Fraction chess

chess_fraction.py

# %%

import os

import openai
import numpy as np
from tqdm import trange

# %%


if "OPENAI_API_KEY" not in os.environ:
    openai.api_key_path = os.path.expanduser("~/.openai_api_key")

# %%

# model = "babbage-002"
model = "davinci-002"

# %%

counts_chess_str = 0
chess_seqs_seqs = []
loop_count = 50
n = 128
total_seqs = loop_count * n
max_tokens = 50
for _ in trange(loop_count):
    r = openai.Completion.create(
        engine=model,
        prompt="<|endoftext|>",
        logprobs=0,
        n=n,
        max_tokens=max_tokens,
        temperature=1,
    )
    for c in r["choices"]:
        if " d4 " in c["text"] or " O-O " in c["text"] or " e4 " in c["text"]:
            chess_seqs_seqs.append(c["text"])
            counts_chess_str += 1

# %%

frac_chess = counts_chess_str / total_seqs
print(f"{frac_chess=}")

# %%
print("chess seqs")
for seq in chess_seqs_seqs:
    print(seq)
    print("========")
# %%
uncertainty = np.sqrt(frac_chess * (1 - frac_chess) / total_seqs)
print(f"{frac_chess:.3f} +/- {uncertainty:.3f}")