Major rewrite based on deep study of Karpathy's autoresearch repo.
Architecture changes:
- Multi-experiment support: .autoresearch/{domain}/{name}/ structure
- Domain categories: engineering, marketing, content, prompts, custom
- Project-level (git-tracked, shareable) or user-level (~/.autoresearch/) scope
- User chooses scope during setup, not installation
New evaluators (8 ready-to-use):
- Free: benchmark_speed, benchmark_size, test_pass_rate, build_speed, memory_usage
- LLM judge (uses existing subscription): llm_judge_content, llm_judge_prompt, llm_judge_copy
- LLM judges call user's CLI tool (claude/codex/gemini) — no extra API keys needed
Script improvements:
- setup_experiment.py: --domain, --scope, --evaluator, --list, --list-evaluators
- run_experiment.py: --experiment domain/name, --resume, --loop, --single
- log_results.py: --dashboard, --domain, --format csv|markdown|terminal, --output
Results export:
- Terminal (default), CSV, and Markdown formats
- Per-experiment, per-domain, or cross-experiment dashboard view
SKILL.md rewritten:
- Clear activation triggers (when the skill should activate)
- Practical examples for each domain
- Evaluator documentation with cost transparency
- Simplified loop protocol matching Karpathy's original philosophy
370 lines
14 KiB
Python
370 lines
14 KiB
Python
#!/usr/bin/env python3
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"""
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autoresearch-agent: Setup Experiment
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Initialize a new experiment with domain, target, evaluator, and git branch.
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Creates the .autoresearch/{domain}/{name}/ directory structure.
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Usage:
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python scripts/setup_experiment.py --domain engineering --name api-speed \
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--target src/api/search.py --eval "pytest bench.py" \
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--metric p50_ms --direction lower
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python scripts/setup_experiment.py --domain marketing --name medium-ctr \
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--target content/titles.md --eval "python evaluate.py" \
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--metric ctr_score --direction higher --evaluator llm_judge_content
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python scripts/setup_experiment.py --list # List all experiments
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python scripts/setup_experiment.py --list-evaluators # List available evaluators
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"""
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import argparse
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import os
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import shutil
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import subprocess
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import sys
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import time
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from datetime import datetime
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from pathlib import Path
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DOMAINS = ["engineering", "marketing", "content", "prompts", "custom"]
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EVALUATOR_DIR = Path(__file__).parent.parent / "evaluators"
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DEFAULT_CONFIG = """# autoresearch global config
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default_time_budget_minutes: 5
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default_scope: project
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dashboard_format: markdown
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"""
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GITIGNORE_CONTENT = """# autoresearch — experiment logs are local state
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**/results.tsv
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**/run.log
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**/run.*.log
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config.yaml
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"""
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def run_cmd(cmd, cwd=None, timeout=None):
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"""Run shell command, return (returncode, stdout, stderr)."""
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result = subprocess.run(
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cmd, shell=True, capture_output=True, text=True,
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cwd=cwd, timeout=timeout
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)
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return result.returncode, result.stdout.strip(), result.stderr.strip()
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def get_autoresearch_root(scope, project_root=None):
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"""Get the .autoresearch root directory based on scope."""
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if scope == "user":
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return Path.home() / ".autoresearch"
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return Path(project_root or ".") / ".autoresearch"
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def init_root(root):
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"""Initialize .autoresearch root if it doesn't exist."""
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created = False
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if not root.exists():
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root.mkdir(parents=True)
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created = True
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print(f" Created {root}/")
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config_file = root / "config.yaml"
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if not config_file.exists():
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config_file.write_text(DEFAULT_CONFIG)
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print(f" Created {config_file}")
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gitignore = root / ".gitignore"
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if not gitignore.exists():
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gitignore.write_text(GITIGNORE_CONTENT)
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print(f" Created {gitignore}")
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return created
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def create_program_md(experiment_dir, domain, name, target, metric, direction, constraints=""):
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"""Generate a program.md template for the experiment."""
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direction_word = "Minimize" if direction == "lower" else "Maximize"
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content = f"""# autoresearch — {name}
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## Goal
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{direction_word} `{metric}` on `{target}`. {"Lower" if direction == "lower" else "Higher"} is better.
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## What the Agent Can Change
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- Only `{target}` — this is the single file being optimized.
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- Everything inside that file is fair game unless constrained below.
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## What the Agent Cannot Change
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- The evaluation script (`evaluate.py` or the eval command). It is read-only.
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- Dependencies — do not add new packages or imports that aren't already available.
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- Any other files in the project unless explicitly noted here.
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{f"- Additional constraints: {constraints}" if constraints else ""}
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## Strategy
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1. First run: establish baseline. Do not change anything.
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2. Profile/analyze the current state — understand why the metric is what it is.
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3. Try the most obvious improvement first (low-hanging fruit).
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4. If that works, push further in the same direction.
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5. If stuck, try something orthogonal or radical.
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6. Read the git log of previous experiments. Don't repeat failed approaches.
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## Simplicity Rule
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A small improvement that adds ugly complexity is NOT worth it.
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Equal performance with simpler code IS worth it.
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Removing code that gets same results is the best outcome.
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## Stop When
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You don't stop. The human will interrupt you when they're satisfied.
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If no improvement in 20+ consecutive runs, change strategy drastically.
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"""
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(experiment_dir / "program.md").write_text(content)
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def create_config(experiment_dir, target, eval_cmd, metric, direction, time_budget):
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"""Write experiment config."""
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content = f"""target: {target}
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evaluate_cmd: {eval_cmd}
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metric: {metric}
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metric_direction: {direction}
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metric_grep: ^{metric}:
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time_budget_minutes: {time_budget}
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created: {datetime.now().strftime('%Y-%m-%d %H:%M')}
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"""
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(experiment_dir / "config.cfg").write_text(content)
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def init_results_tsv(experiment_dir):
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"""Create results.tsv with header."""
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tsv = experiment_dir / "results.tsv"
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if tsv.exists():
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print(f" results.tsv already exists ({tsv.stat().st_size} bytes)")
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return
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tsv.write_text("commit\tmetric\tstatus\tdescription\n")
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print(" Created results.tsv")
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def copy_evaluator(experiment_dir, evaluator_name):
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"""Copy a built-in evaluator to the experiment directory."""
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source = EVALUATOR_DIR / f"{evaluator_name}.py"
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if not source.exists():
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print(f" Warning: evaluator '{evaluator_name}' not found in {EVALUATOR_DIR}")
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print(f" Available: {', '.join(f.stem for f in EVALUATOR_DIR.glob('*.py'))}")
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return False
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dest = experiment_dir / "evaluate.py"
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shutil.copy2(source, dest)
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print(f" Copied evaluator: {evaluator_name}.py -> evaluate.py")
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return True
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def create_branch(path, domain, name):
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"""Create and checkout the experiment branch."""
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branch = f"autoresearch/{domain}/{name}"
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code, _, err = run_cmd(f"git checkout -b {branch}", cwd=path)
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if code != 0:
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if "already exists" in err:
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print(f" Branch '{branch}' already exists. Checking out...")
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run_cmd(f"git checkout {branch}", cwd=path)
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return branch
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print(f" Warning: could not create branch: {err}")
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return None
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print(f" Created branch: {branch}")
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return branch
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def list_experiments(root):
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"""List all experiments across all domains."""
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if not root.exists():
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print("No experiments found. Run setup to create your first experiment.")
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return
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experiments = []
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for domain_dir in sorted(root.iterdir()):
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if not domain_dir.is_dir() or domain_dir.name.startswith("."):
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continue
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for exp_dir in sorted(domain_dir.iterdir()):
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if not exp_dir.is_dir():
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continue
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cfg_file = exp_dir / "config.cfg"
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if not cfg_file.exists():
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continue
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config = {}
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for line in cfg_file.read_text().splitlines():
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if ":" in line:
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k, v = line.split(":", 1)
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config[k.strip()] = v.strip()
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# Count results
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tsv = exp_dir / "results.tsv"
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runs = 0
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if tsv.exists():
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runs = max(0, len(tsv.read_text().splitlines()) - 1)
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experiments.append({
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"domain": domain_dir.name,
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"name": exp_dir.name,
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"target": config.get("target", "?"),
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"metric": config.get("metric", "?"),
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"runs": runs,
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})
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if not experiments:
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print("No experiments found.")
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return
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print(f"\n{'DOMAIN':<15} {'EXPERIMENT':<25} {'TARGET':<30} {'METRIC':<15} {'RUNS':>5}")
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print("-" * 95)
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for e in experiments:
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print(f"{e['domain']:<15} {e['name']:<25} {e['target']:<30} {e['metric']:<15} {e['runs']:>5}")
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print(f"\nTotal: {len(experiments)} experiments")
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def list_evaluators():
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"""List available built-in evaluators."""
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if not EVALUATOR_DIR.exists():
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print("No evaluators directory found.")
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return
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print(f"\nAvailable evaluators ({EVALUATOR_DIR}):\n")
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for f in sorted(EVALUATOR_DIR.glob("*.py")):
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# Read first docstring line
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desc = ""
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for line in f.read_text().splitlines():
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if line.strip().startswith('"""') or line.strip().startswith("'''"):
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continue
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if line.strip() and not line.startswith("#!"):
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desc = line.strip().strip('"').strip("'")
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break
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print(f" {f.stem:<25} {desc}")
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def main():
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parser = argparse.ArgumentParser(description="autoresearch-agent setup")
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parser.add_argument("--domain", choices=DOMAINS, help="Experiment domain")
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parser.add_argument("--name", help="Experiment name (e.g. api-speed, medium-ctr)")
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parser.add_argument("--target", help="Target file to optimize")
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parser.add_argument("--eval", dest="eval_cmd", help="Evaluation command")
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parser.add_argument("--metric", help="Metric name (must appear in eval output as 'name: value')")
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parser.add_argument("--direction", choices=["lower", "higher"], default="lower",
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help="Is lower or higher better?")
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parser.add_argument("--time-budget", type=int, default=5, help="Minutes per experiment (default: 5)")
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parser.add_argument("--evaluator", help="Built-in evaluator to copy (e.g. benchmark_speed)")
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parser.add_argument("--scope", choices=["project", "user"], default="project",
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help="Where to store experiments: project (./) or user (~/)")
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parser.add_argument("--constraints", default="", help="Additional constraints for program.md")
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parser.add_argument("--path", default=".", help="Project root path")
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parser.add_argument("--skip-baseline", action="store_true", help="Skip baseline run")
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parser.add_argument("--skip-branch", action="store_true", help="Don't create git branch")
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parser.add_argument("--list", action="store_true", help="List all experiments")
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parser.add_argument("--list-evaluators", action="store_true", help="List available evaluators")
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args = parser.parse_args()
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project_root = Path(args.path).resolve()
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# List mode
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if args.list:
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root = get_autoresearch_root("project", project_root)
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list_experiments(root)
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user_root = get_autoresearch_root("user")
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if user_root.exists() and user_root != root:
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print(f"\n--- User-level experiments ({user_root}) ---")
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list_experiments(user_root)
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return
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if args.list_evaluators:
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list_evaluators()
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return
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# Validate required args for setup
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if not all([args.domain, args.name, args.target, args.eval_cmd, args.metric]):
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parser.error("Required: --domain, --name, --target, --eval, --metric")
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root = get_autoresearch_root(args.scope, project_root)
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print(f"\n autoresearch-agent setup")
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print(f" Project: {project_root}")
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print(f" Scope: {args.scope}")
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print(f" Domain: {args.domain}")
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print(f" Experiment: {args.name}")
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print(f" Time: {datetime.now().strftime('%Y-%m-%d %H:%M')}\n")
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# Check git
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code, _, _ = run_cmd("git rev-parse --is-inside-work-tree", cwd=str(project_root))
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if code != 0:
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print(" Error: not a git repository. Run: git init && git add . && git commit -m 'initial'")
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sys.exit(1)
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print(" Git repository found")
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# Check target file
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target_path = project_root / args.target
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if not target_path.exists():
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print(f" Error: target file not found: {args.target}")
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sys.exit(1)
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print(f" Target file found: {args.target}")
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# Init root
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init_root(root)
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# Create experiment directory
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experiment_dir = root / args.domain / args.name
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if experiment_dir.exists():
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print(f" Warning: experiment '{args.domain}/{args.name}' already exists.")
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print(f" Use --name with a different name, or delete {experiment_dir}")
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sys.exit(1)
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experiment_dir.mkdir(parents=True)
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print(f" Created {experiment_dir}/")
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# Create files
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create_program_md(experiment_dir, args.domain, args.name,
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args.target, args.metric, args.direction, args.constraints)
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print(" Created program.md")
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create_config(experiment_dir, args.target, args.eval_cmd,
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args.metric, args.direction, args.time_budget)
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print(" Created config.cfg")
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init_results_tsv(experiment_dir)
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# Copy evaluator if specified
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if args.evaluator:
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copy_evaluator(experiment_dir, args.evaluator)
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# Create git branch
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if not args.skip_branch:
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create_branch(str(project_root), args.domain, args.name)
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# Test evaluation command
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print(f"\n Testing evaluation: {args.eval_cmd}")
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code, out, err = run_cmd(args.eval_cmd, cwd=str(project_root), timeout=60)
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if code != 0:
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print(f" Warning: eval command failed (exit {code})")
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if err:
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print(f" stderr: {err[:200]}")
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print(" Fix the eval command before running the experiment loop.")
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else:
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# Check metric is parseable
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full_output = out + "\n" + err
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metric_found = False
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for line in full_output.splitlines():
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if line.strip().startswith(f"{args.metric}:"):
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metric_found = True
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print(f" Eval works. Baseline: {line.strip()}")
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break
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if not metric_found:
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print(f" Warning: eval ran but '{args.metric}:' not found in output.")
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print(f" Make sure your eval command outputs: {args.metric}: <value>")
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# Summary
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print(f"\n Setup complete!")
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print(f" Experiment: {args.domain}/{args.name}")
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print(f" Target: {args.target}")
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print(f" Metric: {args.metric} ({args.direction} is better)")
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print(f" Budget: {args.time_budget} min/experiment")
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if not args.skip_branch:
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print(f" Branch: autoresearch/{args.domain}/{args.name}")
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print(f"\n To start:")
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print(f" python scripts/run_experiment.py --experiment {args.domain}/{args.name} --loop")
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if __name__ == "__main__":
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main()
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