# This is a combination of 16 commits.

# This is the 1st commit message:

refactor: updating codeowners

# This is the commit message #2:

add chat functions

# This is the commit message #3:

use correct testing project

# This is the commit message #4:

refactor: adding system tests + updating corresponding chat samples

# This is the commit message #5:

add countTokens sample

# This is the commit message #6:

refactor: adding in region tags, abstracting out mimetype, adding new image ur

# This is the commit message #7:

refactor: updating gs url in test, fix to args getting passed to sample functions

# This is the commit message #8:

refactor: resolving file paths in tests, adding wait helper function

# This is the commit message #9:

add warning about safety concerns

# This is the commit message #10:

refactor:filling out nonstreamingchat and streamcontent tests

# This is the commit message #11:

add countTokens test

# This is the commit message #12:

refactor: filling out more streaming tests

# This is the commit message #13:

add safety settings test

# This is the commit message #14:

refactor: adding in stream content and multipart content tests

# This is the commit message #15:

feat: add new sendMultiModalPromptWithImage sample

# This is the commit message #16:

refactor: adding region tags

CODEOWNERS

@@ -50,6 +50,7 @@ monitoring/opencensus @GoogleCloudPlatform/nodejs-samples-reviewers
 
 # Data & AI
 ai-platform @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers
+generative-ai @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers
 automl @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers
 cloud-language @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers
 contact-center-insights @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/nodejs-samples-reviewers

generative-ai/snippets/countTokens.js

@@ -0,0 +1,52 @@
+// Copyright 2023 Google LLC
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+const { VertexAI } = require('@google-cloud/vertexai');
+
+async function countTokens(
+    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]  
+}
+
+countTokens(...process.argv.slice(2)).catch(err => {
+    console.error(err.message);
+    process.exitCode = 1;
+});

generative-ai/snippets/index.js

@@ -0,0 +1,124 @@
+const {
+  VertexAI,
+  HarmBlockThreshold,
+  HarmCategory,
+} = require('@google-cloud/vertexai');
+
+const project = 'cloud-llm-preview1';
+const location = 'us-central1';
+
+// Initialize Vertex with your Cloud project and location
+const vertex_ai = new VertexAI({project: project, location: location});
+
+// Instantiate the models
+const generativeModel = vertex_ai.preview.getGenerativeModel({
+  model: 'gemini-pro',
+  // 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_MEDIUM_AND_ABOVE,
+    },
+  ],
+  generation_config: {max_output_tokens: 256},
+});
+
+const generativeVisionModel = vertex_ai.preview.getGenerativeModel({
+  model: 'gemini-pro-vision',
+});
+
+async function streamContentTextOnly() {
+  const req = {
+    contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
+  };
+
+  const streamingResp = await generativeModel.generateContentStream(req);
+
+  for await (const item of streamingResp.stream) {
+    console.log('stream chunk:', item);
+  }
+
+  console.log('aggregated response: ', await streamingResp.response);
+}
+
+async function nonStreamingTextOnly() {
+  const req = {
+    contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
+  };
+
+  const nonstreamingResp = await generativeModel.generateContent(req);
+  console.log('non-streaming response: ', await nonstreamingResp.response);
+}
+
+async function countTokens() {
+  const req = {
+    contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
+  };
+
+  const countTokensResp = await generativeModel.countTokens(req);
+  console.log('count tokens response: ', countTokensResp);
+}
+
+async function nonStreamingChat() {
+  const chat = generativeModel.startChat({});
+  const result1 = await chat.sendMessage('hello');
+  console.log('send message result1: ', result1);
+  const resp1 = result1.response;
+  console.log('send message response1: ', resp1);
+  const result2 = await chat.sendMessage('what day is it today?');
+  console.log('result2: ', result2);
+  const resp2 = result2.response;
+  console.log('send message response2: ', resp2);
+  const result3 = await chat.sendMessage('what day is it tomorrow?');
+  console.log('result3: ', result3);
+  const resp3 = result3.response;
+  console.log('send message response3: ', resp3);
+}
+
+async function streamingChat() {
+  const chat = generativeModel.startChat({});
+  const streamResult1 = await chat.sendMessageStream('hello again');
+  console.log('stream result1: ', streamResult1);
+  const streamResp1 = await streamResult1.response;
+  console.log('stream send message response1: ', streamResp1);
+  const streamResult2 = await chat.sendMessageStream('what is the date today?');
+  console.log('stream result2: ', streamResult2);
+  const streamResp2 = await streamResult2.response;
+  console.log('stream send message response2: ', streamResp2);
+  const streamResult3 = await chat.sendMessageStream(
+    'what is the date tomorrow?'
+  );
+  console.log('stream result3: ', streamResult3);
+  const streamResp3 = await streamResult3.response;
+  console.log('stream send message response3: ', streamResp3);
+}
+
+async function multiPartContent() {
+  const filePart = {
+    file_data: {
+      file_uri: 'gs://sararob_imagegeneration_test/kitten.jpeg',
+      mime_type: 'image/jpeg',
+    },
+  };
+  const textPart = {text: 'What is this a picture of?'};
+
+  const request = {
+    contents: [{role: 'user', parts: [textPart, filePart]}],
+  };
+
+  const generativeVisionModel = vertex_ai.preview.getGenerativeModel({
+    model: 'gemini-pro-vision',
+  });
+
+  const resp = await generativeVisionModel.generateContentStream(request);
+  const contentResponse = await resp.response;
+  console.log(contentResponse.candidates[0].content);
+}
+
+nonStreamingTextOnly();
+streamContentTextOnly();
+countTokens();
+nonStreamingChat();
+streamingChat();
+multiPartContent();

generative-ai/snippets/nonStreamingChat.js

@@ -0,0 +1,73 @@
+// Copyright 2023 Google LLC
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+const {VertexAI} = require('@google-cloud/vertexai');
+
+function wait(time) {
+  return new Promise(resolve => {
+      setTimeout(resolve, time);
+  });
+}
+
+async function createNonStreamingChat(
+  projectId = 'PROJECT_ID',
+  location = 'LOCATION_ID',
+  model = 'MODEL'
+) {
+  // TODO: Find better method. Setting delay to give api time to respond, otherwise it will 404
+  // await wait(10);
+
+  // [START aiplatform_gemini_multiturn_chat]  
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const projectId = 'your-project-id';
+  // const location = 'us-central1';
+
+  // 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,
+  });
+
+  const chat = generativeModel.startChat({});
+
+  const chatInput1 = 'Hello';
+  console.log(`User: ${chatInput1}`);
+
+  const result1 = await chat.sendMessage(chatInput1);
+  const response1 = result1.response.candidates[0].content.parts[0].text;
+  console.log('Chat bot: ', response1);
+
+  const chatInput2 = 'Can you tell me a scientific fun fact?';
+  console.log(`User: ${chatInput2}`);
+  const result2 = await chat.sendMessage(chatInput2);
+  const response2 = result2.response.candidates[0].content.parts[0].text;
+  console.log('Chat bot: ', response2);
+
+  const chatInput3 = 'How can I learn more about that?';
+  console.log(`User: ${chatInput3}`);
+  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

@@ -0,0 +1,64 @@
+// Copyright 2023 Google LLC
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+const {VertexAI} = require('@google-cloud/vertexai');
+
+async function createNonStreamingContent(
+  projectId = 'PROJECT_ID',
+  location = 'LOCATION_ID',
+  model = 'MODEL'
+) {
+  // [START aiplatform_gemini_function_calling]    
+
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const projectId = 'your-project-id';
+  // const location = 'us-central1';
+
+  // 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,
+  });
+
+  const request = {
+    contents: [{role: 'user', parts: [{text: 'What is Node.js?'}]}],
+  };
+
+  console.log('Prompt:');
+  console.log(request.contents[0].parts[0].text);
+  console.log('Non-Streaming Response Text:');
+
+  // Create the response stream
+  const responseStream = await generativeModel.generateContentStream(request);
+
+  // Wait for the response stream to complete
+  const aggregatedResponse = await responseStream.response;
+
+  // Select the text from the response
+  const fullTextResponse =
+    aggregatedResponse.candidates[0].content.parts[0].text;
+
+  console.log(fullTextResponse);
+
+  // [END aiplatform_gemini_function_calling]
+}
+
+createNonStreamingContent(...process.argv.slice(2)).catch(err => {
+  console.error(err.message);
+  process.exitCode = 1;
+});