Playground to explore Google Gemini using various REST clients. The repository contains different approaches using the REST API of Google Gemini.
While using Visual Studio one can use the .http file editor as a convenient way to explore an API. More information about .http files can be found in the official documentation Use .http files in Visual Studio 2022.
Open the project GeminiPlayground.csproj in Visual Studio 2022. The .http files contain HTTP calls to send requests to the different models provided by the Gemini API.
- gemini-pro.http contains requests using the Gemini Pro 1.0 model.
- gemini-pro-vision.http has requests against the Gemini Pro Vision 1.0 endpoints.
- vertex-gemini-pro.http contains requests using the Gemini Pro 1.0 model.
- vertex-gemini-pro-vision.http has requests against the Gemini Pro Vision 1.0 endpoints.
The .http files are using file-based environment variables. To get started you have to create a .env file in the project folder and add the following content to it. More details are described in the .env files paragraph.
Using Google AI Studio allows you to generate an API key that is used to access the Gemini API programmatically.
API_KEY=<your Gemini API key without quotes>
All Google AI Gemini API requests are based on the Quickstart: Get started with Gemini using the REST API.
Vertex AI is a service provided by Google Cloud and access to the API requires a cloud project with billing and Vertex AI API enabled.
PROJECT_ID=<your Google Cloud project ID>
ACCESS_TOKEN=<your access token to Google Cloud>
The region is specified in the .http files directly.
All Vertex AI Gemini API calls are based on the Jupyter notebook Getting Started with the Vertex AI Gemini API with cURL.