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import os
import re
import time
import argparse
from tqdm import tqdm
import sys
sys.path.append('../')
from utilities import *
# OpenAI
import openai
# load demo prompt
from prompts.ext_ans import demo_prompt
def verify_extraction(extraction):
extraction = extraction.strip()
if extraction == "" or extraction == None:
return False
return True
def create_test_prompt(demo_prompt, query, response):
demo_prompt = demo_prompt.strip()
test_prompt = f"{query}\n\n{response}"
full_prompt = f"{demo_prompt}\n\n{test_prompt}\n\nExtracted answer: "
return full_prompt
def extract_answer(response, problem, quick_extract=False):
question_type = problem['question_type']
answer_type = problem['answer_type']
choices = problem['choices']
query = problem['query']
pid = problem['pid']
if response == "":
return ""
if question_type == 'multi_choice' and response in choices:
return response
if answer_type == "integer":
try:
extraction = int(response)
return str(extraction)
except:
pass
if answer_type == "float":
try:
extraction = str(float(response))
return extraction
except:
pass
# quick extraction
if quick_extract:
print("Quickly extracting answer...")
# The answer is "text". -> "text"
try:
result = re.search(r'The answer is "(.*)"\.', response)
if result:
extraction = result.group(1)
return extraction
except:
pass
# general extraction
try:
full_prompt = create_test_prompt(demo_prompt, query, response)
extraction = get_chat_response(full_prompt, openai.api_key, openai.api_base, model=args.llm_engine)
return extraction
except Exception as e:
print(e)
print(f"Error in extracting answer for {pid}")
return ""
if __name__ == '__main__':
parser = argparse.ArgumentParser()
# input
parser.add_argument('--output_file', type=str, default='answer.json')
parser.add_argument('--response_label', type=str, default='response', help='response label for the input file')
# model
parser.add_argument('--llm_engine', type=str, default='gpt-4-0613', help='llm engine',
choices = ['gpt-3.5-turbo', 'gpt-3.5', 'gpt-4', 'gpt-4-0314', 'gpt-4-0613'])
parser.add_argument('--number', type=int, default=-1, help='number of problems to run')
parser.add_argument('--quick_extract', action='store_true', help='use rules to extract answer for some problems')
parser.add_argument('--rerun', action='store_true', help='rerun the answer extraction')
# openai
parser.add_argument("--api_key", required=True, type=str, help="OpenAI API key")
parser.add_argument("--api_base", default=None, type=str, help="OpenAI API base")
# output
parser.add_argument('--save_every', type=int, default=10, help='save every n problems')
parser.add_argument('--output_label', type=str, default='', help='label for the output file')
args = parser.parse_args()
# args
label = args.response_label
result_file = args.output_file
if args.output_label != '':
output_file = result_file.replace('.json', f'_{args.output_label}.json')
else:
output_file = result_file
# read results
print(f"Reading {result_file}...")
try:
results = read_json(output_file)
except:
samples = [json.loads(line) for line in open(result_file)]
results = {}
for sample in samples:
results[sample['pid']] = sample
# full pids
full_pids = list(results.keys())
if args.number > 0:
full_pids = full_pids[:min(args.number, len(full_pids))]
print("Number of testing problems:", len(full_pids))
# test pids
if args.rerun:
test_pids = full_pids
else:
test_pids = []
for pid in full_pids:
# print(pid)
if 'extraction' not in results[pid] or not verify_extraction(results[pid]['extraction']):
test_pids.append(pid)
test_num = len(test_pids)
print("Number of problems to run:", test_num)
# print(test_pids)
# openai api
openai.api_key = args.api_key # Your API key here
if args.api_base:
openai.api_base = args.api_base # Your API base here
# tqdm, enumerate results
for i, pid in enumerate(tqdm(test_pids)):
problem = results[pid]
assert label in problem
response = problem[label]
extraction = extract_answer(response, problem, args.quick_extract)
results[pid]['extraction'] = extraction
if i % args.save_every == 0 or i == test_num - 1:
print(f"Saving results to {output_file}...")
save_json(results, output_file)
print(f"Results saved.")
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