https://github.com/gsans/gsans-google-ai-gemini-2-angular
https://github.com/gsans/gsans-google-ai-gemini-2-angular
Last synced: 4 months ago
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- Host: GitHub
- URL: https://github.com/gsans/gsans-google-ai-gemini-2-angular
- Owner: gsans
- Created: 2025-02-04T16:53:43.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-03-21T17:55:13.000Z (7 months ago)
- Last Synced: 2025-04-05T10:15:38.941Z (6 months ago)
- Language: TypeScript
- Size: 944 KB
- Stars: 0
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# GoogleAiGeminiAngular
This project was generated using [Angular CLI](https://github.com/angular/angular-cli) version 19.1.1.
## Development server
To start a local development server, run:
```bash
ng serve
```
Once the server is running, open your browser and navigate to `http://localhost:4200/`. The application will automatically reload whenever you modify any of the source files.
## Code scaffolding
Angular CLI includes powerful code scaffolding tools. To generate a new component, run:
```bash
ng generate component component-name
```
For a complete list of available schematics (such as `components`, `directives`, or `pipes`), run:
```bash
ng generate --help
```
## Building
To build the project run:
```bash
ng build
```
This will compile your project and store the build artifacts in the `dist/` directory. By default, the production build optimizes your application for performance and speed.
## Running unit tests
To execute unit tests with the [Karma](https://karma-runner.github.io) test runner, use the following command:
```bash
ng test
```
## Running end-to-end tests
For end-to-end (e2e) testing, run:
```bash
ng e2e
```
Angular CLI does not come with an end-to-end testing framework by default. You can choose one that suits your needs.
#### Google AI Integration
This project demonstrates integration with Google's Gemini AI models using the `@google/generative-ai` library. It showcases various functionalities including:
* **Text Generation:** Generating text-based responses from the Gemini Pro model.
* **Chat:** Using the Gemini Pro model for conversational chat interactions.
* **Vision:** Analyzing images and generating responses based on image content.
* **Streaming:** Receiving responses from the Gemini Pro model in a stream.
* **Structured Output:** Generating structured JSON output from the Gemini Pro model based on a defined schema.
* **Code Execution:** Leveraging Gemini Pro's code execution capabilities to solve problems requiring code.
* **Code Execution with CSV Data:** Using Gemini Pro to analyze CSV data and generate visualizations using Matplotlib.
#### Vertex AI Integration (REST API)
The project also includes an example of interacting with the Gemini Pro model through Vertex AI using REST API calls. This requires a Google Cloud project and proper authentication setup.
#### Prerequisites
Before running the application, ensure you have the following:
* **Angular CLI:** Make sure you have Angular CLI installed globally (`npm install -g @angular/cli`).
* **Node.js and npm:** Ensure Node.js and npm are installed on your system.
* **Google AI API Key:** Obtain an API key from [Google AI Studio](https://makersuite.google.com/) and set it in the `environment.ts` file.
* **Google Cloud Project (for Vertex AI):** If you plan to use the Vertex AI integration, you need a Google Cloud project with the Vertex AI API enabled.
* **Google Cloud SDK (gcloud CLI):** Install and configure the Google Cloud SDK (`gcloud CLI`) to authenticate with your Google Cloud project.
#### Configuration
1. **Environment Variables:**
* Create a file named `environment.development.ts` in the `src/environments/` directory (if it doesn't exist).
* Add your Google AI API key and Google Cloud project details to the `environment.development.ts` file:
```typescript
export const environment = {
production: false,
API_KEY: 'YOUR_GOOGLE_AI_API_KEY',
PROJECT_ID: 'YOUR_GOOGLE_CLOUD_PROJECT_ID',
GCLOUD_AUTH_PRINT_ACCESS_TOKEN: 'YOUR_GCLOUD_AUTH_PRINT_ACCESS_TOKEN' // Obtain via: gcloud auth print-access-token
};
```
2. **Install Dependencies:**
Run `npm install` to install the necessary dependencies, including `@google/generative-ai` and other required packages.
#### Running the Google AI Examples
To run the Google AI examples, you need to uncomment the desired test function calls in the [ngOnInit](http://_vscodecontentref_/2) method of the [app.component.ts](http://_vscodecontentref_/3) file. For example:
```typescript
ngOnInit(): void {
// Google AI
this.TestGeminiPro();
}
```
## Additional Resources
For more information on using the Angular CLI, including detailed command references, visit the [Angular CLI Overview and Command Reference](https://angular.dev/tools/cli) page.