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#1	import logging
#2	import os
#3	from typing import Any, Optional
#4
#5	try:
#6	from langchain_anthropic import ChatAnthropic
#7	except ImportError:
#8	raise ImportError("Please install the langchain-anthropic package by running `pip install langchain-anthropic`.")
#9
#10	from embedchain.config import BaseLlmConfig
#11	from embedchain.helpers.json_serializable import register_deserializable
#12	from embedchain.llm.base import BaseLlm
#13
#14	logger = logging.getLogger(__name__)
#15
#16
#17	@register_deserializable
#18	class AnthropicLlm(BaseLlm):
#19	def __init__(self, config: Optional[BaseLlmConfig] = None):
#20	super().__init__(config=config)
#21	if not self.config.api_key and "ANTHROPIC_API_KEY" not in os.environ:
#22	raise ValueError("Please set the ANTHROPIC_API_KEY environment variable or pass it in the config.")
#23
#24	def get_llm_model_answer(self, prompt) -> tuple[str, Optional[dict[str, Any]]]:
#25	if self.config.token_usage:
#26	response, token_info = self._get_answer(prompt, self.config)
#27	model_name = "anthropic/" + self.config.model
#28	if model_name not in self.config.model_pricing_map:
#29	raise ValueError(
#30	f"Model {model_name} not found in `model_prices_and_context_window.json`. \
#31	You can disable token usage by setting `token_usage` to False."
#32	)
#33	total_cost = (
#34	self.config.model_pricing_map[model_name]["input_cost_per_token"] * token_info["input_tokens"]
#35	) + self.config.model_pricing_map[model_name]["output_cost_per_token"] * token_info["output_tokens"]
#36	response_token_info = {
#37	"prompt_tokens": token_info["input_tokens"],
#38	"completion_tokens": token_info["output_tokens"],
#39	"total_tokens": token_info["input_tokens"] + token_info["output_tokens"],
#40	"total_cost": round(total_cost, 10),
#41	"cost_currency": "USD",
#42	}
#43	return response, response_token_info
#44	return self._get_answer(prompt, self.config)
#45
#46	@staticmethod
#47	def _get_answer(prompt: str, config: BaseLlmConfig) -> str:
#48	api_key = config.api_key or os.getenv("ANTHROPIC_API_KEY")
#49	chat = ChatAnthropic(anthropic_api_key=api_key, temperature=config.temperature, model_name=config.model)
#50
#51	if config.max_tokens and config.max_tokens != 1000:
#52	logger.warning("Config option `max_tokens` is not supported by this model.")
#53
#54	messages = BaseLlm._get_messages(prompt, system_prompt=config.system_prompt)
#55
#56	chat_response = chat.invoke(messages)
#57	if config.token_usage:
#58	return chat_response.content, chat_response.response_metadata["token_usage"]
#59	return chat_response.content
#60

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