Add Grok Support (#2260)

docs/components/llms/config.mdx

@@ -75,7 +75,7 @@ Here's the table based on the provided parameters:
 | `openai_base_url`    | Base URL for OpenAI API                       | OpenAI            |
 | `azure_kwargs`       | Azure LLM args for initialization             | AzureOpenAI       |
 | `deepseek_base_url`  | Base URL for DeepSeek API                     | DeepSeek          |
-
+| `xai_base_url`       | Base URL for XAI API                          | XAI               |
 
 ## Supported LLMs
 

docs/components/llms/models/xai.mdx

@@ -0,0 +1,31 @@
+[XAI](https://x.ai/) is a new AI company founded by Elon Musk that develops large language models, including Grok. Grok is trained on real-time data from X (formerly Twitter) and aims to provide accurate, up-to-date responses with a touch of wit and humor.
+
+In order to use LLMs from XAI, go to their [platform](https://console.x.ai) and get the API key. Set the API key as `XAI_API_KEY` environment variable to use the model as given below in the example.
+
+## Usage
+
+```python
+import os
+from mem0 import Memory
+
+os.environ["OPENAI_API_KEY"] = "your-api-key" # used for embedding model
+os.environ["XAI_API_KEY"] = "your-api-key"
+
+config = {
+    "llm": {
+        "provider": "xai",
+        "config": {
+            "model": "grok-2-latest",
+            "temperature": 0.1,
+            "max_tokens": 1000,
+        }
+    }
+}
+
+m = Memory.from_config(config)
+m.add("Likes to play cricket on weekends", user_id="alice", metadata={"category": "hobbies"})
+```
+
+## Config
+
+All available parameters for the `xai` config are present in [Master List of All Params in Config](../config).

docs/components/llms/overview.mdx

@@ -27,6 +27,7 @@ To view all supported llms, visit the [Supported LLMs](./models).
     <Card title="AWS bedrock" href="/components/llms/models/aws_bedrock"></Card>
     <Card title="Gemini" href="/components/llms/models/gemini"></Card>
     <Card title="DeepSeek" href="/components/llms/models/deepseek"></Card>
+    <Card title="XAI" href="/components/llms/models/xai"></Card>
 </CardGroup>
 
 ## Structured vs Unstructured Outputs

docs/docs.json

@@ -102,7 +102,9 @@
                           "components/llms/models/mistral_AI",
                           "components/llms/models/google_AI",
                           "components/llms/models/aws_bedrock",
-                          "components/llms/models/gemini"
+                          "components/llms/models/gemini",
+                          "components/llms/models/deepseek",
+                          "components/llms/models/xai"
                         ]
                       }
                     ]

mem0/configs/llms/base.py

@@ -14,10 +14,10 @@ class BaseLlmConfig(ABC):
     def __init__(
         self,
         model: Optional[str] = None,
-        temperature: float = 0,
+        temperature: float = 0.1,
         api_key: Optional[str] = None,
         max_tokens: int = 3000,
-        top_p: float = 0,
+        top_p: float = 0.1,
         top_k: int = 1,
         # Openrouter specific
         models: Optional[list[str]] = None,
@@ -35,6 +35,8 @@ class BaseLlmConfig(ABC):
         http_client_proxies: Optional[Union[Dict, str]] = None,
         # DeepSeek specific
         deepseek_base_url: Optional[str] = None,
+        # XAI specific
+        xai_base_url: Optional[str] = None,
     ):
         """
         Initializes a configuration class instance for the LLM.
@@ -73,6 +75,8 @@ class BaseLlmConfig(ABC):
         :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
+        :param xai_base_url: XAI base URL to be use, defaults to None
+        :type xai_base_url: Optional[str], optional
         """
 
         self.model = model
@@ -101,3 +105,6 @@ class BaseLlmConfig(ABC):
 
         # AzureOpenAI specific
         self.azure_kwargs = AzureConfig(**azure_kwargs) or {}
+
+        # XAI specific
+        self.xai_base_url = xai_base_url

mem0/llms/configs.py

@@ -23,6 +23,7 @@ class LlmConfig(BaseModel):
             "azure_openai_structured",
             "gemini",
             "deepseek",
+            "xai"
         ):
             return v
         else:

mem0/llms/xai.py

@@ -0,0 +1,48 @@
+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 XAILLM(LLMBase):
+    def __init__(self, config: Optional[BaseLlmConfig] = None):
+        super().__init__(config)
+
+        if not self.config.model:
+            self.config.model = "grok-2-latest"
+
+        api_key = self.config.api_key or os.getenv("XAI_API_KEY")
+        base_url = self.config.xai_base_url or os.getenv("XAI_API_BASE") or "https://api.x.ai/v1"
+        self.client = OpenAI(api_key=api_key, base_url=base_url)
+
+    def generate_response(
+        self,
+        messages: List[Dict[str, str]],
+        response_format=None
+    ):
+        """
+        Generate a response based on the given messages using XAI.
+
+        Args:
+            messages (list): List of message dicts containing 'role' and 'content'.
+            response_format (str or object, optional): Format of the response. Defaults to "text".
+
+        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 response_format:
+            params["response_format"] = response_format
+
+        response = self.client.chat.completions.create(**params)
+        return response.choices[0].message.content

mem0/utils/factory.py

@@ -24,6 +24,7 @@ class LlmFactory:
         "azure_openai_structured": "mem0.llms.azure_openai_structured.AzureOpenAIStructuredLLM",
         "gemini": "mem0.llms.gemini.GeminiLLM",
         "deepseek": "mem0.llms.deepseek.DeepSeekLLM",
+        "xai": "mem0.llms.xai.XAILLM",
     }
 
     @classmethod