Remove tools from LLMs (#2363)

mem0/llms/deepseek.py

@@ -9,64 +9,42 @@ from mem0.llms.base import LLMBase
 
 
 class DeepSeekLLM(LLMBase):
+    """
+    A class for interacting with DeepSeek's language models using the specified configuration.
+    """
+
     def __init__(self, config: Optional[BaseLlmConfig] = None):
+        """
+        Initializes the DeepSeekLLM instance with the given configuration.
+
+        Args:
+            config (Optional[BaseLlmConfig]): Configuration settings for the language model.
+        """
         super().__init__(config)
 
         if not self.config.model:
             self.config.model = "deepseek-chat"
 
         api_key = self.config.api_key or os.getenv("DEEPSEEK_API_KEY")
-        base_url = self.config.deepseek_base_url or os.getenv("DEEPSEEK_API_BASE") or "https://api.deepseek.com"
+        base_url = (
+            self.config.deepseek_base_url
+            or os.getenv("DEEPSEEK_API_BASE")
+            or "https://api.deepseek.com"
+        )
         self.client = OpenAI(api_key=api_key, base_url=base_url)
 
-    def _parse_response(self, response, tools):
-        """
-        Process the response based on whether tools are used or not.
-
-        Args:
-            response: The raw response from API.
-            tools: The list of tools provided in the request.
-
-        Returns:
-            str or dict: The processed response.
-        """
-        if tools:
-            processed_response = {
-                "content": response.choices[0].message.content,
-                "tool_calls": [],
-            }
-
-            if response.choices[0].message.tool_calls:
-                for tool_call in response.choices[0].message.tool_calls:
-                    processed_response["tool_calls"].append(
-                        {
-                            "name": tool_call.function.name,
-                            "arguments": json.loads(tool_call.function.arguments),
-                        }
-                    )
-
-            return processed_response
-        else:
-            return response.choices[0].message.content
-
     def generate_response(
         self,
         messages: List[Dict[str, str]],
-        response_format=None,
-        tools: Optional[List[Dict]] = None,
-        tool_choice: str = "auto",
-    ):
+    ) -> str:
         """
-        Generate a response based on the given messages using DeepSeek.
+        Generates a response using DeepSeek based on the provided messages.
 
         Args:
-            messages (list): List of message dicts containing 'role' and 'content'.
-            response_format (str or object, optional): Format of the response. Defaults to "text".
-            tools (list, optional): List of tools that the model can call. Defaults to None.
-            tool_choice (str, optional): Tool choice method. Defaults to "auto".
+            messages (List[Dict[str, str]]): A list of dictionaries, each containing a 'role' and 'content' key.
 
         Returns:
-            str: The generated response.
+            str: The generated response from the model.
         """
         params = {
             "model": self.config.model,
@@ -75,10 +53,5 @@ class DeepSeekLLM(LLMBase):
             "max_tokens": self.config.max_tokens,
             "top_p": self.config.top_p,
         }
-
-        if tools:
-            params["tools"] = tools
-            params["tool_choice"] = tool_choice
-
         response = self.client.chat.completions.create(**params)
-        return self._parse_response(response, tools)
+        return response.choices[0].message.content