import os
from azure.identity import DefaultAzureCredential, get_bearer_token_provider
from openai import AzureOpenAI
from selfmemory.llms.base import LLMBase
from selfmemory.llms.configs import BaseLlmConfig
SCOPE = "https://cognitiveservices.azure.com/.default"
class AzureOpenAIStructuredLLM(LLMBase):
def __init__(self, config: BaseLlmConfig | None = None):
super().__init__(config)
# Model name should match the custom deployment name chosen for it.
if not self.config.model:
self.config.model = "gpt-4.1-nano-2025-04-14"
api_key = self.config.azure_kwargs.api_key or os.getenv(
"LLM_AZURE_OPENAI_API_KEY"
)
azure_deployment = self.config.azure_kwargs.azure_deployment or os.getenv(
"LLM_AZURE_DEPLOYMENT"
)
azure_endpoint = self.config.azure_kwargs.azure_endpoint or os.getenv(
"LLM_AZURE_ENDPOINT"
)
api_version = self.config.azure_kwargs.api_version or os.getenv(
"LLM_AZURE_API_VERSION"
)
default_headers = self.config.azure_kwargs.default_headers
# If the API key is not provided or is a placeholder, use DefaultAzureCredential.
if api_key is None or api_key == "" or api_key == "your-api-key":
self.credential = DefaultAzureCredential()
azure_ad_token_provider = get_bearer_token_provider(
self.credential,
SCOPE,
)
api_key = None
else:
azure_ad_token_provider = None
# Can display a warning if API version is of model and api-version
self.client = AzureOpenAI(
azure_deployment=azure_deployment,
azure_endpoint=azure_endpoint,
azure_ad_token_provider=azure_ad_token_provider,
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: str | None = None,
tools: list[dict] | None = None,
tool_choice: str = "auto",
) -> str:
"""
Generate a response based on the given messages using Azure OpenAI.
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.
"""
user_prompt = messages[-1]["content"]
user_prompt = user_prompt.replace("assistant", "ai")
messages[-1]["content"] = user_prompt
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
if tools:
params["tools"] = tools
params["tool_choice"] = tool_choice
if tools:
params["tools"] = tools
params["tool_choice"] = tool_choice
response = self.client.chat.completions.create(**params)
return self._parse_response(response, tools)
