mcp-solver

""" ASP solution module for extracting and formatting solutions from ASP solvers. This module provides functions for extracting solution data from ASP solvers and converting it to a standardized format. """ import logging from typing import Any from .error_handling import ASPError, format_solution_error logger = logging.getLogger(__name__) _LAST_SOLUTION = None RESERVED_KEYS = { "satisfiable", "answer_sets", "values", "status", "error_type", "error_message", "warnings", } def export_solution( data: Any = None, status: str | None = None, warnings: list[str] | None = None, ) -> dict[str, Any]: """ Extract and format solutions from an ASP solver or answer set data. Args: data: List of answer sets, or dictionary containing solution data status: Optional status string ("sat", "unsat", "error") warnings: Optional list of warning messages Returns: Dictionary with structured solution data, including: - satisfiable: Boolean indicating if at least one answer set was found - status: String status ("sat", "unsat", or "error") - answer_sets: List of answer sets (each a list of atoms) - values: Flattened dictionary of all atoms (True if present in any answer set) - warnings: List of warning messages (if any) If an error occurs, the returned dictionary will include: - satisfiable: False - error_type: Type of the error - error_message: Detailed error message - status: "error" """ global _LAST_SOLUTION try: # If data is an exception, format as error immediately if isinstance(data, Exception): error_solution = format_solution_error(data) _LAST_SOLUTION = error_solution return error_solution solution_data = _process_input_data(data, status, warnings) solution_data = _extract_values_from_answer_sets(solution_data) # Ensure success flag for normal results to prevent server from overriding status solution_data["success"] = True logger.debug(f"Setting _LAST_SOLUTION: {solution_data}") _LAST_SOLUTION = solution_data return solution_data except Exception as e: error_solution = format_solution_error(e) _LAST_SOLUTION = error_solution logger.error(f"Error in export_solution: {e!s}", exc_info=True) return error_solution def _process_input_data( data: Any, status: str | None = None, warnings: list[str] | None = None, ) -> dict[str, Any]: """ Process input data from various sources into a standardized solution dictionary. """ solution_data: dict[str, Any] = {} # Case 1: Direct dictionary data if isinstance(data, dict): solution_data = data.copy() # Case 2: List of answer sets (each a list of atoms) elif isinstance(data, list) and (not data or isinstance(data[0], list)): solution_data["answer_sets"] = data solution_data["satisfiable"] = bool(data) # Case 3: None or unknown type elif data is None: solution_data["answer_sets"] = [] solution_data["satisfiable"] = False else: raise ASPError(f"Unsupported data type for ASP solution: {type(data).__name__}") # Set the status field if status: solution_data["status"] = status else: solution_data["status"] = ( "sat" if solution_data.get("satisfiable", False) else "unsat" ) # Add warnings if provided if warnings: solution_data["warnings"] = warnings # Ensure values dictionary exists (may be populated later) solution_data["values"] = solution_data.get("values", {}) return solution_data def _extract_values_from_answer_sets(solution_data: dict[str, Any]) -> dict[str, Any]: """ Extract values from answer sets into a flat values dictionary. """ answer_sets = solution_data.get("answer_sets", []) values: dict[str, Any] = {} # For each atom in any answer set, set True for answer_set in answer_sets: for atom in answer_set: if atom not in values: values[atom] = True solution_data["values"] = values return solution_data