GlyphRunner System
c3a826b65c
PHASE A: Safe predicate evaluator (glyphos/control/predicate.py) - AST-based safe expression evaluation - Supports comparisons, boolean ops, attribute access - Helper function: dominant_contains() - Protected against code injection attacks PHASE B: XICContext queue helpers - enqueue_chain(label) for FIFO chain scheduling - pop_next_chain() to get next scheduled chain - jump_to(label) for immediate destination changes PHASE C: Control flow operations (xic_ops.py) - op_IF: Conditional branching with optional else - op_MATCH: Pattern matching against fused fields - op_LOOP: Iterative execution with guardrails - Added to OP_TABLE for operation dispatch PHASE D: Execution loop enhancement (xic_vm.py) - Chain queue scheduling with label matching - Total steps tracking for guardrail enforcement - max_total_steps limit across all operations - Graceful execution stop on guardrail trigger PHASE E: Comprehensive test suite (tests/test_control_flow.py) - 14 unit tests covering all operations - Predicate evaluator tests - IF/MATCH/LOOP operation tests - Queue helper and guardrail tests - All tests passing (14/14) PHASE F: Example programs - demo_control_flow_if.gx.json: IF branching example - demo_control_flow_loop.gx.json: LOOP iteration example PHASE G: Complete documentation - XIC_V2_CONTROL_FLOW_SUMMARY.md: Technical guide - XIC_V2_QUICK_REFERENCE.md: Developer quick reference - FedMart UI and integration documentation Integration points: - FedMart telemetry captures control flow steps - UI dashboard displays control branching - Symbolic pipeline predicate evaluation - 100% backward compatible with XIC v1.5 Test results: 36/36 passing (14 control flow + 12 FedMart + 10 UI) Status: Production ready
79 lines
2.5 KiB
Python
79 lines
2.5 KiB
Python
"""
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Safe predicate evaluator for XIC v2 control flow.
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Supports simple expressions referencing fused symbol fields and helper functions.
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Allowed: comparisons, boolean ops, dominant_contains('glyph://id').
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"""
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import ast
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from typing import Any, Dict
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ALLOWED_NODE_TYPES = (
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ast.Expression, ast.BoolOp, ast.BinOp, ast.UnaryOp, ast.Compare,
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ast.Name, ast.Load, ast.Constant, ast.Call, ast.Attribute,
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ast.And, ast.Or, ast.Not,
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ast.Gt, ast.Lt, ast.GtE, ast.LtE, ast.Eq, ast.NotEq, ast.In, ast.NotIn
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)
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def _validate_node(node: ast.AST):
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"""Recursively validate AST node is safe for eval."""
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if not isinstance(node, ALLOWED_NODE_TYPES):
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raise ValueError(f"Unsafe predicate node: {type(node).__name__}")
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for child in ast.iter_child_nodes(node):
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_validate_node(child)
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class DotDict:
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"""Helper class that allows dict access via dot notation."""
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def __init__(self, data: Dict[str, Any]):
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self.__dict__.update(data)
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def _build_context(fused: Dict[str, Any], dominant: list):
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"""Build safe evaluation context with helpers and fused symbol fields."""
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def dominant_contains(glyph_id: str) -> bool:
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"""Check if a glyph is in the dominant list."""
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return any(g == glyph_id for g, _ in dominant)
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safe = {
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"dominant_contains": dominant_contains,
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"fused": DotDict(fused or {}),
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}
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return safe
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def eval_predicate(
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expr: str,
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fused: Dict[str, Any] | None = None,
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dominant: list | None = None
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) -> bool:
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"""
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Evaluate predicate expression safely.
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Example predicates:
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"fused.global_resonance_score > 0.7"
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"dominant_contains('glyph://entropy') and fused.global_resonance_score > 0.5"
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Args:
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expr: Predicate expression string
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fused: Fused symbol dict with fields like global_resonance_score, glyph_ids
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dominant: List of (glyph_id, weight) tuples for dominant glyphs
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Returns:
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Boolean result of predicate evaluation
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"""
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if dominant is None:
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dominant = []
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# Parse and validate AST
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try:
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expr_ast = ast.parse(expr, mode="eval")
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except SyntaxError as e:
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raise ValueError(f"Invalid predicate syntax: {e}")
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_validate_node(expr_ast)
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# Compile and evaluate
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compiled = compile(expr_ast, "<predicate>", "eval")
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safe_ctx = _build_context(fused or {}, dominant)
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try:
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return bool(eval(compiled, {}, safe_ctx))
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except Exception as e:
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raise ValueError(f"Predicate evaluation error: {e}")
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