#!/usr/bin/env python3
"""
Mass Dissection — All models on remote node
CSCI v1.0 — Cross-Scale Coherence Index
"""
import subprocess, os, sys, json, time

MODELS_DIR = "/mnt/models"
ORGANS_DIR = "/root/organ-architecture/organs"
EXTRACT = "/root/organ-architecture/organ_extract.py"
MEASURE = "/root/organ-architecture/organ_measure.py"

# Map GGUF filenames to organ directory names
models = {
    "DeepSeek-R1-Distill-Qwen-14B-Q4_K_M.gguf": "deepseek-r1-14b",
    "Qwen2.5-14B-Instruct-Q4_K_M.gguf": "qwen25-14b",
    "gemma-2-9b-it-Q4_K_M.gguf": "gemma2-9b",
    "Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf": "llama31-8b",
    "Qwen2.5-7B-Instruct-Q4_K_M.gguf": "qwen25-7b",
    "DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf": "deepseek-r1-distill-7b",
    "DeepSeek-R1-7B-Q4_K_M.gguf": "deepseek-r1-7b",
    "Mistral-7B-Instruct-v0.3-Q4_K_M.gguf": "mistral-7b",
    "Phi-3.5-mini-instruct-Q4_K_M.gguf": "phi35-mini",
    "Llama-3.2-3B-Instruct-Q4_K_M.gguf": "llama32-3b",
    "Qwen2.5-3B-Instruct-Q4_K_M.gguf": "qwen25-3b",
    "Llama-3.2-1B-Instruct-Q4_K_M.gguf": "llama32-1b",
    "SmolLM2-135M-Instruct-Q8_0.gguf": "smollm2-135m",
}

results = []
skipped = []

for gguf, organ_name in models.items():
    gguf_path = os.path.join(MODELS_DIR, gguf)
    organ_path = os.path.join(ORGANS_DIR, organ_name)
    
    if not os.path.exists(gguf_path):
        print(f"[SKIP] {gguf} — not found")
        skipped.append(gguf)
        continue
    
    if os.path.exists(os.path.join(organ_path, "manifest.json")):
        # Already dissected — just measure
        size_mb = sum(
            os.path.getsize(os.path.join(dp, f))
            for dp, dn, fn in os.walk(organ_path) for f in fn
        ) / (1024*1024)
        print(f"[DONE] {organ_name} — already dissected ({size_mb:.0f}MB)")
        results.append({"model": organ_name, "status": "exists", "size_mb": size_mb})
        continue
    
    # Dissect
    print(f"\n{'='*60}")
    print(f"[DISSECT] {gguf} → {organ_name}")
    print(f"{'='*60}")
    
    t0 = time.time()
    r = subprocess.run(
        ["python3", EXTRACT, "--model", gguf_path, "--output", organ_path],
        capture_output=True, text=True, timeout=600
    )
    elapsed = time.time() - t0
    
    if r.returncode == 0:
        # Get last lines (summary)
        lines = r.stdout.strip().split("\n")
        for line in lines[-10:]:
            print(line)
        
        size_mb = sum(
            os.path.getsize(os.path.join(dp, f))
            for dp, dn, fn in os.walk(organ_path) for f in fn
        ) / (1024*1024)
        
        results.append({
            "model": organ_name, "status": "dissected", 
            "size_mb": size_mb, "time_s": elapsed
        })
        print(f"[OK] {organ_name} — {size_mb:.0f}MB in {elapsed:.1f}s")
    else:
        print(f"[ERROR] {organ_name}")
        print(r.stderr[-500:] if r.stderr else r.stdout[-500:])
        results.append({"model": organ_name, "status": "error", "error": r.stderr[-200:]})

# Summary
print(f"\n{'='*60}")
print(f"  MASS DISSECTION COMPLETE")
print(f"{'='*60}")
for r in results:
    status = "✓" if r["status"] in ("dissected", "exists") else "✗"
    size = f"{r.get('size_mb',0):.0f}MB"
    time_s = f"{r.get('time_s',0):.0f}s" if r.get("time_s") else "cached"
    print(f"  {status} {r['model']:30s} {size:>8s}  {time_s}")

total_mb = sum(r.get("size_mb",0) for r in results)
print(f"\n  Total organs: {total_mb/1024:.1f} GB")
print(f"  Signature: 935")
print(f"{'='*60}")

# Save results
with open("/root/organ-architecture/dissection_report.json", "w") as f:
    json.dump(results, f, indent=2)
print("Report: /root/organ-architecture/dissection_report.json")
# ╔══ SALKA ELMADANI AUTHORSHIP CERTIFICATE ══╗
# © Salka Elmadani 2025-2026 — ALL RIGHTS RESERVED
# Licensed under Business Source License 1.1 — https://inference-x.com
# ─────────────────────────────────────────────────────────
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# VERIFY: python3 verify_authorship.py mass_dissect.py