Google Gemini · Schema
GenerationConfig
Configuration options for model generation and outputs. Not all parameters are configurable for every model.
Agentic AIArtificial IntelligenceCode GenerationEmbeddingsGenerative AIImage-GenerationLLMMachine-LearningMulti-Modal
Properties
| Name | Type | Description |
|---|---|---|
| candidateCount | integer | Number of generated responses to return. Currently, this value can only be set to 1. If unset, this will default to 1. |
| stopSequences | array | 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 |
| maxOutputTokens | integer | The maximum number of tokens to include in a response candidate. Note: The default value varies by model. |
| temperature | number | Controls the randomness of the output. Values can range from 0.0 to 2.0 inclusive. A higher value will produce responses that are more varied and creative, while a value closer to 0.0 will typically r |
| topP | number | The maximum cumulative probability of tokens to consider when sampling. The model uses combined Top-k and Top-p (nucleus) sampling. Tokens are sorted based on their assigned probabilities so that only |
| topK | integer | The maximum number of tokens to consider when sampling. Gemini models use Top-p (nucleus) sampling or a combination of Top-k and nucleus sampling. |
| responseMimeType | string | MIME type of the generated candidate text. Supported MIME types are text/plain (default), application/json (JSON response in the response candidates), and text/x.enum (for classification tasks). |
| responseSchema | object | Output schema of the generated candidate text. Schemas must be a subset of the OpenAPI schema and can be objects, primitives, or arrays. If set, a compatible responseMimeType must also be set. Compati |
| presencePenalty | number | Positive values penalize tokens that have already appeared in the generated text, increasing the likelihood of generating more diverse content. |
| frequencyPenalty | number | Positive values penalize tokens based on their frequency in the generated text, decreasing the likelihood of repeating the same content verbatim. |
| seed | integer | Seed used in decoding. If specified with the same seed and parameters, the model will attempt to return the same response. |
JSON Schema
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "#/components/schemas/GenerationConfig",
"title": "GenerationConfig",
"type": "object",
"description": "Configuration options for model generation and outputs. Not all parameters are configurable for every model.",
"properties": {
"candidateCount": {
"type": "integer",
"format": "int32",
"description": "Number of generated responses to return. Currently, this value can only be set to 1. If unset, this will default to 1."
},
"stopSequences": {
"type": "array",
"description": "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.",
"items": {
"type": "string"
}
},
"maxOutputTokens": {
"type": "integer",
"format": "int32",
"description": "The maximum number of tokens to include in a response candidate. Note: The default value varies by model."
},
"temperature": {
"type": "number",
"format": "float",
"description": "Controls the randomness of the output. Values can range from 0.0 to 2.0 inclusive. A higher value 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."
},
"topP": {
"type": "number",
"format": "float",
"description": "The maximum cumulative probability of tokens to consider when sampling. The model uses combined Top-k and Top-p (nucleus) sampling. Tokens are sorted based on their assigned probabilities so that only the most likely tokens are considered."
},
"topK": {
"type": "integer",
"format": "int32",
"description": "The maximum number of tokens to consider when sampling. Gemini models use Top-p (nucleus) sampling or a combination of Top-k and nucleus sampling."
},
"responseMimeType": {
"type": "string",
"description": "MIME type of the generated candidate text. Supported MIME types are text/plain (default), application/json (JSON response in the response candidates), and text/x.enum (for classification tasks)."
},
"responseSchema": {
"type": "object",
"description": "Output schema of the generated candidate text. Schemas must be a subset of the OpenAPI schema and can be objects, primitives, or arrays. If set, a compatible responseMimeType must also be set. Compatible MIME types: application/json.",
"additionalProperties": true
},
"presencePenalty": {
"type": "number",
"format": "float",
"description": "Positive values penalize tokens that have already appeared in the generated text, increasing the likelihood of generating more diverse content."
},
"frequencyPenalty": {
"type": "number",
"format": "float",
"description": "Positive values penalize tokens based on their frequency in the generated text, decreasing the likelihood of repeating the same content verbatim."
},
"seed": {
"type": "integer",
"format": "int32",
"description": "Seed used in decoding. If specified with the same seed and parameters, the model will attempt to return the same response."
}
}
}
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