markitect-main/markitect/query_paradigms/paradigms/fts_paradigm.py

"""
Full Text Search Paradigm - FTS5-powered content search.
"""

import time
from typing import Dict, Any, List, Optional

from ..base import BaseQueryParadigm, QueryResult


class FullTextSearchParadigm(BaseQueryParadigm):
    """Full text search paradigm using FTS5 for content discovery."""

    @property
    def name(self) -> str:
        return "FTS"

    @property
    def description(self) -> str:
        return "Full text search across markdown content using SQLite FTS5 for semantic discovery"

    @property
    def category(self) -> str:
        return "textual"

    @property
    def complexity(self) -> str:
        return "beginner"

    def execute(self, query: str, config: Dict[str, Any] = None) -> QueryResult:
        """Execute full text search query."""
        start_time = time.time()

        try:
            from ...plugins.builtin.search.fts_search import FTSSearchPlugin

            # Get database path from config
            db_path = config.get('db_path') if config else 'markitect.db'

            # Create FTS search plugin
            fts_plugin = FTSSearchPlugin()

            # Execute search
            content_type = config.get('content_type', 'all') if config else 'all'
            limit = config.get('limit', 20) if config else 20
            offset = config.get('offset', 0) if config else 0

            search_results = fts_plugin.search(
                db_path=db_path,
                query=query,
                content_type=content_type,
                limit=limit,
                offset=offset
            )

            execution_time = (time.time() - start_time) * 1000

            # Convert FTS results to standard format
            results = []
            for result in search_results:
                if result['type'] == 'file':
                    results.append({
                        'type': 'file',
                        'score': result['score'],
                        'filename': result['file']['filename'],
                        'content_preview': result.get('highlight', ''),
                        'file_id': result['file']['id'],
                        'created_at': result['file']['created_at']
                    })
                elif result['type'] == 'schema':
                    results.append({
                        'type': 'schema',
                        'score': result['score'],
                        'filename': result['schema']['filename'],
                        'title': result['schema']['title'],
                        'description': result['schema']['description'],
                        'schema_id': result['schema']['id'],
                        'highlight': result.get('highlight', '')
                    })

            return QueryResult(
                paradigm="FTS",
                query=query,
                execution_time_ms=execution_time,
                result_count=len(results),
                results=results,
                metadata={
                    "content_type": content_type,
                    "fts_enabled": True,
                    "query_type": self._detect_query_type(query)
                },
                success=True
            )

        except Exception as e:
            execution_time = (time.time() - start_time) * 1000

            return QueryResult(
                paradigm="FTS",
                query=query,
                execution_time_ms=execution_time,
                result_count=0,
                results=[],
                metadata={"fts_enabled": False},
                success=False,
                error_message=str(e)
            )

    def get_examples(self) -> List[Dict[str, str]]:
        """Get example FTS queries."""
        return [
            {
                "name": "Simple search",
                "description": "Find documents containing specific words",
                "query": "documentation"
            },
            {
                "name": "Multiple terms",
                "description": "Search for documents with multiple terms",
                "query": "API documentation"
            },
            {
                "name": "Exact phrase",
                "description": "Search for exact phrases",
                "query": '"getting started"'
            },
            {
                "name": "Boolean search",
                "description": "Use AND/OR operators",
                "query": "API AND documentation NOT deprecated"
            },
            {
                "name": "Wildcard search",
                "description": "Prefix matching with wildcards",
                "query": "config*"
            },
            {
                "name": "Proximity search",
                "description": "Find terms near each other",
                "query": "NEAR(database query, 5)"
            }
        ]

    def validate_query(self, query: str) -> tuple[bool, Optional[str]]:
        """Validate FTS query syntax."""
        if not query or not query.strip():
            return False, "Query cannot be empty"

        # Use the FTS query parser for validation
        try:
            from ...plugins.builtin.search.query_parser import QueryParser
            parser = QueryParser()
            return parser.validate_query(query)
        except ImportError:
            # Fallback validation
            return self._basic_validation(query)

    def _basic_validation(self, query: str) -> tuple[bool, Optional[str]]:
        """Basic FTS query validation."""
        # Check for balanced quotes
        quote_count = query.count('"')
        if quote_count % 2 != 0:
            return False, "Unmatched quotes in query"

        # Check for balanced parentheses
        open_parens = query.count('(')
        close_parens = query.count(')')
        if open_parens != close_parens:
            return False, "Unmatched parentheses in query"

        return True, None

    def get_syntax_help(self) -> str:
        """Get FTS syntax help."""
        return """Full Text Search Syntax:

Basic Search:
  word                 - Find documents containing 'word'
  multiple words       - Find documents with all words (implicit AND)

Phrase Search:
  "exact phrase"       - Find exact phrase

Boolean Operators:
  word1 AND word2      - Both words must be present
  word1 OR word2       - Either word can be present
  word1 NOT word2      - First word present, second word absent

Wildcards:
  prefix*              - Prefix matching (config* matches configuration)

Proximity Search:
  NEAR(word1 word2, 5) - Words within 5 words of each other

Column-Specific:
  filename:readme      - Search only in filename field
  content:tutorial     - Search only in content field

Examples:
  documentation
  "getting started"
  API AND documentation
  config* OR setting*
  NEAR(database query, 10)
"""

    def _detect_query_type(self, query: str) -> str:
        """Detect FTS query type."""
        query_upper = query.upper()

        if '"' in query:
            return "phrase_search"
        elif 'NEAR(' in query_upper:
            return "proximity_search"
        elif any(op in query_upper for op in [' AND ', ' OR ', ' NOT ']):
            return "boolean_search"
        elif '*' in query:
            return "wildcard_search"
        elif ':' in query:
            return "column_search"
        else:
            return "simple_search"

    def can_translate_from(self, other_paradigm: str) -> bool:
        """Check if we can translate from another paradigm."""
        return other_paradigm.lower() in ["natural_language", "sql"]

    def translate_query(self, query: str, from_paradigm: str) -> Optional[str]:
        """Translate from another paradigm to FTS."""
        if from_paradigm.lower() == "natural_language":
            return self._translate_natural_language_to_fts(query)
        elif from_paradigm.lower() == "sql":
            return self._translate_sql_to_fts(query)
        return None

    def _translate_natural_language_to_fts(self, query: str) -> Optional[str]:
        """Translate natural language to FTS query."""
        query_lower = query.lower()

        # Extract key terms and convert to FTS syntax
        if "search for" in query_lower:
            # Extract what comes after "search for"
            parts = query_lower.split("search for", 1)
            if len(parts) > 1:
                search_term = parts[1].strip()
                return search_term.replace(" and ", " AND ").replace(" or ", " OR ")

        if "find" in query_lower and "contain" in query_lower:
            # Extract terms between "find" and "contain"
            import re
            match = re.search(r'find.*?contain.*?["\'](.+?)["\']', query_lower)
            if match:
                return f'"{match.group(1)}"'

        # Simple keyword extraction
        keywords = [word for word in query.split() if len(word) > 3 and word.lower() not in ['find', 'search', 'for', 'documents', 'files']]
        if keywords:
            return " AND ".join(keywords)

        return None

    def _translate_sql_to_fts(self, query: str) -> Optional[str]:
        """Translate simple SQL LIKE queries to FTS."""
        if 'LIKE' in query.upper():
            import re
            # Extract LIKE patterns
            like_matches = re.findall(r"LIKE\s+'%(.+?)%'", query, re.IGNORECASE)
            if like_matches:
                return " AND ".join(like_matches)

        return None