-    console.log('Prompt:');
-    console.log(request.contents[0].parts[0].text);
-    console.log('Streaming Response Text:');
+  console.log('Prompt:');
+  console.log(request.contents[0].parts[0].text);
+  console.log('Streaming Response Text:');
 
-    // Create the response stream
-    const responseStream = await generativeModel.generateContentStream(request);
+  // Create the response stream
+  const responseStream = await generativeModel.generateContentStream(request);
 
-    // Log the text response as it streams
-    for await (const item of responseStream.stream) {
-        if (item.candidates[0].finishReason === 'SAFETY') {
-            console.log('This response stream terminated due to safety concerns.')
-        } else {
-            process.stdout.write(item.candidates[0].content.parts[0].text);
-        }
+  // Log the text response as it streams
+  for await (const item of responseStream.stream) {
+    if (item.candidates[0].finishReason === 'SAFETY') {
+      console.log('This response stream terminated due to safety concerns.');
+    } else {
+      process.stdout.write(item.candidates[0].content.parts[0].text);
     }
-    // [END aiplatform_gemini_safety_settings]  
+  }
+  // [END aiplatform_gemini_safety_settings]
 }
 
-
 createStreamContent(...process.argv.slice(3)).catch(err => {
-    console.error(err.message);
-    process.exitCode = 1;
+  console.error(err.message);
+  process.exitCode = 1;
 });

generative-ai/snippets/sendMultiModalPromptWithImage.js

@@ -19,14 +19,11 @@ async function sendMultiModalPromptWithImage(
   location = 'LOCATION_ID',
   model = 'MODEL'
 ) {
-  // [START aiplatform_gemini_single_turn_multi_image]  
-
-
-
- // [END aiplatform_gemini_single_turn_multi_image]
+  // [START aiplatform_gemini_single_turn_multi_image]
+  // [END aiplatform_gemini_single_turn_multi_image]
 }
 
 sendMultiModalPromptWithImage(...process.argv.slice(2)).catch(err => {
- console.error(err.message);
- process.exitCode = 1;
-});
+  console.error(err.message);
+  process.exitCode = 1;
+});

generative-ai/snippets/sendMultiModalPromptWithVideo.js

@@ -19,14 +19,11 @@ async function sendMultiModalPromptWithImage(
   location = 'LOCATION_ID',
   model = 'MODEL'
 ) {
-  // [START aiplatform_gemini_single_turn_video]  
-
-
-
+  // [START aiplatform_gemini_single_turn_video]
   // [END aiplatform_gemini_single_turn_video]
 }
 
 sendMultiModalPromptWithImage(...process.argv.slice(2)).catch(err => {
   console.error(err.message);
   process.exitCode = 1;
-});
+});

generative-ai/snippets/streamChat.js

@@ -19,7 +19,7 @@ async function createStreamChat(
   location = 'LOCATION_ID',
   model = 'MODEL'
 ) {
-  // [START aiplatform_gemini_multiturn_chat] 
+  // [START aiplatform_gemini_multiturn_chat]
 
   /**
    * TODO(developer): Uncomment these variables before running the sample.
@@ -43,7 +43,7 @@ async function createStreamChat(
   for await (const item of result1.stream) {
     console.log(item.candidates[0].content.parts[0].text);
   }
-  
+
   // [END aiplatform_gemini_multiturn_chat]
 }
 

generative-ai/snippets/streamContent.js

@@ -20,7 +20,7 @@ async function createStreamContent(
   model = 'MODEL'
 ) {
   // [START aiplatform_gemini_function_calling]
-  
+
   /**
    * TODO(developer): Uncomment these variables before running the sample.
    */
@@ -50,7 +50,7 @@ async function createStreamContent(
   for await (const item of responseStream.stream) {
     process.stdout.write(item.candidates[0].content.parts[0].text);
   }
-  
+
   // [END aiplatform_gemini_function_calling]
 }
 

generative-ai/snippets/streamMultipartContent.js

@@ -22,7 +22,7 @@ async function createStreamMultipartContent(
   mimeType = 'image/jpeg'
 ) {
   // [START aiplatform_gemini_get_started]
-  
+
   /**
    * TODO(developer): Uncomment these variables before running the sample.
    */
@@ -67,7 +67,7 @@ async function createStreamMultipartContent(
   for await (const item of responseStream.stream) {
     process.stdout.write(item.candidates[0].content.parts[0].text);
   }
-  
+
   // [END aiplatform_gemini_get_started]
 }
 

generative-ai/snippets/test/countTokens.test.js

@@ -30,7 +30,7 @@ describe('Count tokens', async () => {
       `node ./countTokens.js ${project} ${location} ${model}`
     );
 
-    // Expect 6 tokens 
+    // Expect 6 tokens
     assert(output.match('totalTokens: 6'));
   });
 });

generative-ai/snippets/test/nonStreamingChat.test.js

@@ -29,7 +29,7 @@ describe('Generative AI NonStreaming Chat', async () => {
     const output = execSync(
       `node ./nonStreamingChat.js ${project} ${location} ${model}`
     );
-  
+
     // Ensure that the beginning of the conversation is consistent
     assert(output.match(/User: Hello/));
     assert(output.match(/User: Can you tell me a scientific fun fact?/));

generative-ai/snippets/test/safetySettings.test.js

@@ -31,6 +31,8 @@ describe('Safety settings', async () => {
     );
 
     // Expect rejection due to safety concerns
-    assert(output.match('This response stream terminated due to safety concerns'));
+    assert(
+      output.match('This response stream terminated due to safety concerns')
+    );
   });
 });

generative-ai/snippets/test/streamContent.test.js

@@ -29,7 +29,6 @@ describe('Generative AI Stream Content', () => {
     const output = execSync(
       `node ./streamContent.js ${project} ${location} ${model}`
     );
-;
     // Ensure that the beginning of the conversation is consistent
     assert(output.match(/Prompt:/));
     assert(output.match(/What is Node.js/));

generative-ai/snippets/test/streamMultipartContent.test.js

@@ -31,7 +31,7 @@ describe('Generative AI Stream Multipart Content', () => {
       `node ./streamMultipartContent.js ${project} ${location} ${model} ${image}`
     );
     // Split up conversation output
-    const conversation  = output.split('\n');
+    const conversation = output.split('\n');
 
     // Ensure that the conversation is what we expect for this scone image
     assert(conversation[0].match(/Prompt Text:/));