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PROTO library for proto-google-cloud-dialogflow-v2
/*
* Copyright 2024 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: google/cloud/dialogflow/v2/generator.proto
// Protobuf Java Version: 3.25.5
package com.google.cloud.dialogflow.v2;
public interface InferenceParameterOrBuilder
extends
// @@protoc_insertion_point(interface_extends:google.cloud.dialogflow.v2.InferenceParameter)
com.google.protobuf.MessageOrBuilder {
/**
*
*
*
* Optional. Maximum number of the output tokens for the generator.
*
*
* optional int32 max_output_tokens = 1 [(.google.api.field_behavior) = OPTIONAL];
*
* @return Whether the maxOutputTokens field is set.
*/
boolean hasMaxOutputTokens();
/**
*
*
*
* Optional. Maximum number of the output tokens for the generator.
*
*
* optional int32 max_output_tokens = 1 [(.google.api.field_behavior) = OPTIONAL];
*
* @return The maxOutputTokens.
*/
int getMaxOutputTokens();
/**
*
*
*
* Optional. Controls the randomness of LLM predictions.
* Low temperature = less random. High temperature = more random.
* If unset (or 0), uses a default value of 0.
*
*
* optional double temperature = 2 [(.google.api.field_behavior) = OPTIONAL];
*
* @return Whether the temperature field is set.
*/
boolean hasTemperature();
/**
*
*
*
* Optional. Controls the randomness of LLM predictions.
* Low temperature = less random. High temperature = more random.
* If unset (or 0), uses a default value of 0.
*
*
* optional double temperature = 2 [(.google.api.field_behavior) = OPTIONAL];
*
* @return The temperature.
*/
double getTemperature();
/**
*
*
*
* Optional. Top-k changes how the model selects tokens for output. A top-k of
* 1 means the selected token is the most probable among all tokens in the
* model's vocabulary (also called greedy decoding), while a top-k of 3 means
* that the next token is selected from among the 3 most probable tokens
* (using temperature). For each token selection step, the top K tokens with
* the highest probabilities are sampled. Then tokens are further filtered
* based on topP with the final token selected using temperature sampling.
* Specify a lower value for less random responses and a higher value for more
* random responses. Acceptable value is [1, 40], default to 40.
*
*
* optional int32 top_k = 3 [(.google.api.field_behavior) = OPTIONAL];
*
* @return Whether the topK field is set.
*/
boolean hasTopK();
/**
*
*
*
* Optional. Top-k changes how the model selects tokens for output. A top-k of
* 1 means the selected token is the most probable among all tokens in the
* model's vocabulary (also called greedy decoding), while a top-k of 3 means
* that the next token is selected from among the 3 most probable tokens
* (using temperature). For each token selection step, the top K tokens with
* the highest probabilities are sampled. Then tokens are further filtered
* based on topP with the final token selected using temperature sampling.
* Specify a lower value for less random responses and a higher value for more
* random responses. Acceptable value is [1, 40], default to 40.
*
*
* optional int32 top_k = 3 [(.google.api.field_behavior) = OPTIONAL];
*
* @return The topK.
*/
int getTopK();
/**
*
*
*
* Optional. Top-p changes how the model selects tokens for output. Tokens are
* selected from most K (see topK parameter) probable to least until the sum
* of their probabilities equals the top-p value. For example, if tokens A, B,
* and C have a probability of 0.3, 0.2, and 0.1 and the top-p value is 0.5,
* then the model will select either A or B as the next token (using
* temperature) and doesn't consider C. The default top-p value is 0.95.
* Specify a lower value for less random responses and a higher value for more
* random responses. Acceptable value is [0.0, 1.0], default to 0.95.
*
*
* optional double top_p = 4 [(.google.api.field_behavior) = OPTIONAL];
*
* @return Whether the topP field is set.
*/
boolean hasTopP();
/**
*
*
*
* Optional. Top-p changes how the model selects tokens for output. Tokens are
* selected from most K (see topK parameter) probable to least until the sum
* of their probabilities equals the top-p value. For example, if tokens A, B,
* and C have a probability of 0.3, 0.2, and 0.1 and the top-p value is 0.5,
* then the model will select either A or B as the next token (using
* temperature) and doesn't consider C. The default top-p value is 0.95.
* Specify a lower value for less random responses and a higher value for more
* random responses. Acceptable value is [0.0, 1.0], default to 0.95.
*
*
* optional double top_p = 4 [(.google.api.field_behavior) = OPTIONAL];
*
* @return The topP.
*/
double getTopP();
}
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