Handle azure deepseek reasoning response (#8288) (#8366)

* Handle azure deepseek reasoning response (#8288)

* Handle deepseek reasoning response

* Add helper method + unit test

* Fix: Follow infinity api url format (#8346)

* Follow infinity api url format

* Update test_infinity.py

* fix(infinity/transformation.py): fix linting error

---------

Co-authored-by: vibhavbhat <[email protected]>
Co-authored-by: Hao Shan <[email protected]>

litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py

@@ -3,7 +3,8 @@
 import time
 import traceback
 import uuid
-from typing import Dict, Iterable, List, Literal, Optional, Union
+import re
+from typing import Dict, Iterable, List, Literal, Optional, Union, Tuple
 
 import litellm
 from litellm._logging import verbose_logger
@@ -220,6 +221,16 @@ def _handle_invalid_parallel_tool_calls(
         # if there is a JSONDecodeError, return the original tool_calls
         return tool_calls
 
+def _parse_content_for_reasoning(message_text: Optional[str]) -> Tuple[Optional[str], Optional[str]]:
+    if not message_text:
+        return None, None
+
+    reasoning_match = re.match(r"<think>(.*?)</think>(.*)", message_text, re.DOTALL)
+
+    if reasoning_match:
+        return reasoning_match.group(1), reasoning_match.group(2)
+
+    return None, message_text
 
 class LiteLLMResponseObjectHandler:
 
@@ -432,8 +443,14 @@ def convert_to_model_response_object(  # noqa: PLR0915
                     for field in choice["message"].keys():
                         if field not in message_keys:
                             provider_specific_fields[field] = choice["message"][field]
+
+                    # Handle reasoning models that display `reasoning_content` within `content`
+                    reasoning_content, content = _parse_content_for_reasoning(choice["message"].get("content", None))
+                    if reasoning_content:
+                        provider_specific_fields["reasoning_content"] = reasoning_content
+
                     message = Message(
-                        content=choice["message"].get("content", None),
+                        content=content,
                         role=choice["message"]["role"] or "assistant",
                         function_call=choice["message"].get("function_call", None),
                         tool_calls=tool_calls,

litellm/llms/infinity/rerank/transformation.py

@@ -20,6 +20,15 @@
 
 
 class InfinityRerankConfig(CohereRerankConfig):
+    def get_complete_url(self, api_base: Optional[str], model: str) -> str:
+        if api_base is None:
+            raise ValueError("api_base is required for Infinity rerank")
+        # Remove trailing slashes and ensure clean base URL
+        api_base = api_base.rstrip("/")
+        if not api_base.endswith("/rerank"):
+            api_base = f"{api_base}/rerank"
+        return api_base
+
     def validate_environment(
         self,
         headers: dict,

litellm/utils.py

@@ -89,6 +89,7 @@
     convert_to_model_response_object,
     convert_to_streaming_response,
     convert_to_streaming_response_async,
+    _parse_content_for_reasoning,
 )
 from litellm.litellm_core_utils.llm_response_utils.get_api_base import get_api_base
 from litellm.litellm_core_utils.llm_response_utils.get_formatted_prompt import (

tests/litellm_utils_tests/test_utils.py

@@ -864,6 +864,18 @@ def test_convert_model_response_object():
             == '{"type":"error","error":{"type":"invalid_request_error","message":"Output blocked by content filtering policy"}}'
         )
 
+@pytest.mark.parametrize(
+    "content, expected_reasoning, expected_content", 
+    [
+        (None, None, None),
+        ("<think>I am thinking here</think>The sky is a canvas of blue", "I am thinking here", "The sky is a canvas of blue"),
+        ("I am a regular response", None, "I am a regular response"),
+
+    ]
+)
+def test_parse_content_for_reasoning(content, expected_reasoning, expected_content):
+    assert(litellm.utils._parse_content_for_reasoning(content) == (expected_reasoning, expected_content))
+
 
 @pytest.mark.parametrize(
     "model, expected_bool",

tests/llm_translation/test_azure_ai.py

@@ -13,7 +13,7 @@
 from litellm.llms.anthropic.chat import ModelResponseIterator
 import httpx
 import json
-from respx import MockRouter
+from litellm.llms.custom_httpx.http_handler import HTTPHandler
 
 load_dotenv()
 import io
@@ -184,3 +184,45 @@ def test_completion_azure_ai_command_r():
         pass
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
+
+def test_azure_deepseek_reasoning_content():
+    import json
+
+    client = HTTPHandler()
+
+    with patch.object(client, "post") as mock_post:
+        mock_response = MagicMock()
+
+        mock_response.text = json.dumps(
+            {
+                "choices": [
+                    {
+                    "finish_reason": "stop",
+                    "index": 0,
+                    "message": {
+                        "content": "<think>I am thinking here</think>\n\nThe sky is a canvas of blue",
+                        "role": "assistant",
+                    }
+                    }
+                ],
+            }
+        ) 
+
+        mock_response.status_code = 200
+        # Add required response attributes
+        mock_response.headers = {"Content-Type": "application/json"}
+        mock_response.json = lambda: json.loads(mock_response.text)
+        mock_post.return_value = mock_response
+
+
+        response = litellm.completion(
+            model='azure_ai/deepseek-r1',
+            messages=[{"role": "user", "content": "Hello, world!"}],
+            api_base="https://litellm8397336933.services.ai.azure.com/models/chat/completions",
+            api_key="my-fake-api-key",
+            client=client
+        )  
+
+        print(response)
+        assert(response.choices[0].message.reasoning_content == "I am thinking here")
+        assert(response.choices[0].message.content == "\n\nThe sky is a canvas of blue")

tests/llm_translation/test_infinity.py

@@ -69,7 +69,7 @@ def return_val():
         _url = mock_post.call_args.kwargs["url"]
         print("Arguments passed to API=", args_to_api)
         print("url = ", _url)
-        assert _url == "https://api.infinity.ai/v1/rerank"
+        assert _url == "https://api.infinity.ai/rerank"
 
         request_data = json.loads(args_to_api)
         assert request_data["query"] == expected_payload["query"]
@@ -133,7 +133,7 @@ def return_val():
         _url = mock_post.call_args.kwargs["url"]
         print("Arguments passed to API=", args_to_api)
         print("url = ", _url)
-        assert _url == "https://env.infinity.ai/v1/rerank"
+        assert _url == "https://env.infinity.ai/rerank"
 
         request_data = json.loads(args_to_api)
         assert request_data["query"] == expected_payload["query"]