Class: LlmConductor::Clients::BaseClient

Inherits:
Object
  • Object
show all
Includes:
Prompts
Defined in:
lib/llm_conductor/clients/base_client.rb

Overview

Base client class providing common functionality for all LLM providers including prompt building, token counting, and response formatting.

Instance Attribute Summary collapse

Instance Method Summary collapse

Methods included from Prompts

#prompt_analyze_content, #prompt_classify_content, #prompt_custom, #prompt_extract_links, #prompt_summarize_text

Constructor Details

#initialize(model:, type:) ⇒ BaseClient

Returns a new instance of BaseClient.



16
17
18
19
 
# File 'lib/llm_conductor/clients/base_client.rb', line 16

def initialize(model:, type:)
  @model = model
  @type = type
end

Instance Attribute Details

#model ⇒ Object (readonly)

Returns the value of attribute model.



14
15
16
 
# File 'lib/llm_conductor/clients/base_client.rb', line 14

def model
  @model
end

#type ⇒ Object (readonly)

Returns the value of attribute type.



14
15
16
 
# File 'lib/llm_conductor/clients/base_client.rb', line 14

def type
  @type
end

Instance Method Details

#generate(data:) ⇒ Object 



21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
 
# File 'lib/llm_conductor/clients/base_client.rb', line 21

def generate(data:)
  prompt = build_prompt(data)
  input_tokens = calculate_tokens(prompt)
  output_text = generate_content(prompt)
  output_tokens = calculate_tokens(output_text || '')

  # Logging AI request metadata if logger is set
  configuration.logger&.debug(
    "Vendor: #{vendor_name}, Model: #{@model} " \
    "Output_tokens: #{output_tokens} Input_tokens: #{input_tokens}"
  )

  build_response(output_text, input_tokens, output_tokens, { prompt: })
rescue StandardError => e
  build_error_response(e)
end

#generate_simple(prompt:) ⇒ Object

Simple generation method that accepts a direct prompt and returns a Response object



39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
 
# File 'lib/llm_conductor/clients/base_client.rb', line 39

def generate_simple(prompt:)
  input_tokens = calculate_tokens(prompt)
  output_text = generate_content(prompt)
  output_tokens = calculate_tokens(output_text || '')

  # Logging AI request metadata if logger is set
  configuration.logger&.debug(
    "Vendor: #{vendor_name}, Model: #{@model} " \
    "Output_tokens: #{output_tokens} Input_tokens: #{input_tokens}"
  )

  build_response(output_text, input_tokens, output_tokens)
rescue StandardError => e
  build_error_response(e)
end