Implement XIC v2 control flow with IF, MATCH, LOOP operations
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
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GlyphRunner System
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"""
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Unit tests for XIC v2 control flow (IF, MATCH, LOOP).
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Tests predicate evaluation, control operations, and guardrails.
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"""
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import pytest
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import sys
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from pathlib import Path
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# Add parent directory to path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from xic_ops import XICContext, op_IF, op_MATCH, op_LOOP, op_PUSH_GLYPH_CONTEXT, op_CALL_GLYPH
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from glyphos.control.predicate import eval_predicate
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from glyphos.symbolic_pipeline import SymbolicPipelineResult, FusedSymbol, GlyphResonanceMap, GlyphResonanceMetrics
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def create_fake_pipeline_result(global_score: float = 0.9, glyph_ids: list = None):
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"""Helper to create a fake symbolic pipeline result for testing."""
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if glyph_ids is None:
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glyph_ids = ["glyph://a", "glyph://b"]
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# Create fake resonance map
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resonance_map = GlyphResonanceMap(global_resonance_score=global_score)
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for glyph_id in glyph_ids:
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resonance_map.resonances[glyph_id] = GlyphResonanceMetrics(
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weight=0.8,
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lineage_score=0.7,
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contributor_score=0.75,
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frequency_score=0.8,
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grammar_score=0.85,
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)
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fused = FusedSymbol(
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summary="Test output",
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glyph_ids=glyph_ids,
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resonance_map=resonance_map,
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)
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return SymbolicPipelineResult(
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steps=[],
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output_text="Test output",
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fused_symbol=fused,
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)
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class TestPredicateEvaluator:
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"""Test safe predicate evaluation."""
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def test_simple_comparison(self):
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"""Test simple numeric comparison."""
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fused = {"global_resonance_score": 0.9}
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result = eval_predicate("fused.global_resonance_score > 0.8", fused)
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assert result is True
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def test_comparison_false(self):
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"""Test comparison that evaluates to False."""
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fused = {"global_resonance_score": 0.5}
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result = eval_predicate("fused.global_resonance_score > 0.8", fused)
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assert result is False
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def test_boolean_and(self):
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"""Test AND operator."""
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fused = {"global_resonance_score": 0.9, "count": 3}
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result = eval_predicate(
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"fused.global_resonance_score > 0.8 and fused.count > 2",
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fused
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)
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assert result is True
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def test_boolean_or(self):
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"""Test OR operator."""
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fused = {"global_resonance_score": 0.5}
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result = eval_predicate(
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"fused.global_resonance_score > 0.8 or fused.global_resonance_score > 0.4",
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fused
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)
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assert result is True
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def test_dominant_contains(self):
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"""Test dominant_contains helper function."""
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dominant = [("glyph://entropy", 0.95), ("glyph://compression", 0.8)]
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result = eval_predicate(
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"dominant_contains('glyph://entropy')",
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{},
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dominant
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)
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assert result is True
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def test_dominant_contains_not_found(self):
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"""Test dominant_contains when glyph not present."""
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dominant = [("glyph://entropy", 0.95)]
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result = eval_predicate(
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"dominant_contains('glyph://other')",
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{},
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dominant
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)
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assert result is False
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def test_unsafe_import(self):
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"""Test that import statements are blocked."""
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with pytest.raises(ValueError):
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eval_predicate("__import__('os')")
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def test_syntax_error(self):
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"""Test handling of syntax errors."""
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with pytest.raises(ValueError, match="Invalid predicate syntax"):
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eval_predicate("fused.score >")
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class TestIFOperation:
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"""Test IF control flow operation."""
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def test_if_then_true(self):
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"""Test IF with true condition and then branch."""
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ctx = XICContext()
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(global_score=0.9)
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op_IF(ctx, "fused.global_resonance_score > 0.8", "then_chain", "else_chain")
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assert ctx.pop_next_chain() == "then_chain"
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assert ctx.pop_next_chain() is None
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def test_if_else_true(self):
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"""Test IF with false condition and else branch."""
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ctx = XICContext()
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(global_score=0.5)
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op_IF(ctx, "fused.global_resonance_score > 0.8", "then_chain", "else_chain")
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assert ctx.pop_next_chain() == "else_chain"
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def test_if_no_else(self):
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"""Test IF without else branch."""
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ctx = XICContext()
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(global_score=0.5)
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op_IF(ctx, "fused.global_resonance_score > 0.8", "then_chain")
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assert ctx.pop_next_chain() is None
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def test_if_logs_control_step(self):
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"""Test that IF logs control steps for observability."""
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ctx = XICContext()
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(global_score=0.9)
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op_IF(ctx, "fused.global_resonance_score > 0.8", "then_chain")
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control_steps = ctx._state.get("control_steps", [])
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assert len(control_steps) > 0
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assert control_steps[0]["type"] == "if"
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assert control_steps[0]["result"] is True
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def test_if_with_dominant_contains(self):
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"""Test IF using dominant_contains helper."""
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ctx = XICContext()
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result = create_fake_pipeline_result(glyph_ids=["glyph://entropy", "glyph://compression"])
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ctx._state["last_symbolic_pipeline"] = result
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op_IF(ctx, "dominant_contains('glyph://entropy')", "found_chain")
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assert ctx.pop_next_chain() == "found_chain"
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class TestMATCHOperation:
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"""Test MATCH control flow operation."""
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def test_match_glyph_ids_found(self):
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"""Test MATCH when pattern is found in glyph_ids."""
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ctx = XICContext()
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(
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glyph_ids=["glyph://a", "glyph://b", "glyph://c"]
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)
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op_MATCH(ctx, "fused.glyph_ids", "glyph://b", "found_chain")
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assert ctx.pop_next_chain() == "found_chain"
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def test_match_glyph_ids_not_found(self):
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"""Test MATCH when pattern is not in glyph_ids."""
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ctx = XICContext()
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(
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glyph_ids=["glyph://a", "glyph://b"]
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)
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op_MATCH(ctx, "fused.glyph_ids", "glyph://x", "found_chain")
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assert ctx.pop_next_chain() is None
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def test_match_logs_step(self):
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"""Test that MATCH logs symbolic steps."""
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ctx = XICContext()
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result()
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op_MATCH(ctx, "fused.glyph_ids", "glyph://a", "chain")
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steps = ctx._state.get("symbolic_steps", [])
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assert any(s["kind"] == "control_match" for s in steps)
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class TestLOOPOperation:
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"""Test LOOP control flow operation."""
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def test_loop_iterations(self):
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"""Test LOOP schedules multiple iterations."""
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ctx = XICContext()
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ctx.params["max_loop_iterations"] = 3
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# Create a pipeline that will be true for the loop condition
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(global_score=1.0)
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op_LOOP(ctx, "fused.global_resonance_score > 0.5", "body_chain", 3)
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# Should have enqueued 3 iterations
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chains = []
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while True:
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c = ctx.pop_next_chain()
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if c is None:
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break
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chains.append(c)
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assert chains == ["body_chain", "body_chain", "body_chain"]
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def test_loop_predicate_false(self):
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"""Test LOOP stops when predicate is false."""
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ctx = XICContext()
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(global_score=0.3)
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op_LOOP(ctx, "fused.global_resonance_score > 0.8", "body_chain", 10)
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# Should not enqueue anything
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assert ctx.pop_next_chain() is None
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def test_loop_max_iterations_guardrail(self):
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"""Test LOOP guardrail triggers at max iterations."""
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ctx = XICContext()
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ctx.params["max_loop_iterations"] = 2
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(global_score=1.0)
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op_LOOP(ctx, "fused.global_resonance_score > 0.5", "body_chain", 2)
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# Should trigger guardrail
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guardrails = ctx._state.get("guardrails", [])
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assert "max_loop_iterations_exceeded" in guardrails
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def test_loop_max_total_steps_guardrail(self):
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"""Test LOOP respects max_total_steps guardrail."""
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ctx = XICContext()
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ctx.params["max_total_steps"] = 5
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ctx._state["total_steps"] = 5 # Already at limit
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(global_score=1.0)
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op_LOOP(ctx, "fused.global_resonance_score > 0.5", "body_chain", 10)
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# Should trigger guardrail immediately
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guardrails = ctx._state.get("guardrails", [])
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assert "max_total_steps_exceeded" in guardrails
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# Should not enqueue any chains
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assert ctx.pop_next_chain() is None
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def test_loop_emits_steps(self):
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"""Test LOOP emits symbolic steps for each iteration."""
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ctx = XICContext()
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ctx.params["max_loop_iterations"] = 2
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(global_score=1.0)
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op_LOOP(ctx, "fused.global_resonance_score > 0.5", "body_chain", 2)
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steps = ctx._state.get("symbolic_steps", [])
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loop_steps = [s for s in steps if s["kind"] == "control_loop"]
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assert len(loop_steps) >= 2
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class TestQueueHelpers:
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"""Test XICContext queue helper methods."""
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def test_enqueue_chain(self):
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"""Test enqueue_chain adds to queue."""
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ctx = XICContext()
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ctx.enqueue_chain("chain1")
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assert ctx.pop_next_chain() == "chain1"
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def test_fifo_order(self):
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"""Test chains dequeue in FIFO order."""
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ctx = XICContext()
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ctx.enqueue_chain("chain1")
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ctx.enqueue_chain("chain2")
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ctx.enqueue_chain("chain3")
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assert ctx.pop_next_chain() == "chain1"
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assert ctx.pop_next_chain() == "chain2"
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assert ctx.pop_next_chain() == "chain3"
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assert ctx.pop_next_chain() is None
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def test_jump_to(self):
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"""Test jump_to clears and replaces queue."""
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ctx = XICContext()
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ctx.enqueue_chain("chain1")
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ctx.enqueue_chain("chain2")
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ctx.jump_to("chain3")
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# Should only have chain3
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assert ctx.pop_next_chain() == "chain3"
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assert ctx.pop_next_chain() is None
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def test_pop_empty_queue(self):
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"""Test pop_next_chain on empty queue returns None."""
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ctx = XICContext()
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assert ctx.pop_next_chain() is None
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class TestIntegration:
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"""Integration tests combining multiple operations."""
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def test_if_with_call_glyph(self):
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"""Test IF depends on CALL_GLYPH result."""
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ctx = XICContext()
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ctx.symbolic_mode = True
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# Simulate CALL_GLYPH execution (would set last_symbolic_pipeline)
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(global_score=0.95)
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# IF should work with the result
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op_IF(ctx, "fused.global_resonance_score > 0.9", "high_resonance")
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assert ctx.pop_next_chain() == "high_resonance"
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def test_guardrail_enforcement(self):
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"""Test that guardrails stop execution."""
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ctx = XICContext()
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ctx._state["guardrails"] = ["max_total_steps_exceeded"]
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ctx.params["max_total_steps"] = 10
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ctx._state["total_steps"] = 10
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# LOOP should respect the guardrail
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result(global_score=1.0)
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op_LOOP(ctx, "fused.global_resonance_score > 0.5", "body", 100)
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# No chains should be enqueued due to guardrail
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assert ctx.pop_next_chain() is None
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class TestErrorHandling:
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"""Test error handling in control flow."""
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def test_if_without_pipeline(self):
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"""Test IF gracefully handles missing pipeline."""
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ctx = XICContext()
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# No pipeline set
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op_IF(ctx, "fused.global_resonance_score > 0.5", "then")
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# Should complete without error, but not enqueue (predicate fails safely)
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assert True # Successfully didn't crash
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def test_malformed_predicate(self):
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"""Test that malformed predicates are caught."""
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ctx = XICContext()
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result()
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# Invalid syntax
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op_IF(ctx, "fused.score >", "then")
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# Should handle error gracefully (may not enqueue)
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assert True # Successfully didn't crash
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def test_loop_with_bad_predicate(self):
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"""Test LOOP handles predicate evaluation errors."""
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ctx = XICContext()
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ctx._state["last_symbolic_pipeline"] = create_fake_pipeline_result()
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op_LOOP(ctx, "fused.nonexistent > 0.5", "body", 2)
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# Should handle error gracefully
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assert True # Successfully didn't crash
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if __name__ == "__main__":
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pytest.main([__file__, "-v", "--tb=short"])
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