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gpt4.py
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gpt4.py
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import os
import argparse
import numpy as np
import openai
import tiktoken
from tqdm import tqdm
from time import sleep
from mp_utils import choices, format_example, gen_prompt, run_eval
openai.api_key = "YOUR_API_KEY"
encoding = tiktoken.encoding_for_model("gpt-4-0613")
def get_response(inputs):
timeout_counter = 0
completion = None
while completion is None and timeout_counter<=30:
try:
completion = openai.ChatCompletion.create(
model="gpt-4",
messages=[
{"role": "user", "content": inputs}
]
)
return completion.choices[0].message['content']
except Exception as msg:
if "timeout=600" in str(msg):
timeout_counter+=1
print(msg)
sleep(5)
continue
print("Some error occured when getting gpt output.")
def eval(subject, dev_df, test_df, num_few_shot, max_length, cot, **kwargs):
cors = []
all_preds = []
answers = choices[: test_df.shape[1] - 2]
for i in tqdm(range(test_df.shape[0])):
prompt_end = format_example(test_df, i, subject, include_answer=False, cot=cot)
prompt = gen_prompt(dev_df, subject, prompt_end, num_few_shot, encoding, max_length, cot=cot)
label = test_df.iloc[i, test_df.shape[1] - 1]
pred = get_response(prompt)
if pred and pred[0] in choices:
cors.append(pred[0] == label)
all_preds.append(pred.replace("\n", "") if pred is not None else "")
acc = np.mean(cors)
print("Average accuracy {:.3f} - {}".format(acc, subject))
print("{} results, {} inappropriate formated answers.".format(len(cors), len(all_preds)-len(cors)))
return acc, all_preds, None
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--data_dir", "-d", type=str, default="../data")
parser.add_argument("--save_dir", "-s", type=str, default="../results/GPT4")
parser.add_argument("--num_few_shot", "-n", type=int, default=0)
parser.add_argument("--max_length", type=int, default=4096)
parser.add_argument("--cot", action='store_true')
args = parser.parse_args()
run_eval(None, None, eval, args)