138 lines
5.6 KiB
Python
138 lines
5.6 KiB
Python
import argparse, json, random, time, threading
|
|
from concurrent.futures import ThreadPoolExecutor
|
|
from pathlib import Path
|
|
from buddhagpt.llm import openrouter_client, chat
|
|
from buddhagpt.datagen import build_messages, parse_pairs, dedupe, interleaved_variant
|
|
|
|
# NOTE: OpenRouter lists this model under the tilde-prefixed "latest" alias id.
|
|
MODEL = "~deepseek/deepseek-v4-flash-latest"
|
|
|
|
|
|
def load_qualifying() -> list[dict]:
|
|
suttas = [json.loads(l) for l in Path("corpus/suttas.jsonl").read_text().splitlines()]
|
|
return [s for s in suttas if len(s["text"]) > 800] # only 2304 of 3920 suttas qualify
|
|
|
|
|
|
def build_full_sample(qualifying: list[dict], target_calls: int, seed: int) -> list[tuple[dict, int]]:
|
|
"""Cycle through the qualifying corpus (reshuffled each pass) until target_calls is
|
|
reached, assigning template variant by running call index so every full run covers
|
|
all templates in TEMPLATES rather than one variant per pass."""
|
|
random.seed(seed)
|
|
sample = []
|
|
while len(sample) < target_calls:
|
|
order = qualifying[:]
|
|
random.shuffle(order)
|
|
for s in order:
|
|
if len(sample) >= target_calls:
|
|
break
|
|
sample.append((s, interleaved_variant(len(sample))))
|
|
return sample
|
|
|
|
|
|
def build_topup_sample(qualifying: list[dict], variants: list[int], per_variant: int, seed: int) -> list[tuple[dict, int]]:
|
|
"""Sample `per_variant` distinct suttas (seeded, no repeats within a variant) for each
|
|
variant in `variants`, for topping up underrepresented templates."""
|
|
sample = []
|
|
for variant in variants:
|
|
random.seed(seed + variant)
|
|
chosen = random.sample(qualifying, min(per_variant, len(qualifying)))
|
|
sample += [(s, variant) for s in chosen]
|
|
random.seed(seed)
|
|
random.shuffle(sample)
|
|
return sample
|
|
|
|
|
|
def run(sample: list[tuple[dict, int]], raw_path: Path) -> tuple[dict, int, int]:
|
|
client = openrouter_client()
|
|
totals = {"input": 0, "output": 0}
|
|
fail_count = 0
|
|
done_count = 0
|
|
raw_count = 0
|
|
start = time.time()
|
|
lock = threading.Lock()
|
|
|
|
Path("data").mkdir(parents=True, exist_ok=True)
|
|
raw_f = raw_path.open("a") # append: incremental persistence, survives interruption
|
|
|
|
def gen_one(args):
|
|
nonlocal fail_count, done_count, raw_count
|
|
s, variant = args
|
|
try:
|
|
text, usage = chat(client, MODEL, build_messages(s, variant), max_tokens=2000)
|
|
except Exception as e:
|
|
with lock:
|
|
fail_count += 1
|
|
print(f"skip {s['uid']}: {e}", flush=True)
|
|
return
|
|
pairs = parse_pairs(text, uid=s["uid"])
|
|
for p in pairs:
|
|
p["variant"] = variant
|
|
with lock:
|
|
totals["input"] += usage["input"]; totals["output"] += usage["output"]
|
|
done_count += 1
|
|
raw_count += len(pairs)
|
|
for p in pairs:
|
|
raw_f.write(json.dumps(p) + "\n")
|
|
raw_f.flush()
|
|
if done_count % 100 == 0:
|
|
elapsed = time.time() - start
|
|
print(f"progress {done_count}/{len(sample)} | fails {fail_count} | "
|
|
f"raw_pairs {raw_count} | {elapsed:.0f}s elapsed", flush=True)
|
|
|
|
with ThreadPoolExecutor(max_workers=8) as pool:
|
|
list(pool.map(gen_one, sample))
|
|
|
|
raw_f.close()
|
|
|
|
fail_rate = fail_count / len(sample) if sample else 0.0
|
|
print(f"calls: {len(sample)} | failed: {fail_count} ({fail_rate:.1%}) | raw pairs parsed: {raw_count}", flush=True)
|
|
return totals, fail_count, raw_count
|
|
|
|
|
|
def rebuild_instructions(raw_path: Path, out_path: Path) -> list[dict]:
|
|
"""Rebuild data/instructions.jsonl from the FULL raw file (word filter + dedupe)."""
|
|
pairs = [json.loads(l) for l in raw_path.read_text().splitlines() if l.strip()]
|
|
pairs = [p for p in pairs if 60 <= len(p["answer"].split()) <= 400]
|
|
print(f"pairs after word-count filter: {len(pairs)}", flush=True)
|
|
pairs = dedupe(pairs)
|
|
with out_path.open("w") as f:
|
|
for p in pairs:
|
|
f.write(json.dumps({"messages": [
|
|
{"role": "user", "content": p["question"]},
|
|
{"role": "assistant", "content": p["answer"]},
|
|
]}) + "\n")
|
|
return pairs
|
|
|
|
|
|
def report_variant_counts(pairs: list[dict], label: str) -> None:
|
|
counts: dict = {}
|
|
for p in pairs:
|
|
v = p.get("variant", "legacy")
|
|
counts[v] = counts.get(v, 0) + 1
|
|
print(f"{label} per-variant counts: {dict(sorted(counts.items(), key=lambda kv: str(kv[0])))}", flush=True)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
ap = argparse.ArgumentParser()
|
|
ap.add_argument("--mode", choices=["full", "topup"], default="full")
|
|
ap.add_argument("--target-calls", type=int, default=3200)
|
|
ap.add_argument("--seed", type=int, default=7)
|
|
ap.add_argument("--topup-variants", type=int, nargs="+", default=[2, 3, 4, 5])
|
|
ap.add_argument("--topup-per-variant", type=int, default=575)
|
|
args = ap.parse_args()
|
|
|
|
qualifying = load_qualifying()
|
|
raw_path = Path("data/instructions_raw.jsonl")
|
|
|
|
if args.mode == "full":
|
|
sample = build_full_sample(qualifying, args.target_calls, args.seed)
|
|
else:
|
|
sample = build_topup_sample(qualifying, args.topup_variants, args.topup_per_variant, args.seed)
|
|
|
|
totals, fail_count, raw_count = run(sample, raw_path)
|
|
|
|
pairs = rebuild_instructions(raw_path, Path("data/instructions.jsonl"))
|
|
report_variant_counts(pairs, "final (post-filter, post-dedupe)")
|
|
# deepseek-v4-flash list price ~$0.08/M in, $0.16/M out
|
|
print(len(pairs), "pairs | tokens", totals, "| est cost $%.2f" % (totals["input"]/1e6*0.08 + totals["output"]/1e6*0.16), flush=True)
|