Datasets:
File size: 1,389 Bytes
b81a0d5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | import os,json,time,concurrent.futures as cf
from openai import OpenAI
from hard import H
from writing import W
c=OpenAI(base_url="https://router.huggingface.co/v1",api_key=os.environ.get("HF_TOKEN","x"),timeout=240)
SUF="\n\nஇறுதி விடையை மட்டும் கூறவும், வேறு எதுவும் வேண்டாம்."
jobs=[("hard",h,s) for h in H for s in range(3)]+[("write",w,0) for w in W]
def call(j):
split,it,s=j; content=it["ta"]+SUF if split=="hard" else it["prompt"]
for a in range(6):
try:
t=time.time()
r=c.chat.completions.create(model="reflection/Beam-1.0-501B-A23B",messages=[{"role":"user","content":content}],max_tokens=6000)
m=r.choices[0].message;u=r.usage
return dict(split=split,id=it["id"],sample=s,output=m.content,prompt_tokens=u.prompt_tokens,completion_tokens=u.completion_tokens,reasoning_tokens=u.completion_tokens_details.reasoning_tokens if u.completion_tokens_details else None,latency=round(time.time()-t,2),finish=r.choices[0].finish_reason)
except Exception as e: err=str(e)[:200]; time.sleep(4*(a+1))
return dict(split=split,id=it["id"],sample=s,error=err)
with cf.ThreadPoolExecutor(6) as ex: R=list(ex.map(call,jobs))
json.dump(R,open("hw_raw.json","w"),ensure_ascii=False,indent=1)
print(len(R),sum('error' in r for r in R))
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