import json import os from typing import Dict, List, Optional from openai import AzureOpenAI from mem0.configs.llms.base import BaseLlmConfig from mem0.llms.base import LLMBase class AzureOpenAIStructuredLLM(LLMBase): """ A class for interacting with Azure OpenAI models using the specified configuration. """ def __init__(self, config: Optional[BaseLlmConfig] = None): """ Initializes the AzureOpenAIStructuredLLM instance with the given configuration. Args: config (Optional[BaseLlmConfig]): Configuration settings for the language model. """ super().__init__(config) # Ensure model name is set; it should match the Azure OpenAI deployment name. if not self.config.model: self.config.model = "gpt-4o-2024-08-06" api_key = ( os.getenv("LLM_AZURE_OPENAI_API_KEY") or self.config.azure_kwargs.api_key ) azure_deployment = ( os.getenv("LLM_AZURE_DEPLOYMENT") or self.config.azure_kwargs.azure_deployment ) azure_endpoint = ( os.getenv("LLM_AZURE_ENDPOINT") or self.config.azure_kwargs.azure_endpoint ) api_version = ( os.getenv("LLM_AZURE_API_VERSION") or self.config.azure_kwargs.api_version ) default_headers = self.config.azure_kwargs.default_headers self.client = AzureOpenAI( azure_deployment=azure_deployment, azure_endpoint=azure_endpoint, api_version=api_version, api_key=api_key, http_client=self.config.http_client, default_headers=default_headers, ) def generate_response( self, messages: List[Dict[str, str]], response_format: Optional[str] = None, ) -> str: """ Generates a response using Azure OpenAI based on the provided messages. Args: messages (List[Dict[str, str]]): A list of dictionaries, each containing a 'role' and 'content' key. response_format (Optional[str]): The desired format of the response. Defaults to None. Returns: str: The generated response from the model. """ params = { "model": self.config.model, "messages": messages, "temperature": self.config.temperature, "max_tokens": self.config.max_tokens, "top_p": self.config.top_p, } if response_format: params["response_format"] = response_format response = self.client.chat.completions.create(**params) return response.choices[0].message.content