Source code for oumi.inference.anthropic_inference_engine

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# you may not use this file except in compliance with the License.
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from typing import Any, Optional

from typing_extensions import override

from oumi.core.configs import GenerationParams, RemoteParams
from oumi.core.types.conversation import Conversation, Message, Role
from oumi.inference.remote_inference_engine import RemoteInferenceEngine
from oumi.utils.logging import logger

_CONTENT_KEY: str = "content"
_ROLE_KEY: str = "role"


[docs] class AnthropicInferenceEngine(RemoteInferenceEngine): """Engine for running inference against the Anthropic API. This class extends RemoteInferenceEngine to provide specific functionality for interacting with Anthropic's language models via their API. It handles the conversion of Oumi's Conversation objects to Anthropic's expected input format, as well as parsing the API responses back into Conversation objects. """ anthropic_version = "2023-06-01" """The version of the Anthropic API to use. For more information on Anthropic API versioning, see: https://docs.anthropic.com/claude/reference/versioning """ @property @override def base_url(self) -> Optional[str]: """Return the default base URL for the Anthropic API.""" return "https://api.anthropic.com/v1/messages" @property @override def api_key_env_varname(self) -> Optional[str]: """Return the default environment variable name for the Anthropic API key.""" return "ANTHROPIC_API_KEY" @override def _convert_conversation_to_api_input( self, conversation: Conversation, generation_params: GenerationParams ) -> dict[str, Any]: """Converts a conversation to an Anthropic API input. This method transforms an Oumi Conversation object into a format suitable for the Anthropic API. It handles system messages separately and structures the conversation history as required by Anthropic. See https://docs.anthropic.com/claude/reference/messages_post for details. Args: conversation: The Oumi Conversation object to convert. generation_params: Parameters for text generation. Returns: Dict[str, Any]: A dictionary containing the formatted input for the Anthropic API, including the model, messages, and generation parameters. """ # Anthropic API expects a top level `system` message, # Extract and exclude system message from the list of messages # in the conversation system_messages = [ message for message in conversation.messages if message.role == Role.SYSTEM ] if len(system_messages) > 0: system_message = system_messages[0].content if len(system_messages) > 1: logger.warning( "Multiple system messages found in conversation. " "Only using the first one." ) else: system_message = None messages = [ message for message in conversation.messages if message.role != Role.SYSTEM ] # Build request body # See https://docs.anthropic.com/claude/reference/messages_post body = { "model": self._model, "messages": self._get_list_of_message_json_dicts( messages, group_adjacent_same_role_turns=True ), "max_tokens": generation_params.max_new_tokens, "temperature": generation_params.temperature, "top_p": generation_params.top_p, } if system_message: body["system"] = system_message if generation_params.stop_strings is not None: body["stop_sequences"] = generation_params.stop_strings return body @override def _convert_api_output_to_conversation( self, response: dict[str, Any], original_conversation: Conversation ) -> Conversation: """Converts an Anthropic API response to a conversation.""" new_message = Message( content=response[_CONTENT_KEY][0]["text"], role=Role.ASSISTANT, ) return Conversation( messages=[*original_conversation.messages, new_message], metadata=original_conversation.metadata, conversation_id=original_conversation.conversation_id, ) @override def _get_request_headers(self, remote_params: RemoteParams) -> dict[str, str]: return { "Content-Type": "application/json", "anthropic-version": self.anthropic_version, "X-API-Key": self._get_api_key(remote_params) or "", }
[docs] @override def get_supported_params(self) -> set[str]: """Returns a set of supported generation parameters for this engine.""" return { "max_new_tokens", "stop_strings", "temperature", "top_p", }