Prompt
(
prompt_data
:
typing
.
Optional
[
PartsType
]
=
None
,
*
,
variables
:
typing
.
Optional
[
typing
.
List
[
typing
.
Dict
[
str
,
PartsType
]]]
=
None
,
prompt_name
:
typing
.
Optional
[
str
]
=
None
,
generation_config
:
typing
.
Optional
[
vertexai
.
generative_models
.
_generative_models
.
GenerationConfig
]
=
None
,
model_name
:
typing
.
Optional
[
str
]
=
None
,
safety_settings
:
typing
.
Optional
[
vertexai
.
generative_models
.
_generative_models
.
SafetySetting
]
=
None
,
system_instruction
:
typing
.
Optional
[
PartsType
]
=
None
,
tools
:
typing
.
Optional
[
typing
.
List
[
vertexai
.
generative_models
.
_generative_models
.
Tool
]
]
=
None
,
tool_config
:
typing
.
Optional
[
vertexai
.
generative_models
.
_generative_models
.
ToolConfig
]
=
None
)
A prompt which may be a template with variables.
The Prompt
class allows users to define a template string with
variables represented in curly braces {variable}
. The variable
name must be a valid Python variable name (no spaces, must start with a
letter). These placeholders can be replaced with specific values using the assemble_contents
method, providing flexibility in generating dynamic prompts.
Usage: Generate content from a single set of variables:
prompt = Prompt(
prompt_data="Hello, {name}! Today is {day}. How are you?",
variables=[{"name": "Alice", "day": "Monday"}]
generation_config=GenerationConfig(
temperature=0.1,
top_p=0.95,
top_k=20,
candidate_count=1,
max_output_tokens=100,
),
model_name="gemini-1.0-pro-002",
safety_settings=[SafetySetting(
category=SafetySetting.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT,
threshold=SafetySetting.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
method=SafetySetting.HarmBlockMethod.SEVERITY,
)],
system_instruction="Please answer in a short sentence.",
)
# Generate content using the assembled prompt.
prompt.generate_content(
contents=prompt.assemble_contents(**prompt.variables)
)
```
Generate content with multiple sets of variables:
```
prompt = Prompt(
prompt_data="Hello, {name}! Today is {day}. How are you?",
variables=[
{"name": "Alice", "day": "Monday"},
{"name": "Bob", "day": "Tuesday"},
],
generation_config=GenerationConfig(
temperature=0.1,
top_p=0.95,
top_k=20,
candidate_count=1,
max_output_tokens=100,
),
model_name="gemini-1.0-pro-002",
safety_settings=[SafetySetting(
category=SafetySetting.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT,
threshold=SafetySetting.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
method=SafetySetting.HarmBlockMethod.SEVERITY,
)],
system_instruction="Please answer in a short sentence.",
)
# Generate content using the assembled prompt for each variable set.
for i in range(len(prompt.variables)):
prompt.generate_content(
contents=prompt.assemble_contents(**prompt.variables[i])
)
```
Methods
Prompt
Prompt
(
prompt_data
:
typing
.
Optional
[
PartsType
]
=
None
,
*
,
variables
:
typing
.
Optional
[
typing
.
List
[
typing
.
Dict
[
str
,
PartsType
]]]
=
None
,
prompt_name
:
typing
.
Optional
[
str
]
=
None
,
generation_config
:
typing
.
Optional
[
vertexai
.
generative_models
.
_generative_models
.
GenerationConfig
]
=
None
,
model_name
:
typing
.
Optional
[
str
]
=
None
,
safety_settings
:
typing
.
Optional
[
vertexai
.
generative_models
.
_generative_models
.
SafetySetting
]
=
None
,
system_instruction
:
typing
.
Optional
[
PartsType
]
=
None
,
tools
:
typing
.
Optional
[
typing
.
List
[
vertexai
.
generative_models
.
_generative_models
.
Tool
]
]
=
None
,
tool_config
:
typing
.
Optional
[
vertexai
.
generative_models
.
_generative_models
.
ToolConfig
]
=
None
)
Initializes the Prompt with a given prompt, and variables.
__repr__
__repr__
()
-
> str
Returns a string representation of the unassembled prompt.
__str__
__str__
()
-
> str
Returns the prompt data as a string, without any variables replaced.
assemble_contents
assemble_contents
(
**
variables_dict
:
PartsType
,
)
-
> typing
.
List
[
vertexai
.
generative_models
.
_generative_models
.
Content
]
Returns the prompt data, as a List[Content], assembled with variables if applicable. Can be ingested into model.generate_content to make API calls.
generate_content
generate_content
(
contents
:
ContentsType
,
*
,
generation_config
:
typing
.
Optional
[
GenerationConfigType
]
=
None
,
safety_settings
:
typing
.
Optional
[
SafetySettingsType
]
=
None
,
model_name
:
typing
.
Optional
[
str
]
=
None
,
tools
:
typing
.
Optional
[
typing
.
List
[
vertexai
.
generative_models
.
_generative_models
.
Tool
]
]
=
None
,
tool_config
:
typing
.
Optional
[
vertexai
.
generative_models
.
_generative_models
.
ToolConfig
]
=
None
,
stream
:
bool
=
False
,
system_instruction
:
typing
.
Optional
[
PartsType
]
=
None
)
-
> typing
.
Union
[
vertexai
.
generative_models
.
_generative_models
.
GenerationResponse
,
typing
.
Iterable
[
vertexai
.
generative_models
.
_generative_models
.
GenerationResponse
],
]
Generates content using the saved Prompt configs.
get_unassembled_prompt_data
get_unassembled_prompt_data
()
-
> PartsType
Returns the prompt data, without any variables replaced.
