Blame for code/v2/judge.py

import os,json,re,concurrent.futures as cf
from openai import OpenAI
from writing import W
c=OpenAI(base_url="https://router.huggingface.co/v1",api_key=os.environ["HF_TOKEN"],timeout=180)
P={w["id"]:w for w in W}
R={json.loads(l)["id"]:json.loads(l) for l in open('all_raw.jsonl') if '"write"' in l}
J=["google/gemma-3-27b-it","deepseek-ai/DeepSeek-V3.1"]
RUB="""You are a strict native Tamil-speaking evaluator. A user sent the PROMPT below to an AI model and got the RESPONSE.
Score the RESPONSE (integers 1-5):
- correctness: facts and advice are accurate and safe
- fluency: natural, grammatical Tamil (or natural Tanglish if the prompt was Tanglish); penalise literal translation, odd word choice, spelling errors
- instruction: follows the requested length/format/audience
- register_match: 1 if it replies in the same script/register as the prompt (Tamil script for Tamil prompts, Romanized Tamil for Tanglish prompts), else 0
Return only JSON: {"correctness":n,"fluency":n,"instruction":n,"register_match":0or1,"note":"<=15 words"}

PROMPT:
%s

RESPONSE:
%s"""
def go(a):
    wid,j=a
    for t in range(4):
        try:
            r=c.chat.completions.create(model=j,messages=[{"role":"user","content":RUB%(P[wid]["prompt"],R[wid]["output"])}],max_tokens=300,temperature=0)
            s=r.choices[0].message.content; d=json.loads(re.search(r"\{.*\}",s,re.S).group(0)); d.update(id=wid,judge=j); return d
        except Exception as e: err=str(e)
    return dict(id=wid,judge=j,error=err)
with cf.ThreadPoolExecutor(6) as ex: out=list(ex.map(go,[(w,j) for w in R for j in J]))
json.dump(out,open("judge.json","w"),ensure_ascii=False,indent=1)
for d in out: print(d)