chore: initial public snapshot for github upload
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from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
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import litellm
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from litellm._logging import verbose_logger
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from litellm.constants import XAI_API_BASE
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from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig
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from litellm.secret_managers.main import get_secret_str
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from litellm.types.llms.openai import ResponsesAPIOptionalRequestParams
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from litellm.types.llms.xai import XAIWebSearchTool, XAIXSearchTool
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from litellm.types.router import GenericLiteLLMParams
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from litellm.types.utils import LlmProviders
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if TYPE_CHECKING:
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from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
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LiteLLMLoggingObj = _LiteLLMLoggingObj
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else:
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LiteLLMLoggingObj = Any
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class XAIResponsesAPIConfig(OpenAIResponsesAPIConfig):
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"""
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Configuration for XAI's Responses API.
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Inherits from OpenAIResponsesAPIConfig since XAI's Responses API is largely
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compatible with OpenAI's, with a few differences:
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- Does not support the 'instructions' parameter
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- Requires code_interpreter tools to have 'container' field removed
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- Recommends store=false when sending images
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Reference: https://docs.x.ai/docs/api-reference#create-new-response
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"""
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@property
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def custom_llm_provider(self) -> LlmProviders:
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return LlmProviders.XAI
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def get_supported_openai_params(self, model: str) -> list:
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"""
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Get supported parameters for XAI Responses API.
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XAI supports most OpenAI Responses API params except 'instructions'.
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"""
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supported_params = super().get_supported_openai_params(model)
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# Remove 'instructions' as it's not supported by XAI
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if "instructions" in supported_params:
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supported_params.remove("instructions")
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return supported_params
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def _transform_web_search_tool(
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self, tool: Dict[str, Any]
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) -> Union[XAIWebSearchTool, Dict[str, Any]]:
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"""
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Transform web_search tool to XAI format.
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XAI supports web_search with specific filters:
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- allowed_domains (max 5)
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- excluded_domains (max 5)
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- enable_image_understanding
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XAI does NOT support search_context_size (OpenAI-specific).
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"""
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xai_tool: Dict[str, Any] = {"type": "web_search"}
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# Remove search_context_size if present (not supported by XAI)
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if "search_context_size" in tool:
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verbose_logger.info(
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"XAI does not support 'search_context_size' parameter. Removing it from web_search tool."
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)
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# Handle filters (XAI-specific structure)
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filters = {}
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if "allowed_domains" in tool:
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allowed_domains = tool["allowed_domains"]
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filters["allowed_domains"] = allowed_domains
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if "excluded_domains" in tool:
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excluded_domains = tool["excluded_domains"]
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filters["excluded_domains"] = excluded_domains
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# Add filters if any were specified
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if filters:
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xai_tool["filters"] = filters
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# Handle enable_image_understanding (top-level in XAI format)
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if "enable_image_understanding" in tool:
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xai_tool["enable_image_understanding"] = tool["enable_image_understanding"]
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return xai_tool
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def _transform_x_search_tool(
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self, tool: Dict[str, Any]
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) -> Union[XAIXSearchTool, Dict[str, Any]]:
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"""
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Transform x_search tool to XAI format.
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XAI supports x_search with specific parameters:
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- allowed_x_handles (max 10)
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- excluded_x_handles (max 10)
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- from_date (ISO8601: YYYY-MM-DD)
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- to_date (ISO8601: YYYY-MM-DD)
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- enable_image_understanding
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- enable_video_understanding
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"""
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xai_tool: Dict[str, Any] = {"type": "x_search"}
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# Handle allowed_x_handles
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if "allowed_x_handles" in tool:
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allowed_handles = tool["allowed_x_handles"]
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xai_tool["allowed_x_handles"] = allowed_handles
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# Handle excluded_x_handles
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if "excluded_x_handles" in tool:
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excluded_handles = tool["excluded_x_handles"]
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xai_tool["excluded_x_handles"] = excluded_handles
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# Handle date range
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if "from_date" in tool:
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xai_tool["from_date"] = tool["from_date"]
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if "to_date" in tool:
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xai_tool["to_date"] = tool["to_date"]
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# Handle media understanding flags
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if "enable_image_understanding" in tool:
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xai_tool["enable_image_understanding"] = tool["enable_image_understanding"]
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if "enable_video_understanding" in tool:
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xai_tool["enable_video_understanding"] = tool["enable_video_understanding"]
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return xai_tool
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def map_openai_params(
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self,
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response_api_optional_params: ResponsesAPIOptionalRequestParams,
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model: str,
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drop_params: bool,
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) -> Dict:
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"""
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Map parameters for XAI Responses API.
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Handles XAI-specific transformations:
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1. Drops 'instructions' parameter (not supported)
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2. Transforms code_interpreter tools to remove 'container' field
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3. Transforms web_search tools to XAI format (removes search_context_size, adds filters)
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4. Transforms x_search tools to XAI format
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5. Sets store=false when images are detected (recommended by XAI)
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"""
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params = dict(response_api_optional_params)
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# Drop instructions parameter (not supported by XAI)
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if "instructions" in params:
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verbose_logger.debug(
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"XAI Responses API does not support 'instructions' parameter. Dropping it."
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)
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params.pop("instructions")
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if "metadata" in params:
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verbose_logger.debug(
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"XAI Responses API does not support 'metadata' parameter. Dropping it."
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)
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params.pop("metadata")
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# Transform tools
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if "tools" in params and params["tools"]:
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tools_list = params["tools"]
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# Ensure tools is a list for iteration
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if not isinstance(tools_list, list):
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tools_list = [tools_list]
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transformed_tools: List[Any] = []
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for tool in tools_list:
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if isinstance(tool, dict):
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tool_type = tool.get("type")
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if tool_type == "code_interpreter":
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# XAI supports code_interpreter but doesn't use the container field
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verbose_logger.debug(
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"XAI: Transforming code_interpreter tool, removing container field"
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)
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transformed_tools.append({"type": "code_interpreter"})
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elif tool_type == "web_search":
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# Transform web_search to XAI format
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verbose_logger.debug(
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"XAI: Transforming web_search tool to XAI format"
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)
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transformed_tools.append(self._transform_web_search_tool(tool))
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elif tool_type == "x_search":
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# Transform x_search to XAI format
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verbose_logger.debug(
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"XAI: Transforming x_search tool to XAI format"
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)
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transformed_tools.append(self._transform_x_search_tool(tool))
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else:
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# Keep other tools as-is
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transformed_tools.append(tool)
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else:
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transformed_tools.append(tool)
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params["tools"] = transformed_tools
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return params
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def validate_environment(
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self, headers: dict, model: str, litellm_params: Optional[GenericLiteLLMParams]
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) -> dict:
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"""
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Validate environment and set up headers for XAI API.
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Uses XAI_API_KEY from environment or litellm_params.
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"""
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litellm_params = litellm_params or GenericLiteLLMParams()
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api_key = (
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litellm_params.api_key or litellm.api_key or get_secret_str("XAI_API_KEY")
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)
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if not api_key:
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raise ValueError(
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"XAI API key is required. Set XAI_API_KEY environment variable or pass api_key parameter."
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)
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headers.update(
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{
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"Authorization": f"Bearer {api_key}",
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}
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)
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return headers
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def get_complete_url(
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self,
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api_base: Optional[str],
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litellm_params: dict,
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) -> str:
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"""
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Get the complete URL for XAI Responses API endpoint.
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Returns:
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str: The full URL for the XAI /responses endpoint
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"""
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api_base = (
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api_base
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or litellm.api_base
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or get_secret_str("XAI_API_BASE")
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or XAI_API_BASE
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)
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# Remove trailing slashes
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api_base = api_base.rstrip("/")
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return f"{api_base}/responses"
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def supports_native_websocket(self) -> bool:
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"""XAI does not support native WebSocket for Responses API"""
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return False
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