This guide explores how to obtain an API key and get started with the Gemini Pro SDKs.
On December 6, 2023, Google unveiled its long-awaited GPT-4 rival Gemini. The model comes in three variants, Gemini Nano to run on edge (laptops, phones, devices, etc.), Gemini Pro powering Google's Bard chatbot, and a yet-to-be-released Gemini Ultra allegedly topping GPT-4 on industry benchmarks.
Gemini Pro also comes with an API, which means it can be integrated inside any AI-powered product. Let's explore how to do that.
Google gives access to the Gemini Pro API as part of their Google AI Studio product. You will need to sign up for this free product to get an API key.
If you have an individual Google account (i.e. you are not part of an organization's workspace), you can simply go to ai.google.dev and click "Get API key in Google AI Studio".
Then click "Get API key".
Then, depending on whether you already have a GCP project click either of the two options. If you don't have a project, Google will create one for you automatically.
An API key will be create, copy it and paste it in a safe location as you will not be able to see it again later.
If your Google account is part of a Workspace account (e.g. you are using a work email) your Workspace admin will need to activate Early Access Apps before you can follow the above steps.
Workspace admins should navigate to the Admin Console and find "Additional Google Services" in the left menu.
Then scroll down to "Early Access Apps" and click on it.
Enable it for everyone:
And also enable Core Data Access Permissions. You will not be able to get an API key without this enabled.
Once this is complete, you should be able to follow the steps in the Individual Account section to get your API key.
Once you have obtained an API key and saved it in a safe place, you can start integrating the Gemini Pro API in your application.
There are multiple options depending on your stack.
The most versatile way to query the Gemini Pro API is via direct HTTP requests:
If your app is in Python, Google offers a handy Python SDK to interact with the API. The documentation can be found here.
Install the SDK:
And use it as such:
If your poison of choice is Typescript, Google's got you covered too. Find the documentation here.
Install the library:
Then use it as such:
If your using other languages such as Go or Swift, find all Google's SDKs here.
Note that the query and response payloads for OpenAI and Gemini Pro's APIs are different.
OpenAI's query payload looks like this:
while Gemini Pro's looks like this:
Notice these three main differences:
Response payloads are also quite different between OpenAI and Gemini's APIs.
OpenAI's response payloads reads:
whereas Gemini's reads:
Note that Gemini returns many safety metrics, which you can also configure thresholds for at query time.
