> [!WARNING]
> **Preview**: Using server prompt templates is a feature that's in Preview, which means that it isn't subject to any SLA or deprecation policy and could change in backwards-incompatible ways.
For Firebase AI Logic, the Firebase console provides a guided UI for you
to specify the contents of a template.
Server prompt templates use a Dotprompt-based syntax and format. On this page,
you can find detailed descriptions of the template format and syntax, along with
examples.
Here are the most important components for an example request to a
Gemini model:
---
model: 'gemini-3.8-flash'
---
{{role "system"}}
All output must be a clearly structured invoice document.
Use a tabular or clearly delineated list format for line items.
{{role "user"}}
Create an example customer invoice for a customer named {{customerName}}.
- The top section within the triple-dashes contains the model name as well as
optionally any model configuration, input validation, or schema you want to
send in the request. It's written as key-value pairs and is commonly called
YAML *frontmatter*.
- The body of the template contains the prompt. It can also optionally include
system instructions and input values (using
[Handlebars](https://handlebarsjs.com/guide/) syntax).
> [!IMPORTANT]
> **Important:** Make sure to review the list of [not-yet-supported features](https://firebase.google.com/docs/ai-logic/server-prompt-templates/best-practices-and-considerations.md.txt) for the initial release of server prompt templates.
This page provides detailed descriptions of the template format and syntax,
along with examples, for the following:
- [Hello world](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-hello-world)
- [Model configuration](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-model-config)
- [Thinking configuration](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-thinking)
- [Safety settings](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-safety-settings)
- [System instructions](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-system-instructions)
- [Input variables](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-input-variables)
- [Control flows (loops \& conditionals)](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-control-flows)
- [Input validation and schema](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-input-validation-and-schema)
- [Output schema](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-output-schema)
- [Multimodal input (images, videos, audio, PDFs, etc.)](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-multimodal-input)
- [Tool use (function calling, code execution, URL context, Grounding with Google Search, Grounding with Google Maps)](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#tools)
All the examples on this page show templates that use
`gemini-3.8-flash`, but you can use any Gemini model supported by
Firebase AI Logic (except for Gemini Live API models).
## Hello world
Here's a minimal example of a server prompt template:
**Configuration (frontmatter)**
---
model: 'gemini-3.8-flash'
---
**Prompt and (as applicable) system instructions**
Write a story about a magic backpack.
*** ** * ** ***
## Control generation of responses
You can control the generation of responses in a variety of ways depending on
your use case and the level of control that you need.
### Model configuration
Set a [model configuration](https://firebase.google.com/docs/ai-logic/model-parameters.md.txt) to control how the
model generates a response, like max output tokens, stop sequences, etc.
**Configuration (frontmatter)**
---
model: 'gemini-3.8-flash'
config:
maxOutputTokens: 200
stopSequences: ["red"]
---
**Prompt and (as applicable) system instructions**
Write a story about a magic backpack.
### Thinking configuration
Specify a [thinking-related configuration](https://firebase.google.com/docs/ai-logic/thinking.md.txt) for models
that support thinking.
> [!NOTE]
> **Note:** The Gemini 2.5 models use *thinking budget* instead of *thinking
> level* , and the Gemini 3.x models support *thinking budget* for backwards-compatibility. However, the Gemini 4.x models do ***not*** support *thinking budget* (and will return a 400 error if it's set). Also, if you set both `thinkingLevel` and `thinkingBudget` in the same config, the request returns an error.
**Configuration (frontmatter)**
- Gemini 3.x and later models (thinking levels)
---
model: 'gemini-3.8-flash'
config:
thinkingConfig:
thinkingLevel: medium
includeThoughts: true
---
- Gemini 2.5 models (thinking budgets)
---
model: 'gemini-2.5-flash'
config:
thinkingConfig:
thinkingBudget: 1024
includeThoughts: true
---
**Prompt and (as applicable) system instructions**
Solve x^2 + 4x + 4 = 0
### Safety settings
Use [safety settings](https://firebase.google.com/docs/ai-logic/safety-settings.md.txt) to adjust the likelihood
of getting responses that may be considered harmful.
**Configuration (frontmatter)**
Example with one safety setting:
---
model: 'gemini-3.8-flash'
config:
safetySettings:
- category: HARM_CATEGORY_HARASSMENT
threshold: BLOCK_ONLY_HIGH
---
Example with multiple safety settings:
---
model: 'gemini-3.8-flash'
config:
safetySettings:
- category: HARM_CATEGORY_HARASSMENT
threshold: BLOCK_ONLY_HIGH
- category: HARM_CATEGORY_HATE_SPEECH
threshold: BLOCK_MEDIUM_AND_ABOVE
---
**Prompt and (as applicable) system instructions**
Write a story about a magic backpack.
### System instructions
Set [system instructions](https://firebase.google.com/docs/ai-logic/system-instructions.md.txt) to steer the
behavior of the model. You include them as part of the prompt:
- Specify the system instructions using the
`{{role "system"}}` syntax.
- Specify the text prompt using the
`{{role "user"}}` syntax.
**Configuration (frontmatter)**
---
model: 'gemini-3.8-flash'
---
**Prompt and (as applicable) system instructions**
{{role "system"}}
All output must be a clearly structured invoice document.
Use a tabular or clearly delineated list format for line items.
{{role "user"}}
Create an example customer invoice for a customer.
*** ** * ** ***
## Input variables
Some prompts are static, but you often need to include some data from the user
as part of the prompt.
You can include dynamic input variables in the prompt using
[Handlebars](https://handlebarsjs.com/guide/) expressions, which
are contained within `{{ }}` tags in the format
of `{{variableName}}` or
`{{object.propertyName}}` (for example,
`Hello, {{name}} from {{address.city}}`).
> [!IMPORTANT]
> **Important:** Always provide [input validation](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-input-validation-and-schema) to ensure that the data passed in the request matches your expectations. Note that if you use an input variable in your prompt and you provide input validation schema, then that value is considered required (unless you denote it as optional in the schema).
**Configuration (frontmatter)**
---
model: 'gemini-3.8-flash'
---
**Prompt and (as applicable) system instructions**
Create an example customer invoice for a customer named {{customerName}}.
You can provide a [default value](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-input-validation-and-schema) in the
template, but the value of an input variable is usually provided by the client
as part of the request.
View client-side request that provides input values
|---|
| *Click your Gemini API provider to view provider-specific content and code on this page.* |
### Swift
```swift
// ...
// Initialize the Gemini Developer API backend service.
// Create a `TemplateGenerativeModel` instance.
let model = FirebaseAI.firebaseAI(backend: .googleAI()).templateGenerativeModel()
let customerName = "Jane"
do {
let response = try await model.generateContent(
// Specify your template ID
templateID: "my-first-template-v1-0-0",
// Provide the values for any input variables required by your template.
inputs: [
"customerName": customerName
]
)
if let text = response.text {
print("Response Text: \(text)")
}
} catch {
print("An error occurred: \(error)")
}
print("\n")
```
### Kotlin
```kotlin
// ...
// Initialize the Gemini Developer API backend service.
// Create a `TemplateGenerativeModel` instance.
val model = Firebase.ai(backend = GenerativeBackend.googleAI()).templateGenerativeModel()
val customerName = "Jane"
val response = model.generateContent(
// Specify your template ID.
"my-first-template-v1-0-0",
// Provide the values for any input variables required by your template.
mapOf(
"customerName" to customerName
)
)
val text = response.text
println(text)
```
### Java
```java
// ...
// Initialize the Gemini Developer API backend service.
// Create a `TemplateGenerativeModel` instance.
TemplateGenerativeModel generativeModel = FirebaseAI.getInstance().templateGenerativeModel();
TemplateGenerativeModelFutures model = TemplateGenerativeModelFutures.from(generativeModel);
String customerName = "Jane";
Future response = model.generateContent(
// Specify your template ID
"my-first-template-v1-0-0",
// Provide the values for any input variables required by your template.
mapOf("customerName", customerName)
);
addCallback(response,
new FutureCallback() {
public void onSuccess(GenerateContentResponse result) {
System.out.println(result.getText());
}
public void onFailure(Throwable t) {
reportError(t);
}
}
executor);
```
### Web
```javascript
// ...
// Initialize the Gemini Developer API backend service.
const ai = getAI(app, { backend: new GoogleAIBackend() });
// Create a `TemplateGenerativeModel` instance.
const model = getTemplateGenerativeModel(ai);
const customerName = 'Jane';
const result = await model.generateContent({
// Specify your template ID.
templateId: 'my-first-template-v1-0-0',
// Provide the values for any input variables required by your template.
templateVariables: {
customerName: customerName,
},
});
const response = result.response;
const text = response.text();
```
### Dart
```dart
// ...
// Initialize the Gemini Developer API backend service.
// Create a `TemplateGenerativeModel` instance.
var _model = FirebaseAI.googleAI().templateGenerativeModel();
var customerName = 'Jane';
var response = await _model.generateContent(
// Specify your template ID
'my-first-template-v1-0-0',
// Provide the values for any input variables required by your template.
inputs: {
'customerName': customerName,
},
);
var text = response?.text;
print(text);
```
### Unity
```c#
// ...
// Initialize the Gemini Developer API backend service.
var firebaseAI = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI());
// Create a `TemplateGenerativeModel` instance.
var model = firebaseAI.GetTemplateGenerativeModel();
var customerName = "Jane";
try
{
var response = await model.GenerateContentAsync(
// Specify your template ID.
"my-first-template-v1-0-0",
// Provide the values for any input variables required by your template.
new Dictionary {
{ "customerName", customerName },
}
);
Debug.Log($"Response Text: {response.Text}");
}
catch (Exception e) {
Debug.LogError($"An error occurred: {e.Message}");
}
```
*** ** * ** ***
## Control flows (loops \& conditionals)
To write more complex prompts, you can use conditional blocks (like `#if` ,
`else`, and `#unless`) and iteration (`#each`).
You can provide additional contextual information as variables with a special
`@` prefix:
- `@first`: true when iterating the first item of an `#each` block.
- `@last`: true when iterating the last item of an `#each` block.
- `@index`: gives the (zero-based) index position of the current element.
See the
[Handlebars documentation](https://handlebarsjs.com/guide/builtin-helpers.html)
for information on all of the built-in logical helpers.
**Configuration (frontmatter)**
---
model: 'gemini-3.8-flash'
---
**Prompt and (as applicable) system instructions**
Create an example customer invoice for a customer named {{customerName}}.
Include entries for each of the following products
{{#each productNames}}
{{#if @first}}
Include line items for the following purchases
{{/if}}
- {{this}}
{{/each}}
{{#if isVipCustomer}}
Give the customer a 5% discount.
{{/if}}
Note that conditionals only accept a variable reference, not any type of
expression, for example:
- The following works: `{{#if isVipCustomer}} ... {{/if}}`
- The following does *not* work: `{{#if customer.type == 'vip'}} ... {{/if}}`
If the variable is a boolean, then the conditional works as you would expect.
If the variable is *not* a boolean then the conditional is effectively an
"is-not-null" check. This can be useful for handling optional inputs, for
example:
{{#if customerName}}
Hello {{customerName}}
{{else}}
Hello Guest
{{/if}}
*** ** * ** ***
## Input validation and schema
If you have data coming from the client, we strongly recommend using input
schema to help protect against prompt injection as well as ensure that the data
passed in the request matches your expectations.
- You can provide default values in case the client doesn't provide a value.
- The schema supports scalar types `string`, `integer`, `number`, `boolean`, and
`object`. Objects, arrays, and enums are denoted by a parenthetical after the
field name.
- All properties are considered required unless you denote it as optional with
`?`. When a property is marked as optional, it's also made nullable to provide
more leniency for LLMs to return null instead of omitting a field.
> [!NOTE]
> **Note:** If you specify an input schema and the client fails to pass valid inputs with a request, then the request will be rejected with a 400 error.
Here's a **basic example** for providing input schema. You can find a more
advanced schema just below.
**Configuration (frontmatter)**
---
model: 'gemini-3.8-flash'
input:
default:
isVipCustomer: false
schema:
customerName: string, the customers name # string, number, and boolean types are defined like this
productNames?(array, list of products to include in the invoice): string # optional fields are marked with a ?
isVipCustomer?: boolean, whether or not the customer is a VIP
---
**Prompt and (as applicable) system instructions**
Create an example customer invoice for a customer named {{customerName}}.
Include entries for each of the following products
{{#each productNames}}
{{#if @first}}
Include line items for the following purchases
{{/if}}
- {{this}}
{{/each}}
{{#if isVipCustomer}}
Give the customer a 5% discount.
{{/if}}
View a more **complex example** for providing input schema
**Configuration (frontmatter)**
---
model: gemini-3.8-flash
input:
schema:
customer:
type: object
description: details about the customer
required: [lastName, address]
properties:
firstName:
type: string
minLength: 2
maxLength: 50
lastName:
type: string
minLength: 2
maxLength: 50
address:
type: object
description: customer's address
required: [street, city, country]
properties:
street:
type: string
city:
type: string
country:
type: string
isVip:
type: boolean
description: whether or not the customer is a VIP
purchases?:
type: array
description: list of things the customer purchased
items:
type: object
required: [itemName, sku, cost, quantity]
properties:
itemName:
type: string
sku:
type: string
minLength: 7
maxLength: 19
pattern: "^[0-9]{1,3}-[a-zA-Z]{3,10}-[0-9]{1,4}$"
category:
enum: ["ELECTRONICS", "APPAREL", "HOME", "MISC" ]
cost:
type: number
minimum: 0
quantity:
type: number
minimum: 1
maximum: 200
---
**Prompt and (as applicable) system instructions**
Create an example customer invoice for a customer.
The customer's address is
{{customer.firstName}} {{customer.lastName}}
{{customer.address.street}}
{{customer.address.city}}
{{customer.address.country}}
{{#each purchases}}
{{#if @first}}
Include line items for the following purchaes
{{/if}}
- {{quantity}} x {{itemName}} ({{sku}}) @ ${{cost}}, category {{category}}
{{/each}}
{{#if customer.isVip}}
Give the customer a 5% discount.
{{/if}}
*** ** * ** ***
## Output schema
If you want the model to generate
[structured JSON output](https://firebase.google.com/docs/ai-logic/generate-structured-output.md.txt),
then you can specify an output schema. By specifying `format: json`, you're
constraining the model to always return a JSON response that follows the
specified schema.
- The schema supports scalar types `string`, `integer`, `number`, `boolean`, and
`object`. Objects, arrays, and enums are denoted by a parenthetical after the
field name.
- All properties are considered required unless you denote it as optional with
`?`. When a property is marked as optional, it's also made nullable to provide
more leniency for LLMs to return null instead of omitting a field.
> [!NOTE]
> **Note:** Server prompt templates do ***not*** yet support [constraining the output to a list of enums](https://firebase.google.com/docs/ai-logic/generate-structured-output.md.txt#generate-enum-basic).
Here's a **basic example** for generating structured JSON output. You can
find a more advanced schema just below.
**Configuration (frontmatter)**
---
model: gemini-3.8-flash
output:
format: json
schema:
invoiceId: string
invoiceFile(object, an invoice file):
url?: string
contents: string
mimeType: string
---
**Prompt and (as applicable) system instructions**
Create an example customer invoice.
View a more **complex example** for generating structured JSON output
**Configuration (frontmatter)**
---
model: gemini-3.8-flash
output:
format: json
schema:
title: string # string, number, and boolean types are defined like this
subtitle?: string # optional fields are marked with a ?
draft?: boolean, true when in draft state
status?(enum, approval status): [PENDING, APPROVED]
date: string, the date of publication for example '2024-04-09' # descriptions follow a comma
tags(array, relevant tags for article): string # arrays are denoted via parentheses
authors(array):
name: string
email?: string
metadata?(object): # objects are also denoted via parentheses
updatedAt?: string, ISO timestamp of last update
approvedBy?: integer, id of approver
extra?: any, arbitrary extra data
(*): string, wildcard field
---
**Prompt and (as applicable) system instructions**
Store all the specified information about the provided article.
*** ** * ** ***
## Multimodal input
Multimodal prompts sent to a Gemini model can include multiple types of input,
including [files](https://firebase.google.com/docs/ai-logic/input-file-requirements.md.txt)
(like text along with images, PDFs, plain-text files, audio, and video).
- Provide a file using its URL with the `{{media url}}`
syntax.
- Provide an inline file with the
`{{media type="mime_type" data="contents"}}`
syntax.
View how to provide base64-encoded data to test your template in the console
If your template has input that's base64-encoded data, here's how you can
include it in the testing experience of the Firebase console:
{
"mimeType": "image/png",
"imageData": "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"
}
### Basic example (multimodal input)
Here's a **basic example** for providing multimodal input. You can find a more
complex example just below.
**Configuration (frontmatter)**
---
model: 'gemini-3.8-flash'
---
**Prompt and (as applicable) system instructions**
Describe this image
{{media type="mimeType" data="imageData"}}
### Complex example (multimodal input)
Here's a more **complex example** for providing multimodal input.
**Configuration (frontmatter)**
---
model: gemini-3.8-flash
input:
schema:
image_urls?(array, urls of external images): string
inline_images?(array, inline image data):
type: object
properties:
mime_type: string
contents: string # inline data must be base64-encoded
---
**Prompt and (as applicable) system instructions**
{{role "system"}}
Use the following image as the basis for comparisons
{{media url="http://example.com/reference_img.bmp"}}
{{role "user"}}
What do the following images have in common?
{{#each image_urls}}
{{media url="this"}}
{{/each}}
{{#each inline_images}}
{{media type="mime_type" data="contents"}}
{{/each}}
*** ** * ** ***
## Tool use
Server prompt templates support the following tools.
- [Function calling](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#function-calling)
- [Code execution](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#code-execution)
- [URL context](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#url-context)
- [Grounding with Google Search](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#grounding-with-google-search)
- [Grounding with Google Maps](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#grounding-with-google-maps)
If you want your users to provide any additional information for the request to
the model, then use [input variables](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-input-variables) within the
server prompt template, along with
[input validation](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-input-validation-and-schema).
> [!IMPORTANT]
> **Important:** During initialization of the model in your client code, do ***not*** list the tools that the model has access to. Instead, tools must be listed in the `tools` object of the template's frontmatter.
### Function calling
See the complete guide for
[function calling using server prompt templates](https://firebase.google.com/docs/ai-logic/server-prompt-templates/multi-turn-interactions.md.txt#function-calling).
### Code execution
The [code execution](https://firebase.google.com/docs/ai-logic/code-execution.md.txt) tool enables the model to
generate and run Python code.
**Configuration (frontmatter)**
---
model: 'gemini-3.8-flash'
tools:
- codeExecution
---
**Prompt and (as applicable) system instructions**
What is the sum of the first 50 prime numbers?
Generate and run code for the calculation, and make sure you get all 50.
### URL context
The [URL context](https://firebase.google.com/docs/ai-logic/url-context.md.txt) tool lets you provide additional
context to the model in the form of URLs. This example also shows how you might
specify input validation for URLs if they're provided by the user.
**Configuration (frontmatter)**
---
model: 'gemini-3.8-flash'
input:
schema:
url1:
type: string
pattern: '^https?://[\w.-]+\.[a-z]{2,}\S*$'
maxLength: 100
url2:
type: string
pattern: '^https?://[\w.-]+\.[a-z]{2,}\S*$'
maxLength: 100
tools:
- urlContext
---
**Prompt and (as applicable) system instructions**
Compare the ingredients and cooking times from the recipes at {{url1}} and {{url2}}
### Grounding with Google Search
The [Grounding with Google Search](https://firebase.google.com/docs/ai-logic/grounding-google-search.md.txt)
tool connects the model to real-time, publicly-available web content.
> [!IMPORTANT]
> **Important:** If a response contains "Google Search suggestions" (the `searchEntryPoint` field within the `groundingMetadata` object), then that response is a "grounded result" so **you're required to comply with the
> "Grounding with Google Search" usage requirements, which includes how
> you display the result** . Learn how to [use and display a grounded result](https://firebase.google.com/docs/ai-logic/grounding-google-search.md.txt#use-and-display-grounded-result).
**Configuration (frontmatter)**
---
model: 'gemini-3.8-flash'
tools:
- googleSearch
---
**Prompt and (as applicable) system instructions**
Who won the Euro 2024?
### Grounding with Google Maps
The [Grounding with Google Maps](https://firebase.google.com/docs/ai-logic/grounding-google-maps.md.txt) tool
provides the model with geospatial data for location-aware functionality.
> [!IMPORTANT]
> **Important:** If a response contains a `groundingMetadata` object (meaning the response is a *Google Maps Grounded Result* ), you're required to comply with the Grounding with Google Maps usage requirements, which includes how you display the result. Learn how to [meet service usage requirements](https://firebase.google.com/docs/ai-logic/grounding-google-maps.md.txt#service-usage-requirements).
To use the `googleMaps` tool, list it in the `tools` object of the template's
frontmatter. The example below shows some additional *optional* configurations:
- Allow [input variables](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-input-variables) from the client-side
code, and perform
[input validation and schema](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#gemini-input-validation-and-schema)
of that input (in this example, a `question`).
- Configure the `googleMaps` tool by providing a location's coordinates and/or
a language code in your client-side code using a `TemplateToolConfig`.
Below the example template, find an
[expandable](https://firebase.google.com/docs/ai-logic/server-prompt-templates/syntax-and-examples.md.txt#grounding-with-google-maps-templatetoolconfig) that shows
client-side code samples for working with these optional configurations.
**Configuration (frontmatter)**
---
model: 'gemini-3.8-flash'
tools:
- googleMaps
input:
schema:
question: string
---
**Prompt and (as applicable) system instructions**
{{role "system"}}
You are a helpful tour guide. Use the Google Maps tool with the provided coordinates to answer the user's question based on their location.
{{role "user"}}
{{question}}
View client-side request that shows working with optional configurations of the `googleMaps` tool when using a template
|---|
| *Click your Gemini API provider to view provider-specific content and code on this page.* |
### Swift
```swift
import CoreLocation
import FirebaseAILogic
// Initialize the Gemini Developer API backend service.
let ai = FirebaseAI.firebaseAI(backend: .googleAI())
// Example: Coordinates for New York City
let latAndLong = CLLocationCoordinate2D(latitude: 40.7128, longitude: -74.0060)
// (Optional) Define a RetrievalConfig to configure the Grounding with Google Maps tool.
// You can optionally provide a location's coordinates and/or a language code
// for more relevant and personalized Google Maps results.
let retrievalConfig = RetrievalConfig(
location: latAndLong,
// Example: Language code for English (US)
languageCode: "en-US"
)
// Wrap the RetrievalConfig inside a TemplateToolConfig.
let templateToolConfig = TemplateToolConfig(retrievalConfig: retrievalConfig)
// Create a `TemplateGenerativeModel` instance.
let model = ai.templateGenerativeModel(
// Pass the template-compatible tool configuration.
toolConfig: templateToolConfig
)
do {
// Generate content using your server template ID, inputs, and grounding configuration.
let response = try await model.generateContent(
// Specify a template ID that uses the Google Maps tool.
templateID: "TEMPLATE_ID",
// Provide the values for any input variables required by your template.
inputs: [
"question": "restaurants near me?"
]
)
print(response.text ?? "No text in response.")
} catch {
print("An error occurred: \(error)")
}
// Make sure to comply with the "Grounding with Google Maps" usage requirements
```
### Kotlin
```kotlin
// ...
// (Optional) Define a RetrievalConfig to configure the Grounding with Google Maps tool.
// You can optionally provide a location's coordinates and/or a language code
// for more relevant and personalized Google Maps results.
val retrievalConfig = RetrievalConfig(
// Example: Coordinates for New York City
latLng = LatLng(latitude = 40.7128, longitude = -74.0060),
// Example: Language code for English (US)
languageCode = "en-US"
)
// Wrap the RetrievalConfig inside a TemplateToolConfig.
val templateToolConfig = TemplateToolConfig(
retrievalConfig = retrievalConfig
)
// Initialize the Gemini Developer API backend service.
// Create a `TemplateGenerativeModel` instance.
val model = Firebase.ai(backend = GenerativeBackend.googleAI()).templateGenerativeModel(
// Pass the template-compatible tool configuration.
toolConfig = templateToolConfig
)
// Generate content using your server template ID, inputs, and grounding configuration.
val response = model.generateContent(
// Specify a template ID that uses the Google Maps tool.
templateId = "TEMPLATE_ID",
// Provide the values for any input variables required by your template.
inputs = mapOf(
"question" to "restaurants near me?"
)
)
println(response.text)
// Make sure to comply with the "Grounding with Google Maps" usage requirements
```
### Java
```java
// ...
// (Optional) Define a TemplateToolConfig to configure the Grounding with Google Maps tool.
// You can optionally provide a location's coordinates and/or a language code
// for more relevant and personalized Google Maps results.
TemplateToolConfig templateToolConfig = new TemplateToolConfig(
new RetrievalConfig(
// Example: Coordinates for New York City.
new LatLng(40.7128, -74.0060),
// Example: Language code for English (US)
"en-US"
)
);
// Initialize the Gemini Developer API backend service.
// Create a `TemplateGenerativeModel` instance.
TemplateGenerativeModel generativeModel = FirebaseAI.getInstance(GenerativeBackend.googleAI())
.templateGenerativeModel(
new RequestOptions(),
List.of(TemplateTool.googleMaps()),
// Pass the template-compatible tool configuration.
templateToolConfig
);
TemplateGenerativeModelFutures model = TemplateGenerativeModelFutures.from(generativeModel);
// Generate content using your server template ID, inputs, and grounding configuration.
ListenableFuture response = model.generateContent(
// Specify a template ID that uses the Google Maps tool.
"TEMPLATE_ID",
// Provide the values for any input variables required by your template.
Map.of("question", "restaurants near me?")
);
Futures.addCallback(response, new FutureCallback() {
@Override
public void onSuccess(GenerateContentResponse result) {
String resultText = result.getText();
System.out.println(resultText);
}
@Override
public void onFailure(Throwable t) {
t.printStackTrace();
}
}, executor);
// Make sure to comply with the "Grounding with Google Maps" usage requirements
```
### Web
```javascript
// ...
// Initialize the Gemini Developer API backend service.
const ai = getAI(app, { backend: new GoogleAIBackend() });
// Create a `TemplateGenerativeModel` instance.
const model = getTemplateGenerativeModel(ai);
// (Optional) Define a templateToolConfig to configure the Grounding with Google Maps tool.
// You can optionally provide a location's coordinates and/or a language code
// for more relevant and personalized Google Maps results.
const templateToolConfig = {
retrievalConfig: {
// Example: Coordinates for New York City
latLng: {
latitude: 40.7128,
longitude: -74.0060
},
// Example: Language code for English (US)
languageCode: 'en-US'
}
};
// Generate content using your server template ID, inputs, and grounding configuration.
const result = await model.generateContent({
// Specify a template ID that uses the Google Maps tool.
templateId: 'TEMPLATE_ID',
// Provide the values for any input variables required by your template.
templateVariables: {
question: 'restaurants near me?',
},
// Pass the template-compatible tool configuration.
toolConfig: templateToolConfig,
});
const response = result.response;
const text = response.text();
// Make sure to comply with the "Grounding with Google Maps" usage requirements
```
### Dart
```dart
// ...
// Initialize the Gemini Developer API backend service.
// Create a `TemplateGenerativeModel` instance.
final model = FirebaseAI.googleAI().templateGenerativeModel();
// (Optional) Define a TemplateToolConfig to configure the Grounding with Google Maps tool.
// You can optionally provide a location's coordinates and/or a language code
// for more relevant and personalized Google Maps results.
final templateToolConfig = TemplateToolConfig(
retrievalConfig: RetrievalConfig(
// Example: Coordinates for New York City
latLng: LatLng(latitude: 40.712728, longitude: -74.006015),
// Example: Language code for English (US)
languageCode: 'en',
),
);
// Generate content using your server template ID, inputs, and grounding configuration.
final response = await model.generateContent(
// Specify a template ID that uses the Google Maps tool.
'TEMPLATE_ID',
// Provide the values for any input variables required by your template
inputs: {
'question': 'restaurants near me?',
},
// Pass the template-compatible tool configuration
toolConfig: templateToolConfig,
);
print(response?.text);
// Make sure to comply with the "Grounding with Google Maps" usage requirements
```
### Unity
```c#
// ...
// Initialize the Gemini Developer API backend service.
var ai = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI());
// Create a `TemplateGenerativeModel` instance.
var model = ai.GetTemplateGenerativeModel();
// Example: Coordinates for New York City
var latLng = new LatLng(40.7128, -74.0060);
// (Optional) Define a RetrievalConfig to configure the Grounding with Google Maps tool.
// You can optionally provide a location's coordinates and/or a language code
// for more relevant and personalized Google Maps results.
var retrievalConfig = new RetrievalConfig(latLng, languageCode: "en");
// Wrap the RetrievalConfig inside a TemplateToolConfig.
var templateToolConfig = new TemplateToolConfig(retrievalConfig: retrievalConfig);
try
{
// Generate content using the server template ID, inputs, and grounding configuration.
var response = await model.GenerateContentAsync(
// Specify a template ID that uses the Google Maps tool.
"TEMPLATE_ID",
// Provide the values for any input variables required by your template.
new Dictionary {
{ "question", "restaurants near me?" }
},
// Pass the template-compatible tool configuration.
toolConfig: templateToolConfig
);
Debug.Log($"Response Text: {response.Text}");
}
catch (Exception e)
{
Debug.LogError($"An error occurred: {e.Message}");
}
// Make sure to comply with the "Grounding with Google Maps" usage requirements
```