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f9d7d7f5f0
* DEV: AI bot migration to the Llm pattern. We added tool and conversation context support to the Llm service in discourse-ai#366, meaning we met all the conditions to migrate this module. This PR migrates to the new pattern, meaning adding a new bot now requires minimal effort as long as the service supports it. On top of this, we introduce the concept of a "Playground" to separate the PM-specific bits from the completion, allowing us to use the bot in other contexts like chat in the future. Commands are called tools, and we simplified all the placeholder logic to perform updates in a single place, making the flow more one-wayish. * Followup fixes based on testing * Cleanup unused inference code * FIX: text-based tools could be in the middle of a sentence * GPT-4-turbo support * Use new LLM API
86 lines
2.4 KiB
Ruby
86 lines
2.4 KiB
Ruby
# frozen_string_literal: true
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module DiscourseAi
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module AiBot
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module Tools
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class Google < Tool
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def self.signature
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{
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name: name,
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description:
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"Will search using Google - global internet search (supports all Google search operators)",
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parameters: [
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{ name: "query", description: "The search query", type: "string", required: true },
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],
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}
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end
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def self.custom_system_message
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"You were trained on OLD data, lean on search to get up to date information from the web"
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end
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def self.name
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"google"
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end
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def query
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parameters[:query].to_s
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end
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def invoke(bot_user, llm)
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yield("") # Triggers placeholder update
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api_key = SiteSetting.ai_google_custom_search_api_key
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cx = SiteSetting.ai_google_custom_search_cx
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escaped_query = CGI.escape(query)
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uri =
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URI(
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"https://www.googleapis.com/customsearch/v1?key=#{api_key}&cx=#{cx}&q=#{escaped_query}&num=10",
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)
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body = Net::HTTP.get(uri)
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parse_search_json(body, escaped_query, llm)
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end
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attr_reader :results_count
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protected
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def description_args
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{
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count: results_count || 0,
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query: query,
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url: "https://google.com/search?q=#{CGI.escape(query)}",
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}
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end
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private
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def minimize_field(result, field, llm, max_tokens: 100)
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data = result[field]
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return "" if data.blank?
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llm.tokenizer.truncate(data, max_tokens).squish
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end
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def parse_search_json(json_data, escaped_query, llm)
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parsed = JSON.parse(json_data)
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results = parsed["items"]
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@results_count = parsed.dig("searchInformation", "totalResults").to_i
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format_results(results, args: escaped_query) do |result|
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{
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title: minimize_field(result, "title", llm),
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link: minimize_field(result, "link", llm),
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snippet: minimize_field(result, "snippet", llm, max_tokens: 120),
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displayLink: minimize_field(result, "displayLink", llm),
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formattedUrl: minimize_field(result, "formattedUrl", llm),
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}
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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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end
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