# frozen_string_literal: true module DiscourseAi module AiBot class ToolRunner attr_reader :tool, :parameters, :llm attr_accessor :running_attached_function, :timeout, :custom_raw TooManyRequestsError = Class.new(StandardError) DEFAULT_TIMEOUT = 2000 MAX_MEMORY = 10_000_000 MARSHAL_STACK_DEPTH = 20 MAX_HTTP_REQUESTS = 20 def initialize(parameters:, llm:, bot_user:, context: {}, tool:, timeout: nil) @parameters = parameters @llm = llm @bot_user = bot_user @context = context @tool = tool @timeout = timeout || DEFAULT_TIMEOUT @running_attached_function = false @http_requests_made = 0 end def mini_racer_context @mini_racer_context ||= begin ctx = MiniRacer::Context.new( max_memory: MAX_MEMORY, marshal_stack_depth: MARSHAL_STACK_DEPTH, ) attach_truncate(ctx) attach_http(ctx) attach_index(ctx) attach_upload(ctx) attach_chain(ctx) ctx.eval(framework_script) ctx end end def framework_script http_methods = %i[get post put patch delete].map { |method| <<~JS }.join("\n") #{method}: function(url, options) { return _http_#{method}(url, options); }, JS <<~JS const http = { #{http_methods} }; const llm = { truncate: _llm_truncate, }; const index = { search: _index_search, } const upload = { create: _upload_create, } const chain = { setCustomRaw: _chain_set_custom_raw, }; function details() { return ""; }; JS end def details eval_with_timeout("details()") end def eval_with_timeout(script, timeout: nil) timeout ||= @timeout mutex = Mutex.new done = false elapsed = 0 t = Thread.new do begin while !done # this is not accurate. but reasonable enough for a timeout sleep(0.001) elapsed += 1 if !self.running_attached_function if elapsed > timeout mutex.synchronize { mini_racer_context.stop unless done } break end end rescue => e STDERR.puts e STDERR.puts "FAILED TO TERMINATE DUE TO TIMEOUT" end end rval = mini_racer_context.eval(script) mutex.synchronize { done = true } # ensure we do not leak a thread in state t.join t = nil rval ensure # exceptions need to be handled t&.join end def invoke mini_racer_context.eval(tool.script) eval_with_timeout("invoke(#{JSON.generate(parameters)})") rescue MiniRacer::ScriptTerminatedError { error: "Script terminated due to timeout" } end private MAX_FRAGMENTS = 200 def rag_search(query, filenames: nil, limit: 10) limit = limit.to_i return [] if limit < 1 limit = [MAX_FRAGMENTS, limit].min upload_refs = UploadReference.where(target_id: tool.id, target_type: "AiTool").pluck(:upload_id) if filenames upload_refs = Upload.where(id: upload_refs).where(original_filename: filenames).pluck(:id) end return [] if upload_refs.empty? vector_rep = DiscourseAi::Embeddings::VectorRepresentations::Base.current_representation query_vector = vector_rep.vector_from(query) fragment_ids = DiscourseAi::Embeddings::Schema .for(RagDocumentFragment, vector: vector_rep) .asymmetric_similarity_search(query_vector, limit: limit, offset: 0) do |builder| builder.join(<<~SQL, target_id: tool.id, target_type: "AiTool") rag_document_fragments ON rag_document_fragments.id = rag_document_fragment_id AND rag_document_fragments.target_id = :target_id AND rag_document_fragments.target_type = :target_type SQL end .map(&:rag_document_fragment_id) fragments = RagDocumentFragment.where(id: fragment_ids, upload_id: upload_refs).pluck( :id, :fragment, :metadata, ) mapped = {} fragments.each do |id, fragment, metadata| mapped[id] = { fragment: fragment, metadata: metadata } end fragment_ids.take(limit).map { |fragment_id| mapped[fragment_id] } end def attach_truncate(mini_racer_context) mini_racer_context.attach( "_llm_truncate", ->(text, length) { @llm.tokenizer.truncate(text, length) }, ) end def attach_index(mini_racer_context) mini_racer_context.attach( "_index_search", ->(*params) do begin query, options = params self.running_attached_function = true options ||= {} options = options.symbolize_keys self.rag_search(query, **options) ensure self.running_attached_function = false end end, ) end def attach_chain(mini_racer_context) mini_racer_context.attach("_chain_set_custom_raw", ->(raw) { self.custom_raw = raw }) end def attach_upload(mini_racer_context) mini_racer_context.attach( "_upload_create", ->(filename, base_64_content) do begin self.running_attached_function = true # protect against misuse filename = File.basename(filename) Tempfile.create(filename) do |file| file.binmode file.write(Base64.decode64(base_64_content)) file.rewind upload = UploadCreator.new( file, filename, for_private_message: @context[:private_message], ).create_for(@bot_user.id) { id: upload.id, short_url: upload.short_url, url: upload.url } end ensure self.running_attached_function = false end end, ) end def attach_http(mini_racer_context) mini_racer_context.attach( "_http_get", ->(url, options) do begin @http_requests_made += 1 if @http_requests_made > MAX_HTTP_REQUESTS raise TooManyRequestsError.new("Tool made too many HTTP requests") end self.running_attached_function = true headers = (options && options["headers"]) || {} result = {} DiscourseAi::AiBot::Tools::Tool.send_http_request(url, headers: headers) do |response| result[:body] = response.body result[:status] = response.code.to_i end result ensure self.running_attached_function = false end end, ) %i[post put patch delete].each do |method| mini_racer_context.attach( "_http_#{method}", ->(url, options) do begin @http_requests_made += 1 if @http_requests_made > MAX_HTTP_REQUESTS raise TooManyRequestsError.new("Tool made too many HTTP requests") end self.running_attached_function = true headers = (options && options["headers"]) || {} body = options && options["body"] result = {} DiscourseAi::AiBot::Tools::Tool.send_http_request( url, method: method, headers: headers, body: body, ) do |response| result[:body] = response.body result[:status] = response.code.to_i end result rescue => e p url p options p e puts e.backtrace raise e ensure self.running_attached_function = false end end, ) end end end end end