Update repository to reflect current state

[tylerbessire]

Summary

• What changed?
• Why?

Testing

• Steps
• Results

Risk Assessment

• Regressions considered
• Rollback plan

[S:PR v1] template=installed pass

Summary by CodeRabbit

• New Features

  • Frequency Ledger System for pattern analysis and relational reasoning.
  • Three new feature extraction functions: extract_task_features(), compute_task_signature(), and compute_numerical_features().
  • Expanded public API with load_rerun_json() and save_submission() utilities.
  • Lazy import mechanism for RFT submodule.

• Documentation

  • Comprehensive README updates emphasizing cognitive architecture and behavioral principles.
  • Enhanced profile documentation with expanded RFT foundation sections.

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[coderabbitai]

Caution

Review failed

The pull request is closed.

Walkthrough

This PR introduces the Frequency Ledger System as a core PUMA component for behavioral pattern analysis, adds three new feature extraction functions, implements lazy import logic for the RFT module, and expands documentation across multiple files to emphasize cognitive-science and Relational Frame Theory foundations.

Changes

Cohort / File(s)	Summary
Documentation Updates README.md, profile/README.md, arc_solver/behavioral_engine.py, arc_solver/rft.py, arc_solver/solver.py	Expanded module and file docstrings to detail PUMA's RFT-based cognitive architecture, Frequency Ledger System, and behavioral principles; updated design annotations; replaced neural-symbolic framing with cognitive-science terminology.
Public API Expansion arc_solver/__init__.py	Added public exports for load_rerun_json, save_submission, and Array via __all__; introduced corresponding imports from io_utils and grid modules.
Feature Extraction Implementation arc_solver/features.py	Added three new public functions: extract_task_features(), compute_task_signature(), and compute_numerical_features(); reworked module docstring to describe frequency-based feature extraction and derivational reasoning workflows.
Frequency Ledger System arc_solver/frequency_ledger.py	New module implementing FrequencySignature and FrequencyLedger dataclasses with methods for observation tracking, abstract grouping discovery, relational pattern derivation, and frequency-guided operation ranking; includes analyze_frequency_patterns() and frequency_guided_search() utility functions.
Lazy Import Mechanism puma/__init__.py	Introduced __getattr__() function to enable lazy dynamic import of puma.rft module; expanded module docstring with extended PUMA narrative; maintained __all__ = ["rft"].

Sequence Diagram

sequenceDiagram
    participant App as Application
    participant Features as features.py
    participant Ledger as FrequencyLedger
    participant RFT as RFT Engine
    
    App->>Features: extract_task_features(train_pairs)
    Features->>Ledger: analyze_frequency_patterns(train_pairs)
    Ledger->>Ledger: add_observation() for each pair
    Ledger->>Ledger: discover_abstract_groupings()
    Ledger->>Ledger: derive_relational_patterns()
    Ledger-->>Features: FrequencyLedger with insights
    Features->>Features: compute_task_signature()
    Features->>Features: compute_numerical_features()
    Features-->>App: Dict with features, signature, vectors
    
    App->>RFT: Use frequency insights for relational reasoning
    RFT->>Ledger: frequency_guided_search(operations)
    Ledger-->>RFT: Ranked operations by relevance

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Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~25–30 minutes

• Frequency Ledger System (arc_solver/frequency_ledger.py): New module with two dataclasses, similarity scoring logic, clustering/grouping algorithms, and relational pattern derivation—requires verification of correctness and integration points.
• Feature Extraction Functions (arc_solver/features.py): Three new public functions with numerical analysis, transformation inference, and signature computation—needs validation of feature semantics and consistency with Frequency Ledger usage.
• Integration & Dependencies: Cross-file dependencies between features.py and frequency_ledger.py should be checked for correctness.
• Lazy Import Logic (puma/__init__.py): Simple dynamic import via __getattr__; verify that lazy loading works as intended and doesn't break existing imports.

Possibly related PRs

• docs: add RFT behavioral profile and image #18 — Both PRs modify Behavioral RFT documentation in README.md and profile/README.md, expanding narrative content around PUMA's architecture and RFT integration.
• V2 #25 — Both PRs modify puma/__init__.py to implement lazy/exported logic for puma.rft via __all__ and dynamic imports.

Suggested labels

codex

Poem

🐰 A Frequency Whisper
Ledgers keep the pattern's song,
Where relational frames belong—
Grouped by color, size, and place,
Behavioral wisdom finds its grace,
Cognitive architecture blooms anew,
Ledger lights the way through!

✨ Finishing touches

• 📝 Generate docstrings

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Post copyable unit tests in a comment
• Commit unit tests in branch claude/update-repo-reflect-01VSHej1dDQAETtvTTUAWeJU

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📜 Recent review details

Configuration used: CodeRabbit UI

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 3ebf9e3 and b8602a8.

📒 Files selected for processing (9)

• README.md (3 hunks)
• arc_solver/__init__.py (1 hunks)
• arc_solver/behavioral_engine.py (1 hunks)
• arc_solver/features.py (1 hunks)
• arc_solver/frequency_ledger.py (1 hunks)
• arc_solver/rft.py (1 hunks)
• arc_solver/solver.py (1 hunks)
• profile/README.md (1 hunks)
• puma/__init__.py (1 hunks)

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