| import json,re,collections,statistics as st |
| d=json.load(open("raw_results.json")) |
| TA_DIG=str.maketrans("௦௧௨௩௪௫௬௭௮௯","0123456789") |
| def norm(x): return re.sub(r"[\s\.\,\!\?\:\"'`*()\[\]₹]|rs|rupees|ரூபாய்","",(x or "").lower().translate(TA_DIG)) |
| def correct(r): |
| o=norm(r["output"]); golds=[norm(r["answer"])]+[norm(a) for a in r["aliases"]] |
| if r["answer"].isdigit(): |
| nums=re.findall(r"\d+(?:\.\d+)?", (r["output"] or "").translate(TA_DIG).replace(",","")) |
| return bool(nums) and float(nums[-1])==float(r["answer"]) |
| return any(g and (o==g or o.startswith(g) or g in o) for g in golds) |
| PIN,POUT=0.40,1.20 |
| for r in d: r["correct"]=correct(r); r["cost_usd"]=(r["prompt_tokens"]*PIN+r["completion_tokens"]*POUT)/1e6 |
| json.dump(d,open("scored_results.json","w"),ensure_ascii=False,indent=1) |
| def summ(rows): |
| return dict(n=len(rows),acc=round(100*sum(r["correct"] for r in rows)/len(rows),1), |
| prompt=round(st.mean(r["prompt_tokens"] for r in rows),1), |
| reasoning=round(st.mean(r["reasoning_tokens"] or 0 for r in rows),1), |
| completion=round(st.mean(r["completion_tokens"] for r in rows),1), |
| cost_per_1k=round(1000*st.mean(r["cost_usd"] for r in rows),4), |
| latency=round(st.mean(r["latency"] for r in rows),2)) |
| S={} |
| for l in("en","ta","tl"): |
| S[l]=summ([r for r in d if r["lang"]==l]) |
| for c in("math","logic","knowledge","everyday"): |
| S[f"{l}/{c}"]=summ([r for r in d if r["lang"]==l and r["cat"]==c]) |
| print(json.dumps(S,indent=0)) |
| wrong=[(r["id"],r["lang"],r["answer"],(r["output"] or "")[:40]) for r in d if not r["correct"]] |
| print(len(wrong)); [print(w) for w in sorted(wrong)] |
| print("total cost $",round(sum(r["cost_usd"] for r in d),4)) |
| json.dump(S,open("summary.json","w"),indent=1) |
|
|
