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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 Nanbeige(BaseAPIModel):
"""Model wrapper around Nanbeige.
Documentations:
Args:
path (str): Model name, e.g. `nanbeige-plus`
key (str): Provide API Key
url (str): Provided URL
query_per_second (int): The maximum queries allowed per second
between two consecutive calls of the API. Defaults to 2.
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,
url: str = None,
query_per_second: int = 2,
max_seq_len: int = 2048,
meta_template: Optional[Dict] = None,
retry: int = 3):
super().__init__(path=path,
max_seq_len=max_seq_len,
query_per_second=query_per_second,
meta_template=meta_template,
retry=retry)
self.headers = {
'Authorization': 'Bearer ' + key,
'Content-Type': 'application/json',
}
self.model = path
self.url = url if url is not None \
else 'http://stardustlm.zhipin.com/api/gpt/open/chat/send/sync'
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 = [{'sender_type': 'USER', 'text': input}]
else:
messages = []
for item in input:
msg = {'text': item['prompt']}
if item['role'] == 'HUMAN':
msg['sender_type'] = 'USER'
elif item['role'] == 'BOT':
msg['sender_type'] = 'BOT'
messages.append(msg)
data = {
'model': self.model,
'messages': messages,
}
max_num_retries = 0
while max_num_retries < self.retry:
self.acquire()
raw_response = requests.request('POST',
url=self.url,
headers=self.headers,
json=data)
self.release()
if raw_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:
print('请求失败：', raw_response)
print('失败信息：', raw_response.text)
max_num_retries += 1
continue
response = raw_response.json()
if response['stardustCode'] == 0:
return response['reply']
# exceed concurrency limit
if response['stardustCode'] == 20035:
print(response)
time.sleep(2)
continue
print(response)
max_num_retries += 1
raise RuntimeError(raw_response.text)
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