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import os
import json
from tqdm import tqdm
import argparse
from indices import *
from data import prepare_data_for_symbol, query_gpt4, create_dataset
from prompt import get_all_prompts
from data_infererence_fetch import get_curday, fetch_all_data, get_all_prompts_online
def main(args):
index_name = args['index_name']
start_date = args['start_date']
end_date = args['end_date']
min_past_weeks = args['min_past_weeks']
max_past_weeks = args['max_past_weeks']
train_ratio = args['train_ratio']
with_basics = True
if index_name == "dow":
index_name = "DOW-30"
index = DOW_30
elif index_name == "euro":
index_name = "EURO-STOXX-50"
index = EURO_STOXX_50
elif index_name == "crypto":
index_name = "CRYPTO"
index = CRYPTO
with_basics = False
else:
raise ValueError("Invalid index name")
data_dir = f"./data/{index_name}_{start_date}_{end_date}"
os.makedirs(data_dir, exist_ok=True)
# Acquire data
print("Acquiring data")
for symbol in tqdm(index):
print(f"Processing {symbol}")
prepare_data_for_symbol(symbol, data_dir, start_date, end_date, with_basics=with_basics)
# Generate prompt and query GPT-4
print("Generating prompts and querying GPT-4")
query_gpt4(index, data_dir, start_date, end_date, min_past_weeks, max_past_weeks, with_basics=with_basics)
# Transform into training format
print("Transforming into training format")
dataset = create_dataset(index, data_dir, start_date, end_date, train_ratio, with_basics=with_basics)
# Save dataset
dataset.save_to_disk(
f"./data/fingpt-forecaster-{index_name.lower()}-{start_date.replace('-', '')}-{end_date.replace('-', '')}-{min_past_weeks}-{max_past_weeks}-{str(train_ratio).replace('.', '')}"
)
if __name__ == "__main__":
ap = argparse.ArgumentParser()
ap.add_argument("--index_name", default="crypto", choices=["dow", "euro", "crypto"], help="index name")
ap.add_argument("--start_date", default="2022-12-31", help="start date")
ap.add_argument("--end_date", default="2023-12-31", help="end date")
ap.add_argument("--min_past_weeks", default=1, help="min past weeks")
ap.add_argument("--max_past_weeks", default=4, help="max past weeks")
ap.add_argument("--train_ratio", default=0.6, help="train ratio")
args = vars(ap.parse_args())
main(args) |