from copy import deepcopy
from dataclasses import dataclass
import json
from pathlib import Path
import random

from omegaconf import OmegaConf
from rich import print

from refined_v4.data import atomic_json,load_rows,write_rows,signature

from . import ROOT,TASKS
from .data import documents


@dataclass
class Config:
    source: str=str(ROOT/'variants/diverse-completion-v1')
    root: str=str(ROOT/'variants/diverse-native-v1')
    tokens: int=2097152
    seed: int=6719


def build(config: Config):
    source,root=Path(config.source),Path(config.root)
    root.mkdir(parents=True,exist_ok=True)
    if (root/'dataset.json').exists():
        saved=json.loads((root/'dataset.json').read_text())
        if saved['sft_tokens']!=config.tokens:
            raise ValueError('Frozen native corpus budget differs')
        return saved
    if not (root/'data').exists():
        (root/'data').symlink_to(source/'data',target_is_directory=True)
    report=deepcopy(json.loads((source/'dataset.json').read_text()))
    report.update(source=str(source),sft_tokens=config.tokens,source_revision='diverse-native-code-v1',
        objective='Pack 2–4 independent native reference programs per document; all input predictions are supervised.')
    for task in TASKS:
        rows=load_rows(root,task,'sft')
        corpus=documents(rows,config.tokens,random.Random(config.seed))
        path=root/'sft'/task/'train.jsonl.gz'
        write_rows(path,corpus)
        report['tasks'][task].update(sft_sha256=signature(path),documents=len(corpus),
            input_prediction_tokens=config.tokens,supervised_suffix_tokens=None,
            sft_objective='All prediction tokens, with explicitly configured implementation-ending weights.')
        atomic_json(root/'data-build-progress.json',report)
    atomic_json(root/'dataset.json',report)
    print('[green]Diverse native few-shot corpus ready[/green]',config.tokens,flush=True)
    return report


if __name__=='__main__':
    build(OmegaConf.to_object(OmegaConf.merge(OmegaConf.structured(Config),OmegaConf.from_cli())))