2023-11-21 20:25:47 +08:00
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import hashlib
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import json
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import time
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from concurrent.futures import ThreadPoolExecutor
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from typing import Dict, List, Optional, Union
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import requests
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from opencompass.utils.prompt import PromptList
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from .base_api import BaseAPIModel
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PromptType = Union[PromptList, str]
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class BaiChuan(BaseAPIModel):
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"""Model wrapper around Baichuan.
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Documentation: https://platform.baichuan-ai.com/docs/api
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Args:
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path (str): The name of Baichuan model.
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e.g. `Baichuan2-53B`
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api_key (str): Provided api key
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secretkey (str): secretkey in order to obtain access_token
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url (str): Provide url
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query_per_second (int): The maximum queries allowed per second
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between two consecutive calls of the API. Defaults to 1.
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max_seq_len (int): Unused here.
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meta_template (Dict, optional): The model's meta prompt
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template if needed, in case the requirement of injecting or
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wrapping of any meta instructions.
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retry (int): Number of retires if the API call fails. Defaults to 2.
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"""
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def __init__(
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self,
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path: str,
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api_key: str,
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secret_key: str,
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url: str,
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query_per_second: int = 2,
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max_seq_len: int = 2048,
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meta_template: Optional[Dict] = None,
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retry: int = 2,
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2023-12-10 13:29:26 +08:00
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generation_kwargs: Dict = {
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'temperature': 0.3,
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'top_p': 0.85,
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'top_k': 5,
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'with_search_enhance': False,
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}): # noqa E125
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2023-11-21 20:25:47 +08:00
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super().__init__(path=path,
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max_seq_len=max_seq_len,
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query_per_second=query_per_second,
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meta_template=meta_template,
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2023-12-10 13:29:26 +08:00
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retry=retry,
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generation_kwargs=generation_kwargs)
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2023-11-21 20:25:47 +08:00
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self.api_key = api_key
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self.secret_key = secret_key
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self.url = url
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self.model = path
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def generate(
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self,
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inputs: List[str or PromptList],
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max_out_len: int = 512,
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) -> List[str]:
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"""Generate results given a list of inputs.
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Args:
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inputs (List[str or PromptList]): A list of strings or PromptDicts.
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The PromptDict should be organized in OpenCompass'
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API format.
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max_out_len (int): The maximum length of the output.
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Returns:
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List[str]: A list of generated strings.
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"""
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with ThreadPoolExecutor() as executor:
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results = list(
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executor.map(self._generate, inputs,
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[max_out_len] * len(inputs)))
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self.flush()
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return results
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def _generate(
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self,
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input: str or PromptList,
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max_out_len: int = 512,
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) -> str:
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"""Generate results given an input.
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Args:
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inputs (str or PromptList): A string or PromptDict.
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The PromptDict should be organized in OpenCompass'
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API format.
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max_out_len (int): The maximum length of the output.
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Returns:
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str: The generated string.
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"""
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assert isinstance(input, (str, PromptList))
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if isinstance(input, str):
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messages = [{'role': 'user', 'content': input}]
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else:
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messages = []
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for item in input:
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msg = {'content': item['prompt']}
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if item['role'] == 'HUMAN':
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msg['role'] = 'user'
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elif item['role'] == 'BOT':
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msg['role'] = 'assistant'
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messages.append(msg)
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data = {'model': self.model, 'messages': messages}
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2023-12-10 13:29:26 +08:00
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data.update(self.generation_kwargs)
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2023-11-21 20:25:47 +08:00
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def calculate_md5(input_string):
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md5 = hashlib.md5()
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md5.update(input_string.encode('utf-8'))
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encrypted = md5.hexdigest()
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return encrypted
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json_data = json.dumps(data)
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time_stamp = int(time.time())
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signature = calculate_md5(self.secret_key + json_data +
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str(time_stamp))
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headers = {
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'Content-Type': 'application/json',
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'Authorization': 'Bearer ' + self.api_key,
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'X-BC-Request-Id': 'your requestId',
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'X-BC-Timestamp': str(time_stamp),
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'X-BC-Signature': signature,
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'X-BC-Sign-Algo': 'MD5',
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}
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max_num_retries = 0
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while max_num_retries < self.retry:
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self.acquire()
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raw_response = requests.request('POST',
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url=self.url,
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headers=headers,
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json=data)
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response = raw_response.json()
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self.release()
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if response is None:
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print('Connection error, reconnect.')
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# if connect error, frequent requests will casuse
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# continuous unstable network, therefore wait here
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# to slow down the request
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self.wait()
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continue
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if raw_response.status_code == 200 and response['code'] == 0:
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2023-11-23 15:06:20 +08:00
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2023-11-21 20:25:47 +08:00
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msg = response['data']['messages'][0]['content']
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return msg
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if response['code'] != 0:
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print(response)
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2023-11-23 15:06:20 +08:00
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time.sleep(1)
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continue
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2023-11-21 20:25:47 +08:00
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print(response)
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max_num_retries += 1
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raise RuntimeError(response)
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