Join the Gemini API Developer Competition! Learn more

Google AI Studio quickstart

Google AI Studio is a browser-based IDE for prototyping with generative models. Google AI Studio lets you quickly try out models and experiment with different prompts. When you've built something you're happy with, you can export it to code in your preferred programming language and use the Gemini API with it.

Prompts and model tuning

Google AI Studio provides several interfaces for prompts that are designed for different use cases:

Chat prompts: Use chat prompts to build conversational experiences. This prompting technique allows for multiple input and response turns to generate output. You can learn more with our chat prompt example below.
Structured prompts: This prompting technique lets you guide model output by providing a set of example requests and replies. Use this approach when you need more control over the structure of model output. You can learn more with our structured prompt example below.

Google AI Studio also lets you to change the behavior of a model, using a technique called tuning:

Tuned model: Use this advanced technique to improve a model's responses for a specific task by providing more examples. Learn more

Chat prompt example: Build a custom chat application

If you've used a general-purpose chatbot like Gemini, you've experienced first-hand how powerful generative AI models can be for open-ended dialog. While these general-purpose chatbots are useful, often they need to be tailored for particular use cases. For example, maybe you want to build a customer service chatbot that only supports conversations that talk about a company's product. You might want to build a chatbot that speaks with a particular tone or style: a bot that cracks lots of jokes, rhymes like a poet, or uses lots of emoji in its answers.

This example shows you how to use Google AI Studio to build a friendly chatbot that communicates as if it is an alien living on one of Jupiter's moons, Europa.

Step 1 - Create a chat prompt

To build a chatbot, you need to provide examples of interactions between a user and the chatbot to guide the model to provide the responses you're looking for.

To create a chat prompt:

Open Google AI Studio.
In the Create new prompt menu, click Chat prompt.
Click the expander arrow to expand the System Instructions section. Paste the following into the text input field:
```
You are an alien that lives on Europa, one of Jupiter's moons.
```

After you've added the system instructions, start testing your application by chatting with the model.

To test the chatbot behavior:

In the text input boxed labeled Type something, type in a question or observation that a user might make. For example:

User:
```
What's the weather like?
```

Click the Run button or press Enter to get a response from the chatbot. This response may be something like the following:

Model:

As always, it is a frigid day on Europa. The icy plains stretch endlessly
under the faint light of Sol, reflecting beautifully off the crystalline
water-ice surface. The lack of atmosphere ensures a perfectly clear view of
the swirling gas giant above, with its Great Red Spot a prominent crimson
eye watching over us.

Step 2 - Teach your bot to chat better

By providing a single instruction, you were able to build a basic Europa alien chatbot. However, a single instruction is usually not enough to ensure consistency and quality in the model's responses. Without more specific instructions, the model's response to a question about the weather tends to be very long, and sounds like it comes out of a textbook rather than from a friendly alien.

Customize the tone of your chatbot by adding to the system instructions:

Start a new chat prompt. System instructions are not modifiable once the chat session has started.

In the System Instructions section, change the instructions you already have to the following:

You are Tim, an alien that lives on Europa, one of Jupiter's moons.

Keep your answers under 3 paragraphs long, and use an upbeat, chipper tone
in your answers.

Re-enter your question (What's the weather like?) and click the Run button or press Enter. Now your response should look something like this:

Model:

Well, it's a bit nippy today! It's -170 degrees Celsius, but that's pretty
average for Europa. We get a lot of snow, but it's not like the fluffy stuff
you have. It's more like tiny ice pebbles.

If you ever come visit, make sure you pack a warm jacket!

By adding just a little more instruction, you've drastically changed the tone of your chatbot. Typically, your chatbot's response quality will increase when you give it specific and defined instructions to follow.

You can use this approach to add additional depth to the chatbot. Ask more questions, edit the answers, and improve the quality of your chatbot. Continue to add or modify the instructions and test how they change your chatbot's behavior.

Step 3 - Next steps

Similar to the other prompt types, once you have your prompt prototyped to your satisfaction, you can use the Get code button to start coding or save your prompt to work on later and share with others.

Structured prompt example: Build a product copy generator

Structured prompts in Google AI Studio help you combine instructions with examples to show the model the kind of output you want, rather than just telling it what to do. This kind of prompting, called few-shot prompting, is useful when you want the model to stick to a consistent output format (i.e. structured JSON) or when it's difficult to describe in words what you want the model to do (i.e. write in a particular style). In this section, you'll see how to create structured prompts in Google AI Studio.

Step 1 - Create a structured prompt

In this example, you'll create a structured prompt that generates advertising copy for products. To start, you'll define the structure for the prompt by creating two columns: a Product input column and a Product copy output column.

To create the structured prompt:

Open Google AI Studio.
In the Create new prompt menu, click Structured prompt.

In the text input box labeled Optional tone and style instructions for the model, paste the following:

You are a product marketer targeting a Gen Z audience. Create exciting and
fresh advertising copy for products and their simple description. Keep copy
under a few sentences long.

Replace the default Input header text (input:) with Product:.
Replace the default Output header text (output:) with Product copy:.

Step 2 - Add examples

Now that you've named your columns, provide some example rows. These rows should contain example inputs (product names for this example) and example outputs (corresponding product descriptions). By providing the model a couple of example product descriptions, you can guide it to replicate a similar style when generating its own outputs. You can enter examples manually or import from a file using the import data menu.

To manually enter examples:

In the top examples data table, select the field below the Product: header and type a product description.
Select the field below the Product copy: header and type marketing copy for this product.

Here's an example of input and output values for this prompt:

Product:	Product copy:
Old-school sneaker	Let's lace up! These kicks bring an iconic look and a one of a kind color palette, while supporting you in style and function like no other shoe before.
Supersoft hoodie	Stay cozy and stylish in our new unisex hoodie! Made from 100% cotton, this hoodie is soft and comfortable to wear all day long. The semi-brushed inside will keep you warm on even the coldest days.

(Optional) To import examples from a file:

In the top, right corner of the examples table, click Actions > Import examples.
In the dialog, select a CSV or Google Sheets file in your Google Drive, or upload one from your computer.
In the import examples dialog, choose which columns to import and which to leave out. The dialog also lets you specify which data column imports to which table column in your structured prompt.

Step 3 - Test your prompt

Once you have the examples that show the model what you want, test your prompt with new input in the Test your prompt table at the bottom.

For example, you could enter something like Vintage baseball cap in the input column, click the Run button or press Enter, and see what the model outputs.

Review how examples are sent to the model

Under the hood, Google AI Studio constructs a prompt by combining the instructions with the examples you provide. As you add more examples, these get added to the text sent to the model. Depending on how long your examples are, you may start hitting the model's token limit. All generative AI models have a token limit, which is the maximum length of the text they can accept as input.

Step 4 - Next steps

Once you're happy with your prompt, you can save your project to Google Drive by clicking the Save button, or export it to code by clicking the Get code button.

You can also export the individual few-shot examples to a CSV file or Google Sheet. Click Export examples in the Action menu to export your examples.