mirror of
https://github.com/discourse/discourse-ai.git
synced 2025-07-01 20:12:15 +00:00
c34fcc8a95
This commit introduces a new Forum Researcher persona specialized in deep forum content analysis along with comprehensive improvements to our AI infrastructure.
Key additions:
New Forum Researcher persona with advanced filtering and analysis capabilities
Robust filtering system supporting tags, categories, dates, users, and keywords
LLM formatter to efficiently process and chunk research results
Infrastructure improvements:
Implemented CancelManager class to centrally manage AI completion cancellations
Replaced callback-based cancellation with a more robust pattern
Added systematic cancellation monitoring with callbacks
Other improvements:
Added configurable default_enabled flag to control which personas are enabled by default
Updated translation strings for the new researcher functionality
Added comprehensive specs for the new components
Renames Researcher -> Web Researcher
This change makes our AI platform more stable while adding powerful research capabilities that can analyze forum trends and surface relevant content.
107 lines
3.0 KiB
Ruby
107 lines
3.0 KiB
Ruby
# frozen_string_literal: true
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module DiscourseAi
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module Completions
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module Endpoints
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class CannedResponse
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CANNED_RESPONSE_ERROR = Class.new(StandardError)
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def initialize(responses)
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@responses = responses
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@completions = 0
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@dialect = nil
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end
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def normalize_model_params(model_params)
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# max_tokens, temperature, stop_sequences are already supported
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model_params
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end
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attr_reader :responses, :completions, :dialect, :model_params
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def prompt_messages
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dialect.prompt.messages
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end
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def perform_completion!(
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dialect,
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_user,
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model_params,
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feature_name: nil,
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feature_context: nil,
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partial_tool_calls: false,
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output_thinking: false,
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cancel_manager: nil
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)
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@dialect = dialect
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@model_params = model_params
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response = responses[completions]
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if response.nil?
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raise CANNED_RESPONSE_ERROR,
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"The number of completions you requested exceed the number of canned responses"
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end
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response = as_structured_output(response) if model_params[:response_format].present?
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raise response if response.is_a?(StandardError)
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@completions += 1
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if block_given?
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cancelled = false
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cancel_fn = lambda { cancelled = true }
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# We buffer and return tool invocations in one go.
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as_array = response.is_a?(Array) ? response : [response]
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as_array.each do |response|
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if is_tool?(response)
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yield(response, cancel_fn)
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elsif is_thinking?(response)
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yield(response, cancel_fn)
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elsif is_structured_output?(response)
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yield(response, cancel_fn)
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else
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response.each_char do |char|
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break if cancelled
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yield(char, cancel_fn)
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end
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end
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end
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end
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response = response.first if response.is_a?(Array) && response.length == 1
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response
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end
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def tokenizer
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DiscourseAi::Tokenizer::OpenAiTokenizer
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end
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private
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def is_thinking?(response)
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response.is_a?(DiscourseAi::Completions::Thinking)
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end
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def is_tool?(response)
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response.is_a?(DiscourseAi::Completions::ToolCall)
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end
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def is_structured_output?(response)
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response.is_a?(DiscourseAi::Completions::StructuredOutput)
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end
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def as_structured_output(response)
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schema_properties = model_params[:response_format].dig(:json_schema, :schema, :properties)
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return response if schema_properties.blank?
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output = DiscourseAi::Completions::StructuredOutput.new(schema_properties)
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output << { schema_properties.keys.first => response }.to_json
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output
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end
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end
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end
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end
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end
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