Class: OCI::GenerativeAiInference::Models::LlamaLlmInferenceRequest

Inherits:
LlmInferenceRequest show all
Defined in:
lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb

Overview

Details for the text generation request for Llama models.

Constant Summary

Constants inherited from LlmInferenceRequest

OCI::GenerativeAiInference::Models::LlmInferenceRequest::RUNTIME_TYPE_ENUM

Instance Attribute Summary collapse

Attributes inherited from LlmInferenceRequest

#runtime_type

Class Method Summary collapse

Instance Method Summary collapse

Methods inherited from LlmInferenceRequest

get_subtype

Constructor Details

#initialize(attributes = {}) ⇒ LlamaLlmInferenceRequest

Initializes the object

Parameters:

  • attributes (Hash) (defaults to: {})

    Model attributes in the form of hash

Options Hash (attributes):

  • :prompt (String)

    The value to assign to the #prompt property

  • :is_stream (BOOLEAN)

    The value to assign to the #is_stream property

  • :num_generations (Integer)

    The value to assign to the #num_generations property

  • :is_echo (BOOLEAN)

    The value to assign to the #is_echo property

  • :top_k (Integer)

    The value to assign to the #top_k property

  • :top_p (Float)

    The value to assign to the #top_p property

  • :temperature (Float)

    The value to assign to the #temperature property

  • :frequency_penalty (Float)

    The value to assign to the #frequency_penalty property

  • :presence_penalty (Float)

    The value to assign to the #presence_penalty property

  • :stop (Array<String>)

    The value to assign to the #stop property

  • :log_probs (Integer)

    The value to assign to the #log_probs property

  • :max_tokens (Integer)

    The value to assign to the #max_tokens property



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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 135

def initialize(attributes = {})
  return unless attributes.is_a?(Hash)

  attributes['runtimeType'] = 'LLAMA'

  super(attributes)

  # convert string to symbol for hash key
  attributes = attributes.each_with_object({}) { |(k, v), h| h[k.to_sym] = v }

  self.prompt = attributes[:'prompt'] if attributes[:'prompt']

  self.is_stream = attributes[:'isStream'] unless attributes[:'isStream'].nil?
  self.is_stream = false if is_stream.nil? && !attributes.key?(:'isStream') # rubocop:disable Style/StringLiterals

  raise 'You cannot provide both :isStream and :is_stream' if attributes.key?(:'isStream') && attributes.key?(:'is_stream')

  self.is_stream = attributes[:'is_stream'] unless attributes[:'is_stream'].nil?
  self.is_stream = false if is_stream.nil? && !attributes.key?(:'isStream') && !attributes.key?(:'is_stream') # rubocop:disable Style/StringLiterals

  self.num_generations = attributes[:'numGenerations'] if attributes[:'numGenerations']

  raise 'You cannot provide both :numGenerations and :num_generations' if attributes.key?(:'numGenerations') && attributes.key?(:'num_generations')

  self.num_generations = attributes[:'num_generations'] if attributes[:'num_generations']

  self.is_echo = attributes[:'isEcho'] unless attributes[:'isEcho'].nil?
  self.is_echo = false if is_echo.nil? && !attributes.key?(:'isEcho') # rubocop:disable Style/StringLiterals

  raise 'You cannot provide both :isEcho and :is_echo' if attributes.key?(:'isEcho') && attributes.key?(:'is_echo')

  self.is_echo = attributes[:'is_echo'] unless attributes[:'is_echo'].nil?
  self.is_echo = false if is_echo.nil? && !attributes.key?(:'isEcho') && !attributes.key?(:'is_echo') # rubocop:disable Style/StringLiterals

  self.top_k = attributes[:'topK'] if attributes[:'topK']

  raise 'You cannot provide both :topK and :top_k' if attributes.key?(:'topK') && attributes.key?(:'top_k')

  self.top_k = attributes[:'top_k'] if attributes[:'top_k']

  self.top_p = attributes[:'topP'] if attributes[:'topP']
  self.top_p = 1.0 if top_p.nil? && !attributes.key?(:'topP') # rubocop:disable Style/StringLiterals

  raise 'You cannot provide both :topP and :top_p' if attributes.key?(:'topP') && attributes.key?(:'top_p')

  self.top_p = attributes[:'top_p'] if attributes[:'top_p']
  self.top_p = 1.0 if top_p.nil? && !attributes.key?(:'topP') && !attributes.key?(:'top_p') # rubocop:disable Style/StringLiterals

  self.temperature = attributes[:'temperature'] if attributes[:'temperature']
  self.temperature = 1.0 if temperature.nil? && !attributes.key?(:'temperature') # rubocop:disable Style/StringLiterals

  self.frequency_penalty = attributes[:'frequencyPenalty'] if attributes[:'frequencyPenalty']
  self.frequency_penalty = 0.0 if frequency_penalty.nil? && !attributes.key?(:'frequencyPenalty') # rubocop:disable Style/StringLiterals

  raise 'You cannot provide both :frequencyPenalty and :frequency_penalty' if attributes.key?(:'frequencyPenalty') && attributes.key?(:'frequency_penalty')

  self.frequency_penalty = attributes[:'frequency_penalty'] if attributes[:'frequency_penalty']
  self.frequency_penalty = 0.0 if frequency_penalty.nil? && !attributes.key?(:'frequencyPenalty') && !attributes.key?(:'frequency_penalty') # rubocop:disable Style/StringLiterals

  self.presence_penalty = attributes[:'presencePenalty'] if attributes[:'presencePenalty']
  self.presence_penalty = 0.0 if presence_penalty.nil? && !attributes.key?(:'presencePenalty') # rubocop:disable Style/StringLiterals

  raise 'You cannot provide both :presencePenalty and :presence_penalty' if attributes.key?(:'presencePenalty') && attributes.key?(:'presence_penalty')

  self.presence_penalty = attributes[:'presence_penalty'] if attributes[:'presence_penalty']
  self.presence_penalty = 0.0 if presence_penalty.nil? && !attributes.key?(:'presencePenalty') && !attributes.key?(:'presence_penalty') # rubocop:disable Style/StringLiterals

  self.stop = attributes[:'stop'] if attributes[:'stop']

  self.log_probs = attributes[:'logProbs'] if attributes[:'logProbs']

  raise 'You cannot provide both :logProbs and :log_probs' if attributes.key?(:'logProbs') && attributes.key?(:'log_probs')

  self.log_probs = attributes[:'log_probs'] if attributes[:'log_probs']

  self.max_tokens = attributes[:'maxTokens'] if attributes[:'maxTokens']

  raise 'You cannot provide both :maxTokens and :max_tokens' if attributes.key?(:'maxTokens') && attributes.key?(:'max_tokens')

  self.max_tokens = attributes[:'max_tokens'] if attributes[:'max_tokens']
end

Instance Attribute Details

#frequency_penaltyFloat

To reduce repetitiveness of generated tokens, this number penalizes new tokens based on their frequency in the generated text so far. Values > 0 encourage the model to use new tokens and values < 0 encourage the model to repeat tokens. Set to 0 to disable.

Returns:

  • (Float)


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 51

def frequency_penalty
  @frequency_penalty
end

#is_echoBOOLEAN

Whether or not to return the user prompt in the response. Applies only to non-stream results.

Returns:

  • (BOOLEAN)


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 26

def is_echo
  @is_echo
end

#is_streamBOOLEAN

Whether to stream back partial progress. If set, tokens are sent as data-only server-sent events as they become available.

Returns:

  • (BOOLEAN)


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 18

def is_stream
  @is_stream
end

#log_probsInteger

Includes the logarithmic probabilities for the most likely output tokens and the chosen tokens.

For example, if the log probability is 5, the API returns a list of the 5 most likely tokens. The API returns the log probability of the sampled token, so there might be up to logprobs+1 elements in the response.

Returns:

  • (Integer)


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 69

def log_probs
  @log_probs
end

#max_tokensInteger

The maximum number of tokens that can be generated per output sequence. The token count of your prompt plus max_tokens cannot exceed the model's context length.

Returns:

  • (Integer)


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 73

def max_tokens
  @max_tokens
end

#num_generationsInteger

The number of of generated texts that will be returned.

Returns:

  • (Integer)


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 22

def num_generations
  @num_generations
end

#presence_penaltyFloat

To reduce repetitiveness of generated tokens, this number penalizes new tokens based on whether they've appeared in the generated text so far. Values > 0 encourage the model to use new tokens and values < 0 encourage the model to repeat tokens.

Similar to frequency penalty, a penalty is applied to previously present tokens, except that this penalty is applied equally to all tokens that have already appeared, regardless of how many times they've appeared. Set to 0 to disable.

Returns:

  • (Float)


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 58

def presence_penalty
  @presence_penalty
end

#promptString

Represents the prompt to be completed. The trailing white spaces are trimmed before completion.

Returns:

  • (String)


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 14

def prompt
  @prompt
end

#stopArray<String>

List of strings that stop the generation if they are generated for the response text. The returned output will not contain the stop strings.

Returns:

  • (Array<String>)


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 62

def stop
  @stop
end

#temperatureFloat

A number that sets the randomness of the generated output. A lower temperature means a less random generations.

Use lower numbers for tasks with a correct answer such as question answering or summarizing. High temperatures can generate hallucinations or factually incorrect information. Start with temperatures lower than 1.0 and increase the temperature for more creative outputs, as you regenerate the prompts to refine the outputs.

Returns:

  • (Float)


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 47

def temperature
  @temperature
end

#top_kInteger

An integer that sets up the model to use only the top k most likely tokens in the generated output. A higher k introduces more randomness into the output making the output text sound more natural. Default value is -1 which means to consider all tokens. Setting to 0 disables this method and considers all tokens.

If also using top p, then the model considers only the top tokens whose probabilities add up to p percent and ignores the rest of the k tokens. For example, if k is 20, but the probabilities of the top 10 add up to .75, then only the top 10 tokens are chosen.

Returns:

  • (Integer)


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 33

def top_k
  @top_k
end

#top_pFloat

If set to a probability 0.0 < p < 1.0, it ensures that only the most likely tokens, with total probability mass of p, are considered for generation at each step.

To eliminate tokens with low likelihood, assign p a minimum percentage for the next token's likelihood. For example, when p is set to 0.75, the model eliminates the bottom 25 percent for the next token. Set to 1 to consider all tokens and set to 0 to disable. If both k and p are enabled, p acts after k.

Returns:

  • (Float)


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 40

def top_p
  @top_p
end

Class Method Details

.attribute_mapObject

Attribute mapping from ruby-style variable name to JSON key.



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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 76

def self.attribute_map
  {
    # rubocop:disable Style/SymbolLiteral
    'runtime_type': :'runtimeType',
    'prompt': :'prompt',
    'is_stream': :'isStream',
    'num_generations': :'numGenerations',
    'is_echo': :'isEcho',
    'top_k': :'topK',
    'top_p': :'topP',
    'temperature': :'temperature',
    'frequency_penalty': :'frequencyPenalty',
    'presence_penalty': :'presencePenalty',
    'stop': :'stop',
    'log_probs': :'logProbs',
    'max_tokens': :'maxTokens'
    # rubocop:enable Style/SymbolLiteral
  }
end

.swagger_typesObject

Attribute type mapping.



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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 97

def self.swagger_types
  {
    # rubocop:disable Style/SymbolLiteral
    'runtime_type': :'String',
    'prompt': :'String',
    'is_stream': :'BOOLEAN',
    'num_generations': :'Integer',
    'is_echo': :'BOOLEAN',
    'top_k': :'Integer',
    'top_p': :'Float',
    'temperature': :'Float',
    'frequency_penalty': :'Float',
    'presence_penalty': :'Float',
    'stop': :'Array<String>',
    'log_probs': :'Integer',
    'max_tokens': :'Integer'
    # rubocop:enable Style/SymbolLiteral
  }
end

Instance Method Details

#==(other) ⇒ Object

Checks equality by comparing each attribute.

Parameters:

  • other (Object)

    the other object to be compared



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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 224

def ==(other)
  return true if equal?(other)

  self.class == other.class &&
    runtime_type == other.runtime_type &&
    prompt == other.prompt &&
    is_stream == other.is_stream &&
    num_generations == other.num_generations &&
    is_echo == other.is_echo &&
    top_k == other.top_k &&
    top_p == other.top_p &&
    temperature == other.temperature &&
    frequency_penalty == other.frequency_penalty &&
    presence_penalty == other.presence_penalty &&
    stop == other.stop &&
    log_probs == other.log_probs &&
    max_tokens == other.max_tokens
end

#build_from_hash(attributes) ⇒ Object

Builds the object from hash

Parameters:

  • attributes (Hash)

    Model attributes in the form of hash

Returns:

  • (Object)

    Returns the model itself



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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 266

def build_from_hash(attributes)
  return nil unless attributes.is_a?(Hash)

  self.class.swagger_types.each_pair do |key, type|
    if type =~ /^Array<(.*)>/i
      # check to ensure the input is an array given that the the attribute
      # is documented as an array but the input is not
      if attributes[self.class.attribute_map[key]].is_a?(Array)
        public_method("#{key}=").call(
          attributes[self.class.attribute_map[key]]
            .map { |v| OCI::Internal::Util.convert_to_type(Regexp.last_match(1), v) }
        )
      end
    elsif !attributes[self.class.attribute_map[key]].nil?
      public_method("#{key}=").call(
        OCI::Internal::Util.convert_to_type(type, attributes[self.class.attribute_map[key]])
      )
    end
    # or else data not found in attributes(hash), not an issue as the data can be optional
  end

  self
end

#eql?(other) ⇒ Boolean

Parameters:

  • other (Object)

    the other object to be compared

Returns:

  • (Boolean)

See Also:

  • `==` method


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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 246

def eql?(other)
  self == other
end

#hashFixnum

Calculates hash code according to all attributes.

Returns:

  • (Fixnum)

    Hash code



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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 255

def hash
  [runtime_type, prompt, is_stream, num_generations, is_echo, top_k, top_p, temperature, frequency_penalty, presence_penalty, stop, log_probs, max_tokens].hash
end

#to_hashHash

Returns the object in the form of hash

Returns:

  • (Hash)

    Returns the object in the form of hash



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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 299

def to_hash
  hash = {}
  self.class.attribute_map.each_pair do |attr, param|
    value = public_method(attr).call
    next if value.nil? && !instance_variable_defined?("@#{attr}")

    hash[param] = _to_hash(value)
  end
  hash
end

#to_sString

Returns the string representation of the object

Returns:

  • (String)

    String presentation of the object



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# File 'lib/oci/generative_ai_inference/models/llama_llm_inference_request.rb', line 293

def to_s
  to_hash.to_s
end