import json, sys, importlib.util

# Direct file import to avoid verl.__init__
spec = importlib.util.spec_from_file_location(
    "physics_reward",
    "/workspace/rl4phyx/RL4Phyx/ZeroSearch/One-Shot-RLVR/verl/utils/reward_score/physics_reward.py"
)
mod = importlib.util.module_from_spec(spec)
spec.loader.exec_module(mod)

rule_based_score = mod.rule_based_score
sympy_fallback_score = mod.sympy_fallback_score

f = "/workspace/rl4phyx/RL4Phyx/SFT/sft_eval_footprint/inference_results_base.jsonl"
with open(f) as fh:
    lines = [json.loads(l) for l in fh if l.strip()]

results = {"rule_ok": 0, "sympy_ok": 0, "sympy_fail": 0, "rule_wrong": 0}
categories = {}
fail_examples = []

for r in lines:
    gt = str(r.get("ground_truth_value", "")).strip()
    cat = r.get("category", "unknown")
    
    score = rule_based_score(gt, gt)
    
    if score == 1.0:
        status = "rule_ok"
        results["rule_ok"] += 1
    elif score is None:
        try:
            s = sympy_fallback_score(gt, gt)
            if s == 1.0:
                status = "sympy_ok"
                results["sympy_ok"] += 1
            else:
                status = "sympy_fail"
                results["sympy_fail"] += 1
                if len(fail_examples) < 20:
                    fail_examples.append({"gt": gt[:80], "cat": cat})
        except Exception as e:
            status = "sympy_fail"
            results["sympy_fail"] += 1
            if len(fail_examples) < 20:
                fail_examples.append({"gt": gt[:80], "cat": cat})
    else:
        status = "rule_wrong"
        results["rule_wrong"] += 1
        if len(fail_examples) < 20:
            fail_examples.append({"gt": gt[:80], "cat": cat})
    
    if cat not in categories:
        categories[cat] = {"rule_ok": 0, "sympy_ok": 0, "fail": 0}
    if "ok" in status:
        categories[cat][status] += 1
    else:
        categories[cat]["fail"] += 1

total = len(lines)
covered = results["rule_ok"] + results["sympy_ok"]

print(f"=== Hybrid Reward Coverage ({total} questions) ===")
print(f"  Rule-based:  {results['rule_ok']:4d} ({results['rule_ok']/total*100:.1f}%)")
print(f"  SymPy:       {results['sympy_ok']:4d} ({results['sympy_ok']/total*100:.1f}%)")
print(f"  TOTAL OK:    {covered:4d} ({covered/total*100:.1f}%)")
print(f"  Failed:      {results['sympy_fail']+results['rule_wrong']:4d} ({(results['sympy_fail']+results['rule_wrong'])/total*100:.1f}%)")

print(f"\n=== By Category ===")
for cat, v in sorted(categories.items()):
    t = v["rule_ok"] + v["sympy_ok"] + v["fail"]
    ok = v["rule_ok"] + v["sympy_ok"]
    print(f"  {cat:25s}: {ok}/{t} = {ok/t*100:.0f}%  [rule={v['rule_ok']}, sympy={v['sympy_ok']}, fail={v['fail']}]")

print(f"\n=== Fail Examples ===")
for ex in fail_examples:
    print(f"  [{ex['cat']:20s}] {ex['gt']}")