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139 lines
4.7 KiB
Python
139 lines
4.7 KiB
Python
from concurrent.futures import ThreadPoolExecutor
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from typing import Dict, List, Optional, Union
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from opencompass.registry import MODELS
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from opencompass.utils import PromptList
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from .base_api import BaseAPIModel
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PromptType = Union[PromptList, str]
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@MODELS.register_module()
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class ClaudeSDK(BaseAPIModel):
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"""Model wrapper around Claude SDK API.
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Args:
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key (str): Authorization key.
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path (str): The model to be used. Defaults to claude-2.
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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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key: str,
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path: str = 'claude-2',
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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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temperature: Optional[float] = 0.0,
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thinking: Optional[Dict] = None,
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retry: int = 2,
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):
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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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retry=retry)
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try:
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from anthropic import Anthropic
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except ImportError:
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raise ImportError('Import anthropic failed. Please install it '
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'with "pip install anthropic" and try again.')
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self.anthropic = Anthropic(api_key=key)
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self.model = path
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self.temperature = temperature
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self.thinking = thinking
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def generate(
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self,
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inputs: List[PromptType],
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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[PromptType]): 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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return results
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def _generate(
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self,
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input: PromptType,
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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 (PromptType): 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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elif item['role'] == 'SYSTEM':
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msg['role'] = 'system'
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messages.append(msg)
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num_retries = 0
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while num_retries < self.retry:
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self.wait()
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try:
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api_params = {
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'model': self.model,
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'max_tokens': max_out_len,
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'temperature': self.temperature,
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'messages': messages,
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}
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if self.thinking is not None:
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api_params['thinking'] = self.thinking
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api_params['stream'] = True
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responses = self.anthropic.messages.create(**api_params)
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# Handle new response format
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for content in responses.content:
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if content.type == 'text':
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return content.text
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# If no text type content is found, return the first
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# content (backward compatibility)
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return responses.content[0].text
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except Exception as e:
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self.logger.error(e)
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num_retries += 1
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raise RuntimeError('Calling Claude API failed after retrying for '
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f'{self.retry} times. Check the logs for details.')
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