| import os,json,time,sys,concurrent.futures as cf |
| from openai import OpenAI |
| from items import ITEMS |
| from native import NATIVE |
| from run import SUFFIX |
| c=OpenAI(base_url="https://router.huggingface.co/v1",api_key=os.environ.get("HF_TOKEN","x"),timeout=180) |
| jobs=[] |
| for it in NATIVE: |
| for s in range(3): jobs.append((it,"ta",s,None,"native")) |
| for it in ITEMS: |
| for l in ("en","ta","tl"): jobs.append((it,l,0,"minimal","parallel")) |
| def call(j): |
| it,l,s,eff,split=j; err=None |
| kw={"extra_body":{"reasoning_effort":eff}} if eff else {} |
| for a in range(8): |
| try: |
| t=time.time() |
| r=c.chat.completions.create(model="reflection/Beam-1.0-501B-A23B",messages=[{"role":"user","content":it[l]+SUFFIX[l]}],max_tokens=6000,**kw) |
| m=r.choices[0].message;u=r.usage |
| return dict(split=split,effort=eff or "default",id=it["id"],cat=it["cat"],lang=l,sample=s,answer=it["answer"],aliases=it.get("aliases",[]),output=m.content, |
| reasoning=getattr(m,"reasoning_content",None),prompt_tokens=u.prompt_tokens,completion_tokens=u.completion_tokens, |
| reasoning_tokens=(u.completion_tokens_details.reasoning_tokens if u.completion_tokens_details else 0),latency=round(time.time()-t,2)) |
| except Exception as e: err=str(e); time.sleep(5*(a+1)) |
| return dict(split=split,id=it["id"],lang=l,sample=s,error=err) |
| with cf.ThreadPoolExecutor(4) as ex: out=list(ex.map(call,jobs)) |
| json.dump(out,open("raw_results2.json","w"),ensure_ascii=False,indent=1) |
| print(len(out),sum('error' in r for r in out)) |
|
|
