#!/usr/bin/env python3
"""
Chat Intent Parser - Determine what type of query the user is making
"""

import re
from typing import Dict, Tuple


class ChatIntentParser:
    """Parse user queries to determine intent and scope"""

    # Patterns for different intents
    PATTERNS = {
        'kg_search': {
            'patterns': [
                r'(search|find|look for|show me).*in.*knowledge|what.*entity|find.*entity',
                r'(entity|concept|topic).*named?',
            ],
            'keywords': ['entity', 'concept', 'topic', 'knowledge', 'search']
        },
        'project_info': {
            'patterns': [
                r'(project|projects).*info|tell.*project',
                r'what.*project|list.*project|show.*project',
            ],
            'keywords': ['project', 'projects']
        },
        'system_status': {
            'patterns': [
                r'(system|status|health|running|services)',
                r'(disk|memory|cpu|load|uptime)',
                r'(docker|container|process)',
            ],
            'keywords': ['system', 'status', 'health', 'disk', 'memory', 'running']
        },
        'architecture': {
            'patterns': [
                r'(architecture|structure|how.*work|design)',
                r'(component|module|service).*architecture',
            ],
            'keywords': ['architecture', 'structure', 'design', 'component']
        },
        'help': {
            'patterns': [
                r'(help|what can|commands|available)',
                r'(how.*use|guide|tutorial)',
            ],
            'keywords': ['help', 'commands', 'guide']
        }
    }

    def __init__(self):
        """Initialize parser"""
        pass

    def parse(self, query: str) -> Dict:
        """Parse query and determine intent"""
        query_lower = query.lower().strip()

        result = {
            'original_query': query,
            'query_lower': query_lower,
            'intent': 'general',
            'confidence': 0.0,
            'scope': 'all',
            'keywords': self._extract_keywords(query_lower),
            'suggestions': []
        }

        # Check for explicit scope flags
        if query_lower.startswith('--kg ') or ' --kg ' in query_lower:
            result['scope'] = 'kg'
            query_lower = query_lower.replace('--kg ', '').replace(' --kg ', '')
        elif query_lower.startswith('--local ') or ' --local ' in query_lower:
            result['scope'] = 'local_memory'
            query_lower = query_lower.replace('--local ', '').replace(' --local ', '')
        elif query_lower.startswith('--bash ') or ' --bash ' in query_lower:
            result['scope'] = 'bash'
            query_lower = query_lower.replace('--bash ', '').replace(' --bash ', '')
        elif query_lower.startswith('--think ') or ' --think ' in query_lower:
            result['scope'] = 'reasoning'
            query_lower = query_lower.replace('--think ', '').replace(' --think ', '')

        # Detect intent from patterns
        best_intent = 'general'
        best_score = 0.0

        for intent, config in self.PATTERNS.items():
            score = self._calculate_score(query_lower, config)
            if score > best_score:
                best_score = score
                best_intent = intent

        result['intent'] = best_intent
        result['confidence'] = min(1.0, best_score)

        # Generate suggestions
        result['suggestions'] = self._suggest_queries(best_intent, query_lower)

        return result

    def _extract_keywords(self, query: str) -> list:
        """Extract important keywords from query"""
        # Simple keyword extraction - words longer than 4 characters
        words = re.findall(r'\b[a-z_]{4,}\b', query)
        # Remove common stop words
        stop_words = {'what', 'that', 'this', 'with', 'from', 'show', 'tell', 'give', 'find'}
        keywords = [w for w in words if w not in stop_words]
        return list(set(keywords))[:5]  # Return top 5 unique keywords

    def _calculate_score(self, query: str, config: Dict) -> float:
        """Calculate how well query matches intent"""
        score = 0.0

        # Check patterns
        for pattern in config['patterns']:
            if re.search(pattern, query, re.IGNORECASE):
                score += 0.4

        # Check keywords
        query_words = set(query.lower().split())
        matching_keywords = sum(1 for kw in config['keywords'] if kw in query_words)
        score += min(0.6, matching_keywords * 0.2)

        return score

    def _suggest_queries(self, intent: str, query: str) -> list:
        """Suggest related queries based on intent"""
        suggestions = {
            'kg_search': [
                'List all research entities',
                'Show me recent findings',
                'What is stored in the sysadmin domain'
            ],
            'project_info': [
                'List all projects',
                'Show project structure',
                'What projects are active'
            ],
            'system_status': [
                'Show disk usage',
                'List running services',
                'What is the system load',
                'Show memory usage'
            ],
            'architecture': [
                'Tell me about the system architecture',
                'Show me the component structure',
                'How do services communicate'
            ],
            'help': [
                'What commands are available',
                'Show me examples',
                'How do I search the knowledge graph'
            ]
        }

        return suggestions.get(intent, [])

    def extract_search_term(self, query: str) -> str:
        """Extract main search term from query"""
        # Remove common prefixes/suffixes
        query = re.sub(r'^(show|find|search|list|tell|what|how)\s+', '', query, flags=re.IGNORECASE)
        query = re.sub(r'\s+(please|thanks|help|info|details)$', '', query, flags=re.IGNORECASE)

        # Extract quoted terms first
        quoted = re.findall(r'"([^"]+)"', query)
        if quoted:
            return quoted[0]

        # Otherwise return first significant phrase
        words = [w for w in query.split() if len(w) > 3]
        return words[0] if words else query.strip()

    def is_multi_turn(self, query: str) -> bool:
        """Check if query suggests multi-turn conversation"""
        multi_turn_indicators = [
            'more', 'also', 'next', 'then', 'tell me more',
            'what else', 'continue', 'go on', 'further'
        ]
        query_lower = query.lower()
        return any(indicator in query_lower for indicator in multi_turn_indicators)


if __name__ == '__main__':
    import json
    parser = ChatIntentParser()

    test_queries = [
        'what is the system status',
        'find me entities in the KG',
        'list all projects',
        'tell me about the architecture',
        '--bash show disk usage',
        '--think analyze performance patterns'
    ]

    for query in test_queries:
        result = parser.parse(query)
        print(f"Query: {query}")
        print(f"Intent: {result['intent']} (confidence: {result['confidence']:.2f})")
        print(f"Scope: {result['scope']}")
        print(f"Keywords: {result['keywords']}")
        print()