Class AiService

firebase-ai-logic-angular-example/src/app/ai.service.ts:25–151

  providedIn: "root",
})
export class AiService {
  private readonly model: GenerativeModel;
  private readonly products: ProductService = inject(ProductService);
  private readonly chat: ChatSession;

  constructor(@Inject("FIREBASE_APP") private firebaseApp: FirebaseApp) {
    const productsToolSet: FunctionDeclarationsTool = {
      functionDeclarations: [
        {
          name: "getNumberOfProducts",
          description:
            "Get a count of the number of products available in the inventory.",
        },
        {
          name: "getProducts",
          description:
            "Get an array of the products with the name and price of each product.",
        },
        {
          name: "addToCart",
          description: "Add one or more products to the cart.",
          parameters: Schema.object({
            properties: {
              productsToAdd: Schema.array({
                items: Schema.object({
                  description: "A single product with its name and price.",
                  properties: {
                    name: Schema.string({
                      description: "The name of the product.",
                    }),
                    price: Schema.number({
                      description: "The numerical price of the product.",
                    }),
                  },
                  // Specify which properties within each product object are required
                  required: ["name", "price"],
                }),
              }),
            },
          }) as ObjectSchemaInterface,
        },
      ],
    };

    // Initialize the Vertex AI service
    const vertexAI = getVertexAI(this.firebaseApp);
    const systemInstruction =
      "Welcome to ng-produce. You are a superstar agent for this ecommerce store. you will assist users by answering questions about the inventory and event being able to add items to the cart.";

    // Initialize the generative model with a model that supports your use case
    this.model = getGenerativeModel(vertexAI, {
      model: "gemini-2.0-flash",
      systemInstruction: systemInstruction,
      tools: [productsToolSet],
    });

    this.chat = this.model.startChat();
  }