You can provide Gemini built-in tools to Gemini models when accessing the Gemini API through Apple's Foundation Models framework to connect the model to external data sources.
The page shows you how to use the following built-in tools for Gemini models:
Grounding with Google Search
Grounding with
For details, best practices, and use cases, see the general Grounding with
Supported models
-
gemini-3.1-pro-preview -
gemini-3.5-flash -
gemini-3.1-flash-lite -
gemini-3-pro-image-preview(aka "Nano Banana Pro") -
gemini-3.1-flash-image-preview(aka "Nano Banana 2")
Enable the Google Search
tool
Provide the googleSearch
tool as part of creating the geminiLanguageModel
:
import
FoundationModels
import
FirebaseCore
import
FirebaseAILogic
// Initialize the Gemini Developer API backend service.
let
ai
=
FirebaseAI
.
firebaseAI
(
backend
:
.
googleAI
())
// Initialize a `geminiLanguageModel` with a Gemini model that supports your use case.
let
model
=
ai
.
geminiLanguageModel
(
name
:
" GEMINI_MODEL_NAME
"
,
// Provide Google Search as a tool that the model can use to generate its response.
serverTools
:
[
GeminiTool
.
googleSearch
()]
)
let
session
=
LanguageModelSession
(
model
:
model
)
let
response
=
try
await
session
.
respond
(
to
:
"What is the weather in Toronto today?"
)
for
entry
in
response
.
transcriptEntries
{
if
case
let
.
response
(
responseEntry
)
=
entry
{
if
let
groundingMetadata
=
responseEntry
.
metadata
[
"groundingMetadata"
]
as
?
GroundingMetadata
{
for
chunk
in
groundingMetadata
.
groundingChunks
{
let
webChunk
=
chunk
.
web
// use the webChunk
}
}
}
}
// Make sure to comply with the "Grounding with Google Search" usage requirements,
// which includes how you use and display the grounded result
Grounding with Google Maps
Grounding with
For details, best practices, and use cases, see the general Grounding with
Supported models
-
gemini-3.1-pro-preview -
gemini-3.5-flash -
gemini-3.1-flash-lite
Enable the Google Maps
tool
Provide the googleMaps
tool as part of creating the geminiLanguageModel
.
You can also optionally provide coordinates in the tool's configuration.
import
FoundationModels
import
FirebaseCore
import
FirebaseAILogic
// Initialize the Gemini Developer API backend service.
let
ai
=
FirebaseAI
.
firebaseAI
(
backend
:
.
googleAI
())
// Initialize a `geminiLanguageModel` with a Gemini model that supports your use case.
let
model
=
ai
.
geminiLanguageModel
(
name
:
" GEMINI_MODEL_NAME
"
,
// Provide Google Maps as a tool that the model can use to generate its response.
serverTools
:
[
GeminiTool
.
googleMaps
()]
)
let
session
=
LanguageModelSession
(
model
:
model
)
let
response
=
try
await
session
respond
(
to
:
"Where is a good place to grab a coffee near Alameda, CA?"
)
for
entry
in
response
.
transcriptEntries
{
if
case
let
.
response
(
responseEntry
)
=
entry
{
if
let
groundingMetadata
=
responseEntry
.
metadata
[
"groundingMetadata"
]
as
?
GroundingMetadata
{
for
chunk
in
groundingMetadata
.
groundingChunks
{
let
mapsChunk
=
chunk
.
maps
// use the mapsChunk
}
}
}
}
// Make sure to comply with the "Grounding with Google Maps
" usage requirements,
// which includes how you meet service usage requirements
Give feedbackabout accessing the Gemini API through Apple's Foundation Models framework
