chatgpt-on-wechat/agent/skills/frontmatter.py

"""
Frontmatter parsing for skills.
"""

import re
import json
from typing import Dict, Any, Optional, List
from agent.skills.types import SkillMetadata, SkillInstallSpec


def parse_frontmatter(content: str) -> Dict[str, Any]:
    """
    Parse YAML-style frontmatter from markdown content.
    
    Returns a dictionary of frontmatter fields.
    """
    frontmatter = {}
    
    # Match frontmatter block between --- markers
    match = re.match(r'^---\s*\n(.*?)\n---\s*\n', content, re.DOTALL)
    if not match:
        return frontmatter
    
    frontmatter_text = match.group(1)
    
    # Try to use PyYAML for proper YAML parsing
    try:
        import yaml
        frontmatter = yaml.safe_load(frontmatter_text)
        if not isinstance(frontmatter, dict):
            frontmatter = {}
        return frontmatter
    except ImportError:
        # Fallback to simple parsing if PyYAML not available
        pass
    except Exception:
        # If YAML parsing fails, fall back to simple parsing
        pass
    
    # Simple YAML-like parsing (supports key: value format only)
    # This is a fallback for when PyYAML is not available
    for line in frontmatter_text.split('\n'):
        line = line.strip()
        if not line or line.startswith('#'):
            continue
        
        if ':' in line:
            key, value = line.split(':', 1)
            key = key.strip()
            value = value.strip()
            
            # Try to parse as JSON if it looks like JSON
            if value.startswith('{') or value.startswith('['):
                try:
                    value = json.loads(value)
                except json.JSONDecodeError:
                    pass
            # Parse boolean values
            elif value.lower() in ('true', 'false'):
                value = value.lower() == 'true'
            # Parse numbers
            elif value.isdigit():
                value = int(value)
            
            frontmatter[key] = value
    
    return frontmatter


def parse_metadata(frontmatter: Dict[str, Any]) -> Optional[SkillMetadata]:
    """
    Parse skill metadata from frontmatter.
    
    Looks for 'metadata' field containing JSON with skill configuration.
    """
    metadata_raw = frontmatter.get('metadata')
    if not metadata_raw:
        return None
    
    # If it's a string, try to parse as JSON
    if isinstance(metadata_raw, str):
        try:
            metadata_raw = json.loads(metadata_raw)
        except json.JSONDecodeError:
            return None
    
    if not isinstance(metadata_raw, dict):
        return None
    
    # Use metadata_raw directly (COW format)
    meta_obj = metadata_raw
    
    # Parse install specs
    install_specs = []
    install_raw = meta_obj.get('install', [])
    if isinstance(install_raw, list):
        for spec_raw in install_raw:
            if not isinstance(spec_raw, dict):
                continue
            
            kind = spec_raw.get('kind', spec_raw.get('type', '')).lower()
            if not kind:
                continue
            
            spec = SkillInstallSpec(
                kind=kind,
                id=spec_raw.get('id'),
                label=spec_raw.get('label'),
                bins=_normalize_string_list(spec_raw.get('bins')),
                os=_normalize_string_list(spec_raw.get('os')),
                formula=spec_raw.get('formula'),
                package=spec_raw.get('package'),
                module=spec_raw.get('module'),
                url=spec_raw.get('url'),
                archive=spec_raw.get('archive'),
                extract=spec_raw.get('extract', False),
                strip_components=spec_raw.get('stripComponents'),
                target_dir=spec_raw.get('targetDir'),
            )
            install_specs.append(spec)
    
    # Parse requires
    requires = {}
    requires_raw = meta_obj.get('requires', {})
    if isinstance(requires_raw, dict):
        for key, value in requires_raw.items():
            requires[key] = _normalize_string_list(value)
    
    return SkillMetadata(
        always=meta_obj.get('always', False),
        skill_key=meta_obj.get('skillKey'),
        primary_env=meta_obj.get('primaryEnv'),
        emoji=meta_obj.get('emoji'),
        homepage=meta_obj.get('homepage'),
        os=_normalize_string_list(meta_obj.get('os')),
        requires=requires,
        install=install_specs,
    )


def _normalize_string_list(value: Any) -> List[str]:
    """Normalize a value to a list of strings."""
    if not value:
        return []
    
    if isinstance(value, list):
        return [str(v).strip() for v in value if v]
    
    if isinstance(value, str):
        return [v.strip() for v in value.split(',') if v.strip()]
    
    return []


def parse_boolean_value(value: Optional[str], default: bool = False) -> bool:
    """Parse a boolean value from frontmatter."""
    if value is None:
        return default
    
    if isinstance(value, bool):
        return value
    
    if isinstance(value, str):
        return value.lower() in ('true', '1', 'yes', 'on')
    
    return default


def get_frontmatter_value(frontmatter: Dict[str, Any], key: str) -> Optional[str]:
    """Get a frontmatter value as a string."""
    value = frontmatter.get(key)
    return str(value) if value is not None else None