feat: Support xAI native client and openai compatible response client

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -26,7 +26,7 @@ body:
     attributes:
       label: What version of camel are you using?
       description: Run command `python3 -c 'print(__import__("camel").__version__)'` in your shell and paste the output here.
-      placeholder: E.g., 0.2.91a0
+      placeholder: E.g., 0.2.91a1
     validations:
       required: true
 

camel/__init__.py

@@ -14,7 +14,7 @@
 
 from camel.logger import disable_logging, enable_logging, set_log_level
 
-__version__ = '0.2.91a0'
+__version__ = '0.2.91a1'
 
 __all__ = [
     '__version__',

camel/configs/__init__.py

@@ -60,6 +60,7 @@
 from .vllm_config import VLLM_API_PARAMS, VLLMConfig
 from .volcano_config import VOLCANO_API_PARAMS, VolcanoConfig
 from .watsonx_config import WATSONX_API_PARAMS, WatsonXConfig
+from .xai_config import XAI_API_PARAMS, XAIConfig
 from .yi_config import YI_API_PARAMS, YiConfig
 from .zhipuai_config import ZHIPUAI_API_PARAMS, ZhipuAIConfig
 
@@ -151,4 +152,6 @@
     'VOLCANO_API_PARAMS',
     'AvianConfig',
     'AVIAN_API_PARAMS',
+    'XAIConfig',
+    'XAI_API_PARAMS',
 ]

camel/configs/xai_config.py

@@ -0,0 +1,89 @@
+# ========= Copyright 2023-2026 @ CAMEL-AI.org. All Rights Reserved. =========
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ========= Copyright 2023-2026 @ CAMEL-AI.org. All Rights Reserved. =========
+
+from __future__ import annotations
+
+from typing import Dict, Optional, Sequence, Type, Union
+
+from pydantic import BaseModel
+
+from camel.configs.base_config import BaseConfig
+
+
+class XAIConfig(BaseConfig):
+    r"""Defines the parameters for generating chat completions using the
+    xAI native SDK (gRPC).
+
+    Args:
+        temperature (float, optional): Sampling temperature to use, between
+            :obj:`0` and :obj:`2`. Higher values make the output more random,
+            while lower values make it more focused and deterministic.
+            (default: :obj:`None`)
+        top_p (float, optional): An alternative to sampling with temperature,
+            called nucleus sampling, where the model considers the results of
+            the tokens with top_p probability mass. So :obj:`0.1` means only
+            the tokens comprising the top 10% probability mass are considered.
+            (default: :obj:`None`)
+        max_tokens (int, optional): The maximum number of tokens to generate
+            in the chat completion. (default: :obj:`None`)
+        stop (str or list, optional): Up to :obj:`4` sequences where the API
+            will stop generating further tokens. (default: :obj:`None`)
+        stream (bool, optional): If True, partial message deltas will be sent
+            as they become available. (default: :obj:`None`)
+        response_format (object, optional): An object specifying the format
+            that the model must output. Setting to a Pydantic BaseModel enables
+            JSON schema mode for structured outputs.
+            (default: :obj:`None`)
+        tool_choice (Union[dict[str, str], str], optional): Controls which (if
+            any) tool is called by the model. :obj:`"none"` means the model
+            will not call any tool. :obj:`"auto"` means the model can pick
+            between generating a message or calling one or more tools.
+            :obj:`"required"` means the model must call one or more tools.
+            (default: :obj:`None`)
+        reasoning_effort (str, optional): Controls the reasoning effort for
+            reasoning models. Valid values: :obj:`"low"`, :obj:`"medium"`,
+            :obj:`"high"`. (default: :obj:`None`)
+        use_encrypted_content (bool, optional): If True, encrypted reasoning
+            traces will be returned and preserved across conversation turns.
+            This is required for multi-turn reasoning with thinking models.
+            (default: :obj:`None`)
+        store_messages (bool, optional): If True, request/response history is
+            stored on xAI's servers for up to 30 days, enabling conversation
+            chaining via previous_response_id. If False, history is managed
+            locally. (default: :obj:`None`)
+        frequency_penalty (float, optional): Penalizes new tokens based on
+            their existing frequency in the text so far. Values between
+            :obj:`-2.0` and :obj:`2.0`. (default: :obj:`None`)
+        presence_penalty (float, optional): Penalizes new tokens based on
+            whether they appear in the text so far. Values between
+            :obj:`-2.0` and :obj:`2.0`. (default: :obj:`None`)
+    """
+
+    temperature: Optional[float] = None
+    top_p: Optional[float] = None
+    max_tokens: Optional[int] = None
+    stop: Optional[Union[str, Sequence[str]]] = None
+    stream: Optional[bool] = None
+    response_format: Optional[Union[Type[BaseModel], dict]] = None
+    tool_choice: Optional[
+        Union[Dict[str, Union[str, Dict[str, str]]], str]
+    ] = None
+    reasoning_effort: Optional[str] = None
+    use_encrypted_content: Optional[bool] = None
+    store_messages: Optional[bool] = None
+    frequency_penalty: Optional[float] = None
+    presence_penalty: Optional[float] = None
+
+
+XAI_API_PARAMS = {param for param in XAIConfig.model_fields.keys()}

camel/embeddings/vlm_embedding.py

@@ -110,11 +110,11 @@ def embed_list(
                     images=obj,
                     return_tensors="pt",
                     padding=True,
-                    **image_processor_kwargs,
+                    **(image_processor_kwargs or {}),
                 )
                 image_feature = (
                     self.model.get_image_features(
-                        **image_input, **model_kwargs
+                        **image_input, **(model_kwargs or {})
                     )
                     .squeeze(dim=0)
                     .tolist()
@@ -125,10 +125,12 @@ def embed_list(
                     text=obj,
                     return_tensors="pt",
                     padding=True,
-                    **tokenizer_kwargs,
+                    **(tokenizer_kwargs or {}),
                 )
                 text_feature = (
-                    self.model.get_text_features(**text_input, **model_kwargs)
+                    self.model.get_text_features(
+                        **text_input, **(model_kwargs or {})
+                    )
                     .squeeze(dim=0)
                     .tolist()
                 )

camel/interpreters/internal_python_interpreter.py

@@ -405,7 +405,7 @@ def _execute_call(self, call: ast.Call) -> Any:
             keyword.arg: self._execute_ast(keyword.value)
             for keyword in call.keywords
         }
-        return callable_func(*args, **kwargs)
+        return callable_func(*args, **kwargs)  # type: ignore[arg-type]
 
     def _execute_subscript(self, subscript: ast.Subscript):
         index = self._execute_ast(subscript.slice)

camel/models/__init__.py

@@ -62,6 +62,7 @@
 from .vllm_model import VLLMModel
 from .volcano_model import VolcanoModel
 from .watsonx_model import WatsonXModel
+from .xai_model import XAIModel
 from .yi_model import YiModel
 from .zhipuai_model import ZhipuAIModel
 
@@ -120,4 +121,5 @@
     'AihubMixModel',
     'FunctionGemmaModel',
     'AvianModel',
+    'XAIModel',
 ]

camel/models/mistral_model.py

@@ -202,15 +202,15 @@ def _to_mistral_chatmessage(
                 mistral_tool_calls = []
                 for tool_call in tool_calls_list:
                     function_call = FunctionCall(
-                        name=tool_call["function"].get("name"),  # type: ignore[attr-defined]
-                        arguments=tool_call["function"].get("arguments"),  # type: ignore[attr-defined]
+                        name=tool_call["function"].get("name"),  # type: ignore[index]
+                        arguments=tool_call["function"].get("arguments"),  # type: ignore[index]
                     )
                     # Preserve the original tool call id to keep tool result
                     # ordering valid across turns.
                     mistral_tool_calls.append(
                         ToolCall(
                             function=function_call,
-                            id=tool_call.get("id"),  # type: ignore[attr-defined]
+                            id=tool_call.get("id"),  # type: ignore[union-attr]
                         )
                     )
 

camel/models/model_factory.py

@@ -60,6 +60,7 @@
 from camel.models.vllm_model import VLLMModel
 from camel.models.volcano_model import VolcanoModel
 from camel.models.watsonx_model import WatsonXModel
+from camel.models.xai_model import XAIModel
 from camel.models.yi_model import YiModel
 from camel.models.zhipuai_model import ZhipuAIModel
 from camel.types import ModelPlatformType, ModelType, UnifiedModelType
@@ -121,6 +122,7 @@ class ModelFactory:
         ModelPlatformType.AIHUBMIX: AihubMixModel,
         ModelPlatformType.AVIAN: AvianModel,
         ModelPlatformType.FUNCTION_GEMMA: FunctionGemmaModel,
+        ModelPlatformType.XAI: XAIModel,
     }
 
     @staticmethod