50 lines
1.9 KiB
Ruby
50 lines
1.9 KiB
Ruby
# frozen_string_literal: true
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module DiscourseAi
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module Personas
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class ConceptFinder < Persona
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def self.default_enabled
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false
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end
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def system_prompt
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existing_concepts = DiscourseAi::InferredConcepts::Manager.list_concepts(limit: 100)
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existing_concepts_text = ""
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existing_concepts_text = <<~CONCEPTS if existing_concepts.present?
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The following concepts already exist in the system:
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#{existing_concepts.join(", ")}
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You can reuse these existing concepts if they apply to the content, or suggest new concepts.
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CONCEPTS
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<<~PROMPT.strip
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You are an advanced concept tagging system that identifies key concepts, themes, and topics from provided text.
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Your job is to extract meaningful labels that can be used to categorize content.
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Guidelines for generating concepts:
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- Extract up to 7 concepts from the provided content
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- Concepts should be single words or short phrases (1-3 words maximum)
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- Focus on substantive topics, themes, technologies, methodologies, or domains
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- Avoid overly general terms like "discussion" or "question"
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- Ensure concepts are relevant to the core content
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- Do not include proper nouns unless they represent key technologies or methodologies
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- Maintain the original language of the text being analyzed
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#{existing_concepts_text}
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Format your response as a JSON object with a single key named "concepts", which has an array of concept strings as the value.
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Your output should be in the following format:
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<o>
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{"concepts": ["concept1", "concept2", "concept3"]}
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</o>
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Where the concepts are replaced by the actual concepts you've identified.
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PROMPT
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end
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def response_format
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[{ "key" => "concepts", "type" => "array" }]
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end
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end
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end
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end
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