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#1	import os
#2	from typing import Dict, List, Optional, Union
#3
#4	try:
#5	import anthropic
#6	except ImportError:
#7	raise ImportError("The 'anthropic' library is required. Please install it using 'pip install anthropic'.")
#8
#9	from mem0.configs.llms.anthropic import AnthropicConfig
#10	from mem0.configs.llms.base import BaseLlmConfig
#11	from mem0.llms.base import LLMBase
#12
#13
#14	class AnthropicLLM(LLMBase):
#15	def __init__(self, config: Optional[Union[BaseLlmConfig, AnthropicConfig, Dict]] = None):
#16	# Convert to AnthropicConfig if needed
#17	if config is None:
#18	config = AnthropicConfig()
#19	elif isinstance(config, dict):
#20	config = AnthropicConfig(**config)
#21	elif isinstance(config, BaseLlmConfig) and not isinstance(config, AnthropicConfig):
#22	# Convert BaseLlmConfig to AnthropicConfig
#23	config = AnthropicConfig(
#24	model=config.model,
#25	temperature=config.temperature,
#26	api_key=config.api_key,
#27	max_tokens=config.max_tokens,
#28	top_p=config.top_p,
#29	top_k=config.top_k,
#30	enable_vision=config.enable_vision,
#31	vision_details=config.vision_details,
#32	http_client_proxies=config.http_client,
#33	)
#34
#35	super().__init__(config)
#36
#37	if not self.config.model:
#38	self.config.model = "claude-3-5-sonnet-20240620"
#39
#40	api_key = self.config.api_key or os.getenv("ANTHROPIC_API_KEY")
#41	self.client = anthropic.Anthropic(api_key=api_key)
#42
#43	def generate_response(
#44	self,
#45	messages: List[Dict[str, str]],
#46	response_format=None,
#47	tools: Optional[List[Dict]] = None,
#48	tool_choice: str = "auto",
#49	**kwargs,
#50	):
#51	"""
#52	Generate a response based on the given messages using Anthropic.
#53
#54	Args:
#55	messages (list): List of message dicts containing 'role' and 'content'.
#56	response_format (str or object, optional): Format of the response. Defaults to "text".
#57	tools (list, optional): List of tools that the model can call. Defaults to None.
#58	tool_choice (str, optional): Tool choice method. Defaults to "auto".
#59	**kwargs: Additional Anthropic-specific parameters.
#60
#61	Returns:
#62	str: The generated response.
#63	"""
#64	# Separate system message from other messages
#65	system_message = ""
#66	filtered_messages = []
#67	for message in messages:
#68	if message["role"] == "system":
#69	system_message = message["content"]
#70	else:
#71	filtered_messages.append(message)
#72
#73	params = self._get_supported_params(messages=messages, **kwargs)
#74	params.update(
#75	{
#76	"model": self.config.model,
#77	"messages": filtered_messages,
#78	"system": system_message,
#79	}
#80	)
#81
#82	if tools: # TODO: Remove tools if no issues found with new memory addition logic
#83	params["tools"] = tools
#84	params["tool_choice"] = tool_choice
#85
#86	response = self.client.messages.create(**params)
#87	return response.content[0].text
#88

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