2125_GCE/XIC_V2_CONTROL_FLOW_SUMMARY.md

# XIC v2 Control Flow Implementation - Complete Summary

**Date**: 2026-05-21  
**Status**: ✅ **COMPLETE & TESTED**  
**Test Results**: 36/36 tests passing (FedMart + UI + Control Flow)

---

## Overview

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.

---

## What Was Implemented

### 1. Safe Predicate Evaluator (`glyphos/control/predicate.py`)
- Safe AST-based expression evaluation
- Prevents dangerous operations (imports, system calls)
- Supports:
  - Comparisons: `>`, `<`, `>=`, `<=`, `==`, `!=`
  - Boolean operators: `and`, `or`, `not`
  - Attribute access: `fused.global_resonance_score`
  - Helper functions: `dominant_contains('glyph://id')`

**Example Predicates:**
```python
"fused.global_resonance_score > 0.8"
"dominant_contains('glyph://entropy') and fused.global_resonance_score > 0.5"
"fused.glyph_count >= 3"
```

### 2. XICContext Queue Helpers
Three new methods added to `XICContext` class:

```python
def enqueue_chain(self, label: str):
    """Schedule a chain/label to run next (FIFO)."""

def pop_next_chain(self):
    """Get next scheduled chain (FIFO). Returns None if queue empty."""

def jump_to(self, label: str):
    """Immediate jump: clear queue and run label next."""
```

### 3. Control Flow Operations

#### `IF` - Conditional Branching
```
IF <predicate> <then_label> [<else_label>]
```
- Evaluates predicate against last symbolic pipeline result
- Enqueues then_label if true, else_label if false (optional)
- Logs control steps for observability

**Example:**
```json
{"op": "IF", "args": ["fused.global_resonance_score > 0.8", "high_resonance", "low_resonance"]}
```

#### `MATCH` - Pattern Matching
```
MATCH <path> <pattern> <then_label>
```
- Pattern matches against fused_symbol fields
- Currently supports `fused.glyph_ids` (checks if pattern is in list)
- Enqueues then_label if pattern matches

**Example:**
```json
{"op": "MATCH", "args": ["fused.glyph_ids", "glyph://entropy", "found_entropy"]}
```

#### `LOOP` - Iterative Execution
```
LOOP <predicate> <body_label> [max_iter]
```
- Repeatedly enqueues body_label while predicate is true
- Enforces guardrails:
  - `max_loop_iterations`: max iterations per LOOP (default: 50)
  - `max_total_steps`: max total steps for entire program (default: 1000)
- Emits symbolic steps for each iteration

**Example:**
```json
{
  "op": "SET_PARAM",
  "args": ["max_loop_iterations", 5]
},
{
  "op": "LOOP",
  "args": ["fused.global_resonance_score > 0.6", "body_chain", 5]
}
```

### 4. Modified Execution Loop (`xic_vm.py`)
Enhanced `run_xic_program()` to:
- Handle chain queue scheduling with `pop_next_chain()`
- Track `total_steps` for guardrail enforcement
- Find and jump to CHAIN instructions by label
- Enforce `max_total_steps` limit
- Stop execution if guardrails are triggered

---

## File Summary

| File | Type | Change | Status |
|------|------|--------|--------|
| `glyphos/control/predicate.py` | New | Safe predicate evaluator | ✅ 78 LOC |
| `glyphos/control/__init__.py` | New | Package init | ✅ Empty |
| `xic_ops.py` | Modified | +Queue helpers, +3 control ops | ✅ 608 → 773 LOC |
| `xic_vm.py` | Modified | +Chain queue handling | ✅ 31 → 60 LOC |
| `tests/test_control_flow.py` | New | 14 unit tests | ✅ 377 LOC |
| `programs/demo_control_flow_if.gx.json` | New | IF demo program | ✅ Created |
| `programs/demo_control_flow_loop.gx.json` | New | LOOP demo program | ✅ Created |

---

## Test Results

### Control Flow Tests (14 passing)
```
✅ Predicate: simple comparison
✅ Predicate: false comparison
✅ Predicate: AND operator
✅ Predicate: dominant_contains
✅ IF: then branch
✅ IF: else branch
✅ IF: no else
✅ MATCH: pattern found
✅ MATCH: pattern not found
✅ LOOP: iterations
✅ LOOP: false condition
✅ LOOP: max iterations guardrail
✅ Queue: FIFO order
✅ Queue: jump_to
```

### Full Test Suite (36/36 passing)
- **FedMart Integration**: 12/12 ✅
- **UI Integration**: 10/10 ✅
- **Control Flow**: 14/14 ✅

---

## Usage Guide

### 1. IF Control Flow Example

```json
{
  "magic": "GXIC1",
  "version": 1,
  "entrypoint": "main",
  "symbols": {
    "main": 0,
    "high_resonance": 5,
    "low_resonance": 8,
    "end": 10
  },
  "instructions": [
    {"op": "SET_MODE", "args": ["symbolic"]},
    {"op": "SET_CONTEXT", "args": ["domain", "analysis"]},
    {"op": "PUSH_GLYPH_CONTEXT", "args": ["glyph://a"]},
    {"op": "PUSH_GLYPH_CONTEXT", "args": ["glyph://b"]},
    {"op": "RUN_PROMPT", "args": ["Analyze the relationship"]},
    {"op": "IF", "args": ["fused.global_resonance_score > 0.8", "high_resonance", "low_resonance"]},
    {"op": "CHAIN", "args": ["high_resonance"]},
    {"op": "LOG", "args": ["High resonance path"]},
    {"op": "CHAIN", "args": ["end"]},
    {"op": "CHAIN", "args": ["low_resonance"]},
    {"op": "LOG", "args": ["Low resonance path"]},
    {"op": "CHAIN", "args": ["end"]},
    {"op": "CHAIN", "args": ["end"]},
    {"op": "LOG", "args": ["Done"]}
  ]
}
```

### 2. LOOP Control Flow Example

```json
{
  "instructions": [
    {"op": "SET_MODE", "args": ["symbolic"]},
    {"op": "SET_PARAM", "args": ["max_loop_iterations", 5]},
    {"op": "LOOP", "args": ["fused.global_resonance_score > 0.6", "body", 5]},
    {"op": "CHAIN", "args": ["body"]},
    {"op": "RUN_PROMPT", "args": ["Refine analysis"]},
    {"op": "CHAIN", "args": ["end"]},
    {"op": "CHAIN", "args": ["end"]},
    {"op": "LOG", "args": ["Complete"]}
  ]
}
```

### 3. Using Predicates

**Simple comparisons:**
```
"fused.global_resonance_score > 0.8"
"fused.glyph_count >= 2"
```

**Boolean operators:**
```
"fused.global_resonance_score > 0.8 and fused.glyph_count > 1"
"fused.global_resonance_score > 0.7 or fused.global_resonance_score < 0.3"
```

**Helper functions:**
```
"dominant_contains('glyph://compression')"
"dominant_contains('glyph://entropy') and fused.global_resonance_score > 0.5"
```

---

## Backward Compatibility

✅ **100% Backward Compatible**
- No changes to .gx binary format
- No changes to glyph ontology
- New operations are optional
- Existing XIC v1.5 programs run unchanged
- New operations integrate seamlessly

---

## Guardrails & Safety

### Built-in Guardrails
1. **max_loop_iterations** (default: 50)
   - Prevents infinite loops
   - Configurable via `SET_PARAM`

2. **max_total_steps** (default: 1000)
   - Limits total program execution
   - Enforced across IF/LOOP/RUN_PROMPT
   - Prevents resource exhaustion

3. **Predicate Safety**
   - AST validation prevents code injection
   - No system calls, imports, or __builtins__
   - Only safe comparisons and helpers allowed

### Guardrail Triggering
When a guardrail is triggered:
- Logged to `ctx._state["guardrails"]`
- Emitted as SymbolicStep with kind="guardrail"
- Execution stops gracefully
- FedMart telemetry captures event

---

## Integration Points

### With FedMart Telemetry
- Control flow steps logged as SymbolicStep objects
- Guardrail events captured in telemetry
- Dashboard shows control flow execution in timeline

### With UI Dashboard
- Timeline displays IF/MATCH/LOOP steps
- Control flow branching visible in step sequence
- Guardrail enforcement shown in alerts

### With Symbolic Pipeline
- Predicates evaluated against last pipeline result
- Fused symbol fields accessible in all predicates
- Dominant glyphs helper function built-in

---

## Advanced Features

### Custom Predicate Evaluation
```python
from glyphos.control.predicate import eval_predicate

result = eval_predicate(
    "fused.global_resonance_score > 0.7 and dominant_contains('glyph://entropy')",
    fused={"global_resonance_score": 0.85},
    dominant=[("glyph://entropy", 0.95), ("glyph://compression", 0.8)]
)
# Returns: True
```

### Queue Management
```python
ctx = XICContext()
ctx.enqueue_chain("analysis_1")
ctx.enqueue_chain("analysis_2")
next_chain = ctx.pop_next_chain()  # Returns: "analysis_1"

# Jump immediately to a different chain
ctx.jump_to("emergency_shutdown")
```

---

## Future Enhancements

### Recommended for v3.0
1. **Extended Pattern Matching** - Support more complex path expressions
2. **Custom Predicates** - Register custom predicate functions
3. **Loop Optimization** - Cache predicate results within iterations
4. **Control Flow Visualization** - Graph rendering in dashboard
5. **Debugging Support** - Breakpoints in control flow
6. **Performance Profiling** - Time each control branch

---

## Verification Checklist

- [x] Predicate evaluator is secure (AST validation)
- [x] Queue helpers work correctly (FIFO, jump)
- [x] IF operation branches properly
- [x] MATCH operation pattern matches
- [x] LOOP operation iterates and respects limits
- [x] Execution loop handles chain scheduling
- [x] Guardrails are enforced
- [x] Symbolic steps are emitted
- [x] FedMart telemetry integration works
- [x] All 36 tests passing
- [x] Backward compatibility maintained
- [x] Example programs created
- [x] Documentation complete

---

## Files Modified/Created

### New Files
```
glyphos/control/predicate.py          (78 lines)
glyphos/control/__init__.py           (0 lines)
tests/test_control_flow.py            (377 lines)
programs/demo_control_flow_if.gx.json (example)
programs/demo_control_flow_loop.gx.json (example)
```

### Modified Files
```
xic_ops.py   (165 lines added)
xic_vm.py    (29 lines modified)
```

---

## Conclusion

XIC v2 control flow is **complete, tested, and production-ready**. The implementation provides:

✅ Safe predicate evaluation with AST validation  
✅ Three control flow operations (IF, MATCH, LOOP)  
✅ Queue-based chain scheduling  
✅ Comprehensive guardrail enforcement  
✅ Full integration with FedMart telemetry  
✅ Real-time UI visualization  
✅ 100% backward compatibility  
✅ 36/36 tests passing  

Ready for immediate use in XIC programs.

---

**Status**: ✅ **PRODUCTION READY**  
**Version**: XIC v2.0  
**Date**: 2026-05-21