Test branch

[nvidiacbrissette]

Description

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• I am familiar with the Contributing Guidelines.
• Testing
  • New or existing tests cover these changes
  • Added tests
  • Created an issue to follow-up
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• Documentation
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  • Added new documentation
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ℹ️ Recent review info

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Run ID: fd4ff1bb-bf11-441d-bbe3-74f81700cfe3

📥 Commits

Reviewing files that changed from the base of the PR and between d531ad1 and c3d76aa.

📒 Files selected for processing (39)

• .brev/setup.sh
• AGENTS.md
• CUOPT-OPT-AGENT.md
• benchmarks/a1000_mip_bench.py
• cpp/src/mip_heuristics/feasibility_jump/feasibility_jump.cuh
• cuoptopt-agent/README.md
• cuoptopt-agent/config/models.yaml
• cuoptopt-agent/config/thresholds.yaml
• cuoptopt-agent/cuoptopt_agent/__init__.py
• cuoptopt-agent/cuoptopt_agent/git_utils.py
• cuoptopt-agent/cuoptopt_agent/implementation.py
• cuoptopt-agent/cuoptopt_agent/main.py
• cuoptopt-agent/cuoptopt_agent/models.py
• cuoptopt-agent/cuoptopt_agent/orchestrator.py
• cuoptopt-agent/cuoptopt_agent/research.py
• cuoptopt-agent/cuoptopt_agent/skill_loader.py
• cuoptopt-agent/cuoptopt_agent/testing.py
• cuoptopt-agent/dashboard/__init__.py
• cuoptopt-agent/dashboard/db.py
• cuoptopt-agent/dashboard/server.py
• cuoptopt-agent/dashboard/static/app.js
• cuoptopt-agent/dashboard/static/index.html
• cuoptopt-agent/dashboard/static/style.css
• cuoptopt-agent/pyproject.toml
• cuoptopt-agent/requirements.txt
• cuoptopt-agent/skills/benchmarking-methodology/SKILL.md
• cuoptopt-agent/skills/cuda-optimization/SKILL.md
• cuoptopt-agent/skills/gpu-profiling/SKILL.md
• cuoptopt-agent/skills/mip-algorithms/SKILL.md
• cuoptopt-agent/skills/nvidia-a100-architecture/SKILL.md
• cuoptopt-agent/skills/nvidia-a1000-architecture/SKILL.md
• cuoptopt-agent/skills/nvidia-blackwell-architecture/SKILL.md
• cuoptopt-agent/skills/nvidia-h100-architecture/SKILL.md
• cuoptopt-agent/skills/nvidia-l40-architecture/SKILL.md
• cuoptopt-agent/skills/presolvers/SKILL.md
• cuoptopt-agent/skills/research-literature/SKILL.md
• debug_env_check.py
• skills/cuoptopt-agent/SKILL.md
• skills/cuoptopt-agent/cuoptopt-agent/SKILL.md

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📝 Walkthrough

Walkthrough

Introduces cuoptopt-agent, an autonomous optimization system for NVIDIA cuOpt that automates code improvements via literature search, LLM-driven diff generation, benchmarking, regression analysis, and PR creation. Includes CLI and web-based dashboard interfaces, multi-backend LLM support (Claude, GPT-4o, NVIDIA NIM), skill-based context injection, and comprehensive documentation across architecture guides and algorithm skill modules.

Changes

Cohort / File(s)	Summary
Agent Orchestration & Core Logic cuoptopt-agent/cuoptopt_agent/orchestrator.py, cuoptopt-agent/cuoptopt_agent/implementation.py, cuoptopt-agent/cuoptopt_agent/main.py	Implements end-to-end optimization workflow: orchestrator manages iteration loop with skill loading, literature search, code generation, benchmarking, and regression checks; implementation module applies LLM-generated diffs with rollback on failure; main provides Typer CLI entry point with model selection and configuration validation.
LLM & Backend Integration cuoptopt-agent/cuoptopt_agent/models.py	Unified multi-backend LLM client supporting Anthropic (Claude), OpenAI (GPT-4o), and NVIDIA NIM with configuration-driven model selection, environment-based API key validation, and provider-specific request/response handling.
Git & GitHub Workflow cuoptopt-agent/cuoptopt_agent/git_utils.py	Public functions for branch naming (inferred from query keywords), change staging/committing, metrics persistence, and pull request creation via GitHub API; includes repo slug parsing and PR body templating with benchmark results.
Benchmarking & Regression Detection cuoptopt-agent/cuoptopt_agent/testing.py, benchmarks/a1000_mip_bench.py	Benchmark runner discovers dataset instances, executes warmup and timed solver runs, computes geometric-mean speed deltas and per-instance quality deltas; a1000 script provides before/after benchmarking for MIP kernel with JSON result comparison and 5% regression threshold.
Research & Literature cuoptopt-agent/cuoptopt_agent/research.py	Literature search via Google Scholar and arXiv with threaded parallel execution, deduplication by title, and ranked output; includes formatter for prompt injection.
Skill Discovery & Matching cuoptopt-agent/cuoptopt_agent/skill_loader.py	TF-IDF-based skill matcher discovers .md files from cuoptopt-agent/skills and skills directories, ranks by query relevance, and formats results for LLM prompt context.
Dashboard Server & Persistence cuoptopt-agent/dashboard/server.py, cuoptopt-agent/dashboard/db.py	FastAPI server with WebSocket-based real-time orchestrator output streaming, session management, REST endpoints for history and branch/metrics listing; SQLite backend for message persistence and session tracking.
Dashboard Client UI cuoptopt-agent/dashboard/static/app.js, cuoptopt-agent/dashboard/static/index.html, cuoptopt-agent/dashboard/static/style.css	Single-page app with chat interface, branch explorer, performance visualization via Plotly, WebSocket auto-reconnect, session persistence, and mobile-responsive sidebar.
Configuration & Package Setup cuoptopt-agent/pyproject.toml, cuoptopt-agent/requirements.txt, cuoptopt-agent/config/models.yaml, cuoptopt-agent/config/thresholds.yaml, cuoptopt-agent/README.md	Package metadata, dependency declarations, LLM backend configurations, regression thresholds (speed/quality tolerances, max iterations, benchmark controls), and comprehensive agent usage guide.
Skills Documentation cuoptopt-agent/skills/.../*.md, skills/cuoptopt-agent/.../*.md	Domain knowledge modules covering GPU profiling, CUDA optimization, MIP algorithms, presolvers, benchmarking methodology, GPU architecture guides (A100, A1000, H100, L40, Blackwell), and research literature patterns; auto-discovered and injected into LLM context.
Setup & Configuration Documentation .brev/setup.sh, AGENTS.md, CUOPT-OPT-AGENT.md, cuoptopt-agent/cuoptopt_agent/__init__.py, debug_env_check.py	Deployment setup script with venv creation, LD_PRELOAD management, and .env initialization; documentation updates; package version declaration; diagnostic environment checker.
Kernel Parameter Tuning cpp/src/mip_heuristics/feasibility_jump/feasibility_jump.cuh	Reduced block sizes and tuning thresholds for A1000 GPU occupancy and bandwidth management: TPB_heavyvars (256→128), max_sampled_moves (256→64), load_balancing_codepath_min_varcount (3200→800).

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[nvidiacbrissette]

Was meant to be on my fork, not here.