feat: add Vertex AI for Firebase snippets

packages/firebase_snippets_app/lib/snippets/vertex_ai.dart

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+// Copyright 2024 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
+//
+//      http://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.
+
+// ignore_for_file: avoid_print, unused_local_variable
+
+import 'dart:io';
+
+import 'package:firebase_core/firebase_core.dart';
+import 'package:firebase_vertexai/firebase_vertexai.dart';
+import 'package:firebase_snippets_app/snippets/snippet_base.dart';
+
+class VertexAISnippets extends DocSnippet {
+  late final GenerativeModel model;
+
+  @override
+  void runAll() {
+    initializeModel();
+    configureModel();
+    safetySetting();
+    multiSafetySetting();
+    textGenTextOnlyPromptStream();
+    textGenTextOnlyPrompt();
+    textGenMultimodalOneImagePromptStream();
+    textGenMultimodalOneImagePrompt();
+    textGenMultiModalMultiImagePromptStreaming();
+    textGenMultiModalMultiImagePrompt();
+    textGenMultiModalVideoPromptStreaming();
+    textGenMultiModalVideoPrompt();
+    countTokensText();
+    countTokensTextImage();
+    chatStream();
+    chat();
+    setSystemInstructions();
+  }
+
+  void initializeModel() async {
+    // [START initialize_model]
+    // Initialize FirebaseApp
+    await Firebase.initializeApp();
+    // Initialize the {{vertexai}} service and the generative model
+    // Specify a model that supports your use case
+    // Gemini 1.5 models are versatile and can be used with all API capabilities
+    final model = FirebaseVertexAI.instance
+        .generativeModel(model: 'gemini-1.5-flash');
+    // [END initialize_model]
+  }
+
+  void configureModel() {
+    // [START configure_model]
+    // ...
+
+    final generationConfig = GenerationConfig(
+      maxOutputTokens: 200,
+      stopSequences: ["red"],
+      temperature: 0.9,
+      topP: 0.1,
+      topK: 16,
+    );
+    final model = FirebaseVertexAI.instance.generativeModel(
+      model: 'gemini-1.5-flash',
+      generationConfig: generationConfig,
+    );
+
+    // ...
+    // [END configure_model]
+  }
+
+  void safetySetting() {
+    // [START safety_setting]
+    // ...
+
+    final safetySettings = [
+      SafetySetting(HarmCategory.harassment, HarmBlockThreshold.high)
+    ];
+    final model = FirebaseVertexAI.instance.generativeModel(
+      model: 'gemini-1.5-flash',
+      safetySettings: safetySettings,
+    );
+
+    // ...
+    // [END safety_setting]
+  }
+
+  void multiSafetySetting() {
+    // [START multi_safety_setting]
+    // ...
+
+    final safetySettings = [
+      SafetySetting(HarmCategory.harassment, HarmBlockThreshold.high),
+      SafetySetting(HarmCategory.hateSpeech, HarmBlockThreshold.high),
+    ];
+    final model = FirebaseVertexAI.instance.generativeModel(
+      model: 'gemini-1.5-flash',
+      safetySettings: safetySettings,
+    );
+
+    // ...
+    // [END multi_safety_setting]
+  }
+
+  void textGenTextOnlyPromptStream() async {
+    // [START text_gen_text_only_prompt_streaming]
+    // Provide a prompt that contains text
+    final prompt = [Content.text('Write a story about a magic backpack.')];
+
+    // To stream generated text output, call generateContentStream with the text input
+    final response = model.generateContentStream(prompt);
+    await for (final chunk in response) {
+      print(chunk.text);
+    }
+    // [END text_gen_text_only_prompt_streaming]
+  }
+
+  void textGenTextOnlyPrompt() async {
+    // [START text_gen_text_only_prompt]
+    // Provide a prompt that contains text
+    final prompt = [Content.text('Write a story about a magic backpack.')];
+
+    // To generate text output, call generateContent with the text input
+    final response = await model.generateContent(prompt);
+    print(response.text);
+    // [END text_gen_text_only_prompt]
+  }
+
+  void textGenMultimodalOneImagePromptStream() async {
+    // [START text_gen_multimodal_one_image_prompt_streaming]
+    // Provide a text prompt to include with the image
+    final prompt = TextPart("What's in the picture?");
+    // Prepare images for input
+    final image = await File('image0.jpg').readAsBytes();
+    final imagePart = DataPart('image/jpeg', image);
+
+    // To stream generated text output, call generateContentStream with the text and image
+    final response = await model.generateContentStream([
+      Content.multi([prompt, imagePart])
+    ]);
+    await for (final chunk in response) {
+      print(chunk.text);
+    }
+    // [END text_gen_multimodal_one_image_prompt_streaming]
+  }
+
+  void textGenMultimodalOneImagePrompt() async {
+    // [START text_gen_multimodal_one_image_prompt]
+    // Provide a text prompt to include with the image
+    final prompt = TextPart("What's in the picture?");
+    // Prepare images for input
+    final image = await File('image0.jpg').readAsBytes();
+    final imagePart = DataPart('image/jpeg', image);
+
+    // To generate text output, call generateContent with the text and image
+    final response = await model.generateContent([
+      Content.multi([prompt, imagePart])
+    ]);
+    print(response.text);
+    // [END text_gen_multimodal_one_image_prompt]
+  }
+
+  void textGenMultiModalMultiImagePromptStreaming() async {
+    // [START text_gen_multimodal_multi_image_prompt_streaming]
+    final (firstImage, secondImage) = await (
+      File('image0.jpg').readAsBytes(),
+      File('image1.jpg').readAsBytes()
+    ).wait;
+    // Provide a text prompt to include with the images
+    final prompt = TextPart("What's different between these pictures?");
+    // Prepare images for input
+    final imageParts = [
+      DataPart('image/jpeg', firstImage),
+      DataPart('image/jpeg', secondImage),
+    ];
+
+    // To stream generated text output, call generateContentStream with the text and images
+    final response = model.generateContentStream([
+      Content.multi([prompt, ...imageParts])
+    ]);
+    await for (final chunk in response) {
+      print(chunk.text);
+    }
+    // [END text_gen_multimodal_multi_image_prompt_streaming]
+  }
+
+  void textGenMultiModalMultiImagePrompt() async {
+    // [START text_gen_multimodal_multi_image_prompt]
+    final (firstImage, secondImage) = await (
+      File('image0.jpg').readAsBytes(),
+      File('image1.jpg').readAsBytes()
+    ).wait;
+    // Provide a text prompt to include with the images
+    final prompt = TextPart("What's different between these pictures?");
+    // Prepare images for input
+    final imageParts = [
+      DataPart('image/jpeg', firstImage),
+      DataPart('image/jpeg', secondImage),
+    ];
+
+    // To generate text output, call generateContent with the text and images
+    final response = await model.generateContent([
+      Content.multi([prompt, ...imageParts])
+    ]);
+    print(response.text);
+    // [END text_gen_multimodal_multi_image_prompt]
+  }
+
+  void textGenMultiModalVideoPromptStreaming() async {
+    // [START text_gen_multimodal_video_prompt_streaming]
+    // Provide a text prompt to include with the video
+    final prompt = TextPart("What's in the video?");
+
+    // Prepare video for input
+    final video = await File('video0.mp4').readAsBytes();
+
+    // Provide the video as `Data` with the appropriate mimetype
+    final videoPart = DataPart('video/mp4', video);
+
+    // To stream generated text output, call generateContentStream with the text and image
+    final response = model.generateContentStream([
+      Content.multi([prompt, videoPart])
+    ]);
+    await for (final chunk in response) {
+      print(chunk.text);
+    }
+    // [END text_gen_multimodal_video_prompt_streaming]
+  }
+
+  void textGenMultiModalVideoPrompt() async {
+    // [START text_gen_multimodal_video_prompt]
+    // Provide a text prompt to include with the video
+    final prompt = TextPart("What's in the video?");
+
+    // Prepare video for input
+    final video = await File('video0.mp4').readAsBytes();
+
+    // Provide the video as `Data` with the appropriate mimetype
+    final videoPart = DataPart('video/mp4', video);
+
+    // To generate text output, call generateContent with the text and images
+    final response = await model.generateContent([
+      Content.multi([prompt, videoPart])
+    ]);
+    print(response.text);
+    // [END text_gen_multimodal_video_prompt]
+  }
+
+  void countTokensText() async {
+    // [START count_tokens_text]
+    // Provide a prompt that contains text
+    final prompt = [Content.text('Write a story about a magic backpack.')];
+
+    // Count tokens and billable characters before calling generateContent
+    final tokenCount = await model.countTokens(prompt);
+    print('Token count: ${tokenCount.totalTokens}');
+    print('Billable characters: ${tokenCount.totalBillableCharacters}');
+
+    // To generate text output, call generateContent with the text input
+    final response = await model.generateContent(prompt);
+    print(response.text);
+    // [END count_tokens_text]
+  }
+
+  void countTokensTextImage() async {
+    // [START count_tokens_text_image]
+    // Provide a text prompt to include with the image
+    final prompt = TextPart("What's in the picture?");
+    // Prepare image for input
+    final image = await File('image0.jpg').readAsBytes();
+    final imagePart = DataPart('image/jpeg', image);
+
+    // Count tokens and billable characters before calling generateContent
+    final tokenCount = await model.countTokens([
+      Content.multi([prompt, imagePart])
+    ]);
+    print('Token count: ${tokenCount.totalTokens}');
+    print('Billable characters: ${tokenCount.totalBillableCharacters}');
+
+    // To generate text output, call generateContent with the text and image
+    final response = await model.generateContent([
+      Content.multi([prompt, imagePart])
+    ]);
+    print(response.text);
+    // [END count_tokens_text_image]
+  }
+
+  void chatStream() async {
+    // [START chat_streaming]
+    final chat = model.startChat();
+    // Provide a prompt that contains text
+    final prompt = Content.text('Write a story about a magic backpack.');
+
+    final response = chat.sendMessageStream(prompt);
+    await for (final chunk in response) {
+      print(chunk.text);
+    }
+    // [END chat_streaming]
+  }
+
+  void chat() async {
+    // [START chat]
+    final chat = model.startChat();
+    // Provide a prompt that contains text
+    final prompt = Content.text('Write a story about a magic backpack.');
+
+    final response = await chat.sendMessage(prompt);
+    print(response.text);
+    // [END chat]
+  }
+
+  void setSystemInstructions() async {
+    // [START system_instructions_text]
+    await Firebase.initializeApp();
+    // Initialize the Vertex AI service and the generative model
+    // Specify a model that supports system instructions, like a Gemini 1.5 model
+    final model = FirebaseVertexAI.instance.generativeModel(
+      model: 'gemini-1.5-flash-preview-0514',
+      systemInstruction: Content.system('You are a cat. Your name is Neko.'),
+    );
+    // [END system_instructions_text]
+  }
+}