diff --git a/scripts/populate_tox/config.py b/scripts/populate_tox/config.py
index ba2f4dc6d5..00257164f5 100644
--- a/scripts/populate_tox/config.py
+++ b/scripts/populate_tox/config.py
@@ -237,6 +237,9 @@
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index c621d68fd4..286f31b9b8 100644
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@@ -236,6 +235,5 @@
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 {"info": {"classifiers": ["Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Programming Language :: Python :: 3.14", "Programming Language :: Python :: 3.9", "Programming Language :: Rust"], "name": "uuid_utils", "requires_python": ">=3.9", "version": "0.14.1", "yanked": false}, "urls": [{"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-macosx_10_12_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-manylinux_2_5_i686.manylinux1_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-musllinux_1_2_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-musllinux_1_2_armv7l.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-musllinux_1_2_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-musllinux_1_2_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-win32.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-cp39-abi3-win_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-pp311-pypy311_pp73-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-pp311-pypy311_pp73-macosx_10_12_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-pp311-pypy311_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-pp311-pypy311_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-pp311-pypy311_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "uuid_utils-0.14.1-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl"}, {"packagetype": "sdist", "filename": "uuid_utils-0.14.1.tar.gz"}]}
-{"info": {"classifiers": ["Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Programming Language :: Python :: 3.14", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy"], "name": "zope.interface", "requires_python": ">=3.10", "version": "8.2", "yanked": false}, "urls": [{"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp310-cp310-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp310-cp310-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp310-cp310-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp310-cp310-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp310-cp310-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp311-cp311-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp311-cp311-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp311-cp311-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp311-cp311-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp311-cp311-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp312-cp312-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp312-cp312-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp312-cp312-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp312-cp312-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp312-cp312-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp313-cp313-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp313-cp313-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp313-cp313-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp313-cp313-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp313-cp313-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp314-cp314-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp314-cp314-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp314-cp314-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp314-cp314-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.2-cp314-cp314-win_amd64.whl"}, {"packagetype": "sdist", "filename": "zope_interface-8.2.tar.gz"}]}
+{"info": {"classifiers": ["Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Programming Language :: Python :: 3.14", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy"], "name": "zope.interface", "requires_python": ">=3.10", "version": "8.3", "yanked": false}, "urls": [{"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp310-cp310-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp310-cp310-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp310-cp310-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp310-cp310-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp310-cp310-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp311-cp311-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp311-cp311-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp311-cp311-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp311-cp311-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp311-cp311-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp312-cp312-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp312-cp312-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp312-cp312-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp312-cp312-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp312-cp312-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp313-cp313-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp313-cp313-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp313-cp313-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp313-cp313-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp313-cp313-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp314-cp314-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp314-cp314-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp314-cp314-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp314-cp314-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp314-cp314-win_amd64.whl"}, {"packagetype": "sdist", "filename": "zope_interface-8.3.tar.gz"}]}
diff --git a/tests/conftest.py b/tests/conftest.py
index d747a4aaff..1d32b6b70a 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -55,6 +55,18 @@
     openai = None
 
 
+try:
+    import anthropic
+except ImportError:
+    anthropic = None
+
+
+try:
+    import google
+except ImportError:
+    google = None
+
+
 from tests import _warning_recorder, _warning_recorder_mgr
 
 from typing import TYPE_CHECKING
@@ -1097,7 +1109,12 @@ def inner(response_content, serialize_pydantic=False, request_headers=None):
         )
 
         if serialize_pydantic:
-            response_content = json.dumps(response_content.model_dump()).encode("utf-8")
+            response_content = json.dumps(
+                response_content.model_dump(
+                    by_alias=True,
+                    exclude_none=True,
+                )
+            ).encode("utf-8")
 
         response = HttpxResponse(
             200,
@@ -1224,6 +1241,30 @@ def streaming_chat_completions_model_response():
     ]
 
 
+@pytest.fixture
+def nonstreaming_chat_completions_model_response():
+    return openai.types.chat.ChatCompletion(
+        id="chatcmpl-test",
+        choices=[
+            openai.types.chat.chat_completion.Choice(
+                index=0,
+                finish_reason="stop",
+                message=openai.types.chat.ChatCompletionMessage(
+                    role="assistant", content="Test response"
+                ),
+            )
+        ],
+        created=1234567890,
+        model="gpt-3.5-turbo",
+        object="chat.completion",
+        usage=openai.types.CompletionUsage(
+            prompt_tokens=10,
+            completion_tokens=20,
+            total_tokens=30,
+        ),
+    )
+
+
 @pytest.fixture
 def nonstreaming_responses_model_response():
     return openai.types.responses.Response(
@@ -1263,6 +1304,54 @@ def nonstreaming_responses_model_response():
     )
 
 
+@pytest.fixture
+def nonstreaming_anthropic_model_response():
+    return anthropic.types.Message(
+        id="msg_123",
+        type="message",
+        role="assistant",
+        model="claude-3-opus-20240229",
+        content=[
+            anthropic.types.TextBlock(
+                type="text",
+                text="Hello, how can I help you?",
+            )
+        ],
+        stop_reason="end_turn",
+        stop_sequence=None,
+        usage=anthropic.types.Usage(
+            input_tokens=10,
+            output_tokens=20,
+        ),
+    )
+
+
+@pytest.fixture
+def nonstreaming_google_genai_model_response():
+    return google.genai.types.GenerateContentResponse(
+        response_id="resp_123",
+        candidates=[
+            google.genai.types.Candidate(
+                content=google.genai.types.Content(
+                    role="model",
+                    parts=[
+                        google.genai.types.Part(
+                            text="Hello, how can I help you?",
+                        )
+                    ],
+                ),
+                finish_reason="STOP",
+            )
+        ],
+        model_version="gemini/gemini-pro",
+        usage_metadata=google.genai.types.GenerateContentResponseUsageMetadata(
+            prompt_token_count=10,
+            candidates_token_count=20,
+            total_token_count=30,
+        ),
+    )
+
+
 @pytest.fixture
 def responses_tool_call_model_responses():
     def inner(
diff --git a/tests/integrations/litellm/test_litellm.py b/tests/integrations/litellm/test_litellm.py
index 9cc680fd3e..413f31964a 100644
--- a/tests/integrations/litellm/test_litellm.py
+++ b/tests/integrations/litellm/test_litellm.py
@@ -39,20 +39,25 @@ async def __call__(self, *args, **kwargs):
 from litellm.litellm_core_utils import streaming_handler
 from litellm.litellm_core_utils import thread_pool_executor
 from litellm.litellm_core_utils import litellm_logging
+from litellm.llms.custom_httpx.http_handler import HTTPHandler
 
 
 LITELLM_VERSION = package_version("litellm")
 
 
-@pytest.fixture()
-def reset_litellm_executor():
-    yield
+def _reset_litellm_executor():
     thread_pool_executor.executor = ThreadPoolExecutor(max_workers=100)
     litellm_utils.executor = thread_pool_executor.executor
     streaming_handler.executor = thread_pool_executor.executor
     litellm_logging.executor = thread_pool_executor.executor
 
 
+@pytest.fixture()
+def reset_litellm_executor():
+    yield
+    _reset_litellm_executor()
+
+
 @pytest.fixture
 def clear_litellm_cache():
     """
@@ -165,7 +170,13 @@ def model_dump(self):
     ],
 )
 def test_nonstreaming_chat_completion(
-    sentry_init, capture_events, send_default_pii, include_prompts
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
 ):
     sentry_init(
         integrations=[LiteLLMIntegration(include_prompts=include_prompts)],
@@ -175,22 +186,28 @@ def test_nonstreaming_chat_completion(
     events = capture_events()
 
     messages = [{"role": "user", "content": "Hello!"}]
-    mock_response = MockCompletionResponse()
 
-    with start_transaction(name="litellm test"):
-        # Simulate what litellm does: call input callback, then success callback
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-        }
+    client = OpenAI(api_key="test-key")
 
-        _input_callback(kwargs)
-        _success_callback(
-            kwargs,
-            mock_response,
-            datetime.now(),
-            datetime.now(),
-        )
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
     assert len(events) == 1
     (event,) = events
@@ -198,8 +215,13 @@ def test_nonstreaming_chat_completion(
     assert event["type"] == "transaction"
     assert event["transaction"] == "litellm test"
 
-    assert len(event["spans"]) == 1
-    (span,) = event["spans"]
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["description"] == "chat gpt-3.5-turbo"
@@ -248,14 +270,14 @@ def test_streaming_chat_completion(
 
     messages = [{"role": "user", "content": "Hello!"}]
 
-    client = OpenAI(api_key="z")
+    client = OpenAI(api_key="test-key")
 
     model_response = get_model_response(
         server_side_event_chunks(
             streaming_chat_completions_model_response,
             include_event_type=False,
         ),
-        request_headers={"X-Stainless-Raw-Response": "True"},
+        request_headers={"X-Stainless-Raw-Response": "true"},
     )
 
     with mock.patch.object(
@@ -462,7 +484,13 @@ def test_exception_handling(sentry_init, capture_events):
     assert len(error_events) == 1
 
 
-def test_span_origin(sentry_init, capture_events):
+def test_span_origin(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
     sentry_init(
         integrations=[LiteLLMIntegration()],
         traces_sample_rate=1.0,
@@ -470,21 +498,28 @@ def test_span_origin(sentry_init, capture_events):
     events = capture_events()
 
     messages = [{"role": "user", "content": "Hello!"}]
-    mock_response = MockCompletionResponse()
 
-    with start_transaction(name="litellm test"):
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-        }
+    client = OpenAI(api_key="test-key")
 
-        _input_callback(kwargs)
-        _success_callback(
-            kwargs,
-            mock_response,
-            datetime.now(),
-            datetime.now(),
-        )
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
     (event,) = events
 
@@ -492,7 +527,15 @@ def test_span_origin(sentry_init, capture_events):
     assert event["spans"][0]["origin"] == "auto.ai.litellm"
 
 
-def test_multiple_providers(sentry_init, capture_events):
+def test_multiple_providers(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+    nonstreaming_anthropic_model_response,
+    nonstreaming_google_genai_model_response,
+):
     """Test that the integration correctly identifies different providers."""
     sentry_init(
         integrations=[LiteLLMIntegration()],
@@ -502,38 +545,89 @@ def test_multiple_providers(sentry_init, capture_events):
 
     messages = [{"role": "user", "content": "Hello!"}]
 
-    # Test with different model prefixes
-    test_cases = [
-        ("gpt-3.5-turbo", "openai"),
-        ("claude-3-opus-20240229", "anthropic"),
-        ("gemini/gemini-pro", "gemini"),
-    ]
+    openai_client = OpenAI(api_key="test-key")
+    openai_model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        openai_client.completions._client._client,
+        "send",
+        return_value=openai_model_response,
+    ):
+        with start_transaction(name="test gpt-3.5-turbo"):
+            litellm.completion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=openai_client,
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
-    for model, _ in test_cases:
-        mock_response = MockCompletionResponse(model=model)
-        with start_transaction(name=f"test {model}"):
-            kwargs = {
-                "model": model,
-                "messages": messages,
-            }
-
-            _input_callback(kwargs)
-            _success_callback(
-                kwargs,
-                mock_response,
-                datetime.now(),
-                datetime.now(),
+    _reset_litellm_executor()
+
+    anthropic_client = HTTPHandler()
+    anthropic_model_response = get_model_response(
+        nonstreaming_anthropic_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        anthropic_client,
+        "post",
+        return_value=anthropic_model_response,
+    ):
+        with start_transaction(name="test claude-3-opus-20240229"):
+            litellm.completion(
+                model="claude-3-opus-20240229",
+                messages=messages,
+                client=anthropic_client,
+                api_key="test-key",
             )
 
-    assert len(events) == len(test_cases)
+            litellm_utils.executor.shutdown(wait=True)
+
+    _reset_litellm_executor()
 
-    for i in range(len(test_cases)):
+    gemini_client = HTTPHandler()
+    gemini_model_response = get_model_response(
+        nonstreaming_google_genai_model_response,
+        serialize_pydantic=True,
+    )
+
+    with mock.patch.object(
+        gemini_client,
+        "post",
+        return_value=gemini_model_response,
+    ):
+        with start_transaction(name="test gemini/gemini-pro"):
+            litellm.completion(
+                model="gemini/gemini-pro",
+                messages=messages,
+                client=gemini_client,
+                api_key="test-key",
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
+
+    assert len(events) == 3
+
+    for i in range(3):
         span = events[i]["spans"][0]
         # The provider should be detected by litellm.get_llm_provider
         assert SPANDATA.GEN_AI_SYSTEM in span["data"]
 
 
-def test_additional_parameters(sentry_init, capture_events):
+def test_additional_parameters(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
     """Test that additional parameters are captured."""
     sentry_init(
         integrations=[LiteLLMIntegration()],
@@ -542,29 +636,41 @@ def test_additional_parameters(sentry_init, capture_events):
     events = capture_events()
 
     messages = [{"role": "user", "content": "Hello!"}]
-    mock_response = MockCompletionResponse()
+    client = OpenAI(api_key="test-key")
 
-    with start_transaction(name="litellm test"):
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-            "temperature": 0.7,
-            "max_tokens": 100,
-            "top_p": 0.9,
-            "frequency_penalty": 0.5,
-            "presence_penalty": 0.5,
-        }
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
 
-        _input_callback(kwargs)
-        _success_callback(
-            kwargs,
-            mock_response,
-            datetime.now(),
-            datetime.now(),
-        )
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+                temperature=0.7,
+                max_tokens=100,
+                top_p=0.9,
+                frequency_penalty=0.5,
+                presence_penalty=0.5,
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
     (event,) = events
-    (span,) = event["spans"]
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
 
     assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
     assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
@@ -573,7 +679,13 @@ def test_additional_parameters(sentry_init, capture_events):
     assert span["data"][SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY] == 0.5
 
 
-def test_no_integration(sentry_init, capture_events):
+def test_no_integration(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
     """Test that when integration is not enabled, callbacks don't break."""
     sentry_init(
         traces_sample_rate=1.0,
@@ -581,28 +693,37 @@ def test_no_integration(sentry_init, capture_events):
     events = capture_events()
 
     messages = [{"role": "user", "content": "Hello!"}]
-    mock_response = MockCompletionResponse()
+    client = OpenAI(api_key="test-key")
 
-    with start_transaction(name="litellm test"):
-        # When the integration isn't enabled, the callbacks should exit early
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-        }
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
 
-        # These should not crash, just do nothing
-        _input_callback(kwargs)
-        _success_callback(
-            kwargs,
-            mock_response,
-            datetime.now(),
-            datetime.now(),
-        )
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
     (event,) = events
     # Should still have the transaction, but no child spans since integration is off
     assert event["type"] == "transaction"
-    assert len(event.get("spans", [])) == 0
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 0
 
 
 def test_response_without_usage(sentry_init, capture_events):
@@ -660,50 +781,6 @@ def test_integration_setup(sentry_init):
     assert _failure_callback in (litellm.failure_callback or [])
 
 
-def test_message_dict_extraction(sentry_init, capture_events):
-    """Test that response messages are properly extracted with dict() fallback."""
-    sentry_init(
-        integrations=[LiteLLMIntegration(include_prompts=True)],
-        traces_sample_rate=1.0,
-        send_default_pii=True,
-    )
-    events = capture_events()
-
-    messages = [{"role": "user", "content": "Hello!"}]
-
-    # Create a message that has dict() method instead of model_dump()
-    class DictMessage:
-        def __init__(self):
-            self.role = "assistant"
-            self.content = "Response"
-            self.tool_calls = None
-
-        def dict(self):
-            return {"role": self.role, "content": self.content}
-
-    mock_response = MockCompletionResponse(choices=[MockChoice(message=DictMessage())])
-
-    with start_transaction(name="litellm test"):
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-        }
-
-        _input_callback(kwargs)
-        _success_callback(
-            kwargs,
-            mock_response,
-            datetime.now(),
-            datetime.now(),
-        )
-
-    (event,) = events
-    (span,) = event["spans"]
-
-    # Should have extracted the response message
-    assert SPANDATA.GEN_AI_RESPONSE_TEXT in span["data"]
-
-
 def test_litellm_message_truncation(sentry_init, capture_events):
     """Test that large messages are truncated properly in LiteLLM integration."""
     sentry_init(
@@ -766,7 +843,13 @@ def test_litellm_message_truncation(sentry_init, capture_events):
 IMAGE_DATA_URI = f"data:image/png;base64,{IMAGE_B64}"
 
 
-def test_binary_content_encoding_image_url(sentry_init, capture_events):
+def test_binary_content_encoding_image_url(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
     sentry_init(
         integrations=[LiteLLMIntegration(include_prompts=True)],
         traces_sample_rate=1.0,
@@ -786,15 +869,37 @@ def test_binary_content_encoding_image_url(sentry_init, capture_events):
             ],
         }
     ]
-    mock_response = MockCompletionResponse()
+    client = OpenAI(api_key="test-key")
 
-    with start_transaction(name="litellm test"):
-        kwargs = {"model": "gpt-4-vision-preview", "messages": messages}
-        _input_callback(kwargs)
-        _success_callback(kwargs, mock_response, datetime.now(), datetime.now())
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-4-vision-preview",
+                messages=messages,
+                client=client,
+                custom_llm_provider="openai",
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
     (event,) = events
-    (span,) = event["spans"]
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
     messages_data = json.loads(span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
 
     blob_item = next(
@@ -816,7 +921,13 @@ def test_binary_content_encoding_image_url(sentry_init, capture_events):
     )
 
 
-def test_binary_content_encoding_mixed_content(sentry_init, capture_events):
+def test_binary_content_encoding_mixed_content(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
     sentry_init(
         integrations=[LiteLLMIntegration(include_prompts=True)],
         traces_sample_rate=1.0,
@@ -837,15 +948,37 @@ def test_binary_content_encoding_mixed_content(sentry_init, capture_events):
             ],
         }
     ]
-    mock_response = MockCompletionResponse()
+    client = OpenAI(api_key="test-key")
 
-    with start_transaction(name="litellm test"):
-        kwargs = {"model": "gpt-4-vision-preview", "messages": messages}
-        _input_callback(kwargs)
-        _success_callback(kwargs, mock_response, datetime.now(), datetime.now())
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-4-vision-preview",
+                messages=messages,
+                client=client,
+                custom_llm_provider="openai",
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
     (event,) = events
-    (span,) = event["spans"]
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
     messages_data = json.loads(span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
 
     content_items = [
@@ -855,7 +988,13 @@ def test_binary_content_encoding_mixed_content(sentry_init, capture_events):
     assert any(item.get("type") == "blob" for item in content_items)
 
 
-def test_binary_content_encoding_uri_type(sentry_init, capture_events):
+def test_binary_content_encoding_uri_type(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
     sentry_init(
         integrations=[LiteLLMIntegration(include_prompts=True)],
         traces_sample_rate=1.0,
@@ -874,15 +1013,37 @@ def test_binary_content_encoding_uri_type(sentry_init, capture_events):
             ],
         }
     ]
-    mock_response = MockCompletionResponse()
+    client = OpenAI(api_key="test-key")
 
-    with start_transaction(name="litellm test"):
-        kwargs = {"model": "gpt-4-vision-preview", "messages": messages}
-        _input_callback(kwargs)
-        _success_callback(kwargs, mock_response, datetime.now(), datetime.now())
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-4-vision-preview",
+                messages=messages,
+                client=client,
+                custom_llm_provider="openai",
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
     (event,) = events
-    (span,) = event["spans"]
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
     messages_data = json.loads(span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
 
     uri_item = next(
diff --git a/tox.ini b/tox.ini
index 77cdfa3fec..cd5d939f6d 100644
--- a/tox.ini
+++ b/tox.ini
@@ -550,6 +550,8 @@ deps =
     litellm-v1.81.16: litellm==1.81.16
     litellm-v1.83.4: litellm==1.83.4
     litellm-latest: litellm==1.83.4
+    litellm: anthropic
+    litellm: google-genai
 
     openai-base-v1.0.1: openai==1.0.1
     openai-base-v1.109.1: openai==1.109.1