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my-project-public — gitlawb

#1	import os
#2	from typing import Dict, List, Optional
#3
#4	from openai import OpenAI
#5
#6	from mem0.configs.llms.base import BaseLlmConfig
#7	from mem0.llms.base import LLMBase
#8
#9
#10	class XAILLM(LLMBase):
#11	def __init__(self, config: Optional[BaseLlmConfig] = None):
#12	super().__init__(config)
#13
#14	if not self.config.model:
#15	self.config.model = "grok-2-latest"
#16
#17	api_key = self.config.api_key or os.getenv("XAI_API_KEY")
#18	base_url = self.config.xai_base_url or os.getenv("XAI_API_BASE") or "https://api.x.ai/v1"
#19	self.client = OpenAI(api_key=api_key, base_url=base_url)
#20
#21	def generate_response(
#22	self,
#23	messages: List[Dict[str, str]],
#24	response_format=None,
#25	tools: Optional[List[Dict]] = None,
#26	tool_choice: str = "auto",
#27	):
#28	"""
#29	Generate a response based on the given messages using XAI.
#30
#31	Args:
#32	messages (list): List of message dicts containing 'role' and 'content'.
#33	response_format (str or object, optional): Format of the response. Defaults to "text".
#34	tools (list, optional): List of tools that the model can call. Defaults to None.
#35	tool_choice (str, optional): Tool choice method. Defaults to "auto".
#36
#37	Returns:
#38	str: The generated response.
#39	"""
#40	params = {
#41	"model": self.config.model,
#42	"messages": messages,
#43	"temperature": self.config.temperature,
#44	"max_tokens": self.config.max_tokens,
#45	"top_p": self.config.top_p,
#46	}
#47
#48	if response_format:
#49	params["response_format"] = response_format
#50
#51	response = self.client.chat.completions.create(**params)
#52	return response.choices[0].message.content
#53

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