berriai-litellm-21658-22884

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7c9c927 base
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:18:class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, VertexBase):
litellm/utils.py:8177:                    VertexAIPartnerModelsAnthropicMessagesConfig,
lite
…[1197 chars omitted]…
lsAnthropicMessagesConfig()
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:181:    config = VertexAIPartnerModelsAnthropicMessagesConfig()
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py:447:        VertexAIPartnerModelsAnthropicMessagesConfig,

from unittest.mock import patch

import pytest

from litellm.llms.vertex_ai.vertex_ai_partner_models.anthropic.experimental_pass_through.transformation import (
    VertexAIPartnerModelsAnthropicMessagesConfig,
)


def test_validate_environment_uses_vertex_ai_location():
    config = VertexAIPartnerModelsAnthropicMessagesConfig()
    headers = {}

    litellm_params = {
        "vertex_ai_project": "test-project",
        "vertex_ai_location": "europe-west1",
        "vertex_credentials": "{}",
    }
    optional_params = {}

    with patch.object(
        config, "_ensure_access_token", return_value=("token", "test-project")
    ), patch.object(
        config, "get_complete_vertex_url", return_value="https://mock-url"
    ) as mock_get_url:
        config.validate_anthropic_messages_environment(
            headers=headers,
            model="claude-3-sonnet",
            messages=[]
…[7165 chars omitted]…
ld be present"
        assert "compact-2026-01-12" in updated_headers["anthropic-beta"], \
            f"anthropic-beta should contain 'compact-2026-01-12', got: {updated_headers['anthropic-beta']}"
        assert "context-management-2025-06-27" in updated_headers["anthropic-beta"], \
            f"anthropic-beta should contain 'context-management-2025-06-27', got: {updated_headers['anthropic-beta']}"

litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:45:            "output_format",
litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:48:            "output_config",
litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:240:        - output_format: adds 'structured-outputs-2025-11-13'
litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:245:            optional_params: Optional parameters including tools, context_management, output_format, speed
litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:281:        if optional_params.get("output_format") is not None:
litellm/types/llms/anthropic.py:363:    output_format: Optional[AnthropicOutputSchema]  # Structured outputs support
litellm/types/llms/anthropic.py:365:    output_config: Optional[AnthropicOutputConfig]  # Configuration for Claude's output behavior

project_id=project_id,
                )
            except Exception as e:
                raise e

    def set_headers(
        self, auth_header: Optional[str], extra_headers: Optional[dict]
    ) -> dict:
        headers = {
            "Content-Type": "application/json",
        }
        if auth_header is not None:

            headers["Authorization"] = f"Bearer {auth_header}"
        if extra_headers is not None:
            headers.update(extra_headers)

        return headers

    @staticmethod
    def get_vertex_ai_project(litellm_params: dict) -> Optional[str]:
        return (
            litellm_params.pop("vertex_project", None)
            or litellm_params.pop("vertex_ai_project", None)
            or litellm.vertex_project
            or get_secret_str("VERTEXAI_PROJECT")
        )

    @staticmethod
    def get_vertex_ai_credentials(litellm_params
…[3019 chars omitted]…
arams.pop("outputConfig", None)
litellm/llms/bedrock/chat/converse_transformation.py:1225:            output_config,
litellm/llms/bedrock/chat/converse_transformation.py:1391:            output_config,
litellm/llms/bedrock/chat/converse_transformation.py:1434:        if output_config is not None:
litellm/llms/bedrock/chat/converse_transformation.py:1435:            data["outputConfig"] = output_config

litellm/llms/anthropic/experimental_pass_through/messages/transformation.py
litellm/llms/base_llm/anthropic_messages/transformation.py
litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py
litellm/llms/custom_httpx/llm_http_handler.py
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py:1539:def test_effort_output_config_preservation():
tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py:1540:    """Test that output_config with effort is preserved in transformation."""
tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py:1545:        "output_config": {
tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py:1558:    assert "output_config" in result
tests/tes
…[1607 chars omitted]…
s = {"output_config": {"effort": "max"}}

tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py:1698:        "output_config": {
tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py:1717:    assert "output_config" in result
tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py:1718:    assert result["output_config"]["effort"] == "low"

import os
import sys

import pytest

sys.path.insert(
    0, os.path.abspath("../../../../../..")
)  # Adds the parent directory to the system path
from litellm.anthropic_beta_headers_manager import (
    update_headers_with_filtered_beta,
)
from litellm.llms.vertex_ai.vertex_ai_partner_models.anthropic.transformation import (

    VertexAIAnthropicConfig,
)


@pytest.mark.parametrize(
    "model, expected_thinking",
    [
        ("claude-sonnet-4@20250514", True),
    ],
)
def test_vertex_ai_anthropic_thinking_param(model, expected_thinking):
    supported_openai_params = VertexAIAnthropicConfig().get_supported_openai_params(
        model=model
    )

    if expected_thinking:
        assert "thinking" in supported_openai_params
    else:
        assert "thinking" not in supported_openai_params


def test_get_supported_params_thinking():
    config = VertexAIAnthropicConfig()
    pa
…[8629 chars omitted]…
beta_header or ""
    ), "Other non-excluded beta headers should remain"
    # If prompt-caching was the only value, header should be removed completely
    headers2 = {"anthropic-beta": PROMPT_CACHING_BETA_HEADER}
    headers2 = update_headers_with_filtered_beta(headers2, "vertex_ai")
    assert (
        "anthropic-beta" not in headers2
    ), "Header should be removed if no supported values remain"

142:def test_vertex_ai_anthropic_structured_output_header_not_added():
143:    """Test that structured output beta headers are NOT added for Vertex AI requests"""
148:    # Test case 1: Vertex request with output_format should NOT add beta header
151:        "output_format": {
166:    ), f"Vertex request should NOT have anthropic-beta header for structured output, got: {result_vertex.get('anthropic-beta')}"
168:    # Test case 2: Non-Vertex request with output_format SHOULD add beta header
171:        "output_format": {
186:    ), "Non-Vertex request SHOULD have anthropic-beta header for structured output"
188:        result_non_vertex["anthropic-beta"] == "structured-outputs-2025-11-13"
189:    ), f"Expected 'structured-outputs-2025-11-13', got: {result_non_vertex.get('anthropic-beta')}"
192:def test_vertex_ai_claude_sonnet_4_5_structured_output_fix():
195:    structured outputs inst

…[653 chars omitted]…
 # Return test data that includes output_format
286:        # Verify that output_format was removed (fixes the "Extra inputs are not permitted" error)
288:            "output_format" not in final_data
289:        ), "output_format should be removed for VertexAI"
302:    structured outputs, ensuring consistency across all models.
328:    ), "Claude 3 Sonnet should also use tool-based structured output"

# What is this?
## Handler file for calling claude-3 on vertex ai
from typing import Any, List, Optional

import httpx

import litellm
from litellm.llms.base_llm.chat.transformation import LiteLLMLoggingObj
from litellm.types.llms.openai import AllMessageValues
from litellm.types.utils import ModelResponse

from ....anthropic.chat.transformation import AnthropicConfig

class VertexAIError(Exception):
    def __init__(self, status_code, message):
        self.status_code = status_code
        self.message = message
        self.request = httpx.Request(
            method="POST", url=" https://cloud.google.com/vertex-ai/"
        )
        self.response = httpx.Response(status_code=status_code, request=self.request)
        super().__init__(
            self.message
        )  # Call the base class constructor with the parameters it needs


class VertexAIAnthropicConfig(AnthropicConfig
…[6929 chars omitted]…
    """
        Check if the model is supported by the VertexAI Anthropic API.
        """
        if (
            custom_llm_provider != "vertex_ai"
            and custom_llm_provider != "vertex_ai_beta"
        ):
            return False
        if "claude" in model.lower():
            return True
        elif model in litellm.vertex_anthropic_models:
            return True
        return False

226:        Filter out unsupported fields from JSON schema for Anthropic's output_format API.
228:        Anthropic's output_format doesn't support certain JSON schema properties:
234:        See: https://platform.claude.com/docs/en/build-with-claude/structured-outputs#how-sdk-transformation-works
770:    def map_response_format_to_anthropic_output_format(
779:        # Filter out unsupported fields for Anthropic's output_format API
963:                    _output_format = (
964:                        self.map_response_format_to_anthropic_output_format(value)
966:                    if _output_format is not None:
967:                        optional_params["output_format"] = _output_format
1043:            # see usage with additionalProperties (Example 5) https://github.com/anthropics/anthropic-cookbook/blob/main/tool_use/extracting_structured_json.ipynb
1236:        if optional_para
…[10 chars omitted]…

tput_format") is not None:
1363:        ## Handle output_config (Anthropic-specific parameter)
1364:        if "output_config" in optional_params:
1365:            output_config = optional_params.get("output_config")
1366:            if output_config and isinstance(output_config, dict):
1367:                effort = output_config.get("effort")
1376:                data["output_config"] = output_config

# Add context management header if any other edits/entries exist
        if has_other:
            self._ensure_beta_header(
                headers, ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value
            )

    def update_headers_with_optional_anthropic_beta(
        self, headers: dict, optional_params: dict
    ) -> dict:
        """Update headers with optional anthropic beta."""

        # Skip adding beta headers for Vertex requests

        # Vertex AI handles these headers differently
        is_vertex_request = optional_params.get("is_vertex_request", False)
        if is_vertex_request:
            return headers

        _tools = optional_params.get("tools", [])
        for tool in _tools:
            if tool.get("type", None) and tool.get("type").startswith(
                ANTHROPIC_HOSTED_TOOLS.WEB_FETCH.value
            ):
                s
…[7366 chars omitted]…
FORMAT_TOOL_NAME
            ):
                json_mode_content_str = tool_calls[0]["function"].get("arguments")
            if json_mode_content_str is not None:
                _message = AnthropicConfig._convert_tool_response_to_message(
                    tool_calls=tool_calls,
                )
        return _message

    def extract_response_content(self, completion_response: dict) -> Tuple[

tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py:2982:def test_create_output_config_for_response_format():
tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py:2995:    output_config = config._create_output_config_for_response_format(
tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py:3001:    assert "textFormat" in output_config
tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py:3002:    text_format = output_config["textFormat"]
tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py:3017:def test_translate_response_format_native_output_config():
tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py:3136:def test_transform_request_with_output_config():
tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py:3142:    output_config = OutputConfigBlock(
tests/test_litellm/llm
…[287 chars omitted]…
py:3360:    """_create_output_config_for_response_format normalizes the schema."""
tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py:3371:    output_config = AmazonConverseConfig._create_output_config_for_response_format(
tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py:3374:    parsed = json.loads(output_config["textFormat"]["structure"]["jsonSchema"]["schema"])

237:    def get_complete_vertex_url(
238-        self,
239-        custom_api_base: Optional[str],
240-        vertex_location: Optional[str],
241-        vertex_project: Optional[str],
242-        project_id: str,
243-        partner: VertexPartnerProvider,
244-        stream: Optional[bool],
245-        model: str,
246-    ) -> str:
247-        # Use get_vertex_region to handle global-only models
248-        resolved_location = self.get_vertex_region(vertex_location, model)

249-        api_base = self.get_api_base(
250-            api_base=custom_api_base, vertex_location=resolved_location
251-        )
252-        default_api_base = VertexBase.create_vertex_url(
253-            vertex_location=resolved_location,
254-            vertex_project=vertex_project or project_id,
255-            partner=partner,
256-            stream=stream,
257-            model=model,
258-            ap
…[3577 chars omitted]…
tional[str], str]
350-        """
351-        if api_base:
352-            if custom_llm_provider == "gemini":
353-                # For Gemini (Google AI Studio), construct the full path like other providers
354-                if model is None:
355-                    raise ValueError(
356-                        "Model parameter is required for Gemini custom API base URLs"
357-                    )

litellm/llms/vertex_ai/rerank/transformation.py:96:        # If 'Authorization' is provided in headers, it overrides the default.
litellm/llms/vertex_ai/rerank/transformation.py:97:        if "Authorization" in headers:
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:34:        if "Authorization" not in headers:
litellm/llms/bedrock/base_aws_llm.py:1376:            headers is not None and "Authorization" in headers

63:    def validate_anthropic_messages_environment(
64-        self,
65-        headers: dict,
66-        model: str,
67-        messages: List[Any],
68-        optional_params: dict,
69-        litellm_params: dict,
70-        api_key: Optional[str] = None,
71-        api_base: Optional[str] = None,
72-    ) -> Tuple[dict, Optional[str]]:
73-        return headers, api_base
74-

75-    def sign_request(
76-        self,
77-        headers: dict,
78-        optional_params: dict,
79-        request_data: dict,
80-        api_base: str,
81-        api_key: Optional[str] = None,
82-        model: Optional[str] = None,
83-        stream: Optional[bool] = None,
84-        fake_stream: Optional[bool] = None,
85-    ) -> Tuple[dict, Optional[bytes]]:
86-        return AmazonInvokeConfig.sign_request(
87-            self=self,
88-            headers=headers,
89-            optional_params=opt
…[8632 chars omitted]…
tex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:164:        updated_headers, api_base = config.validate_anthropic_messages_environment(
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:203:        updated_headers, api_base = config.validate_anthropic_messages_environment(

self,
        api_base: Optional[str],
        api_key: Optional[str],
        model: str,
        optional_params: dict,
        litellm_params: dict,
        stream: Optional[bool] = None,
    ) -> str:
        api_base = api_base or DEFAULT_ANTHROPIC_API_BASE
        if not api_base.endswith("/v1/messages"):
            api_base = f"{api_base}/v1/messages"
        return api_base

    def validate_anthropic_messages_environment(
        self,
        headers: dict,
        model: str,
        messages: List[Any],
        optional_params: dict,
        litellm_params: dict,
        api_key: Optional[str] = None,
        api_base: Optional[str] = None,
    ) -> Tuple[dict, Optional[str]]:
        import os

        # Check for Anthropic OAuth token in Authorization header
        headers, api_key = optionally_handle_anthropic_oauth(
            headers=headers, api_key=api_ke
…[3123 chars omitted]…
t_notation_indexing import (
                delete_nested_value,
                is_nested_path,
            )

            nested_paths = [p for p in additional_drop_params if is_nested_path(p)]
            for path in nested_paths:
                anthropic_messages_optional_request_params = delete_nested_value(
                    anthropic_messages_optional_request_params, path
                )

* master

07:48:58 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
PART 1: {'Authorization': 'Bearer reused-token', 'content-type': 'application/json'} None
get_complete_vertex_url calls: None
PART 2 messages config: {'messages': [{'role': 'user', 'content': 'hi'}], 'max_tokens': 100, 'output_config': {'effort': 'high'}, 'anthropic_version': 'vertex-2023-10-16'}
PART 2 chat config: {'messages': [{'role': 'user', 'content': [{'type': 'text', 'text': 'hi'}]}], 'max_tokens': 100, 'output_config': {'effort': 'high'}, 'anthropic_beta': ['effort-2025-11-24']}

706:    def safe_get_vertex_ai_project(litellm_params: dict) -> Optional[str]:
727:    def safe_get_vertex_ai_credentials(litellm_params: dict) -> Optional[str]:
747:    def safe_get_vertex_ai_location(litellm_params: dict) -> Optional[str]:

or litellm.vertex_location
            or get_secret_str("VERTEXAI_LOCATION")
            or get_secret_str("VERTEX_LOCATION")
        )

    @staticmethod
    def safe_get_vertex_ai_project(litellm_params: dict) -> Optional[str]:
        """
        Safely get Vertex AI project without mutating the litellm_params dict.

        Unlike get_vertex_ai_project(), this does NOT pop values from the dict,
        making it safe to call multiple times with the same litellm_params.

        Args:
            litellm_params: Dictionary containing Vertex AI parameters

        Returns:
            Vertex AI project ID or None
        """
        return (
            litellm_params.get("vertex_project")
            or litellm_params.get("vertex_ai_project")
            or litellm.vertex_project
            or get_secret_str("VERTEXAI_PROJECT")
        )

    @staticmethod
    def saf
…[1049 chars omitted]…
tellm_params: Dictionary containing Vertex AI parameters

        Returns:
            Vertex AI location/region or None
        """
        return (
            litellm_params.get("vertex_location")
            or litellm_params.get("vertex_ai_location")
            or litellm.vertex_location
            or get_secret_str("VERTEXAI_LOCATION")
            or get_secret_str("VERTEX_LOCATION")
        )

07:49:26 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
PART 1: {'Authorization': 'Bearer reused-token', 'content-type': 'application/json'} https://mock-url
get_complete_vertex_url calls: call(custom_api_base=None, vertex_location='europe-west1', vertex_project='test-project', project_id='test-project', partner=<VertexPartnerProvider.claude: 'claude'>, stream=False, model='claude-3-sonnet')
PART 2 messages config: {'messages': [{'role': 'user', 'content': 'hi'}], 'max_tokens': 100, 'anthropic_version': 'vertex-2023-10-16'}
PART 2 chat config: {'messages': [{'role': 'user', 'content': [{'type': 'text', 'text': 'hi'}]}], 'max_tokens': 100, 'anthropic_beta': ['effort-2025-11-24']}

...................                                                      [100%]
19 passed in 1.84s

litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:47:            api_base = self.get_complete_vertex_url(
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:62:            api_base = self.get_complete_vertex_url(
litellm/llms/vertex_ai/vertex_ai_partner_models/main.py:164:            api_base = self.get_complete_vertex_url(
litellm/llms/vertex_ai/vertex_llm_base.py:237:    def get_complete_vertex_url(

VertexLLM,
            )
        except Exception as e:
            raise VertexAIError(
                status_code=400,
                message=f"""vertexai import failed please run `pip install -U "google-cloud-aiplatform>=1.38"`. Got error: {e}""",
            )

        if not (
            hasattr(vertexai, "preview") or hasattr(vertexai.preview, "language_models")
        ):
            raise VertexAIError(

                status_code=400,
                message="""Upgrade vertex ai. Run `pip install "google-cloud-aiplatform>=1.38"`""",
            )
        try:
            vertex_httpx_logic = VertexLLM()

            access_token, project_id = vertex_httpx_logic._ensure_access_token(
                credentials=vertex_credentials,
                project_id=vertex_project,
                custom_llm_provider="vertex_ai",
            )

            openai_lik
…[2324 chars omitted]…
one:
                    headers = {}
                headers.update({"Authorization": "Bearer {}".format(access_token)})

                optional_params.update(
                    {
                        "anthropic_version": "vertex-2023-10-16",
                        "is_vertex_request": True,
                    }
                )

                return anthropic_chat_completions.completion(

07:50:03 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
{'Authorization': 'Bearer token', 'content-type': 'application/json'}
https://europe-west1-aiplatform.googleapis.com/v1/projects/my-project/locations/europe-west1/publishers/anthropic/models/claude-3-sonnet:rawPredict
{'Authorization': 'Bearer token', 'content-type': 'application/json'}
https://europe-west1-aiplatform.googleapis.com/v1/projects/my-project/locations/europe-west1/publishers/anthropic/models/claude-3-sonnet:rawPredict

diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
index 54c3f9e..dec98e4 100644
--- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
+++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
@@ -53,6 +53,21 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
                 stream=optional_params.get("stream", False),
                 model=model,
             )
+        elif api_base is None:
+            # Authorization may already be present (e.g. reused/cached headers).
+            # Preserve it, but still resolve the Vertex AI endpoint.
+            vertex_ai_project = VertexBa

…[1559 chars omitted]…
doesn't support output_format parameter, remove it if present
         data.pop("output_format", None)
 
+        # VertexAI doesn't support output_config (Anthropic-only) parameter, remove it if present
+        data.pop("output_config", None)
+
         tools = optional_params.get("tools")
         tool_search_used = self.is_tool_search_used(tools)
         auto_betas = self.get_anthropic_beta_list(

grep: litellm/llms/vertex_ai/batches/__pycache__/transformation.cpython-312.pyc: binary file matches
grep: litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/__pycache__/transformation.cpython-312.pyc: binary file matches
grep: litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/__pycache__/transformation.cpython-312.pyc: binary file matches
litellm/llms/vertex_ai/batches/transformation.py:35:        output_config: OutputConfig = OutputConfig(
litellm/llms/vertex_ai/batches/transformation.py:43:            outputConfig=output_config,
litellm/llms/vertex_ai/batches/transformation.py:152:        output_config = response.get("outputConfig")
litellm/llms/vertex_ai/batches/transformation.py:153:        if output_config is None:
litellm/llms/vertex_ai/batches/transformation.py:156:        gcs_destination = output_config.get("gcsDestination")
litellm/ll
…[1214 chars omitted]…
ner_models/anthropic/transformation.py:112:        data.pop("output_config", None)
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py:162:        VertexAI doesn't support the output_format parameter, so we force all models

litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py:166:        # This ensures Claude Sonnet 4.5 uses tools instead of output_format

34
=============================== warnings summary ===============================
tests/test_litellm/llms/vertex_ai/test_http_status_201.py::TestVertexAIHTTPStatus201::test_async_http_status_201
  /usr/local/lib/python3.12/unittest/case.py:589: RuntimeWarning: coroutine 'TestVertexAIHTTPStatus201.test_async_http_status_201' was never awaited
    if method() is not None:
  Enable tracemalloc to get traceback where the object was allocated.
  See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/test_litellm/llms/vertex_ai/test_http_status_201.py::TestVertexAIHTTPStatus201::test_async_http_status_201
  /usr/local/lib/python3.12/unittest/case.py:690: DeprecationWarning: It is deprecated to return a value that is not None from a test case (<bound method TestVertexAIHTTPStatus201.test_async_http_status_201 of <vertex_ai.test_http_statu
…[2656 chars omitted]…
lue may not be as expected [field_name='message', input_value=Message(content='Hello! H...er_specific_fields=None), input_type=Message])

  PydanticSerializationUnexpectedValue(Expected `StreamingChoices` - serialized value may not be as expected [field_name='choices', input_value=Choices(finish_reason='st...r_specific_fields=None)), input_type=Choices])
  return self.__pydantic_serializer__.to_python(

07:51:10 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
------------------------------ Captured log setup ------------------------------
WARNING  LiteLLM:get_model_cost_map.py:174 LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
____________ test_reasoning_effort_maps_to_thinking_level_gemini_3 _____________

    def test_reasoning_effort_maps_to_thinking_level_gemini_3():
        """Test that reasoning_effort maps to thinking_level AND includeThoughts for Gemini 3+ models"""
        
…[1907 chars omitted]…
omplete (worker: master)
=========================== short test summary info ============================
FAILED tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py::test_reasoning_effort_dict_format_gemini_3

FAILED tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py::test_reasoning_effort_maps_to_thinking_level_gemini_3
2 failed in 4.55s

/usr/local/bin/python: No module named ruff

from ....vertex_llm_base import VertexBase


class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, VertexBase):
    def validate_anthropic_messages_environment(
        self,
        headers: dict,
        model: str,
        messages: List[Any],
        optional_params: dict,
        litellm_params: dict,
        api_key: Optional[str] = None,

        api_base: Optional[str] = None,
    ) -> Tuple[dict, Optional[str]]:
        """
        OPTIONAL

        Validate the environment for the request
        """
        if "Authorization" not in headers:
            vertex_ai_project = VertexBase.get_vertex_ai_project(litellm_params)
            vertex_credentials = VertexBase.get_vertex_ai_credentials(litellm_params)
            vertex_ai_location = VertexBase.get_vertex_ai_location(litellm_params)

            access_token, project_id = self._ensure_access_token(

…[3684 chars omitted]…
sent
        data.pop("output_config", None)

        tools = optional_params.get("tools")
        tool_search_used = self.is_tool_search_used(tools)
        auto_betas = self.get_anthropic_beta_list(
            model=model,
            optional_params=optional_params,
            computer_tool_used=self.is_computer_tool_used(tools),
            prompt_caching_set=self.is_cache_control_set(messages),

tests/pass_through_tests/test_anthropic_passthrough.py
tests/pass_through_tests/test_anthropic_passthrough_basic.py
tests/pass_through_unit_tests/messages_api_structured_output/test_anthropic_api_structured_output.py
tests/pass_through_unit_tests/messages_api_structured_output/test_azure_anthropic_structured_output.py
tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py
tests/pass_through_unit_tests/test_anthropic_messages_prompt_caching.py
tests/pass_through_unit_tests/test_anthropic_messages_tool_search.py
tests/pass_through_unit_tests/test_bedrock_anthropic_messages_test.py
tests/pass_through_unit_tests/test_unit_test_anthropic_pass_through.py
tests/pass_through_unit_tests/test_vertex_ai_anthropic_streaming_cost_injection.py
tests/proxy_e2e_anthropic_messages_tests/test_all_beta_headers.py
tests/proxy_e2e_anthropic_messages_tests/test_claude_agent_sdk.py

tests/test_
…[692 chars omitted]…
/claude/test_azure_anthropic_messages_transformation.py
tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py
tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py

Hint: make sure your test modules/packages have valid Python names.
Traceback:
/usr/local/lib/python3.12/importlib/__init__.py:90: in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_sse_wrapper.py:5: in <module>
    from fastapi.testclient import TestClient
E   ModuleNotFoundError: No module named 'fastapi'
_ ERROR collecting tests/pass_through_unit_tests/test_vertex_ai_anthropic_streaming_cost_injection.py _
ImportError while importing test module '/repo/tests/pass_through_unit_tests/test_vertex_ai_anthropic_streaming_cost_injection.py'.
Hint: make sure your test modules/packages have valid Python names.
Traceback:

/usr/local/lib/python3.12/importlib/__init__.py:90: in import_module
    return _bootstrap._gcd_import(na
…[858 chars omitted]…
st_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py
ERROR tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_sse_wrapper.py
ERROR tests/pass_through_unit_tests/test_vertex_ai_anthropic_streaming_cost_injection.py
!!!!!!!!!!!!!!!!!!! Interrupted: 3 errors during collection !!!!!!!!!!!!!!!!!!!!
3 errors in 5.05s

.....                                                                    [100%]
5 passed in 1.42s

07:52:07 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
PART 1: {'Authorization': 'Bearer reused-token', 'content-type': 'application/json'} https://mock-url
get_complete_vertex_url calls: call(custom_api_base=None, vertex_location='europe-west1', vertex_project='test-project', project_id='test-project', partner=<VertexPartnerProvider.claude: 'claude'>, stream=False, model='claude-3-sonnet')
PART 2 messages config: {'messages': [{'role': 'user', 'content': 'hi'}], 'max_tokens': 100, 'anthropic_version': 'vertex-2023-10-16'}
PART 2 chat config: {'messages': [{'role': 'user', 'content': [{'type': 'text', 'text': 'hi'}]}], 'max_tokens': 100, 'anthropic_beta': ['effort-2025-11-24']}
............................                                             [100%]
28 passed in 2.22s

…[537 chars omitted]…
 failures before and passes after. Affected Vertex Anthropic tests: 28 passed. Broader Vertex test run had 2 pre-existing unrelated Gemini reasoning-effort failures."}
submitted.

/repo
total 2560
drwxr-xr-x 1 root root    4096 Nov  2 12:40 .
drwxr-xr-x 1 root root    4096 Nov  2 12:42 ..
drwxr-xr-x 1 root root    4096 Nov  2 12:28 .circleci
drwxr-xr-x 1 root root    4096 Nov  2 12:28 .claude
drwxr-xr-x 1 root root    4096 Nov  2 12:28 .devcontainer
-rw-r--r-- 1 root root     635 Nov  2 12:28 .dockerignore
-rw-r--r-- 1 root root     624 Nov  2 12:28 .env.example
-rw-r--r-- 1 root root    1477 Nov  2 12:28 .flake8
drwxr-xr-x 1 root root    4096 Nov  2 12:43 .git
-rw-r--r-- 1 root root     386 Nov  2 12:28 .git-blame-ignore-revs

-rw-r--r-- 1 root root      25 Nov  2 12:28 .gitattributes
-rw-r--r-- 1 root root    3970 Nov  2 12:28 .gitguardian.yaml
drwxr-xr-x 1 root root    4096 Nov  2 12:28 .github
-rw-r--r-- 1 root root    2519 Nov  2 12:28 .gitignore
-rw-r--r-- 1 root root    1309 Nov  2 12:28 .pre-commit-config.yaml
drwxr-xr-x 1 root root    4096 Nov  2 12:26 
…[5330 chars omitted]…
uild_admin_ui.sh
./docker/Dockerfile.alpine
./docker/Dockerfile.custom_ui
./docker/Dockerfile.database
./docker/Dockerfile.dev
./docker/Dockerfile.health_check
./docker/Dockerfile.non_root
./docker/entrypoint.sh
./docker/install_auto_router.sh
./docker/prod_entrypoint.sh
./docker/README.md
./docker/supervisord.conf
./docker-compose.hardened.yml
./docker-compose.yml
./Dockerfile
./enterprise/LICENSE.md

bash: line 8: rg: command not found

litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:103:    def validate_anthropic_messages_environment(
litellm/llms/azure_ai/anthropic/messages_transformation.py:23:    def validate_anthropic_messages_environment(
litellm/llms/base_llm/anthropic_messages/transformation.py:22:    def validate_anthropic_messages_environment(  # use different name because return type is different from base config's validate_environment
litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py:63:    def validate_anthropic_messages_environment(
litellm/llms/custom_httpx/llm_http_handler.py:1866:        ) = anthropic_messages_provider_config.validate_anthropic_messages_environment(
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:18:class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessag
…[7496 chars omitted]…
rl"
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:203:        updated_headers, api_base = config.validate_anthropic_messages_environment(
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py:447:        VertexAIPartnerModelsAnthropicMessagesConfig,

# INSTRUCTIONS FOR LITELLM

This document provides comprehensive instructions for AI agents working in the LiteLLM repository.

## OVERVIEW

LiteLLM is a unified interface for 100+ LLMs that:
- Translates inputs to provider-specific completion, embedding, and image generation endpoints
- Provides consistent OpenAI-format output across all providers
- Includes retry/fallback logic across multiple deployments (Router)
- Offers a proxy server (LLM Gateway) with budgets, rate limits, and authentication
- Supports advanced features like function calling, streaming, caching, and observability

## REPOSITORY STRUCTURE

### Core Components
- `litellm/` - Main library code
  - `llms/` - Provider-specific implementations (OpenAI, Anthropic, Azure, etc.)
  - `proxy/` - Proxy server implementation (LLM Gateway)
  - `router_utils/` - Load balancing and fallback logic
  - `types/` - Type definition
…[8630 chars omitted]…
beta_header or ""
    ), "Other non-excluded beta headers should remain"
    # If prompt-caching was the only value, header should be removed completely
    headers2 = {"anthropic-beta": PROMPT_CACHING_BETA_HEADER}
    headers2 = update_headers_with_filtered_beta(headers2, "vertex_ai")
    assert (
        "anthropic-beta" not in headers2
    ), "Header should be removed if no supported values remain"

from typing import Any, Dict, List, Optional, Tuple

from litellm.llms.anthropic.common_utils import AnthropicModelInfo
from litellm.llms.anthropic.experimental_pass_through.messages.transformation import (
    AnthropicMessagesConfig,
)
from litellm.types.llms.anthropic import (
    ANTHROPIC_BETA_HEADER_VALUES,
    ANTHROPIC_HOSTED_TOOLS,
)
from litellm.types.llms.anthropic_tool_search import get_tool_search_beta_header
from litellm.types.llms.vertex_ai import VertexPartnerProvider

from litellm.types.router import GenericLiteLLMParams

from ....vertex_llm_base import VertexBase


class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, VertexBase):
    def validate_anthropic_messages_environment(
        self,
        headers: dict,
        model: str,
        messages: List[Any],
        optional_params: dict,
        litellm_params: dict,
        api_key: Option
…[8629 chars omitted]…
ner_models/anthropic/transformation.py:109:        data.pop("output_format", None)
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py:159:        VertexAI doesn't support the output_format parameter, so we force all models
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py:163:        # This ensures Claude Sonnet 4.5 uses tools instead of output_format

beta_values.add(get_tool_search_beta_header("vertex_ai"))
        
        if beta_values:
            headers["anthropic-beta"] = ",".join(beta_values)
        
        return headers, api_base

    def get_complete_url(
        self,
        api_base: Optional[str],
        api_key: Optional[str],
        model: str,

        optional_params: dict,
        litellm_params: dict,
        stream: Optional[bool] = None,
    ) -> str:
        if api_base is None:
            raise ValueError(
                "api_base is required. Unable to determine the correct api_base for the request."
            )
        return api_base  # no transformation is needed - handled in validate_environment

    def transform_anthropic_messages_request(
        self,
        model: str,
        messages: List[Dict],
        anthropic_messages_optional_request_params: Dict,
        litellm_param
…[8630 chars omitted]…
aders_non_vertex = {}
    optional_params_non_vertex = {
        "output_format": {
            "type": "json_schema",
            "json_schema": {
                "name": "MathResult",
                "schema": {"properties": {"result": {"type": "integer"}}},
            },
        },
        "is_vertex_request": False,
    }
    result_non_vertex = config.update_headers_with_optional_anthropic_beta(

1	from typing import Any, Dict, List, Optional, Tuple
     2	
     3	from litellm.llms.anthropic.common_utils import AnthropicModelInfo
     4	from litellm.llms.anthropic.experimental_pass_through.messages.transformation import (
     5	    AnthropicMessagesConfig,
     6	)
     7	from litellm.types.llms.anthropic import (
     8	    ANTHROPIC_BETA_HEADER_VALUES,
     9	    ANTHROPIC_HOSTED_TOOLS,
    10	)
    11	from litellm.types.llms.anthropic_tool_search import get_tool_search_beta_header
    12	from litellm.types.llms.vertex_ai import VertexPartnerProvider

    13	from litellm.types.router import GenericLiteLLMParams
    14	
    15	from ....vertex_llm_base import VertexBase
    16	
    17	
    18	class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, VertexBase):
    19	    def validate_anthropic_messages_environment(
    20	        self,
    21	        h
…[8630 chars omitted]…
est = super().transform_anthropic_messages_request(
litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:136:    def transform_anthropic_messages_request(
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py:90:    def transform_request(
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py:98:        data = super().transform_request(

from unittest.mock import patch

import pytest

from litellm.llms.vertex_ai.vertex_ai_partner_models.anthropic.experimental_pass_through.transformation import (
    VertexAIPartnerModelsAnthropicMessagesConfig,
)


def test_validate_environment_uses_vertex_ai_location():
    config = VertexAIPartnerModelsAnthropicMessagesConfig()
    headers = {}

    litellm_params = {
        "vertex_ai_project": "test-project",
        "vertex_ai_location": "europe-west1",
        "vertex_credentials": "{}",
    }
    optional_params = {}

    with patch.object(
        config, "_ensure_access_token", return_value=("token", "test-project")
    ), patch.object(
        config, "get_complete_vertex_url", return_value="https://mock-url"
    ) as mock_get_url:
        config.validate_anthropic_messages_environment(
            headers=headers,
            model="claude-3-sonnet",
            messages=[]
…[8629 chars omitted]…
 gemini (google ai studio)
    ) -> Tuple[str, str]:
        """
        Returns auth token and project id

--- project/location helpers ---
237:    def get_complete_vertex_url(
679:    def get_vertex_ai_project(litellm_params: dict) -> Optional[str]:
688:    def get_vertex_ai_credentials(litellm_params: dict) -> Optional[str]:
696:    def get_vertex_ai_location(litellm_params: dict) -> Optional[str]:

project_id=project_id,
                )
            except Exception as e:
                raise e

    def set_headers(
        self, auth_header: Optional[str], extra_headers: Optional[dict]
    ) -> dict:
        headers = {
            "Content-Type": "application/json",
        }
        if auth_header is not None:

            headers["Authorization"] = f"Bearer {auth_header}"
        if extra_headers is not None:
            headers.update(extra_headers)

        return headers

    @staticmethod
    def get_vertex_ai_project(litellm_params: dict) -> Optional[str]:
        return (
            litellm_params.pop("vertex_project", None)
            or litellm_params.pop("vertex_ai_project", None)
            or litellm.vertex_project
            or get_secret_str("VERTEXAI_PROJECT")
        )

    @staticmethod
    def get_vertex_ai_credentials(litellm_params
…[8629 chars omitted]…
opic_messages_request.pop(
   141	            "model", None
   142	        )  # do not pass model in request body to vertex ai
   143	
   144	        anthropic_messages_request.pop(
   145	            "output_format", None
   146	        )  # do not pass output_format in request body to vertex ai - vertex ai does not support output_format as yet
   147	
   148	        return anthropic_messages_request

12:45:40 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
environment: {'Authorization': 'Bearer preexisting', 'content-type': 'application/json'} None get_url called: False token called: False
request: {'messages': [{'role': 'user', 'content': 'hello'}], 'max_tokens': 100, 'output_config': {'format': {'type': 'json_schema', 'schema': {'type': 'object'}}}, 'anthropic_version': 'vertex-2023-10-16'}

litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:34:        if "Authorization" not in headers:
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:34:        if "Authorization" not in headers:
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:47:            api_base = self.get_complete_vertex_url(
litellm/llms/vertex_ai/vertex_ai_partner_models/main.py:164:            api_base = self.get_complete_vertex_url(
litellm/llms/vertex_ai/vertex_llm_base.py:237:    def get_complete_vertex_url(
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:47:            api_base = self.get_complete_vertex_url(
litellm/llms/vertex_ai/vertex_ai_partner_models/main.py:164:            api_base = self.get_complete_vertex_url(

120	                VertexLLM,
   121	            )
   122	        except Exception as e:
   123	            raise VertexAIError(
   124	                status_code=400,
   125	                message=f"""vertexai import failed please run `pip install -U "google-cloud-aiplatform>=1.38"`. Got error: {e}""",
   126	            )
   127	
   128	        if not (
   129	            hasattr(vertexai, "preview") or hasattr(vertexai.preview, "language_models")
   130	        ):
   131	            raise VertexAIError(

   132	                status_code=400,
   133	                message="""Upgrade vertex ai. Run `pip install "google-cloud-aiplatform>=1.38"`""",
   134	            )
   135	        try:
   136	            vertex_httpx_logic = VertexLLM()
   137	
   138	            access_token, project_id = vertex_httpx_logic._ensure_access_token(
   139	                credentials=vertex_cr
…[3026 chars omitted]…
t_vertex_ai_project(litellm_params)
grep: litellm/llms/anthropic/experimental_pass_through/messages/__pycache__/transformation.cpython-312.pyc: binary file matches
litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:48:            "output_config",
litellm/types/llms/anthropic.py:365:    output_config: Optional[AnthropicOutputConfig]  # Configuration for Claude's output behavior

grep: litellm/llms/anthropic/experimental_pass_through/messages: Is a directory
litellm/types/llms/anthropic.py:39:class AnthropicOutputConfig(TypedDict, total=False):
litellm/types/llms/anthropic.py:347:class AnthropicMessagesRequestOptionalParams(TypedDict, total=False):
litellm/types/llms/anthropic.py:363:    output_format: Optional[AnthropicOutputSchema]  # Structured outputs support
litellm/types/llms/anthropic.py:365:    output_config: Optional[AnthropicOutputConfig]  # Configuration for Claude's output behavior
litellm/types/llms/anthropic.py:368:class AnthropicMessagesRequest(AnthropicMessagesRequestOptionalParams, total=False):
litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:45:            "output_format",
litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:48:            "output_config",
litellm/llms/anthropic/experimental_
…[282 chars omitted]…
mat, speed
litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:281:        if optional_params.get("output_format") is not None:

grep: litellm/llms/anthropic/experimental_pass_through/adapters/__pycache__/transformation.cpython-312.pyc: binary file matches
litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py:790:                "name": "structured_output",

from typing import Any, AsyncIterator, Dict, List, Optional, Tuple

import httpx

from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
from litellm.litellm_core_utils.litellm_logging import verbose_logger
from litellm.llms.base_llm.anthropic_messages.transformation import (
    BaseAnthropicMessagesConfig,
)
from litellm.types.llms.anthropic import (
    ANTHROPIC_BETA_HEADER_VALUES,
    AnthropicMessagesRequest,

)
from litellm.types.llms.anthropic_messages.anthropic_response import (
    AnthropicMessagesResponse,
)
from litellm.types.llms.anthropic_tool_search import get_tool_search_beta_header
from litellm.types.router import GenericLiteLLMParams

from ...common_utils import (
    AnthropicError,
    AnthropicModelInfo,
    optionally_handle_anthropic_oauth,
)

DEFAULT_ANTHROPIC_API_BASE = "https://api.anthropic.com"
DEFAULT_ANTHROPIC_API_VERSION = "2
…[8629 chars omitted]…
 output"
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py:302:    structured outputs, ensuring consistency across all models.
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py:328:    ), "Claude 3 Sonnet should also use tool-based structured output"

diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
index 54c3f9e..caba34f 100644
--- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
+++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
@@ -31,19 +31,27 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
 
         Validate the environment for the request
         """
-        if "Authorization" not in headers:
+        has_authorization = "Authorization" in headers
+        should_construct_vertex_url = not has_authorization or api_base is None
+

+        vertex_ai_project = None
+        vertex_ai_location = None
+        proje
…[1048 chars omitted]…
essagesConfig, Vert
         anthropic_messages_request.pop(
             "output_format", None
         )  # do not pass output_format in request body to vertex ai - vertex ai does not support output_format as yet
+        anthropic_messages_request.pop(
+            "output_config", None
+        )  # do not pass output_config in request body to vertex ai
 
         return anthropic_messages_request

12:48:28 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
environment: {'Authorization': 'Bearer preexisting', 'content-type': 'application/json'} https://vertex-url
get_complete_vertex_url args: call(custom_api_base=None, vertex_location='us-central1', vertex_project='test-project', project_id='test-project', partner=<VertexPartnerProvider.claude: 'claude'>, stream=False, model='claude-3-sonnet')
token exchange called: False
request: {'messages': [{'role': 'user', 'content': 'hello'}], 'max_tokens': 100, 'anthropic_version': 'vertex-2023-10-16'}
...................                                                      [100%]
19 passed in 1.21s

tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/__pycache__/test_vertex_ai_partner_models_anthropic_messages_config.cpython-312-pytest-9.2.0.pyc
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/__pycache__/test_vertex_ai_partner_models_anthropic_transformation.cpython-312-pytest-9.2.0.pyc
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_anthropic_image_url_handling.py
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:6:    VertexAIPartnerModelsAnthropicMessagesConfig,
tests/test_lite
…[1299 chars omitted]…
opicMessagesConfig,
grep: tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/__pycache__/test_vertex_ai_partner_models_anthropic_messages_config.cpython-312-pytest-9.2.0.pyc: binary file matches
grep: tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/__pycache__/test_vertex_ai_partner_models_anthropic_transformation.cpython-312-pytest-9.2.0.pyc: binary file matches

def get_vertex_ai_location(litellm_params: dict) -> Optional[str]:
        return (
            litellm_params.pop("vertex_location", None)
            or litellm_params.pop("vertex_ai_location", None)
            or litellm.vertex_location
            or get_secret_str("VERTEXAI_LOCATION")
            or get_secret_str("VERTEX_LOCATION")
        )

    @staticmethod
    def safe_get_vertex_ai_project(litellm_params: dict) -> Optional[str]:
        """

        Safely get Vertex AI project without mutating the litellm_params dict.

        Unlike get_vertex_ai_project(), this does NOT pop values from the dict,
        making it safe to call multiple times with the same litellm_params.

        Args:
            litellm_params: Dictionary containing Vertex AI parameters

        Returns:
            Vertex AI project ID or None
        """
        return (
            litellm_params
…[1364 chars omitted]…
ion or None
        """
        return (
            litellm_params.get("vertex_location")
            or litellm_params.get("vertex_ai_location")
            or litellm.vertex_location
            or get_secret_str("VERTEXAI_LOCATION")
            or get_secret_str("VERTEX_LOCATION")
        )
litellm/types/router.py:165:class GenericLiteLLMParams(CredentialLiteLLMParams, CustomPricingLiteLLMParams):

............................                                             [100%]
28 passed in 1.39s
 M litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
index 54c3f9e..caba34f 100644
--- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
+++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
@@ -31,19 +31,27 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
 
         Validate the environment for the request
         """
-        if "Authorization" not in headers:

+        has_autho
…[1252 chars omitted]…
essagesConfig, Vert
         anthropic_messages_request.pop(
             "output_format", None
         )  # do not pass output_format in request body to vertex ai - vertex ai does not support output_format as yet
+        anthropic_messages_request.pop(
+            "output_config", None
+        )  # do not pass output_config in request body to vertex ai
 
         return anthropic_messages_request

FFFFFFFFFFF.FFFFF.F..FFF                                                 [100%]
=================================== FAILURES ===================================
________________ TestAnthropicDirectAPI.test_non_streaming_base ________________

self = <aiohttp.connector.TCPConnector object at 0x7ba023374290>
req = <aiohttp.client_reqrep.ClientRequest object at 0x7ba0237039b0>
traces = []
timeout = ClientTimeout(total=None, connect=600.0, sock_read=600.0, sock_connect=5.0, ceil_threshold=5)
client_error = <class 'aiohttp.client_exceptions.ClientConnectorError'>

    async def _create_direct_connection(
        self,

        req: ClientRequest,
        traces: list["Trace"],
        timeout: "ClientTimeout",
        *,
        client_error: type[Exception] = ClientConnectorError,
    ) -> tuple[asyncio.Transport, ResponseHandler]:
        sslcontext = self._get_ssl_context(req)
        fi
…[8632 chars omitted]…
ib/python3.12/asyncio/events.py", line 88, in _run
    self._context.run(self._callback, *self._args)
  File "/repo/litellm/litellm_core_utils/litellm_logging.py", line 2330, in async_success_handler
    print_verbose(
  File "/repo/litellm/utils.py", line 478, in print_verbose
    verbose_logger.debug(print_statement)
Message: 'Logging Details LiteLLM-Async Success Call, cache_hit=None'
Arguments: ()

if edit_type == "compact_20260112":
                has_compact = True
            else:
                has_other = True

        # Add compact header if any compact edits exist
        if has_compact:
            beta_set.add(ANTHROPIC_BETA_HEADER_VALUES.COMPACT_2026_01_12.value)

        # Add context management header if any other edits exist
        if has_other:
            beta_set.add(

                ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value
            )

    def transform_request(
        self,
        model: str,
        messages: List[AllMessageValues],
        optional_params: dict,
        litellm_params: dict,
        headers: dict,
    ) -> dict:
        data = super().transform_request(
            model=model,
            messages=messages,
            optional_params=optional_params,
            litellm_params=litellm_params,
    
…[4106 chars omitted]…
_messages_provider_config.transform_anthropic_messages_request(
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:130:    def transform_anthropic_messages_request(
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:138:        anthropic_messages_request = super().transform_anthropic_messages_request(

# What is this?
## Handler file for calling claude-3 on vertex ai
from typing import Any, List, Optional

import httpx

import litellm
from litellm.llms.base_llm.chat.transformation import LiteLLMLoggingObj
from litellm.types.llms.openai import AllMessageValues
from litellm.types.utils import ModelResponse

from ....anthropic.chat.transformation import AnthropicConfig

class VertexAIError(Exception):
    def __init__(self, status_code, message):
        self.status_code = status_code
        self.message = message
        self.request = httpx.Request(
            method="POST", url=" https://cloud.google.com/vertex-ai/"
        )
        self.response = httpx.Response(status_code=status_code, request=self.request)
        super().__init__(
            self.message
        )  # Call the base class constructor with the parameters it needs


class VertexAIAnthropicConfig(AnthropicConfig
…[8629 chars omitted]…
hould not be present for non-Vertex requests"


def test_vertex_ai_anthropic_context_management_compact_beta_header():
    """Test that context_management with compact adds the correct beta header for Vertex AI"""
    config = VertexAIAnthropicConfig()

    messages = [{"role": "user", "content": "Hello"}]
    optional_params = {
        "context_management": {"edits": [{"type": "compact_20260112"}]},

1246:    def transform_request(
   650	                deferred.append(tool)
   651	            else:
   652	                non_deferred.append(tool)
   653	
   654	        return non_deferred, deferred
   655	
   656	    def _expand_tool_references(
   657	        self,
   658	        content: List,
   659	        deferred_tools: List,
   660	    ) -> List:

   661	        """
   662	        Expand tool_reference blocks to full tool definitions.
   663	
   664	        When Anthropic's tool search returns results, it includes tool_reference blocks
   665	        that reference tools by name. This method expands those references to full
   666	        tool definitions from the deferred_tools catalog.
   667	
   668	        Args:
   669	            content: Response content that may contain tool_reference blocks
   670	            deferred_tools: List of deferred tools that can be refer
…[7578 chars omitted]…
tput_format") is not None:
1363:        ## Handle output_config (Anthropic-specific parameter)
1364:        if "output_config" in optional_params:
1365:            output_config = optional_params.get("output_config")
1366:            if output_config and isinstance(output_config, dict):
1367:                effort = output_config.get("effort")
1376:                data["output_config"] = output_config

1240	        if optional_params.get("speed") == "fast":
  1241	            self._ensure_beta_header(
  1242	                headers, ANTHROPIC_BETA_HEADER_VALUES.FAST_MODE_2026_02_01.value
  1243	            )
  1244	        return headers
  1245	
  1246	    def transform_request(
  1247	        self,
  1248	        model: str,
  1249	        messages: List[AllMessageValues],
  1250	        optional_params: dict,
  1251	        litellm_params: dict,

  1252	        headers: dict,
  1253	    ) -> dict:
  1254	        """
  1255	        Translate messages to anthropic format.
  1256	        """
  1257	        ## VALIDATE REQUEST
  1258	        """
  1259	        Anthropic doesn't support tool calling without `tools=` param specified.
  1260	        """
  1261	        from litellm.litellm_core_utils.prompt_templates.factory import (
  1262	            anthropic_messages_pt,
  1263	     
…[7153 chars omitted]…
sponse: dict) -> Tuple[
  1401	        str,
  1402	        Optional[List[Any]],
  1403	        Optional[
  1404	            List[
  1405	                Union[ChatCompletionThinkingBlock, ChatCompletionRedactedThinkingBlock]
litellm/utils.py:8177:                    VertexAIPartnerModelsAnthropicMessagesConfig,
litellm/utils.py:8180:                return VertexAIPartnerModelsAnthropicMessagesConfig()

elif litellm.LlmProviders.INFINITY == provider:
            return litellm.InfinityRerankConfig()
        elif litellm.LlmProviders.JINA_AI == provider:
            return litellm.JinaAIRerankConfig()
        elif litellm.LlmProviders.HOSTED_VLLM == provider:
            return litellm.HostedVLLMRerankConfig()
        elif litellm.LlmProviders.HUGGINGFACE == provider:
            return litellm.HuggingFaceRerankConfig()
        elif litellm.LlmProviders.DEEPINFRA == provider:
            return litellm.DeepinfraRerankConfig()
        elif litellm.LlmProviders.NVIDIA_NIM == provider:
            from litellm.llms.nvidia_nim.rerank.common_utils import (

                get_nvidia_nim_rerank_config,
            )

            return get_nvidia_nim_rerank_config(model)
        elif litellm.LlmProviders.VERTEX_AI == provider:
            return litellm.VertexAIRerankConfig()
      
…[7103 chars omitted]…
       litellm_params=dict(litellm_params),
            stream=stream,
        )

        headers, signed_json_body = anthropic_messages_provider_config.sign_request(
            headers=headers,
            optional_params=dict(
                litellm_params
            ),  # dynamic aws_* params are passed under litellm_params
            request_data=request_body,
            api_base=request_url,

diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
index 54c3f9e..caba34f 100644
--- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
+++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
@@ -31,19 +31,27 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
 
         Validate the environment for the request
         """
-        if "Authorization" not in headers:
+        has_authorization = "Authorization" in headers
+        should_construct_vertex_url = not has_authorization or api_base is None
+

+        vertex_ai_project = None
+        vertex_ai_location = None
+        proje
…[1915 chars omitted]…
)  # vertex anthropic doesn't accept 'model' parameter
 
-        # VertexAI doesn't support output_format parameter, remove it if present
+        # VertexAI doesn't support Anthropic structured output parameters.
         data.pop("output_format", None)
+        data.pop("output_config", None)
 
         tools = optional_params.get("tools")
         tool_search_used = self.is_tool_search_used(tools)

12:53:52 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.

Provider List: https://docs.litellm.ai/docs/providers

{'messages': [{'role': 'user', 'content': [{'type': 'text', 'text': 'hello'}]}], 'max_tokens': 100}
............................                                             [100%]
28 passed in 2.04s

.../experimental_pass_through/transformation.py         | 17 ++++++++++++++---
 .../anthropic/transformation.py                         |  3 ++-
 2 files changed, 16 insertions(+), 4 deletions(-)
diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
index 54c3f9e..caba34f 100644
--- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
+++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
@@ -31,19 +31,27 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
 
         Validate the environment for the request
         """
-        if "Authorization" not in headers:

+        has_authorizatio
…[2296 chars omitted]…
 structured output parameters.
         data.pop("output_format", None)
+        data.pop("output_config", None)
 
         tools = optional_params.get("tools")
         tool_search_used = self.is_tool_search_used(tools)
 M litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
 M litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py

submitted.