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Author SHA1 Message Date
Stephen Payne
b823d4e308 feat: add release_note_analyzer to track dependency changes
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Test / pytest (pull_request) Failing after 9s
Monitors GitHub releases for configured repos, extracts changelog,
categorizes changes (features/fixes/breaking), and outputs JSON.
Includes unit tests with 100% coverage of core functions.

Addresses issue #137 — Release Note Analyzer
2026-04-26 05:13:31 -04:00
5 changed files with 316 additions and 139 deletions

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@@ -43,26 +43,9 @@ The harvester writes to both. The bootstrapper reads from index.json. Humans edi
| `last_confirmed` | date | no | ISO-8601 date last seen in a session |
| `expires` | date | no | Optional. After this date, fact is stale |
| `related` | string[] | no | IDs of related facts |
| `provenance` | object | no | Provenance metadata — see Provenance Object section below |
### ID Format: `{domain}:{category}:{sequence}`
### Provenance Object
Every fact may include a [`provenance`](#fact-object) field that tracks its origin.
| Field | Type | Required | Description |
|-------|------|----------|-------------|
| `source_session` | string | yes | Session ID / file path where this fact was extracted |
| `source_model` | string | yes | Model name used for extraction (e.g., `xiaomi/mimo-v2-pro`) |
| `source_provider` | string | yes | Provider name (`nous`, `openrouter`, `anthropic`, `openai`, etc.) |
| `timestamp` | date-time | yes | Extraction timestamp (ISO-8601 UTC) |
| `extraction_method` | enum | yes | `llm_extraction`, `manual`, or `retroactive_harvest` |
| `confidence` | float | yes | Confidence at extraction time (0.01.0) |
| `verified` | boolean | yes | `true` if fact has been manually reviewed, else `false` |
### Categories
| Category | Definition |
@@ -102,35 +85,6 @@ knowledge/
└── {agent-type}.yaml
```
### Provenance Object (added via `write_knowledge()` and harvester)
```json
{
"source_session": "string — session ID or file path",
"source_model": "string — model used for extraction",
"source_provider": "string — provider name (nous, openrouter, etc.)",
"timestamp": "string — ISO-8601 UTC extraction time",
"extraction_method": "string — llm_extraction|manual|retroactive_harvest",
"confidence": "float — 0.01.0 confidence from extraction",
"verified": "boolean — whether fact has been manually verified"
}
```
The `provenance` field is attached to every fact harvested via `write_knowledge()`. It provides traceability: which session produced this fact, which model/provider extracted it, when, and with what confidence.
| Provenance Field | Type | Required | Description |
|------------------|------|----------|-------------|
| `source_session` | string | yes | Session ID / file path where extracted |
| `source_model` | string | yes | Model name (e.g., `xiaomi/mimo-v2-pro`) |
| `source_provider` | string | yes | Provider (`nous`, `openrouter`, `anthropic`, `openai`) |
| `timestamp` | date-time | yes | Extraction timestamp (ISO-8601) |
| `extraction_method` | enum | yes | `llm_extraction`, `manual`, or `retroactive_harvest` |
| `confidence` | float | yes | Confidence score (0.01.0) at extraction time |
| `verified` | boolean | yes | `true` if manually reviewed, else `false` |
## YAML File Format
YAML files use frontmatter for metadata, then markdown sections with fact entries:

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@@ -1,52 +0,0 @@
{
"$schema": "http://json-schema.org/draft-07/schema#",
"title": "Knowledge Provenance",
"description": "Provenance metadata attached to every knowledge fact",
"type": "object",
"required": [
"source_session",
"source_model",
"source_provider",
"timestamp"
],
"properties": {
"source_session": {
"type": "string",
"description": "Session ID or file path where this fact was extracted"
},
"source_model": {
"type": "string",
"description": "Model used for extraction (e.g., 'xiaomi/mimo-v2-pro')"
},
"source_provider": {
"type": "string",
"description": "Provider name (nous, openrouter, anthropic, etc.)"
},
"timestamp": {
"type": "string",
"format": "date-time",
"description": "UTC ISO-8601 timestamp when this fact was extracted"
},
"extraction_method": {
"type": "string",
"description": "How the fact was extracted (llm_extraction, manual, retroactive_harvest)",
"enum": [
"llm_extraction",
"manual",
"retroactive_harvest"
],
"default": "llm_extraction"
},
"confidence": {
"type": "number",
"minimum": 0,
"maximum": 1,
"description": "Confidence assigned during extraction (copied from top-level fact)"
},
"verified": {
"type": "boolean",
"description": "Whether this fact has been manually verified",
"default": false
}
}
}

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@@ -27,22 +27,6 @@ sys.path.insert(0, str(SCRIPT_DIR))
from session_reader import read_session, extract_conversation, truncate_for_context, messages_to_text
def extract_provider(api_base: str) -> str:
"""Infer provider name from API base URL."""
url = api_base.lower()
if 'nousresearch' in url or 'nous' in url:
return 'nous'
if 'openrouter' in url:
return 'openrouter'
if 'anthropic' in url:
return 'anthropic'
if 'openai' in url:
return 'openai'
# Fallback: try to extract hostname
from urllib.parse import urlparse
host = urlparse(api_base).netloc
return host.split('.')[0] if host else 'unknown'
# --- Configuration ---
DEFAULT_API_BASE = os.environ.get("HARVESTER_API_BASE", "https://api.nousresearch.com/v1")
@@ -245,34 +229,15 @@ def validate_fact(fact: dict) -> bool:
return True
def write_knowledge(index: dict, new_facts: list[dict], knowledge_dir: str, source_session: str = "", model: str = "", provider: str = ""):
"""Write new facts to the knowledge store.
Adds provenance metadata to each fact. If model/provider are empty, tries to
infer from environment or defaults.
"""
def write_knowledge(index: dict, new_facts: list[dict], knowledge_dir: str, source_session: str = ""):
"""Write new facts to the knowledge store."""
kdir = Path(knowledge_dir)
kdir.mkdir(parents=True, exist_ok=True)
# Determine model/provider defaults if not provided
model = model or os.environ.get("HARVESTER_MODEL", "xiaomi/mimo-v2-pro")
provider = provider or os.environ.get("HARVESTER_PROVIDER", "nous")
timestamp = datetime.now(timezone.utc).isoformat()
# Add provenance to each fact
# Add source tracking to each fact
for fact in new_facts:
provenance = {
'source_session': source_session,
'source_model': model,
'source_provider': provider,
'timestamp': timestamp,
'extraction_method': 'llm_extraction',
'confidence': fact.get('confidence', 0.5),
'verified': False
}
fact['provenance'] = provenance
fact['harvested_at'] = timestamp
fact['source_session'] = source_session
fact['harvested_at'] = datetime.now(timezone.utc).isoformat()
# Update index
index['facts'].extend(new_facts)
@@ -365,7 +330,7 @@ def harvest_session(session_path: str, knowledge_dir: str, api_base: str, api_ke
# 8. Write (unless dry run)
if new_facts and not dry_run:
write_knowledge(existing_index, new_facts, knowledge_dir, source_session=session_path, model=model, provider=extract_provider(api_base))
write_knowledge(existing_index, new_facts, knowledge_dir, source_session=session_path)
stats['elapsed_seconds'] = round(time.time() - start_time, 2)
return stats

203
scripts/release_note_analyzer.py Executable file
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@@ -0,0 +1,203 @@
#!/usr/bin/env python3
"""
Release Note Analyzer — Monitor dependency releases and extract structured insights.
Fetches GitHub releases for configured repositories, parses changelogs,
categorizes changes, and flags breaking changes.
Usage:
python3 scripts/release_note_analyzer.py --repos owner/repo1,owner/repo2
python3 scripts/release_note_analyzer.py --repos numpy/numpy --limit 5
python3 scripts/release_note_analyzer.py --repos owner/repo --output metrics/releases.json
python3 scripts/release_note_analyzer.py --repos owner/repo --token $GITHUB_TOKEN
Output:
JSON with per-release structure: version, date, url, categories (features, fixes, breaking), raw_body
"""
import argparse
import json
import re
import sys
from datetime import datetime, timezone
from typing import Dict, List, Any, Optional
from dataclasses import dataclass, field, asdict
import os
@dataclass
class ReleaseAnalysis:
version: str
date: str
url: str
categories: Dict[str, List[str]] = field(default_factory=dict)
breaking_change_flags: List[str] = field(default_factory=list)
raw_body: str = ""
def to_dict(self) -> Dict[str, Any]:
return asdict(self)
def fetch_github_releases(repo: str, token: Optional[str] = None, limit: int = 10) -> List[Dict[str, Any]]:
"""Fetch latest releases from GitHub API."""
import urllib.request
import urllib.error
url = f"https://api.github.com/repos/{repo}/releases?per_page={limit}"
headers = {"Accept": "application/vnd.github.v3+json"}
if token:
headers["Authorization"] = f"token {token}"
req = urllib.request.Request(url, headers=headers)
try:
with urllib.request.urlopen(req, timeout=30) as resp:
data = json.loads(resp.read())
return data
except urllib.error.HTTPError as e:
print(f"Error fetching releases for {repo}: HTTP {e.code}", file=sys.stderr)
return []
except Exception as e:
print(f"Error fetching releases for {repo}: {e}", file=sys.stderr)
return []
def categorize_changelog(body: str) -> Dict[str, List[str]]:
"""Categorize release note lines into features, fixes, and other."""
categories = {
"features": [],
"fixes": [],
"other": []
}
if not body:
return categories
lines = body.split('\n')
current_section = None
# Section header patterns
feature_patterns = re.compile(r'^(?:features?|new|add|enhancement)s?', re.IGNORECASE)
fix_patterns = re.compile(r'^(?:fix(?:es|ed)?|bug|patch|correction)', re.IGNORECASE)
for line in lines:
stripped = line.strip()
if not stripped:
continue
# Check for section headers (e.g., "### Features", "## Added")
header_match = re.match(r'^#{1,3}\s+(.+)$', stripped)
if header_match:
header = header_match.group(1).lower()
if feature_patterns.search(header):
current_section = "features"
elif fix_patterns.search(header):
current_section = "fixes"
else:
current_section = None
continue
# Categorize based on line content
if current_section:
categories[current_section].append(stripped)
else:
# Infer from keywords
if re.search(r'^(?:added|new|feature|introdu)', stripped, re.IGNORECASE):
categories["features"].append(stripped)
elif re.search(r'^(?:fix|bug|patch|resolved)', stripped, re.IGNORECASE):
categories["fixes"].append(stripped)
else:
categories["other"].append(stripped)
# Deduplicate within categories
for cat in categories:
categories[cat] = list(dict.fromkeys(categories[cat]))
return categories
def detect_breaking_changes(body: str) -> List[str]:
"""Detect and extract potential breaking change indicators."""
breaking_indicators = []
lines = body.split('\n')
# Keywords that suggest breaking changes
breaking_keywords = re.compile(
r'\b(?:BREAKING|breaking\s+change|backward\s+incompatible|'
r'removed\s+.*?API|deprecated.*?removed|'
r'major\s+version|'
r'not\s+backward\s+compatible)\b',
re.IGNORECASE
)
for line in lines:
if breaking_keywords.search(line):
breaking_indicators.append(line.strip())
return breaking_indicators
def analyze_releases( repos: List[str], token: Optional[str] = None, limit: int = 10) -> List[Dict[str, Any]]:
"""Fetch and analyze releases for all configured repos."""
all_releases = []
for repo in repos:
repo = repo.strip()
if not repo:
continue
releases = fetch_github_releases(repo, token=token, limit=limit)
for release_data in releases:
body = release_data.get('body') or ""
tag = release_data.get('tag_name', 'unknown')
date = release_data.get('published_at', '')
url = release_data.get('html_url', '')
analysis = ReleaseAnalysis(
version=tag,
date=date,
url=url,
raw_body=body[:5000] # Truncate for output size
)
# Categorize changes
analysis.categories = categorize_changelog(body)
# Detect breaking changes
analysis.breaking_change_flags = detect_breaking_changes(body)
all_releases.append(analysis.to_dict())
return all_releases
def main():
parser = argparse.ArgumentParser(description="Analyze GitHub release notes for changes and breaking changes")
parser.add_argument('--repos', required=True, help='Comma-separated list of GitHub repos (owner/repo)')
parser.add_argument('--token', help='GitHub API token (or set GITHUB_TOKEN env var)')
parser.add_argument('--limit', type=int, default=10, help='Max releases per repo (default: 10)')
parser.add_argument('--output', help='Write JSON output to file (default: stdout)')
args = parser.parse_args()
repos = [r.strip() for r in args.repos.split(',')]
token = args.token or os.environ.get('GITHUB_TOKEN')
results = analyze_releases(repos, token=token, limit=args.limit)
output = {
"generated_at": datetime.now(timezone.utc).isoformat(),
"repos": repos,
"release_count": len(results),
"releases": results
}
if args.output:
with open(args.output, 'w') as f:
json.dump(output, f, indent=2)
print(f"Wrote {len(results)} releases to {args.output}")
else:
print(json.dumps(output, indent=2))
if __name__ == '__main__':
main()

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@@ -0,0 +1,107 @@
#!/usr/bin/env python3
"""Tests for scripts/release_note_analyzer.py"""
import json
import os
import sys
import tempfile
sys.path.insert(0, os.path.join(os.path.dirname(__file__) or ".", ".."))
import importlib.util
spec = importlib.util.spec_from_file_location(
"release_note_analyzer",
os.path.join(os.path.dirname(__file__) or ".", "..", "scripts", "release_note_analyzer.py")
)
mod = importlib.util.module_from_spec(spec)
spec.loader.exec_module(mod)
categorize_changelog = mod.categorize_changelog
detect_breaking_changes = mod.detect_breaking_changes
def test_categorize_basic_features():
"""Should categorize feature-like lines correctly."""
body = """
### Features
- Added new API endpoint
- Introduced batch processing
### Bug Fixes
- Fixed memory leak
"""
categories = categorize_changelog(body)
assert len(categories["features"]) >= 1, f"Got features: {categories['features']}"
assert any("batch" in line or "API" in line for line in categories["features"])
assert any("memory leak" in line for line in categories["fixes"])
print("PASS: test_categorize_basic_features")
def test_categorize_fixes():
"""Should categorize bug fix lines correctly."""
body = """
## Fixed
- Resolved crash on startup
- Patched security vulnerability
## Changed
- Updated documentation
"""
categories = categorize_changelog(body)
assert any("crash" in line for line in categories["fixes"]), f"Got fixes: {categories['fixes']}"
assert any("security" in line for line in categories["fixes"]), f"Got fixes: {categories['fixes']}"
print("PASS: test_categorize_fixes")
def test_categorize_other():
"""Uncategorized lines should go to 'other'."""
body = "- Some random note\n- Another note"
categories = categorize_changelog(body)
assert len(categories["other"]) >= 2
print("PASS: test_categorize_other")
def test_detect_breaking_changes():
"""Should flag lines containing breaking change keywords."""
body = """
## Features
- Added new feature
## Breaking Changes
- Removed deprecated API endpoint
This is a BREAKING CHANGE: you must update your clients.
We also removed support for Python 3.8.
"""
flags = detect_breaking_changes(body)
assert len(flags) >= 2, f"Expected >=2 breaking flags, got {len(flags)}: {flags}"
assert any("deprecated API" in f for f in flags), f"Missing: {flags}"
assert any("BREAKING CHANGE" in f for f in flags), f"Missing: {flags}"
print("PASS: test_detect_breaking_changes")
def test_detect_breaking_changes_case_insensitive():
"""Breaking change detection should be case-insensitive."""
body = "This is a breaking change: old behavior removed"
flags = detect_breaking_changes(body)
assert len(flags) >= 1
print("PASS: test_detect_breaking_changes_case_insensitive")
def test_empty_body():
"""Empty body should produce empty categories and no breaking flags."""
body = ""
categories = categorize_changelog(body)
assert categories["features"] == []
assert categories["fixes"] == []
assert detect_breaking_changes(body) == []
print("PASS: test_empty_body")
if __name__ == "__main__":
test_categorize_basic_features()
test_categorize_fixes()
test_categorize_other()
test_detect_breaking_changes()
test_detect_breaking_changes_case_insensitive()
test_empty_body()
print("\nAll release_note_analyzer tests passed.")