| import openai |
| import json |
| import os |
| import string |
| import regex |
| import time |
| from collections import Counter |
|
|
| openai.api_key = 'this is your openai key' |
|
|
| def excute(data_path,start_idx): |
| data = open(data_path, 'r') |
| for k, example in enumerate(data): |
| if k < start_idx: |
| continue |
| time.sleep(0.5) |
| print(k) |
| example = json.loads(example) |
| q = example['question'] |
| answer = example['answer'] |
| try: |
| rsp = openai.ChatCompletion.create( |
| model="gpt-3.5-turbo", |
| messages=[ |
| {"role": "user", "content": |
| """Construct a global reasoning chain for this complex question [Question]:"{}" and answer the question, and generate a query to the |
| search engine based on what you already know at each step of the reasoning chain, starting with [Query]. |
| You should generate the answer for each [Query], starting with [Answer]. |
| You should generate the final answer for the [Question] by referring the [Query]-[Answer] pairs, starting with [Final Content]. |
| For exmaple: |
| [Question]:"How many places of higher learning are in the city where the Yongle emperor greeted the person to whom the edict |
| was addressed?" |
| [Query 1]: Who was the edict addressed to? |
| [Answer 1]: the Karmapa |
| [Query 2]: Where did the Yongle Emperor greet the Karmapa? |
| [Answer 2]: Nanjing |
| [Query 3]: How many places of higher learning are in Nanjing? |
| [Answer 3]: 75 |
| [Final Content]: The edict was addressed to Karmapa [1]. Yongle Emperor greet the Karampa in Nanjing [2]. There are 75 places |
| of higher learning are in Nanjing [3]. So the final answer is 75. |
| |
| [Question]:"Which magazine was started first Arthur’s Magazine or First for Women?" |
| [Query 1]: When was Arthur’s Magazine started? |
| [Answer 1]: 1844. |
| [Query 2]: When was First for Women started? |
| [Answer 2]: 1989 |
| [Final Content]: Arthur’s Magazine started in 1844 [1]. First for Women started in 1989 [2]. So Arthur’s Magazine was started |
| first. So the final answer is Arthur’s Magazi |
| [Question]: {} |
| """.format(q, q)} |
| ] |
| ) |
| except: |
| print('start_idx is {}'.format(k)) |
| return k |
| predict_answer = rsp.get("choices")[0]["message"]["content"] |
| print(predict_answer) |
| return -1 |
|
|
| if __name__ == '__main__': |
| start_idx = 0 |
| while not start_idx == -1: |
| start_idx = excute('/hotpotqa/hotpot_dev_fullwiki_v1_line.json', |
| start_idx=start_idx) |
| print('saved message') |
