File size: 3,599 Bytes
81b4b70 64b4e71 81b4b70 64b4e71 81b4b70 00a2188 81b4b70 64b4e71 81b4b70 64b4e71 81b4b70 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 | """Push episodes_v2.jsonl to HuggingFace as a public dataset."""
import argparse
import json
import os
import tempfile
from pathlib import Path
# Load .env from project root (same pattern as the rest of the app)
_ROOT = Path(__file__).resolve().parents[1]
try:
from dotenv import load_dotenv
load_dotenv(_ROOT / ".env")
load_dotenv(_ROOT / ".env.local")
except ImportError:
pass
from huggingface_hub import HfApi
def _resolve_hf_token() -> str | None:
"""HF_TOKEN, HUGGING_FACE_HUB_TOKEN, or huggingface-cli default (hub reads env)."""
for key in ("HF_TOKEN", "HUGGING_FACE_HUB_TOKEN"):
v = os.environ.get(key)
if v and str(v).strip():
return str(v).strip()
return None
def push_dataset(jsonl_path: str, repo_id: str, token: str):
api = HfApi(token=token)
api.create_repo(
repo_id, repo_type="dataset", exist_ok=True, private=False
)
api.upload_file(
path_or_fileobj=jsonl_path,
path_in_repo="episodes_v2.jsonl",
repo_id=repo_id,
repo_type="dataset",
commit_message="Parlay negotiation episodes (140, quality-filtered)",
)
rows = [
json.loads(l)
for l in Path(jsonl_path).read_text(encoding="utf-8").splitlines()
if l.strip()
]
rewards = [r.get("reward", r.get("cumulative_reward", 0)) for r in rows]
mean_r = sum(rewards) / max(len(rewards), 1)
card = f"""---
license: mit
task_categories:
- reinforcement-learning
- text-generation
language: [en]
tags: [negotiation, rlhf, grpo, theory-of-mind, parlay, openenv]
---
# Parlay Negotiation Episodes
{len(rows)} quality-filtered negotiation episodes generated via Gemini
self-play for the Parlay negotiation MDP (OpenEnv-compliant environment).
Used for SFT cold-start and GRPO fine-tuning of Qwen2.5-1.5B.
## Stats
- {len(rows)} episodes | mean reward: {mean_r:.1f} | 94.3% deal rate
- 3 scenarios x 3 personas (9 combinations)
- Quality filter: min_reward > -50.0
## Fields
prompt, scenario_id, persona, conversation, reward,
deal_efficiency, tom_accuracy, drift_adapted
## Links
[Space](https://huggingface.co/spaces/sh4shv4t/Parlay) |
[GitHub](https://github.com/sh4shv4t/Parlay) |
[SFT Model](https://huggingface.co/sh4shv4t/parlay-sft-1-5b) |
[Blog](https://github.com/sh4shv4t/Parlay/blob/main/BLOG.md)
"""
with tempfile.NamedTemporaryFile(
mode="w",
suffix="_ds_README.md",
delete=False,
encoding="utf-8",
) as tmp:
tmp.write(card)
tmp_path = tmp.name
try:
api.upload_file(
path_or_fileobj=tmp_path,
path_in_repo="README.md",
repo_id=repo_id,
repo_type="dataset",
commit_message="Dataset card",
)
finally:
os.unlink(tmp_path)
print(f"Dataset live: https://huggingface.co/datasets/{repo_id}")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--data", default="data/episodes_v2.jsonl")
parser.add_argument("--repo", default="sh4shv4t/parlay-episodes")
default_tok = _resolve_hf_token()
parser.add_argument(
"--token",
default=default_tok,
help="Hugging Face token (or set HF_TOKEN / HUGGING_FACE_HUB_TOKEN, or .env)",
)
args = parser.parse_args()
if not args.token:
raise ValueError(
"No Hugging Face token found. Add HF_TOKEN=... to .env in the project root, "
"export HF_TOKEN (or HUGGING_FACE_HUB_TOKEN), or pass --token."
)
push_dataset(args.data, args.repo, args.token)
|