"""Final comparison across ALL tested configurations."""
import json, csv, statistics, os

def lat(path):
    rows = [json.loads(l) for l in open(path)]
    ok = [r for r in rows if not r.get("error")]
    ttfts = sorted([r["ttft_s"] for r in ok if r.get("ttft_s")])
    tpots = sorted([r["tpot_s"] for r in ok if r.get("tpot_s") and r["tpot_s"] > 0])
    lats = sorted([r["latency_s"] for r in ok])
    p = lambda v, q: v[min(int(q * len(v)), len(v) - 1)] if v else 0
    return len(ok), len(rows), p(ttfts,.5), p(ttfts,.9), p(tpots,.5), p(tpots,.9), p(lats,.5)

def gpu(path):
    rows = list(csv.DictReader(open(path)))
    vals = [float(r["util_pct"]) for r in rows]
    return statistics.fmean(vals) if vals else 0

print("COMPLETE CONFIGURATION COMPARISON")
print("All use same 1000-req trace (200 req for GPU tests), 8xH20")
print("=" * 85)
fmt = "%-35s %6s %8s %8s %8s %8s %8s"
print(fmt % ("Config", "OK/N", "TTFT50", "TTFT90", "TPOT50", "TPOT90", "E2E50"))
print("-" * 85)

configs = [
    ("gpu_ab_combined", "TP=1 DP=8 old cache-aware"),
    ("gpu_ab_hybrid", "TP=1 DP=8 hybrid routing"),
    ("tp2dp4_hybrid", "TP=2 DP=4 hybrid routing  *** NEW"),
    ("gpu_ab_pdsep", "TP=1 PD-Sep 4P+4D"),
    ("gpu_ab_6p2d", "TP=1 PD-Sep 6P+2D"),
    ("adaptive_v2_baseline", "TP=1 kv_both baseline"),
    ("adaptive_v2_offload", "TP=1 adaptive offload"),
]

for d, label in configs:
    mp = "outputs/%s/metrics.jsonl" % d
    if not os.path.exists(mp):
        continue
    ok, n, t50, t90, p50, p90, e50 = lat(mp)
    print(fmt % (label, "%d/%d" % (ok, n),
                 "%.3f" % t50, "%.3f" % t90, "%.3f" % p50, "%.3f" % p90, "%.3f" % e50))

print()
print("KEY TRADEOFF: TP=1 vs TP=2")
print("  TP=1 DP=8: Better TPOT (0.072), more instances for routing diversity")
print("  TP=2 DP=4: Better TTFT (0.565), faster prefill, larger KV cache per inst")
print("  Which is better depends on SLO: TTFT-sensitive -> TP=2, TPOT-sensitive -> TP=1")