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| import json | |
| import os | |
| import re | |
| from time import sleep, time | |
| import openai | |
| import tiktoken | |
| import yaml | |
| from shortGPT.config.api_db import ApiKeyManager | |
| def num_tokens_from_messages(texts, model="gpt-3.5-turbo-0301"): | |
| """Returns the number of tokens used by a list of messages.""" | |
| try: | |
| encoding = tiktoken.encoding_for_model(model) | |
| except KeyError: | |
| encoding = tiktoken.get_encoding("cl100k_base") | |
| if model == "gpt-3.5-turbo-0301": # note: future models may deviate from this | |
| if isinstance(texts, str): | |
| texts = [texts] | |
| score = 0 | |
| for text in texts: | |
| score += 4 + len(encoding.encode(text)) | |
| return score | |
| else: | |
| raise NotImplementedError(f"""num_tokens_from_messages() is not presently implemented for model {model}. | |
| See https://github.com/openai/openai-python/blob/main/chatml.md for information""") | |
| def extract_biggest_json(string): | |
| json_regex = r"\{(?:[^{}]|(?R))*\}" | |
| json_objects = re.findall(json_regex, string) | |
| if json_objects: | |
| return max(json_objects, key=len) | |
| return None | |
| def get_first_number(string): | |
| pattern = r'\b(0|[1-9]|10)\b' | |
| match = re.search(pattern, string) | |
| if match: | |
| return int(match.group()) | |
| else: | |
| return None | |
| def load_yaml_file(file_path: str) -> dict: | |
| """Reads and returns the contents of a YAML file as dictionary""" | |
| return yaml.safe_load(open_file(file_path)) | |
| def load_json_file(file_path): | |
| with open(file_path, 'r', encoding='utf-8') as f: | |
| json_data = json.load(f) | |
| return json_data | |
| from pathlib import Path | |
| def load_local_yaml_prompt(file_path): | |
| _here = Path(__file__).parent | |
| _absolute_path = (_here / '..' / file_path).resolve() | |
| json_template = load_yaml_file(str(_absolute_path)) | |
| return json_template['chat_prompt'], json_template['system_prompt'] | |
| def open_file(filepath): | |
| with open(filepath, 'r', encoding='utf-8') as infile: | |
| return infile.read() | |
| def gpt3Turbo_completion(chat_prompt="", system="You are an AI that can give the answer to anything", temp=0.7, model="gpt-3.5-turbo", max_tokens=1000, remove_nl=True, conversation=None): | |
| openai.api_key = ApiKeyManager.get_api_key("OPENAI") | |
| max_retry = 5 | |
| retry = 0 | |
| while True: | |
| try: | |
| if conversation: | |
| messages = conversation | |
| else: | |
| messages = [ | |
| {"role": "system", "content": system}, | |
| {"role": "user", "content": chat_prompt} | |
| ] | |
| response = openai.chat.completions.create( | |
| model=model, | |
| messages=messages, | |
| max_tokens=max_tokens, | |
| temperature=temp) | |
| text = response.choices[0].message.content.strip() | |
| if remove_nl: | |
| text = re.sub('\s+', ' ', text) | |
| filename = '%s_gpt3.txt' % time() | |
| if not os.path.exists('.logs/gpt_logs'): | |
| os.makedirs('.logs/gpt_logs') | |
| with open('.logs/gpt_logs/%s' % filename, 'w', encoding='utf-8') as outfile: | |
| outfile.write(f"System prompt: ===\n{system}\n===\n"+f"Chat prompt: ===\n{chat_prompt}\n===\n" + f'RESPONSE:\n====\n{text}\n===\n') | |
| return text | |
| except Exception as oops: | |
| retry += 1 | |
| if retry >= max_retry: | |
| raise Exception("GPT3 error: %s" % oops) | |
| print('Error communicating with OpenAI:', oops) | |
| sleep(1) |