e8f3bbcb35
Rewrite all reference files, asset templates, and SKILL.md to use current API patterns (.call(), result.field, T::Enum classes, Tools::Base). Add two new reference files (toolsets, observability) covering tools DSL, event system, and Langfuse integration. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
188 lines
6.7 KiB
Ruby
188 lines
6.7 KiB
Ruby
# frozen_string_literal: true
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# =============================================================================
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# DSPy.rb Configuration Template — v0.34.3 API
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#
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# Rails initializer patterns for DSPy.rb with RubyLLM, observability,
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# and feature-flagged model selection.
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#
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# Key patterns:
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# - Use after_initialize for Rails setup
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# - Use dspy-ruby_llm for multi-provider routing
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# - Use structured_outputs: true for reliable parsing
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# - Use dspy-o11y + dspy-o11y-langfuse for observability
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# - Use ENV-based feature flags for model selection
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# =============================================================================
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# =============================================================================
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# Gemfile Dependencies
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# =============================================================================
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#
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# # Core
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# gem 'dspy'
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#
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# # Provider adapter (choose one strategy):
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#
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# # Strategy A: Unified adapter via RubyLLM (recommended)
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# gem 'dspy-ruby_llm'
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# gem 'ruby_llm'
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#
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# # Strategy B: Per-provider adapters (direct SDK access)
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# gem 'dspy-openai' # OpenAI, OpenRouter, Ollama
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# gem 'dspy-anthropic' # Claude
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# gem 'dspy-gemini' # Gemini
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#
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# # Observability (optional)
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# gem 'dspy-o11y'
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# gem 'dspy-o11y-langfuse'
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#
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# # Optimization (optional)
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# gem 'dspy-miprov2' # MIPROv2 optimizer
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# gem 'dspy-gepa' # GEPA optimizer
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#
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# # Schema formats (optional)
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# gem 'sorbet-baml' # BAML schema format (84% token reduction)
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# =============================================================================
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# Rails Initializer — config/initializers/dspy.rb
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# =============================================================================
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Rails.application.config.after_initialize do
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# Skip in test unless explicitly enabled
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next if Rails.env.test? && ENV["DSPY_ENABLE_IN_TEST"].blank?
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# Configure RubyLLM provider credentials
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RubyLLM.configure do |config|
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config.gemini_api_key = ENV["GEMINI_API_KEY"] if ENV["GEMINI_API_KEY"].present?
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config.anthropic_api_key = ENV["ANTHROPIC_API_KEY"] if ENV["ANTHROPIC_API_KEY"].present?
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config.openai_api_key = ENV["OPENAI_API_KEY"] if ENV["OPENAI_API_KEY"].present?
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end
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# Configure DSPy with unified RubyLLM adapter
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model = ENV.fetch("DSPY_MODEL", "ruby_llm/gemini-2.5-flash")
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DSPy.configure do |config|
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config.lm = DSPy::LM.new(model, structured_outputs: true)
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config.logger = Rails.logger
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end
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# Enable Langfuse observability (optional)
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if ENV["LANGFUSE_PUBLIC_KEY"].present? && ENV["LANGFUSE_SECRET_KEY"].present?
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DSPy::Observability.configure!
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end
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end
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# =============================================================================
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# Feature Flags — config/initializers/feature_flags.rb
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# =============================================================================
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# Use different models for different roles:
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# - Fast/cheap for classification, routing, simple tasks
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# - Powerful for synthesis, reasoning, complex analysis
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module FeatureFlags
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SELECTOR_MODEL = ENV.fetch("DSPY_SELECTOR_MODEL", "ruby_llm/gemini-2.5-flash-lite")
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SYNTHESIZER_MODEL = ENV.fetch("DSPY_SYNTHESIZER_MODEL", "ruby_llm/gemini-2.5-flash")
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REASONING_MODEL = ENV.fetch("DSPY_REASONING_MODEL", "ruby_llm/claude-sonnet-4-20250514")
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end
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# Usage in tools/modules:
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#
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# class ClassifyTool < DSPy::Tools::Base
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# def call(query:)
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# predictor = DSPy::Predict.new(ClassifySignature)
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# predictor.configure { |c| c.lm = DSPy::LM.new(FeatureFlags::SELECTOR_MODEL, structured_outputs: true) }
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# predictor.call(query: query)
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# end
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# end
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# =============================================================================
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# Environment Variables — .env
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# =============================================================================
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#
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# # Provider API keys (set the ones you need)
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# GEMINI_API_KEY=...
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# ANTHROPIC_API_KEY=...
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# OPENAI_API_KEY=...
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#
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# # DSPy model configuration
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# DSPY_MODEL=ruby_llm/gemini-2.5-flash
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# DSPY_SELECTOR_MODEL=ruby_llm/gemini-2.5-flash-lite
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# DSPY_SYNTHESIZER_MODEL=ruby_llm/gemini-2.5-flash
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# DSPY_REASONING_MODEL=ruby_llm/claude-sonnet-4-20250514
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#
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# # Langfuse observability (optional)
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# LANGFUSE_PUBLIC_KEY=pk-...
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# LANGFUSE_SECRET_KEY=sk-...
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# DSPY_TELEMETRY_BATCH_SIZE=5
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#
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# # Test environment
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# DSPY_ENABLE_IN_TEST=1 # Set to enable DSPy in test env
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# =============================================================================
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# Per-Provider Configuration (without RubyLLM)
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# =============================================================================
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# OpenAI (dspy-openai gem)
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# DSPy.configure do |c|
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# c.lm = DSPy::LM.new('openai/gpt-4o-mini', api_key: ENV['OPENAI_API_KEY'])
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# end
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# Anthropic (dspy-anthropic gem)
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# DSPy.configure do |c|
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# c.lm = DSPy::LM.new('anthropic/claude-sonnet-4-20250514', api_key: ENV['ANTHROPIC_API_KEY'])
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# end
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# Gemini (dspy-gemini gem)
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# DSPy.configure do |c|
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# c.lm = DSPy::LM.new('gemini/gemini-2.5-flash', api_key: ENV['GEMINI_API_KEY'])
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# end
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# Ollama (dspy-openai gem, local models)
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# DSPy.configure do |c|
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# c.lm = DSPy::LM.new('ollama/llama3.2', base_url: 'http://localhost:11434')
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# end
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# OpenRouter (dspy-openai gem, 200+ models)
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# DSPy.configure do |c|
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# c.lm = DSPy::LM.new('openrouter/anthropic/claude-3.5-sonnet',
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# api_key: ENV['OPENROUTER_API_KEY'],
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# base_url: 'https://openrouter.ai/api/v1')
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# end
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# =============================================================================
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# VCR Test Configuration — spec/support/dspy.rb
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# =============================================================================
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# VCR.configure do |config|
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# config.cassette_library_dir = "spec/vcr_cassettes"
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# config.hook_into :webmock
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# config.configure_rspec_metadata!
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# config.filter_sensitive_data('<GEMINI_API_KEY>') { ENV['GEMINI_API_KEY'] }
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# config.filter_sensitive_data('<OPENAI_API_KEY>') { ENV['OPENAI_API_KEY'] }
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# config.filter_sensitive_data('<ANTHROPIC_API_KEY>') { ENV['ANTHROPIC_API_KEY'] }
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# end
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# =============================================================================
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# Schema Format Configuration (optional)
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# =============================================================================
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# BAML schema format — 84% token reduction for Enhanced Prompting mode
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# DSPy.configure do |c|
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# c.lm = DSPy::LM.new('openai/gpt-4o-mini',
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# api_key: ENV['OPENAI_API_KEY'],
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# schema_format: :baml # Requires sorbet-baml gem
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# )
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# end
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# TOON schema + data format — table-oriented format
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# DSPy.configure do |c|
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# c.lm = DSPy::LM.new('openai/gpt-4o-mini',
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# api_key: ENV['OPENAI_API_KEY'],
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# schema_format: :toon, # How DSPy describes the signature
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# data_format: :toon # How inputs/outputs are rendered in prompts
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# )
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# end
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#
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# Note: BAML and TOON apply only when structured_outputs: false.
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# With structured_outputs: true, the provider receives JSON Schema directly.
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