"""Apply the corrected answer parser to both models' saved generations."""
import json,hashlib
from pathlib import Path
from huggingface_hub import HfApi,hf_hub_download,CommitOperationAdd
from evaluate import check,summary
api=HfApi();repo="SEE7/Astheral"
def read(name):return Path(hf_hub_download(repo,name)).read_text()
m=json.loads(read("evaluation.json"))
assert m["version"]=="2"
changed={}
outputs={}
for filename in ["base_outputs.json","astheral_outputs.json","astheral_merged_outputs.json","merged_regressions_outputs.json"]:
    rows=json.loads(read(filename))
    for row in rows:row["pass"]=check(row,row["output"])
    outputs[filename]=rows
    changed[filename]=json.dumps(rows,indent=2)
m["base_scores"]=summary(outputs["base_outputs.json"])
m["astheral_scores"]=summary(outputs["astheral_outputs.json"])
m["merged_scores"]=summary(outputs["astheral_merged_outputs.json"])
for field,filename in [("astheral_scores","astheral_outputs.json"),("merged_scores","astheral_merged_outputs.json")]:
    confirmations=[r for r in outputs[filename] if r["group"]=="confirmation"]
    if confirmations:m[field]["confirmation"]={"passed":sum(r["pass"] for r in confirmations),"total":len(confirmations)}
s=m["merged_scores"];b=m["base_scores"]
m["evaluation_parser_revision"]="2: boxed answer, unambiguous leading answer paragraph, then numeric fallback"
m["quality_gate_passed"]=(s["regression"]["passed"]==2 and s["fresh"]["passed"]==s["fresh"]["total"] and s["number"]["passed"]>=b["number"]["passed"])
if "confirmation" in s:m["quality_gate_passed"] &= s["confirmation"]["passed"]==s["confirmation"]["total"]
mode_rows=outputs["astheral_merged_outputs.json"]
mode_passed=sum(("<think>" not in r["output"] and "</think>" not in r["output"]) if r["mode"]=="instruct" else (r["output"].lstrip().startswith("<think>") and "</think>" in r["output"]) for r in mode_rows)
m["mode_adherence"]={"passed":mode_passed,"total":len(mode_rows)}
m["quality_gate_passed"] &= mode_passed==len(mode_rows)
m["thinking_output_characters"]={name:sum(len(r["output"]) for r in rows if r["mode"]=="thinking")/sum(r["mode"]=="thinking" for r in rows) for name,rows in [("base",outputs["base_outputs.json"]),("astheral",outputs["astheral_merged_outputs.json"])]}
changed["evaluation.json"]=json.dumps(m,indent=2)
changed["evaluate.py"]=Path(__file__).with_name("evaluate.py").read_text()
# Keep future reruns aligned with the corrected comparative gate.
train=read("train.py")
train=train.replace('s["number"]["passed"]>=14','s["number"]["passed"]>=max(14,summary(baseline)["number"]["passed"])')
changed["train.py"]=train
settings=read("settings.json")
fingerprint=hashlib.sha256(("NousResearch/DeepHermes-3-Llama-3-8B-Preview"+"53d902c7dcfa4c749a3b455149064f82af2e2549"+changed["evaluate.py"]+settings).encode()).hexdigest()
changed["v2-baseline.json"]=json.dumps({"fingerprint":fingerprint,"outputs":outputs["base_outputs.json"],"parser_corrected_without_regenerating":True})
manifest=json.loads(read("artifact_manifest.json"))
for name,body in changed.items():manifest[name]={"bytes":len(body.encode()),"sha256":hashlib.sha256(body.encode()).hexdigest()}
changed["artifact_manifest.json"]=json.dumps(manifest,indent=2)
api.create_commit(repo_id=repo,operations=[CommitOperationAdd(path_in_repo=n,path_or_fileobj=v.encode()) for n,v in changed.items()],commit_message="Correct numerical answer extraction consistently for base and Astheral evaluations")
print("CORRECTED_EVALUATION",json.dumps({"base":b,"astheral":s,"quality_gate_passed":m["quality_gate_passed"]}),flush=True)