Class: DSPy::Propose::GroundedProposer

Inherits:
Object
  • Object
show all
Extended by:
T::Sig
Defined in:
lib/dspy/propose/grounded_proposer.rb

Overview

Grounded Proposer for generating better instructions based on training data Analyzes task patterns and creates contextually appropriate instructions

Defined Under Namespace

Classes: Config, ProposalResult

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(config: nil) ⇒ GroundedProposer 



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# File 'lib/dspy/propose/grounded_proposer.rb', line 92

def initialize(config: nil)
  @config = config || Config.new
end

Instance Attribute Details

#config ⇒ Object (readonly)

Returns the value of attribute config.



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# File 'lib/dspy/propose/grounded_proposer.rb', line 89

def config
  @config
end

Instance Method Details

#propose_instructions(signature_class, examples, few_shot_examples: nil, current_instruction: nil) ⇒ Object 



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# File 'lib/dspy/propose/grounded_proposer.rb', line 105

def propose_instructions(signature_class, examples, few_shot_examples: nil, current_instruction: nil)
  DSPy::Context.with_span(
    operation: 'optimization.instruction_proposal',
    'dspy.module' => 'GroundedProposer',
    'proposal.signature' => signature_class.name,
    'proposal.num_examples' => examples.size,
    'proposal.has_few_shot' => !few_shot_examples.nil?,
    'proposal.has_current_instruction' => !current_instruction.nil?
  ) do
    # Analyze the task and training data
    analysis = analyze_task(signature_class, examples, few_shot_examples)
    
    # Generate instruction candidates
    candidates = generate_instruction_candidates(
      signature_class, 
      analysis, 
      current_instruction
    )

    # Filter and rank candidates
    filtered_candidates = filter_and_rank_candidates(candidates, analysis)

    metadata = {
      generation_timestamp: Time.now.iso8601,
      model_used: @config.proposal_model,
      num_examples_analyzed: [examples.size, @config.max_examples_for_analysis].min,
      original_instruction: current_instruction
    }

    result = ProposalResult.new(
      candidate_instructions: filtered_candidates,
      analysis: analysis,
      metadata: metadata
    )

    emit_proposal_complete_event(result)
    result
  end
end