Class: Langchain::LLM::MistralAI

Inherits:
Base
  • Object
show all
Defined in:
lib/langchain/llm/mistral_ai.rb

Overview

Gem requirements:

gem "mistral-ai"

Usage:

llm = Langchain::LLM::MistralAI.new(api_key: ENV["MISTRAL_AI_API_KEY"])

Constant Summary collapse

DEFAULTS = 
{
  chat_completion_model_name: "mistral-medium",
  embeddings_model_name: "mistral-embed"
}.freeze

Instance Attribute Summary collapse

Attributes inherited from Base

#client

Instance Method Summary collapse

Methods inherited from Base

#chat_parameters, #complete, #default_dimension, #default_dimensions, #summarize

Methods included from DependencyHelper

#depends_on

Constructor Details

#initialize(api_key:, default_options: {}) ⇒ MistralAI

Returns a new instance of MistralAI.



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# File 'lib/langchain/llm/mistral_ai.rb', line 17

def initialize(api_key:, default_options: {})
  depends_on "mistral-ai"

  @client = Mistral.new(
    credentials: {api_key: api_key},
    options: {server_sent_events: true}
  )

  @defaults = DEFAULTS.merge(default_options)
  chat_parameters.update(
    model: {default: @defaults[:chat_completion_model_name]},
    n: {default: @defaults[:n]},
    safe_prompt: {}
  )
  chat_parameters.remap(seed: :random_seed)
  chat_parameters.ignore(:n, :top_k)
end

Instance Attribute Details

#defaults ⇒ Object (readonly)

Returns the value of attribute defaults.



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# File 'lib/langchain/llm/mistral_ai.rb', line 15

def defaults
  @defaults
end

Instance Method Details

#chat(params = {}) ⇒ Object 



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# File 'lib/langchain/llm/mistral_ai.rb', line 35

def chat(params = {})
  parameters = chat_parameters.to_params(params)

  response = client.chat_completions(parameters)

  Langchain::LLM::MistralAIResponse.new(response.to_h)
end

#embed(text:, model: defaults[:embeddings_model_name], encoding_format: nil) ⇒ Object 



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# File 'lib/langchain/llm/mistral_ai.rb', line 43

def embed(
  text:,
  model: defaults[:embeddings_model_name],
  encoding_format: nil
)
  params = {
    input: text,
    model: model
  }
  params[:encoding_format] = encoding_format if encoding_format

  response = client.embeddings(params)

  Langchain::LLM::MistralAIResponse.new(response.to_h)
end