#!/usr/bin/env python3
"""
Test the Multilingual Triangulation Probe

First test: "consciousness" concept
- Ground: EN, ZH, AR
- Deepen: DE (Bewusstsein)
- Triangulate: back to EN
"""
import sys
sys.path.insert(0, '.')

from nyx_probing.core.model import NyxModel
from nyx_probing.probes.multilingual_probe import (
    MultilingualTriangulationProbe,
    LANGUAGES,
    LanguageZone,
)

print("=" * 70)
print("🌙 MULTILINGUAL TRIANGULATION PROBE TEST")
print("=" * 70)

# Test concepts with translations
CONCEPTS = {
    "consciousness": {
        "EN": "consciousness",
        "DE": "Bewusstsein",
        "ZH": "意识",
        "AR": "الوعي",
        "FR": "conscience",
    },
    "heart": {
        "EN": "heart",
        "DE": "Herz",
        "ZH": "心",
        "AR": "قلب",
        "FR": "cœur",
    },
    "emergence": {
        "EN": "emergence",
        "DE": "Entstehung",
        "ZH": "涌现",
        "AR": "ظهور",
        "FR": "émergence",
    },
    "being": {
        "EN": "being",
        "DE": "Sein",
        "ZH": "存在",
        "AR": "كينونة",
        "FR": "être",
    },
}

# Load model
print("\n📦 Loading model...")
model = NyxModel()
model.load()

# Create probe
print("\n🔬 Creating triangulation probe...")
probe = MultilingualTriangulationProbe(
    model,
    grounding_languages=["EN", "ZH", "AR"],
    deepening_language="DE",
    triangulation_target="EN",
)

# Test each concept
print("\n" + "=" * 70)
print("🧪 RUNNING TRIANGULATION TESTS")
print("=" * 70)

results = []
for concept_name, translations in CONCEPTS.items():
    print(f"\n{'─' * 70}")
    print(f"Testing: {concept_name.upper()}")
    print('─' * 70)
    
    try:
        result = probe.probe(concept_name, translations)
        results.append(result)
        
        # Print summary
        print(probe.summary(result))
        
        # Print some details
        print(f"\n  Deepening completion preview:")
        print(f"  '{result.deepening.completion[:100]}...'")
        
        print(f"\n  Triangulation completion:")
        print(f"  Prompt: '{result.triangulation.translation_prompt}'")
        print(f"  Output: '{result.triangulation.model_completion[:100]}...'")
        
    except Exception as e:
        print(f"  ERROR: {e}")
        import traceback
        traceback.print_exc()

# Summary table
print("\n" + "=" * 70)
print("📊 SUMMARY TABLE")
print("=" * 70)

print(f"\n{'Concept':<15} | {'Grounding':<10} | {'Depth':<6} | {'Valley':<12} | {'Transfer':<10} | {'Recommendation'}")
print("-" * 100)

for r in results:
    print(f"{r.concept:<15} | {r.grounding.average_convergence:.3f}     | {r.deepening.depth_score}/3    | {r.deepening.valley_type:<12} | {'✓' if r.depth_transferable else '✗':<10} | {r.curriculum_recommendation[:30]}")

# Final analysis
print("\n" + "=" * 70)
print("🌙 CURRICULUM IMPLICATIONS")
print("=" * 70)

# Group by recommendation
high_depth = [r for r in results if r.depth_accessible and r.depth_transferable]
needs_work = [r for r in results if not r.depth_accessible]
needs_bridge = [r for r in results if r.depth_accessible and not r.depth_transferable]

if high_depth:
    print(f"\n✅ READY FOR MULTILINGUAL CURRICULUM:")
    for r in high_depth:
        print(f"   - {r.concept}: {r.curriculum_recommendation}")

if needs_bridge:
    print(f"\n⚠️  NEEDS BRIDGING (depth accessible but not transferable):")
    for r in needs_bridge:
        print(f"   - {r.concept}: depth={r.deepening.depth_score} but transfer failed")

if needs_work:
    print(f"\n❌ NEEDS GROUNDING FIRST:")
    for r in needs_work:
        print(f"   - {r.concept}: depth only {r.deepening.depth_score}/3")

print("\n" + "=" * 70)
print("✅ TRIANGULATION PROBE TEST COMPLETE")
print("=" * 70)