vibe_data_ana/src/tools/tool_manager.py

"""Tool manager — selects applicable tools based on data profile.

The ToolManager filters tools by data type compatibility (e.g., time series tools
need datetime columns). The actual tool+parameter selection is fully AI-driven.
"""

from typing import List, Dict, Any

from src.tools.base import AnalysisTool, ToolRegistry, _global_registry
from src.models import DataProfile


class ToolManager:
    """
    Tool manager that selects applicable tools based on data characteristics.
    
    This is a filter, not a decision maker. AI decides which tools to actually
    call and with what parameters at runtime.
    """

    def __init__(self, registry: ToolRegistry = None):
        self.registry = registry if registry else _global_registry
        self._missing_tools: List[str] = []

    def select_tools(self, data_profile: DataProfile) -> List[AnalysisTool]:
        """
        Return all tools applicable to this data profile.
        Each tool's is_applicable() checks if the data has the right column types.
        """
        self._missing_tools = []
        return self.registry.get_applicable_tools(data_profile)

    def get_all_tools(self) -> List[AnalysisTool]:
        """Return all registered tools regardless of data profile."""
        tool_names = self.registry.list_tools()
        return [self.registry.get_tool(name) for name in tool_names]

    def get_missing_tools(self) -> List[str]:
        return list(set(self._missing_tools))

    def get_tool_descriptions(self, tools: List[AnalysisTool] = None) -> List[Dict[str, Any]]:
        """Get tool descriptions for AI consumption."""
        if tools is None:
            tools = self.get_all_tools()
        return [
            {
                'name': t.name,
                'description': t.description,
                'parameters': t.parameters
            }
            for t in tools
        ]