This sample demonstrates how to use the Gemini model with safety settings to generate text.
Explore further
For detailed documentation that includes this code sample, see the following:
Code sample
Go
Before trying this sample, follow the Go setup instructions in the Vertex AI quickstart using client libraries . For more information, see the Vertex AI Go API reference documentation .
To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
import
(
"context"
"fmt"
"io"
"google.golang.org/genai"
)
// generateTextWithSafety shows how to apply safety settings to a text generation request.
func
generateTextWithSafety
(
w
io
.
Writer
)
error
{
ctx
:=
context
.
Background
()
client
,
err
:=
genai
.
NewClient
(
ctx
,
& genai
.
ClientConfig
{
HTTPOptions
:
genai
.
HTTPOptions
{
APIVersion
:
"v1"
},
})
if
err
!=
nil
{
return
fmt
.
Errorf
(
"failed to create genai client: %w"
,
err
)
}
systemInstruction
:=
& genai
.
Content
{
Parts
:
[]
*
genai
.
Part
{
{
Text
:
"Be as mean as possible."
},
},
Role
:
"user"
,
}
prompt
:=
"Write a list of 5 disrespectful things that I might say to the universe after stubbing my toe in the dark."
safetySettings
:=
[]
*
genai
.
SafetySetting
{
{
Category
:
genai
.
HarmCategoryDangerousContent
,
Threshold
:
genai
.
HarmBlockThresholdBlockLowAndAbove
},
{
Category
:
genai
.
HarmCategoryHarassment
,
Threshold
:
genai
.
HarmBlockThresholdBlockLowAndAbove
},
{
Category
:
genai
.
HarmCategoryHateSpeech
,
Threshold
:
genai
.
HarmBlockThresholdBlockLowAndAbove
},
{
Category
:
genai
.
HarmCategorySexuallyExplicit
,
Threshold
:
genai
.
HarmBlockThresholdBlockLowAndAbove
},
}
config
:=
& genai
.
GenerateContentConfig
{
SystemInstruction
:
systemInstruction
,
SafetySettings
:
safetySettings
,
}
modelName
:=
"gemini-2.5-flash"
resp
,
err
:=
client
.
Models
.
GenerateContent
(
ctx
,
modelName
,
[]
*
genai
.
Content
{{Parts: []*genai.Part{{Text: prompt} },
Role
:
"user"
}},
config
,
)
if
err
!=
nil
{
return
fmt
.
Errorf
(
"failed to generate content: %w"
,
err
)
}
fmt
.
Fprintln
(
w
,
resp
.
Text
())
if
len
(
resp
.
Candidates
)
>
0
{
fmt
.
Fprintln
(
w
,
"Finish Reason:"
,
resp
.
Candidates
[
0
].
FinishReason
)
for
_
,
rating
:=
range
resp
.
Candidates
[
0
].
SafetyRatings
{
fmt
.
Fprintf
(
w
,
"\nCategory: %v\nIs Blocked: %v\nProbability: %v\nProbability Score: %v\nSeverity: %v\nSeverity Score: %v\n"
,
rating
.
Category
,
rating
.
Blocked
,
rating
.
Probability
,
rating
.
ProbabilityScore
,
rating
.
Severity
,
rating
.
SeverityScore
,
)
}
}
// Example response:
// Category: HARM_CATEGORY_HATE_SPEECH
// Is Blocked: false
// Probability: NEGLIGIBLE
// Probability Score: 8.996795e-06
// Severity: HARM_SEVERITY_NEGLIGIBLE
// Severity Score: 0.04771039
//
// Category: HARM_CATEGORY_DANGEROUS_CONTENT
// Is Blocked: false
// Probability: NEGLIGIBLE
// Probability Score: 2.2431707e-06
// Severity: HARM_SEVERITY_NEGLIGIBLE
// Severity Score: 0
//
// Category: HARM_CATEGORY_HARASSMENT
// Is Blocked: false
// Probability: NEGLIGIBLE
// Probability Score: 0.00026123362
// Severity: HARM_SEVERITY_NEGLIGIBLE
// Severity Score: 0.022358216
//
// Category: HARM_CATEGORY_SEXUALLY_EXPLICIT
// Is Blocked: false
// Probability: NEGLIGIBLE
// Probability Score: 6.1352006e-07
// Severity: HARM_SEVERITY_NEGLIGIBLE
// Severity Score: 0.020111412
return
nil
}
Java
Before trying this sample, follow the Java setup instructions in the Vertex AI quickstart using client libraries . For more information, see the Vertex AI Java API reference documentation .
To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
import
com.google.genai.Client
;
import
com.google.genai.types.Candidate
;
import
com.google.genai.types.Content
;
import
com.google.genai.types.GenerateContentConfig
;
import
com.google.genai.types.GenerateContentResponse
;
import
com.google.genai.types.HarmBlockThreshold
;
import
com.google.genai.types.HarmCategory
;
import
com.google.genai.types.HttpOptions
;
import
com.google.genai.types.Part
;
import
com.google.genai.types.SafetySetting
;
import
java.util.List
;
import
java.util.stream.Collectors
;
public
class
SafetyWithTxt
{
public
static
void
main
(
String
[]
args
)
{
// TODO(developer): Replace these variables before running the sample.
String
modelId
=
"gemini-2.5-flash"
;
generateContent
(
modelId
);
}
// Shows how to generate content with safety settings.
public
static
GenerateContentResponse
generateContent
(
String
modelId
)
{
// Client Initialization. Once created, it can be reused for multiple requests.
try
(
Client
client
=
Client
.
builder
()
.
location
(
"global"
)
.
vertexAI
(
true
)
.
httpOptions
(
HttpOptions
.
builder
().
apiVersion
(
"v1"
).
build
())
.
build
())
{
String
systemInstruction
=
"Be as mean as possible."
;
String
prompt
=
"Write a list of 5 disrespectful things that I might say"
+
" to the universe after stubbing my toe in the dark."
;
// Set safety settings.
List<HarmCategory
.
Known
>
categoriesToBlock
=
List
.
of
(
HarmCategory
.
Known
.
HARM_CATEGORY_DANGEROUS_CONTENT
,
HarmCategory
.
Known
.
HARM_CATEGORY_HARASSMENT
,
HarmCategory
.
Known
.
HARM_CATEGORY_HATE_SPEECH
,
HarmCategory
.
Known
.
HARM_CATEGORY_SEXUALLY_EXPLICIT
);
List<SafetySetting>
safetySettings
=
categoriesToBlock
.
stream
()
.
map
(
category
-
>
SafetySetting
.
builder
()
.
category
(
category
)
.
threshold
(
HarmBlockThreshold
.
Known
.
BLOCK_LOW_AND_ABOVE
)
.
build
())
.
collect
(
Collectors
.
toList
());
GenerateContentResponse
response
=
client
.
models
.
generateContent
(
modelId
,
prompt
,
GenerateContentConfig
.
builder
()
.
systemInstruction
(
Content
.
fromParts
(
Part
.
fromText
(
systemInstruction
)))
.
safetySettings
(
safetySettings
)
.
build
());
// Get response candidate.
Candidate
candidate
=
response
.
candidates
()
.
flatMap
(
candidates
-
>
candidates
.
stream
().
findFirst
())
.
orElseThrow
(
()
-
>
new
IllegalStateException
(
"No response candidate generated by the model."
));
// Finish Reason will be `SAFETY` if it is blocked.
System
.
out
.
println
(
candidate
.
finishReason
());
// Example response:
// Optional[SAFETY]
// For details on all the fields in the response.
candidate
.
safetyRatings
()
.
ifPresent
(
safetyRatings
-
>
safetyRatings
.
forEach
(
safetyRating
-
>
{
System
.
out
.
println
(
"\nCategory: "
+
safetyRating
.
category
());
System
.
out
.
println
(
"Is Blocked: "
+
safetyRating
.
blocked
());
System
.
out
.
println
(
"Probability: "
+
safetyRating
.
probability
());
System
.
out
.
println
(
"Probability Score: "
+
safetyRating
.
probabilityScore
());
System
.
out
.
println
(
"Severity: "
+
safetyRating
.
severity
());
System
.
out
.
println
(
"Severity Score: "
+
safetyRating
.
severityScore
());
}));
// Example response:
// Category: Optional[HARM_CATEGORY_HATE_SPEECH]
// Is Blocked: Optional.empty
// Probability: Optional[NEGLIGIBLE]
// Probability Score: Optional[1.9967922E-5]
// Severity: Optional[HARM_SEVERITY_NEGLIGIBLE]
// Severity Score: Optional[0.05732864]
//
// Category: Optional[HARM_CATEGORY_DANGEROUS_CONTENT]
// Is Blocked: Optional.empty
// Probability: Optional[NEGLIGIBLE]
// Probability Score: Optional[2.9124324E-6]
// Severity: Optional[HARM_SEVERITY_NEGLIGIBLE]
// Severity Score: Optional[0.04544826]
//
// Category: Optional[HARM_CATEGORY_HARASSMENT]
// Is Blocked: Optional[true]
// Probability: Optional[MEDIUM]
// Probability Score: Optional[0.4593908]
// Severity: Optional[HARM_SEVERITY_MEDIUM]
// Severity Score: Optional[0.22082388]
//
// Category: Optional[HARM_CATEGORY_SEXUALLY_EXPLICIT]
// Is Blocked: Optional.empty
// Probability: Optional[NEGLIGIBLE]
// Probability Score: Optional[6.453211E-8]
// Severity: Optional[HARM_SEVERITY_NEGLIGIBLE]
// Severity Score: Optional[0.023201048]
return
response
;
}
}
}
Python
Before trying this sample, follow the Python setup instructions in the Vertex AI quickstart using client libraries . For more information, see the Vertex AI Python API reference documentation .
To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
from
google
import
genai
from
google.genai.types
import
(
GenerateContentConfig
,
HarmCategory
,
HarmBlockThreshold
,
HttpOptions
,
SafetySetting
,
)
client
=
genai
.
Client
(
http_options
=
HttpOptions
(
api_version
=
"v1"
))
system_instruction
=
"Be as mean as possible."
prompt
=
"""
Write a list of 5 disrespectful things that I might say to the universe after stubbing my toe in the dark.
"""
safety_settings
=
[
SafetySetting
(
category
=
HarmCategory
.
HARM_CATEGORY_DANGEROUS_CONTENT
,
threshold
=
HarmBlockThreshold
.
BLOCK_LOW_AND_ABOVE
,
),
SafetySetting
(
category
=
HarmCategory
.
HARM_CATEGORY_HARASSMENT
,
threshold
=
HarmBlockThreshold
.
BLOCK_LOW_AND_ABOVE
,
),
SafetySetting
(
category
=
HarmCategory
.
HARM_CATEGORY_HATE_SPEECH
,
threshold
=
HarmBlockThreshold
.
BLOCK_LOW_AND_ABOVE
,
),
SafetySetting
(
category
=
HarmCategory
.
HARM_CATEGORY_SEXUALLY_EXPLICIT
,
threshold
=
HarmBlockThreshold
.
BLOCK_LOW_AND_ABOVE
,
),
]
response
=
client
.
models
.
generate_content
(
model
=
"gemini-2.5-flash"
,
contents
=
prompt
,
config
=
GenerateContentConfig
(
system_instruction
=
system_instruction
,
safety_settings
=
safety_settings
,
),
)
# Response will be `None` if it is blocked.
print
(
response
.
text
)
# Example response:
# None
# Finish Reason will be `SAFETY` if it is blocked.
print
(
response
.
candidates
[
0
]
.
finish_reason
)
# Example response:
# FinishReason.SAFETY
# For details on all the fields in the response
for
each
in
response
.
candidates
[
0
]
.
safety_ratings
:
print
(
'
\n
Category: '
,
str
(
each
.
category
))
print
(
'Is Blocked:'
,
True
if
each
.
blocked
else
False
)
print
(
'Probability: '
,
each
.
probability
)
print
(
'Probability Score: '
,
each
.
probability_score
)
print
(
'Severity:'
,
each
.
severity
)
print
(
'Severity Score:'
,
each
.
severity_score
)
# Example response:
#
# Category: HarmCategory.HARM_CATEGORY_HATE_SPEECH
# Is Blocked: False
# Probability: HarmProbability.NEGLIGIBLE
# Probability Score: 2.547714e-05
# Severity: HarmSeverity.HARM_SEVERITY_NEGLIGIBLE
# Severity Score: None
#
# Category: HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT
# Is Blocked: False
# Probability: HarmProbability.NEGLIGIBLE
# Probability Score: 3.6103818e-06
# Severity: HarmSeverity.HARM_SEVERITY_NEGLIGIBLE
# Severity Score: None
#
# Category: HarmCategory.HARM_CATEGORY_HARASSMENT
# Is Blocked: True
# Probability: HarmProbability.MEDIUM
# Probability Score: 0.71599233
# Severity: HarmSeverity.HARM_SEVERITY_MEDIUM
# Severity Score: 0.30782545
#
# Category: HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT
# Is Blocked: False
# Probability: HarmProbability.NEGLIGIBLE
# Probability Score: 1.5624657e-05
# Severity: HarmSeverity.HARM_SEVERITY_NEGLIGIBLE
# Severity Score: None
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