google.ai.generativelanguage.GenerateAnswerRequest

Request to generate a grounded answer from the model.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

inline_passages google.ai.generativelanguage.GroundingPassages

Passages provided inline with the request.

This field is a member of oneof_ grounding_source.

semantic_retriever google.ai.generativelanguage.SemanticRetrieverConfig

Content retrieved from resources created via the Semantic Retriever API.

This field is a member of oneof_ grounding_source.

model str

Required. The name of the Model to use for generating the grounded response.

Format: model=models/{model}.

contents MutableSequence[google.ai.generativelanguage.Content]

Required. The content of the current conversation with the model. For single-turn queries, this is a single question to answer. For multi-turn queries, this is a repeated field that contains conversation history and the last Content in the list containing the question.

answer_style google.ai.generativelanguage.GenerateAnswerRequest.AnswerStyle

Required. Style in which answers should be returned.

safety_settings MutableSequence[google.ai.generativelanguage.SafetySetting]

Optional. A list of unique SafetySetting instances for blocking unsafe content.

This will be enforced on the GenerateAnswerRequest.contents and GenerateAnswerResponse.candidate. There should not be more than one setting for each SafetyCategory type. The API will block any contents 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.

temperature float

Optional. Controls the randomness of the output.

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. A low temperature (~0.2) is usually recommended for Attributed-Question-Answering use cases.

Child Classes

class AnswerStyle