Remove tools from LLMs (#2363)

mem0/llms/litellm.py

@@ -4,70 +4,50 @@ from typing import Dict, List, Optional
 try:
     import litellm
 except ImportError:
-    raise ImportError("The 'litellm' library is required. Please install it using 'pip install litellm'.")
+    raise ImportError(
+        "The 'litellm' library is required. Please install it using 'pip install litellm'."
+    )
 
 from mem0.configs.llms.base import BaseLlmConfig
 from mem0.llms.base import LLMBase
 
 
 class LiteLLM(LLMBase):
+    """
+    A class for interacting with LiteLLM's language models using the specified configuration.
+    """
+
     def __init__(self, config: Optional[BaseLlmConfig] = None):
+        """
+        Initializes the LiteLLM 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 = "gpt-4o-mini"
 
-    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",
-    ):
+        response_format: Optional[str] = None,
+    ) -> str:
         """
-        Generate a response based on the given messages using Litellm.
+        Generates a response using LiteLLM 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.
+            response_format (Optional[str]): The desired format of the response. Defaults to None.
 
         Returns:
-            str: The generated response.
+            str: The generated response from the model.
         """
         if not litellm.supports_function_calling(self.config.model):
-            raise ValueError(f"Model '{self.config.model}' in litellm does not support function calling.")
+            raise ValueError(
+                f"Model '{self.config.model}' in LiteLLM does not support function calling."
+            )
 
         params = {
             "model": self.config.model,
@@ -78,9 +58,6 @@ class LiteLLM(LLMBase):
         }
         if response_format:
             params["response_format"] = response_format
-        if tools:  # TODO: Remove tools if no issues found with new memory addition logic
-            params["tools"] = tools
-            params["tool_choice"] = tool_choice
 
         response = litellm.completion(**params)
-        return self._parse_response(response, tools)
+        return response.choices[0].message.content