File size: 7,911 Bytes
256a159 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 |
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 ERNIEBot(BaseAPIModel):
"""Model wrapper around ERNIE-Bot.
Documentation: https://cloud.baidu.com/doc/WENXINWORKSHOP/s/jlil56u11
Args:
path (str): The name of ENRIE-bot model.
e.g. `erniebot`
model_type (str): The type of the model
e.g. `chat`
secretkey (str): secretkey in order to obtain access_token
key (str): Authorization key.
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,
key: str,
secretkey: 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': 0.8,
}):
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.headers = {'Content_Type': 'application/json'}
self.secretkey = secretkey
self.key = key
self.url = url
access_token, _ = self._generate_access_token()
self.access_token = access_token
print(access_token)
def _generate_access_token(self):
try:
BAIDU_APIKEY = self.key
BAIDU_SECRETKEY = self.secretkey
url = f'https://aip.baidubce.com/oauth/2.0/token?' \
f'client_id={BAIDU_APIKEY}&client_secret={BAIDU_SECRETKEY}' \
f'&grant_type=client_credentials'
headers = {
'Content-Type': 'application/json',
'Accept': 'application/json'
}
response = requests.request('POST', url, headers=headers)
resp_dict = response.json()
if response.status_code == 200:
access_token = resp_dict.get('access_token')
refresh_token = resp_dict.get('refresh_token')
if 'error' in resp_dict:
raise ValueError(f'Failed to obtain certificate.'
f'{resp_dict.get("error")}')
else:
return access_token, refresh_token
else:
error = resp_dict.get('error')
raise ValueError(
f'Failed to requests obtain certificate {error}.')
except Exception as ex:
raise ex
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))
"""
{
"messages": [
{"role":"user","content":"请介绍一下你自己"},
{"role":"assistant","content":"我是百度公司开发的人工智能语言模型"},
{"role":"user","content": "我在上海，周末可以去哪里玩？"},
{"role":"assistant","content": "上海是一个充满活力和文化氛围的城市"},
{"role":"user","content": "周末这里的天气怎么样？"}
]
}
"""
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 = {'messages': messages}
data.update(self.generation_kwargs)
max_num_retries = 0
while max_num_retries < self.retry:
self.acquire()
try:
raw_response = requests.request('POST',
url=self.url +
self.access_token,
headers=self.headers,
json=data)
response = raw_response.json()
except Exception as err:
print('Request Error:{}'.format(err))
time.sleep(3)
continue
self.release()
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:
try:
msg = response['result']
return msg
except KeyError:
print(response)
self.logger.error(str(response['error_code']))
if response['error_code'] == 336007:
# exceed max length
return ''
time.sleep(1)
continue
if (response['error_code'] == 110 or response['error_code'] == 100
or response['error_code'] == 111
or response['error_code'] == 200
or response['error_code'] == 1000
or response['error_code'] == 1001
or response['error_code'] == 1002
or response['error_code'] == 21002
or response['error_code'] == 216100
or response['error_code'] == 336001
or response['error_code'] == 336003
or response['error_code'] == 336000
or response['error_code'] == 336007):
print(response['error_msg'])
return ''
print(response)
max_num_retries += 1
raise RuntimeError(response['error_msg'])
|