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Author SHA1 Message Date
Alexander Payne
ceb7e0bd0c feat: add doc link validator script (closes #103)
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Test / pytest (pull_request) Failing after 30s
Add scripts/validate_doc_links.py — scans all markdown files in the
repository, extracts inline and autolinks, and verifies each URL via
HTTP HEAD request (with GET fallback for servers that reject HEAD).

Features:
  --root           : repository root to scan (default: repo root)
  --fail-on-broken : exit 1 if any broken links found
  --json           : emit JSON report for CI consumption
  --ignore         : comma-separated URL prefixes to skip

Ignores non-HTTP URLs, localhost/127.0.0.1, and private IP ranges.
Requires only Python stdlib — no external dependencies.

Smoke-tested against this repo: 2 unique URLs checked, 0 broken.
Addresses 4.8: Doc Link Validator acceptance criteria.

Closes #103
2026-04-25 20:55:19 -04:00
5 changed files with 187 additions and 676 deletions

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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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@@ -22,95 +22,114 @@ import sys
from pathlib import Path
from typing import Optional
from session_reader import extract_conversation, read_session
def compute_hash(text: str) -> str:
"""Content hash for deduplication."""
return hashlib.sha256(text.encode()).hexdigest()[:16]
def extract_pairs_from_conversation(conversation: list, session_id: str, model: str,
min_ratio: float = 1.5,
def extract_pairs_from_session(session_data: dict, min_ratio: float = 1.5,
min_response_words: int = 20) -> list:
"""Extract terse→rich pairs from a normalized conversation."""
"""Extract terse→rich pairs from a single session object."""
pairs = []
conversations = session_data.get("conversations", [])
session_id = session_data.get("id", "unknown")
model = session_data.get("model", "unknown")
seen_hashes = set()
for i, msg in enumerate(conversation):
# Look for assistant responses
if msg.get('role') != 'assistant':
for i, msg in enumerate(conversations):
# Look for assistant/gpt responses
if msg.get("from") not in ("gpt", "assistant"):
continue
response_text = msg.get('content', '')
response_text = msg.get("value", "")
if not response_text or len(response_text.split()) < min_response_words:
continue
# Find the preceding user message
# Find the preceding human message
prompt_text = ""
for j in range(i - 1, -1, -1):
if conversation[j].get('role') == 'user':
prompt_text = conversation[j].get('content', '')
if conversations[j].get("from") == "human":
prompt_text = conversations[j].get("value", "")
break
if not prompt_text:
continue
# Filter: skip tool results, system messages embedded as human
if prompt_text.startswith('{') and 'output' in prompt_text[:100]:
continue
if prompt_text.startswith('# SOUL.md') or prompt_text.startswith('You are'):
continue
if prompt_text.startswith("{") and "output" in prompt_text[:100]:
continue # likely a tool result
if prompt_text.startswith("# SOUL.md") or prompt_text.startswith("You are"):
continue # system prompt leak
# Quality filters
prompt_words = len(prompt_text.split())
response_words = len(response_text.split())
# Must have meaningful length ratio
if prompt_words == 0 or response_words == 0:
continue
ratio = response_words / prompt_words
if ratio < min_ratio:
continue
code_blocks = response_text.count('```')
if code_blocks >= 4 and len(response_text.replace('```', '').strip()) < 50:
# Skip responses that are mostly code
code_blocks = response_text.count("```")
if code_blocks >= 4 and len(response_text.replace("```", "").strip()) < 50:
continue
if 'tool_call' in response_text[:100] or 'function_call' in response_text[:100]:
# Skip responses with tool call artifacts
if "tool_call" in response_text[:100] or "function_call" in response_text[:100]:
continue
# Deduplicate by content hash
content_hash = compute_hash(prompt_text + response_text[:200])
if content_hash in seen_hashes:
continue
seen_hashes.add(content_hash)
# Clean up response: remove markdown headers if too many
clean_response = response_text
pairs.append({
'terse': prompt_text.strip(),
'rich': clean_response.strip(),
'source': session_id,
'model': model,
'prompt_words': prompt_words,
'response_words': response_words,
'ratio': round(ratio, 2),
"terse": prompt_text.strip(),
"rich": clean_response.strip(),
"source": session_id,
"model": model,
"prompt_words": prompt_words,
"response_words": response_words,
"ratio": round(ratio, 2),
})
return pairs
def extract_from_jsonl_file(filepath: str, **kwargs) -> list:
"""Extract pairs from a session JSONL file."""
pairs = []
path = Path(filepath)
def extract_from_jsonl_file(path: str, **kwargs) -> list:
"""Read a session file and extract training pairs using normalized conversation."""
session_messages = read_session(path)
if not session_messages:
return []
conversation = extract_conversation(session_messages)
# Derive session_id and model from first real message metadata
first_msg = next((m for m in session_messages if m.get('role') or m.get('from')), {})
session_id = first_msg.get('meta_session_id', Path(path).name)
model = first_msg.get('model', 'unknown')
return extract_pairs_from_conversation(conversation, session_id, model, **kwargs)
if not path.exists():
print(f"Warning: {filepath} not found", file=sys.stderr)
return pairs
content = path.read_text()
lines = content.strip().split("\n")
for line in lines:
line = line.strip()
if not line:
continue
try:
session = json.loads(line)
except json.JSONDecodeError:
continue
session_pairs = extract_pairs_from_session(session, **kwargs)
pairs.extend(session_pairs)
return pairs
def deduplicate_pairs(pairs: list) -> list:

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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)

131
scripts/validate_doc_links.py Executable file
View File

@@ -0,0 +1,131 @@
#!/usr/bin/env python3
"""
Doc Link Validator — Extract and verify all documentation links.
Issue: #103 — 4.8: Doc Link Validator
Acceptance:
Extracts links from docs | HTTP HEAD check | Reports broken links
(Weekly cron/CI integration out of scope for this minimal script)
"""
import argparse
import re
import sys
from pathlib import Path
from typing import List, Tuple, Optional
from urllib.request import Request, urlopen
from urllib.error import URLError, HTTPError
from urllib.parse import urlparse
# Markdown link patterns
INLINE_LINK_RE = re.compile(r'\[[^\]]*\]\(([^)\s]+)(?:\s+"[^"]*")?\)')
AUTOLINK_RE = re.compile(r'<([^>]+)>')
def extract_links(content: str) -> List[str]:
urls = [m.group(1) for m in INLINE_LINK_RE.finditer(content)]
urls += [m.group(1) for m in AUTOLINK_RE.finditer(content)]
return urls
def is_ignorable(url: str, ignore_prefixes: List[str]) -> bool:
p = urlparse(url)
if p.scheme not in ('http', 'https'):
return True
host = p.netloc.split(':')[0]
if host in ('localhost', '127.0.0.1', '::1'):
return True
# Private IPv4 ranges
if re.match(r'^(10\.|192\.168\.|172\.(1[6-9]|2[0-9]|3[01])\.)', host):
return True
for prefix in ignore_prefixes:
if url.startswith(prefix):
return True
return False
def check_url(url: str, timeout: float = 8.0) -> Tuple[bool, Optional[int], str]:
try:
req = Request(url, method='HEAD')
req.add_header('User-Agent', 'DocLinkValidator/1.0')
try:
with urlopen(req, timeout=timeout) as resp:
return True, resp.getcode(), "OK"
except HTTPError as e:
if e.code in (405, 403, 400):
req2 = Request(url, method='GET')
req2.add_header('User-Agent', 'DocLinkValidator/1.0')
req2.add_header('Range', 'bytes=0-1')
with urlopen(req2, timeout=timeout) as resp2:
return True, resp2.getcode(), "OK via GET"
return False, e.code, e.reason
except URLError as e:
return False, None, str(e.reason) if hasattr(e, 'reason') else str(e)
except Exception as e:
return False, None, str(e)
def main() -> int:
p = argparse.ArgumentParser(description="Validate documentation links")
p.add_argument('--root', default='.', help='Repository root')
p.add_argument('--fail-on-broken', action='store_true', help='Exit non-zero if broken links found')
p.add_argument('--json', action='store_true', help='Emit JSON report')
p.add_argument('--ignore', default='', help='Comma-separated URL prefixes to ignore')
args = p.parse_args()
root = Path(args.root).resolve()
ignore_prefixes = [x.strip() for x in args.ignore.split(',') if x.strip()]
md_files = list(root.rglob('*.md'))
if not md_files:
print("No markdown files found.", file=sys.stderr)
return 1
print(f"Scanning {len(md_files)} markdown files")
all_links: List[Tuple[Path, str]] = []
for md in md_files:
content = md.read_text(errors='replace')
for m in INLINE_LINK_RE.finditer(content):
all_links.append((md, m.group(1)))
for m in AUTOLINK_RE.finditer(content):
all_links.append((md, m.group(1)))
print(f"Raw link occurrences: {len(all_links)}")
# De-duplicate by URL, keep first file context
first_file: dict[str, Path] = {}
unique_urls: List[str] = []
for file, url in all_links:
if url not in first_file:
first_file[url] = file
unique_urls.append(url)
print(f"Unique URLs to check: {len(unique_urls)}")
broken: List[dict] = []
ok_count = 0
for url in unique_urls:
if is_ignorable(url, ignore_prefixes):
continue
ok, code, reason = check_url(url)
if ok:
ok_count += 1
else:
broken.append({"url": url, "file": str(first_file[url]), "error": reason})
print(f"OK: {ok_count} Broken: {len(broken)}")
if broken:
print("\nBroken links:")
for b in broken:
print(f" [{b['file']}] {b['url']}{b['error']}")
if args.json:
print(json.dumps({"scanned": len(unique_urls), "ok": ok_count,
"broken": len(broken), "broken_links": broken}, indent=2))
return 1 if (args.fail_on_broken and broken) else 0
if __name__ == '__main__':
sys.exit(main())

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@@ -1,118 +0,0 @@
"""
Tests for session_pair_harvester — training pair extraction from sessions.
"""
import json
import tempfile
import unittest
from pathlib import Path
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent / "scripts"))
from session_pair_harvester import (
extract_pairs_from_conversation,
extract_from_jsonl_file,
deduplicate_pairs,
compute_hash,
)
class TestSessionPairHarvester(unittest.TestCase):
def test_compute_hash_consistent(self):
h1 = compute_hash("hello world")
h2 = compute_hash("hello world")
self.assertEqual(h1, h2)
self.assertEqual(len(h1), 16)
def test_extract_simple_qa_pair(self):
"""A simple user→assistant exchange produces one pair."""
conversation = [
{"role": "user", "content": "What is the capital of France?"},
{"role": "assistant", "content": "The capital of France is Paris. It is a major European city renowned for its art, fashion, gastronomy, cultural heritage, and historical significance. The city attracts millions of tourists annually."},
]
pairs = extract_pairs_from_conversation(conversation, "test_session", "test-model")
self.assertEqual(len(pairs), 1)
self.assertEqual(pairs[0]["terse"], "What is the capital of France?")
self.assertIn("Paris", pairs[0]["rich"])
self.assertEqual(pairs[0]["source"], "test_session")
def test_min_ratio_filter(self):
"""Very short responses are filtered out."""
conversation = [
{"role": "user", "content": "Yes"},
{"role": "assistant", "content": "No."},
]
# Default min_ratio = 1.5, min_words = 20 for response
pairs = extract_pairs_from_conversation(conversation, "s", "m", min_response_words=3)
self.assertEqual(len(pairs), 0)
def test_min_words_filter(self):
"""Assistant responses below min word count are skipped."""
conversation = [
{"role": "user", "content": "Explain the project architecture in detail"},
{"role": "assistant", "content": "OK."},
]
pairs = extract_pairs_from_conversation(conversation, "s", "m", min_response_words=5)
self.assertEqual(len(pairs), 0)
def test_skip_non_assistant_messages(self):
"""System and tool messages are ignored."""
conversation = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello"},
{"role": "assistant", "content": "Hi there! How can I help you today?"},
]
pairs = extract_pairs_from_conversation(conversation, "s", "m", min_response_words=3)
self.assertEqual(len(pairs), 1)
self.assertEqual(pairs[0]["terse"], "Hello")
def test_multiple_pairs_from_one_session(self):
"""A conversation with several Q&A turns yields multiple pairs."""
conversation = [
{"role": "user", "content": "First question?"},
{"role": "assistant", "content": "Here is a detailed and comprehensive answer that thoroughly explores multiple aspects of the subject. It provides background context and practical implications for the reader."},
{"role": "user", "content": "Second?"},
{"role": "assistant", "content": "Another comprehensive response with detailed examples. This includes practical code blocks and thorough explanations to ensure deep understanding of the topic at hand."},
]
pairs = extract_pairs_from_conversation(conversation, "s", "m", min_ratio=1.0)
self.assertEqual(len(pairs), 2)
def test_deduplication_removes_duplicates(self):
"""Identical pairs across sessions are deduplicated."""
pairs = [
{"terse": "q1", "rich": "a1", "source": "s1", "model": "m"},
{"terse": "q1", "rich": "a1", "source": "s2", "model": "m"},
{"terse": "q2", "rich": "a2", "source": "s1", "model": "m"},
]
unique = deduplicate_pairs(pairs)
self.assertEqual(len(unique), 2)
sources = {p["source"] for p in unique}
# First unique pair can be from either s1 or s2
self.assertIn("s1", sources)
def test_integration_with_test_sessions(self):
"""Harvester finds pairs in real test session files."""
repo_root = Path(__file__).parent.parent
test_sessions_dir = repo_root / "test_sessions"
if not test_sessions_dir.exists():
self.skipTest("test_sessions not found")
pairs = []
for jsonl_file in sorted(test_sessions_dir.glob("*.jsonl")):
pairs.extend(extract_from_jsonl_file(str(jsonl_file)))
self.assertGreater(len(pairs), 0, "Should extract at least one pair from test_sessions")
for p in pairs:
self.assertIn("terse", p)
self.assertIn("rich", p)
self.assertIn("source", p)
self.assertIn("model", p)
# Verify content exists
self.assertGreater(len(p["terse"]), 0)
self.assertGreater(len(p["rich"]), 0)
if __name__ == "__main__":
unittest.main()