mirror of
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117 lines
3.9 KiB
Python
117 lines
3.9 KiB
Python
"""
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Interface for Anthropic's messages API
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Use this to call LLMs in Anthropic /messages Request/Response format
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This is an __init__.py file to allow the following interface
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- litellm.messages.acreate
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- litellm.messages.create
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"""
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from typing import AsyncIterator, Dict, Iterator, List, Optional, Union
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from litellm.llms.anthropic.experimental_pass_through.messages.handler import (
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anthropic_messages as _async_anthropic_messages,
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)
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from litellm.types.llms.anthropic_messages.anthropic_response import (
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AnthropicMessagesResponse,
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)
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async def acreate(
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max_tokens: int,
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messages: List[Dict],
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model: str,
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metadata: Optional[Dict] = None,
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stop_sequences: Optional[List[str]] = None,
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stream: Optional[bool] = False,
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system: Optional[str] = None,
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temperature: Optional[float] = 1.0,
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thinking: Optional[Dict] = None,
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tool_choice: Optional[Dict] = None,
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tools: Optional[List[Dict]] = None,
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top_k: Optional[int] = None,
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top_p: Optional[float] = None,
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**kwargs
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) -> Union[AnthropicMessagesResponse, AsyncIterator]:
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"""
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Async wrapper for Anthropic's messages API
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Args:
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max_tokens (int): Maximum tokens to generate (required)
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messages (List[Dict]): List of message objects with role and content (required)
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model (str): Model name to use (required)
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metadata (Dict, optional): Request metadata
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stop_sequences (List[str], optional): Custom stop sequences
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stream (bool, optional): Whether to stream the response
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system (str, optional): System prompt
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temperature (float, optional): Sampling temperature (0.0 to 1.0)
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thinking (Dict, optional): Extended thinking configuration
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tool_choice (Dict, optional): Tool choice configuration
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tools (List[Dict], optional): List of tool definitions
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top_k (int, optional): Top K sampling parameter
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top_p (float, optional): Nucleus sampling parameter
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**kwargs: Additional arguments
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Returns:
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Dict: Response from the API
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"""
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return await _async_anthropic_messages(
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max_tokens=max_tokens,
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messages=messages,
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model=model,
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metadata=metadata,
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stop_sequences=stop_sequences,
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stream=stream,
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system=system,
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temperature=temperature,
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thinking=thinking,
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tool_choice=tool_choice,
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tools=tools,
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top_k=top_k,
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top_p=top_p,
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**kwargs,
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)
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async def create(
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max_tokens: int,
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messages: List[Dict],
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model: str,
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metadata: Optional[Dict] = None,
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stop_sequences: Optional[List[str]] = None,
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stream: Optional[bool] = False,
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system: Optional[str] = None,
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temperature: Optional[float] = 1.0,
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thinking: Optional[Dict] = None,
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tool_choice: Optional[Dict] = None,
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tools: Optional[List[Dict]] = None,
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top_k: Optional[int] = None,
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top_p: Optional[float] = None,
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**kwargs
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) -> Union[AnthropicMessagesResponse, Iterator]:
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"""
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Async wrapper for Anthropic's messages API
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Args:
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max_tokens (int): Maximum tokens to generate (required)
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messages (List[Dict]): List of message objects with role and content (required)
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model (str): Model name to use (required)
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metadata (Dict, optional): Request metadata
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stop_sequences (List[str], optional): Custom stop sequences
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stream (bool, optional): Whether to stream the response
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system (str, optional): System prompt
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temperature (float, optional): Sampling temperature (0.0 to 1.0)
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thinking (Dict, optional): Extended thinking configuration
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tool_choice (Dict, optional): Tool choice configuration
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tools (List[Dict], optional): List of tool definitions
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top_k (int, optional): Top K sampling parameter
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top_p (float, optional): Nucleus sampling parameter
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**kwargs: Additional arguments
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Returns:
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Dict: Response from the API
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"""
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raise NotImplementedError("This function is not implemented")
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