Class: Raif::Llm
- Inherits:
-
Object
- Object
- Raif::Llm
- Includes:
- ActiveModel::Model, Concerns::Llms::MessageFormatting
- Defined in:
- app/models/raif/llm.rb
Direct Known Subclasses
Raif::Llms::Anthropic, Raif::Llms::Bedrock, Raif::Llms::Google, Raif::Llms::OpenAiBase, Raif::Llms::OpenRouter
Constant Summary collapse
- VALID_RESPONSE_FORMATS =
[:text, :json, :html].freeze
Instance Attribute Summary collapse
-
#api_name ⇒ Object
Returns the value of attribute api_name.
-
#default_max_completion_tokens ⇒ Object
Returns the value of attribute default_max_completion_tokens.
-
#default_temperature ⇒ Object
Returns the value of attribute default_temperature.
-
#display_name ⇒ Object
Returns the value of attribute display_name.
-
#input_token_cost ⇒ Object
Returns the value of attribute input_token_cost.
-
#key ⇒ Object
Returns the value of attribute key.
-
#output_token_cost ⇒ Object
Returns the value of attribute output_token_cost.
-
#provider_settings ⇒ Object
Returns the value of attribute provider_settings.
-
#supported_provider_managed_tools ⇒ Object
Returns the value of attribute supported_provider_managed_tools.
-
#supports_native_tool_use ⇒ Object
(also: #supports_native_tool_use?)
Returns the value of attribute supports_native_tool_use.
Class Method Summary collapse
-
.cache_creation_input_token_cost_multiplier ⇒ Object
Multiplier applied to the base input_token_cost to derive the per-token cost for cache creation writes.
-
.cache_read_input_token_cost_multiplier ⇒ Object
Multiplier applied to the base input_token_cost to derive the per-token cost for cache reads.
-
.prompt_tokens_include_cached_tokens? ⇒ Boolean
Override in subclasses to indicate whether prompt_tokens reported by the provider already include cached tokens as a subset (OpenAI, Google, OpenRouter) or whether cached tokens are reported separately and are additive to prompt_tokens (Anthropic, Bedrock).
- .valid_response_formats ⇒ Object
Instance Method Summary collapse
-
#build_forced_tool_choice(tool_name) ⇒ Hash
Build the tool_choice parameter to force a specific tool to be called.
-
#build_required_tool_choice ⇒ Hash, String
Build the tool_choice parameter to require the model to call any tool (but not a specific one).
- #chat(message: nil, messages: nil, response_format: :text, available_model_tools: [], source: nil, system_prompt: nil, temperature: nil, max_completion_tokens: nil, tool_choice: nil, &block) ⇒ Object
-
#initialize(key:, api_name:, display_name: nil, model_provider_settings: {}, supported_provider_managed_tools: [], supports_native_tool_use: true, temperature: nil, max_completion_tokens: nil, input_token_cost: nil, output_token_cost: nil) ⇒ Llm
constructor
A new instance of Llm.
- #name ⇒ Object
- #perform_model_completion!(model_completion, &block) ⇒ Object
-
#supports_faithful_required_tool_choice?(available_model_tools) ⇒ Boolean
Whether the provider can faithfully enforce tool_choice: :required for the given tool set.
- #supports_provider_managed_tool?(tool_klass) ⇒ Boolean
- #validate_provider_managed_tool_support!(tool) ⇒ Object
Constructor Details
#initialize(key:, api_name:, display_name: nil, model_provider_settings: {}, supported_provider_managed_tools: [], supports_native_tool_use: true, temperature: nil, max_completion_tokens: nil, input_token_cost: nil, output_token_cost: nil) ⇒ Llm
Returns a new instance of Llm.
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# File 'app/models/raif/llm.rb', line 26 def initialize( key:, api_name:, display_name: nil, model_provider_settings: {}, supported_provider_managed_tools: [], supports_native_tool_use: true, temperature: nil, max_completion_tokens: nil, input_token_cost: nil, output_token_cost: nil ) @key = key @api_name = api_name @display_name = display_name @provider_settings = model_provider_settings @supports_native_tool_use = supports_native_tool_use @default_temperature = temperature || 0.7 @default_max_completion_tokens = max_completion_tokens @input_token_cost = input_token_cost @output_token_cost = output_token_cost @supported_provider_managed_tools = supported_provider_managed_tools.map(&:to_s) end |
Instance Attribute Details
#api_name ⇒ Object
Returns the value of attribute api_name.
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# File 'app/models/raif/llm.rb', line 8 def api_name @api_name end |
#default_max_completion_tokens ⇒ Object
Returns the value of attribute default_max_completion_tokens.
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# File 'app/models/raif/llm.rb', line 8 def default_max_completion_tokens @default_max_completion_tokens end |
#default_temperature ⇒ Object
Returns the value of attribute default_temperature.
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# File 'app/models/raif/llm.rb', line 8 def default_temperature @default_temperature end |
#display_name ⇒ Object
Returns the value of attribute display_name.
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# File 'app/models/raif/llm.rb', line 8 def display_name @display_name end |
#input_token_cost ⇒ Object
Returns the value of attribute input_token_cost.
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# File 'app/models/raif/llm.rb', line 8 def input_token_cost @input_token_cost end |
#key ⇒ Object
Returns the value of attribute key.
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# File 'app/models/raif/llm.rb', line 8 def key @key end |
#output_token_cost ⇒ Object
Returns the value of attribute output_token_cost.
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# File 'app/models/raif/llm.rb', line 8 def output_token_cost @output_token_cost end |
#provider_settings ⇒ Object
Returns the value of attribute provider_settings.
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# File 'app/models/raif/llm.rb', line 8 def provider_settings @provider_settings end |
#supported_provider_managed_tools ⇒ Object
Returns the value of attribute supported_provider_managed_tools.
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# File 'app/models/raif/llm.rb', line 8 def supported_provider_managed_tools @supported_provider_managed_tools end |
#supports_native_tool_use ⇒ Object Also known as: supports_native_tool_use?
Returns the value of attribute supports_native_tool_use.
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# File 'app/models/raif/llm.rb', line 8 def supports_native_tool_use @supports_native_tool_use end |
Class Method Details
.cache_creation_input_token_cost_multiplier ⇒ Object
Multiplier applied to the base input_token_cost to derive the per-token cost for cache creation writes. Return nil when there is no write surcharge.
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# File 'app/models/raif/llm.rb', line 157 def self.cache_creation_input_token_cost_multiplier nil end |
.cache_read_input_token_cost_multiplier ⇒ Object
Multiplier applied to the base input_token_cost to derive the per-token cost for cache reads. Return nil when the provider has no cache pricing.
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# File 'app/models/raif/llm.rb', line 151 def self.cache_read_input_token_cost_multiplier nil end |
.prompt_tokens_include_cached_tokens? ⇒ Boolean
Override in subclasses to indicate whether prompt_tokens reported by the provider already include cached tokens as a subset (OpenAI, Google, OpenRouter) or whether cached tokens are reported separately and are additive to prompt_tokens (Anthropic, Bedrock).
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# File 'app/models/raif/llm.rb', line 145 def self.prompt_tokens_include_cached_tokens? true end |
.valid_response_formats ⇒ Object
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# File 'app/models/raif/llm.rb', line 137 def self.valid_response_formats VALID_RESPONSE_FORMATS end |
Instance Method Details
#build_forced_tool_choice(tool_name) ⇒ Hash
Build the tool_choice parameter to force a specific tool to be called. Each provider implements this to return the correct format.
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# File 'app/models/raif/llm.rb', line 169 def build_forced_tool_choice(tool_name) raise NotImplementedError, "#{self.class.name} must implement #build_forced_tool_choice" end |
#build_required_tool_choice ⇒ Hash, String
Build the tool_choice parameter to require the model to call any tool (but not a specific one). Each provider implements this to return the correct format.
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# File 'app/models/raif/llm.rb', line 176 def build_required_tool_choice raise NotImplementedError, "#{self.class.name} must implement #build_required_tool_choice" end |
#chat(message: nil, messages: nil, response_format: :text, available_model_tools: [], source: nil, system_prompt: nil, temperature: nil, max_completion_tokens: nil, tool_choice: nil, &block) ⇒ Object
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# File 'app/models/raif/llm.rb', line 54 def chat(message: nil, messages: nil, response_format: :text, available_model_tools: [], source: nil, system_prompt: nil, temperature: nil, max_completion_tokens: nil, tool_choice: nil, &block) unless response_format.is_a?(Symbol) raise ArgumentError, "Raif::Llm#chat - Invalid response format: #{response_format}. Must be a symbol (you passed #{response_format.class}) and be one of: #{VALID_RESPONSE_FORMATS.join(", ")}" # rubocop:disable Layout/LineLength end unless VALID_RESPONSE_FORMATS.include?(response_format) raise ArgumentError, "Raif::Llm#chat - Invalid response format: #{response_format}. Must be one of: #{VALID_RESPONSE_FORMATS.join(", ")}" end unless .present? || .present? raise ArgumentError, "Raif::Llm#chat - You must provide either a message: or messages: argument" end if .present? && .present? raise ArgumentError, "Raif::Llm#chat - You must provide either a message: or messages: argument, not both" end # Normalize :required / "required" to the symbol form for validation tool_choice = :required if tool_choice.to_s == "required" if tool_choice == :required if available_model_tools.blank? raise ArgumentError, "Raif::Llm#chat - tool_choice: :required requires at least one available model tool" end elsif tool_choice.present? && !available_model_tools.map(&:to_s).include?(tool_choice.to_s) raise ArgumentError, "Raif::Llm#chat - Invalid tool choice: #{tool_choice} is not included in the available model tools: #{available_model_tools.join(", ")}" end unless Raif.config.llm_api_requests_enabled Raif.logger.warn("LLM API requests are disabled. Skipping request to #{api_name}.") return end = [{ "role" => "user", "content" => }] if .present? temperature ||= default_temperature max_completion_tokens ||= default_max_completion_tokens model_completion = Raif::ModelCompletion.create!( messages: (), system_prompt: system_prompt, response_format: response_format, source: source, llm_model_key: key.to_s, model_api_name: api_name, temperature: temperature, max_completion_tokens: max_completion_tokens, available_model_tools: available_model_tools, tool_choice: tool_choice&.to_s, stream_response: block_given? ) model_completion.started! retry_with_backoff(model_completion) do perform_model_completion!(model_completion, &block) ensure_model_completion_present!(model_completion) end model_completion.completed! model_completion rescue Raif::Errors::StreamingError => e Rails.logger.error("Raif streaming error -- code: #{e.code} -- type: #{e.type} -- message: #{e.} -- event: #{e.event}") model_completion&.record_failure!(e) unless model_completion&.failed? raise e rescue Faraday::Error => e Raif.logger.error("LLM API request failed (status: #{e.response_status}): #{e.}") Raif.logger.error(e.response_body) model_completion&.record_failure!(e) unless model_completion&.failed? raise e rescue StandardError => e model_completion&.record_failure!(e) unless model_completion&.failed? raise e end |
#name ⇒ Object
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# File 'app/models/raif/llm.rb', line 50 def name I18n.t("raif.model_names.#{key}", default: display_name || key.to_s.humanize) end |
#perform_model_completion!(model_completion, &block) ⇒ Object
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# File 'app/models/raif/llm.rb', line 133 def perform_model_completion!(model_completion, &block) raise NotImplementedError, "#{self.class.name} must implement #perform_model_completion!" end |
#supports_faithful_required_tool_choice?(available_model_tools) ⇒ Boolean
Whether the provider can faithfully enforce tool_choice: :required for the given tool set. Override in subclasses when a provider can only enforce required tool use for some tool types.
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# File 'app/models/raif/llm.rb', line 183 def supports_faithful_required_tool_choice?(available_model_tools) available_model_tools.present? end |
#supports_provider_managed_tool?(tool_klass) ⇒ Boolean
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# File 'app/models/raif/llm.rb', line 161 def supports_provider_managed_tool?(tool_klass) supported_provider_managed_tools&.include?(tool_klass.to_s) end |
#validate_provider_managed_tool_support!(tool) ⇒ Object
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# File 'app/models/raif/llm.rb', line 187 def validate_provider_managed_tool_support!(tool) unless supports_provider_managed_tool?(tool) raise Raif::Errors::UnsupportedFeatureError, "Invalid provider-managed tool: #{tool.name} for #{key}" end end |