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* Wire conversation history through OpenAI responses API * Fix RuboCop hash brace spacing in assistant tests * Pipelock ignores * Batch fixes --------- Co-authored-by: sokiee <sokysrm@gmail.com>
161 lines
4.4 KiB
Ruby
161 lines
4.4 KiB
Ruby
class Assistant::Responder
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def initialize(message:, instructions:, function_tool_caller:, llm:)
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@message = message
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@instructions = instructions
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@function_tool_caller = function_tool_caller
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@llm = llm
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end
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def on(event_name, &block)
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listeners[event_name.to_sym] << block
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end
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def respond(previous_response_id: nil)
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# Track whether response was handled by streamer
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response_handled = false
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# For the first response
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streamer = proc do |chunk|
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case chunk.type
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when "output_text"
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emit(:output_text, chunk.data)
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when "response"
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response = chunk.data
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response_handled = true
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if response.function_requests.any?
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handle_follow_up_response(response)
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else
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emit(:response, { id: response.id })
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end
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end
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end
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response = get_llm_response(streamer: streamer, previous_response_id: previous_response_id)
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# For synchronous (non-streaming) responses, handle function requests if not already handled by streamer
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unless response_handled
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if response && response.function_requests.any?
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handle_follow_up_response(response)
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elsif response
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emit(:response, { id: response.id })
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end
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end
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end
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private
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attr_reader :message, :instructions, :function_tool_caller, :llm
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def handle_follow_up_response(response)
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streamer = proc do |chunk|
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case chunk.type
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when "output_text"
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emit(:output_text, chunk.data)
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when "response"
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# We do not currently support function executions for a follow-up response (avoid recursive LLM calls that could lead to high spend)
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emit(:response, { id: chunk.data.id })
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end
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end
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function_tool_calls = function_tool_caller.fulfill_requests(response.function_requests)
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emit(:response, {
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id: response.id,
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function_tool_calls: function_tool_calls
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})
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# Get follow-up response with tool call results
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get_llm_response(
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streamer: streamer,
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function_results: function_tool_calls.map(&:to_result),
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previous_response_id: response.id
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)
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end
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def get_llm_response(streamer:, function_results: [], previous_response_id: nil)
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response = llm.chat_response(
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message.content,
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model: message.ai_model,
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instructions: instructions,
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functions: function_tool_caller.function_definitions,
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function_results: function_results,
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messages: conversation_history,
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streamer: streamer,
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previous_response_id: previous_response_id,
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session_id: chat_session_id,
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user_identifier: chat_user_identifier,
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family: message.chat&.user&.family
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)
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unless response.success?
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raise response.error
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end
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response.data
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end
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def emit(event_name, payload = nil)
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listeners[event_name.to_sym].each { |block| block.call(payload) }
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end
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def listeners
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@listeners ||= Hash.new { |h, k| h[k] = [] }
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end
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def chat_session_id
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chat&.id&.to_s
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end
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def chat_user_identifier
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return unless chat&.user_id
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::Digest::SHA256.hexdigest(chat.user_id.to_s)
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end
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def chat
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@chat ||= message.chat
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end
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def conversation_history
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messages = []
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return messages unless chat&.messages
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chat.messages
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.where(type: [ "UserMessage", "AssistantMessage" ], status: "complete")
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.includes(:tool_calls)
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.ordered
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.each do |chat_message|
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if chat_message.tool_calls.any?
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messages << {
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role: chat_message.role,
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content: chat_message.content || "",
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tool_calls: chat_message.tool_calls.map(&:to_tool_call)
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}
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chat_message.tool_calls.map(&:to_result).each do |fn_result|
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# Handle nil explicitly to avoid serializing to "null"
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output = fn_result[:output]
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content = if output.nil?
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""
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elsif output.is_a?(String)
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output
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else
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output.to_json
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end
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messages << {
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role: "tool",
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tool_call_id: fn_result[:call_id],
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name: fn_result[:name],
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content: content
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}
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end
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elsif !chat_message.content.blank?
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messages << { role: chat_message.role, content: chat_message.content || "" }
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end
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end
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messages
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end
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end
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