OpenCompass/opencompass/models/claude_sdk_api.py

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from concurrent.futures import ThreadPoolExecutor
from typing import Dict, List, Optional, Union
from opencompass.registry import MODELS
from opencompass.utils import PromptList
from .base_api import BaseAPIModel
PromptType = Union[PromptList, str]
@MODELS.register_module()
class ClaudeSDK(BaseAPIModel):
"""Model wrapper around Claude SDK API.
Args:
key (str): Authorization key.
path (str): The model to be used. Defaults to claude-2.
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,
key: str,
path: str = 'claude-2',
query_per_second: int = 2,
max_seq_len: int = 2048,
meta_template: Optional[Dict] = None,
temperature: Optional[float] = 0.0,
retry: int = 2,
):
super().__init__(path=path,
max_seq_len=max_seq_len,
query_per_second=query_per_second,
meta_template=meta_template,
retry=retry)
try:
from anthropic import Anthropic
except ImportError:
raise ImportError('Import anthropic failed. Please install it '
'with "pip install anthropic" and try again.')
self.anthropic = Anthropic(api_key=key)
self.model = path
self.temperature = temperature
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)))
return results
def _generate(
self,
input: PromptType,
max_out_len: int = 512,
) -> str:
"""Generate results given an input.
Args:
inputs (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.
"""
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'
elif item['role'] == 'SYSTEM':
msg['role'] = 'system'
messages.append(msg)
num_retries = 0
while num_retries < self.retry:
self.wait()
try:
responses = self.anthropic.messages.create(
model=self.model,
max_tokens=max_out_len,
temperature=self.temperature,
messages=messages)
return responses.content[0].text
except Exception as e:
self.logger.error(e)
num_retries += 1
raise RuntimeError('Calling Claude API failed after retrying for '
f'{self.retry} times. Check the logs for details.')