first commit

llms/azure_openai_structured.py

@@ -0,0 +1,91 @@
+import os
+from typing import Dict, List, Optional
+
+from azure.identity import DefaultAzureCredential, get_bearer_token_provider
+from openai import AzureOpenAI
+
+from mem0.configs.llms.base import BaseLlmConfig
+from mem0.llms.base import LLMBase
+
+SCOPE = "https://cognitiveservices.azure.com/.default"
+
+
+class AzureOpenAIStructuredLLM(LLMBase):
+    def __init__(self, config: Optional[BaseLlmConfig] = 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: Optional[str] = None,
+        tools: Optional[List[Dict]] = 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)