OpenCompass/opencompass/models/doubao_api.py

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from concurrent.futures import ThreadPoolExecutor
from typing import Dict, List, Optional, Union
from opencompass.utils.prompt import PromptList
from .base_api import BaseAPIModel
try:
from volcenginesdkarkruntime import Ark
except ImportError:
Ark = None
PromptType = Union[PromptList, str]
class Doubao(BaseAPIModel):
"""Model wrapper around Doubao.
Documentation:
https://www.volcengine.com/docs/82379/1263482
Args:
path (str): The name of Doubao model.
e.g. `Doubao`
accesskey (str): The access key
secretkey (str): secretkey in order to obtain access_token
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.
"""
is_api: bool = True
def __init__(self,
path: str,
accesskey: str,
secretkey: str,
query_per_second: int = 2,
max_seq_len: int = 2048,
meta_template: Optional[Dict] = None,
retry: int = 2,
generation_kwargs: Dict = {
'temperature': 0.7,
'top_p': 0.9,
}):
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)
if not Ark:
print('Please install related packages via'
' `pip install \'volcengine-python-sdk[ark]\'`')
self.accesskey = accesskey
self.secretkey = secretkey
self.model = path
def generate(
self,
inputs: List[PromptType],
max_out_len: int = 512,
) -> List[str]:
"""Generate results given a list of inputs.
Args:
inputs (List[PromptType]): 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: PromptType,
max_out_len: int = 512,
) -> str:
"""Generate results given an input.
Args:
input (PromptType): 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.
messages
[
{
"role": "user",
"content": "天为什么这么蓝?"
}, {
"role": "assistant",
"content": "因为有你"
}, {
"role": "user",
"content": "花儿为什么这么香?"
},
]
"""
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)
client = Ark(ak=self.accesskey, sk=self.secretkey)
req = {
'model': self.path,
'messages': messages,
}
req.update(self.generation_kwargs)
def _chat(client, req):
try:
completion = client.chat.completions.create(**req)
return completion.choices[0].message.content
except Exception as e:
print(e)
return e
max_num_retries = 0
while max_num_retries < self.retry:
self.acquire()
response = _chat(client, req)
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 isinstance(response, str):
print(response)
return response
max_num_retries += 1
raise RuntimeError(response)