Files
pipelines/prompt_bench/tools/build_finetune_dataset.py
2026-04-13 15:43:01 -04:00

115 lines
4.0 KiB
Python

"""Build a fine-tuning JSONL dataset from batch request + output files.
Joins the original request JSONL (system + user messages) with the batch
output JSONL (assistant completions) by custom_id to produce a ChatML-style
messages JSONL suitable for fine-tuning.
"""
from __future__ import annotations
import json
import logging
from pathlib import Path
from typing import Annotated
import typer
logger = logging.getLogger(__name__)
HTTP_OK = 200
def load_requests(path: Path) -> dict[str, list[dict]]:
"""Parse request JSONL into {custom_id: messages}."""
results: dict[str, list[dict]] = {}
with path.open(encoding="utf-8") as handle:
for raw_line in handle:
stripped = raw_line.strip()
if not stripped:
continue
record = json.loads(stripped)
custom_id = record["custom_id"]
messages = record["body"]["messages"]
results[custom_id] = messages
return results
def load_completions(path: Path) -> dict[str, str]:
"""Parse batch output JSONL into {custom_id: assistant_content}."""
results: dict[str, str] = {}
with path.open(encoding="utf-8") as handle:
for line_number, raw_line in enumerate(handle, 1):
stripped = raw_line.strip()
if not stripped:
continue
record = json.loads(stripped)
custom_id = record["custom_id"]
response = record.get("response", {})
if response.get("status_code") != HTTP_OK:
logger.warning("Skipping %s (line %d): status %s", custom_id, line_number, response.get("status_code"))
continue
body = response.get("body", {})
choices = body.get("choices", [])
if not choices:
logger.warning("Skipping %s (line %d): no choices", custom_id, line_number)
continue
content = choices[0].get("message", {}).get("content", "")
if not content:
logger.warning("Skipping %s (line %d): empty content", custom_id, line_number)
continue
results[custom_id] = content
return results
def main(
requests_path: Annotated[Path, typer.Option("--requests", help="Batch request JSONL")] = Path(
"output/openai_batch/requests.jsonl",
),
batch_output: Annotated[Path, typer.Option("--batch-output", help="Batch output JSONL")] = Path(
"batch_69d84558d91c819091d53f08d78f9fd6_output.jsonl",
),
output_path: Annotated[Path, typer.Option("--output", help="Fine-tuning JSONL output")] = Path(
"output/finetune_dataset.jsonl",
),
log_level: Annotated[str, typer.Option(help="Log level")] = "INFO",
) -> None:
"""Build fine-tuning dataset by joining request and output JSONL files."""
logging.basicConfig(level=log_level, format="%(asctime)s %(levelname)s %(name)s: %(message)s")
logger.info("Loading requests from %s", requests_path)
requests = load_requests(requests_path)
logger.info("Loaded %d requests", len(requests))
logger.info("Loading completions from %s", batch_output)
completions = load_completions(batch_output)
logger.info("Loaded %d completions", len(completions))
output_path.parent.mkdir(parents=True, exist_ok=True)
matched = 0
skipped = 0
with output_path.open("w", encoding="utf-8") as handle:
for custom_id, messages in requests.items():
assistant_content = completions.get(custom_id)
if assistant_content is None:
skipped += 1
continue
example = {
"messages": [*messages, {"role": "assistant", "content": assistant_content}],
}
handle.write(json.dumps(example, ensure_ascii=False))
handle.write("\n")
matched += 1
logger.info("Wrote %d examples to %s (skipped %d unmatched)", matched, output_path, skipped)
def cli() -> None:
"""Typer entry point."""
typer.run(main)
if __name__ == "__main__":
cli()