Class: Prescient::Provider::HuggingFace

Inherits:
Base
  • Object
show all
Includes:
HTTParty
Defined in:
lib/prescient/provider/huggingface.rb

Constant Summary collapse

EMBEDDING_DIMENSIONS = 
{
  'sentence-transformers/all-MiniLM-L6-v2'     => 384,
  'sentence-transformers/all-mpnet-base-v2'    => 768,
  'sentence-transformers/all-roberta-large-v1' => 1024,
}.freeze

Instance Attribute Summary

Attributes inherited from Base

#options

Instance Method Summary collapse

Methods inherited from Base

#available?

Constructor Details

#initialize(**options) ⇒ HuggingFace

Returns a new instance of HuggingFace.



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# File 'lib/prescient/provider/huggingface.rb', line 16

def initialize(**options)
  super
  self.class.default_timeout(@options[:timeout] || 60)
end

Instance Method Details

#generate_embedding(text, **_options) ⇒ Object 



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# File 'lib/prescient/provider/huggingface.rb', line 21

def generate_embedding(text, **_options)
  handle_errors do
    clean_text_input = clean_text(text)

    response = self.class.post("/pipeline/feature-extraction/#{@options[:embedding_model]}",
                               headers: {
                                 'Content-Type'  => 'application/json',
                                 'Authorization' => "Bearer #{@options[:api_key]}",
                               },
                               body:    {
                                 inputs:  clean_text_input,
                                 options: {
                                   wait_for_model: true,
                                 },
                               }.to_json)

    validate_response!(response, 'embedding generation')

    # HuggingFace returns embeddings as nested arrays, get the first one
    embedding_data = response.parsed_response
    embedding_data = embedding_data.first if embedding_data.is_a?(Array) && embedding_data.first.is_a?(Array)

    raise Prescient::InvalidResponseError, 'No embedding returned' unless embedding_data.is_a?(Array)

    expected_dimensions = EMBEDDING_DIMENSIONS[@options[:embedding_model]] || 384
    normalize_embedding(embedding_data, expected_dimensions)
  end
end

#generate_response(prompt, context_items = [], **options) ⇒ Object 



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# File 'lib/prescient/provider/huggingface.rb', line 50

def generate_response(prompt, context_items = [], **options)
  handle_errors do
    formatted_prompt = build_prompt(prompt, context_items)

    response = self.class.post("/models/#{@options[:chat_model]}",
                               headers: {
                                 'Content-Type'  => 'application/json',
                                 'Authorization' => "Bearer #{@options[:api_key]}",
                               },
                               body:    {
                                 inputs:     formatted_prompt,
                                 parameters: {
                                   max_new_tokens:   options[:max_tokens] || 2000,
                                   temperature:      options[:temperature] || 0.7,
                                   top_p:            options[:top_p] || 0.9,
                                   return_full_text: false,
                                 },
                                 options:    {
                                   wait_for_model: true,
                                 },
                               }.to_json)

    validate_response!(response, 'text generation')

    # HuggingFace returns different formats depending on the model
    generated_text = nil
    parsed_response = response.parsed_response

    if parsed_response.is_a?(Array) && parsed_response.first.is_a?(Hash)
      generated_text = parsed_response.first['generated_text']
    elsif parsed_response.is_a?(Hash)
      generated_text = parsed_response['generated_text'] || parsed_response['text']
    end

    raise Prescient::InvalidResponseError, 'No response generated' unless generated_text

    {
      response:        generated_text.strip,
      model:           @options[:chat_model],
      provider:        'huggingface',
      processing_time: nil,
      metadata:        {},
    }
  end
end

#health_check ⇒ Object 



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# File 'lib/prescient/provider/huggingface.rb', line 96

def health_check
  handle_errors do
    # Test embedding model
    embedding_response = self.class.post("/pipeline/feature-extraction/#{@options[:embedding_model]}",
                                         headers: {
                                           'Authorization' => "Bearer #{@options[:api_key]}",
                                         },
                                         body:    { inputs: 'test' }.to_json)

    # Test chat model
    chat_response = self.class.post("/models/#{@options[:chat_model]}",
                                    headers: {
                                      'Authorization' => "Bearer #{@options[:api_key]}",
                                    },
                                    body:    {
                                      inputs:     'test',
                                      parameters: { max_new_tokens: 5 },
                                    }.to_json)

    embedding_healthy = embedding_response.success?
    chat_healthy = chat_response.success?

    {
      status:          embedding_healthy && chat_healthy ? 'healthy' : 'partial',
      provider:        'huggingface',
      embedding_model: {
        name:      @options[:embedding_model],
        available: embedding_healthy,
      },
      chat_model:      {
        name:      @options[:chat_model],
        available: chat_healthy,
      },
      ready:           embedding_healthy && chat_healthy,
    }
  end
rescue Prescient::ConnectionError => e
  {
    status:   'unavailable',
    provider: 'huggingface',
    error:    e.class.name,
    message:  e.message,
  }
end

#list_models ⇒ Object 



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# File 'lib/prescient/provider/huggingface.rb', line 141

def list_models
  # HuggingFace doesn't provide a simple API to list all models
  # Return the configured models
  [
    {
      name:       @options[:embedding_model],
      type:       'embedding',
      dimensions: EMBEDDING_DIMENSIONS[@options[:embedding_model]],
    },
    {
      name: @options[:chat_model],
      type: 'text-generation',
    },
  ]
end