Class: AssemblyAI::Lemur::LemurBaseParams

Inherits:
Object
  • Object
show all
Defined in:
lib/assemblyai/lemur/types/lemur_base_params.rb

Constant Summary collapse

OMIT = 
Object.new

Instance Attribute Summary collapse

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(transcript_ids: OMIT, input_text: OMIT, context: OMIT, final_model: OMIT, max_output_size: OMIT, temperature: OMIT, additional_properties: nil) ⇒ AssemblyAI::Lemur::LemurBaseParams

Parameters:

  • transcript_ids (Array<String>) (defaults to: OMIT) —

    A list of completed transcripts with text. Up to a maximum of 100 files or 100 hours, whichever is lower. Use either transcript_ids or input_text as input into LeMUR.

  • input_text (String) (defaults to: OMIT) —

    Custom formatted transcript data. Maximum size is the context limit of the selected model, which defaults to 100000. Use either transcript_ids or input_text as input into LeMUR.

  • context (AssemblyAI::Lemur::LemurBaseParamsContext) (defaults to: OMIT) —

    Context to provide the model. This can be a string or a free-form JSON value.

  • final_model (AssemblyAI::Lemur::LemurModel) (defaults to: OMIT) —

    The model that is used for the final prompt after compression is performed.

  • max_output_size (Integer) (defaults to: OMIT) —

    Max output size in tokens, up to 4000

  • temperature (Float) (defaults to: OMIT) —

    The temperature to use for the model. Higher values result in answers that are more creative, lower values are more conservative. Can be any value between 0.0 and 1.0 inclusive.

  • additional_properties (OpenStruct) (defaults to: nil) —

    Additional properties unmapped to the current class definition



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# File 'lib/assemblyai/lemur/types/lemur_base_params.rb', line 53

def initialize(transcript_ids: OMIT, input_text: OMIT, context: OMIT, final_model: OMIT, max_output_size: OMIT,
               temperature: OMIT, additional_properties: nil)
  @transcript_ids = transcript_ids if transcript_ids != OMIT
  @input_text = input_text if input_text != OMIT
  @context = context if context != OMIT
  @final_model = final_model if final_model != OMIT
  @max_output_size = max_output_size if max_output_size != OMIT
  @temperature = temperature if temperature != OMIT
  @additional_properties = additional_properties
  @_field_set = {
    "transcript_ids": transcript_ids,
    "input_text": input_text,
    "context": context,
    "final_model": final_model,
    "max_output_size": max_output_size,
    "temperature": temperature
  }.reject do |_k, v|
    v == OMIT
  end
end

Instance Attribute Details

#additional_properties ⇒ OpenStruct (readonly)

Returns Additional properties unmapped to the current class definition.

Returns:

  • (OpenStruct) —

    Additional properties unmapped to the current class definition



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# File 'lib/assemblyai/lemur/types/lemur_base_params.rb', line 31

def additional_properties
  @additional_properties
end

#context ⇒ AssemblyAI::Lemur::LemurBaseParamsContext (readonly)

Returns Context to provide the model. This can be a string or a free-form JSON value.

Returns:



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# File 'lib/assemblyai/lemur/types/lemur_base_params.rb', line 20

def context
  @context
end

#final_model ⇒ AssemblyAI::Lemur::LemurModel (readonly)

Returns The model that is used for the final prompt after compression is performed.

Returns:



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# File 'lib/assemblyai/lemur/types/lemur_base_params.rb', line 22

def final_model
  @final_model
end

#input_text ⇒ String (readonly)

Returns Custom formatted transcript data. Maximum size is the context limit of the selected model, which defaults to 100000. Use either transcript_ids or input_text as input into LeMUR.

Returns:

  • (String) —

    Custom formatted transcript data. Maximum size is the context limit of the selected model, which defaults to 100000. Use either transcript_ids or input_text as input into LeMUR.



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# File 'lib/assemblyai/lemur/types/lemur_base_params.rb', line 18

def input_text
  @input_text
end

#max_output_size ⇒ Integer (readonly)

Returns Max output size in tokens, up to 4000.

Returns:

  • (Integer) —

    Max output size in tokens, up to 4000



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# File 'lib/assemblyai/lemur/types/lemur_base_params.rb', line 24

def max_output_size
  @max_output_size
end

#temperature ⇒ Float (readonly)

Returns The temperature to use for the model. Higher values result in answers that are more creative, lower values are more conservative. Can be any value between 0.0 and 1.0 inclusive.

Returns:

  • (Float) —

    The temperature to use for the model. Higher values result in answers that are more creative, lower values are more conservative. Can be any value between 0.0 and 1.0 inclusive.



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# File 'lib/assemblyai/lemur/types/lemur_base_params.rb', line 29

def temperature
  @temperature
end

#transcript_ids ⇒ Array<String> (readonly)

Returns A list of completed transcripts with text. Up to a maximum of 100 files or 100 hours, whichever is lower. Use either transcript_ids or input_text as input into LeMUR.

Returns:

  • (Array<String>) —

    A list of completed transcripts with text. Up to a maximum of 100 files or 100 hours, whichever is lower. Use either transcript_ids or input_text as input into LeMUR.



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# File 'lib/assemblyai/lemur/types/lemur_base_params.rb', line 14

def transcript_ids
  @transcript_ids
end

Class Method Details

.from_json(json_object:) ⇒ AssemblyAI::Lemur::LemurBaseParams

Deserialize a JSON object to an instance of LemurBaseParams

Parameters:

  • json_object (String)

Returns:



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# File 'lib/assemblyai/lemur/types/lemur_base_params.rb', line 78

def self.from_json(json_object:)
  struct = JSON.parse(json_object, object_class: OpenStruct)
  parsed_json = JSON.parse(json_object)
  transcript_ids = struct["transcript_ids"]
  input_text = struct["input_text"]
  if parsed_json["context"].nil?
    context = nil
  else
    context = parsed_json["context"].to_json
    context = AssemblyAI::Lemur::LemurBaseParamsContext.from_json(json_object: context)
  end
  final_model = struct["final_model"]
  max_output_size = struct["max_output_size"]
  temperature = struct["temperature"]
  new(
    transcript_ids: transcript_ids,
    input_text: input_text,
    context: context,
    final_model: final_model,
    max_output_size: max_output_size,
    temperature: temperature,
    additional_properties: struct
  )
end

.validate_raw(obj:) ⇒ Void

Leveraged for Union-type generation, validate_raw attempts to parse the given

hash and check each fields type against the current object's property
definitions.

Parameters:

  • obj (Object)

Returns:

  • (Void) 


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# File 'lib/assemblyai/lemur/types/lemur_base_params.rb', line 116

def self.validate_raw(obj:)
  obj.transcript_ids&.is_a?(Array) != false || raise("Passed value for field obj.transcript_ids is not the expected type, validation failed.")
  obj.input_text&.is_a?(String) != false || raise("Passed value for field obj.input_text is not the expected type, validation failed.")
  obj.context.nil? || AssemblyAI::Lemur::LemurBaseParamsContext.validate_raw(obj: obj.context)
  obj.final_model&.is_a?(AssemblyAI::Lemur::LemurModel) != false || raise("Passed value for field obj.final_model is not the expected type, validation failed.")
  obj.max_output_size&.is_a?(Integer) != false || raise("Passed value for field obj.max_output_size is not the expected type, validation failed.")
  obj.temperature&.is_a?(Float) != false || raise("Passed value for field obj.temperature is not the expected type, validation failed.")
end

Instance Method Details

#to_json(*_args) ⇒ String

Serialize an instance of LemurBaseParams to a JSON object

Returns:

  • (String) 


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# File 'lib/assemblyai/lemur/types/lemur_base_params.rb', line 106

def to_json(*_args)
  @_field_set&.to_json
end