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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# XIC v2 Control Flow Implementation - Complete Summary
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**Date**: 2026-05-21
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**Status**: ✅ **COMPLETE & TESTED**
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**Test Results**: 36/36 tests passing (FedMart + UI + Control Flow)
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---
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## Overview
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Successfully implemented XIC v2 control flow with **IF**, **MATCH**, and **LOOP** operations. The system adds conditional branching, pattern matching, and iterative execution to XIC v1.5 while maintaining full backward compatibility.
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---
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## What Was Implemented
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### 1. Safe Predicate Evaluator (`glyphos/control/predicate.py`)
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- Safe AST-based expression evaluation
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- Prevents dangerous operations (imports, system calls)
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- Supports:
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- Comparisons: `>`, `<`, `>=`, `<=`, `==`, `!=`
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- Boolean operators: `and`, `or`, `not`
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- Attribute access: `fused.global_resonance_score`
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- Helper functions: `dominant_contains('glyph://id')`
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**Example Predicates:**
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```python
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"fused.global_resonance_score > 0.8"
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"dominant_contains('glyph://entropy') and fused.global_resonance_score > 0.5"
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"fused.glyph_count >= 3"
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```
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### 2. XICContext Queue Helpers
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Three new methods added to `XICContext` class:
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```python
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def enqueue_chain(self, label: str):
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"""Schedule a chain/label to run next (FIFO)."""
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def pop_next_chain(self):
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"""Get next scheduled chain (FIFO). Returns None if queue empty."""
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def jump_to(self, label: str):
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"""Immediate jump: clear queue and run label next."""
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```
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### 3. Control Flow Operations
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#### `IF` - Conditional Branching
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```
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IF <predicate> <then_label> [<else_label>]
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```
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- Evaluates predicate against last symbolic pipeline result
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- Enqueues then_label if true, else_label if false (optional)
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- Logs control steps for observability
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**Example:**
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```json
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{"op": "IF", "args": ["fused.global_resonance_score > 0.8", "high_resonance", "low_resonance"]}
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```
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#### `MATCH` - Pattern Matching
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```
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MATCH <path> <pattern> <then_label>
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```
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- Pattern matches against fused_symbol fields
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- Currently supports `fused.glyph_ids` (checks if pattern is in list)
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- Enqueues then_label if pattern matches
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**Example:**
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```json
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{"op": "MATCH", "args": ["fused.glyph_ids", "glyph://entropy", "found_entropy"]}
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```
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#### `LOOP` - Iterative Execution
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```
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LOOP <predicate> <body_label> [max_iter]
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```
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- Repeatedly enqueues body_label while predicate is true
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- Enforces guardrails:
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- `max_loop_iterations`: max iterations per LOOP (default: 50)
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- `max_total_steps`: max total steps for entire program (default: 1000)
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- Emits symbolic steps for each iteration
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**Example:**
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```json
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{
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"op": "SET_PARAM",
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"args": ["max_loop_iterations", 5]
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},
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{
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"op": "LOOP",
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"args": ["fused.global_resonance_score > 0.6", "body_chain", 5]
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}
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```
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### 4. Modified Execution Loop (`xic_vm.py`)
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Enhanced `run_xic_program()` to:
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- Handle chain queue scheduling with `pop_next_chain()`
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- Track `total_steps` for guardrail enforcement
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- Find and jump to CHAIN instructions by label
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- Enforce `max_total_steps` limit
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- Stop execution if guardrails are triggered
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---
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## File Summary
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| File | Type | Change | Status |
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|------|------|--------|--------|
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| `glyphos/control/predicate.py` | New | Safe predicate evaluator | ✅ 78 LOC |
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| `glyphos/control/__init__.py` | New | Package init | ✅ Empty |
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| `xic_ops.py` | Modified | +Queue helpers, +3 control ops | ✅ 608 → 773 LOC |
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| `xic_vm.py` | Modified | +Chain queue handling | ✅ 31 → 60 LOC |
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| `tests/test_control_flow.py` | New | 14 unit tests | ✅ 377 LOC |
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| `programs/demo_control_flow_if.gx.json` | New | IF demo program | ✅ Created |
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| `programs/demo_control_flow_loop.gx.json` | New | LOOP demo program | ✅ Created |
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---
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## Test Results
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### Control Flow Tests (14 passing)
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```
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✅ Predicate: simple comparison
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✅ Predicate: false comparison
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✅ Predicate: AND operator
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✅ Predicate: dominant_contains
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✅ IF: then branch
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✅ IF: else branch
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✅ IF: no else
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✅ MATCH: pattern found
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✅ MATCH: pattern not found
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✅ LOOP: iterations
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✅ LOOP: false condition
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✅ LOOP: max iterations guardrail
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✅ Queue: FIFO order
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✅ Queue: jump_to
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```
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### Full Test Suite (36/36 passing)
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- **FedMart Integration**: 12/12 ✅
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- **UI Integration**: 10/10 ✅
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- **Control Flow**: 14/14 ✅
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---
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## Usage Guide
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### 1. IF Control Flow Example
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```json
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{
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"magic": "GXIC1",
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"version": 1,
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"entrypoint": "main",
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"symbols": {
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"main": 0,
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"high_resonance": 5,
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"low_resonance": 8,
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"end": 10
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},
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"instructions": [
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{"op": "SET_MODE", "args": ["symbolic"]},
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{"op": "SET_CONTEXT", "args": ["domain", "analysis"]},
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{"op": "PUSH_GLYPH_CONTEXT", "args": ["glyph://a"]},
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{"op": "PUSH_GLYPH_CONTEXT", "args": ["glyph://b"]},
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{"op": "RUN_PROMPT", "args": ["Analyze the relationship"]},
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{"op": "IF", "args": ["fused.global_resonance_score > 0.8", "high_resonance", "low_resonance"]},
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{"op": "CHAIN", "args": ["high_resonance"]},
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{"op": "LOG", "args": ["High resonance path"]},
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{"op": "CHAIN", "args": ["end"]},
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{"op": "CHAIN", "args": ["low_resonance"]},
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{"op": "LOG", "args": ["Low resonance path"]},
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{"op": "CHAIN", "args": ["end"]},
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{"op": "CHAIN", "args": ["end"]},
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{"op": "LOG", "args": ["Done"]}
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]
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}
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```
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### 2. LOOP Control Flow Example
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```json
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{
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"instructions": [
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{"op": "SET_MODE", "args": ["symbolic"]},
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{"op": "SET_PARAM", "args": ["max_loop_iterations", 5]},
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{"op": "LOOP", "args": ["fused.global_resonance_score > 0.6", "body", 5]},
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{"op": "CHAIN", "args": ["body"]},
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{"op": "RUN_PROMPT", "args": ["Refine analysis"]},
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{"op": "CHAIN", "args": ["end"]},
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{"op": "CHAIN", "args": ["end"]},
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{"op": "LOG", "args": ["Complete"]}
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]
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}
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```
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### 3. Using Predicates
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**Simple comparisons:**
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```
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"fused.global_resonance_score > 0.8"
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"fused.glyph_count >= 2"
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```
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**Boolean operators:**
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```
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"fused.global_resonance_score > 0.8 and fused.glyph_count > 1"
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"fused.global_resonance_score > 0.7 or fused.global_resonance_score < 0.3"
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```
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**Helper functions:**
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```
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"dominant_contains('glyph://compression')"
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"dominant_contains('glyph://entropy') and fused.global_resonance_score > 0.5"
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```
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---
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## Backward Compatibility
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✅ **100% Backward Compatible**
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- No changes to .gx binary format
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- No changes to glyph ontology
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- New operations are optional
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- Existing XIC v1.5 programs run unchanged
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- New operations integrate seamlessly
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---
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## Guardrails & Safety
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### Built-in Guardrails
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1. **max_loop_iterations** (default: 50)
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- Prevents infinite loops
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- Configurable via `SET_PARAM`
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2. **max_total_steps** (default: 1000)
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- Limits total program execution
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- Enforced across IF/LOOP/RUN_PROMPT
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- Prevents resource exhaustion
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3. **Predicate Safety**
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- AST validation prevents code injection
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- No system calls, imports, or __builtins__
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- Only safe comparisons and helpers allowed
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### Guardrail Triggering
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When a guardrail is triggered:
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- Logged to `ctx._state["guardrails"]`
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- Emitted as SymbolicStep with kind="guardrail"
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- Execution stops gracefully
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- FedMart telemetry captures event
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---
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## Integration Points
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### With FedMart Telemetry
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- Control flow steps logged as SymbolicStep objects
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- Guardrail events captured in telemetry
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- Dashboard shows control flow execution in timeline
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### With UI Dashboard
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- Timeline displays IF/MATCH/LOOP steps
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- Control flow branching visible in step sequence
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- Guardrail enforcement shown in alerts
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### With Symbolic Pipeline
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- Predicates evaluated against last pipeline result
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- Fused symbol fields accessible in all predicates
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- Dominant glyphs helper function built-in
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---
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## Advanced Features
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### Custom Predicate Evaluation
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```python
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from glyphos.control.predicate import eval_predicate
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result = eval_predicate(
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"fused.global_resonance_score > 0.7 and dominant_contains('glyph://entropy')",
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fused={"global_resonance_score": 0.85},
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dominant=[("glyph://entropy", 0.95), ("glyph://compression", 0.8)]
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)
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# Returns: True
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```
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### Queue Management
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```python
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ctx = XICContext()
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ctx.enqueue_chain("analysis_1")
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ctx.enqueue_chain("analysis_2")
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next_chain = ctx.pop_next_chain() # Returns: "analysis_1"
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# Jump immediately to a different chain
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ctx.jump_to("emergency_shutdown")
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```
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---
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## Future Enhancements
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### Recommended for v3.0
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1. **Extended Pattern Matching** - Support more complex path expressions
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2. **Custom Predicates** - Register custom predicate functions
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3. **Loop Optimization** - Cache predicate results within iterations
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4. **Control Flow Visualization** - Graph rendering in dashboard
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5. **Debugging Support** - Breakpoints in control flow
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6. **Performance Profiling** - Time each control branch
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---
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## Verification Checklist
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- [x] Predicate evaluator is secure (AST validation)
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- [x] Queue helpers work correctly (FIFO, jump)
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- [x] IF operation branches properly
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- [x] MATCH operation pattern matches
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- [x] LOOP operation iterates and respects limits
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- [x] Execution loop handles chain scheduling
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- [x] Guardrails are enforced
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- [x] Symbolic steps are emitted
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- [x] FedMart telemetry integration works
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- [x] All 36 tests passing
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- [x] Backward compatibility maintained
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- [x] Example programs created
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- [x] Documentation complete
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---
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## Files Modified/Created
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### New Files
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```
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glyphos/control/predicate.py (78 lines)
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glyphos/control/__init__.py (0 lines)
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tests/test_control_flow.py (377 lines)
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programs/demo_control_flow_if.gx.json (example)
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programs/demo_control_flow_loop.gx.json (example)
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```
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### Modified Files
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```
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xic_ops.py (165 lines added)
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xic_vm.py (29 lines modified)
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```
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---
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## Conclusion
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XIC v2 control flow is **complete, tested, and production-ready**. The implementation provides:
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✅ Safe predicate evaluation with AST validation
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✅ Three control flow operations (IF, MATCH, LOOP)
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✅ Queue-based chain scheduling
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✅ Comprehensive guardrail enforcement
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✅ Full integration with FedMart telemetry
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✅ Real-time UI visualization
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✅ 100% backward compatibility
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✅ 36/36 tests passing
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Ready for immediate use in XIC programs.
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---
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**Status**: ✅ **PRODUCTION READY**
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**Version**: XIC v2.0
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**Date**: 2026-05-21
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