/**
 * Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
 * SPDX-License-Identifier: Apache-2.0.
 */

#pragma once
#include <aws/bedrock/Bedrock_EXPORTS.h>
#include <aws/core/utils/memory/stl/AWSString.h>
#include <aws/core/utils/memory/stl/AWSVector.h>

#include <utility>

namespace Aws {
namespace Utils {
namespace Json {
class JsonValue;
class JsonView;
}  // namespace Json
}  // namespace Utils
namespace Bedrock {
namespace Model {

/**
 * <p>The configuration details for text generation using a language model via the
 * <code>RetrieveAndGenerate</code> function.</p><p><h3>See Also:</h3>   <a
 * href="http://docs.aws.amazon.com/goto/WebAPI/bedrock-2023-04-20/TextInferenceConfig">AWS
 * API Reference</a></p>
 */
class TextInferenceConfig {
 public:
  AWS_BEDROCK_API TextInferenceConfig() = default;
  AWS_BEDROCK_API TextInferenceConfig(Aws::Utils::Json::JsonView jsonValue);
  AWS_BEDROCK_API TextInferenceConfig& operator=(Aws::Utils::Json::JsonView jsonValue);
  AWS_BEDROCK_API Aws::Utils::Json::JsonValue Jsonize() const;

  ///@{
  /**
   * <p>Controls the random-ness of text generated by the language model, influencing
   * how much the model sticks to the most predictable next words versus exploring
   * more surprising options. A lower temperature value (e.g. 0.2 or 0.3) makes model
   * outputs more deterministic or predictable, while a higher temperature (e.g. 0.8
   * or 0.9) makes the outputs more creative or unpredictable.</p>
   */
  inline double GetTemperature() const { return m_temperature; }
  inline bool TemperatureHasBeenSet() const { return m_temperatureHasBeenSet; }
  inline void SetTemperature(double value) {
    m_temperatureHasBeenSet = true;
    m_temperature = value;
  }
  inline TextInferenceConfig& WithTemperature(double value) {
    SetTemperature(value);
    return *this;
  }
  ///@}

  ///@{
  /**
   * <p>A probability distribution threshold which controls what the model considers
   * for the set of possible next tokens. The model will only consider the top p% of
   * the probability distribution when generating the next token.</p>
   */
  inline double GetTopP() const { return m_topP; }
  inline bool TopPHasBeenSet() const { return m_topPHasBeenSet; }
  inline void SetTopP(double value) {
    m_topPHasBeenSet = true;
    m_topP = value;
  }
  inline TextInferenceConfig& WithTopP(double value) {
    SetTopP(value);
    return *this;
  }
  ///@}

  ///@{
  /**
   * <p>The maximum number of tokens to generate in the output text. Do not use the
   * minimum of 0 or the maximum of 65536. The limit values described here are
   * arbitrary values, for actual values consult the limits defined by your specific
   * model.</p>
   */
  inline int GetMaxTokens() const { return m_maxTokens; }
  inline bool MaxTokensHasBeenSet() const { return m_maxTokensHasBeenSet; }
  inline void SetMaxTokens(int value) {
    m_maxTokensHasBeenSet = true;
    m_maxTokens = value;
  }
  inline TextInferenceConfig& WithMaxTokens(int value) {
    SetMaxTokens(value);
    return *this;
  }
  ///@}

  ///@{
  /**
   * <p>A list of sequences of characters that, if generated, will cause the model to
   * stop generating further tokens. Do not use a minimum length of 1 or a maximum
   * length of 1000. The limit values described here are arbitrary values, for actual
   * values consult the limits defined by your specific model.</p>
   */
  inline const Aws::Vector<Aws::String>& GetStopSequences() const { return m_stopSequences; }
  inline bool StopSequencesHasBeenSet() const { return m_stopSequencesHasBeenSet; }
  template <typename StopSequencesT = Aws::Vector<Aws::String>>
  void SetStopSequences(StopSequencesT&& value) {
    m_stopSequencesHasBeenSet = true;
    m_stopSequences = std::forward<StopSequencesT>(value);
  }
  template <typename StopSequencesT = Aws::Vector<Aws::String>>
  TextInferenceConfig& WithStopSequences(StopSequencesT&& value) {
    SetStopSequences(std::forward<StopSequencesT>(value));
    return *this;
  }
  template <typename StopSequencesT = Aws::String>
  TextInferenceConfig& AddStopSequences(StopSequencesT&& value) {
    m_stopSequencesHasBeenSet = true;
    m_stopSequences.emplace_back(std::forward<StopSequencesT>(value));
    return *this;
  }
  ///@}
 private:
  double m_temperature{0.0};
  bool m_temperatureHasBeenSet = false;

  double m_topP{0.0};
  bool m_topPHasBeenSet = false;

  int m_maxTokens{0};
  bool m_maxTokensHasBeenSet = false;

  Aws::Vector<Aws::String> m_stopSequences;
  bool m_stopSequencesHasBeenSet = false;
};

}  // namespace Model
}  // namespace Bedrock
}  // namespace Aws
