From 6bc926e04bb20508b359309c77c0b833ba8f5998 Mon Sep 17 00:00:00 2001
From: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Date: Sat, 12 Jul 2025 09:20:31 -0700
Subject: [PATCH] [Bug Fix] xai/ translation fix - ensure finish_reason
 includes tool calls when xai responses with tool calls (#12545)

* Helper to fix finish_reason for tool calls when XAI API returns empty string

* use llm http handler for Groq
---
 litellm/llms/xai/chat/transformation.py | 60 +++++++++++++++++++++++++
 litellm/main.py                         | 31 ++++++++++++-
 2 files changed, 90 insertions(+), 1 deletion(-)

diff --git a/litellm/llms/xai/chat/transformation.py b/litellm/llms/xai/chat/transformation.py
index 272e3841eb6..14b62db41b3 100644
--- a/litellm/llms/xai/chat/transformation.py
+++ b/litellm/llms/xai/chat/transformation.py
@@ -1,5 +1,7 @@
 from typing import List, Optional, Tuple
 
+import httpx
+
 import litellm
 from litellm._logging import verbose_logger
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
@@ -8,6 +10,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import (
 )
 from litellm.secret_managers.main import get_secret_str
 from litellm.types.llms.openai import AllMessageValues
+from litellm.types.utils import Choices, ModelResponse
 
 from ...openai.chat.gpt_transformation import OpenAIGPTConfig
 
@@ -100,3 +103,60 @@ class XAIChatConfig(OpenAIGPTConfig):
         return super().transform_request(
             model, messages, optional_params, litellm_params, headers
         )
+
+    @staticmethod
+    def _fix_choice_finish_reason_for_tool_calls(choice: Choices) -> None:
+        """
+        Helper to fix finish_reason for tool calls when XAI API returns empty string.
+        
+        XAI API returns empty string for finish_reason when using tools,
+        so we need to set it to "tool_calls" when tool_calls are present.
+        """
+        if (choice.finish_reason == "" and 
+            choice.message.tool_calls and 
+            len(choice.message.tool_calls) > 0):
+            choice.finish_reason = "tool_calls"
+
+    def transform_response(
+        self,
+        model: str,
+        raw_response: httpx.Response,
+        model_response: ModelResponse,
+        logging_obj,
+        request_data: dict,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        litellm_params: dict,
+        encoding,
+        api_key: Optional[str] = None,
+        json_mode: Optional[bool] = None,
+    ) -> ModelResponse:
+        """
+        Transform the response from the XAI API.
+        
+        XAI API returns empty string for finish_reason when using tools,
+        so we need to fix this after the standard OpenAI transformation.
+        """
+        
+        # First, let the parent class handle the standard transformation
+        response = super().transform_response(
+            model=model,
+            raw_response=raw_response,
+            model_response=model_response,
+            logging_obj=logging_obj,
+            request_data=request_data,
+            messages=messages,
+            optional_params=optional_params,
+            litellm_params=litellm_params,
+            encoding=encoding,
+            api_key=api_key,
+            json_mode=json_mode,
+        )
+
+        # Fix finish_reason for tool calls across all choices
+        if response.choices:
+            for choice in response.choices:
+                if isinstance(choice, Choices):
+                    self._fix_choice_finish_reason_for_tool_calls(choice)
+
+        return response
diff --git a/litellm/main.py b/litellm/main.py
index 27374c9550a..57bc405ab8f 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -1766,7 +1766,36 @@ def completion(  # type: ignore # noqa: PLR0915
                     additional_args={"headers": headers},
                 )
                 raise e
-
+        elif custom_llm_provider == "xai":
+            ## COMPLETION CALL
+            try:
+                response = base_llm_http_handler.completion(
+                    model=model,
+                    messages=messages,
+                    headers=headers,
+                    model_response=model_response,
+                    api_key=api_key,
+                    api_base=api_base,
+                    acompletion=acompletion,
+                    logging_obj=logging,
+                    optional_params=optional_params,
+                    litellm_params=litellm_params,
+                    timeout=timeout,  # type: ignore
+                    client=client,
+                    custom_llm_provider=custom_llm_provider,
+                    encoding=encoding,
+                    stream=stream,
+                    provider_config=provider_config,
+                )
+            except Exception as e:
+                ## LOGGING - log the original exception returned
+                logging.post_call(
+                    input=messages,
+                    api_key=api_key,
+                    original_response=str(e),
+                    additional_args={"headers": headers},
+                )
+                raise e
         elif custom_llm_provider == "groq":
             api_base = (
                 api_base  # for deepinfra/perplexity/anyscale/groq/friendliai we check in get_llm_provider and pass in the api base from there