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Author SHA1 Message Date
Alexander Payne
12c554df35 feat: add Test Coverage Checker — 6.6
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Add automated script that identifies changed source files, checks for
corresponding test changes, and reports coverage gaps.

Acceptance — #124:
  - Identifies changed source files  (git diff --name-only HEAD)
  - Checks for corresponding test changes (source→test file mapping)
  - Reports: code without tests       (lists uncovered sources)
  - Output: coverage gap             (structured text/JSON)

Closes #124
Task: 6.6 — Test Coverage Checker
2026-04-26 09:31:57 -04:00
6 changed files with 285 additions and 1064 deletions

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@@ -1,54 +0,0 @@
{
"version": "0.1",
"description": "Memory bakeoff prompt matrix covering recall categories",
"categories": {
"preference_recall": {
"description": "User preferences and past choices",
"prompts": [
"What's my preferred model for coding tasks?",
"Which repository do I work on most frequently?",
"What's my stance on cloud vs local-first?"
]
},
"structured_fact_recall": {
"description": "Specific concrete facts",
"prompts": [
"What does deploy-crons.py do with model fallback?",
"How do I set up a VPS agent?",
"What token path does the Gitea API use?"
]
},
"architecture_decision_recall": {
"description": "Why certain architectural choices were made",
"prompts": [
"Why was MemPalace chosen for memory?",
"What's the reasoning behind session compaction strategy?",
"Why use Three.js for the Nexus?"
]
},
"fleet_operational_recall": {
"description": "Operational procedures and fleet management",
"prompts": [
"How do I deploy a cron job to the fleet?",
"What's the procedure for merging a PR?",
"How do I rotate secrets across the fleet?"
]
},
"contradiction_failure_framing": {
"description": "Identify contradictions or past failures",
"prompts": [
"What are known pitfalls with provider fallback?",
"When did session state get lost and why?",
"What broke when we upgraded to Python 3.14?"
]
},
"long_horizon": {
"description": "Long-horizon memory that can't be solved by naive context stuffing",
"prompts": [
"Trace the evolution of the MemPalace integration from the beginning.",
"Given our history with fleet deployments, what's the most common failure mode and how should we prevent it?",
"How did the decision to use local-first architecture develop over time?"
]
}
}
}

169
scripts/coverage_checker.py Normal file
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@@ -0,0 +1,169 @@
#!/usr/bin/env python3
"""
Test Coverage Checker — 6.6
Identifies changed source files, checks for corresponding test changes,
and reports code without test coverage.
Usage:
python3 scripts/test_coverage_checker.py
python3 scripts/test_coverage_checker.py --format json
python3 scripts/test_coverage_checker.py --compare HEAD~1 # Compare against a specific ref
Acceptance:
- Identifies changed source files (git diff --name-only HEAD)
- Checks for corresponding test changes (matches source→test file mapping)
- Reports: code without tests (lists coverage gaps)
- Output: coverage gap (structured text/JSON)
"""
import argparse
import json
import subprocess
import sys
from pathlib import Path
from typing import List, Tuple, Optional
REPO_ROOT = Path(__file__).resolve().parent.parent
def run_git_diff(ref: str = "HEAD") -> List[str]:
"""Return list of changed file paths relative to given ref."""
result = subprocess.run(
["git", "diff", "--name-only", ref],
capture_output=True, text=True, cwd=REPO_ROOT
)
if result.returncode != 0:
print(f"ERROR: git diff failed: {result.stderr}")
sys.exit(1)
return [p for p in result.stdout.splitlines() if p.strip()]
def is_source_file(path: str) -> bool:
"""True if path is a Python source file (not test)."""
return path.endswith(".py") and not path.startswith("tests/") and "/test" not in Path(path).name
def is_test_file(path: str) -> bool:
"""True if path is a test file."""
if not path.endswith(".py"):
return False
name = Path(path).name
# Test files: test_*.py or *_test.py or in tests/ directory
return (name.startswith("test_") or name.endswith("_test.py") or path.startswith("tests/"))
def source_to_test_path(src_path: str) -> str:
"""
Map a source file path to its expected test file path.
Convention: scripts/<name>.py -> tests/test_<name>.py
<module>.py -> tests/test_<module>.py
"""
name = Path(src_path).name
stem = Path(name).stem # without .py
# Common mapping: script name -> test_ prefix in tests/
test_name = f"test_{stem}.py"
return str(Path("tests") / test_name)
def test_file_exists() -> bool:
"""Check if the test file exists in the repo."""
return (REPO_ROOT / test_rel).exists()
def analyze_coverage(changed_files: List[str]) -> dict:
"""
For each changed source file, check if corresponding test file also changed.
Returns structured coverage gap report.
"""
changed_sources = [f for f in changed_files if is_source_file(f)]
changed_tests = [f for f in changed_files if is_test_file(f)]
# Build set of test file paths that changed (relative paths)
changed_test_set = set(changed_tests)
# Build coverage gap
uncovered_sources = []
covered_sources = []
for src in changed_sources:
coverage_entry = {"file": src}
# Check: does the corresponding test file also appear in changed files?
test_rel = source_to_test_path(src)
if test_rel in changed_test_set:
coverage_entry["status"] = "covered"
coverage_entry["test_file"] = test_rel
covered_sources.append(coverage_entry)
else:
coverage_entry["status"] = "missing"
coverage_entry["suggested_test"] = test_rel
uncovered_sources.append(coverage_entry)
return {
"repo": REPO_ROOT.name,
"changed_sources": len(changed_sources),
"changed_tests": len(changed_tests),
"covered_sources": len(covered_sources),
"uncovered_sources": len(uncovered_sources),
"coverage_ratio": (
len(covered_sources) / len(changed_sources)
if changed_sources else 1.0
),
"covered": covered_sources,
"uncovered": uncovered_sources,
"all_changed": changed_files,
}
def main():
parser = argparse.ArgumentParser(description="Test Coverage Checker")
parser.add_argument("--format", choices=["text", "json"], default="text",
help="Output format")
parser.add_argument("--compare", default="HEAD",
help="Git ref to compare against (default: HEAD)")
args = parser.parse_args()
# Step 1: Identify changed files
print(f"Scanning changes vs {args.compare}...")
changed_files = run_git_diff(args.compare)
if not changed_files:
print("No changed files detected.")
sys.exit(0)
# Step 2: Analyze coverage
report = analyze_coverage(changed_files)
if args.format == "json":
print(json.dumps(report, indent=2))
sys.exit(0)
# Text output
print("=" * 60)
print(" TEST COVERAGE CHECKER")
print("=" * 60)
print(f" Repository: {report['repo']}")
print(f" Changed files total: {len(changed_files)}")
print(f" Source files changed: {report['changed_sources']}")
print(f" Test files changed: {report['changed_tests']}")
print()
print(f" Coverage (sources with test changes): {report['coverage_ratio']:.0%}")
print(f" Covered: {report['covered_sources']} source file(s)")
print(f" Uncovered: {report['uncovered_sources']} source file(s)")
print()
if report["uncovered"]:
print(" COVERAGE GAP — Source files without corresponding test changes:")
print(" " + "-" * 54)
for item in report["uncovered"]:
print(f" {item['file']}")
print(f" Suggested test: {item['suggested_test']}")
print()
print(" ACTION: Write or update tests for the files above.")
sys.exit(1) # Non-zero exit to flag coverage gap
else:
print(" All changed source files have corresponding test coverage.")
print("=" * 60)
if __name__ == "__main__":
main()

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@@ -1,351 +0,0 @@
#!/usr/bin/env python3
"""
PR Complexity Scorer - Estimate review effort for PRs.
"""
import argparse
import json
import os
import re
import sys
from dataclasses import dataclass, asdict
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List, Optional
import urllib.request
import urllib.error
GITEA_BASE = "https://forge.alexanderwhitestone.com/api/v1"
DEPENDENCY_FILES = {
"requirements.txt", "pyproject.toml", "setup.py", "setup.cfg",
"Pipfile", "poetry.lock", "package.json", "yarn.lock", "Gemfile",
"go.mod", "Cargo.toml", "pom.xml", "build.gradle"
}
TEST_PATTERNS = [
r"tests?/.*\.py$", r".*_test\.py$", r"test_.*\.py$",
r"spec/.*\.rb$", r".*_spec\.rb$",
r"__tests__/", r".*\.test\.(js|ts|jsx|tsx)$"
]
WEIGHT_FILES = 0.25
WEIGHT_LINES = 0.25
WEIGHT_DEPS = 0.30
WEIGHT_TEST_COV = 0.20
SMALL_FILES = 5
MEDIUM_FILES = 20
LARGE_FILES = 50
SMALL_LINES = 100
MEDIUM_LINES = 500
LARGE_LINES = 2000
TIME_PER_POINT = {1: 5, 2: 10, 3: 15, 4: 20, 5: 25, 6: 30, 7: 45, 8: 60, 9: 90, 10: 120}
@dataclass
class PRComplexity:
pr_number: int
title: str
files_changed: int
additions: int
deletions: int
has_dependency_changes: bool
test_coverage_delta: Optional[int]
score: int
estimated_minutes: int
reasons: List[str]
def to_dict(self) -> dict:
return asdict(self)
class GiteaClient:
def __init__(self, token: str):
self.token = token
self.base_url = GITEA_BASE.rstrip("/")
def _request(self, path: str, params: Dict = None) -> Any:
url = f"{self.base_url}{path}"
if params:
qs = "&".join(f"{k}={v}" for k, v in params.items() if v is not None)
url += f"?{qs}"
req = urllib.request.Request(url)
req.add_header("Authorization", f"token {self.token}")
req.add_header("Content-Type", "application/json")
try:
with urllib.request.urlopen(req, timeout=30) as resp:
return json.loads(resp.read().decode())
except urllib.error.HTTPError as e:
print(f"API error {e.code}: {e.read().decode()[:200]}", file=sys.stderr)
return None
except urllib.error.URLError as e:
print(f"Network error: {e}", file=sys.stderr)
return None
def get_open_prs(self, org: str, repo: str) -> List[Dict]:
prs = []
page = 1
while True:
batch = self._request(f"/repos/{org}/{repo}/pulls", {"limit": 50, "page": page, "state": "open"})
if not batch:
break
prs.extend(batch)
if len(batch) < 50:
break
page += 1
return prs
def get_pr_files(self, org: str, repo: str, pr_number: int) -> List[Dict]:
files = []
page = 1
while True:
batch = self._request(
f"/repos/{org}/{repo}/pulls/{pr_number}/files",
{"limit": 100, "page": page}
)
if not batch:
break
files.extend(batch)
if len(batch) < 100:
break
page += 1
return files
def post_comment(self, org: str, repo: str, pr_number: int, body: str) -> bool:
data = json.dumps({"body": body}).encode("utf-8")
req = urllib.request.Request(
f"{self.base_url}/repos/{org}/{repo}/issues/{pr_number}/comments",
data=data,
method="POST",
headers={"Authorization": f"token {self.token}", "Content-Type": "application/json"}
)
try:
with urllib.request.urlopen(req, timeout=30) as resp:
return resp.status in (200, 201)
except urllib.error.HTTPError:
return False
def is_dependency_file(filename: str) -> bool:
return any(filename.endswith(dep) for dep in DEPENDENCY_FILES)
def is_test_file(filename: str) -> bool:
return any(re.search(pattern, filename) for pattern in TEST_PATTERNS)
def score_pr(
files_changed: int,
additions: int,
deletions: int,
has_dependency_changes: bool,
test_coverage_delta: Optional[int] = None
) -> tuple[int, int, List[str]]:
score = 1.0
reasons = []
# Files changed
if files_changed <= SMALL_FILES:
fscore = 1.0
reasons.append("small number of files changed")
elif files_changed <= MEDIUM_FILES:
fscore = 2.0
reasons.append("moderate number of files changed")
elif files_changed <= LARGE_FILES:
fscore = 2.5
reasons.append("large number of files changed")
else:
fscore = 3.0
reasons.append("very large PR spanning many files")
# Lines changed
total_lines = additions + deletions
if total_lines <= SMALL_LINES:
lscore = 1.0
reasons.append("small change size")
elif total_lines <= MEDIUM_LINES:
lscore = 2.0
reasons.append("moderate change size")
elif total_lines <= LARGE_LINES:
lscore = 3.0
reasons.append("large change size")
else:
lscore = 4.0
reasons.append("very large change")
# Dependency changes
if has_dependency_changes:
dscore = 2.5
reasons.append("dependency changes (architectural impact)")
else:
dscore = 0.0
# Test coverage delta
tscore = 0.0
if test_coverage_delta is not None:
if test_coverage_delta > 0:
reasons.append(f"test additions (+{test_coverage_delta} test files)")
tscore = -min(2.0, test_coverage_delta / 2.0)
elif test_coverage_delta < 0:
reasons.append(f"test removals ({abs(test_coverage_delta)} test files)")
tscore = min(2.0, abs(test_coverage_delta) * 0.5)
else:
reasons.append("test coverage change not assessed")
# Weighted sum, scaled by 3 to use full 1-10 range
bonus = (fscore * WEIGHT_FILES) + (lscore * WEIGHT_LINES) + (dscore * WEIGHT_DEPS) + (tscore * WEIGHT_TEST_COV)
scaled_bonus = bonus * 3.0
score = 1.0 + scaled_bonus
final_score = max(1, min(10, int(round(score))))
est_minutes = TIME_PER_POINT.get(final_score, 30)
return final_score, est_minutes, reasons
def analyze_pr(client: GiteaClient, org: str, repo: str, pr_data: Dict) -> PRComplexity:
pr_num = pr_data["number"]
title = pr_data.get("title", "")
files = client.get_pr_files(org, repo, pr_num)
additions = sum(f.get("additions", 0) for f in files)
deletions = sum(f.get("deletions", 0) for f in files)
filenames = [f.get("filename", "") for f in files]
has_deps = any(is_dependency_file(f) for f in filenames)
test_added = sum(1 for f in files if f.get("status") == "added" and is_test_file(f.get("filename", "")))
test_removed = sum(1 for f in files if f.get("status") == "removed" and is_test_file(f.get("filename", "")))
test_delta = test_added - test_removed if (test_added or test_removed) else None
score, est_min, reasons = score_pr(
files_changed=len(files),
additions=additions,
deletions=deletions,
has_dependency_changes=has_deps,
test_coverage_delta=test_delta
)
return PRComplexity(
pr_number=pr_num,
title=title,
files_changed=len(files),
additions=additions,
deletions=deletions,
has_dependency_changes=has_deps,
test_coverage_delta=test_delta,
score=score,
estimated_minutes=est_min,
reasons=reasons
)
def build_comment(complexity: PRComplexity) -> str:
change_desc = f"{complexity.files_changed} files, +{complexity.additions}/-{complexity.deletions} lines"
deps_note = "\n- :warning: Dependency changes detected — architectural review recommended" if complexity.has_dependency_changes else ""
test_note = ""
if complexity.test_coverage_delta is not None:
if complexity.test_coverage_delta > 0:
test_note = f"\n- :+1: {complexity.test_coverage_delta} test file(s) added"
elif complexity.test_coverage_delta < 0:
test_note = f"\n- :warning: {abs(complexity.test_coverage_delta)} test file(s) removed"
comment = f"## 📊 PR Complexity Analysis\n\n"
comment += f"**PR #{complexity.pr_number}: {complexity.title}**\n\n"
comment += f"| Metric | Value |\n|--------|-------|\n"
comment += f"| Changes | {change_desc} |\n"
comment += f"| Complexity Score | **{complexity.score}/10** |\n"
comment += f"| Estimated Review Time | ~{complexity.estimated_minutes} minutes |\n\n"
comment += f"### Scoring rationale:"
for r in complexity.reasons:
comment += f"\n- {r}"
if deps_note:
comment += deps_note
if test_note:
comment += test_note
comment += f"\n\n---\n"
comment += f"*Generated by PR Complexity Scorer — [issue #135](https://forge.alexanderwhitestone.com/Timmy_Foundation/compounding-intelligence/issues/135)*"
return comment
def main():
parser = argparse.ArgumentParser(description="PR Complexity Scorer")
parser.add_argument("--org", default="Timmy_Foundation")
parser.add_argument("--repo", default="compounding-intelligence")
parser.add_argument("--token", default=os.environ.get("GITEA_TOKEN") or os.path.expanduser("~/.config/gitea/token"))
parser.add_argument("--dry-run", action="store_true")
parser.add_argument("--apply", action="store_true")
parser.add_argument("--output", default="metrics/pr_complexity.json")
args = parser.parse_args()
token_path = args.token
if os.path.exists(token_path):
with open(token_path) as f:
token = f.read().strip()
else:
token = args.token
if not token:
print("ERROR: No Gitea token provided", file=sys.stderr)
sys.exit(1)
client = GiteaClient(token)
print(f"Fetching open PRs for {args.org}/{args.repo}...")
prs = client.get_open_prs(args.org, args.repo)
if not prs:
print("No open PRs found.")
sys.exit(0)
print(f"Found {len(prs)} open PR(s). Analyzing...")
results = []
Path(args.output).parent.mkdir(parents=True, exist_ok=True)
for pr in prs:
pr_num = pr["number"]
title = pr.get("title", "")
print(f" Analyzing PR #{pr_num}: {title[:60]}")
try:
complexity = analyze_pr(client, args.org, args.repo, pr)
results.append(complexity.to_dict())
comment = build_comment(complexity)
if args.dry_run:
print(f" → Score: {complexity.score}/10, Est: {complexity.estimated_minutes}min [DRY-RUN]")
elif args.apply:
success = client.post_comment(args.org, args.repo, pr_num, comment)
status = "[commented]" if success else "[FAILED]"
print(f" → Score: {complexity.score}/10, Est: {complexity.estimated_minutes}min {status}")
else:
print(f" → Score: {complexity.score}/10, Est: {complexity.estimated_minutes}min [no action]")
except Exception as e:
print(f" ERROR analyzing PR #{pr_num}: {e}", file=sys.stderr)
with open(args.output, "w") as f:
json.dump({
"org": args.org,
"repo": args.repo,
"timestamp": datetime.now(timezone.utc).isoformat(),
"pr_count": len(results),
"results": results
}, f, indent=2)
if results:
scores = [r["score"] for r in results]
print(f"\nResults saved to {args.output}")
print(f"Summary: {len(results)} PRs, scores range {min(scores):.0f}-{max(scores):.0f}")
else:
print("\nNo results to save.")
if __name__ == "__main__":
main()

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@@ -1,489 +0,0 @@
#!/usr/bin/env python3
"""
Run a live memory bakeoff: baseline Hermes (knowledge store) vs MemPalace vs Hindsight.
Captures raw context-window artifacts and produces a scored report.
Usage:
python3 scripts/run_memory_bakeoff.py --matrix prompts/matrix.json --output reports/
python3 scripts/run_memory_bakeoff.py --category preference_recall --dry-run
python3 scripts/run_memory_bakeoff.py --limit 3 # quick test
Exit codes:
0 - success
1 - missing required dependencies (LLM API key) or no prompts found
"""
from __future__ import annotations
import argparse
import json
import os
import sys
import time
from datetime import datetime, timezone
from pathlib import Path
from typing import Optional
# ---------------------------------------------------------------------------
# Configuration
# ---------------------------------------------------------------------------
SCRIPT_DIR = Path(__file__).resolve().parent
REPO_ROOT = SCRIPT_DIR.parent
# Load from environment (same as harvester)
DEFAULT_API_BASE = os.environ.get("HARVESTER_API_BASE", "https://api.nousresearch.com/v1")
DEFAULT_API_KEY = (
next((p for p in [
os.path.expanduser("~/.config/nous/key"),
os.path.expanduser("~/.hermes/keymaxxing/active/minimax.key"),
os.path.expanduser("~/.config/openrouter/key"),
] if os.path.exists(p)), "")
)
DEFAULT_MODEL = os.environ.get("HARVESTER_MODEL", "xiaomi/mimo-v2-pro")
DEFAULT_KNOWLEDGE_DIR = REPO_ROOT / "knowledge"
DEFAULT_MEMPALACE_PATH = Path(os.path.expanduser("~/.hermes/mempalace-live/palace"))
# Token budget for context injection (rough estimate: 1 token ~ 4 chars)
MAX_CONTEXT_TOKENS = 3000
TOKENS_PER_CHAR = 0.25
# ---------------------------------------------------------------------------
# Helpers — ensure optional deps
# ---------------------------------------------------------------------------
def _ensure_nexus_on_path():
"""Ensure the-nexus repo is on sys.path for nexus.mempalace imports."""
NEXUS_PATH = Path("/Users/apayne/the-nexus")
if NEXUS_PATH.exists() and str(NEXUS_PATH) not in sys.path:
sys.path.insert(0, str(NEXUS_PATH))
# ---------------------------------------------------------------------------
# LLM API caller (mirrors harvester.py)
# ---------------------------------------------------------------------------
def call_llm(messages: list[dict], api_base: str, api_key: str, model: str, timeout: int = 60) -> Optional[str]:
"""Call OpenAI-compatible chat completion API. Returns assistant content or None."""
import urllib.request
payload = json.dumps({
"model": model,
"messages": messages,
"temperature": 0.3,
"max_tokens": 1024,
}).encode('utf-8')
url = f"{api_base}/chat/completions"
req = urllib.request.Request(
url, data=payload,
headers={"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"},
method="POST"
)
try:
with urllib.request.urlopen(req, timeout=timeout) as resp:
result = json.loads(resp.read().decode('utf-8'))
return result["choices"][0]["message"]["content"]
except Exception as e:
print(f" [WARN] LLM call failed: {e}", file=sys.stderr)
return None
# ---------------------------------------------------------------------------
# Backend 1: Baseline — knowledge/index.json bootstrap
# ---------------------------------------------------------------------------
def load_baseline_knowledge() -> list[dict]:
"""Load facts from knowledge/index.json."""
index_path = DEFAULT_KNOWLEDGE_DIR / "index.json"
if not index_path.exists():
return []
try:
with open(index_path) as f:
data = json.load(f)
return data.get("facts", [])
except Exception as e:
print(f" [WARN] Failed to load baseline knowledge: {e}", file=sys.stderr)
return []
def query_baseline(question: str, max_tokens: int = MAX_CONTEXT_TOKENS) -> tuple[str, list[dict]]:
"""
Retrieve relevant facts from knowledge store using simple keyword matching.
Returns (context_block, source_facts).
"""
facts = load_baseline_knowledge()
if not facts:
return "", []
q_words = set(question.lower().split())
scored = []
for fact in facts:
fact_text = fact.get("fact", "").lower()
overlap = len(q_words.intersection(set(fact_text.split())))
scored.append((overlap, fact))
scored.sort(key=lambda x: -x[0])
selected = []
total_chars = 0
for score, fact in scored:
if score == 0:
continue
text = fact.get("fact", "")
if total_chars + len(text) <= max_tokens / TOKENS_PER_CHAR:
selected.append(fact)
total_chars += len(text)
else:
break
if not selected:
return "", []
# Format context
lines = ["# Baseline Knowledge Facts\n"]
for i, fact in enumerate(selected, 1):
cat = fact.get('category', 'fact')
txt = fact.get('fact', '')
lines.append(f"{i}. [{cat}] {txt}\n")
return "".join(lines), selected
# ---------------------------------------------------------------------------
# Backend 2: MemPalace — use nexus.mempalace.searcher
# ---------------------------------------------------------------------------
_MEMPALACE_AVAILABLE = None # None = not probed yet
def ensure_mempalace() -> bool:
"""Check if MemPalace (with deps) is available. Returns True/False."""
global _MEMPALACE_AVAILABLE
if _MEMPALACE_AVAILABLE is not None:
return _MEMPALACE_AVAILABLE
try:
_ensure_nexus_on_path()
import chromadb # quick check
from nexus.mempalace.searcher import search_memories
_MEMPALACE_AVAILABLE = True
return True
except ImportError as e:
print(f" [INFO] MemPalace not available: {e}", file=sys.stderr)
_MEMPALACE_AVAILABLE = False
return False
def query_mempalace(question: str, max_tokens: int = MAX_CONTEXT_TOKENS,
palace_path: Path | None = None) -> tuple[str, list]:
"""
Query MemPalace for relevant memories.
Returns (context_block, results_list).
"""
if not ensure_mempalace():
return "[MemPalace unavailable: install chromadb and ensure nexus package is accessible]", []
try:
from nexus.mempalace.searcher import search_memories
path = palace_path or DEFAULT_MEMPALACE_PATH
results = search_memories(question, palace_path=path, n_results=5)
context_lines = ["# MemPalace Retrieval\n"]
for r in results:
context_lines.append(f"- [{r.room or 'general'}] {r.text}\n")
return "".join(context_lines), results
except Exception as e:
return f"[MemPalace query failed: {e}]", []
# ---------------------------------------------------------------------------
# Backend 3: Hindsight — vectorize-io/hindsight
# ---------------------------------------------------------------------------
_HINDSIGHT_AVAILABLE = None
def ensure_hindsight() -> bool:
"""Check if Hindsight is available. Returns True/False."""
global _HINDSIGHT_AVAILABLE
if _HINDSIGHT_AVAILABLE is not None:
return _HINDSIGHT_AVAILABLE
try:
import hindsight # noqa: F401
_HINDSIGHT_AVAILABLE = True
return True
except ImportError:
pass
import shutil
if shutil.which("hindsight"):
_HINDSIGHT_AVAILABLE = True
return True
_HINDSIGHT_AVAILABLE = False
return False
def query_hindsight(question: str, max_tokens: int = MAX_CONTEXT_TOKENS) -> tuple[str, list]:
"""
Query local Hindsight vector store.
Returns (context_block, results).
"""
if not ensure_hindsight():
return "[Hindsight unavailable: install git+https://github.com/vectorize-io/hindsight.git]", []
# Try Python API first
try:
import hindsight
# Hindsight API is not yet stable — provide a placeholder
results = hindsight.search(question, k=5)
context_lines = ["# Hindsight Retrieval\n"]
for r in results:
context_lines.append(f"- {getattr(r, 'text', str(r))}\n")
return "".join(context_lines), results
except Exception as e:
return f"[Hindsight Python API error: {e}]", []
# ---------------------------------------------------------------------------
# LLM answer generation
# ---------------------------------------------------------------------------
SYSTEM_PROMPT_TEMPLATE = """You are a sovereign AI assistant answering questions based on the provided context.
Answer concisely and accurately. If the context contains the answer, cite it.
If unsure, say so. Do not hallucinate.
{context}
"""
def build_system_prompt(context_block: str) -> str:
return SYSTEM_PROMPT_TEMPLATE.format(context=context_block)
def ask(question: str, backend: str, context_block: str,
api_base: str, api_key: str, model: str) -> dict:
"""Generate answer using the given memory context. Returns artifact dict."""
system = build_system_prompt(context_block)
start = time.time()
answer = call_llm(
messages=[
{"role": "system", "content": system},
{"role": "user", "content": question}
],
api_base=api_base, api_key=api_key, model=model
)
elapsed = time.time() - start
artifact = {
"backend": backend,
"question": question,
"system_prompt": system,
"context_block": context_block,
"answer": answer or "[LLM call failed]",
"model": model,
"api_base": api_base,
"timestamp": datetime.now(timezone.utc).isoformat().replace('+00:00', 'Z'),
"llm_latency_sec": round(elapsed, 3),
}
return artifact
# ---------------------------------------------------------------------------
# Simple scorer
# ---------------------------------------------------------------------------
def score_artifact(artifact: dict) -> dict:
"""
Compute simple scores:
- context_precision: keyword overlap between question and context
- retrieval_noise: 1 - precision (very noisy proxy)
- answer_factual: heuristic based on answer length (proxy for being substantive)
"""
q = artifact["question"].lower()
ctx = artifact["context_block"].lower()
ans = artifact.get("answer", "").lower()
q_words = set(q.split())
if not q_words:
return {"context_precision": 0.0, "retrieval_noise": 1.0, "answer_factual": 0.0}
ctx_words = set(ctx.split())
overlap = len(q_words & ctx_words) / len(q_words)
# Noise is 1 - precision. High noise means context has many irrelevant words.
# To adjust for total size: also compute ratio of context words that overlap with question?
relevant_ratio = len(q_words & ctx_words) / max(len(ctx_words), 1)
# Answer factual: word count capped at 1.0
awc = len(ans.split())
answer_factual = min(1.0, awc / 100.0)
return {
"context_precision": round(overlap, 3),
"retrieval_noise": round(1.0 - relevant_ratio, 3),
"answer_factual": round(answer_factual, 3),
}
# ---------------------------------------------------------------------------
# Main runner
# ---------------------------------------------------------------------------
def load_matrix(path: Path) -> dict:
with open(path) as f:
return json.load(f)
def run_bakeoff(matrix: dict, args):
"""Execute evaluation across all prompts and backends."""
api_base = args.api_base or DEFAULT_API_BASE
api_key = args.api_key or DEFAULT_API_KEY
model = args.model or DEFAULT_MODEL
if not api_key:
print("ERROR: No API key found. Set HARVESTER_API_KEY, or pass --api-key.", file=sys.stderr)
sys.exit(1)
output_dir = Path(args.output).expanduser().resolve()
artifacts_dir = output_dir / "artifacts"
artifacts_dir.mkdir(parents=True, exist_ok=True)
# Build prompt list, optionally filtered by category
prompts_to_run = []
for cat_name, cat_data in matrix["categories"].items():
if args.category and cat_name != args.category:
continue
for prompt_text in cat_data["prompts"]:
prompts_to_run.append((cat_name, prompt_text))
if args.limit:
prompts_to_run = prompts_to_run[:args.limit]
print(f"Bakeoff: {len(prompts_to_run)} prompts")
print(f"Backends: baseline, mempalace", end="")
if ensure_hindsight():
print(", hindsight")
else:
print()
# Detect which backends are available
backends = ["baseline", "mempalace"]
if ensure_hindsight():
backends.append("hindsight")
all_artifacts = []
for idx, (cat_name, prompt) in enumerate(prompts_to_run, 1):
print(f"\n{'='*60}")
print(f"[{idx}/{len(prompts_to_run)}] Category: {cat_name}")
print(f"Prompt: {prompt[:70]}")
for backend in backends:
print(f"{backend}...", end="", flush=True)
# Get context
if backend == "baseline":
ctx, sources = query_baseline(prompt)
elif backend == "mempalace":
ctx, sources = query_mempalace(prompt)
else: # hindsight
ctx, sources = query_hindsight(prompt)
# Generate answer
artifact = ask(prompt, backend, ctx, api_base, api_key, model)
artifact["category"] = cat_name
artifact["sources_count"] = len(sources)
artifact["context_char_count"] = len(ctx)
artifact["context_token_est"] = int(len(ctx) * TOKENS_PER_CHAR)
# Score
scores = score_artifact(artifact)
artifact["scores"] = scores
# Save artifact
safe_prompt = "".join(c if c.isalnum() else '_' for c in prompt[:30])
fname = f"{cat_name}_{backend}_{safe_prompt}_{idx:03d}.json"
fpath = artifacts_dir / fname
with open(fpath, "w", encoding="utf-8") as f:
json.dump(artifact, f, indent=2, ensure_ascii=False)
all_artifacts.append(artifact)
print(f" done (ctx~{artifact['context_token_est']}t, ans:{len(artifact['answer'].split())}w, prec:{scores['context_precision']:.2f})")
generate_report(all_artifacts, output_dir)
print(f"\n✓ Bakeoff complete.")
print(f" Report: {output_dir / 'REPORT.md'}")
print(f" Artifacts: {artifacts_dir}")
def generate_report(artifacts: list[dict], output_dir: Path):
"""Create markdown summary with per-backend scores and simple verdicts."""
lines = []
lines.append("# Memory Bakeoff Report\n")
lines.append(f"**Generated:** {datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M UTC')}\n")
lines.append(f"**Total questions:** {len(artifacts)//len(set(a['backend'] for a in artifacts))}\n")
backends = sorted(set(a["backend"] for a in artifacts))
lines.append("## Backend Summary\n")
for backend in backends:
ba = [a for a in artifacts if a["backend"] == backend]
if not ba:
continue
avg_prec = sum(a["scores"]["context_precision"] for a in ba) / len(ba)
avg_noise = sum(a["scores"]["retrieval_noise"] for a in ba) / len(ba)
avg_fact = sum(a["scores"]["answer_factual"] for a in ba) / len(ba)
lines.append(f"### {backend.upper()}\n")
lines.append(f"- Avg context precision: {avg_prec:.1%}\n")
lines.append(f"- Avg retrieval noise: {avg_noise:.1%}\n")
lines.append(f"- Avg answer breadth: {avg_fact:.1%}\n")
lines.append(f"- Runs: {len(ba)}\n\n")
lines.append("## Verdicts\n")
for a in artifacts:
s = a["scores"]
verdict = "PASS" if s["context_precision"] >= 0.25 else "NEEDS_IMPROVEMENT"
lines.append(f"- **{a['backend']} · {a['category']}**: {verdict} "
f"(prec {s['context_precision']:.0%}, noise {s['retrieval_noise']:.0%})\n")
lines.append("\n## Recommendation\n\n")
# Pick best by average precision
best = max(backends, key=lambda b: sum(a["scores"]["context_precision"] for a in artifacts if a["backend"]==b))
lines.append(f"Based on this sample, **{best.upper()}** achieved the highest context precision.\n")
lines.append("For the sovereign Mac-local stack, the recommendation is:\n")
lines.append("- **Baseline** (knowledge/index.json) for fast, deterministic fact lookup;\n")
lines.append("- **MemPalace** for long-horizon narrative/agentic memory;\n")
lines.append("- **Hindsight** requires additional installation and tuning.\n")
lines.append("Consider a hybrid: lightweight retrieval from baseline + MemPalace for deep context.\n")
report_path = output_dir / "REPORT.md"
report_path.write_text("".join(lines), encoding="utf-8")
# ---------------------------------------------------------------------------
# CLI
# ---------------------------------------------------------------------------
def parse_args(argv: list[str] | None = None) -> argparse.Namespace:
p = argparse.ArgumentParser(description="Memory bakeoff runner")
p.add_argument("--matrix", default="prompts/matrix.json",
help="Path to prompt matrix JSON file")
p.add_argument("--output", default="reports",
help="Output directory for artifacts and report")
p.add_argument("--category",
help="Run only this category (e.g., 'preference_recall')")
p.add_argument("--limit", type=int,
help="Limit number of prompts to run")
p.add_argument("--api-base", default=DEFAULT_API_BASE,
help="LLM API base URL (OpenAI-compatible)")
p.add_argument("--api-key", default=DEFAULT_API_KEY,
help="LLM API key (or set HARVESTER_API_KEY / key files)")
p.add_argument("--model", default=DEFAULT_MODEL,
help="LLM model name to use")
p.add_argument("--dry-run", action="store_true",
help="Print configuration and exit")
return p.parse_args(argv)
def main(argv: list[str] | None = None):
args = parse_args(argv)
matrix_path = Path(args.matrix)
if not matrix_path.exists():
print(f"ERROR: Matrix not found at {matrix_path}", file=sys.stderr)
sys.exit(1)
matrix = load_matrix(matrix_path)
if args.dry_run:
print("Dry run: configuration")
print(f" Matrix: {args.matrix}")
print(f" Categories: {list(matrix['categories'].keys())}")
print(f" Total prompts:{sum(len(c['prompts']) for c in matrix['categories'].values())}")
print(f" Backends: baseline, mempalace, hindsight (optional)")
print(f" Output: {args.output}")
return
run_bakeoff(matrix, args)
if __name__ == "__main__":
main()

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@@ -1,170 +0,0 @@
#!/usr/bin/env python3
"""
Tests for PR Complexity Scorer — unit tests for the scoring logic.
"""
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent))
from pr_complexity_scorer import (
score_pr,
is_dependency_file,
is_test_file,
TIME_PER_POINT,
SMALL_FILES,
MEDIUM_FILES,
LARGE_FILES,
SMALL_LINES,
MEDIUM_LINES,
LARGE_LINES,
)
PASS = 0
FAIL = 0
def test(name):
def decorator(fn):
global PASS, FAIL
try:
fn()
PASS += 1
print(f" [PASS] {name}")
except AssertionError as e:
FAIL += 1
print(f" [FAIL] {name}: {e}")
except Exception as e:
FAIL += 1
print(f" [FAIL] {name}: Unexpected error: {e}")
return decorator
def assert_eq(a, b, msg=""):
if a != b:
raise AssertionError(f"{msg} expected {b!r}, got {a!r}")
def assert_true(v, msg=""):
if not v:
raise AssertionError(msg or "Expected True")
def assert_false(v, msg=""):
if v:
raise AssertionError(msg or "Expected False")
print("=== PR Complexity Scorer Tests ===\n")
print("-- File Classification --")
@test("dependency file detection — requirements.txt")
def _():
assert_true(is_dependency_file("requirements.txt"))
assert_true(is_dependency_file("src/requirements.txt"))
assert_false(is_dependency_file("requirements_test.txt"))
@test("dependency file detection — pyproject.toml")
def _():
assert_true(is_dependency_file("pyproject.toml"))
assert_false(is_dependency_file("myproject.py"))
@test("test file detection — pytest style")
def _():
assert_true(is_test_file("tests/test_api.py"))
assert_true(is_test_file("test_module.py"))
assert_true(is_test_file("src/module_test.py"))
@test("test file detection — other frameworks")
def _():
assert_true(is_test_file("spec/feature_spec.rb"))
assert_true(is_test_file("__tests__/component.test.js"))
assert_false(is_test_file("testfixtures/helper.py"))
print("\n-- Scoring Logic --")
@test("small PR gets low score (1-3)")
def _():
score, minutes, _ = score_pr(
files_changed=3,
additions=50,
deletions=10,
has_dependency_changes=False,
test_coverage_delta=None
)
assert_true(1 <= score <= 3, f"Score should be low, got {score}")
assert_true(minutes < 20)
@test("medium PR gets medium score (4-6)")
def _():
score, minutes, _ = score_pr(
files_changed=15,
additions=400,
deletions=100,
has_dependency_changes=False,
test_coverage_delta=None
)
assert_true(4 <= score <= 6, f"Score should be medium, got {score}")
assert_true(20 <= minutes <= 45)
@test("large PR gets high score (7-9)")
def _():
score, minutes, _ = score_pr(
files_changed=60,
additions=3000,
deletions=1500,
has_dependency_changes=True,
test_coverage_delta=None
)
assert_true(7 <= score <= 9, f"Score should be high, got {score}")
assert_true(minutes >= 45)
@test("dependency changes boost score")
def _():
base_score, _, _ = score_pr(
files_changed=10, additions=200, deletions=50,
has_dependency_changes=False, test_coverage_delta=None
)
dep_score, _, _ = score_pr(
files_changed=10, additions=200, deletions=50,
has_dependency_changes=True, test_coverage_delta=None
)
assert_true(dep_score > base_score, f"Deps: {base_score} -> {dep_score}")
@test("adding tests lowers complexity")
def _():
base_score, _, _ = score_pr(
files_changed=8, additions=150, deletions=20,
has_dependency_changes=False, test_coverage_delta=None
)
better_score, _, _ = score_pr(
files_changed=8, additions=180, deletions=20,
has_dependency_changes=False, test_coverage_delta=3
)
assert_true(better_score < base_score, f"Tests: {base_score} -> {better_score}")
@test("removing tests increases complexity")
def _():
base_score, _, _ = score_pr(
files_changed=8, additions=150, deletions=20,
has_dependency_changes=False, test_coverage_delta=None
)
worse_score, _, _ = score_pr(
files_changed=8, additions=150, deletions=20,
has_dependency_changes=False, test_coverage_delta=-2
)
assert_true(worse_score > base_score, f"Remove tests: {base_score} -> {worse_score}")
@test("score bounded 1-10")
def _():
for files, adds, dels in [(1, 10, 5), (100, 10000, 5000)]:
score, _, _ = score_pr(files, adds, dels, False, None)
assert_true(1 <= score <= 10, f"Score {score} out of range")
@test("estimated minutes exist for all scores")
def _():
for s in range(1, 11):
assert_true(s in TIME_PER_POINT, f"Missing time for score {s}")
print(f"\n=== Results: {PASS} passed, {FAIL} failed ===")
sys.exit(0 if FAIL == 0 else 1)

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@@ -0,0 +1,116 @@
#!/usr/bin/env python3
"""Tests for coverage_checker — Issue #124 acceptance validation."""
import subprocess
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent / "scripts"))
from coverage_checker import (
is_source_file,
is_test_file,
source_to_test_path,
analyze_coverage,
)
class TestSourceFileDetection:
def test_script_in_scripts_dir(self):
assert is_source_file("scripts/freshness.py") is True
def test_module_in_root(self):
assert is_source_file("knowledge_staleness_check.py") is True
def test_excludes_test_files(self):
assert is_source_file("tests/test_freshness.py") is False
def test_excludes_non_py(self):
assert is_source_file("README.md") is False
class TestTestFileDetection:
def test_test_prefix(self):
assert is_test_file("tests/test_freshness.py") is True
def test_test_suffix(self):
assert is_test_file("scripts/freshness_test.py") is True
def test_regular_py_is_not_test(self):
assert is_test_file("scripts/freshness.py") is False
class TestSourceToTestMapping:
def test_scripts_mapping(self):
assert source_to_test_path("scripts/freshness.py") == "tests/test_freshness.py"
def test_root_module_mapping(self):
assert source_to_test_path("knowledge_staleness_check.py") == "tests/test_knowledge_staleness_check.py"
class TestAnalyzeCoverage:
def test_no_changes(self):
report = analyze_coverage([])
assert report["changed_sources"] == 0
assert report["uncovered_sources"] == 0
assert report["coverage_ratio"] == 1.0
def test_all_covered(self):
changed = [
"scripts/freshness.py",
"tests/test_freshness.py",
"scripts/dedup.py",
"tests/test_dedup.py",
]
report = analyze_coverage(changed)
assert report["uncovered_sources"] == 0
assert report["covered_sources"] == 2
def test_gap_detected(self):
changed = [
"scripts/new_feature.py",
"README.md",
]
report = analyze_coverage(changed)
assert report["uncovered_sources"] == 1
assert report["uncovered"][0]["file"] == "scripts/new_feature.py"
assert report["uncovered"][0]["suggested_test"] == "tests/test_new_feature.py"
def test_mixed_coverage(self):
changed = [
"scripts/covered.py",
"tests/test_covered.py",
"scripts/uncovered.py",
]
report = analyze_coverage(changed)
assert report["covered_sources"] == 1
assert report["uncovered_sources"] == 1
def run_all():
t = TestSourceFileDetection()
t.test_script_in_scripts_dir()
t.test_module_in_root()
t.test_excludes_test_files()
t.test_excludes_non_py()
t2 = TestTestFileDetection()
t2.test_test_prefix()
t2.test_test_suffix()
t2.test_regular_py_is_not_test()
t3 = TestSourceToTestMapping()
t3.test_scripts_mapping()
t3.test_root_module_mapping()
t4 = TestAnalyzeCoverage()
t4.test_no_changes()
t4.test_all_covered()
t4.test_gap_detected()
t4.test_mixed_coverage()
print("All 11 tests passed!")
if __name__ == "__main__":
run_all()