fix(types): keep loose payloads working under the sweep's validators

An off-schema Anthropic stream event is now skipped instead of ending the
guardrail's text and stop_reason scan, and MAI image usage accepts the loose
numbers it did before. New dict and list adapters hide their input from
validation errors, RerankResponse indexing keeps its field types, and the
delete_user test mocks the int /user/delete returns.

litellm/caching/caching.py

@@ -44,7 +44,9 @@ from .s3_cache import S3Cache
 RESPONSE_CACHE_TARGET: Final = "llm_response"
 _ALWAYS_KEYED_PROVIDER_PARAMS: Final = frozenset({"continuation_token"})
 _DECODED_LITERAL: Final = TypeAdapter(object)
-_REDIS_STARTUP_NODES_ADAPTER: Final = TypeAdapter(list[dict[str, object]], config=ConfigDict(strict=True))
+_REDIS_STARTUP_NODES_ADAPTER: Final = TypeAdapter(
+    list[dict[str, object]], config=ConfigDict(strict=True, hide_input_in_errors=True)
+)
 
 
 @contextmanager

litellm/llms/a2a/chat/guardrail_translation/handler.py

@@ -29,7 +29,7 @@ if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
     from litellm.types.proxy.auth.user_api_key_auth import UserAPIKeyAuth
 
-_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True))
+_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True, hide_input_in_errors=True))
 
 
 class _A2ATextPart(TypedDict, total=False):

litellm/llms/anthropic/chat/guardrail_translation/handler.py

@@ -1823,7 +1823,7 @@ class AnthropicMessagesHandler(BaseTranslation):
                         delta: _SSETextDelta = data.get("delta", {})
                         if delta.get("type") == "text_delta":
                             text += delta.get("text", "")
-                    except json.JSONDecodeError:
+                    except (json.JSONDecodeError, ValidationError):
                         verbose_proxy_logger.warning("Failed to parse JSON from SSE data: %s", data_line)
 
         except Exception as e:
@@ -1887,7 +1887,7 @@ class AnthropicMessagesHandler(BaseTranslation):
                                 stop_reason: object = delta.get("stop_reason")
                                 if stop_reason is not None:
                                     return True
-                            except json.JSONDecodeError:
+                            except (json.JSONDecodeError, ValidationError):
                                 verbose_proxy_logger.warning("Failed to parse JSON from SSE data: %s", data_line)
 
                 except Exception as e:

litellm/llms/azure_ai/image_generation/mai_transformation.py

@@ -21,13 +21,13 @@ if TYPE_CHECKING:
     from litellm.litellm_core_utils.tokenizer import Encoding as Tokenizer
 
 
-@with_config(ConfigDict(extra="allow", strict=True))
+@with_config(ConfigDict(extra="allow"))
 class _MAIImageUsageDetails(TypedDict, total=False):
     text_tokens: ReadOnly[NotRequired[int | float | None]]
     image_tokens: ReadOnly[NotRequired[int | float | None]]
 
 
-@with_config(ConfigDict(extra="allow", strict=True))
+@with_config(ConfigDict(extra="allow"))
 class _MAIImageUsage(TypedDict, total=False):
     input_tokens_details: ReadOnly[NotRequired[object]]
     num_input_text_tokens: ReadOnly[NotRequired[int | float | None]]
@@ -39,7 +39,7 @@ class _MAIImageUsage(TypedDict, total=False):
     total_tokens: ReadOnly[NotRequired[int | float | None]]
 
 
-@with_config(ConfigDict(extra="allow", strict=True))
+@with_config(ConfigDict(extra="allow"))
 class _MAIImageResponse(TypedDict, total=False):
     usage: ReadOnly[NotRequired[object]]
 

litellm/llms/edenai/audio_transcription/transformation.py

@@ -22,7 +22,7 @@ from litellm.utils import convert_to_model_response_object
 
 from ..common_utils import EdenAIException, authorized_headers, endpoint_url, reported_cost
 
-_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True))
+_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True, hide_input_in_errors=True))
 
 
 def _form_fields(model: str, optional_params: Mapping[str, object]) -> dict[str, object]:  # mutable-ok: httpx form data

litellm/llms/openai/image_generation/dall_e_2_transformation.py

@@ -10,7 +10,7 @@ from litellm.types.llms.openai import OpenAIImageGenerationOptionalParams
 from litellm.types.utils import ImageResponse
 from litellm.utils import convert_to_model_response_object
 
-_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True))
+_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True, hide_input_in_errors=True))
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.logging import Logging as LiteLLMLoggingObj

litellm/llms/openai/image_generation/dall_e_3_transformation.py

@@ -10,7 +10,7 @@ from litellm.types.llms.openai import OpenAIImageGenerationOptionalParams
 from litellm.types.utils import ImageResponse
 from litellm.utils import convert_to_model_response_object
 
-_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True))
+_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True, hide_input_in_errors=True))
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.logging import Logging as LiteLLMLoggingObj

litellm/llms/openai/image_generation/gpt_transformation.py

@@ -10,7 +10,7 @@ from litellm.types.llms.openai import OpenAIImageGenerationOptionalParams
 from litellm.types.utils import ImageResponse
 from litellm.utils import convert_to_model_response_object
 
-_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True))
+_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True, hide_input_in_errors=True))
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.logging import Logging as LiteLLMLoggingObj

litellm/proxy/auth/oauth2_check.py

@@ -3,7 +3,7 @@ import os
 from typing import Final, cast
 
 import httpx
-from pydantic import TypeAdapter
+from pydantic import ConfigDict, TypeAdapter
 
 from litellm._logging import verbose_proxy_logger
 from litellm.llms.custom_httpx.http_handler import (
@@ -12,7 +12,7 @@ from litellm.llms.custom_httpx.http_handler import (
 )
 from litellm.proxy._types import CommonProxyErrors, LitellmUserRoles, UserAPIKeyAuth
 
-_TOKEN_INFO_RESPONSE: Final = TypeAdapter(dict[str, object])
+_TOKEN_INFO_RESPONSE: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True, hide_input_in_errors=True))
 
 
 class Oauth2Handler:
@@ -182,7 +182,7 @@ class Oauth2Handler:
             response.raise_for_status()
 
             # If we get here, the request was successful
-            data = _TOKEN_INFO_RESPONSE.validate_python(response.json(), strict=True)
+            data = _TOKEN_INFO_RESPONSE.validate_python(response.json())
 
             verbose_proxy_logger.debug(
                 "Oauth2 token validation for token=%s, response from endpoint=%s",

litellm/proxy/client/users.py

@@ -6,8 +6,8 @@ from pydantic import ConfigDict, TypeAdapter
 
 from .exceptions import NotFoundError, UnauthorizedError
 
-_JSON_VALUE: Final = TypeAdapter(object, config=ConfigDict(strict=True))
-_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True))
+_JSON_VALUE: Final = TypeAdapter(object, config=ConfigDict(strict=True, hide_input_in_errors=True))
+_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True, hide_input_in_errors=True))
 
 
 class UsersManagementClient:

litellm/types/rerank.py

@@ -4,7 +4,7 @@ https://docs.cohere.com/reference/rerank
 
 """
 
-from typing import Literal
+from typing import Literal, overload
 
 from pydantic import ConfigDict, PrivateAttr
 from typing_extensions import ReadOnly, Required, TypedDict
@@ -95,6 +95,18 @@ class RerankResponse(LiteLLMBaseModel):
     def hidden_params(self, hidden_params: dict[str, object]) -> None:  # mutable-ok: API requires mutation
         self._hidden_params = hidden_params
 
+    @overload
+    def __getitem__(self, key: Literal["id"]) -> str | None: ...
+
+    @overload
+    def __getitem__(self, key: Literal["results"]) -> list[RerankResponseResult] | None: ...
+
+    @overload
+    def __getitem__(self, key: Literal["meta"]) -> RerankResponseMeta | None: ...
+
+    @overload
+    def __getitem__(self, key: str) -> object: ...
+
     def __getitem__(self, key: str) -> object:
         return self.__dict__[key]
 

tests/unit/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py

@@ -302,6 +302,28 @@ class TestAnthropicMessagesHandlerStreamingOutputProcessing:
                     texts.append(data["delta"]["text"])
         return texts
 
+    def test_off_schema_delta_is_skipped_without_ending_the_text_scan(self):
+        events = [
+            {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "abc"}},
+            {"type": "content_block_delta", "index": 1, "delta": {"type": "thinking_delta", "text": None}},
+            {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "def"}},
+        ]
+        chunk = "".join(f"event: content_block_delta\ndata: {json.dumps(event)}\n\n" for event in events).encode()
+
+        assert AnthropicMessagesHandler().get_streaming_string_so_far([chunk]) == "abcdef"
+
+    def test_off_schema_message_delta_does_not_hide_a_later_stop_reason(self):
+        events = [
+            {"type": "message_delta", "delta": None},
+            {"type": "message_delta", "delta": {"stop_reason": "end_turn", "stop_sequence": None}},
+        ]
+        chunk = "".join(f"event: message_delta\ndata: {json.dumps(event)}\n\n" for event in events).encode()
+
+        scan_key = AnthropicMessagesHandler().get_streaming_scan_key([chunk])
+
+        assert scan_key is not None
+        assert scan_key.stream_ended is True
+
     @pytest.mark.asyncio
     async def test_deliver_ended_stream_rewrites_writes_text_back_into_sse_chunks(self):
         handler = AnthropicMessagesHandler()

tests/unit/llms/azure_ai/image_generation/test_mai_image_generation.py

@@ -386,6 +386,14 @@ class TestAzureMAIImageGeneration:
         assert normalized["input_tokens"] == 22
         assert normalized["total_tokens"] == 22
 
+    def test_normalize_mai_usage_accepts_a_bool_token_count(self):
+        normalized = AzureFoundryMAIImageGenerationConfig().normalize_mai_image_usage(
+            {"input_tokens": 22, "output_tokens": True}
+        )
+
+        assert normalized["output_tokens"] == 1
+        assert normalized["total_tokens"] == 23
+
     def test_azure_sync_image_generation_uses_mai_response_transform(self):
         raw_response = MagicMock(spec=httpx.Response)
         raw_response.json.return_value = {

tests/unit/proxy/client/test_users.py

@@ -5,7 +5,6 @@ import pytest
 import requests
 
 
-
 from litellm.proxy.client.users import (
     NotFoundError,
     UnauthorizedError,
@@ -72,9 +71,9 @@ def test_create_user_unauthorized(mock_post, client):
 @patch("requests.post")
 def test_delete_user_success(mock_post, client):
     mock_post.return_value.status_code = 200
-    mock_post.return_value.json.return_value = {"deleted": 1}
+    mock_post.return_value.json.return_value = 1
     result = client.delete_user(["u1"])
-    assert result["deleted"] == 1
+    assert result == 1
     mock_post.assert_called_once()