fsi-anomaly / data /build_domain.py
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"""Build domain-adaptation corpus: analyst/forensic chat text + playbooks + a
small story mix for fluency. Output: data/domain_full.txt (one text blob per line)."""
import json, random, re
from pathlib import Path
rng = random.Random(20260802)
def load(p):
return [json.loads(l) for l in open(p, encoding="utf-8") if l.strip()]
def lines_from_jsonl(p, out):
for r in load(p):
if "raw" in r and r.get("raw"):
out.append(r["raw"])
elif r.get("user") and r.get("assistant"):
p_tok = {"analyst": "<|analyst|>", "skeptic": "<|skeptic|>", "none": ""}.get(r.get("persona", "analyst"), "<|analyst|>")
out.append(f"{p_tok}<|user|>{r['user']}<|assistant|>{r['assistant']}<|endoftext|>")
def paragraphs(p, out):
for para in re.split(r"\n\s*\n", Path(p).read_text(encoding="utf-8")):
para = " ".join(para.split())
if len(para) > 40:
out.append(para)
def main():
out = []
for f in ["sft_forensic.jsonl", "sft_sop_mix.jsonl", "sft_sop.jsonl", "sft_distill_mix.jsonl",
"general_chat.jsonl", "persona_dialogue.jsonl", "tool_use.jsonl",
"distill_analyst_a.jsonl", "distill_analyst_b.jsonl", "distill_dialogue.jsonl",
"distill_method.jsonl", "distill_qa.jsonl", "distill_skeptic.jsonl"]:
lines_from_jsonl(f"data/{f}", out)
for f in ["library/the_prince.txt", "library/verification_playbook.txt", "library/manipulation_playbook.txt"]:
paragraphs(f"data/{f}", out)
rng.shuffle(out)
# story mix: reservoir sample for fluency (10% by count)
story = []
with open("data/TinyStoriesV2-GPT4-train.txt", encoding="utf-8") as fh:
for i, line in enumerate(fh):
s = line.strip()
if not s:
continue
if len(story) < 900:
story.append(s)
else:
j = rng.randrange(i + 1)
if j < 900:
story[j] = s
rng.shuffle(story)
final = out + story[:900]
rng.shuffle(final)
Path("data/domain_full.txt").write_text("\n".join(final), encoding="utf-8")
print(f"domain lines: {len(final):,} (domain {len(out):,} + story {min(900,len(story)):,})", flush=True)
if __name__ == "__main__":
main()