import time from concurrent.futures import ThreadPoolExecutor from typing import Dict, List, Optional, Union import requests from opencompass.utils.prompt import PromptList from .base_api import BaseAPIModel PromptType = Union[PromptList, str] class MyAPIModel(BaseAPIModel): """Model wrapper around Baichuan. Documentation: https://platform.baichuan-ai.com/docs/api Args: path (str): The name of Baichuan model. e.g. `Baichuan2-53B` api_key (str): Provided api key url (str): Provide url query_per_second (int): The maximum queries allowed per second between two consecutive calls of the API. Defaults to 1. max_seq_len (int): Unused here. meta_template (Dict, optional): The model's meta prompt template if needed, in case the requirement of injecting or wrapping of any meta instructions. retry (int): Number of retires if the API call fails. Defaults to 2. """ def __init__( self, path: str, api_key: str, url: str, query_per_second: int = 2, max_seq_len: int = 2048, meta_template: Optional[Dict] = None, retry: int = 2, generation_kwargs: Dict = { 'temperature': 0.3, 'top_p': 0.85, 'top_k': 5, 'with_search_enhance': False, 'stream': False, 'do_sample':False, }): # noqa E125 super().__init__(path=path, max_seq_len=max_seq_len, query_per_second=query_per_second, meta_template=meta_template, retry=retry, generation_kwargs=generation_kwargs) self.api_key = api_key self.url = url self.model = path def generate( self, inputs: List[str or PromptList], max_out_len: int = 512, ) -> List[str]: """Generate results given a list of inputs. Args: inputs (List[str or PromptList]): A list of strings or PromptDicts. The PromptDict should be organized in OpenCompass' API format. max_out_len (int): The maximum length of the output. Returns: List[str]: A list of generated strings. """ with ThreadPoolExecutor() as executor: results = list( executor.map(self._generate, inputs, [max_out_len] * len(inputs))) self.flush() return results def _generate( self, input: str or PromptList, max_out_len: int = 512, ) -> str: """Generate results given an input. Args: inputs (str or PromptList): A string or PromptDict. The PromptDict should be organized in OpenCompass' API format. max_out_len (int): The maximum length of the output. Returns: str: The generated string. """ assert isinstance(input, (str, PromptList)) if isinstance(input, str): messages = [{'role': 'user', 'content': input}] else: messages = [] for item in input: msg = {'content': item['prompt']} if item['role'] == 'HUMAN': msg['role'] = 'user' elif item['role'] == 'BOT': msg['role'] = 'assistant' messages.append(msg) data = {'model': self.model, 'messages': messages} data.update(self.generation_kwargs) headers = { 'Content-Type': 'application/json', 'api-key': self.api_key, } max_num_retries = 0 while max_num_retries < self.retry: self.acquire() try: raw_response = requests.request('POST', url=self.url, headers=headers, json=data) response = raw_response.json() except Exception as err: print('Request Error:{}'.format(err)) time.sleep(3) continue self.release() # print(response.keys()) # print(response['choices'][0]['message']['content']) if response is None: print('Connection error, reconnect.') # if connect error, frequent requests will casuse # continuous unstable network, therefore wait here # to slow down the request self.wait() continue if raw_response.status_code == 200: # msg = response['choices'][0]['message']['content'] msg = response return msg if raw_response.status_code != 200: print(raw_response.json()) time.sleep(1) continue print(response) max_num_retries += 1 raise RuntimeError(response)