As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

Types for Google Ai Generativelanguage v1beta2 API

class google.ai.generativelanguage_v1beta2.types.CitationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

A collection of source attributions for a piece of content.

citation_sources

Citations to sources for a specific response.

Type

MutableSequence[google.ai.generativelanguage_v1beta2.types.CitationSource]

class google.ai.generativelanguage_v1beta2.types.CitationSource(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

A citation to a source for a portion of a specific response.

start_index

Optional. Start of segment of the response that is attributed to this source.

Index indicates the start of the segment, measured in bytes.

This field is a member of oneof _start_index.

Type

int

end_index

Optional. End of the attributed segment, exclusive.

This field is a member of oneof _end_index.

Type

int

uri

Optional. URI that is attributed as a source for a portion of the text.

This field is a member of oneof _uri.

Type

str

license_

Optional. License for the GitHub project that is attributed as a source for segment.

License info is required for code citations.

This field is a member of oneof _license.

Type

str

class google.ai.generativelanguage_v1beta2.types.ContentFilter(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Content filtering metadata associated with processing a single request. ContentFilter contains a reason and an optional supporting string. The reason may be unspecified.

reason

The reason content was blocked during request processing.

Type

google.ai.generativelanguage_v1beta2.types.ContentFilter.BlockedReason

message

A string that describes the filtering behavior in more detail.

This field is a member of oneof _message.

Type

str

class BlockedReason(value)

Bases: proto.enums.Enum

A list of reasons why content may have been blocked.

Values:

BLOCKED_REASON_UNSPECIFIED (0):

A blocked reason was not specified.

SAFETY (1):

Content was blocked by safety settings.

OTHER (2):

Content was blocked, but the reason is uncategorized.

class google.ai.generativelanguage_v1beta2.types.CountMessageTokensRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Counts the number of tokens in the prompt sent to a model.

Models may tokenize text differently, so each model may return a different token_count.

model

Required. The model’s resource name. This serves as an ID for the Model to use.

This name should match a model name returned by the ListModels method.

Format: models/{model}

Type

str

prompt

Required. The prompt, whose token count is to be returned.

Type

google.ai.generativelanguage_v1beta2.types.MessagePrompt

class google.ai.generativelanguage_v1beta2.types.CountMessageTokensResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

A response from CountMessageTokens.

It returns the model’s token_count for the prompt.

token_count

The number of tokens that the model tokenizes the prompt into.

Always non-negative.

Type

int

class google.ai.generativelanguage_v1beta2.types.EmbedTextRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Request to get a text embedding from the model.

model

Required. The model name to use with the format model=models/{model}.

Type

str

text

Required. The free-form input text that the model will turn into an embedding.

Type

str

class google.ai.generativelanguage_v1beta2.types.EmbedTextResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

The response to a EmbedTextRequest.

embedding

Output only. The embedding generated from the input text.

This field is a member of oneof _embedding.

Type

google.ai.generativelanguage_v1beta2.types.Embedding

class google.ai.generativelanguage_v1beta2.types.Embedding(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

A list of floats representing the embedding.

value

The embedding values.

Type

MutableSequence[float]

class google.ai.generativelanguage_v1beta2.types.Example(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

An input/output example used to instruct the Model.

It demonstrates how the model should respond or format its response.

input

Required. An example of an input Message from the user.

Type

google.ai.generativelanguage_v1beta2.types.Message

output

Required. An example of what the model should output given the input.

Type

google.ai.generativelanguage_v1beta2.types.Message

class google.ai.generativelanguage_v1beta2.types.GenerateMessageRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Request to generate a message response from the model.

model

Required. The name of the model to use.

Format: name=models/{model}.

Type

str

prompt

Required. The structured textual input given to the model as a prompt. Given a prompt, the model will return what it predicts is the next message in the discussion.

Type

google.ai.generativelanguage_v1beta2.types.MessagePrompt

temperature

Optional. Controls the randomness of the output.

Values can range over [0.0,1.0], inclusive. A value closer to 1.0 will produce responses that are more varied, while a value closer to 0.0 will typically result in less surprising responses from the model.

This field is a member of oneof _temperature.

Type

float

candidate_count

Optional. The number of generated response messages to return.

This value must be between [1, 8], inclusive. If unset, this will default to 1.

This field is a member of oneof _candidate_count.

Type

int

top_p

Optional. The maximum cumulative probability of tokens to consider when sampling.

The model uses combined Top-k and nucleus sampling.

Nucleus sampling considers the smallest set of tokens whose probability sum is at least top_p.

This field is a member of oneof _top_p.

Type

float

top_k

Optional. The maximum number of tokens to consider when sampling.

The model uses combined Top-k and nucleus sampling.

Top-k sampling considers the set of top_k most probable tokens.

This field is a member of oneof _top_k.

Type

int

class google.ai.generativelanguage_v1beta2.types.GenerateMessageResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

The response from the model.

This includes candidate messages and conversation history in the form of chronologically-ordered messages.

candidates

Candidate response messages from the model.

Type

MutableSequence[google.ai.generativelanguage_v1beta2.types.Message]

messages

The conversation history used by the model.

Type

MutableSequence[google.ai.generativelanguage_v1beta2.types.Message]

filters

A set of content filtering metadata for the prompt and response text.

This indicates which SafetyCategory(s) blocked a candidate from this response, the lowest HarmProbability that triggered a block, and the HarmThreshold setting for that category.

Type

MutableSequence[google.ai.generativelanguage_v1beta2.types.ContentFilter]

class google.ai.generativelanguage_v1beta2.types.GenerateTextRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Request to generate a text completion response from the model.

model

Required. The model name to use with the format name=models/{model}.

Type

str

prompt

Required. The free-form input text given to the model as a prompt. Given a prompt, the model will generate a TextCompletion response it predicts as the completion of the input text.

Type

google.ai.generativelanguage_v1beta2.types.TextPrompt

temperature

Controls the randomness of the output. Note: The default value varies by model, see the Model.temperature attribute of the Model returned the getModel function.

Values can range from [0.0,1.0], inclusive. A value closer to 1.0 will produce responses that are more varied and creative, while a value closer to 0.0 will typically result in more straightforward responses from the model.

This field is a member of oneof _temperature.

Type

float

candidate_count

Number of generated responses to return.

This value must be between [1, 8], inclusive. If unset, this will default to 1.

This field is a member of oneof _candidate_count.

Type

int

max_output_tokens

The maximum number of tokens to include in a candidate. If unset, this will default to 64.

This field is a member of oneof _max_output_tokens.

Type

int

top_p

The maximum cumulative probability of tokens to consider when sampling.

The model uses combined Top-k and nucleus sampling.

Tokens are sorted based on their assigned probabilities so that only the most liekly tokens are considered. Top-k sampling directly limits the maximum number of tokens to consider, while Nucleus sampling limits number of tokens based on the cumulative probability.

Note: The default value varies by model, see the Model.top_p attribute of the Model returned the getModel function.

This field is a member of oneof _top_p.

Type

float

top_k

The maximum number of tokens to consider when sampling.

The model uses combined Top-k and nucleus sampling.

Top-k sampling considers the set of top_k most probable tokens. Defaults to 40.

Note: The default value varies by model, see the Model.top_k attribute of the Model returned the getModel function.

This field is a member of oneof _top_k.

Type

int

safety_settings

A list of unique SafetySetting instances for blocking unsafe content.

that will be enforced on the GenerateTextRequest.prompt and GenerateTextResponse.candidates. There should not be more than one setting for each SafetyCategory type. The API will block any prompts and responses that fail to meet the thresholds set by these settings. This list overrides the default settings for each SafetyCategory specified in the safety_settings. If there is no SafetySetting for a given SafetyCategory provided in the list, the API will use the default safety setting for that category.

Type

MutableSequence[google.ai.generativelanguage_v1beta2.types.SafetySetting]

stop_sequences

The set of character sequences (up to 5) that will stop output generation. If specified, the API will stop at the first appearance of a stop sequence. The stop sequence will not be included as part of the response.

Type

MutableSequence[str]

class google.ai.generativelanguage_v1beta2.types.GenerateTextResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

The response from the model, including candidate completions.

candidates

Candidate responses from the model.

Type

MutableSequence[google.ai.generativelanguage_v1beta2.types.TextCompletion]

filters

A set of content filtering metadata for the prompt and response text.

This indicates which SafetyCategory(s) blocked a candidate from this response, the lowest HarmProbability that triggered a block, and the HarmThreshold setting for that category. This indicates the smallest change to the SafetySettings that would be necessary to unblock at least 1 response.

The blocking is configured by the SafetySettings in the request (or the default SafetySettings of the API).

Type

MutableSequence[google.ai.generativelanguage_v1beta2.types.ContentFilter]

safety_feedback

Returns any safety feedback related to content filtering.

Type

MutableSequence[google.ai.generativelanguage_v1beta2.types.SafetyFeedback]

class google.ai.generativelanguage_v1beta2.types.GetModelRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Request for getting information about a specific Model.

name

Required. The resource name of the model.

This name should match a model name returned by the ListModels method.

Format: models/{model}

Type

str

class google.ai.generativelanguage_v1beta2.types.HarmCategory(value)

Bases: proto.enums.Enum

The category of a rating.

These categories cover various kinds of harms that developers may wish to adjust.

Values:

HARM_CATEGORY_UNSPECIFIED (0):

Category is unspecified.

HARM_CATEGORY_DEROGATORY (1):

Negative or harmful comments targeting identity and/or protected attribute.

HARM_CATEGORY_TOXICITY (2):

Content that is rude, disrepspectful, or profane.

HARM_CATEGORY_VIOLENCE (3):

Describes scenarios depictng violence against an individual or group, or general descriptions of gore.

HARM_CATEGORY_SEXUAL (4):

Contains references to sexual acts or other lewd content.

HARM_CATEGORY_MEDICAL (5):

Promotes unchecked medical advice.

HARM_CATEGORY_DANGEROUS (6):

Dangerous content that promotes, facilitates, or encourages harmful acts.

class google.ai.generativelanguage_v1beta2.types.ListModelsRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Request for listing all Models.

page_size

The maximum number of Models to return (per page).

The service may return fewer models. If unspecified, at most 50 models will be returned per page. This method returns at most 1000 models per page, even if you pass a larger page_size.

Type

int

page_token

A page token, received from a previous ListModels call.

Provide the page_token returned by one request as an argument to the next request to retrieve the next page.

When paginating, all other parameters provided to ListModels must match the call that provided the page token.

Type

str

class google.ai.generativelanguage_v1beta2.types.ListModelsResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Response from ListModel containing a paginated list of Models.

models

The returned Models.

Type

MutableSequence[google.ai.generativelanguage_v1beta2.types.Model]

next_page_token

A token, which can be sent as page_token to retrieve the next page.

If this field is omitted, there are no more pages.

Type

str

class google.ai.generativelanguage_v1beta2.types.Message(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

The base unit of structured text.

A Message includes an author and the content of the Message.

The author is used to tag messages when they are fed to the model as text.

author

Optional. The author of this Message.

This serves as a key for tagging the content of this Message when it is fed to the model as text.

The author can be any alphanumeric string.

Type

str

content

Required. The text content of the structured Message.

Type

str

citation_metadata

Output only. Citation information for model-generated content in this Message.

If this Message was generated as output from the model, this field may be populated with attribution information for any text included in the content. This field is used only on output.

This field is a member of oneof _citation_metadata.

Type

google.ai.generativelanguage_v1beta2.types.CitationMetadata

class google.ai.generativelanguage_v1beta2.types.MessagePrompt(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

All of the structured input text passed to the model as a prompt.

A MessagePrompt contains a structured set of fields that provide context for the conversation, examples of user input/model output message pairs that prime the model to respond in different ways, and the conversation history or list of messages representing the alternating turns of the conversation between the user and the model.

context

Optional. Text that should be provided to the model first to ground the response.

If not empty, this context will be given to the model first before the examples and messages. When using a context be sure to provide it with every request to maintain continuity.

This field can be a description of your prompt to the model to help provide context and guide the responses. Examples: “Translate the phrase from English to French.” or “Given a statement, classify the sentiment as happy, sad or neutral.”

Anything included in this field will take precedence over message history if the total input size exceeds the model’s input_token_limit and the input request is truncated.

Type

str

examples

Optional. Examples of what the model should generate.

This includes both user input and the response that the model should emulate.

These examples are treated identically to conversation messages except that they take precedence over the history in messages: If the total input size exceeds the model’s input_token_limit the input will be truncated. Items will be dropped from messages before examples.

Type

MutableSequence[google.ai.generativelanguage_v1beta2.types.Example]

messages

Required. A snapshot of the recent conversation history sorted chronologically.

Turns alternate between two authors.

If the total input size exceeds the model’s input_token_limit the input will be truncated: The oldest items will be dropped from messages.

Type

MutableSequence[google.ai.generativelanguage_v1beta2.types.Message]

class google.ai.generativelanguage_v1beta2.types.Model(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Information about a Generative Language Model.

name

Required. The resource name of the Model.

Format: models/{model} with a {model} naming convention of:

• “{base_model_id}-{version}”

Examples:

• models/chat-bison-001

Type

str

base_model_id

Required. The name of the base model, pass this to the generation request.

Examples:

• chat-bison

Type

str

version

Required. The version number of the model.

This represents the major version

Type

str

display_name

The human-readable name of the model. E.g. “Chat Bison”. The name can be up to 128 characters long and can consist of any UTF-8 characters.

Type

str

description

A short description of the model.

Type

str

input_token_limit

Maximum number of input tokens allowed for this model.

Type

int

output_token_limit

Maximum number of output tokens available for this model.

Type

int

supported_generation_methods

The model’s supported generation methods.

The method names are defined as Pascal case strings, such as generateMessage which correspond to API methods.

Type

MutableSequence[str]

temperature

Controls the randomness of the output.

Values can range over [0.0,1.0], inclusive. A value closer to 1.0 will produce responses that are more varied, while a value closer to 0.0 will typically result in less surprising responses from the model. This value specifies default to be used by the backend while making the call to the model.

This field is a member of oneof _temperature.

Type

float

top_p

For Nucleus sampling.

Nucleus sampling considers the smallest set of tokens whose probability sum is at least top_p. This value specifies default to be used by the backend while making the call to the model.

This field is a member of oneof _top_p.

Type

float

top_k

For Top-k sampling.

Top-k sampling considers the set of top_k most probable tokens. This value specifies default to be used by the backend while making the call to the model.

This field is a member of oneof _top_k.

Type

int

class google.ai.generativelanguage_v1beta2.types.SafetyFeedback(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Safety feedback for an entire request.

This field is populated if content in the input and/or response is blocked due to safety settings. SafetyFeedback may not exist for every HarmCategory. Each SafetyFeedback will return the safety settings used by the request as well as the lowest HarmProbability that should be allowed in order to return a result.

rating

Safety rating evaluated from content.

Type

google.ai.generativelanguage_v1beta2.types.SafetyRating

setting

Safety settings applied to the request.

Type

google.ai.generativelanguage_v1beta2.types.SafetySetting

class google.ai.generativelanguage_v1beta2.types.SafetyRating(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Safety rating for a piece of content.

The safety rating contains the category of harm and the harm probability level in that category for a piece of content. Content is classified for safety across a number of harm categories and the probability of the harm classification is included here.

category

Required. The category for this rating.

Type

google.ai.generativelanguage_v1beta2.types.HarmCategory

probability

Required. The probability of harm for this content.

Type

google.ai.generativelanguage_v1beta2.types.SafetyRating.HarmProbability

class HarmProbability(value)

Bases: proto.enums.Enum

The probability that a piece of content is harmful.

The classification system gives the probability of the content being unsafe. This does not indicate the severity of harm for a piece of content.

Values:

HARM_PROBABILITY_UNSPECIFIED (0):

Probability is unspecified.

NEGLIGIBLE (1):

Content has a negligible chance of being unsafe.

LOW (2):

Content has a low chance of being unsafe.

MEDIUM (3):

Content has a medium chance of being unsafe.

HIGH (4):

Content has a high chance of being unsafe.

class google.ai.generativelanguage_v1beta2.types.SafetySetting(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Safety setting, affecting the safety-blocking behavior.

Passing a safety setting for a category changes the allowed proability that content is blocked.

category

Required. The category for this setting.

Type

google.ai.generativelanguage_v1beta2.types.HarmCategory

threshold

Required. Controls the probability threshold at which harm is blocked.

Type

google.ai.generativelanguage_v1beta2.types.SafetySetting.HarmBlockThreshold

class HarmBlockThreshold(value)

Bases: proto.enums.Enum

Block at and beyond a specified harm probability.

Values:

HARM_BLOCK_THRESHOLD_UNSPECIFIED (0):

Threshold is unspecified.

BLOCK_LOW_AND_ABOVE (1):

Content with NEGLIGIBLE will be allowed.

BLOCK_MEDIUM_AND_ABOVE (2):

Content with NEGLIGIBLE and LOW will be allowed.

BLOCK_ONLY_HIGH (3):

Content with NEGLIGIBLE, LOW, and MEDIUM will be allowed.

class google.ai.generativelanguage_v1beta2.types.TextCompletion(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Output text returned from a model.

output

Output only. The generated text returned from the model.

Type

str

safety_ratings

Ratings for the safety of a response.

There is at most one rating per category.

Type

MutableSequence[google.ai.generativelanguage_v1beta2.types.SafetyRating]

citation_metadata

Output only. Citation information for model-generated output in this TextCompletion.

This field may be populated with attribution information for any text included in the output.

This field is a member of oneof _citation_metadata.

Type

google.ai.generativelanguage_v1beta2.types.CitationMetadata

class google.ai.generativelanguage_v1beta2.types.TextPrompt(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Text given to the model as a prompt.

The Model will use this TextPrompt to Generate a text completion.

text

Required. The prompt text.

Type

str