DeepSeek Integration (#2173)

mem0/configs/llms/base.py

@@ -33,6 +33,8 @@ class BaseLlmConfig(ABC):
         azure_kwargs: Optional[AzureConfig] = {},
         # AzureOpenAI specific
         http_client_proxies: Optional[Union[Dict, str]] = None,
+        # DeepSeek specific
+        deepseek_base_url: Optional[str] = None,
     ):
         """
         Initializes a configuration class instance for the LLM.
@@ -69,6 +71,8 @@ class BaseLlmConfig(ABC):
         :type azure_kwargs: Optional[Dict[str, Any]], defaults a dict inside init
         :param http_client_proxies: The proxy server(s) settings used to create self.http_client, defaults to None
         :type http_client_proxies: Optional[Dict | str], optional
+        :param deepseek_base_url: DeepSeek base URL to be use, defaults to None
+        :type deepseek_base_url: Optional[str], optional
         """
 
         self.model = model
@@ -92,5 +96,8 @@ class BaseLlmConfig(ABC):
         # Ollama specific
         self.ollama_base_url = ollama_base_url
 
+        # DeepSeek specific
+        self.deepseek_base_url = deepseek_base_url
+
         # AzureOpenAI specific
         self.azure_kwargs = AzureConfig(**azure_kwargs) or {}

mem0/llms/configs.py

@@ -22,6 +22,7 @@ class LlmConfig(BaseModel):
             "openai_structured",
             "azure_openai_structured",
             "gemini",
+            "deepseek",
         ):
             return v
         else:

mem0/llms/deepseek.py

@@ -0,0 +1,84 @@
+import json
+import os
+from typing import Dict, List, Optional
+
+from openai import OpenAI
+
+from mem0.configs.llms.base import BaseLlmConfig
+from mem0.llms.base import LLMBase
+
+
+class DeepSeekLLM(LLMBase):
+    def __init__(self, config: Optional[BaseLlmConfig] = None):
+        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"
+        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",
+    ):
+        """
+        Generate a response based on the given messages using DeepSeek.
+
+        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".
+
+        Returns:
+            str: The generated response.
+        """
+        params = {
+            "model": self.config.model,
+            "messages": messages,
+            "temperature": self.config.temperature,
+            "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)

mem0/utils/factory.py

@@ -23,6 +23,7 @@ class LlmFactory:
         "anthropic": "mem0.llms.anthropic.AnthropicLLM",
         "azure_openai_structured": "mem0.llms.azure_openai_structured.AzureOpenAIStructuredLLM",
         "gemini": "mem0.llms.gemini.GeminiLLM",
+        "deepseek": "mem0.llms.deepseek.DeepSeekLLM",
     }
 
     @classmethod