"""AI-First Knowledge Extraction Module.

This module provides intelligent knowledge extraction capabilities using pattern-based
analysis (placeholder for future LLM integration). It extracts structured knowledge
from documentation, code repositories, and other sources.

The IntelligentKnowledge class serves as the foundation for AI-powered understanding
of CLIs, APIs, and documentation.
"""
import re
from typing import Dict, List, Any
from pathlib import Path
import json
from ..knowledge_store import get_knowledge_store


class IntelligentKnowledge:
    """Use AI/LLM to extract and understand knowledge from various sources."""
    
    def __init__(self):
        self.store = get_knowledge_store()
    
    def extract_from_documentation(self, text: str, context: str = "") -> Dict[str, Any]:
        """Extract structured knowledge from documentation text.
        
        This is a placeholder for LLM-based extraction.
        In production, this would use an LLM API to intelligently parse docs.
        """
        knowledge = {
            "summary": "",
            "key_concepts": [],
            "examples": [],
            "api_patterns": [],
            "authentication": None,
            "rate_limits": None
        }
        
        # Basic pattern extraction (would be replaced with LLM in production)
        # Extract examples
        example_patterns = [
            r'```(?:bash|shell|sh)\n(.*?)\n```',
            r'```(?:python|py)\n(.*?)\n```',
            r'```(?:javascript|js)\n(.*?)\n```',
            r'\$\s+(.+?)(?:\n|$)',
        ]
        
        for pattern in example_patterns:
            matches = re.findall(pattern, text, re.DOTALL | re.MULTILINE)
            for match in matches[:5]:  # Limit examples
                knowledge["examples"].append({
                    "code": match.strip(),
                    "language": "detected",
                    "context": context
                })
        
        # Extract API patterns
        api_patterns = [
            r'(?:GET|POST|PUT|PATCH|DELETE)\s+(/[\w/\{\}:-]+)',
            r'endpoint[:\s]+([^\s\n]+)',
            r'https?://[^\s\n]+/api/[^\s\n]+',
        ]
        
        for pattern in api_patterns:
            matches = re.findall(pattern, text, re.IGNORECASE)
            knowledge["api_patterns"].extend(matches[:10])
        
        # Look for authentication mentions
        if re.search(r'(?:api[_\s]key|authorization|bearer|token|oauth)', text, re.IGNORECASE):
            knowledge["authentication"] = "detected"
        
        # Look for rate limit mentions
        rate_limit_match = re.search(r'(\d+)\s*(?:requests?|calls?)\s*(?:per|/)\s*(\w+)', text, re.IGNORECASE)
        if rate_limit_match:
            knowledge["rate_limits"] = f"{rate_limit_match.group(1)} per {rate_limit_match.group(2)}"
        
        return knowledge
    
    def analyze_code_repository(self, repo_path: Path) -> Dict[str, Any]:
        """Analyze a code repository to understand its structure and capabilities."""
        knowledge = {
            "structure": {},
            "entry_points": [],
            "configuration": {},
            "dependencies": [],
            "api_definitions": [],
            "cli_definitions": []
        }
        
        # This is a simplified version - in production would use more sophisticated analysis
        # Check for common configuration files
        config_files = {
            "package.json": "node",
            "setup.py": "python",
            "pyproject.toml": "python",
            "Cargo.toml": "rust",
            "go.mod": "go"
        }
        
        for config_file, lang in config_files.items():
            config_path = repo_path / config_file
            if config_path.exists():
                knowledge["structure"]["language"] = lang
                knowledge["structure"]["config_file"] = config_file
                
                # Parse configuration
                try:
                    if config_file == "package.json":
                        with open(config_path, 'r') as f:
                            data = json.load(f)
                            knowledge["entry_points"] = list(data.get("bin", {}).keys())
                            knowledge["dependencies"] = list(data.get("dependencies", {}).keys())
                    elif config_file in ["setup.py", "pyproject.toml"]:
                        # Would parse Python config here
                        pass
                except:
                    pass
                break
        
        # Look for API definitions
        api_files = list(repo_path.rglob("*api*.{json,yaml,yml}"))
        for api_file in api_files[:5]:
            knowledge["api_definitions"].append(str(api_file.relative_to(repo_path)))
        
        # Look for CLI definitions
        cli_indicators = ["cli.py", "cli.js", "cmd/", "commands/"]
        for indicator in cli_indicators:
            if (repo_path / indicator).exists():
                knowledge["cli_definitions"].append(indicator)
        
        return knowledge