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#!/usr/bin/env python3
"""
Gitea Issue Body Parser
Extracts structured data from Gitea issue markdown bodies:
- Title
- Context section
- Acceptance criteria (checkboxes)
- Labels
- Epic/parent references
Usage:
python3 scripts/gitea_issue_parser.py <issue_body.txt
python3 scripts/gitea_issue_parser.py --url https://forge.../api/v1/repos/.../issues/123
echo "issue body" | python3 scripts/gitea_issue_parser.py --stdin
Output: JSON with {title, context, criteria[], labels[], epic_ref}
"""
import argparse
import json
import re
import sys
from typing import Optional
def parse_issue_body(body: str, title: str = "", labels: list = None) -> dict:
"""Parse a Gitea issue body into structured JSON."""
result = {
"title": title,
"context": "",
"criteria": [],
"labels": labels or [],
"epic_ref": None,
"sections": {},
}
if not body:
return result
# Extract epic/parent reference from title or body
epic_pattern = r"#(\d+)"
title_refs = re.findall(epic_pattern, title)
body_refs = re.findall(epic_pattern, body[:200]) # Check early body refs
# Look for "Closes #N" or "Part of #N" or "Epic: #N"
close_match = re.search(r"(?:Closes?|Fixes?|Resolves?)\s+#(\d+)", body, re.IGNORECASE)
part_match = re.search(r"(?:Part of|Epic|Parent|Blocks?)\s+#(\d+)", body, re.IGNORECASE)
if close_match:
result["epic_ref"] = f"#{close_match.group(1)}"
elif part_match:
result["epic_ref"] = f"#{part_match.group(1)}"
elif title_refs:
result["epic_ref"] = f"#{title_refs[0]}"
elif body_refs:
result["epic_ref"] = f"#{body_refs[0]}"
# Split into sections by ## headers
section_pattern = r"^##\s+(.+)$"
lines = body.split("\n")
current_section = None
current_content = []
for line in lines:
header_match = re.match(section_pattern, line)
if header_match:
# Save previous section
if current_section:
result["sections"][current_section] = "\n".join(current_content).strip()
current_section = header_match.group(1).strip().lower()
current_content = []
else:
current_content.append(line)
# Save last section
if current_section:
result["sections"][current_section] = "\n".join(current_content).strip()
# Extract context
for key in ["context", "background", "description", "problem"]:
if key in result["sections"]:
result["context"] = result["sections"][key]
break
# Extract acceptance criteria (checkboxes)
criteria_section = None
for key in ["acceptance criteria", "acceptance_criteria", "criteria", "requirements", "definition of done"]:
if key in result["sections"]:
criteria_section = result["sections"][key]
break
if criteria_section:
checkbox_pattern = r"-\s*\[[ xX]?\]\s*(.+)"
for match in re.finditer(checkbox_pattern, criteria_section):
result["criteria"].append(match.group(1).strip())
# Also try plain numbered/bulleted lists if no checkboxes found
if not result["criteria"]:
list_pattern = r"^\s*(?:\d+\.|-|\*)\s+(.+)"
for match in re.finditer(list_pattern, criteria_section, re.MULTILINE):
result["criteria"].append(match.group(1).strip())
# If no sectioned criteria found, scan whole body for checkboxes
if not result["criteria"]:
for match in re.finditer(r"-\s*\[[ xX]?\]\s*(.+)", body):
result["criteria"].append(match.group(1).strip())
return result
def parse_from_url(api_url: str, token: str = None) -> dict:
"""Parse an issue from a Gitea API URL."""
import urllib.request
headers = {}
if token:
headers["Authorization"] = f"token {token}"
req = urllib.request.Request(api_url, headers=headers)
resp = json.loads(urllib.request.urlopen(req, timeout=30).read())
title = resp.get("title", "")
body = resp.get("body", "")
labels = [l["name"] for l in resp.get("labels", [])]
return parse_issue_body(body, title, labels)
def main():
parser = argparse.ArgumentParser(description="Parse Gitea issue body into structured JSON")
parser.add_argument("input", nargs="?", help="Issue body file (or - for stdin)")
parser.add_argument("--url", help="Gitea API URL for the issue")
parser.add_argument("--stdin", action="store_true", help="Read from stdin")
parser.add_argument("--token", help="Gitea API token (or set GITEA_TOKEN env var)")
parser.add_argument("--title", default="", help="Issue title (for epic ref extraction)")
parser.add_argument("--labels", nargs="*", default=[], help="Issue labels")
parser.add_argument("--pretty", action="store_true", help="Pretty-print JSON output")
args = parser.parse_args()
import os
token = args.token or os.environ.get("GITEA_TOKEN")
if args.url:
result = parse_from_url(args.url, token)
elif args.stdin or (args.input and args.input == "-"):
body = sys.stdin.read()
result = parse_issue_body(body, args.title, args.labels)
elif args.input:
with open(args.input) as f:
body = f.read()
result = parse_issue_body(body, args.title, args.labels)
else:
parser.print_help()
sys.exit(1)
indent = 2 if args.pretty else None
print(json.dumps(result, indent=indent))
if __name__ == "__main__":
main()

276
scripts/session_metadata.py Normal file
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#!/usr/bin/env python3
"""
session_metadata.py - Extract structured metadata from Hermes session transcripts.
Works alongside session_reader.py to provide higher-level session analysis.
"""
import json
import re
import sys
from dataclasses import dataclass, asdict
from datetime import datetime
from pathlib import Path
from typing import Dict, List, Optional, Any
# Import from session_reader (the canonical reader)
from session_reader import read_session
@dataclass
class SessionSummary:
"""Structured summary of a Hermes session transcript."""
session_id: str
model: str
repo: str
outcome: str
message_count: int
tool_calls: int
duration_estimate: str
key_actions: List[str]
errors_encountered: List[str]
start_time: Optional[str] = None
end_time: Optional[str] = None
total_tokens_estimate: int = 0
user_messages: int = 0
assistant_messages: int = 0
tool_outputs: int = 0
def extract_session_metadata(file_path: str) -> SessionSummary:
"""
Extract structured metadata from a Hermes session JSONL transcript.
Uses session_reader.read_session() for file reading.
"""
session_id = Path(file_path).stem
messages = []
model = "unknown"
repo = "unknown"
tool_calls_count = 0
key_actions = []
errors = []
start_time = None
end_time = None
total_tokens = 0
# Common repo patterns to look for
repo_patterns = [
r"(?:the-nexus|compounding-intelligence|timmy-config|hermes-agent)",
r"(?:forge\.alexanderwhitestone\.com/([^/]+/[^/\\s]+))",
r"(?:github\.com/([^/]+/[^/\\s]+))",
r"(?:Timmy_Foundation/([^/\\s]+))",
]
try:
# Use the canonical reader from session_reader.py
messages = read_session(file_path)
except FileNotFoundError:
return SessionSummary(
session_id=session_id,
model="unknown",
repo="unknown",
outcome="failure",
message_count=0,
tool_calls=0,
duration_estimate="0m",
key_actions=[],
errors_encountered=[f"File not found: {file_path}"]
)
# Process messages for metadata
for entry in messages:
# Extract model from assistant messages
if entry.get("role") == "assistant" and entry.get("model"):
model = entry["model"]
# Extract timestamps
if entry.get("timestamp"):
ts = entry["timestamp"]
if start_time is None:
start_time = ts
end_time = ts
# Count tool calls
if entry.get("tool_calls"):
tool_calls_count += len(entry["tool_calls"])
for tc in entry["tool_calls"]:
if tc.get("function", {}).get("name"):
action = f"{tc['function']['name']}"
if action not in key_actions:
key_actions.append(action)
# Estimate tokens from content length
content = entry.get("content", "")
if isinstance(content, str):
total_tokens += len(content.split())
elif isinstance(content, list):
for item in content:
if isinstance(item, dict) and "text" in item:
total_tokens += len(item["text"].split())
# Look for repo mentions in content
if entry.get("content"):
content_str = str(entry["content"])
for pattern in repo_patterns:
match = re.search(pattern, content_str, re.IGNORECASE)
if match:
if match.groups():
repo = match.group(1)
else:
repo = match.group(0)
break
# Look for error messages
if entry.get("role") == "tool" and entry.get("is_error"):
error_msg = entry.get("content", "Unknown error")
if isinstance(error_msg, str) and len(error_msg) < 200:
errors.append(error_msg[:200])
# Count message types
user_messages = sum(1 for m in messages if m.get("role") == "user")
assistant_messages = sum(1 for m in messages if m.get("role") == "assistant")
tool_outputs = sum(1 for m in messages if m.get("role") == "tool")
# Calculate duration estimate
duration_estimate = "unknown"
if start_time and end_time:
try:
# Try to parse timestamps
start_dt = None
end_dt = None
# Handle various timestamp formats
for fmt in ["%Y-%m-%dT%H:%M:%S.%fZ", "%Y-%m-%dT%H:%M:%SZ", "%Y-%m-%d %H:%M:%S"]:
try:
if start_dt is None:
start_dt = datetime.strptime(start_time, fmt)
if end_dt is None:
end_dt = datetime.strptime(end_time, fmt)
except ValueError:
continue
if start_dt and end_dt:
duration = end_dt - start_dt
minutes = duration.total_seconds() / 60
duration_estimate = f"{minutes:.0f}m"
except Exception:
pass
# Classify outcome
outcome = "unknown"
if errors:
# Check if any errors are fatal
fatal_errors = any("405" in e or "permission" in e.lower() or "authentication" in e.lower()
for e in errors)
if fatal_errors:
outcome = "failure"
else:
outcome = "partial"
elif messages:
# Check last message for success indicators
last_msg = messages[-1]
if last_msg.get("role") == "assistant":
content = last_msg.get("content", "")
if isinstance(content, str):
success_indicators = ["done", "completed", "success", "merged", "pushed"]
if any(indicator in content.lower() for indicator in success_indicators):
outcome = "success"
else:
outcome = "unknown"
# Deduplicate key actions (keep unique, limit to 10)
unique_actions = []
for action in key_actions:
if action not in unique_actions:
unique_actions.append(action)
if len(unique_actions) >= 10:
break
# Deduplicate errors (keep unique, limit to 5)
unique_errors = []
for error in errors:
if error not in unique_errors:
unique_errors.append(error)
if len(unique_errors) >= 5:
break
return SessionSummary(
session_id=session_id,
model=model,
repo=repo,
outcome=outcome,
message_count=len(messages),
tool_calls=tool_calls_count,
duration_estimate=duration_estimate,
key_actions=unique_actions,
errors_encountered=unique_errors,
start_time=start_time,
end_time=end_time,
total_tokens_estimate=total_tokens,
user_messages=user_messages,
assistant_messages=assistant_messages,
tool_outputs=tool_outputs
)
def process_session_directory(directory_path: str, output_file: Optional[str] = None) -> List[SessionSummary]:
"""
Process all JSONL files in a directory.
"""
directory = Path(directory_path)
if not directory.exists():
print(f"Error: Directory {directory_path} does not exist", file=sys.stderr)
return []
jsonl_files = list(directory.glob("*.jsonl"))
if not jsonl_files:
print(f"Warning: No JSONL files found in {directory_path}", file=sys.stderr)
return []
summaries = []
for jsonl_file in sorted(jsonl_files):
print(f"Processing {jsonl_file.name}...", file=sys.stderr)
summary = extract_session_metadata(str(jsonl_file))
summaries.append(summary)
if output_file:
with open(output_file, 'w', encoding='utf-8') as f:
json.dump([asdict(s) for s in summaries], f, indent=2)
print(f"Wrote {len(summaries)} summaries to {output_file}", file=sys.stderr)
return summaries
def main():
"""CLI entry point."""
import argparse
parser = argparse.ArgumentParser(description="Extract metadata from Hermes session JSONL transcripts")
parser.add_argument("path", help="Path to JSONL file or directory of session files")
parser.add_argument("-o", "--output", help="Output JSON file (default: stdout)")
parser.add_argument("-v", "--verbose", action="store_true", help="Verbose output")
args = parser.parse_args()
path = Path(args.path)
if path.is_file():
summary = extract_session_metadata(str(path))
if args.output:
with open(args.output, 'w') as f:
json.dump(asdict(summary), f, indent=2)
print(f"Wrote summary to {args.output}", file=sys.stderr)
else:
print(json.dumps(asdict(summary), indent=2))
elif path.is_dir():
summaries = process_session_directory(str(path), args.output)
if not args.output:
print(json.dumps([asdict(s) for s in summaries], indent=2))
else:
print(f"Error: {args.path} is not a file or directory", file=sys.stderr)
sys.exit(1)
if __name__ == "__main__":
main()

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#!/usr/bin/env python3
"""Tests for gitea_issue_parser."""
import json
import sys
import os
sys.path.insert(0, os.path.dirname(__file__))
from gitea_issue_parser import parse_issue_body
def test_basic_structure():
body = """## Context
This is the background.
## Acceptance Criteria
- [ ] First criterion
- [x] Second criterion (already done)
- [ ] Third criterion
## Labels
`pipeline`, `extraction`
"""
result = parse_issue_body(body, "Test Issue", ["pipeline", "extraction"])
assert result["title"] == "Test Issue"
assert "background" in result["context"].lower()
assert len(result["criteria"]) == 3
assert "First criterion" in result["criteria"]
assert result["labels"] == ["pipeline", "extraction"]
print("PASS: test_basic_structure")
def test_epic_ref():
body = "Closes #645\n\nSome description."
result = parse_issue_body(body, "feat: thing (#688)")
assert result["epic_ref"] == "#645"
print("PASS: test_epic_ref")
def test_epic_ref_from_title():
body = "Some description without close ref."
result = parse_issue_body(body, "feat: scene descriptions (#645)")
assert result["epic_ref"] == "#645"
print("PASS: test_epic_ref_from_title")
def test_no_checkboxes():
body = """## Requirements
1. First thing
2. Second thing
3. Third thing
"""
result = parse_issue_body(body)
assert len(result["criteria"]) == 3
print("PASS: test_no_checkboxes")
def test_empty_body():
result = parse_issue_body("", "Empty Issue")
assert result["title"] == "Empty Issue"
assert result["criteria"] == []
assert result["context"] == ""
print("PASS: test_empty_body")
def test_real_issue_format():
body = """Closes #681
## Changes
Add `#!/usr/bin/env python3` shebang to 6 Python scripts.
## Verification
All 6 files confirmed missing shebangs before fix.
## Impact
Scripts can now be executed directly.
"""
result = parse_issue_body(body, "fix: add python3 shebangs (#685)")
assert result["epic_ref"] == "#681"
assert "shebang" in result["context"].lower()
print("PASS: test_real_issue_format")
def test_all_sections_captured():
body = """## Context
Background info.
## Acceptance Criteria
- [ ] Do thing
## Labels
`test`
"""
result = parse_issue_body(body)
assert "context" in result["sections"]
assert "acceptance criteria" in result["sections"]
print("PASS: test_all_sections_captured")
if __name__ == "__main__":
test_basic_structure()
test_epic_ref()
test_epic_ref_from_title()
test_no_checkboxes()
test_empty_body()
test_real_issue_format()
test_all_sections_captured()
print("\nAll tests passed.")