Refactored base class config for llms (#3241)

mem0/llms/anthropic.py

@@ -1,17 +1,37 @@
 import os
-from typing import Dict, List, Optional
+from typing import Dict, List, Optional, Union
 
 try:
     import anthropic
 except ImportError:
     raise ImportError("The 'anthropic' library is required. Please install it using 'pip install anthropic'.")
 
+from mem0.configs.llms.anthropic import AnthropicConfig
 from mem0.configs.llms.base import BaseLlmConfig
 from mem0.llms.base import LLMBase
 
 
 class AnthropicLLM(LLMBase):
-    def __init__(self, config: Optional[BaseLlmConfig] = None):
+    def __init__(self, config: Optional[Union[BaseLlmConfig, AnthropicConfig, Dict]] = None):
+        # Convert to AnthropicConfig if needed
+        if config is None:
+            config = AnthropicConfig()
+        elif isinstance(config, dict):
+            config = AnthropicConfig(**config)
+        elif isinstance(config, BaseLlmConfig) and not isinstance(config, AnthropicConfig):
+            # Convert BaseLlmConfig to AnthropicConfig
+            config = AnthropicConfig(
+                model=config.model,
+                temperature=config.temperature,
+                api_key=config.api_key,
+                max_tokens=config.max_tokens,
+                top_p=config.top_p,
+                top_k=config.top_k,
+                enable_vision=config.enable_vision,
+                vision_details=config.vision_details,
+                http_client_proxies=config.http_client,
+            )
+
         super().__init__(config)
 
         if not self.config.model:
@@ -26,6 +46,7 @@ class AnthropicLLM(LLMBase):
         response_format=None,
         tools: Optional[List[Dict]] = None,
         tool_choice: str = "auto",
+        **kwargs,
     ):
         """
         Generate a response based on the given messages using Anthropic.
@@ -35,6 +56,7 @@ class AnthropicLLM(LLMBase):
             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".
+            **kwargs: Additional Anthropic-specific parameters.
 
         Returns:
             str: The generated response.
@@ -48,14 +70,16 @@ class AnthropicLLM(LLMBase):
             else:
                 filtered_messages.append(message)
 
-        params = {
-            "model": self.config.model,
-            "messages": filtered_messages,
-            "system": system_message,
-            "temperature": self.config.temperature,
-            "max_tokens": self.config.max_tokens,
-            "top_p": self.config.top_p,
-        }
+        # Get common parameters
+        params = self._get_common_params(**kwargs)
+        params.update(
+            {
+                "model": self.config.model,
+                "messages": filtered_messages,
+                "system": system_message,
+            }
+        )
+
         if tools:  # TODO: Remove tools if no issues found with new memory addition logic
             params["tools"] = tools
             params["tool_choice"] = tool_choice