google.generativeai.types.GenerationConfig

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A simple dataclass used to configure the generation parameters of GenerativeModel.generate_content.

View aliases

Main aliases

`google.generativeai.GenerationConfig`

google.generativeai.types.GenerationConfig(
    candidate_count: (int | None) = None,
    stop_sequences: (Iterable[str] | None) = None,
    max_output_tokens: (int | None) = None,
    temperature: (float | None) = None,
    top_p: (float | None) = None,
    top_k: (int | None) = None,
    seed: (int | None) = None,
    response_mime_type: (str | None) = None,
    response_schema: (protos.Schema | Mapping[str, Any] | type | None) = None,
    presence_penalty: (float | None) = None,
    frequency_penalty: (float | None) = None,
    response_logprobs: (bool | None) = None,
    logprobs: (int | None) = None
)

Attributes
candidate_count	Number of generated responses to return.
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.
max_output_tokens	The maximum number of tokens to include in a candidate. If unset, this will default to output_token_limit specified in the model’s specification.
temperature	Controls the randomness of the output. Note: The default value varies by model, see the Model.temperature attribute of the Model returned the genai.get_model 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.
top_p	Optional. 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 likely 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 genai.get_model function.
top_k	int 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. Defaults to 40. Note: The default value varies by model, see the Model.top_k attribute of the Model returned the genai.get_model function.
seed	Optional. Seed used in decoding. If not set, the request uses a randomly generated seed.
response_mime_type	Optional. Output response mimetype of the generated candidate text. Supported mimetype: text/plain: (default) Text output. text/x-enum: for use with a string-enum in response_schema application/json: JSON response in the candidates.
response_schema	Optional. Specifies the format of the JSON requested if response_mime_type is application/json.
presence_penalty	Optional.
frequency_penalty	Optional.
response_logprobs	Optional. If true, export the `logprobs` results in response.
logprobs	Optional. Number of candidates of log probabilities to return at each step of decoding.

Methods

__eq__

__eq__(
    other
)

Return self==value.

Class Variables
candidate_count	None
frequency_penalty	None
logprobs	None
max_output_tokens	None
presence_penalty	None
response_logprobs	None
response_mime_type	None
response_schema	None
seed	None
stop_sequences	None
temperature	None
top_k	None
top_p	None