Camel.models.anthropic model

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strip_trailing_whitespace_from_messages

def strip_trailing_whitespace_from_messages(messages: List[OpenAIMessage]):

• messages (List[OpenAIMessage]): List of messages to process

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AnthropicModel

class AnthropicModel(BaseModelBackend):

• model_type (Union[ModelType, str]): Model for which a backend is created, one of CLAUDE_* series.
• model_config_dict (Optional[Dict[str, Any]], optional): A dictionary that will be fed into Anthropic API. If :obj:None, :obj:AnthropicConfig().as_dict() will be used. (default: :obj:None)
• api_key (Optional[str], optional): The API key for authenticating with the Anthropic service. (default: :obj:None)
• url (Optional[str], optional): The url to the Anthropic service. (default: :obj:None)
• token_counter (Optional[BaseTokenCounter], optional): Token counter to use for the model. If not provided, :obj:AnthropicTokenCounter will be used. (default: :obj:None)
• timeout (Optional[float], optional): The timeout value in seconds for API calls. If not provided, will fall back to the MODEL_TIMEOUT environment variable or default to 180 seconds. (default: :obj:None)
• max_retries (int, optional): Maximum number of retries for API calls. (default: :obj:3)
• client (Optional[Any], optional): A custom synchronous Anthropic client instance. If provided, this client will be used instead of creating a new one. (default: :obj:None)
• async_client (Optional[Any], optional): A custom asynchronous Anthropic client instance. If provided, this client will be used instead of creating a new one. (default: :obj:None)
• use_beta_for_structured_outputs (bool, optional): Whether to use the beta API for structured outputs. (default: :obj:False) **kwargs (Any): Additional arguments to pass to the client initialization.

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init

def __init__(
    self,
    model_type: Union[ModelType, str],
    model_config_dict: Optional[Dict[str, Any]] = None,
    api_key: Optional[str] = None,
    url: Optional[str] = None,
    token_counter: Optional[BaseTokenCounter] = None,
    timeout: Optional[float] = None,
    max_retries: int = 3,
    client: Optional[Any] = None,
    async_client: Optional[Any] = None,
    use_beta_for_structured_outputs: bool = False,
    **kwargs: Any
):

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token_counter

def token_counter(self):

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_convert_openai_to_anthropic_messages

def _convert_openai_to_anthropic_messages(self, messages: List[OpenAIMessage]):

• messages (List[OpenAIMessage]): Messages in OpenAI format.

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_convert_anthropic_to_openai_response

def _convert_anthropic_to_openai_response(self, response: Any, model: str):

• response: The response object from Anthropic API.
• model (str): The model name.

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_convert_anthropic_stream_to_openai_chunk

def _convert_anthropic_stream_to_openai_chunk(
    self,
    chunk: Any,
    model: str,
    tool_call_index: Dict[str, int],
    finish_reason_sent: bool = False
):

• chunk: The streaming chunk from Anthropic API.
• model (str): The model name.
• tool_call_index (Dict[str, int]): A mutable dict tracking tool call indices by their IDs, used to maintain consistent indexing across streaming chunks.

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_convert_openai_tools_to_anthropic

def _convert_openai_tools_to_anthropic(self, tools: Optional[List[Dict[str, Any]]]):

• tools (Optional[List[Dict[str, Any]]]): Tools in OpenAI format.

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_run

def _run(
    self,
    messages: List[OpenAIMessage],
    response_format: Optional[Type[BaseModel]] = None,
    tools: Optional[List[Dict[str, Any]]] = None
):

• messages (List[OpenAIMessage]): Message list with the chat history in OpenAI API format.
• response_format (Optional[Type[BaseModel]]): The format of the response. (Not supported by Anthropic API directly)
• tools (Optional[List[Dict[str, Any]]]): The schema of the tools to use for the request.

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_wrap_anthropic_stream

def _wrap_anthropic_stream(self, stream: Any, model: str):

• stream: The streaming response from Anthropic API.
• model (str): The model name.

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_wrap_anthropic_async_stream

def _wrap_anthropic_async_stream(self, stream: Any, model: str):

• stream: The async streaming response from Anthropic API.
• model (str): The model name.

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stream

def stream(self):