Use honest NumPy-first vector backends

[CoreyLeath-code]

Summary

• Make NumPy/BLAS the default cosine-similarity backend.
• Keep the C++ ctypes path opt-in for safe FFI/interop demonstration only.
• Retain pure Python as the NumPy-unavailable degradation path.
• Add a reproducible three-way benchmark that writes measurements at execution time without checked-in result values.
• Replace unsupported C++ speed/acceleration language with evidence-bound documentation and placeholders.

Safety and compatibility

• Preserves cosine_sim(left, right) as the compatibility facade.
• C++ inputs are coerced to contiguous float64 buffers before pointer passing; unequal dimensions raise ValueError, and uncoercible inputs raise TypeError.
• No performance result is asserted or hardcoded.

Validation

• Known-case tests cover NumPy, C++, and Python implementations.
• Deterministic cross-backend agreement, C++ coercion, dispatch, and vector-benchmark contract tests are included.
• Green: Lint & Test Engine, HelixAgent Enterprise CI, and HelixAgent Security & Supply Chain.

Summary by CodeRabbit

• New Features

  • Added NumPy-based vector operations as the default, with optional C++ interoperability and a pure-Python fallback.
  • Added explicit vector backend selection through configuration or function arguments.
  • Added reproducible vector-operation benchmarks with timing metrics and JSON output.

• Documentation

  • Updated architecture, capability, and performance documentation to reflect backend behavior and evidence-based claims.

• Bug Fixes

  • Improved vector validation, input handling, and error reporting for unavailable native acceleration.

• Tests

  • Added coverage for backend agreement, validation, fallback behavior, and benchmark reporting.

[coderabbitai]

Caution

Review failed

The pull request is closed.

ℹ️ Recent review info

⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

Plan: Pro Plus

Run ID: 95bfaa3c-a97c-4e37-86e7-21a9c86b9f1a

📥 Commits

Reviewing files that changed from the base of the PR and between a98b4ce and 683b609.

📒 Files selected for processing (11)

• README.md
• agent/agent_core.py
• benchmarks/vector_ops.py
• docs/CLAIMS_MATRIX.md
• docs/architecture.md
• docs/metrics.md
• requirements.txt
• streamlit_app.py
• tests/test_benchmark.py
• tests/test_runtime_invariants.py
• tests/test_vector_backends.py

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📝 Walkthrough

Walkthrough

The runtime now supports NumPy, optional C++ ctypes, and pure-Python cosine-similarity backends. Backend selection is explicit or environment-driven. A deterministic benchmark and evidence-bound architecture documentation were added.

Changes

Vector backend system

Layer / File(s)	Summary
Backend contracts, implementations, and validation agent/agent_core.py, requirements.txt, tests/test_vector_backends.py, tests/test_runtime_invariants.py, streamlit_app.py	The runtime adds NumPy, C++, and pure-Python cosine implementations. The compatibility facade selects NumPy by default, C++ only when requested, and Python when NumPy is unavailable. Tests cover validation, ctypes buffers, backend selection, and numerical invariants.
Deterministic vector benchmark benchmarks/vector_ops.py, tests/test_benchmark.py	The benchmark measures available backends with deterministic vectors, warmups, repetitions, percentile timings, metadata, Markdown output, and JSON output.
Architecture and evidence documentation README.md, docs/CLAIMS_MATRIX.md, docs/architecture.md, docs/metrics.md	Documentation describes the Python runtime, NumPy-default vector operations, optional C++ ctypes interop, pure-Python fallback, and reproducible local benchmark scope.

Estimated code review effort: 4 (Complex) | ~45 minutes

Sequence Diagram(s)

sequenceDiagram
  participant Caller
  participant cosine_sim
  participant NumPyBackend
  participant CppBackend
  participant PythonBackend
  Caller->>cosine_sim: request cosine similarity with backend
  alt NumPy selected or available by default
    cosine_sim->>NumPyBackend: validate and calculate
  else C++ explicitly selected
    cosine_sim->>CppBackend: coerce buffers and calculate through ctypes
  else NumPy unavailable
    cosine_sim->>PythonBackend: validate and calculate
  end

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Possibly related PRs

• CoreyLeath-code/HelixAgent#19: Added the Streamlit vector-similarity lab that uses cosine_sim.
• CoreyLeath-code/HelixAgent#27: Established the earlier cosine_sim backend facade extended here with explicit dispatch.
• CoreyLeath-code/HelixAgent#38: Covered related cosine-similarity backend behavior and Python fallback invariants.

✨ Finishing Touches

📝 Generate docstrings

• Create stacked PR
• Commit on current branch

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch agent/honest-vector-backends

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