From f08742c6f4ef09ab22ac07f96a691bab6c864d25 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 14 Jul 2026 17:29:48 -0700
Subject: [PATCH 01/93] fix(interactions): track cost and spend for Google
 Interactions API requests

---
 litellm/cost_calculator.py                    |   7 +
 litellm/litellm_core_utils/litellm_logging.py |  54 +++++--
 .../usage_object_transformation.py            | 109 ++++++++++++-
 .../test_usage_object_transformation.py       | 121 ++++++++++++++
 .../test_litellm_logging.py                   | 147 ++++++++++++++++++
 tests/test_litellm/test_cost_calculator.py    |  33 ++++
 6 files changed, 460 insertions(+), 11 deletions(-)
 create mode 100644 tests/test_litellm/litellm_core_utils/llm_cost_calc/test_usage_object_transformation.py

diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py
index a40a8e1389c..3c541605caa 100644
--- a/litellm/cost_calculator.py
+++ b/litellm/cost_calculator.py
@@ -19,6 +19,7 @@ from litellm.litellm_core_utils.llm_cost_calc.tool_call_cost_tracking import (
     StandardBuiltInToolCostTracking,
 )
 from litellm.litellm_core_utils.llm_cost_calc.usage_object_transformation import (
+    InteractionsUsageObjectTransformation,
     TranscriptionUsageObjectTransformation,
 )
 from litellm.litellm_core_utils.llm_cost_calc.utils import (
@@ -899,6 +900,8 @@ def _get_usage_object(
                 usage_obj,
             )
         )
+    elif isinstance(usage_obj, dict) and InteractionsUsageObjectTransformation.is_interactions_usage_object(usage_obj):
+        return InteractionsUsageObjectTransformation.transform_interactions_usage_object(usage_obj)
     elif isinstance(usage_obj, dict):
         return Usage(**usage_obj)
     elif isinstance(usage_obj, BaseModel):
@@ -1267,6 +1270,10 @@ def completion_cost(
                         )
                         if tr_usage is not None:
                             _usage = tr_usage.model_dump()
+                    elif InteractionsUsageObjectTransformation.is_interactions_usage_object(_usage):
+                        _usage = InteractionsUsageObjectTransformation.transform_interactions_usage_object(
+                            _usage
+                        ).model_dump()
                     else:
                         _usage = _usage
 
diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index 461ab62b815..0f6e0ccf9c1 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -68,6 +68,9 @@ from litellm.litellm_core_utils.get_litellm_params import get_litellm_params
 from litellm.litellm_core_utils.llm_cost_calc.tool_call_cost_tracking import (
     StandardBuiltInToolCostTracking,
 )
+from litellm.litellm_core_utils.llm_cost_calc.usage_object_transformation import (
+    InteractionsUsageObjectTransformation,
+)
 from litellm.litellm_core_utils.logging_utils import truncate_base64_in_messages
 from litellm.litellm_core_utils.model_param_helper import ModelParamHelper
 from litellm.litellm_core_utils.redact_messages import (
@@ -93,6 +96,10 @@ from litellm.types.llms.openai import (
     ResponseIncompleteEvent,
     ResponsesAPIResponse,
 )
+from litellm.types.interactions import (
+    InteractionsAPIResponse,
+    InteractionsAPIStreamingResponse,
+)
 from litellm.types.mcp import MCPPostCallResponseObject
 from litellm.types.prompts.init_prompts import PromptSpec
 from litellm.types.rerank import RerankResponse
@@ -1888,6 +1895,7 @@ class Logging(LiteLLMLoggingBaseClass):
             or isinstance(logging_result, FineTuningJob)
             or isinstance(logging_result, LiteLLMBatch)
             or isinstance(logging_result, ResponsesAPIResponse)
+            or isinstance(logging_result, InteractionsAPIResponse)
             or isinstance(logging_result, OpenAIFileObject)
             or isinstance(logging_result, LiteLLMRealtimeStreamLoggingObject)
             or isinstance(logging_result, OpenAIModerationResponse)
@@ -1973,7 +1981,7 @@ class Logging(LiteLLMLoggingBaseClass):
         try:
             ## BUILD COMPLETE STREAMED RESPONSE
             complete_streaming_response: Optional[
-                Union[ModelResponse, TextCompletionResponse, ResponsesAPIResponse]
+                Union[ModelResponse, TextCompletionResponse, ResponsesAPIResponse, InteractionsAPIResponse]
             ] = None
             if "complete_streaming_response" in self.model_call_details:
                 return  # break out of this.
@@ -2428,14 +2436,14 @@ class Logging(LiteLLMLoggingBaseClass):
         ## BUILD COMPLETE STREAMED RESPONSE
         if "async_complete_streaming_response" in self.model_call_details:
             return  # break out of this.
-        complete_streaming_response: Optional[Union[ModelResponse, TextCompletionResponse, ResponsesAPIResponse]] = (
-            self._get_assembled_streaming_response(
-                result=result,
-                start_time=start_time,
-                end_time=end_time,
-                is_async=True,
-                streaming_chunks=self.streaming_chunks,
-            )
+        complete_streaming_response: (
+            Union[ModelResponse, TextCompletionResponse, ResponsesAPIResponse, InteractionsAPIResponse] | None
+        ) = self._get_assembled_streaming_response(
+            result=result,
+            start_time=start_time,
+            end_time=end_time,
+            is_async=True,
+            streaming_chunks=self.streaming_chunks,
         )
 
         if complete_streaming_response is not None:
@@ -3153,7 +3161,7 @@ class Logging(LiteLLMLoggingBaseClass):
         end_time: datetime.datetime,
         is_async: bool,
         streaming_chunks: List[Any],
-    ) -> Optional[Union[ModelResponse, TextCompletionResponse, ResponsesAPIResponse]]:
+    ) -> Union[ModelResponse, TextCompletionResponse, ResponsesAPIResponse, InteractionsAPIResponse] | None:
         if self.stream is not True:
             return None
         if isinstance(result, ModelResponse):
@@ -3180,9 +3188,31 @@ class Logging(LiteLLMLoggingBaseClass):
                     ),
                 )
             return result.response
+        elif isinstance(result, InteractionsAPIStreamingResponse):
+            return self._assemble_completed_interaction_response(result)
         else:
             return None
 
+    @staticmethod
+    def _assemble_completed_interaction_response(
+        result: InteractionsAPIStreamingResponse,
+    ) -> InteractionsAPIResponse | None:
+        """
+        The Interactions API streaming iterator hands the terminal event to the
+        success handlers: the new schema (Api-Revision: 2026-05-20) emits
+        ``interaction.completed`` carrying the full interaction object, the
+        legacy schema (2026-05-07) emits a chunk with ``status="completed"``
+        and usage on the chunk itself. Build the equivalent non-streaming
+        response so cost calculation and spend tracking see one shape.
+        """
+        if result.event_type == "interaction.completed" and result.interaction is not None:
+            return InteractionsAPIResponse(**result.interaction)
+        if result.status == "completed":
+            return InteractionsAPIResponse(
+                **result.model_dump(exclude={"event_type", "delta", "index", "step", "interaction_id", "interaction"})
+            )
+        return None
+
     def _handle_anthropic_messages_response_logging(self, result: Any) -> ModelResponse:
         """
         Handles logging for Anthropic messages responses.
@@ -4687,6 +4717,8 @@ class StandardLoggingPayloadSetup:
         elif isinstance(usage, dict):
             if ResponseAPILoggingUtils._is_response_api_usage(usage):
                 return ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage(usage)
+            if InteractionsUsageObjectTransformation.is_interactions_usage_object(usage):
+                return InteractionsUsageObjectTransformation.transform_interactions_usage_object(usage)
             return Usage(**usage)
 
         raise ValueError(f"usage is required, got={usage} of type {type(usage)}")
@@ -4713,6 +4745,8 @@ class StandardLoggingPayloadSetup:
         if isinstance(_raw, dict):
             if ResponseAPILoggingUtils._is_response_api_usage(_raw):
                 return ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage(_raw).model_dump()
+            if InteractionsUsageObjectTransformation.is_interactions_usage_object(_raw):
+                return InteractionsUsageObjectTransformation.transform_interactions_usage_object(_raw).model_dump()
             return _raw
         if isinstance(_raw, Usage):
             return _raw.model_dump()
diff --git a/litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py b/litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py
index 1c6adbec174..3f591180b77 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py
@@ -1,6 +1,7 @@
-from typing import Any, Optional, Union
+from typing import Any, Mapping, Optional, Sequence, Union
 
 from litellm.types.utils import (
+    CompletionTokensDetailsWrapper,
     PromptTokensDetailsWrapper,
     TranscriptionUsageDurationObject,
     TranscriptionUsageTokensObject,
@@ -34,3 +35,109 @@ class TranscriptionUsageObjectTransformation:
                 ),
             )
         return None
+
+
+_INTERACTIONS_MODALITY_FIELDS: Mapping[str, str] = {
+    "text": "text_tokens",
+    "audio": "audio_tokens",
+    "image": "image_tokens",
+    "video": "video_tokens",
+    "document": "text_tokens",
+}
+
+
+def _modality_field(entry: Mapping[str, Any]) -> str | None:
+    return _INTERACTIONS_MODALITY_FIELDS.get(str(entry.get("modality", "")).lower())
+
+
+def _token_count(value: Any) -> int:
+    return value if isinstance(value, int) else 0
+
+
+def _modality_token_sums(entries: Sequence[Mapping[str, Any]]) -> Mapping[str, int]:
+    fields = {field for entry in entries if (field := _modality_field(entry)) is not None}
+    return {
+        field: sum(_token_count(entry.get("tokens")) for entry in entries if _modality_field(entry) == field)
+        for field in fields
+    }
+
+
+def _subtract_cached_from_input(
+    input_sums: Mapping[str, int],
+    cached_sums: Mapping[str, int],
+    total_cached_tokens: int,
+) -> Mapping[str, int]:
+    if cached_sums:
+        return {field: max(0, tokens - cached_sums.get(field, 0)) for field, tokens in input_sums.items()}
+    if total_cached_tokens and "text_tokens" in input_sums:
+        return {
+            **input_sums,
+            "text_tokens": max(0, input_sums["text_tokens"] - total_cached_tokens),
+        }
+    return input_sums
+
+
+class InteractionsUsageObjectTransformation:
+    """
+    Maps the Google Interactions API usage block (total_input_tokens,
+    output_tokens_by_modality, ...) into LiteLLM's chat-format ``Usage`` so the
+    generic cost calculator and spend tracking can bill it.
+    """
+
+    @staticmethod
+    def is_interactions_usage_object(usage_object: Any) -> bool:
+        if not isinstance(usage_object, dict):
+            return False
+        if "prompt_tokens" in usage_object or "input_tokens" in usage_object:
+            return False
+        return "total_input_tokens" in usage_object or "total_output_tokens" in usage_object
+
+    @staticmethod
+    def transform_interactions_usage_object(usage_object: Mapping[str, Any]) -> Usage:
+        input_entries = tuple(usage_object.get("input_tokens_by_modality") or ()) + tuple(
+            usage_object.get("tool_use_tokens_by_modality") or ()
+        )
+        cached_sums = _modality_token_sums(tuple(usage_object.get("cached_tokens_by_modality") or ()))
+        output_sums = _modality_token_sums(tuple(usage_object.get("output_tokens_by_modality") or ()))
+
+        total_cached_tokens = _token_count(usage_object.get("total_cached_tokens"))
+        input_sums = _subtract_cached_from_input(
+            input_sums=_modality_token_sums(input_entries),
+            cached_sums=cached_sums,
+            total_cached_tokens=total_cached_tokens,
+        )
+
+        reasoning_tokens = _token_count(usage_object.get("total_reasoning_tokens")) or _token_count(
+            usage_object.get("total_thought_tokens")
+        )
+        prompt_tokens = _token_count(usage_object.get("total_input_tokens")) + _token_count(
+            usage_object.get("total_tool_use_tokens")
+        )
+        completion_tokens = _token_count(usage_object.get("total_output_tokens")) + reasoning_tokens
+        total_tokens = _token_count(usage_object.get("total_tokens")) or (prompt_tokens + completion_tokens)
+
+        prompt_tokens_details = (
+            PromptTokensDetailsWrapper(
+                cached_tokens=total_cached_tokens or None,
+                **input_sums,
+            )
+            if input_sums or total_cached_tokens
+            else None
+        )
+        completion_tokens_details = (
+            CompletionTokensDetailsWrapper(
+                reasoning_tokens=reasoning_tokens or None,
+                **output_sums,
+            )
+            if output_sums or reasoning_tokens
+            else None
+        )
+
+        return Usage(
+            prompt_tokens=prompt_tokens,
+            completion_tokens=completion_tokens,
+            total_tokens=total_tokens,
+            prompt_tokens_details=prompt_tokens_details,
+            completion_tokens_details=completion_tokens_details,
+            cache_read_input_tokens=total_cached_tokens or None,
+        )
diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_usage_object_transformation.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_usage_object_transformation.py
new file mode 100644
index 00000000000..01241cf260d
--- /dev/null
+++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_usage_object_transformation.py
@@ -0,0 +1,121 @@
+from litellm.litellm_core_utils.llm_cost_calc.usage_object_transformation import (
+    InteractionsUsageObjectTransformation,
+)
+from litellm.types.utils import Usage
+
+OMNI_VIDEO_USAGE = {
+    "total_tokens": 18247,
+    "total_input_tokens": 16,
+    "input_tokens_by_modality": [{"modality": "text", "tokens": 16}],
+    "total_cached_tokens": 0,
+    "total_output_tokens": 17937,
+    "output_tokens_by_modality": [{"modality": "video", "tokens": 17376}],
+    "total_tool_use_tokens": 0,
+    "total_thought_tokens": 294,
+}
+
+
+def test_detects_interactions_usage_object():
+    assert InteractionsUsageObjectTransformation.is_interactions_usage_object(OMNI_VIDEO_USAGE) is True
+
+
+def test_rejects_chat_and_responses_api_usage_objects():
+    chat_usage = {"prompt_tokens": 10, "completion_tokens": 20, "total_tokens": 30}
+    responses_api_usage = {"input_tokens": 10, "output_tokens": 20, "total_tokens": 30}
+    assert InteractionsUsageObjectTransformation.is_interactions_usage_object(chat_usage) is False
+    assert InteractionsUsageObjectTransformation.is_interactions_usage_object(responses_api_usage) is False
+    assert InteractionsUsageObjectTransformation.is_interactions_usage_object(None) is False
+    assert InteractionsUsageObjectTransformation.is_interactions_usage_object("usage") is False
+
+
+def test_transforms_real_omni_video_usage_block():
+    usage = InteractionsUsageObjectTransformation.transform_interactions_usage_object(OMNI_VIDEO_USAGE)
+
+    assert isinstance(usage, Usage)
+    assert usage.prompt_tokens == 16
+    assert usage.completion_tokens == 17937 + 294
+    assert usage.total_tokens == 18247
+    assert usage.prompt_tokens_details is not None
+    assert usage.prompt_tokens_details.text_tokens == 16
+    assert usage.completion_tokens_details is not None
+    assert usage.completion_tokens_details.video_tokens == 17376
+    assert usage.completion_tokens_details.reasoning_tokens == 294
+
+
+def test_transforms_reasoning_tokens_spec_field_name():
+    usage = InteractionsUsageObjectTransformation.transform_interactions_usage_object(
+        {
+            "total_input_tokens": 10,
+            "total_output_tokens": 20,
+            "total_reasoning_tokens": 5,
+        }
+    )
+    assert usage.completion_tokens == 25
+    assert usage.completion_tokens_details is not None
+    assert usage.completion_tokens_details.reasoning_tokens == 5
+    assert usage.total_tokens == 35
+
+
+def test_cached_tokens_subtracted_from_text_input():
+    usage = InteractionsUsageObjectTransformation.transform_interactions_usage_object(
+        {
+            "total_input_tokens": 1000,
+            "input_tokens_by_modality": [{"modality": "text", "tokens": 1000}],
+            "total_cached_tokens": 400,
+            "total_output_tokens": 50,
+        }
+    )
+    assert usage.prompt_tokens == 1000
+    assert usage.prompt_tokens_details is not None
+    assert usage.prompt_tokens_details.text_tokens == 600
+    assert usage.prompt_tokens_details.cached_tokens == 400
+    assert usage._cache_read_input_tokens == 400
+
+
+def test_cached_tokens_subtracted_per_modality_when_breakdown_present():
+    usage = InteractionsUsageObjectTransformation.transform_interactions_usage_object(
+        {
+            "total_input_tokens": 1500,
+            "input_tokens_by_modality": [
+                {"modality": "text", "tokens": 1000},
+                {"modality": "audio", "tokens": 500},
+            ],
+            "total_cached_tokens": 300,
+            "cached_tokens_by_modality": [{"modality": "audio", "tokens": 300}],
+            "total_output_tokens": 50,
+        }
+    )
+    assert usage.prompt_tokens_details is not None
+    assert usage.prompt_tokens_details.text_tokens == 1000
+    assert usage.prompt_tokens_details.audio_tokens == 200
+    assert usage.prompt_tokens_details.cached_tokens == 300
+
+
+def test_tool_use_tokens_billed_as_input():
+    usage = InteractionsUsageObjectTransformation.transform_interactions_usage_object(
+        {
+            "total_input_tokens": 100,
+            "input_tokens_by_modality": [{"modality": "text", "tokens": 100}],
+            "total_tool_use_tokens": 40,
+            "tool_use_tokens_by_modality": [{"modality": "text", "tokens": 40}],
+            "total_output_tokens": 10,
+        }
+    )
+    assert usage.prompt_tokens == 140
+    assert usage.prompt_tokens_details is not None
+    assert usage.prompt_tokens_details.text_tokens == 140
+
+
+def test_document_modality_folds_into_text():
+    usage = InteractionsUsageObjectTransformation.transform_interactions_usage_object(
+        {
+            "total_input_tokens": 80,
+            "input_tokens_by_modality": [
+                {"modality": "text", "tokens": 30},
+                {"modality": "document", "tokens": 50},
+            ],
+            "total_output_tokens": 10,
+        }
+    )
+    assert usage.prompt_tokens_details is not None
+    assert usage.prompt_tokens_details.text_tokens == 80
diff --git a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
index ade2c677745..3769c656b0c 100644
--- a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
+++ b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
@@ -3773,3 +3773,150 @@ def test_zero_token_video_usage_preserves_duration_seconds(logging_obj):
     assert payload["metadata"]["usage_object"]["duration_seconds"] == 4.0
     assert payload["total_tokens"] == 0
     assert payload["completion_tokens"] == 0
+
+
+INTERACTIONS_USAGE_BLOCK = {
+    "total_tokens": 175,
+    "total_input_tokens": 100,
+    "input_tokens_by_modality": [{"modality": "text", "tokens": 100}],
+    "total_cached_tokens": 0,
+    "total_output_tokens": 50,
+    "output_tokens_by_modality": [{"modality": "text", "tokens": 50}],
+    "total_tool_use_tokens": 0,
+    "total_thought_tokens": 25,
+}
+
+
+def _interactions_logging_obj(stream: bool):
+    logging_obj = LitellmLogging(
+        model="gemini-2.5-flash",
+        messages=[],
+        stream=stream,
+        call_type="acreate",
+        start_time=time.time(),
+        litellm_call_id="interactions-call-id",
+        function_id="interactions-fn-id",
+    )
+    logging_obj.update_environment_variables(
+        litellm_params={},
+        optional_params={},
+        model="gemini-2.5-flash",
+        custom_llm_provider="gemini",
+        input="hi",
+    )
+    return logging_obj
+
+
+def test_interactions_response_is_recognized_for_logging():
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    logging_obj = _interactions_logging_obj(stream=False)
+    response = InteractionsAPIResponse(id="interactions/abc", model="gemini-2.5-flash", status="completed")
+    assert logging_obj._is_recognized_call_type_for_logging(logging_result=response) is True
+
+
+def test_non_streaming_interactions_success_sets_response_cost_and_usage():
+    import datetime as dt
+
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    logging_obj = _interactions_logging_obj(stream=False)
+    response = InteractionsAPIResponse(
+        id="interactions/abc",
+        model="gemini-2.5-flash",
+        status="completed",
+        steps=[],
+        usage=dict(INTERACTIONS_USAGE_BLOCK),
+    )
+
+    logging_obj._success_handler_helper_fn(
+        result=response,
+        start_time=dt.datetime.now(),
+        end_time=dt.datetime.now(),
+        cache_hit=False,
+    )
+
+    assert logging_obj.model_call_details["response_cost"] > 0
+    standard_logging_object = logging_obj.model_call_details["standard_logging_object"]
+    assert standard_logging_object["prompt_tokens"] == 100
+    assert standard_logging_object["completion_tokens"] == 75
+    assert standard_logging_object["total_tokens"] == 175
+    assert standard_logging_object["response_cost"] == logging_obj.model_call_details["response_cost"]
+
+
+def test_assembled_streaming_response_from_completed_interaction_event():
+    import datetime as dt
+
+    from litellm.types.interactions import (
+        InteractionsAPIResponse,
+        InteractionsAPIStreamingResponse,
+    )
+
+    logging_obj = _interactions_logging_obj(stream=True)
+    completed_event = InteractionsAPIStreamingResponse(
+        event_type="interaction.completed",
+        interaction={
+            "id": "interactions/abc",
+            "model": "gemini-2.5-flash",
+            "status": "completed",
+            "steps": [],
+            "usage": dict(INTERACTIONS_USAGE_BLOCK),
+        },
+    )
+
+    assembled = logging_obj._get_assembled_streaming_response(
+        result=completed_event,
+        start_time=dt.datetime.now(),
+        end_time=dt.datetime.now(),
+        is_async=True,
+        streaming_chunks=[],
+    )
+
+    assert isinstance(assembled, InteractionsAPIResponse)
+    assert assembled.usage == INTERACTIONS_USAGE_BLOCK
+
+    in_progress_event = InteractionsAPIStreamingResponse(event_type="interaction.in_progress")
+    assert (
+        logging_obj._get_assembled_streaming_response(
+            result=in_progress_event,
+            start_time=dt.datetime.now(),
+            end_time=dt.datetime.now(),
+            is_async=True,
+            streaming_chunks=[],
+        )
+        is None
+    )
+
+
+def test_assembled_streaming_response_from_legacy_completed_chunk():
+    from litellm.types.interactions import (
+        InteractionsAPIResponse,
+        InteractionsAPIStreamingResponse,
+    )
+
+    legacy_chunk = InteractionsAPIStreamingResponse(
+        event_type="interaction.complete",
+        id="interactions/legacy",
+        model="gemini-2.5-flash",
+        status="completed",
+        outputs=[],
+        usage=dict(INTERACTIONS_USAGE_BLOCK),
+    )
+
+    assembled = LitellmLogging._assemble_completed_interaction_response(legacy_chunk)
+
+    assert isinstance(assembled, InteractionsAPIResponse)
+    assert assembled.id == "interactions/legacy"
+    assert assembled.usage == INTERACTIONS_USAGE_BLOCK
+
+
+def test_standard_logging_payload_maps_interactions_usage():
+    from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup
+
+    usage = StandardLoggingPayloadSetup.get_usage_from_response_obj(
+        response_obj={"usage": dict(INTERACTIONS_USAGE_BLOCK)}
+    )
+
+    assert usage.prompt_tokens == 100
+    assert usage.completion_tokens == 75
+    assert usage.total_tokens == 175
diff --git a/tests/test_litellm/test_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py
index 9636db4f4cd..c76439e5ad1 100644
--- a/tests/test_litellm/test_cost_calculator.py
+++ b/tests/test_litellm/test_cost_calculator.py
@@ -3479,3 +3479,36 @@ def test_batch_cost_calculator_cache_creation_falls_back_to_input_rate():
     )
 
     assert prompt_cost == pytest.approx((1000 * 3e-6 + 8000 * 3e-7 + 2000 * 3e-6) / 2)
+
+
+def test_completion_cost_bills_interactions_api_response():
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    model_info = litellm.get_model_info(model="gemini-2.5-flash", custom_llm_provider="gemini")
+    response = InteractionsAPIResponse(
+        id="interactions/abc123",
+        model="gemini-2.5-flash",
+        status="completed",
+        steps=[],
+        usage={
+            "total_tokens": 175,
+            "total_input_tokens": 100,
+            "input_tokens_by_modality": [{"modality": "text", "tokens": 100}],
+            "total_cached_tokens": 0,
+            "total_output_tokens": 50,
+            "output_tokens_by_modality": [{"modality": "text", "tokens": 50}],
+            "total_tool_use_tokens": 0,
+            "total_thought_tokens": 25,
+        },
+    )
+
+    cost = completion_cost(completion_response=response, custom_llm_provider="gemini")
+
+    reasoning_rate = model_info.get("output_cost_per_reasoning_token") or model_info["output_cost_per_token"]
+    expected = (
+        100 * model_info["input_cost_per_token"]
+        + 50 * model_info["output_cost_per_token"]
+        + 25 * reasoning_rate
+    )
+    assert cost == pytest.approx(expected)
+    assert cost > 0

From f1a5054a16a503c5e087121abf87c0246aa8b6d0 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 14 Jul 2026 18:11:20 -0700
Subject: [PATCH 02/93] fix(interactions): bill only interaction creation, not
 GET polls

---
 litellm/litellm_core_utils/litellm_logging.py | 18 ++++++++-
 litellm/types/utils.py                        |  6 +++
 .../test_litellm_logging.py                   | 40 +++++++++++++++++--
 ui/litellm-dashboard/src/lib/http/schema.d.ts |  2 +-
 4 files changed, 60 insertions(+), 6 deletions(-)

diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index 0f6e0ccf9c1..94ee595a169 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -1895,7 +1895,7 @@ class Logging(LiteLLMLoggingBaseClass):
             or isinstance(logging_result, FineTuningJob)
             or isinstance(logging_result, LiteLLMBatch)
             or isinstance(logging_result, ResponsesAPIResponse)
-            or isinstance(logging_result, InteractionsAPIResponse)
+            or (isinstance(logging_result, InteractionsAPIResponse) and self._is_interactions_create_call_type())
             or isinstance(logging_result, OpenAIFileObject)
             or isinstance(logging_result, LiteLLMRealtimeStreamLoggingObject)
             or isinstance(logging_result, OpenAIModerationResponse)
@@ -1913,6 +1913,22 @@ class Logging(LiteLLMLoggingBaseClass):
             return True
         return False
 
+    def _is_interactions_create_call_type(self) -> bool:
+        """
+        Only interaction creation is billable. GET polls, deletes, and cancels
+        also return an ``InteractionsAPIResponse`` (with usage once completed),
+        so recognizing those would write spend on every poll of a background
+        interaction. The proxy sets ``call_type`` from its route_type
+        (``create_interaction``/``acreate_interaction``); the SDK sets it from
+        the decorated function name (``create``/``acreate``).
+        """
+        return self.call_type in (
+            CallTypes.create_interaction.value,
+            CallTypes.acreate_interaction.value,
+            "create",
+            "acreate",
+        )
+
     def _flush_passthrough_collected_chunks_helper(
         self,
         raw_bytes: List[bytes],
diff --git a/litellm/types/utils.py b/litellm/types/utils.py
index 90ea99ceb23..0fafd4a27fe 100644
--- a/litellm/types/utils.py
+++ b/litellm/types/utils.py
@@ -396,6 +396,12 @@ class CallTypes(str, Enum):
     vector_store_search = "vector_store_search"
     avector_store_search = "avector_store_search"
 
+    #########################################################
+    # Google Interactions API Call Types
+    #########################################################
+    create_interaction = "create_interaction"
+    acreate_interaction = "acreate_interaction"
+
     #########################################################
     # Container Call Types
     #########################################################
diff --git a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
index 3769c656b0c..2bf9f54d7c9 100644
--- a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
+++ b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
@@ -3787,12 +3787,12 @@ INTERACTIONS_USAGE_BLOCK = {
 }
 
 
-def _interactions_logging_obj(stream: bool):
+def _interactions_logging_obj(stream: bool, call_type: str = "acreate"):
     logging_obj = LitellmLogging(
         model="gemini-2.5-flash",
         messages=[],
         stream=stream,
-        call_type="acreate",
+        call_type=call_type,
         start_time=time.time(),
         litellm_call_id="interactions-call-id",
         function_id="interactions-fn-id",
@@ -3807,14 +3807,46 @@ def _interactions_logging_obj(stream: bool):
     return logging_obj
 
 
-def test_interactions_response_is_recognized_for_logging():
+@pytest.mark.parametrize("call_type", ["create", "acreate", "create_interaction", "acreate_interaction"])
+def test_interactions_response_is_recognized_for_logging(call_type):
     from litellm.types.interactions import InteractionsAPIResponse
 
-    logging_obj = _interactions_logging_obj(stream=False)
+    logging_obj = _interactions_logging_obj(stream=False, call_type=call_type)
     response = InteractionsAPIResponse(id="interactions/abc", model="gemini-2.5-flash", status="completed")
     assert logging_obj._is_recognized_call_type_for_logging(logging_result=response) is True
 
 
+@pytest.mark.parametrize(
+    "call_type",
+    ["aget", "get", "aget_interaction", "adelete_interaction", "acancel_interaction"],
+)
+def test_interactions_get_poll_is_not_billed(call_type):
+    import datetime as dt
+
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    logging_obj = _interactions_logging_obj(stream=False, call_type=call_type)
+    response = InteractionsAPIResponse(
+        id="interactions/abc",
+        model="gemini-2.5-flash",
+        status="completed",
+        steps=[],
+        usage=dict(INTERACTIONS_USAGE_BLOCK),
+    )
+
+    assert logging_obj._is_recognized_call_type_for_logging(logging_result=response) is False
+
+    logging_obj._success_handler_helper_fn(
+        result=response,
+        start_time=dt.datetime.now(),
+        end_time=dt.datetime.now(),
+        cache_hit=False,
+    )
+
+    assert logging_obj.model_call_details.get("response_cost") is None
+    assert logging_obj.model_call_details.get("standard_logging_object") is None
+
+
 def test_non_streaming_interactions_success_sets_response_cost_and_usage():
     import datetime as dt
 
diff --git a/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts
index 5629cd6c8d4..59c0532ccbe 100644
--- a/ui/litellm-dashboard/src/lib/http/schema.d.ts
+++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts
@@ -21685,7 +21685,7 @@ export interface components {
          * CallTypes
          * @enum {string}
          */
-        CallTypes: "embedding" | "aembedding" | "completion" | "acompletion" | "atext_completion" | "text_completion" | "image_generation" | "aimage_generation" | "image_edit" | "aimage_edit" | "moderation" | "amoderation" | "atranscription" | "transcription" | "aspeech" | "speech" | "rerank" | "arerank" | "search" | "asearch" | "_arealtime" | "_aresponses_websocket" | "create_batch" | "acreate_batch" | "aretrieve_batch" | "retrieve_batch" | "acancel_batch" | "cancel_batch" | "pass_through_endpoint" | "anthropic_messages" | "get_assistants" | "aget_assistants" | "create_assistants" | "acreate_assistants" | "delete_assistant" | "adelete_assistant" | "acreate_thread" | "create_thread" | "aget_thread" | "get_thread" | "a_add_message" | "add_message" | "aget_messages" | "get_messages" | "arun_thread" | "run_thread" | "arun_thread_stream" | "run_thread_stream" | "afile_retrieve" | "file_retrieve" | "afile_delete" | "file_delete" | "afile_list" | "file_list" | "acreate_file" | "create_file" | "afile_content" | "file_content" | "create_fine_tuning_job" | "acreate_fine_tuning_job" | "create_video" | "acreate_video" | "avideo_retrieve" | "video_retrieve" | "avideo_content" | "video_content" | "video_remix" | "avideo_remix" | "video_list" | "avideo_list" | "video_retrieve_job" | "avideo_retrieve_job" | "video_delete" | "avideo_delete" | "video_create_character" | "avideo_create_character" | "video_get_character" | "avideo_get_character" | "video_edit" | "avideo_edit" | "video_extension" | "avideo_extension" | "vector_store_file_create" | "avector_store_file_create" | "vector_store_file_list" | "avector_store_file_list" | "vector_store_file_retrieve" | "avector_store_file_retrieve" | "vector_store_file_content" | "avector_store_file_content" | "vector_store_file_update" | "avector_store_file_update" | "vector_store_file_delete" | "avector_store_file_delete" | "vector_store_create" | "avector_store_create" | "vector_store_search" | "avector_store_search" | "create_container" | "acreate_container" | "list_containers" | "alist_containers" | "retrieve_container" | "aretrieve_container" | "delete_container" | "adelete_container" | "list_container_files" | "alist_container_files" | "upload_container_file" | "aupload_container_file" | "create_sandbox" | "acreate_sandbox" | "delete_sandbox" | "adelete_sandbox" | "run_code" | "arun_code" | "code_interpreter_tool" | "acode_interpreter_tool" | "acancel_fine_tuning_job" | "cancel_fine_tuning_job" | "alist_fine_tuning_jobs" | "list_fine_tuning_jobs" | "aretrieve_fine_tuning_job" | "retrieve_fine_tuning_job" | "responses" | "aresponses" | "alist_input_items" | "llm_passthrough_route" | "allm_passthrough_route" | "generate_content" | "agenerate_content" | "generate_content_stream" | "agenerate_content_stream" | "ocr" | "aocr" | "call_mcp_tool" | "list_mcp_tools" | "asend_message" | "send_message" | "acreate_skill";
+        CallTypes: "embedding" | "aembedding" | "completion" | "acompletion" | "atext_completion" | "text_completion" | "image_generation" | "aimage_generation" | "image_edit" | "aimage_edit" | "moderation" | "amoderation" | "atranscription" | "transcription" | "aspeech" | "speech" | "rerank" | "arerank" | "search" | "asearch" | "_arealtime" | "_aresponses_websocket" | "create_batch" | "acreate_batch" | "aretrieve_batch" | "retrieve_batch" | "acancel_batch" | "cancel_batch" | "pass_through_endpoint" | "anthropic_messages" | "get_assistants" | "aget_assistants" | "create_assistants" | "acreate_assistants" | "delete_assistant" | "adelete_assistant" | "acreate_thread" | "create_thread" | "aget_thread" | "get_thread" | "a_add_message" | "add_message" | "aget_messages" | "get_messages" | "arun_thread" | "run_thread" | "arun_thread_stream" | "run_thread_stream" | "afile_retrieve" | "file_retrieve" | "afile_delete" | "file_delete" | "afile_list" | "file_list" | "acreate_file" | "create_file" | "afile_content" | "file_content" | "create_fine_tuning_job" | "acreate_fine_tuning_job" | "create_video" | "acreate_video" | "avideo_retrieve" | "video_retrieve" | "avideo_content" | "video_content" | "video_remix" | "avideo_remix" | "video_list" | "avideo_list" | "video_retrieve_job" | "avideo_retrieve_job" | "video_delete" | "avideo_delete" | "video_create_character" | "avideo_create_character" | "video_get_character" | "avideo_get_character" | "video_edit" | "avideo_edit" | "video_extension" | "avideo_extension" | "vector_store_file_create" | "avector_store_file_create" | "vector_store_file_list" | "avector_store_file_list" | "vector_store_file_retrieve" | "avector_store_file_retrieve" | "vector_store_file_content" | "avector_store_file_content" | "vector_store_file_update" | "avector_store_file_update" | "vector_store_file_delete" | "avector_store_file_delete" | "vector_store_create" | "avector_store_create" | "vector_store_search" | "avector_store_search" | "create_interaction" | "acreate_interaction" | "create_container" | "acreate_container" | "list_containers" | "alist_containers" | "retrieve_container" | "aretrieve_container" | "delete_container" | "adelete_container" | "list_container_files" | "alist_container_files" | "upload_container_file" | "aupload_container_file" | "create_sandbox" | "acreate_sandbox" | "delete_sandbox" | "adelete_sandbox" | "run_code" | "arun_code" | "code_interpreter_tool" | "acode_interpreter_tool" | "acancel_fine_tuning_job" | "cancel_fine_tuning_job" | "alist_fine_tuning_jobs" | "list_fine_tuning_jobs" | "aretrieve_fine_tuning_job" | "retrieve_fine_tuning_job" | "responses" | "aresponses" | "alist_input_items" | "llm_passthrough_route" | "allm_passthrough_route" | "generate_content" | "agenerate_content" | "generate_content_stream" | "agenerate_content_stream" | "ocr" | "aocr" | "call_mcp_tool" | "list_mcp_tools" | "asend_message" | "send_message" | "acreate_skill";
         /** CallbackDelete */
         CallbackDelete: {
             /** Callback Name */

From 59d4e52a3d2b5e088af0e894e34bbd0ed5fbfe9a Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 14 Jul 2026 20:05:33 -0700
Subject: [PATCH 03/93] fix(interactions): bill background interactions once
 completed via cost polling

---
 litellm/constants.py                          |  11 ++
 .../interactions/background_cost_polling.py   | 131 +++++++++++++
 litellm/interactions/main.py                  |   9 +
 litellm/litellm_core_utils/litellm_logging.py |  27 ++-
 .../proxy/hooks/proxy_track_cost_callback.py  |  12 ++
 .../credential_migration.py                   |  73 ++-----
 .../test_background_cost_polling.py           | 184 ++++++++++++++++++
 .../test_litellm_logging.py                   |  59 +++++-
 .../hooks/test_proxy_track_cost_callback.py   |  43 ++++
 tests/test_litellm/test_cost_calculator.py    |  29 +++
 10 files changed, 519 insertions(+), 59 deletions(-)
 create mode 100644 litellm/interactions/background_cost_polling.py
 create mode 100644 tests/test_litellm/interactions/test_background_cost_polling.py

diff --git a/litellm/constants.py b/litellm/constants.py
index 715d57e594d..be880b72854 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -1457,6 +1457,17 @@ STALE_OBJECT_CLEANUP_BATCH_SIZE = max(1, int(os.getenv("STALE_OBJECT_CLEANUP_BAT
 # installations with large numbers of stale managed objects).
 _batch_polling_env = os.getenv("PROXY_BATCH_POLLING_ENABLED", "true").lower()
 PROXY_BATCH_POLLING_ENABLED = _batch_polling_env == "true"
+BACKGROUND_INTERACTION_COST_POLL_INITIAL_INTERVAL_SECONDS = float(
+    os.getenv("BACKGROUND_INTERACTION_COST_POLL_INITIAL_INTERVAL_SECONDS", 5)
+)
+BACKGROUND_INTERACTION_COST_POLL_MAX_INTERVAL_SECONDS = float(
+    os.getenv("BACKGROUND_INTERACTION_COST_POLL_MAX_INTERVAL_SECONDS", 60)
+)
+BACKGROUND_INTERACTION_COST_POLL_TIMEOUT_SECONDS = float(
+    os.getenv("BACKGROUND_INTERACTION_COST_POLL_TIMEOUT_SECONDS", 3600)
+)
+_background_interaction_cost_polling_env = os.getenv("BACKGROUND_INTERACTION_COST_POLLING_ENABLED", "true").lower()
+BACKGROUND_INTERACTION_COST_POLLING_ENABLED = _background_interaction_cost_polling_env == "true"
 PROXY_BUDGET_RESCHEDULER_MAX_TIME = int(os.getenv("PROXY_BUDGET_RESCHEDULER_MAX_TIME", 605))
 PROXY_BATCH_WRITE_AT = int(os.getenv("PROXY_BATCH_WRITE_AT", 10))  # in seconds, increased from 10
 
diff --git a/litellm/interactions/background_cost_polling.py b/litellm/interactions/background_cost_polling.py
new file mode 100644
index 00000000000..fefbf8715cb
--- /dev/null
+++ b/litellm/interactions/background_cost_polling.py
@@ -0,0 +1,131 @@
+"""
+Cost tracking for background interactions.
+
+A create request with ``background=true`` returns ``in_progress`` with no
+usage block, and GET polls are deliberately never billed (billing them would
+double-charge every poll; the GET response also does not echo ``background``,
+so a poll cannot be told apart from a re-fetch of an already-billed
+interaction). The create call is therefore the only place that can own
+billing: it schedules a poll task that fetches the interaction until it
+reaches a terminal status and logs the final usage as a single success event
+attributed to the original request.
+"""
+
+import asyncio
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Any, Awaitable, Callable, Iterator, Optional
+
+from litellm._logging import verbose_logger
+from litellm.constants import (
+    BACKGROUND_INTERACTION_COST_POLL_INITIAL_INTERVAL_SECONDS,
+    BACKGROUND_INTERACTION_COST_POLL_MAX_INTERVAL_SECONDS,
+    BACKGROUND_INTERACTION_COST_POLL_TIMEOUT_SECONDS,
+    BACKGROUND_INTERACTION_COST_POLLING_ENABLED,
+)
+from litellm.types.interactions import InteractionsAPIResponse
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+
+_TERMINAL_STATUSES = frozenset({"completed", "failed", "cancelled", "incomplete", "budget_exceeded"})
+
+
+@dataclass(frozen=True, slots=True)
+class BackgroundInteractionPollContext:
+    interaction_id: str
+    custom_llm_provider: str
+    logging_obj: "LiteLLMLoggingObj"
+    api_key: Optional[str] = None
+    api_base: Optional[str] = None
+    initial_interval_seconds: float = BACKGROUND_INTERACTION_COST_POLL_INITIAL_INTERVAL_SECONDS
+    max_interval_seconds: float = BACKGROUND_INTERACTION_COST_POLL_MAX_INTERVAL_SECONDS
+    timeout_seconds: float = BACKGROUND_INTERACTION_COST_POLL_TIMEOUT_SECONDS
+
+
+FetchInteraction = Callable[[BackgroundInteractionPollContext], Awaitable[InteractionsAPIResponse]]
+
+
+async def _fetch_interaction(context: BackgroundInteractionPollContext) -> InteractionsAPIResponse:
+    from litellm.interactions import aget
+
+    return await aget(
+        interaction_id=context.interaction_id,
+        custom_llm_provider=context.custom_llm_provider,
+        **{"api_key": context.api_key, "api_base": context.api_base, "no-log": True},
+    )
+
+
+def _poll_intervals(initial: float, maximum: float, timeout: float) -> Iterator[float]:
+    elapsed = 0.0
+    interval = initial
+    while elapsed + interval <= timeout:
+        yield interval
+        elapsed += interval
+        interval = min(interval * 2, maximum)
+
+
+async def poll_and_log_background_interaction_cost(
+    context: BackgroundInteractionPollContext,
+    fetch_interaction: FetchInteraction = _fetch_interaction,
+) -> None:
+    for interval in _poll_intervals(
+        initial=context.initial_interval_seconds,
+        maximum=context.max_interval_seconds,
+        timeout=context.timeout_seconds,
+    ):
+        await asyncio.sleep(interval)
+        try:
+            response = await fetch_interaction(context)
+        except Exception as e:  # noqa: BLE001  # any fetch error must not kill the billing poll loop
+            verbose_logger.debug(
+                "Background interaction cost poll for %s failed, will retry: %s",
+                context.interaction_id,
+                e,
+            )
+            continue
+        if response.status not in _TERMINAL_STATUSES:
+            continue
+        if response.usage is not None:
+            await context.logging_obj.async_log_background_interaction_completion(result=response)
+        return
+    verbose_logger.warning(
+        "Gave up cost polling for background interaction %s after %ss; its usage will not be tracked",
+        context.interaction_id,
+        context.timeout_seconds,
+    )
+
+
+_ACTIVE_POLL_TASKS: set["asyncio.Task[None]"] = set()  # mutable-ok: asyncio requires strong refs to running tasks
+
+
+def maybe_schedule_background_interaction_cost_polling(
+    response: Any,
+    create_kwargs: dict[str, Any],
+    custom_llm_provider: str,
+) -> Optional["asyncio.Task[None]"]:
+    from litellm.litellm_core_utils.litellm_logging import Logging
+
+    if not BACKGROUND_INTERACTION_COST_POLLING_ENABLED:
+        return None
+    if not isinstance(response, InteractionsAPIResponse):
+        return None
+    if response.status != "in_progress" or not response.id:
+        return None
+    logging_obj = create_kwargs.get("litellm_logging_obj")
+    if not isinstance(logging_obj, Logging):
+        return None
+    try:
+        asyncio.get_running_loop()
+    except RuntimeError:
+        return None
+    context = BackgroundInteractionPollContext(
+        interaction_id=response.id,
+        custom_llm_provider=custom_llm_provider,
+        logging_obj=logging_obj,
+        api_key=create_kwargs.get("api_key"),
+        api_base=create_kwargs.get("api_base"),
+    )
+    task = asyncio.create_task(poll_and_log_background_interaction_cost(context))
+    _ACTIVE_POLL_TASKS.add(task)
+    task.add_done_callback(_ACTIVE_POLL_TASKS.discard)
+    return task
diff --git a/litellm/interactions/main.py b/litellm/interactions/main.py
index 8634269ee94..5a0ea9280b2 100644
--- a/litellm/interactions/main.py
+++ b/litellm/interactions/main.py
@@ -39,6 +39,9 @@ from typing import Any, AsyncIterator, Coroutine, Dict, Iterator, List, Optional
 import httpx
 
 import litellm
+from litellm.interactions.background_cost_polling import (
+    maybe_schedule_background_interaction_cost_polling,
+)
 from litellm.interactions.http_handler import interactions_http_handler
 from litellm.interactions.utils import (
     InteractionsAPIRequestUtils,
@@ -170,6 +173,12 @@ async def acreate(
         else:
             response = init_response
 
+        maybe_schedule_background_interaction_cost_polling(
+            response=response,
+            create_kwargs=kwargs,
+            custom_llm_provider=custom_llm_provider,
+        )
+
         return response  # type: ignore
     except Exception as e:
         raise litellm.exception_type(
diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index 94ee595a169..ac6334bea76 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -1895,7 +1895,11 @@ class Logging(LiteLLMLoggingBaseClass):
             or isinstance(logging_result, FineTuningJob)
             or isinstance(logging_result, LiteLLMBatch)
             or isinstance(logging_result, ResponsesAPIResponse)
-            or (isinstance(logging_result, InteractionsAPIResponse) and self._is_interactions_create_call_type())
+            or (
+                isinstance(logging_result, InteractionsAPIResponse)
+                and logging_result.usage is not None
+                and self._is_interactions_create_call_type()
+            )
             or isinstance(logging_result, OpenAIFileObject)
             or isinstance(logging_result, LiteLLMRealtimeStreamLoggingObject)
             or isinstance(logging_result, OpenAIModerationResponse)
@@ -1921,6 +1925,13 @@ class Logging(LiteLLMLoggingBaseClass):
         interaction. The proxy sets ``call_type`` from its route_type
         (``create_interaction``/``acreate_interaction``); the SDK sets it from
         the decorated function name (``create``/``acreate``).
+
+        Recognition additionally requires a usage block (checked at the call
+        site): a ``background=true`` create returns ``in_progress`` without
+        usage, and billing it would write a $0 spend log under the interaction
+        id that collides with the row the background poll task writes once the
+        interaction completes (see
+        ``litellm.interactions.background_cost_polling``).
         """
         return self.call_type in (
             CallTypes.create_interaction.value,
@@ -1929,6 +1940,20 @@ class Logging(LiteLLMLoggingBaseClass):
             "acreate",
         )
 
+    async def async_log_background_interaction_completion(
+        self,
+        result: InteractionsAPIResponse,
+    ) -> None:
+        """
+        Log the terminal result of a background interaction as a fresh success
+        event. The create request already ran success logging for its
+        ``in_progress`` response (no usage, so no cost was tracked); clearing
+        the dedup flag lets the completed result flow through cost calculation
+        and spend tracking exactly once, spanning create to completion.
+        """
+        self.model_call_details.pop("has_logged_async_success", None)
+        await self.async_success_handler(result=result)
+
     def _flush_passthrough_collected_chunks_helper(
         self,
         raw_bytes: List[bytes],
diff --git a/litellm/proxy/hooks/proxy_track_cost_callback.py b/litellm/proxy/hooks/proxy_track_cost_callback.py
index b839426fcda..6359eae0fa4 100644
--- a/litellm/proxy/hooks/proxy_track_cost_callback.py
+++ b/litellm/proxy/hooks/proxy_track_cost_callback.py
@@ -279,6 +279,12 @@ class _ProxyDBLogger(CustomLogger):
                     await _release_budget_reservation(budget_reservation=budget_reservation)
             else:
                 await _release_budget_reservation(budget_reservation=budget_reservation)
+                if _is_unbilled_in_progress_interaction(completion_response):
+                    verbose_proxy_logger.debug(
+                        "Cost tracking deferred for in-progress background interaction; "
+                        "a poll task logs the final usage once it completes"
+                    )
+                    return
                 # Non-model call types (health checks, afile_delete) have no model or standard_logging_object.
                 # Use .get() for "stream" to avoid KeyError on health checks.
                 # WS session wrappers (_aresponses_websocket, _arealtime) also reach here with
@@ -418,6 +424,12 @@ def _write_spend_metadata_to_kwargs(kwargs: dict, metadata: dict) -> None:
                     bucket[key] = value
 
 
+def _is_unbilled_in_progress_interaction(completion_response: Any) -> bool:
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    return isinstance(completion_response, InteractionsAPIResponse) and completion_response.usage is None
+
+
 def _should_track_cost_callback(
     user_api_key: Optional[str],
     user_id: Optional[str],
diff --git a/litellm/proxy/management_endpoints/credential_migration.py b/litellm/proxy/management_endpoints/credential_migration.py
index 4d51295f8dc..6f79a39c883 100644
--- a/litellm/proxy/management_endpoints/credential_migration.py
+++ b/litellm/proxy/management_endpoints/credential_migration.py
@@ -130,9 +130,7 @@ def classify_value(value: object, key: str = "scan") -> ValueClass:
         return "plaintext"
     if value.startswith(_V2_GCM_PREFIX):
         return "migrated"
-    decrypted = decrypt_value_helper(
-        value=value, key=key, exception_type="debug", return_original_value=False
-    )
+    decrypted = decrypt_value_helper(value=value, key=key, exception_type="debug", return_original_value=False)
     if decrypted is None:
         # Did not decrypt under nacl and has no v2 marker: legacy plaintext.
         return "plaintext"
@@ -151,9 +149,7 @@ def reencrypt_value(value: object, key: str = "migrate") -> object:
         return value
     if value.startswith(_V2_GCM_PREFIX):
         return value  # idempotent: already migrated
-    decrypted = decrypt_value_helper(
-        value=value, key=key, exception_type="debug", return_original_value=False
-    )
+    decrypted = decrypt_value_helper(value=value, key=key, exception_type="debug", return_original_value=False)
     if decrypted is None:
         # Either legacy plaintext (no ciphertext to migrate) or corrupt. Either
         # way, do not overwrite — preserve the value as stored.
@@ -161,9 +157,7 @@ def reencrypt_value(value: object, key: str = "migrate") -> object:
     return encrypt_value_helper(decrypted)
 
 
-def reencrypt_selective_dict(
-    data: dict[str, object], sensitive_keys: list[str]
-) -> dict[str, object]:
+def reencrypt_selective_dict(data: dict[str, object], sensitive_keys: list[str]) -> dict[str, object]:
     """Return a copy of ``data`` with only ``sensitive_keys`` re-encrypted.
 
     Non-sensitive fields (e.g. ``base_url``, ``connection_id``) are left as-is.
@@ -212,9 +206,7 @@ async def _migrate_config_settings_row(
     dict with selected sensitive fields (vantage_settings / cloudzero_settings).
     """
     report = LocationReport(location=param_name)
-    record = await prisma_client.db.litellm_config.find_unique(
-        where={"param_name": param_name}
-    )
+    record = await prisma_client.db.litellm_config.find_unique(where={"param_name": param_name})
     if record is None or record.param_value is None:
         return report
 
@@ -266,9 +258,7 @@ async def _migrate_sso_config(prisma_client: object, dry_run: bool) -> LocationR
     every present string field.
     """
     report = LocationReport(location="sso_config")
-    record = await prisma_client.db.litellm_ssoconfig.find_unique(
-        where={"id": "sso_config"}
-    )
+    record = await prisma_client.db.litellm_ssoconfig.find_unique(where={"id": "sso_config"})
     if record is None or record.sso_settings is None:
         return report
 
@@ -344,9 +334,7 @@ async def _migrate_callback_vars_table(
     rows = await table.find_many()
     for row in rows or []:
         metadata = getattr(row, "metadata", None)
-        if not isinstance(metadata, dict) or (
-            "logging" not in metadata and "callback_settings" not in metadata
-        ):
+        if not isinstance(metadata, dict) or ("logging" not in metadata and "callback_settings" not in metadata):
             continue
 
         # Classify every callback-var value directly (strip the litellm_enc::
@@ -534,9 +522,7 @@ async def _scan_config_env_vars(prisma_client: object) -> LocationReport:
     """Scan the ``environment_variables`` config row (``param_value`` dict)."""
     report = LocationReport(location="config_environment_variables")
     try:
-        record = await prisma_client.db.litellm_config.find_unique(
-            where={"param_name": "environment_variables"}
-        )
+        record = await prisma_client.db.litellm_config.find_unique(where={"param_name": "environment_variables"})
     except Exception as e:  # pragma: no cover - defensive
         verbose_proxy_logger.debug("scan: config env vars unavailable: %s", str(e))
         return report
@@ -557,11 +543,7 @@ async def _scan_covered_tables(prisma_client: object) -> list[LocationReport]:
     """Read-only classification of every rotation-covered table. No writes."""
     reports: list[LocationReport] = []
     for location, db_attr, json_cols, scalar_cols in _COVERED_TABLE_SPECS:
-        reports.append(
-            await _scan_one_table(
-                prisma_client, location, db_attr, json_cols, scalar_cols
-            )
-        )
+        reports.append(await _scan_one_table(prisma_client, location, db_attr, json_cols, scalar_cols))
     reports.append(await _scan_config_env_vars(prisma_client))
     return reports
 
@@ -575,9 +557,7 @@ _VANTAGE_SENSITIVE = ["api_key", "integration_token"]
 _CLOUDZERO_SENSITIVE = ["api_key"]
 
 
-async def _migrate_covered_tables(
-    prisma_client: object, user_api_key_dict: object
-) -> list[LocationReport]:
+async def _migrate_covered_tables(prisma_client: object, user_api_key_dict: object) -> list[LocationReport]:
     """Re-encrypt the tables already covered by ``_rotate_master_key`` (model
     table, credentials, MCP credential/env tables, config environment_variables)
     by running that orchestrator in *same-key* mode. With the AES gate on, the
@@ -597,8 +577,7 @@ async def _migrate_covered_tables(
     current_key = _get_salt_key()
     if current_key is None:
         raise RuntimeError(
-            "Cannot migrate covered tables: no salt key / master key is set. "
-            "Set LITELLM_SALT_KEY before migrating."
+            "Cannot migrate covered tables: no salt key / master key is set. Set LITELLM_SALT_KEY before migrating."
         )
     await _rotate_master_key(
         prisma_client=cast("PrismaClient", prisma_client),
@@ -648,19 +627,9 @@ async def migrate_encryption(
 
     # Net-new walkers (items 3, 4, 11, 12, 13).
     report.add(await _migrate_callback_vars_table(prisma_client, "team", dry_run))
-    report.add(
-        await _migrate_callback_vars_table(prisma_client, "verification_token", dry_run)
-    )
-    report.add(
-        await _migrate_config_settings_row(
-            prisma_client, "vantage_settings", _VANTAGE_SENSITIVE, dry_run
-        )
-    )
-    report.add(
-        await _migrate_config_settings_row(
-            prisma_client, "cloudzero_settings", _CLOUDZERO_SENSITIVE, dry_run
-        )
-    )
+    report.add(await _migrate_callback_vars_table(prisma_client, "verification_token", dry_run))
+    report.add(await _migrate_config_settings_row(prisma_client, "vantage_settings", _VANTAGE_SENSITIVE, dry_run))
+    report.add(await _migrate_config_settings_row(prisma_client, "cloudzero_settings", _CLOUDZERO_SENSITIVE, dry_run))
     report.add(await _migrate_sso_config(prisma_client, dry_run))
 
     return report
@@ -683,20 +652,10 @@ async def check_encryption(prisma_client: object) -> MigrationReport:
 
     # Net-new walker locations, in dry-run (read-only) mode.
     report.add(await _migrate_callback_vars_table(prisma_client, "team", dry_run=True))
+    report.add(await _migrate_callback_vars_table(prisma_client, "verification_token", dry_run=True))
+    report.add(await _migrate_config_settings_row(prisma_client, "vantage_settings", _VANTAGE_SENSITIVE, dry_run=True))
     report.add(
-        await _migrate_callback_vars_table(
-            prisma_client, "verification_token", dry_run=True
-        )
-    )
-    report.add(
-        await _migrate_config_settings_row(
-            prisma_client, "vantage_settings", _VANTAGE_SENSITIVE, dry_run=True
-        )
-    )
-    report.add(
-        await _migrate_config_settings_row(
-            prisma_client, "cloudzero_settings", _CLOUDZERO_SENSITIVE, dry_run=True
-        )
+        await _migrate_config_settings_row(prisma_client, "cloudzero_settings", _CLOUDZERO_SENSITIVE, dry_run=True)
     )
     report.add(await _migrate_sso_config(prisma_client, dry_run=True))
     return report
diff --git a/tests/test_litellm/interactions/test_background_cost_polling.py b/tests/test_litellm/interactions/test_background_cost_polling.py
new file mode 100644
index 00000000000..aac97826b02
--- /dev/null
+++ b/tests/test_litellm/interactions/test_background_cost_polling.py
@@ -0,0 +1,184 @@
+import asyncio
+import time
+
+import pytest
+
+from litellm.interactions.background_cost_polling import (
+    BackgroundInteractionPollContext,
+    maybe_schedule_background_interaction_cost_polling,
+    poll_and_log_background_interaction_cost,
+)
+from litellm.litellm_core_utils.litellm_logging import Logging as LitellmLogging
+from litellm.types.interactions import InteractionsAPIResponse
+
+USAGE_BLOCK = {
+    "total_tokens": 175,
+    "total_input_tokens": 100,
+    "input_tokens_by_modality": [{"modality": "text", "tokens": 100}],
+    "total_cached_tokens": 0,
+    "total_output_tokens": 50,
+    "output_tokens_by_modality": [{"modality": "text", "tokens": 50}],
+    "total_tool_use_tokens": 0,
+    "total_thought_tokens": 25,
+}
+
+
+def _logging_obj(call_type: str = "acreate_interaction") -> LitellmLogging:
+    logging_obj = LitellmLogging(
+        model="gemini-2.5-flash",
+        messages=[],
+        stream=False,
+        call_type=call_type,
+        start_time=time.time(),
+        litellm_call_id="bg-interactions-call-id",
+        function_id="bg-interactions-fn-id",
+    )
+    logging_obj.update_environment_variables(
+        litellm_params={},
+        optional_params={},
+        model="gemini-2.5-flash",
+        custom_llm_provider="gemini",
+        input="hi",
+    )
+    return logging_obj
+
+
+def _context(logging_obj: LitellmLogging, timeout_seconds: float = 1.0) -> BackgroundInteractionPollContext:
+    return BackgroundInteractionPollContext(
+        interaction_id="interactions/bg-abc",
+        custom_llm_provider="gemini",
+        logging_obj=logging_obj,
+        initial_interval_seconds=0.001,
+        max_interval_seconds=0.002,
+        timeout_seconds=timeout_seconds,
+    )
+
+
+def _response(status: str, with_usage: bool) -> InteractionsAPIResponse:
+    return InteractionsAPIResponse(
+        id="interactions/bg-abc",
+        model="gemini-2.5-flash",
+        status=status,
+        steps=[],
+        usage=dict(USAGE_BLOCK) if with_usage else None,
+    )
+
+
+def _fetch_sequence(*responses):
+    remaining = list(responses)
+    calls = []
+
+    async def fetch(context):
+        calls.append(context.interaction_id)
+        item = remaining.pop(0) if len(remaining) > 1 else remaining[0]
+        if isinstance(item, Exception):
+            raise item
+        return item
+
+    return fetch, calls
+
+
+@pytest.mark.asyncio
+async def test_poller_bills_once_when_interaction_completes():
+    logging_obj = _logging_obj()
+    fetch, calls = _fetch_sequence(
+        _response("in_progress", with_usage=False),
+        _response("completed", with_usage=True),
+    )
+
+    await poll_and_log_background_interaction_cost(_context(logging_obj), fetch_interaction=fetch)
+
+    assert len(calls) == 2
+    assert logging_obj.model_call_details["response_cost"] > 0
+    assert logging_obj.model_call_details["standard_logging_object"]["total_tokens"] == 175
+
+
+@pytest.mark.asyncio
+async def test_poller_stops_without_billing_on_terminal_status_without_usage():
+    logging_obj = _logging_obj()
+    fetch, calls = _fetch_sequence(_response("failed", with_usage=False))
+
+    await poll_and_log_background_interaction_cost(_context(logging_obj), fetch_interaction=fetch)
+
+    assert len(calls) == 1
+    assert logging_obj.model_call_details.get("response_cost") is None
+
+
+@pytest.mark.asyncio
+async def test_poller_gives_up_after_timeout_without_billing():
+    logging_obj = _logging_obj()
+    fetch, calls = _fetch_sequence(_response("in_progress", with_usage=False))
+
+    await poll_and_log_background_interaction_cost(
+        _context(logging_obj, timeout_seconds=0.01),
+        fetch_interaction=fetch,
+    )
+
+    assert len(calls) >= 2
+    assert logging_obj.model_call_details.get("response_cost") is None
+
+
+@pytest.mark.asyncio
+async def test_poller_retries_after_fetch_error_and_still_bills():
+    logging_obj = _logging_obj()
+    fetch, calls = _fetch_sequence(
+        RuntimeError("transient network error"),
+        _response("completed", with_usage=True),
+    )
+
+    await poll_and_log_background_interaction_cost(_context(logging_obj), fetch_interaction=fetch)
+
+    assert len(calls) == 2
+    assert logging_obj.model_call_details["response_cost"] > 0
+
+
+@pytest.mark.asyncio
+async def test_schedule_creates_poll_task_for_in_progress_create():
+    logging_obj = _logging_obj()
+    task = maybe_schedule_background_interaction_cost_polling(
+        response=_response("in_progress", with_usage=False),
+        create_kwargs={"litellm_logging_obj": logging_obj},
+        custom_llm_provider="gemini",
+    )
+
+    assert isinstance(task, asyncio.Task)
+    task.cancel()
+    with pytest.raises(asyncio.CancelledError):
+        await task
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "response,create_kwargs",
+    [
+        (_response("completed", with_usage=True), {"litellm_logging_obj": "placeholder"}),
+        (_response("in_progress", with_usage=False), {}),
+        ("not a response", {"litellm_logging_obj": "placeholder"}),
+    ],
+)
+async def test_schedule_skips_non_pollable_results(response, create_kwargs):
+    if create_kwargs.get("litellm_logging_obj") == "placeholder":
+        create_kwargs = {"litellm_logging_obj": _logging_obj()}
+
+    task = maybe_schedule_background_interaction_cost_polling(
+        response=response,
+        create_kwargs=create_kwargs,
+        custom_llm_provider="gemini",
+    )
+
+    assert task is None
+
+
+@pytest.mark.asyncio
+async def test_schedule_respects_kill_switch(monkeypatch):
+    import litellm.interactions.background_cost_polling as module
+
+    monkeypatch.setattr(module, "BACKGROUND_INTERACTION_COST_POLLING_ENABLED", False)
+
+    task = maybe_schedule_background_interaction_cost_polling(
+        response=_response("in_progress", with_usage=False),
+        create_kwargs={"litellm_logging_obj": _logging_obj()},
+        custom_llm_provider="gemini",
+    )
+
+    assert task is None
diff --git a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
index 2bf9f54d7c9..4d8b19150f7 100644
--- a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
+++ b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
@@ -3812,10 +3812,67 @@ def test_interactions_response_is_recognized_for_logging(call_type):
     from litellm.types.interactions import InteractionsAPIResponse
 
     logging_obj = _interactions_logging_obj(stream=False, call_type=call_type)
-    response = InteractionsAPIResponse(id="interactions/abc", model="gemini-2.5-flash", status="completed")
+    response = InteractionsAPIResponse(
+        id="interactions/abc",
+        model="gemini-2.5-flash",
+        status="completed",
+        usage=dict(INTERACTIONS_USAGE_BLOCK),
+    )
     assert logging_obj._is_recognized_call_type_for_logging(logging_result=response) is True
 
 
+@pytest.mark.parametrize("call_type", ["acreate", "acreate_interaction"])
+def test_in_progress_background_create_is_not_billed(call_type):
+    import datetime as dt
+
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    logging_obj = _interactions_logging_obj(stream=False, call_type=call_type)
+    response = InteractionsAPIResponse(id="interactions/abc", model="gemini-2.5-flash", status="in_progress")
+
+    assert logging_obj._is_recognized_call_type_for_logging(logging_result=response) is False
+
+    logging_obj._success_handler_helper_fn(
+        result=response,
+        start_time=dt.datetime.now(),
+        end_time=dt.datetime.now(),
+        cache_hit=False,
+    )
+
+    assert logging_obj.model_call_details.get("response_cost") is None
+    assert logging_obj.model_call_details.get("standard_logging_object") is None
+
+
+@pytest.mark.asyncio
+async def test_background_interaction_completion_rebills_after_in_progress_success():
+    import datetime as dt
+
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    logging_obj = _interactions_logging_obj(stream=False)
+    in_progress = InteractionsAPIResponse(id="interactions/abc", model="gemini-2.5-flash", status="in_progress")
+    await logging_obj.async_success_handler(
+        result=in_progress,
+        start_time=dt.datetime.now(),
+        end_time=dt.datetime.now(),
+    )
+
+    assert logging_obj.model_call_details.get("response_cost") is None
+    assert logging_obj.should_run_logging(event_type="async_success") is False
+
+    completed = InteractionsAPIResponse(
+        id="interactions/abc",
+        model="gemini-2.5-flash",
+        status="completed",
+        steps=[],
+        usage=dict(INTERACTIONS_USAGE_BLOCK),
+    )
+    await logging_obj.async_log_background_interaction_completion(result=completed)
+
+    assert logging_obj.model_call_details["response_cost"] > 0
+    assert logging_obj.model_call_details["standard_logging_object"]["total_tokens"] == 175
+
+
 @pytest.mark.parametrize(
     "call_type",
     ["aget", "get", "aget_interaction", "adelete_interaction", "acancel_interaction"],
diff --git a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
index f289148101a..02a586a3dcc 100644
--- a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
+++ b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
@@ -604,6 +604,49 @@ async def test_track_cost_callback_skips_when_no_standard_logging_object():
         mock_proxy_logging.failed_tracking_alert.assert_not_called()
 
 
+@pytest.mark.asyncio
+async def test_track_cost_callback_defers_in_progress_background_interaction():
+    """
+    A background=true interaction create returns in_progress with no usage
+    block, so its success event has a model but no standard_logging_object.
+    The callback must skip quietly (billing happens later via the background
+    poll task) instead of raising 'Cost tracking failed' and alerting.
+    """
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    logger = _ProxyDBLogger()
+
+    kwargs = {
+        "call_type": "acreate_interaction",
+        "model": "gemini/gemini-3-flash-preview",
+        "litellm_call_id": "test-call-id",
+        "litellm_params": {},
+        "stream": False,
+    }
+    in_progress_response = InteractionsAPIResponse(
+        id="interactions/bg-abc",
+        model="gemini-3-flash-preview",
+        status="in_progress",
+    )
+
+    with patch(
+        "litellm.proxy.proxy_server.proxy_logging_obj",
+    ) as mock_proxy_logging:
+        mock_proxy_logging.failed_tracking_alert = AsyncMock()
+        mock_proxy_logging.db_spend_update_writer = MagicMock()
+        mock_proxy_logging.db_spend_update_writer.update_database = AsyncMock()
+
+        await logger._PROXY_track_cost_callback(
+            kwargs=kwargs,
+            completion_response=in_progress_response,
+            start_time=datetime.now(),
+            end_time=datetime.now(),
+        )
+
+        mock_proxy_logging.db_spend_update_writer.update_database.assert_not_called()
+        mock_proxy_logging.failed_tracking_alert.assert_not_called()
+
+
 @pytest.mark.asyncio
 async def test_async_post_call_failure_hook_propagates_trace_id_from_logging_obj():
     """
diff --git a/tests/test_litellm/test_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py
index c76439e5ad1..42fef833944 100644
--- a/tests/test_litellm/test_cost_calculator.py
+++ b/tests/test_litellm/test_cost_calculator.py
@@ -3512,3 +3512,32 @@ def test_completion_cost_bills_interactions_api_response():
     )
     assert cost == pytest.approx(expected)
     assert cost > 0
+
+
+def test_completion_cost_bills_interactions_video_output_at_video_rate():
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    model_info = litellm.get_model_info(model="gemini-omni-flash-preview", custom_llm_provider="gemini")
+    video_tokens = 5792 * 8
+    response = InteractionsAPIResponse(
+        id="interactions/video123",
+        model="gemini-omni-flash-preview",
+        status="completed",
+        steps=[],
+        usage={
+            "total_tokens": 10 + video_tokens,
+            "total_input_tokens": 10,
+            "input_tokens_by_modality": [{"modality": "text", "tokens": 10}],
+            "total_cached_tokens": 0,
+            "total_output_tokens": video_tokens,
+            "output_tokens_by_modality": [{"modality": "video", "tokens": video_tokens}],
+            "total_tool_use_tokens": 0,
+            "total_thought_tokens": 0,
+        },
+    )
+
+    cost = completion_cost(completion_response=response, custom_llm_provider="gemini")
+
+    expected = 10 * model_info["input_cost_per_token"] + video_tokens * model_info["output_cost_per_video_token"]
+    assert model_info["output_cost_per_video_token"] != model_info["output_cost_per_token"]
+    assert cost == pytest.approx(expected)

From bbb156577245a9a27ae529276bcaa771e3d06266 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Wed, 15 Jul 2026 06:32:16 -0700
Subject: [PATCH 04/93] fix(interactions): hold budget reservation open until
 background interaction completes

---
 .../interactions/background_cost_polling.py   | 26 ++++++
 .../proxy/hooks/proxy_track_cost_callback.py  | 14 ++-
 .../test_background_cost_polling.py           | 56 +++++++++++-
 .../hooks/test_proxy_track_cost_callback.py   | 85 +++++++++++++++++++
 4 files changed, 176 insertions(+), 5 deletions(-)

diff --git a/litellm/interactions/background_cost_polling.py b/litellm/interactions/background_cost_polling.py
index fefbf8715cb..846b26f28b9 100644
--- a/litellm/interactions/background_cost_polling.py
+++ b/litellm/interactions/background_cost_polling.py
@@ -22,6 +22,7 @@ from litellm.constants import (
     BACKGROUND_INTERACTION_COST_POLL_TIMEOUT_SECONDS,
     BACKGROUND_INTERACTION_COST_POLLING_ENABLED,
 )
+from litellm.litellm_core_utils.core_helpers import get_litellm_metadata_from_kwargs
 from litellm.types.interactions import InteractionsAPIResponse
 
 if TYPE_CHECKING:
@@ -87,12 +88,37 @@ async def poll_and_log_background_interaction_cost(
             continue
         if response.usage is not None:
             await context.logging_obj.async_log_background_interaction_completion(result=response)
+        else:
+            await _release_open_budget_reservation(logging_obj=context.logging_obj)
         return
     verbose_logger.warning(
         "Gave up cost polling for background interaction %s after %ss; its usage will not be tracked",
         context.interaction_id,
         context.timeout_seconds,
     )
+    await _release_open_budget_reservation(logging_obj=context.logging_obj)
+
+
+async def _release_open_budget_reservation(logging_obj: "LiteLLMLoggingObj") -> None:
+    """
+    The proxy keeps the pre-call budget reservation open for an in-progress
+    background interaction so concurrent creates cannot stack past the budget.
+    The completion success event reconciles it to the actual cost; when the
+    interaction terminates without billable usage (or polling gives up), no
+    such event fires, so the poller must release the reservation here or the
+    spend counters stay pinned at the estimated cost.
+    """
+    metadata = get_litellm_metadata_from_kwargs(kwargs=logging_obj.model_call_details)
+    budget_reservation = metadata.get("user_api_key_budget_reservation")
+    if not isinstance(budget_reservation, dict):
+        return
+
+    from litellm.proxy.spend_tracking.budget_reservation import release_budget_reservation
+
+    try:
+        await release_budget_reservation(budget_reservation=budget_reservation)
+    except Exception:  # noqa: BLE001  # a failed release must not crash the poll task; counters expire via TTL
+        verbose_logger.exception("Failed to release budget reservation for an unbilled background interaction")
 
 
 _ACTIVE_POLL_TASKS: set["asyncio.Task[None]"] = set()  # mutable-ok: asyncio requires strong refs to running tasks
diff --git a/litellm/proxy/hooks/proxy_track_cost_callback.py b/litellm/proxy/hooks/proxy_track_cost_callback.py
index 6359eae0fa4..a645bb9929f 100644
--- a/litellm/proxy/hooks/proxy_track_cost_callback.py
+++ b/litellm/proxy/hooks/proxy_track_cost_callback.py
@@ -5,6 +5,7 @@ from typing import Any, List, Optional, Union, cast
 
 import litellm
 from litellm._logging import verbose_proxy_logger
+from litellm.constants import BACKGROUND_INTERACTION_COST_POLLING_ENABLED
 from litellm.integrations.custom_logger import CustomLogger
 from litellm.litellm_core_utils.core_helpers import (
     _get_parent_otel_span_from_kwargs,
@@ -278,13 +279,20 @@ class _ProxyDBLogger(CustomLogger):
                 elif budget_reservation is not None:
                     await _release_budget_reservation(budget_reservation=budget_reservation)
             else:
-                await _release_budget_reservation(budget_reservation=budget_reservation)
                 if _is_unbilled_in_progress_interaction(completion_response):
+                    if BACKGROUND_INTERACTION_COST_POLLING_ENABLED:
+                        verbose_proxy_logger.debug(
+                            "Cost tracking deferred for in-progress background interaction; "
+                            "the budget reservation stays open until the poll task logs the final usage"
+                        )
+                        return
+                    await _release_budget_reservation(budget_reservation=budget_reservation)
                     verbose_proxy_logger.debug(
-                        "Cost tracking deferred for in-progress background interaction; "
-                        "a poll task logs the final usage once it completes"
+                        "Background interaction cost polling is disabled; released the budget "
+                        "reservation for an in-progress interaction that will not be billed"
                     )
                     return
+                await _release_budget_reservation(budget_reservation=budget_reservation)
                 # Non-model call types (health checks, afile_delete) have no model or standard_logging_object.
                 # Use .get() for "stream" to avoid KeyError on health checks.
                 # WS session wrappers (_aresponses_websocket, _arealtime) also reach here with
diff --git a/tests/test_litellm/interactions/test_background_cost_polling.py b/tests/test_litellm/interactions/test_background_cost_polling.py
index aac97826b02..24abeec1053 100644
--- a/tests/test_litellm/interactions/test_background_cost_polling.py
+++ b/tests/test_litellm/interactions/test_background_cost_polling.py
@@ -1,5 +1,6 @@
 import asyncio
 import time
+from typing import Optional
 
 import pytest
 
@@ -23,7 +24,10 @@ USAGE_BLOCK = {
 }
 
 
-def _logging_obj(call_type: str = "acreate_interaction") -> LitellmLogging:
+def _logging_obj(
+    call_type: str = "acreate_interaction",
+    litellm_params: Optional[dict] = None,
+) -> LitellmLogging:
     logging_obj = LitellmLogging(
         model="gemini-2.5-flash",
         messages=[],
@@ -34,7 +38,7 @@ def _logging_obj(call_type: str = "acreate_interaction") -> LitellmLogging:
         function_id="bg-interactions-fn-id",
     )
     logging_obj.update_environment_variables(
-        litellm_params={},
+        litellm_params=litellm_params or {},
         optional_params={},
         model="gemini-2.5-flash",
         custom_llm_provider="gemini",
@@ -43,6 +47,14 @@ def _logging_obj(call_type: str = "acreate_interaction") -> LitellmLogging:
     return logging_obj
 
 
+def _reservation() -> dict:
+    return {"reserved_cost": 0.05, "entries": [], "finalized": False, "input_cost": 0.001}
+
+
+def _logging_obj_with_reservation(reservation: dict) -> LitellmLogging:
+    return _logging_obj(litellm_params={"metadata": {"user_api_key_budget_reservation": reservation}})
+
+
 def _context(logging_obj: LitellmLogging, timeout_seconds: float = 1.0) -> BackgroundInteractionPollContext:
     return BackgroundInteractionPollContext(
         interaction_id="interactions/bg-abc",
@@ -118,6 +130,46 @@ async def test_poller_gives_up_after_timeout_without_billing():
     assert logging_obj.model_call_details.get("response_cost") is None
 
 
+@pytest.mark.asyncio
+async def test_poller_releases_budget_reservation_when_interaction_ends_without_usage():
+    reservation = _reservation()
+    logging_obj = _logging_obj_with_reservation(reservation)
+    fetch, _ = _fetch_sequence(_response("failed", with_usage=False))
+
+    await poll_and_log_background_interaction_cost(_context(logging_obj), fetch_interaction=fetch)
+
+    assert reservation["finalized"] is True
+
+
+@pytest.mark.asyncio
+async def test_poller_releases_budget_reservation_on_timeout_give_up():
+    reservation = _reservation()
+    logging_obj = _logging_obj_with_reservation(reservation)
+    fetch, _ = _fetch_sequence(_response("in_progress", with_usage=False))
+
+    await poll_and_log_background_interaction_cost(
+        _context(logging_obj, timeout_seconds=0.01),
+        fetch_interaction=fetch,
+    )
+
+    assert reservation["finalized"] is True
+
+
+@pytest.mark.asyncio
+async def test_poller_leaves_reservation_reconciliation_to_the_completion_event():
+    reservation = _reservation()
+    logging_obj = _logging_obj_with_reservation(reservation)
+    fetch, _ = _fetch_sequence(
+        _response("in_progress", with_usage=False),
+        _response("completed", with_usage=True),
+    )
+
+    await poll_and_log_background_interaction_cost(_context(logging_obj), fetch_interaction=fetch)
+
+    assert logging_obj.model_call_details["response_cost"] > 0
+    assert reservation["finalized"] is False
+
+
 @pytest.mark.asyncio
 async def test_poller_retries_after_fetch_error_and_still_bills():
     logging_obj = _logging_obj()
diff --git a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
index 02a586a3dcc..725e7f22f7d 100644
--- a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
+++ b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
@@ -647,6 +647,91 @@ async def test_track_cost_callback_defers_in_progress_background_interaction():
         mock_proxy_logging.failed_tracking_alert.assert_not_called()
 
 
+def _in_progress_interaction_kwargs(reservation: dict) -> dict:
+    return {
+        "call_type": "acreate_interaction",
+        "model": "gemini/gemini-3-flash-preview",
+        "litellm_call_id": "test-call-id",
+        "litellm_params": {"metadata": {"user_api_key_budget_reservation": reservation}},
+        "stream": False,
+    }
+
+
+@pytest.mark.asyncio
+async def test_track_cost_callback_keeps_reservation_open_for_in_progress_background_interaction():
+    """
+    The pre-call budget reservation must stay open while a background
+    interaction is in flight, so concurrent creates cannot stack past the
+    budget; the poll task's completion event reconciles it to the actual cost.
+    """
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    logger = _ProxyDBLogger()
+    reservation = {"reserved_cost": 0.05, "entries": [], "finalized": False}
+    in_progress_response = InteractionsAPIResponse(
+        id="interactions/bg-abc",
+        model="gemini-3-flash-preview",
+        status="in_progress",
+    )
+
+    with patch(
+        "litellm.proxy.proxy_server.proxy_logging_obj",
+    ) as mock_proxy_logging:
+        mock_proxy_logging.failed_tracking_alert = AsyncMock()
+        mock_proxy_logging.db_spend_update_writer = MagicMock()
+        mock_proxy_logging.db_spend_update_writer.update_database = AsyncMock()
+
+        await logger._PROXY_track_cost_callback(
+            kwargs=_in_progress_interaction_kwargs(reservation),
+            completion_response=in_progress_response,
+            start_time=datetime.now(),
+            end_time=datetime.now(),
+        )
+
+        assert reservation["finalized"] is False
+        mock_proxy_logging.failed_tracking_alert.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_track_cost_callback_releases_reservation_for_in_progress_interaction_when_polling_disabled(
+    monkeypatch,
+):
+    """
+    With the poll task kill switch off nothing will ever reconcile the
+    reservation, so the callback must release it or the spend counters stay
+    pinned at the estimated cost forever.
+    """
+    import litellm.proxy.hooks.proxy_track_cost_callback as callback_module
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    monkeypatch.setattr(callback_module, "BACKGROUND_INTERACTION_COST_POLLING_ENABLED", False)
+
+    logger = _ProxyDBLogger()
+    reservation = {"reserved_cost": 0.05, "entries": [], "finalized": False}
+    in_progress_response = InteractionsAPIResponse(
+        id="interactions/bg-abc",
+        model="gemini-3-flash-preview",
+        status="in_progress",
+    )
+
+    with patch(
+        "litellm.proxy.proxy_server.proxy_logging_obj",
+    ) as mock_proxy_logging:
+        mock_proxy_logging.failed_tracking_alert = AsyncMock()
+        mock_proxy_logging.db_spend_update_writer = MagicMock()
+        mock_proxy_logging.db_spend_update_writer.update_database = AsyncMock()
+
+        await logger._PROXY_track_cost_callback(
+            kwargs=_in_progress_interaction_kwargs(reservation),
+            completion_response=in_progress_response,
+            start_time=datetime.now(),
+            end_time=datetime.now(),
+        )
+
+        assert reservation["finalized"] is True
+        mock_proxy_logging.failed_tracking_alert.assert_not_called()
+
+
 @pytest.mark.asyncio
 async def test_async_post_call_failure_hook_propagates_trace_id_from_logging_obj():
     """

From 194dca7dd0d67ef23795fc13668092af1e2a86ef Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Wed, 15 Jul 2026 07:15:50 -0700
Subject: [PATCH 05/93] fix(interactions): settle pending background
 interaction billing before delete

---
 .../interactions/background_cost_polling.py   |  91 ++++++++++++-
 litellm/interactions/main.py                  |   3 +
 .../test_background_cost_polling.py           | 123 ++++++++++++++++++
 3 files changed, 211 insertions(+), 6 deletions(-)

diff --git a/litellm/interactions/background_cost_polling.py b/litellm/interactions/background_cost_polling.py
index 846b26f28b9..ed30d2573bd 100644
--- a/litellm/interactions/background_cost_polling.py
+++ b/litellm/interactions/background_cost_polling.py
@@ -9,6 +9,16 @@ interaction). The create call is therefore the only place that can own
 billing: it schedules a poll task that fetches the interaction until it
 reaches a terminal status and logs the final usage as a single success event
 attributed to the original request.
+
+Deleting an interaction makes every subsequent poll fail, which would let a
+caller retrieve the completed output themselves and then delete it before the
+poll task settles, leaving the work unbilled and the budget reservation
+refunded at the poll timeout. ``adelete`` therefore settles any pending poll
+for the interaction before dispatching the delete: it fetches the current
+state with the create's credentials, bills it if it is terminal with usage,
+and releases the reservation otherwise. A settlement gate on the create's
+logging object makes the poll task and the delete path mutually exclusive, so
+the interaction is billed exactly once no matter who settles first.
 """
 
 import asyncio
@@ -65,6 +75,25 @@ def _poll_intervals(initial: float, maximum: float, timeout: float) -> Iterator[
         interval = min(interval * 2, maximum)
 
 
+_SETTLED_KEY = "background_interaction_settled"
+
+
+def _is_settled(logging_obj: "LiteLLMLoggingObj") -> bool:
+    return logging_obj.model_call_details.get(_SETTLED_KEY) is True
+
+
+def _claim_settlement(logging_obj: "LiteLLMLoggingObj") -> bool:
+    """
+    Exactly-once gate between the poll task and the delete-time settlement:
+    both run on the same event loop and neither awaits between reading and
+    setting the flag, so whichever claims first owns billing or release.
+    """
+    if _is_settled(logging_obj):
+        return False
+    logging_obj.model_call_details[_SETTLED_KEY] = True
+    return True
+
+
 async def poll_and_log_background_interaction_cost(
     context: BackgroundInteractionPollContext,
     fetch_interaction: FetchInteraction = _fetch_interaction,
@@ -75,6 +104,8 @@ async def poll_and_log_background_interaction_cost(
         timeout=context.timeout_seconds,
     ):
         await asyncio.sleep(interval)
+        if _is_settled(context.logging_obj):
+            return
         try:
             response = await fetch_interaction(context)
         except Exception as e:  # noqa: BLE001  # any fetch error must not kill the billing poll loop
@@ -86,11 +117,15 @@ async def poll_and_log_background_interaction_cost(
             continue
         if response.status not in _TERMINAL_STATUSES:
             continue
+        if not _claim_settlement(context.logging_obj):
+            return
         if response.usage is not None:
             await context.logging_obj.async_log_background_interaction_completion(result=response)
         else:
             await _release_open_budget_reservation(logging_obj=context.logging_obj)
         return
+    if not _claim_settlement(context.logging_obj):
+        return
     verbose_logger.warning(
         "Gave up cost polling for background interaction %s after %ss; its usage will not be tracked",
         context.interaction_id,
@@ -104,9 +139,10 @@ async def _release_open_budget_reservation(logging_obj: "LiteLLMLoggingObj") ->
     The proxy keeps the pre-call budget reservation open for an in-progress
     background interaction so concurrent creates cannot stack past the budget.
     The completion success event reconciles it to the actual cost; when the
-    interaction terminates without billable usage (or polling gives up), no
-    such event fires, so the poller must release the reservation here or the
-    spend counters stay pinned at the estimated cost.
+    interaction terminates without billable usage (or polling gives up, or it
+    is deleted before settling), no such event fires, so whoever claims the
+    settlement must release the reservation here or the spend counters stay
+    pinned at the estimated cost.
     """
     metadata = get_litellm_metadata_from_kwargs(kwargs=logging_obj.model_call_details)
     budget_reservation = metadata.get("user_api_key_budget_reservation")
@@ -121,7 +157,21 @@ async def _release_open_budget_reservation(logging_obj: "LiteLLMLoggingObj") ->
         verbose_logger.exception("Failed to release budget reservation for an unbilled background interaction")
 
 
-_ACTIVE_POLL_TASKS: set["asyncio.Task[None]"] = set()  # mutable-ok: asyncio requires strong refs to running tasks
+@dataclass(frozen=True, slots=True)
+class _ActiveBackgroundPoll:
+    task: "asyncio.Task[None]"
+    context: BackgroundInteractionPollContext
+
+
+_ACTIVE_POLLS: dict[
+    str, _ActiveBackgroundPoll
+] = {}  # mutable-ok: asyncio requires strong refs to running tasks, and delete settlement looks polls up by interaction id
+
+
+def _discard_poll(interaction_id: str, task: "asyncio.Task[None]") -> None:
+    entry = _ACTIVE_POLLS.get(interaction_id)
+    if entry is not None and entry.task is task:
+        del _ACTIVE_POLLS[interaction_id]
 
 
 def maybe_schedule_background_interaction_cost_polling(
@@ -152,6 +202,35 @@ def maybe_schedule_background_interaction_cost_polling(
         api_base=create_kwargs.get("api_base"),
     )
     task = asyncio.create_task(poll_and_log_background_interaction_cost(context))
-    _ACTIVE_POLL_TASKS.add(task)
-    task.add_done_callback(_ACTIVE_POLL_TASKS.discard)
+    _ACTIVE_POLLS[context.interaction_id] = _ActiveBackgroundPoll(task=task, context=context)
+    task.add_done_callback(
+        lambda finished, interaction_id=context.interaction_id: _discard_poll(interaction_id, finished)
+    )
     return task
+
+
+async def maybe_settle_background_interaction_before_delete(
+    interaction_id: str,
+    fetch_interaction: FetchInteraction = _fetch_interaction,
+) -> None:
+    entry = _ACTIVE_POLLS.get(interaction_id)
+    if entry is None:
+        return
+    context = entry.context
+    try:
+        response = await fetch_interaction(context)
+    except Exception as e:  # noqa: BLE001  # unfetchable pre-delete state settles by releasing the reservation
+        verbose_logger.debug(
+            "Could not fetch background interaction %s before delete, releasing its reservation: %s",
+            interaction_id,
+            e,
+        )
+        if _claim_settlement(context.logging_obj):
+            await _release_open_budget_reservation(logging_obj=context.logging_obj)
+        return
+    if not _claim_settlement(context.logging_obj):
+        return
+    if response.status in _TERMINAL_STATUSES and response.usage is not None:
+        await context.logging_obj.async_log_background_interaction_completion(result=response)
+        return
+    await _release_open_budget_reservation(logging_obj=context.logging_obj)
diff --git a/litellm/interactions/main.py b/litellm/interactions/main.py
index 5a0ea9280b2..985c60c2cc2 100644
--- a/litellm/interactions/main.py
+++ b/litellm/interactions/main.py
@@ -41,6 +41,7 @@ import httpx
 import litellm
 from litellm.interactions.background_cost_polling import (
     maybe_schedule_background_interaction_cost_polling,
+    maybe_settle_background_interaction_before_delete,
 )
 from litellm.interactions.http_handler import interactions_http_handler
 from litellm.interactions.utils import (
@@ -474,6 +475,8 @@ async def adelete(
         loop = asyncio.get_event_loop()
         kwargs["adelete_interaction"] = True
 
+        await maybe_settle_background_interaction_before_delete(interaction_id=interaction_id)
+
         func = partial(
             delete,
             interaction_id=interaction_id,
diff --git a/tests/test_litellm/interactions/test_background_cost_polling.py b/tests/test_litellm/interactions/test_background_cost_polling.py
index 24abeec1053..64436ebe4a7 100644
--- a/tests/test_litellm/interactions/test_background_cost_polling.py
+++ b/tests/test_litellm/interactions/test_background_cost_polling.py
@@ -5,8 +5,10 @@ from typing import Optional
 import pytest
 
 from litellm.interactions.background_cost_polling import (
+    _SETTLED_KEY,
     BackgroundInteractionPollContext,
     maybe_schedule_background_interaction_cost_polling,
+    maybe_settle_background_interaction_before_delete,
     poll_and_log_background_interaction_cost,
 )
 from litellm.litellm_core_utils.litellm_logging import Logging as LitellmLogging
@@ -221,6 +223,127 @@ async def test_schedule_skips_non_pollable_results(response, create_kwargs):
     assert task is None
 
 
+def _register_poll(logging_obj: LitellmLogging, poll_fetch=None) -> asyncio.Task:
+    import litellm.interactions.background_cost_polling as bg
+
+    if poll_fetch is None:
+        poll_fetch, _ = _fetch_sequence(_response("in_progress", with_usage=False))
+    context = _context(logging_obj)
+    task = asyncio.create_task(poll_and_log_background_interaction_cost(context, fetch_interaction=poll_fetch))
+    bg._ACTIVE_POLLS[context.interaction_id] = bg._ActiveBackgroundPoll(task=task, context=context)
+    task.add_done_callback(lambda finished: bg._discard_poll(context.interaction_id, finished))
+    return task
+
+
+@pytest.mark.asyncio
+async def test_delete_settlement_bills_pending_background_interaction():
+    logging_obj = _logging_obj()
+    task = _register_poll(logging_obj)
+    fetch, calls = _fetch_sequence(_response("completed", with_usage=True))
+
+    await maybe_settle_background_interaction_before_delete(
+        interaction_id="interactions/bg-abc",
+        fetch_interaction=fetch,
+    )
+
+    assert len(calls) == 1
+    assert logging_obj.model_call_details["response_cost"] > 0
+    assert logging_obj.model_call_details["standard_logging_object"]["total_tokens"] == 175
+    await asyncio.wait_for(task, timeout=5)
+
+
+@pytest.mark.asyncio
+async def test_delete_settlement_releases_reservation_when_still_in_progress():
+    reservation = _reservation()
+    logging_obj = _logging_obj_with_reservation(reservation)
+    task = _register_poll(logging_obj)
+    fetch, _ = _fetch_sequence(_response("in_progress", with_usage=False))
+
+    await maybe_settle_background_interaction_before_delete(
+        interaction_id="interactions/bg-abc",
+        fetch_interaction=fetch,
+    )
+
+    assert reservation["finalized"] is True
+    assert logging_obj.model_call_details.get("response_cost") is None
+    await asyncio.wait_for(task, timeout=5)
+
+
+@pytest.mark.asyncio
+async def test_delete_settlement_releases_reservation_when_prefetch_fails():
+    reservation = _reservation()
+    logging_obj = _logging_obj_with_reservation(reservation)
+    task = _register_poll(logging_obj)
+    fetch, _ = _fetch_sequence(RuntimeError("interaction already deleted"))
+
+    await maybe_settle_background_interaction_before_delete(
+        interaction_id="interactions/bg-abc",
+        fetch_interaction=fetch,
+    )
+
+    assert reservation["finalized"] is True
+    assert logging_obj.model_call_details.get("response_cost") is None
+    await asyncio.wait_for(task, timeout=5)
+
+
+@pytest.mark.asyncio
+async def test_delete_settlement_ignores_interactions_without_pending_poll():
+    fetch, calls = _fetch_sequence(_response("completed", with_usage=True))
+
+    await maybe_settle_background_interaction_before_delete(
+        interaction_id="interactions/never-polled",
+        fetch_interaction=fetch,
+    )
+
+    assert calls == []
+
+
+@pytest.mark.asyncio
+async def test_delete_settlement_noop_after_poll_task_finished():
+    logging_obj = _logging_obj()
+    poll_fetch, _ = _fetch_sequence(_response("completed", with_usage=True))
+    task = _register_poll(logging_obj, poll_fetch=poll_fetch)
+    await asyncio.wait_for(task, timeout=5)
+    assert logging_obj.model_call_details["response_cost"] > 0
+
+    settle_fetch, settle_calls = _fetch_sequence(_response("completed", with_usage=True))
+    await maybe_settle_background_interaction_before_delete(
+        interaction_id="interactions/bg-abc",
+        fetch_interaction=settle_fetch,
+    )
+
+    assert settle_calls == []
+
+
+@pytest.mark.asyncio
+async def test_delete_settlement_does_not_rebill_when_gate_already_claimed():
+    logging_obj = _logging_obj()
+    logging_obj.model_call_details[_SETTLED_KEY] = True
+    task = _register_poll(logging_obj)
+    fetch, calls = _fetch_sequence(_response("completed", with_usage=True))
+
+    await maybe_settle_background_interaction_before_delete(
+        interaction_id="interactions/bg-abc",
+        fetch_interaction=fetch,
+    )
+
+    assert len(calls) == 1
+    assert logging_obj.model_call_details.get("response_cost") is None
+    await asyncio.wait_for(task, timeout=5)
+
+
+@pytest.mark.asyncio
+async def test_poller_exits_without_billing_once_settled_elsewhere():
+    logging_obj = _logging_obj()
+    logging_obj.model_call_details[_SETTLED_KEY] = True
+    fetch, calls = _fetch_sequence(_response("completed", with_usage=True))
+
+    await poll_and_log_background_interaction_cost(_context(logging_obj), fetch_interaction=fetch)
+
+    assert calls == []
+    assert logging_obj.model_call_details.get("response_cost") is None
+
+
 @pytest.mark.asyncio
 async def test_schedule_respects_kill_switch(monkeypatch):
     import litellm.interactions.background_cost_polling as module

From e458aa1230a1e23a06aa6ebff88561f5fa510dda Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Wed, 15 Jul 2026 08:12:49 -0700
Subject: [PATCH 06/93] fix(interactions): bill google_search grounding queries
 per query

---
 .../usage_object_transformation.py            | 12 ++++++-
 .../test_usage_object_transformation.py       | 29 +++++++++++++++
 tests/test_litellm/test_cost_calculator.py    | 36 +++++++++++++++++++
 3 files changed, 76 insertions(+), 1 deletion(-)

diff --git a/litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py b/litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py
index 3f591180b77..23fafc4132d 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py
@@ -62,6 +62,14 @@ def _modality_token_sums(entries: Sequence[Mapping[str, Any]]) -> Mapping[str, i
     }
 
 
+def _google_search_query_count(usage_object: Mapping[str, Any]) -> int:
+    return sum(
+        _token_count(entry.get("count"))
+        for entry in tuple(usage_object.get("grounding_tool_count") or ())
+        if isinstance(entry, Mapping) and entry.get("type") == "google_search"
+    )
+
+
 def _subtract_cached_from_input(
     input_sums: Mapping[str, int],
     cached_sums: Mapping[str, int],
@@ -116,12 +124,14 @@ class InteractionsUsageObjectTransformation:
         completion_tokens = _token_count(usage_object.get("total_output_tokens")) + reasoning_tokens
         total_tokens = _token_count(usage_object.get("total_tokens")) or (prompt_tokens + completion_tokens)
 
+        web_search_requests = _google_search_query_count(usage_object)
         prompt_tokens_details = (
             PromptTokensDetailsWrapper(
                 cached_tokens=total_cached_tokens or None,
+                web_search_requests=web_search_requests or None,
                 **input_sums,
             )
-            if input_sums or total_cached_tokens
+            if input_sums or total_cached_tokens or web_search_requests
             else None
         )
         completion_tokens_details = (
diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_usage_object_transformation.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_usage_object_transformation.py
index 01241cf260d..2d8092959ce 100644
--- a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_usage_object_transformation.py
+++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_usage_object_transformation.py
@@ -106,6 +106,35 @@ def test_tool_use_tokens_billed_as_input():
     assert usage.prompt_tokens_details.text_tokens == 140
 
 
+def test_google_search_grounding_count_maps_to_web_search_requests():
+    usage = InteractionsUsageObjectTransformation.transform_interactions_usage_object(
+        {
+            "total_input_tokens": 103,
+            "input_tokens_by_modality": [{"modality": "text", "tokens": 103}],
+            "total_output_tokens": 226,
+            "total_thought_tokens": 351,
+            "grounding_tool_count": [
+                {"type": "google_search", "count": 3},
+                {"type": "url_context", "count": 2},
+            ],
+        }
+    )
+    assert usage.prompt_tokens_details is not None
+    assert usage.prompt_tokens_details.web_search_requests == 3
+
+
+def test_no_grounding_leaves_web_search_requests_unset():
+    usage = InteractionsUsageObjectTransformation.transform_interactions_usage_object(
+        {
+            "total_input_tokens": 10,
+            "input_tokens_by_modality": [{"modality": "text", "tokens": 10}],
+            "total_output_tokens": 5,
+        }
+    )
+    assert usage.prompt_tokens_details is not None
+    assert getattr(usage.prompt_tokens_details, "web_search_requests", None) is None
+
+
 def test_document_modality_folds_into_text():
     usage = InteractionsUsageObjectTransformation.transform_interactions_usage_object(
         {
diff --git a/tests/test_litellm/test_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py
index 42fef833944..b144c614474 100644
--- a/tests/test_litellm/test_cost_calculator.py
+++ b/tests/test_litellm/test_cost_calculator.py
@@ -3514,6 +3514,42 @@ def test_completion_cost_bills_interactions_api_response():
     assert cost > 0
 
 
+def test_completion_cost_bills_interactions_google_search_per_query():
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    model_info = litellm.get_model_info(model="gemini-3-flash-preview", custom_llm_provider="gemini")
+    response = InteractionsAPIResponse(
+        id="interactions/search123",
+        model="gemini-3-flash-preview",
+        status="completed",
+        steps=[],
+        usage={
+            "total_tokens": 680,
+            "total_input_tokens": 103,
+            "input_tokens_by_modality": [{"modality": "text", "tokens": 103}],
+            "total_cached_tokens": 0,
+            "total_output_tokens": 226,
+            "total_tool_use_tokens": 0,
+            "total_thought_tokens": 351,
+            "grounding_tool_count": [{"type": "google_search", "count": 3}],
+        },
+    )
+
+    cost = completion_cost(completion_response=response, custom_llm_provider="gemini")
+
+    per_query_cost = model_info["search_context_cost_per_query"]["search_context_size_medium"]
+    reasoning_rate = model_info.get("output_cost_per_reasoning_token") or model_info["output_cost_per_token"]
+    expected = (
+        103 * model_info["input_cost_per_token"]
+        + 226 * model_info["output_cost_per_token"]
+        + 351 * reasoning_rate
+        + 3 * per_query_cost
+    )
+    assert model_info.get("web_search_billing_unit") == "per_query"
+    assert cost == pytest.approx(expected)
+    assert cost > 3 * per_query_cost
+
+
 def test_completion_cost_bills_interactions_video_output_at_video_rate():
     from litellm.types.interactions import InteractionsAPIResponse
 

From abf7dab0c2822edf8c3b2bc78618e62e5e6941f8 Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Fri, 31 Jul 2026 21:14:18 +0000
Subject: [PATCH 07/93] feat(azure_ai): support entra id / oauth auth on every
 azure ai foundry route

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/images/main.py                        |  27 ++--
 litellm/llms/azure/common_utils.py            |  29 +++-
 litellm/llms/azure_ai/common_utils.py         |  47 +++++-
 .../image_edit/flux2_transformation.py        |  18 +--
 .../azure_ai/image_edit/mai_transformation.py |  19 +--
 .../azure_ai/image_edit/transformation.py     |  22 ++-
 .../document_intelligence/transformation.py   |  16 +-
 litellm/llms/azure_ai/ocr/transformation.py   |  10 +-
 .../llms/azure_ai/rerank/transformation.py    |   8 +-
 .../llms/base_llm/rerank/transformation.py    |   2 +
 litellm/llms/cohere/rerank/transformation.py  |   2 +
 litellm/llms/custom_httpx/llm_http_handler.py |   1 +
 .../llms/dashscope/rerank/transformation.py   |   2 +
 .../llms/deepinfra/rerank/transformation.py   |   2 +
 .../fireworks_ai/rerank/transformation.py     |   2 +
 .../llms/hosted_vllm/rerank/transformation.py |   2 +
 .../llms/huggingface/rerank/transformation.py |   2 +
 .../llms/infinity/rerank/transformation.py    |   4 +-
 litellm/llms/jina_ai/rerank/transformation.py |   2 +
 .../llms/nvidia_nim/rerank/transformation.py  |   2 +
 .../llms/vertex_ai/rerank/transformation.py   |   8 +-
 litellm/llms/voyage/rerank/transformation.py  |   2 +
 litellm/llms/watsonx/rerank/transformation.py |   2 +
 litellm/main.py                               |   4 +-
 .../llms/azure/test_azure_common_utils.py     |  63 +++++++-
 ...test_azure_ai_image_edit_transformation.py |  33 ++++
 .../test_mai_image_edit_transformation.py     |  14 ++
 .../test_azure_ai_rerank_transformation.py    |  24 +++
 .../llms/azure_ai/test_azure_ai_entra_auth.py | 153 ++++++++++++++++++
 ...ocument_intelligence_ocr_transformation.py |  27 ++++
 30 files changed, 480 insertions(+), 69 deletions(-)
 create mode 100644 tests/test_litellm/llms/azure_ai/test_azure_ai_entra_auth.py

diff --git a/litellm/images/main.py b/litellm/images/main.py
index 17ea9aa177b..4c88eb52cd8 100644
--- a/litellm/images/main.py
+++ b/litellm/images/main.py
@@ -430,24 +430,31 @@ def image_generation(
                 aimg_generation=aimg_generation,
             )
         elif custom_llm_provider == "azure_ai":
-            from litellm.llms.azure_ai.common_utils import AzureFoundryModelInfo
+            from litellm.llms.azure_ai.common_utils import (
+                AzureFoundryModelInfo,
+                get_azure_ai_auth_headers,
+            )
 
             api_base = AzureFoundryModelInfo.get_api_base(api_base)
             api_key = AzureFoundryModelInfo.get_api_key(api_key)
             if extra_headers is not None:
                 optional_params["extra_headers"] = extra_headers
 
-            default_headers = {
+            caller_set_auth = "api-key" in headers or "Authorization" in headers
+            auth_headers = (
+                headers
+                if caller_set_auth
+                else get_azure_ai_auth_headers(
+                    api_key=api_key,
+                    litellm_params=litellm_params_dict,
+                    api_key_header="api-key",
+                )
+            )
+            headers = {
                 "Content-Type": "application/json",
+                **auth_headers,
+                **headers,
             }
-            # Only add api-key header if api_key is not None
-            # Azure AD authentication will use Authorization header instead
-            if api_key is not None:
-                default_headers["api-key"] = api_key
-
-            for k, v in default_headers.items():
-                if k not in headers:
-                    headers[k] = v
 
             model_response = azure_chat_completions.image_generation(
                 model=model,
diff --git a/litellm/llms/azure/common_utils.py b/litellm/llms/azure/common_utils.py
index 91f5793e269..85100e595e6 100644
--- a/litellm/llms/azure/common_utils.py
+++ b/litellm/llms/azure/common_utils.py
@@ -2,6 +2,7 @@ import asyncio
 import hashlib
 import json
 import os
+from functools import lru_cache
 from typing import Any, Callable, Dict, Literal, NamedTuple, Optional, Union, cast
 
 import httpx
@@ -57,6 +58,24 @@ def process_azure_headers(headers: Union[httpx.Headers, dict]) -> dict:
     return {**llm_response_headers, **openai_headers}
 
 
+@lru_cache(maxsize=128)
+def _cached_entra_id_token_provider(
+    tenant_id: str,
+    client_id: str,
+    client_secret: str,
+    scope: str,
+) -> Callable[[], str]:
+    """Build (once per credential set) a bearer token provider backed by a `ClientSecretCredential`.
+
+    The credential caches the access token internally and only talks to Entra ID when it is close
+    to expiry, so reusing the provider keeps one AAD round trip per token lifetime instead of one
+    per request.
+    """
+    from azure.identity import ClientSecretCredential, get_bearer_token_provider
+
+    return get_bearer_token_provider(ClientSecretCredential(tenant_id, client_id, client_secret), scope)
+
+
 def get_azure_ad_token_from_entra_id(
     tenant_id: str,
     client_id: str,
@@ -75,8 +94,6 @@ def get_azure_ad_token_from_entra_id(
     Returns:
         callable that returns a bearer token.
     """
-    from azure.identity import ClientSecretCredential, get_bearer_token_provider
-
     verbose_logger.debug("Getting Azure AD Token from Entra ID")
 
     if tenant_id.startswith("os.environ/"):
@@ -102,9 +119,13 @@ def get_azure_ad_token_from_entra_id(
     )
     if _tenant_id is None or _client_id is None or _client_secret is None:
         raise ValueError("tenant_id, client_id, and client_secret must be provided")
-    credential = ClientSecretCredential(_tenant_id, _client_id, _client_secret)
 
-    token_provider = get_bearer_token_provider(credential, scope)
+    token_provider = _cached_entra_id_token_provider(
+        tenant_id=_tenant_id,
+        client_id=_client_id,
+        client_secret=_client_secret,
+        scope=scope,
+    )
 
     verbose_logger.debug("token_provider %s", token_provider)
 
diff --git a/litellm/llms/azure_ai/common_utils.py b/litellm/llms/azure_ai/common_utils.py
index 9965aa693c3..5dd5f5c78cc 100644
--- a/litellm/llms/azure_ai/common_utils.py
+++ b/litellm/llms/azure_ai/common_utils.py
@@ -1,9 +1,54 @@
+from collections.abc import Mapping
 from typing import List, Literal, Optional
 
 import litellm
 from litellm.llms.base_llm.base_utils import BaseLLMModelInfo, BaseTokenCounter
 from litellm.secret_managers.main import get_secret_str
 from litellm.types.llms.openai import AllMessageValues
+from litellm.types.router import GenericLiteLLMParams
+
+AzureAIApiKeyHeader = Literal["Authorization", "api-key", "Api-Key", "Ocp-Apim-Subscription-Key"]
+
+
+def get_azure_ai_entra_token(litellm_params: Mapping[str, object] | None = None) -> str | None:
+    """
+    Resolve an Entra ID / OAuth access token for an Azure AI Foundry deployment.
+
+    Accepts the same credential set as the `azure` provider: service principal
+    (`tenant_id` / `client_id` / `client_secret`), a pre-fetched `azure_ad_token`, an OIDC
+    federated token, username/password, or `DefaultAzureCredential` / managed identity.
+    """
+    from litellm.llms.azure.common_utils import get_azure_ad_token
+
+    params = GenericLiteLLMParams.model_validate(litellm_params) if litellm_params else GenericLiteLLMParams()
+
+    return get_azure_ad_token(params)
+
+
+def get_azure_ai_auth_headers(
+    api_key: str | None,
+    litellm_params: Mapping[str, object] | None = None,
+    api_key_header: AzureAIApiKeyHeader = "Authorization",
+    api_key_env_var: str = "AZURE_AI_API_KEY",
+) -> dict[str, str]:
+    """
+    Build the auth headers for an Azure AI Foundry route.
+
+    Prefers the API key when one is configured, and otherwise falls back to Entra ID / OAuth,
+    sending the access token as a bearer token.
+    """
+    if api_key:
+        return {api_key_header: f"Bearer {api_key}" if api_key_header == "Authorization" else api_key}
+
+    azure_ad_token = get_azure_ai_entra_token(litellm_params=litellm_params)
+    if azure_ad_token:
+        return {"Authorization": f"Bearer {azure_ad_token}"}
+
+    raise ValueError(
+        f"Missing Azure AI credentials - set an API key (`api_key` or {api_key_env_var}), or Entra ID / OAuth "
+        "credentials (`tenant_id` + `client_id` + `client_secret`, `azure_ad_token`, an OIDC token, or a managed "
+        "identity with `litellm.enable_azure_ad_token_refresh = True`)"
+    )
 
 
 class AzureFoundryModelInfo(BaseLLMModelInfo):
@@ -43,7 +88,7 @@ class AzureFoundryModelInfo(BaseLLMModelInfo):
 
     @staticmethod
     def get_api_key(api_key: Optional[str] = None) -> Optional[str]:
-        return api_key or litellm.api_key or litellm.openai_key or get_secret_str("AZURE_AI_API_KEY")
+        return api_key or litellm.api_key or get_secret_str("AZURE_AI_API_KEY")
 
     @property
     def api_version(self, api_version: Optional[str] = None) -> Optional[str]:
diff --git a/litellm/llms/azure_ai/image_edit/flux2_transformation.py b/litellm/llms/azure_ai/image_edit/flux2_transformation.py
index 1bc3bdcddc1..db429b85082 100644
--- a/litellm/llms/azure_ai/image_edit/flux2_transformation.py
+++ b/litellm/llms/azure_ai/image_edit/flux2_transformation.py
@@ -5,7 +5,10 @@ from typing import Any, Dict, Optional, Tuple
 from httpx._types import RequestFiles
 
 import litellm
-from litellm.llms.azure_ai.common_utils import AzureFoundryModelInfo
+from litellm.llms.azure_ai.common_utils import (
+    AzureFoundryModelInfo,
+    get_azure_ai_auth_headers,
+)
 from litellm.llms.azure_ai.image_generation.flux_transformation import (
     AzureFoundryFluxImageGenerationConfig,
 )
@@ -71,16 +74,13 @@ class AzureFoundryFlux2ImageEditConfig(OpenAIImageEditConfig):
         """
         Validate Azure AI Foundry environment and set up authentication
         """
-        api_key = AzureFoundryModelInfo.get_api_key(api_key)
-
-        if not api_key:
-            raise ValueError(
-                f"Azure AI API key is required for model {model}. Set AZURE_AI_API_KEY environment variable or pass api_key parameter."
-            )
-
         headers.update(
             {
-                "Api-Key": api_key,
+                **get_azure_ai_auth_headers(
+                    api_key=AzureFoundryModelInfo.get_api_key(api_key),
+                    litellm_params=litellm_params,
+                    api_key_header="Api-Key",
+                ),
                 "Content-Type": "application/json",
             }
         )
diff --git a/litellm/llms/azure_ai/image_edit/mai_transformation.py b/litellm/llms/azure_ai/image_edit/mai_transformation.py
index aa1092b0a53..fdac9912193 100644
--- a/litellm/llms/azure_ai/image_edit/mai_transformation.py
+++ b/litellm/llms/azure_ai/image_edit/mai_transformation.py
@@ -3,7 +3,10 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, cast
 import httpx
 from httpx._types import RequestFiles
 
-from litellm.llms.azure_ai.common_utils import AzureFoundryModelInfo
+from litellm.llms.azure_ai.common_utils import (
+    AzureFoundryModelInfo,
+    get_azure_ai_auth_headers,
+)
 from litellm.llms.azure_ai.image_generation.mai_transformation import (
     AzureFoundryMAIImageGenerationConfig,
 )
@@ -91,15 +94,13 @@ class AzureFoundryMAIImageEditConfig(OpenAIImageEditConfig):
         litellm_params: Optional[dict] = None,
         api_base: Optional[str] = None,
     ) -> dict:
-        api_key = AzureFoundryModelInfo.get_api_key(api_key)
-
-        if not api_key:
-            raise ValueError(
-                f"Azure AI API key is required for model {model}. "
-                "Set AZURE_AI_API_KEY environment variable or pass api_key parameter."
+        headers.update(
+            get_azure_ai_auth_headers(
+                api_key=AzureFoundryModelInfo.get_api_key(api_key),
+                litellm_params=litellm_params,
+                api_key_header="api-key",
             )
-
-        headers.update({"api-key": api_key})
+        )
         return headers
 
     def get_complete_url(
diff --git a/litellm/llms/azure_ai/image_edit/transformation.py b/litellm/llms/azure_ai/image_edit/transformation.py
index 5393a0ba55f..22b0b169faf 100644
--- a/litellm/llms/azure_ai/image_edit/transformation.py
+++ b/litellm/llms/azure_ai/image_edit/transformation.py
@@ -3,7 +3,10 @@ from typing import Optional
 import httpx
 
 import litellm
-from litellm.llms.azure_ai.common_utils import AzureFoundryModelInfo
+from litellm.llms.azure_ai.common_utils import (
+    AzureFoundryModelInfo,
+    get_azure_ai_auth_headers,
+)
 from litellm.llms.openai.image_edit.transformation import OpenAIImageEditConfig
 from litellm.secret_managers.main import get_secret_str
 from litellm.utils import _add_path_to_api_base
@@ -30,19 +33,14 @@ class AzureFoundryFluxImageEditConfig(OpenAIImageEditConfig):
     ) -> dict:
         """
         Validate Azure AI Foundry environment and set up authentication
-        Uses Api-Key header format
+        Uses the Api-Key header format, or an Entra ID / OAuth bearer token when no key is set
         """
-        api_key = AzureFoundryModelInfo.get_api_key(api_key)
-
-        if not api_key:
-            raise ValueError(
-                f"Azure AI API key is required for model {model}. Set AZURE_AI_API_KEY environment variable or pass api_key parameter."
-            )
-
         headers.update(
-            {
-                "Api-Key": api_key,  # Azure AI Foundry uses Api-Key header format
-            }
+            get_azure_ai_auth_headers(
+                api_key=AzureFoundryModelInfo.get_api_key(api_key),
+                litellm_params=litellm_params,
+                api_key_header="Api-Key",
+            )
         )
         return headers
 
diff --git a/litellm/llms/azure_ai/ocr/document_intelligence/transformation.py b/litellm/llms/azure_ai/ocr/document_intelligence/transformation.py
index 7d915892a28..4db4472dfc2 100644
--- a/litellm/llms/azure_ai/ocr/document_intelligence/transformation.py
+++ b/litellm/llms/azure_ai/ocr/document_intelligence/transformation.py
@@ -25,6 +25,7 @@ from litellm.constants import (
     AZURE_OPERATION_POLLING_TIMEOUT,
 )
 from litellm.litellm_core_utils.url_utils import encode_url_path_segment
+from litellm.llms.azure_ai.common_utils import get_azure_ai_auth_headers
 from litellm.llms.base_llm.ocr.transformation import (
     BaseOCRConfig,
     DocumentType,
@@ -215,17 +216,13 @@ class AzureDocumentIntelligenceOCRConfig(BaseOCRConfig):
         """
         Validate environment and return headers for Azure Document Intelligence.
 
-        Authentication uses Ocp-Apim-Subscription-Key header.
+        Authentication uses the Ocp-Apim-Subscription-Key header, or an Entra ID / OAuth bearer
+        token when no subscription key is set.
         """
         # Get API key from environment if not provided
         if api_key is None:
             api_key = get_secret_str(AZURE_DOCUMENT_INTELLIGENCE_API_KEY_ENV_VAR)
 
-        if api_key is None:
-            raise ValueError(
-                "Missing Azure Document Intelligence API Key - Set AZURE_DOCUMENT_INTELLIGENCE_API_KEY environment variable or pass api_key parameter"
-            )
-
         # Validate API base/endpoint is provided
         if api_base is None:
             api_base = get_secret_str("AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT")
@@ -236,7 +233,12 @@ class AzureDocumentIntelligenceOCRConfig(BaseOCRConfig):
             )
 
         headers = {
-            "Ocp-Apim-Subscription-Key": api_key,
+            **get_azure_ai_auth_headers(
+                api_key=api_key,
+                litellm_params=litellm_params,
+                api_key_header="Ocp-Apim-Subscription-Key",
+                api_key_env_var=AZURE_DOCUMENT_INTELLIGENCE_API_KEY_ENV_VAR,
+            ),
             "Content-Type": "application/json",
             **headers,
         }
diff --git a/litellm/llms/azure_ai/ocr/transformation.py b/litellm/llms/azure_ai/ocr/transformation.py
index a57e3e869cf..abc23008f6a 100644
--- a/litellm/llms/azure_ai/ocr/transformation.py
+++ b/litellm/llms/azure_ai/ocr/transformation.py
@@ -9,6 +9,7 @@ from litellm.litellm_core_utils.prompt_templates.image_handling import (
     async_convert_url_to_base64,
     convert_url_to_base64,
 )
+from litellm.llms.azure_ai.common_utils import get_azure_ai_auth_headers
 from litellm.llms.base_llm.ocr.transformation import DocumentType, OCRRequestData
 from litellm.llms.mistral.ocr.transformation import MistralOCRConfig
 from litellm.secret_managers.main import get_secret_str
@@ -47,17 +48,12 @@ class AzureAIOCRConfig(MistralOCRConfig):
         """
         Validate environment and return headers for Azure AI OCR.
 
-        Azure AI uses Bearer token authentication with AZURE_AI_API_KEY.
+        Authenticates with AZURE_AI_API_KEY, or with an Entra ID / OAuth token when no key is set.
         """
         # Get API key from environment if not provided
         if api_key is None:
             api_key = get_secret_str(AZURE_AI_OCR_API_KEY_ENV_VAR)
 
-        if api_key is None:
-            raise ValueError(
-                "Missing Azure AI API Key - A call is being made to Azure AI but no key is set either in the environment variables or via params"
-            )
-
         # Validate API base is provided
         if api_base is None:
             api_base = get_secret_str("AZURE_AI_API_BASE")
@@ -68,7 +64,7 @@ class AzureAIOCRConfig(MistralOCRConfig):
             )
 
         headers = {
-            "Authorization": f"Bearer {api_key}",
+            **get_azure_ai_auth_headers(api_key=api_key, litellm_params=litellm_params),
             "Content-Type": "application/json",
             **headers,
         }
diff --git a/litellm/llms/azure_ai/rerank/transformation.py b/litellm/llms/azure_ai/rerank/transformation.py
index 928f53bd485..24cdc67a23b 100644
--- a/litellm/llms/azure_ai/rerank/transformation.py
+++ b/litellm/llms/azure_ai/rerank/transformation.py
@@ -2,12 +2,14 @@
 Translate between Cohere's `/rerank` format and Azure AI's `/rerank` format.
 """
 
+from collections.abc import Mapping
 from typing import Optional
 
 import httpx
 
 import litellm
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+from litellm.llms.azure_ai.common_utils import get_azure_ai_auth_headers
 from litellm.llms.cohere.rerank.transformation import CohereRerankConfig
 from litellm.secret_managers.main import get_secret_str
 from litellm.types.utils import RerankResponse
@@ -64,15 +66,13 @@ class AzureAIRerankConfig(CohereRerankConfig):
         model: str,
         api_key: Optional[str] = None,
         optional_params: Optional[dict] = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
         if api_key is None:
             api_key = get_secret_str("AZURE_AI_API_KEY") or litellm.azure_key
 
-        if api_key is None:
-            raise ValueError("Azure AI API key is required. Please set 'AZURE_AI_API_KEY' or 'litellm.azure_key'")
-
         default_headers = {
-            "Authorization": f"Bearer {api_key}",
+            **get_azure_ai_auth_headers(api_key=api_key, litellm_params=litellm_params),
             "accept": "application/json",
             "content-type": "application/json",
         }
diff --git a/litellm/llms/base_llm/rerank/transformation.py b/litellm/llms/base_llm/rerank/transformation.py
index eac44ba85c5..e9f210fb31c 100644
--- a/litellm/llms/base_llm/rerank/transformation.py
+++ b/litellm/llms/base_llm/rerank/transformation.py
@@ -1,4 +1,5 @@
 from abc import ABC, abstractmethod
+from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any, Dict, List, Tuple, Union
 
 import httpx
@@ -24,6 +25,7 @@ class BaseRerankConfig(ABC):
         model: str,
         api_key: str | None = None,
         optional_params: dict | None = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
         pass
 
diff --git a/litellm/llms/cohere/rerank/transformation.py b/litellm/llms/cohere/rerank/transformation.py
index e494e89fbf2..86d9a3d224d 100644
--- a/litellm/llms/cohere/rerank/transformation.py
+++ b/litellm/llms/cohere/rerank/transformation.py
@@ -1,3 +1,4 @@
+from collections.abc import Mapping
 from typing import Any, Dict, List, Union
 
 import httpx
@@ -81,6 +82,7 @@ class CohereRerankConfig(BaseRerankConfig):
         model: str,
         api_key: str | None = None,
         optional_params: dict | None = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
         if api_key is None:
             api_key = get_secret_str("COHERE_API_KEY") or get_secret_str("CO_API_KEY") or litellm.cohere_key
diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py
index ec1301e5923..e41fbea94d6 100644
--- a/litellm/llms/custom_httpx/llm_http_handler.py
+++ b/litellm/llms/custom_httpx/llm_http_handler.py
@@ -1063,6 +1063,7 @@ class BaseLLMHTTPHandler:
             headers=headers or {},
             model=model,
             optional_params=optional_rerank_params,
+            litellm_params=litellm_params,
         )
 
         api_base = provider_config.get_complete_url(
diff --git a/litellm/llms/dashscope/rerank/transformation.py b/litellm/llms/dashscope/rerank/transformation.py
index 365e15fdd7a..b8c369b892c 100644
--- a/litellm/llms/dashscope/rerank/transformation.py
+++ b/litellm/llms/dashscope/rerank/transformation.py
@@ -22,6 +22,7 @@ as supported only for gte-rerank-v2 / qwen3-vl-rerank.
 Docs - https://help.aliyun.com/zh/model-studio/text-rerank-api
 """
 
+from collections.abc import Mapping
 from typing import Any, Dict, List, Union
 
 import httpx
@@ -85,6 +86,7 @@ class DashScopeRerankConfig(BaseRerankConfig):
         model: str,
         api_key: str | None = None,
         optional_params: dict | None = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
         if api_key is None:
             api_key = get_secret_str("DASHSCOPE_API_KEY")
diff --git a/litellm/llms/deepinfra/rerank/transformation.py b/litellm/llms/deepinfra/rerank/transformation.py
index 82069e4e195..87a6ecc7120 100644
--- a/litellm/llms/deepinfra/rerank/transformation.py
+++ b/litellm/llms/deepinfra/rerank/transformation.py
@@ -2,6 +2,7 @@
 Translate between Cohere's `/rerank` format and Deepinfra's `/rerank` format.
 """
 
+from collections.abc import Mapping
 from typing import Any, Dict, List, Union
 
 import httpx
@@ -67,6 +68,7 @@ class DeepinfraRerankConfig(BaseRerankConfig):
         model: str,
         api_key: str | None = None,
         optional_params: dict | None = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
         if api_key is None:
             api_key = get_secret_str("DEEPINFRA_API_KEY")
diff --git a/litellm/llms/fireworks_ai/rerank/transformation.py b/litellm/llms/fireworks_ai/rerank/transformation.py
index 393a6c5a8e5..e727f5c1d2b 100644
--- a/litellm/llms/fireworks_ai/rerank/transformation.py
+++ b/litellm/llms/fireworks_ai/rerank/transformation.py
@@ -4,6 +4,7 @@ Fireworks AI Rerank API transformation
 Reference: https://docs.fireworks.ai/inference-api-reference/rerank
 """
 
+from collections.abc import Mapping
 from typing import Any, Dict, List, Union
 
 import httpx
@@ -104,6 +105,7 @@ class FireworksAIRerankConfig(FireworksAIMixin, BaseRerankConfig):
         model: str,
         api_key: str | None = None,
         optional_params: dict | None = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
         api_key = self._get_api_key(api_key)
         if api_key is None:
diff --git a/litellm/llms/hosted_vllm/rerank/transformation.py b/litellm/llms/hosted_vllm/rerank/transformation.py
index 77504eba04a..cd35cc72492 100644
--- a/litellm/llms/hosted_vllm/rerank/transformation.py
+++ b/litellm/llms/hosted_vllm/rerank/transformation.py
@@ -2,6 +2,7 @@
 Transformation logic for Hosted VLLM rerank
 """
 
+from collections.abc import Mapping
 from typing import Any, Dict, List, Union
 
 import httpx
@@ -107,6 +108,7 @@ class HostedVLLMRerankConfig(BaseRerankConfig):
         model: str,
         api_key: str | None = None,
         optional_params: dict | None = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
         if api_key is None:
             api_key = get_secret_str("HOSTED_VLLM_API_KEY") or "fake-api-key"
diff --git a/litellm/llms/huggingface/rerank/transformation.py b/litellm/llms/huggingface/rerank/transformation.py
index cdad77a9815..245551cf4f2 100644
--- a/litellm/llms/huggingface/rerank/transformation.py
+++ b/litellm/llms/huggingface/rerank/transformation.py
@@ -1,4 +1,5 @@
 import os
+from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any, Dict, List, Tuple, Union
 
 import httpx
@@ -125,6 +126,7 @@ class HuggingFaceRerankConfig(BaseRerankConfig):
         api_key: str | None = None,
         optional_params: dict | None = None,
         api_base: str | None = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
         # Get API credentials
         api_key, api_base = self.get_api_credentials(api_key=api_key, api_base=api_base)
diff --git a/litellm/llms/infinity/rerank/transformation.py b/litellm/llms/infinity/rerank/transformation.py
index 94746da4609..7451b06c01a 100644
--- a/litellm/llms/infinity/rerank/transformation.py
+++ b/litellm/llms/infinity/rerank/transformation.py
@@ -4,12 +4,13 @@ Transformation logic from Cohere's /v1/rerank format to Infinity's  `/v1/rerank`
 Why separate file? Make it easy to see how transformation works
 """
 
-from litellm._uuid import uuid
+from collections.abc import Mapping
 from typing import List, Optional
 
 import httpx
 
 import litellm
+from litellm._uuid import uuid
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.llms.cohere.rerank.transformation import CohereRerankConfig
 from litellm.secret_managers.main import get_secret_str
@@ -46,6 +47,7 @@ class InfinityRerankConfig(CohereRerankConfig):
         model: str,
         api_key: Optional[str] = None,
         optional_params: Optional[dict] = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
         if api_key is None:
             api_key = get_secret_str("INFINITY_API_KEY") or get_secret_str("INFINITY_API_KEY") or litellm.infinity_key
diff --git a/litellm/llms/jina_ai/rerank/transformation.py b/litellm/llms/jina_ai/rerank/transformation.py
index 7f4c0709bdd..903e629803b 100644
--- a/litellm/llms/jina_ai/rerank/transformation.py
+++ b/litellm/llms/jina_ai/rerank/transformation.py
@@ -6,6 +6,7 @@ Why separate file? Make it easy to see how transformation works
 Docs - https://jina.ai/reranker
 """
 
+from collections.abc import Mapping
 from typing import Any, Dict, List, Tuple, Union
 
 from httpx import URL, Response
@@ -139,6 +140,7 @@ class JinaAIRerankConfig(BaseRerankConfig):
         model: str,
         api_key: str | None = None,
         optional_params: dict | None = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> Dict:
         if api_key is None:
             raise ValueError("api_key is required. Set via `api_key` parameter or `JINA_API_KEY` environment variable.")
diff --git a/litellm/llms/nvidia_nim/rerank/transformation.py b/litellm/llms/nvidia_nim/rerank/transformation.py
index 2d72d52f991..07b792468c9 100644
--- a/litellm/llms/nvidia_nim/rerank/transformation.py
+++ b/litellm/llms/nvidia_nim/rerank/transformation.py
@@ -1,3 +1,4 @@
+from collections.abc import Mapping
 from typing import Any, Dict, List, Literal, Union
 
 import httpx
@@ -148,6 +149,7 @@ class NvidiaNimRerankConfig(BaseRerankConfig):
         model: str,
         api_key: str | None = None,
         optional_params: dict | None = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
         """
         Validate that the Nvidia NIM API key is present.
diff --git a/litellm/llms/vertex_ai/rerank/transformation.py b/litellm/llms/vertex_ai/rerank/transformation.py
index b9680af20cc..055a02aa40d 100644
--- a/litellm/llms/vertex_ai/rerank/transformation.py
+++ b/litellm/llms/vertex_ai/rerank/transformation.py
@@ -4,6 +4,7 @@ Translates from Cohere's `/v1/rerank` input format to Vertex AI Discovery Engine
 Why separate file? Make it easy to see how transformation works
 """
 
+from collections.abc import Mapping
 from typing import Any, Dict, List, Union
 
 import httpx
@@ -74,14 +75,15 @@ class VertexAIRerankConfig(BaseRerankConfig, VertexBase):
         model: str,
         api_key: str | None = None,
         optional_params: Dict | None = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
         """
         Validate and set up authentication for Vertex AI Discovery Engine API
         """
         # Get credentials and project info from optional_params (which contains vertex_credentials, etc.)
-        litellm_params = optional_params.copy() if optional_params else {}
-        vertex_credentials = self.safe_get_vertex_ai_credentials(litellm_params)
-        vertex_project = self.safe_get_vertex_ai_project(litellm_params)
+        vertex_params = optional_params.copy() if optional_params else {}
+        vertex_credentials = self.safe_get_vertex_ai_credentials(vertex_params)
+        vertex_project = self.safe_get_vertex_ai_project(vertex_params)
 
         # Get access token using the base class method
         access_token, project_id = self._ensure_access_token(
diff --git a/litellm/llms/voyage/rerank/transformation.py b/litellm/llms/voyage/rerank/transformation.py
index e426e39962b..df9f32dd96d 100644
--- a/litellm/llms/voyage/rerank/transformation.py
+++ b/litellm/llms/voyage/rerank/transformation.py
@@ -4,6 +4,7 @@ Transformation logic for Voyage AI's /v1/rerank endpoint.
 Docs - https://docs.voyageai.com/docs/reranker
 """
 
+from collections.abc import Mapping
 from typing import Any, Dict, List, Tuple, Union
 
 import httpx
@@ -137,6 +138,7 @@ class VoyageRerankConfig(BaseRerankConfig):
         model: str,
         api_key: str | None = None,
         optional_params: dict | None = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> Dict:
         if api_key is None:
             api_key = get_secret_str("VOYAGE_API_KEY") or get_secret_str("VOYAGE_AI_API_KEY")
diff --git a/litellm/llms/watsonx/rerank/transformation.py b/litellm/llms/watsonx/rerank/transformation.py
index 25b593f1c0a..549ccca4748 100644
--- a/litellm/llms/watsonx/rerank/transformation.py
+++ b/litellm/llms/watsonx/rerank/transformation.py
@@ -5,6 +5,7 @@ Docs - https://cloud.ibm.com/apidocs/watsonx-ai#text-rerank
 """
 
 import uuid
+from collections.abc import Mapping
 from typing import Any, Dict, List, Union, cast
 
 import httpx
@@ -60,6 +61,7 @@ class IBMWatsonXRerankConfig(IBMWatsonXMixin, BaseRerankConfig):
         model: str,
         api_key: str | None = None,
         optional_params: dict | None = None,
+        litellm_params: Mapping[str, object] | None = None,
     ) -> Dict:
         optional_params = optional_params or {}
 
diff --git a/litellm/main.py b/litellm/main.py
index acdec7385da..b167a257d18 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -6739,6 +6739,8 @@ def embedding(
                 aembedding=aembedding,
             )
         elif custom_llm_provider == "azure_ai":
+            from litellm.llms.azure_ai.common_utils import get_azure_ai_entra_token
+
             api_base = (
                 api_base  # for deepinfra/perplexity/anyscale/groq/friendliai we check in get_llm_provider and pass in the api base from there
                 or litellm.api_base
@@ -6748,8 +6750,8 @@ def embedding(
             api_key = (
                 api_key
                 or litellm.api_key  # for deepinfra/perplexity/anyscale/friendliai we check in get_llm_provider and pass in the api key from there
-                or litellm.openai_key
                 or get_secret_str("AZURE_AI_API_KEY")
+                or get_azure_ai_entra_token(litellm_params=litellm_params_dict)
             )
 
             ## EMBEDDING CALL
diff --git a/tests/test_litellm/llms/azure/test_azure_common_utils.py b/tests/test_litellm/llms/azure/test_azure_common_utils.py
index a3280b90fe3..450920f1f44 100644
--- a/tests/test_litellm/llms/azure/test_azure_common_utils.py
+++ b/tests/test_litellm/llms/azure/test_azure_common_utils.py
@@ -11,7 +11,12 @@ sys.path.insert(
     0, os.path.abspath("../../../..")
 )  # Adds the parent directory to the system path
 import litellm
-from litellm.llms.azure.common_utils import BaseAzureLLM, get_azure_ad_token
+from litellm.llms.azure.common_utils import (
+    BaseAzureLLM,
+    _cached_entra_id_token_provider,
+    get_azure_ad_token,
+    get_azure_ad_token_from_entra_id,
+)
 from litellm.secret_managers.get_azure_ad_token_provider import (
     get_azure_ad_token_provider,
 )
@@ -2034,3 +2039,59 @@ def test_azure_traditional_api_uses_azure_openai_client():
         assert isinstance(
             async_client, AsyncAzureOpenAI
         ), f"Expected AsyncAzureOpenAI client for api_version={api_version}"
+
+
+class TestEntraIdTokenProviderCache:
+    def setup_method(self):
+        _cached_entra_id_token_provider.cache_clear()
+
+    def teardown_method(self):
+        _cached_entra_id_token_provider.cache_clear()
+
+    def test_reuses_credential_for_the_same_service_principal(self):
+        with (
+            patch("azure.identity.ClientSecretCredential") as mock_credential,
+            patch("azure.identity.get_bearer_token_provider", side_effect=lambda credential, scope: lambda: "token"),
+        ):
+            first = get_azure_ad_token_from_entra_id(
+                tenant_id="tenant",
+                client_id="client",
+                client_secret="secret",
+                scope="https://cognitiveservices.azure.com/.default",
+            )
+            second = get_azure_ad_token_from_entra_id(
+                tenant_id="tenant",
+                client_id="client",
+                client_secret="secret",
+                scope="https://cognitiveservices.azure.com/.default",
+            )
+
+        assert first is second
+        assert mock_credential.call_count == 1
+
+    @pytest.mark.parametrize(
+        "second_call_kwargs",
+        [
+            {"tenant_id": "other-tenant"},
+            {"client_id": "other-client"},
+            {"client_secret": "other-secret"},
+            {"scope": "https://ai.azure.com/.default"},
+        ],
+    )
+    def test_does_not_share_a_provider_across_credentials_or_scopes(self, second_call_kwargs):
+        base_kwargs = {
+            "tenant_id": "tenant",
+            "client_id": "client",
+            "client_secret": "secret",
+            "scope": "https://cognitiveservices.azure.com/.default",
+        }
+
+        with (
+            patch("azure.identity.ClientSecretCredential") as mock_credential,
+            patch("azure.identity.get_bearer_token_provider", side_effect=lambda credential, scope: lambda: "token"),
+        ):
+            first = get_azure_ad_token_from_entra_id(**base_kwargs)
+            second = get_azure_ad_token_from_entra_id(**{**base_kwargs, **second_call_kwargs})
+
+        assert first is not second
+        assert mock_credential.call_count == 2
diff --git a/tests/test_litellm/llms/azure_ai/image_edit/test_azure_ai_image_edit_transformation.py b/tests/test_litellm/llms/azure_ai/image_edit/test_azure_ai_image_edit_transformation.py
index da1041f3d60..9c9401fa8e9 100644
--- a/tests/test_litellm/llms/azure_ai/image_edit/test_azure_ai_image_edit_transformation.py
+++ b/tests/test_litellm/llms/azure_ai/image_edit/test_azure_ai_image_edit_transformation.py
@@ -5,6 +5,10 @@ sys.path.insert(
     0, os.path.abspath("../../../../..")
 )  # Adds the parent directory to the system path
 
+import litellm
+from litellm.llms.azure_ai.image_edit.flux2_transformation import (
+    AzureFoundryFlux2ImageEditConfig,
+)
 from litellm.llms.azure_ai.image_edit.transformation import (
     AzureFoundryFluxImageEditConfig,
 )
@@ -32,3 +36,32 @@ def test_azure_ai_url_generation():
     )
     expected_url = f"{api_base}/openai/deployments/FLUX.1-Kontext-pro/images/edits?api-version=2025-04-01-preview"
     assert complete_url == expected_url
+
+
+def test_azure_ai_validate_environment_with_entra_token(monkeypatch):
+    monkeypatch.delenv("AZURE_AI_API_KEY", raising=False)
+    monkeypatch.setattr(litellm, "api_key", None)
+    config = AzureFoundryFluxImageEditConfig()
+
+    headers = config.validate_environment(
+        {},
+        "FLUX.1-Kontext-pro",
+        litellm_params={"azure_ad_token": "entra-token"},
+    )
+
+    assert headers == {"Authorization": "Bearer entra-token"}
+
+
+def test_flux2_validate_environment_with_entra_token(monkeypatch):
+    monkeypatch.delenv("AZURE_AI_API_KEY", raising=False)
+    monkeypatch.setattr(litellm, "api_key", None)
+    config = AzureFoundryFlux2ImageEditConfig()
+
+    headers = config.validate_environment(
+        {},
+        "flux.2-pro",
+        litellm_params={"azure_ad_token": "entra-token"},
+    )
+
+    assert headers["Authorization"] == "Bearer entra-token"
+    assert headers["Content-Type"] == "application/json"
diff --git a/tests/test_litellm/llms/azure_ai/image_edit/test_mai_image_edit_transformation.py b/tests/test_litellm/llms/azure_ai/image_edit/test_mai_image_edit_transformation.py
index d5256be02d7..c4e39a26aeb 100644
--- a/tests/test_litellm/llms/azure_ai/image_edit/test_mai_image_edit_transformation.py
+++ b/tests/test_litellm/llms/azure_ai/image_edit/test_mai_image_edit_transformation.py
@@ -8,6 +8,7 @@ import pytest
 
 sys.path.insert(0, os.path.abspath("../../../../../.."))
 
+import litellm
 from litellm.llms.azure_ai.image_edit import (
     AzureFoundryMAIImageEditConfig,
     get_azure_ai_image_edit_config,
@@ -169,3 +170,16 @@ class TestAzureMAIImageEdit:
         assert image_response.data[0].b64_json == "abc123"
         assert image_response.usage.output_tokens == 1024
         assert image_response.usage.total_tokens == 1024
+
+
+def test_mai_validate_environment_with_entra_token(monkeypatch):
+    monkeypatch.delenv("AZURE_AI_API_KEY", raising=False)
+    monkeypatch.setattr(litellm, "api_key", None)
+
+    headers = AzureFoundryMAIImageEditConfig().validate_environment(
+        headers={},
+        model="MAI-Image-2.5",
+        litellm_params={"azure_ad_token": "entra-token"},
+    )
+
+    assert headers == {"Authorization": "Bearer entra-token"}
diff --git a/tests/test_litellm/llms/azure_ai/rerank/test_azure_ai_rerank_transformation.py b/tests/test_litellm/llms/azure_ai/rerank/test_azure_ai_rerank_transformation.py
index ffabce6e00c..150f5794ab1 100644
--- a/tests/test_litellm/llms/azure_ai/rerank/test_azure_ai_rerank_transformation.py
+++ b/tests/test_litellm/llms/azure_ai/rerank/test_azure_ai_rerank_transformation.py
@@ -7,6 +7,7 @@ sys.path.insert(
     0, os.path.abspath("../../../../..")
 )  # Adds the parent directory to the system path
 
+import litellm
 from litellm.llms.azure_ai.rerank.transformation import AzureAIRerankConfig
 
 
@@ -97,3 +98,26 @@ class TestAzureAIRerankConfigGetCompleteUrl:
             model=self.model,
         )
         assert url == "https://my-resource.services.ai.azure.com/v1/rerank?r=1"
+
+
+class TestAzureAIRerankConfigValidateEnvironment:
+    def test_uses_api_key_when_set(self):
+        headers = AzureAIRerankConfig().validate_environment(
+            headers={},
+            model="azure_ai/cohere-rerank-v3-english",
+            api_key="my-key",
+        )
+
+        assert headers["Authorization"] == "Bearer my-key"
+
+    def test_falls_back_to_entra_token(self, monkeypatch):
+        monkeypatch.delenv("AZURE_AI_API_KEY", raising=False)
+        monkeypatch.setattr(litellm, "azure_key", None)
+
+        headers = AzureAIRerankConfig().validate_environment(
+            headers={},
+            model="azure_ai/cohere-rerank-v3-english",
+            litellm_params={"azure_ad_token": "entra-token"},
+        )
+
+        assert headers["Authorization"] == "Bearer entra-token"
diff --git a/tests/test_litellm/llms/azure_ai/test_azure_ai_entra_auth.py b/tests/test_litellm/llms/azure_ai/test_azure_ai_entra_auth.py
new file mode 100644
index 00000000000..8ac37feee4b
--- /dev/null
+++ b/tests/test_litellm/llms/azure_ai/test_azure_ai_entra_auth.py
@@ -0,0 +1,153 @@
+"""
+Entra ID / OAuth auth for Azure AI Foundry routes.
+
+Every azure_ai route must authenticate with an Entra ID token when no API key is configured,
+instead of requiring an API key.
+"""
+
+from unittest.mock import patch
+
+import pytest
+
+import litellm
+from litellm.llms.azure_ai.common_utils import get_azure_ai_auth_headers
+from litellm.llms.azure_ai.ocr.transformation import AzureAIOCRConfig
+
+ENTRA_PARAMS = {"azure_ad_token": "entra-token"}
+
+
+@pytest.fixture(autouse=True)
+def clear_azure_env(monkeypatch):
+    for env_var in (
+        "AZURE_AI_API_KEY",
+        "AZURE_API_KEY",
+        "AZURE_AD_TOKEN",
+        "AZURE_TENANT_ID",
+        "AZURE_CLIENT_ID",
+        "AZURE_CLIENT_SECRET",
+        "AZURE_SCOPE",
+        "OPENAI_API_KEY",
+        "AZURE_DOCUMENT_INTELLIGENCE_API_KEY",
+    ):
+        monkeypatch.delenv(env_var, raising=False)
+    monkeypatch.setattr(litellm, "api_key", None)
+    monkeypatch.setattr(litellm, "openai_key", None)
+
+
+def test_api_key_wins_over_entra_credentials():
+    headers = get_azure_ai_auth_headers(api_key="my-key", litellm_params=ENTRA_PARAMS, api_key_header="Api-Key")
+
+    assert headers == {"Api-Key": "my-key"}
+
+
+def test_entra_token_used_when_no_api_key():
+    headers = get_azure_ai_auth_headers(api_key=None, litellm_params=ENTRA_PARAMS, api_key_header="Api-Key")
+
+    assert headers == {"Authorization": "Bearer entra-token"}
+
+
+def test_service_principal_token_is_requested_with_the_configured_scope():
+    with patch("litellm.llms.azure.common_utils.get_azure_ad_token_from_entra_id") as mock_entra_id:
+        mock_entra_id.return_value = lambda: "sp-token"
+
+        headers = get_azure_ai_auth_headers(
+            api_key=None,
+            litellm_params={
+                "tenant_id": "tenant",
+                "client_id": "client",
+                "client_secret": "secret",
+                "azure_scope": "https://ai.azure.com/.default",
+            },
+        )
+
+    mock_entra_id.assert_called_once_with(
+        tenant_id="tenant",
+        client_id="client",
+        client_secret="secret",
+        scope="https://ai.azure.com/.default",
+    )
+    assert headers == {"Authorization": "Bearer sp-token"}
+
+
+def test_error_mentions_both_credential_types_when_nothing_is_configured():
+    with pytest.raises(ValueError) as exc_info:
+        get_azure_ai_auth_headers(api_key=None, litellm_params={})
+
+    message = str(exc_info.value)
+    assert "AZURE_AI_API_KEY" in message
+    assert "client_secret" in message
+
+
+def test_ocr_authenticates_with_entra_token():
+    headers = AzureAIOCRConfig().validate_environment(
+        headers={},
+        model="azure_ai/mistral-ocr",
+        api_base="https://my-resource.services.ai.azure.com",
+        litellm_params=ENTRA_PARAMS,
+    )
+
+    assert headers["Authorization"] == "Bearer entra-token"
+
+
+def test_embedding_falls_back_to_entra_token_instead_of_openai_key(monkeypatch):
+    monkeypatch.setenv("OPENAI_API_KEY", "sk-openai-key")
+
+    with patch.object(litellm.main.azure_ai_embedding, "embedding") as mock_embedding:
+        mock_embedding.return_value = litellm.EmbeddingResponse()
+
+        litellm.embedding(
+            model="azure_ai/cohere-embed-v3-english",
+            input=["hello"],
+            api_base="https://my-resource.services.ai.azure.com",
+            azure_ad_token="entra-token",
+        )
+
+    assert mock_embedding.call_args.kwargs["api_key"] == "entra-token"
+
+
+def test_image_generation_authenticates_with_entra_token():
+    with patch.object(litellm.images.main.azure_chat_completions, "image_generation") as mock_image_generation:
+        mock_image_generation.return_value = litellm.ImageResponse()
+
+        litellm.image_generation(
+            model="azure_ai/FLUX-1.1-pro",
+            prompt="a red circle",
+            api_base="https://my-resource.services.ai.azure.com",
+            azure_ad_token="entra-token",
+        )
+
+    headers = mock_image_generation.call_args.kwargs["headers"]
+    assert headers["Authorization"] == "Bearer entra-token"
+    assert "api-key" not in headers
+
+
+def test_image_generation_keeps_caller_supplied_authorization_header():
+    with patch.object(litellm.images.main.azure_chat_completions, "image_generation") as mock_image_generation:
+        mock_image_generation.return_value = litellm.ImageResponse()
+
+        litellm.image_generation(
+            model="azure_ai/FLUX-1.1-pro",
+            prompt="a red circle",
+            api_base="https://my-resource.services.ai.azure.com",
+            headers={"Authorization": "Bearer caller-token"},
+        )
+
+    headers = mock_image_generation.call_args.kwargs["headers"]
+    assert headers["Authorization"] == "Bearer caller-token"
+    assert "api-key" not in headers
+
+
+def test_image_generation_still_uses_api_key_header():
+    with patch.object(litellm.images.main.azure_chat_completions, "image_generation") as mock_image_generation:
+        mock_image_generation.return_value = litellm.ImageResponse()
+
+        litellm.image_generation(
+            model="azure_ai/FLUX-1.1-pro",
+            prompt="a red circle",
+            api_base="https://my-resource.services.ai.azure.com",
+            api_key="my-key",
+        )
+
+    headers = mock_image_generation.call_args.kwargs["headers"]
+    assert headers["api-key"] == "my-key"
+    assert "Authorization" not in headers
diff --git a/tests/test_litellm/llms/azure_ai/test_azure_document_intelligence_ocr_transformation.py b/tests/test_litellm/llms/azure_ai/test_azure_document_intelligence_ocr_transformation.py
index 39d6f1dc355..b8e11a0bfcb 100644
--- a/tests/test_litellm/llms/azure_ai/test_azure_document_intelligence_ocr_transformation.py
+++ b/tests/test_litellm/llms/azure_ai/test_azure_document_intelligence_ocr_transformation.py
@@ -248,3 +248,30 @@ def test_get_complete_url_combines_pages_and_features():
 
     assert "&pages=1,2,3" in url
     assert "&features=keyValuePairs,languages" in url
+
+
+def test_validate_environment_uses_subscription_key(monkeypatch):
+    monkeypatch.delenv("AZURE_DOCUMENT_INTELLIGENCE_API_KEY", raising=False)
+
+    headers = AzureDocumentIntelligenceOCRConfig().validate_environment(
+        headers={},
+        model="prebuilt-layout",
+        api_key="my-key",
+        api_base="https://example.cognitiveservices.azure.com",
+    )
+
+    assert headers["Ocp-Apim-Subscription-Key"] == "my-key"
+
+
+def test_validate_environment_falls_back_to_entra_token(monkeypatch):
+    monkeypatch.delenv("AZURE_DOCUMENT_INTELLIGENCE_API_KEY", raising=False)
+
+    headers = AzureDocumentIntelligenceOCRConfig().validate_environment(
+        headers={},
+        model="prebuilt-layout",
+        api_base="https://example.cognitiveservices.azure.com",
+        litellm_params={"azure_ad_token": "entra-token"},
+    )
+
+    assert headers["Authorization"] == "Bearer entra-token"
+    assert "Ocp-Apim-Subscription-Key" not in headers

From c5d50817a70373f3443423fa8a6a97980ad156a9 Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Fri, 31 Jul 2026 22:01:28 +0000
Subject: [PATCH 08/93] fix(azure_ai): detect caller auth headers
 case-insensitively in image generation

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/images/main.py                                   | 3 ++-
 .../llms/azure_ai/test_azure_ai_entra_auth.py            | 9 +++++----
 2 files changed, 7 insertions(+), 5 deletions(-)

diff --git a/litellm/images/main.py b/litellm/images/main.py
index 4c88eb52cd8..3bee6000d3f 100644
--- a/litellm/images/main.py
+++ b/litellm/images/main.py
@@ -440,7 +440,8 @@ def image_generation(
             if extra_headers is not None:
                 optional_params["extra_headers"] = extra_headers
 
-            caller_set_auth = "api-key" in headers or "Authorization" in headers
+            caller_header_names = frozenset(name.lower() for name in headers)
+            caller_set_auth = "api-key" in caller_header_names or "authorization" in caller_header_names
             auth_headers = (
                 headers
                 if caller_set_auth
diff --git a/tests/test_litellm/llms/azure_ai/test_azure_ai_entra_auth.py b/tests/test_litellm/llms/azure_ai/test_azure_ai_entra_auth.py
index 8ac37feee4b..1145439a7b4 100644
--- a/tests/test_litellm/llms/azure_ai/test_azure_ai_entra_auth.py
+++ b/tests/test_litellm/llms/azure_ai/test_azure_ai_entra_auth.py
@@ -121,7 +121,8 @@ def test_image_generation_authenticates_with_entra_token():
     assert "api-key" not in headers
 
 
-def test_image_generation_keeps_caller_supplied_authorization_header():
+@pytest.mark.parametrize("header_name", ["Authorization", "authorization", "api-key", "API-KEY"])
+def test_image_generation_keeps_caller_supplied_auth_header(header_name):
     with patch.object(litellm.images.main.azure_chat_completions, "image_generation") as mock_image_generation:
         mock_image_generation.return_value = litellm.ImageResponse()
 
@@ -129,12 +130,12 @@ def test_image_generation_keeps_caller_supplied_authorization_header():
             model="azure_ai/FLUX-1.1-pro",
             prompt="a red circle",
             api_base="https://my-resource.services.ai.azure.com",
-            headers={"Authorization": "Bearer caller-token"},
+            headers={header_name: "caller-credential"},
         )
 
     headers = mock_image_generation.call_args.kwargs["headers"]
-    assert headers["Authorization"] == "Bearer caller-token"
-    assert "api-key" not in headers
+    assert headers[header_name] == "caller-credential"
+    assert len(headers) == 2
 
 
 def test_image_generation_still_uses_api_key_header():

From 05c91aa5f23a8f354a0076ab85ae9701a433bd3a Mon Sep 17 00:00:00 2001
From: ozolam <ozlamdan@gmail.com>
Date: Thu, 16 Jul 2026 14:12:28 +0300
Subject: [PATCH 09/93] fix(claude-code): correct skill install command and
 marketplace setup UX

- formatInstallCommand now produces /plugin install {name}@litellm instead of /plugin marketplace add {source}
- extraKnownMarketplaces snippet fixed: source must be a nested object not a flat string; the flat string caused Claude Code to reject the settings file
- marketplace key renamed from my-org to litellm to match the name the proxy returns in marketplace.json
- setup tab now shows /plugin marketplace add command as primary option with settings.json as secondary
- usage tab now shows a hint to run /plugin marketplace update litellm when a plugin is not found
---
 .../claude_code_plugins/helpers.test.ts       | 26 +-----
 .../components/claude_code_plugins/helpers.ts | 22 ++---
 .../claude_code_plugins/skill_detail.tsx      | 93 ++++++++++++++++++-
 3 files changed, 102 insertions(+), 39 deletions(-)

diff --git a/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.test.ts b/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.test.ts
index c16eba24f7b..a04134a63d8 100644
--- a/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.test.ts
+++ b/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.test.ts
@@ -25,7 +25,7 @@ describe("buildMarketplaceSettingsSnippet", () => {
   it("nests the url under a source object so Claude Code accepts the marketplace", () => {
     expect(JSON.parse(buildMarketplaceSettingsSnippet("https://proxy.example.com"))).toEqual({
       extraKnownMarketplaces: {
-        "my-org": {
+        litellm: {
           source: {
             source: "url",
             url: "https://proxy.example.com/claude-code/marketplace.json",
@@ -37,28 +37,12 @@ describe("buildMarketplaceSettingsSnippet", () => {
 });
 
 describe("formatInstallCommand", () => {
-  it("formats github source with repo", () => {
-    const source: PluginSource = { source: "github", repo: "org/repo" };
-    expect(formatInstallCommand({ name: "my-plugin", source })).toBe("/plugin marketplace add org/repo");
+  it("produces a /plugin install command scoped to the litellm marketplace", () => {
+    expect(formatInstallCommand({ name: "my-plugin" })).toBe("/plugin install my-plugin@litellm");
   });
 
-  it("formats url source", () => {
-    const source: PluginSource = { source: "url", url: "https://example.com/plugin" };
-    expect(formatInstallCommand({ name: "my-plugin", source })).toBe(
-      "/plugin marketplace add https://example.com/plugin",
-    );
-  });
-
-  it("formats git-subdir source using its url", () => {
-    const source: PluginSource = { source: "git-subdir", url: "https://github.com/org/repo", path: "plugins/x" };
-    expect(formatInstallCommand({ name: "my-plugin", source })).toBe(
-      "/plugin marketplace add https://github.com/org/repo",
-    );
-  });
-
-  it("falls back to plugin name when no repo or url", () => {
-    const source: PluginSource = { source: "github" };
-    expect(formatInstallCommand({ name: "my-plugin", source })).toBe("/plugin marketplace add my-plugin");
+  it("uses the plugin name as the identifier", () => {
+    expect(formatInstallCommand({ name: "code-review" })).toBe("/plugin install code-review@litellm");
   });
 });
 
diff --git a/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.ts b/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.ts
index a4e70f78af1..85b4ef357f7 100644
--- a/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.ts
+++ b/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.ts
@@ -179,13 +179,14 @@ export const parseSkillSource = (rawUrl: string, subPath?: string): SkillSourceP
 /**
  * Build the `~/.claude/settings.json` snippet that registers the proxy as a marketplace.
  * Claude Code expects `extraKnownMarketplaces.<name>.source` to be a source object, not a
- * bare `"url"` string, so the url/source pair is nested one level deeper.
+ * bare `"url"` string, so the url/source pair is nested one level deeper. The key must be
+ * "litellm" to match the name the proxy returns in marketplace.json.
  */
 export const buildMarketplaceSettingsSnippet = (proxyOrigin: string): string =>
   JSON.stringify(
     {
       extraKnownMarketplaces: {
-        "my-org": {
+        litellm: {
           source: {
             source: "url",
             url: `${proxyOrigin}/claude-code/marketplace.json`,
@@ -198,20 +199,11 @@ export const buildMarketplaceSettingsSnippet = (proxyOrigin: string): string =>
   );
 
 /**
- * Generate install command for Claude Code CLI
- * Format: /plugin marketplace add org/repo OR /plugin marketplace add url
+ * Generate install command for Claude Code CLI.
+ * Installs the named plugin from the "litellm" marketplace registered in settings.json.
  */
-export const formatInstallCommand = (plugin: { name: string; source: PluginSource }): string => {
-  const { source } = plugin;
-  if (source.source === "github" && source.repo) {
-    return `/plugin marketplace add ${source.repo}`;
-  }
-  if ((source.source === "url" || source.source === "git-subdir") && source.url) {
-    return `/plugin marketplace add ${source.url}`;
-  }
-  // Fallback to plugin name
-  return `/plugin marketplace add ${plugin.name}`;
-};
+export const formatInstallCommand = (plugin: { name: string }): string =>
+  `/plugin install ${plugin.name}@litellm`;
 
 /**
  * Extract unique categories from plugins list
diff --git a/ui/litellm-dashboard/src/components/claude_code_plugins/skill_detail.tsx b/ui/litellm-dashboard/src/components/claude_code_plugins/skill_detail.tsx
index fe001641135..8c99e9a3301 100644
--- a/ui/litellm-dashboard/src/components/claude_code_plugins/skill_detail.tsx
+++ b/ui/litellm-dashboard/src/components/claude_code_plugins/skill_detail.tsx
@@ -261,6 +261,32 @@ const SkillDetail: React.FC<SkillDetailProps> = ({ skill, onBack }) => {
             </pre>
           </div>
 
+          {/* Shown when the marketplace catalog is stale and the plugin isn't found yet */}
+          <div
+            style={{
+              border: "1px solid #fce8b2",
+              borderRadius: 8,
+              padding: "12px 16px",
+              backgroundColor: "#fefce8",
+              marginBottom: 16,
+            }}
+          >
+            <p style={{ fontSize: 13, color: "#5f6368", lineHeight: 1.6, margin: "0 0 8px 0" }}>
+              If you see &quot;Plugin {skill.name} not found in marketplace&quot;, update the catalog first:
+            </p>
+            <pre
+              style={{
+                margin: 0,
+                fontSize: 13,
+                fontFamily: "monospace",
+                color: "#202124",
+                backgroundColor: "transparent",
+              }}
+            >
+              /plugin marketplace update litellm
+            </pre>
+          </div>
+
           <p style={{ fontSize: 13, color: "#5f6368", lineHeight: 1.6, margin: 0 }}>
             Don&apos;t have the marketplace configured yet?{" "}
             <span onClick={() => setActiveTab("setup")} style={{ color: "#1a73e8", cursor: "pointer" }}>
@@ -276,12 +302,73 @@ const SkillDetail: React.FC<SkillDetailProps> = ({ skill, onBack }) => {
           <h2 style={{ fontSize: 18, fontWeight: 400, color: "#202124", margin: "0 0 8px 0" }}>
             One-time marketplace setup
           </h2>
-          <p style={{ fontSize: 14, color: "#5f6368", margin: "0 0 24px 0", lineHeight: 1.6 }}>
-            Add this to{" "}
+
+          {/* Option 1: single command — fastest path for most users */}
+          <p style={{ fontSize: 14, color: "#5f6368", margin: "0 0 12px 0", lineHeight: 1.6 }}>
+            Run this command in Claude Code to register the marketplace:
+          </p>
+          <div
+            style={{
+              border: "1px solid #dadce0",
+              borderRadius: 8,
+              overflow: "hidden",
+              marginBottom: 24,
+            }}
+          >
+            <div
+              style={{
+                display: "flex",
+                alignItems: "center",
+                justifyContent: "space-between",
+                padding: "10px 16px",
+                backgroundColor: "#f8f9fa",
+                borderBottom: "1px solid #dadce0",
+              }}
+            >
+              <span style={{ fontSize: 13, color: "#3c4043", fontWeight: 500 }}>Run in Claude Code</span>
+              <button
+                onClick={() => {
+                  const origin = typeof window !== "undefined" ? window.location.origin : "";
+                  copyToClipboard(`/plugin marketplace add ${origin}/claude-code/marketplace.json`, "marketplace-cmd");
+                }}
+                style={{
+                  display: "flex",
+                  alignItems: "center",
+                  gap: 4,
+                  fontSize: 12,
+                  color: copiedKey === "marketplace-cmd" ? "#137333" : "#1a73e8",
+                  background: "none",
+                  border: "none",
+                  cursor: "pointer",
+                  padding: 0,
+                }}
+              >
+                {copiedKey === "marketplace-cmd" ? <CheckOutlined /> : <CopyOutlined />}
+                {copiedKey === "marketplace-cmd" ? "Copied" : "Copy"}
+              </button>
+            </div>
+            <pre
+              style={{
+                margin: 0,
+                padding: "14px 16px",
+                fontSize: 13,
+                fontFamily: "monospace",
+                color: "#202124",
+                backgroundColor: "#fff",
+              }}
+            >
+              {`/plugin marketplace add ${typeof window !== "undefined" ? window.location.origin : "<proxy-url>"}/claude-code/marketplace.json`}
+            </pre>
+          </div>
+
+          {/* Option 2: settings.json — for persistent config or managed deployments.
+              extraKnownMarketplaces requires source to be a nested object, not a flat string. */}
+          <p style={{ fontSize: 14, color: "#5f6368", margin: "0 0 12px 0", lineHeight: 1.6 }}>
+            Or add this to{" "}
             <code style={{ fontSize: 13, backgroundColor: "#f1f3f4", padding: "1px 6px", borderRadius: 4 }}>
               ~/.claude/settings.json
             </code>{" "}
-            to point Claude Code at your proxy:
+            for a persistent configuration:
           </p>
           <div
             style={{

From a33378bdc1e147c680aec8503fb750e0439d9b31 Mon Sep 17 00:00:00 2001
From: ozolam <ozlamdan@gmail.com>
Date: Thu, 16 Jul 2026 14:12:29 +0300
Subject: [PATCH 10/93] fix(claude-code): fix prettier formatting and remove
 unused import

---
 .../src/components/claude_code_plugins/helpers.test.ts         | 2 +-
 .../src/components/claude_code_plugins/helpers.ts              | 3 +--
 2 files changed, 2 insertions(+), 3 deletions(-)

diff --git a/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.test.ts b/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.test.ts
index a04134a63d8..1d07ca09df5 100644
--- a/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.test.ts
+++ b/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.test.ts
@@ -19,7 +19,7 @@ import {
   isValidSubPath,
   buildMarketplaceSettingsSnippet,
 } from "./helpers";
-import { MarketplacePluginEntry, PluginSource } from "./types";
+import { MarketplacePluginEntry } from "./types";
 
 describe("buildMarketplaceSettingsSnippet", () => {
   it("nests the url under a source object so Claude Code accepts the marketplace", () => {
diff --git a/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.ts b/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.ts
index 85b4ef357f7..5b3d4f20c1e 100644
--- a/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.ts
+++ b/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.ts
@@ -202,8 +202,7 @@ export const buildMarketplaceSettingsSnippet = (proxyOrigin: string): string =>
  * Generate install command for Claude Code CLI.
  * Installs the named plugin from the "litellm" marketplace registered in settings.json.
  */
-export const formatInstallCommand = (plugin: { name: string }): string =>
-  `/plugin install ${plugin.name}@litellm`;
+export const formatInstallCommand = (plugin: { name: string }): string => `/plugin install ${plugin.name}@litellm`;
 
 /**
  * Extract unique categories from plugins list

From 141281b1d658e192a2b188ddf03d19f6eab58814 Mon Sep 17 00:00:00 2001
From: ozolam <ozlamdan@gmail.com>
Date: Thu, 16 Jul 2026 14:15:43 +0300
Subject: [PATCH 11/93] ci: retrigger CI


From 346c065fe0c7516b563996d2cee7061ce276fc3a Mon Sep 17 00:00:00 2001
From: ozolam <ozlamdan@gmail.com>
Date: Tue, 11 Aug 2026 21:34:41 +0300
Subject: [PATCH 12/93] fix(claude-code): restrict marketplace catalog
 mutations to proxy admins

---
 .../claude_code_marketplace.py                | 24 +++++++
 .../test_claude_code_marketplace.py           | 71 +++++++++++++++++++
 2 files changed, 95 insertions(+)

diff --git a/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_marketplace.py b/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_marketplace.py
index 46ee9b0911d..4730372511a 100644
--- a/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_marketplace.py
+++ b/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_marketplace.py
@@ -28,6 +28,7 @@ from fastapi.responses import JSONResponse
 from litellm._logging import verbose_proxy_logger
 from litellm.proxy._types import CommonProxyErrors, UserAPIKeyAuth
 from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+from litellm.proxy.common_utils.resource_ownership import is_proxy_admin
 from litellm.repositories.table_repositories import ClaudeCodePluginRepository
 from litellm.types.proxy.claude_code_endpoints import (
     ListPluginsResponse,
@@ -221,6 +222,18 @@ def _name_conflict_error(name: str) -> HTTPException:
     )
 
 
+def _require_proxy_admin(user_api_key_dict: UserAPIKeyAuth) -> None:
+    """Catalog mutations are restricted to proxy admins: marketplace.json is served
+    unauthenticated and any registered/updated entry is immediately installable by
+    every user, so a non-admin key must never be able to add or overwrite one.
+    """
+    if not is_proxy_admin(user_api_key_dict):
+        raise HTTPException(
+            status_code=403,
+            detail={"error": "Only proxy admins may modify the Claude Code plugin marketplace."},
+        )
+
+
 @router.post(
     "/claude-code/plugins",
     tags=["Claude Code Marketplace"],
@@ -271,6 +284,8 @@ async def register_plugin(
     from prisma.errors import UniqueViolationError
 
     try:
+        _require_proxy_admin(user_api_key_dict)
+
         prisma_client: Final = await _get_prisma_client()
 
         if not re.match(r"^[a-z0-9-]+$", request.name):
@@ -468,6 +483,7 @@ async def get_plugin(
 async def update_plugin(
     plugin_name: str,
     request: UpdatePluginRequest,
+    user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
 ):
     """
     Update an existing plugin in the LiteLLM marketplace.
@@ -509,6 +525,8 @@ async def update_plugin(
     from prisma.errors import PrismaError
 
     try:
+        _require_proxy_admin(user_api_key_dict)
+
         prisma_client: Final = await _get_prisma_client()
 
         _validate_plugin_source(request.source)
@@ -570,6 +588,8 @@ async def enable_plugin(
         - plugin_name: The name of the plugin to enable
     """
     try:
+        _require_proxy_admin(user_api_key_dict)
+
         prisma_client: Final = await _get_prisma_client()
 
         plugin: Final[_PluginRecord | None] = await ClaudeCodePluginRepository(prisma_client).table.find_unique(
@@ -615,6 +635,8 @@ async def disable_plugin(
         - plugin_name: The name of the plugin to disable
     """
     try:
+        _require_proxy_admin(user_api_key_dict)
+
         prisma_client: Final = await _get_prisma_client()
 
         plugin: Final[_PluginRecord | None] = await ClaudeCodePluginRepository(prisma_client).table.find_unique(
@@ -660,6 +682,8 @@ async def delete_plugin(
         - plugin_name: The name of the plugin to delete
     """
     try:
+        _require_proxy_admin(user_api_key_dict)
+
         prisma_client: Final = await _get_prisma_client()
 
         plugin: Final[_PluginRecord | None] = await ClaudeCodePluginRepository(prisma_client).table.find_unique(
diff --git a/tests/test_litellm/proxy/anthropic_endpoints/test_claude_code_marketplace.py b/tests/test_litellm/proxy/anthropic_endpoints/test_claude_code_marketplace.py
index 18e0f2cb559..d1ccd86044c 100644
--- a/tests/test_litellm/proxy/anthropic_endpoints/test_claude_code_marketplace.py
+++ b/tests/test_litellm/proxy/anthropic_endpoints/test_claude_code_marketplace.py
@@ -18,6 +18,9 @@ from litellm.types.proxy.claude_code_endpoints import (
     UpdatePluginRequest,
 )
 from litellm.proxy.anthropic_endpoints.claude_code_endpoints.claude_code_marketplace import (
+    delete_plugin,
+    disable_plugin,
+    enable_plugin,
     get_marketplace,
     register_plugin,
     update_plugin,
@@ -72,6 +75,12 @@ _USER = UserAPIKeyAuth(
     user_id="test-user",
 )
 
+_NON_ADMIN_USER = UserAPIKeyAuth(
+    user_role=LitellmUserRoles.INTERNAL_USER,
+    api_key="sk-5678",
+    user_id="regular-user",
+)
+
 _GIT_SUBDIR_SOURCE = {
     "source": "git-subdir",
     "url": "https://github.com/org/monorepo.git",
@@ -151,6 +160,7 @@ async def test_update_plugin_replaces_existing_source():
     response = await update_plugin(
         plugin_name=name,
         request=UpdatePluginRequest(source=new_source, version="2.0.0", description="updated"),
+        user_api_key_dict=_USER,
     )
 
     assert response.status == "success"
@@ -170,6 +180,7 @@ async def test_update_plugin_not_found():
         await update_plugin(
             plugin_name="does-not-exist",
             request=UpdatePluginRequest(source=_GIT_SUBDIR_SOURCE),
+            user_api_key_dict=_USER,
         )
 
     assert exc_info.value.status_code == 404
@@ -213,6 +224,7 @@ async def test_update_plugin_db_error_maps_to_structured_500():
         await update_plugin(
             plugin_name=name,
             request=UpdatePluginRequest(source={"source": "github", "repo": "org/replacement"}),
+            user_api_key_dict=_USER,
         )
 
     assert exc_info.value.status_code == 500
@@ -341,3 +353,62 @@ async def test_register_plugin_unknown_source_type():
 
     assert exc_info.value.status_code == 400
     assert "git-subdir" in exc_info.value.detail["error"]
+
+
+@pytest.mark.asyncio
+async def test_register_plugin_rejects_non_admin():
+    """A non-admin key cannot add an entry to the marketplace catalog."""
+    request = RegisterPluginRequest(name="attacker-plugin", source=_GIT_SUBDIR_SOURCE)
+
+    with pytest.raises(HTTPException) as exc_info:
+        await register_plugin(request=request, user_api_key_dict=_NON_ADMIN_USER)
+
+    assert exc_info.value.status_code == 403
+
+    table = litellm.proxy.proxy_server.prisma_client.db.litellm_claudecodeplugintable
+    assert await table.find_unique(where={"name": "attacker-plugin"}) is None
+
+
+@pytest.mark.asyncio
+async def test_update_plugin_rejects_non_admin_overwrite():
+    """A non-admin key cannot overwrite an existing plugin's source."""
+    name = "trusted-plugin"
+    await register_plugin(
+        request=RegisterPluginRequest(name=name, source=_GIT_SUBDIR_SOURCE, version="1.0.0"),
+        user_api_key_dict=_USER,
+    )
+
+    malicious_source = {"source": "github", "repo": "attacker/malicious-repo"}
+    with pytest.raises(HTTPException) as exc_info:
+        await update_plugin(
+            plugin_name=name,
+            request=UpdatePluginRequest(source=malicious_source),
+            user_api_key_dict=_NON_ADMIN_USER,
+        )
+
+    assert exc_info.value.status_code == 403
+
+    stored = await _read_stored_manifest(name)
+    assert stored["source"] == _GIT_SUBDIR_SOURCE
+
+
+@pytest.mark.asyncio
+async def test_enable_disable_delete_plugin_reject_non_admin():
+    """Non-admin keys cannot enable, disable, or delete catalog entries."""
+    name = "trusted-plugin-2"
+    await register_plugin(
+        request=RegisterPluginRequest(name=name, source=_GIT_SUBDIR_SOURCE, version="1.0.0"),
+        user_api_key_dict=_USER,
+    )
+
+    for coro in (
+        enable_plugin(plugin_name=name, user_api_key_dict=_NON_ADMIN_USER),
+        disable_plugin(plugin_name=name, user_api_key_dict=_NON_ADMIN_USER),
+        delete_plugin(plugin_name=name, user_api_key_dict=_NON_ADMIN_USER),
+    ):
+        with pytest.raises(HTTPException) as exc_info:
+            await coro
+        assert exc_info.value.status_code == 403
+
+    table = litellm.proxy.proxy_server.prisma_client.db.litellm_claudecodeplugintable
+    assert (await table.find_unique(where={"name": name})).enabled is True

From 168ee2d9fdbd63cb3f2f4fd6de665595cbcbd8b8 Mon Sep 17 00:00:00 2001
From: ozolam <ozlamdan@gmail.com>
Date: Tue, 11 Aug 2026 22:38:25 +0300
Subject: [PATCH 13/93] fix(claude-code): use Annotated dependency style to
 stay within B008 lint budget

---
 .../claude_code_marketplace.py                | 30 ++++++++++++-------
 1 file changed, 20 insertions(+), 10 deletions(-)

diff --git a/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_marketplace.py b/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_marketplace.py
index 4730372511a..09ba2c93ea0 100644
--- a/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_marketplace.py
+++ b/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_marketplace.py
@@ -6,21 +6,21 @@ Plugins are stored as metadata + git source references in LiteLLM database.
 Actual plugin files are hosted on GitHub/GitLab/Bitbucket.
 
 Endpoints:
-/claude-code/marketplace.json  - GET  - List plugins for Claude Code discovery
-/claude-code/plugins           - POST - Register a new plugin (create-only)
-/claude-code/plugins           - GET  - List plugins (admin)
-/claude-code/plugins/{name}    - GET  - Get plugin details
-/claude-code/plugins/{name}    - PUT  - Update an existing plugin
-/claude-code/plugins/{name}/enable  - POST - Enable a plugin
-/claude-code/plugins/{name}/disable - POST - Disable a plugin
-/claude-code/plugins/{name}    - DELETE - Delete a plugin
+/claude-code/marketplace.json  - GET  - List plugins for Claude Code discovery (unauthenticated)
+/claude-code/plugins           - POST - Register a new plugin (create-only, proxy admin only)
+/claude-code/plugins           - GET  - List plugins (any authenticated key)
+/claude-code/plugins/{name}    - GET  - Get plugin details (any authenticated key)
+/claude-code/plugins/{name}    - PUT  - Update an existing plugin (proxy admin only)
+/claude-code/plugins/{name}/enable  - POST - Enable a plugin (proxy admin only)
+/claude-code/plugins/{name}/disable - POST - Disable a plugin (proxy admin only)
+/claude-code/plugins/{name}    - DELETE - Delete a plugin (proxy admin only)
 """
 
 import json
 import re
 from collections.abc import Mapping, Sequence
 from datetime import datetime, timezone
-from typing import Final, Protocol, TypedDict
+from typing import Annotated, Final, Protocol, TypedDict
 
 from fastapi import APIRouter, Depends, HTTPException
 from fastapi.responses import JSONResponse
@@ -255,6 +255,8 @@ async def register_plugin(
     the same name already exists it returns 409 Conflict; use
     PUT /claude-code/plugins/{plugin_name} to update an existing plugin.
 
+    Requires a proxy admin API key.
+
     Parameters:
         - name: Plugin name (kebab-case)
         - source: Git source reference (github, url, or git-subdir format)
@@ -483,7 +485,7 @@ async def get_plugin(
 async def update_plugin(
     plugin_name: str,
     request: UpdatePluginRequest,
-    user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
+    user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)],
 ):
     """
     Update an existing plugin in the LiteLLM marketplace.
@@ -497,6 +499,8 @@ async def update_plugin(
     Returns 404 if no plugin with the given name exists; use
     POST /claude-code/plugins to create a new plugin.
 
+    Requires a proxy admin API key.
+
     Parameters:
         - plugin_name: Name of the plugin to update (path parameter)
         - source: Git source reference (github, url, or git-subdir format)
@@ -584,6 +588,8 @@ async def enable_plugin(
     """
     Enable a disabled plugin.
 
+    Requires a proxy admin API key.
+
     Parameters:
         - plugin_name: The name of the plugin to enable
     """
@@ -631,6 +637,8 @@ async def disable_plugin(
     """
     Disable a plugin without deleting it.
 
+    Requires a proxy admin API key.
+
     Parameters:
         - plugin_name: The name of the plugin to disable
     """
@@ -678,6 +686,8 @@ async def delete_plugin(
     """
     Delete a plugin from the marketplace.
 
+    Requires a proxy admin API key.
+
     Parameters:
         - plugin_name: The name of the plugin to delete
     """

From 3db1759d04ba8d888a08dbe8308cc75a348141d8 Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Thu, 13 Aug 2026 19:45:32 +0000
Subject: [PATCH 14/93] fix(bedrock): stop emitting an empty assistant delta
 after the finish_reason chunk

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/llms/bedrock/chat/invoke_handler.py   |  8 +++-
 .../llms/bedrock/chat/test_invoke_handler.py  | 46 +++++++++++++++++++
 2 files changed, 52 insertions(+), 2 deletions(-)

diff --git a/litellm/llms/bedrock/chat/invoke_handler.py b/litellm/llms/bedrock/chat/invoke_handler.py
index 8d2b3dae71b..595884ae630 100644
--- a/litellm/llms/bedrock/chat/invoke_handler.py
+++ b/litellm/llms/bedrock/chat/invoke_handler.py
@@ -561,6 +561,10 @@ class AWSEventStreamDecoder:
             elif "usage" in chunk_data:
                 usage = converse_config._transform_usage(chunk_data.get("usage", {}))
 
+            carries_message_content: Final = any(
+                key in chunk_data for key in ("start", "delta", "contentBlockIndex", "stopReason")
+            )
+
             model_response_provider_specific_fields: Final = {}
             if "trace" in chunk_data:
                 trace: Final = chunk_data.get("trace")
@@ -571,8 +575,8 @@ class AWSEventStreamDecoder:
                         finish_reason=finish_reason,
                         index=0,  # Always 0 - Bedrock never returns multiple choices
                         delta=Delta(
-                            content=text,
-                            role="assistant",
+                            content=text if carries_message_content else None,
+                            role="assistant" if carries_message_content else None,
                             tool_calls=[tool_use] if tool_use else None,
                             provider_specific_fields=(provider_specific_fields if provider_specific_fields else None),
                             thinking_blocks=thinking_blocks,
diff --git a/tests/test_litellm/llms/bedrock/chat/test_invoke_handler.py b/tests/test_litellm/llms/bedrock/chat/test_invoke_handler.py
index ee50b9db015..9783976db4a 100644
--- a/tests/test_litellm/llms/bedrock/chat/test_invoke_handler.py
+++ b/tests/test_litellm/llms/bedrock/chat/test_invoke_handler.py
@@ -1,3 +1,4 @@
+import datetime
 import os
 import sys
 from unittest.mock import AsyncMock, MagicMock
@@ -8,6 +9,8 @@ sys.path.insert(
     0, os.path.abspath("../../../../..")
 )  # Adds the parent directory to the system path
 
+from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper
 from litellm.llms.bedrock.chat.invoke_handler import (
     AWSEventStreamDecoder,
     make_call,
@@ -293,3 +296,46 @@ def test_make_sync_call_honors_explicit_stream_chunk_size():
 
     response.iter_bytes.assert_called_once_with(chunk_size=2048)
 
+
+@pytest.mark.asyncio
+async def test_converse_stream_ends_on_finish_reason_chunk():
+    """The usage-only metadata event Bedrock sends after messageStop must not reach the caller as an extra
+    assistant delta following the finish_reason chunk."""
+    model = "anthropic.claude-sonnet-4-6"
+    events = (
+        {"role": "assistant"},
+        {"contentBlockIndex": 0, "delta": {"text": "Hello"}},
+        {"contentBlockIndex": 0, "delta": {"text": " world"}},
+        {"contentBlockIndex": 0},
+        {"stopReason": "end_turn"},
+        {"usage": {"inputTokens": 10, "outputTokens": 5, "totalTokens": 15}, "metrics": {"latencyMs": 100}},
+    )
+
+    async def bedrock_stream():
+        decoder = AWSEventStreamDecoder(model=model)
+        for event in events:
+            yield decoder._chunk_parser(chunk_data=event)
+
+    wrapper = CustomStreamWrapper(
+        completion_stream=bedrock_stream(),
+        model=model,
+        custom_llm_provider="bedrock",
+        logging_obj=LiteLLMLoggingObj(
+            model=model,
+            messages=[{"role": "user", "content": "hi"}],
+            stream=True,
+            call_type="completion",
+            start_time=datetime.datetime.now(),
+            litellm_call_id="1234",
+            function_id="1234",
+        ),
+    )
+
+    chunks = [chunk async for chunk in wrapper]
+
+    assert [choice.finish_reason for chunk in chunks for choice in chunk.choices].count("stop") == 1
+    assert chunks[-1].choices[0].finish_reason == "stop", (
+        f"stream must end on the finish_reason chunk, got trailing {chunks[-1].model_dump(exclude_none=True)}"
+    )
+    assert any(getattr(chunk, "usage", None) is not None for chunk in wrapper.chunks)
+

From b6ee13803d1c21bc0b07dac6e6b9ad2ede7ad7aa Mon Sep 17 00:00:00 2001
From: HarryZhou <2373256746@qq.com>
Date: Sun, 9 Aug 2026 22:59:25 +0800
Subject: [PATCH 15/93] fix(responses-bridge): preserve reasoning input items
 as reasoning_content

---
 .../transformation.py                         | 164 +++++++++++++++++-
 .../test_reasoning_input_item_preservation.py | 147 ++++++++++++++++
 2 files changed, 310 insertions(+), 1 deletion(-)
 create mode 100644 tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py

diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index 4892e3b348c..5d3ed0477e3 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -557,7 +557,108 @@ class LiteLLMCompletionResponsesConfig:
                     continue
 
                 messages.extend(chat_completion_messages)
-        return messages
+        return LiteLLMCompletionResponsesConfig._merge_reasoning_only_assistant_messages(messages)
+
+    @staticmethod
+    def _merge_reasoning_only_assistant_messages(
+        messages: list[
+            AllMessageValues
+            | GenericChatCompletionMessage
+            | ChatCompletionMessageToolCall
+            | ChatCompletionResponseMessage
+        ],
+    ) -> list[
+        AllMessageValues | GenericChatCompletionMessage | ChatCompletionMessageToolCall | ChatCompletionResponseMessage
+    ]:
+        """
+        Responses API emits prior-turn reasoning as its own ``reasoning`` input
+        item, which becomes a standalone assistant message with
+        ``content=None`` + ``reasoning_content``. Chat-completions providers
+        (e.g. DeepSeek V4, Kimi K2.6) expect the chain-of-thought on the
+        assistant message that carries the answer or tool calls. This pass
+        merges standalone reasoning-only assistant messages into the
+        immediately following assistant message.
+
+        If the reasoning item is not followed by an assistant message (e.g. a
+        stateless chain replays ``reasoning`` + ``user``), the standalone
+        reasoning message is preserved so the reasoning is still passed back.
+        """
+
+        def _role(msg: Any) -> str:
+            if isinstance(msg, dict):
+                return str(msg.get("role") or "")
+            return str(getattr(msg, "role", "") or "")
+
+        def _reasoning_text(msg: Any) -> str | None:
+            if isinstance(msg, dict):
+                value = msg.get("reasoning_content")
+            else:
+                value = getattr(msg, "reasoning_content", None)
+            return value if isinstance(value, str) and value else None
+
+        def _content(msg: Any) -> Any:
+            if isinstance(msg, dict):
+                return msg.get("content")
+            return getattr(msg, "content", None)
+
+        def _tool_calls(msg: Any) -> Any:
+            if isinstance(msg, dict):
+                return msg.get("tool_calls")
+            return getattr(msg, "tool_calls", None)
+
+        merged: list[
+            AllMessageValues
+            | GenericChatCompletionMessage
+            | ChatCompletionMessageToolCall
+            | ChatCompletionResponseMessage
+        ] = []
+        pending_reasoning: list[str] = []
+
+        for msg in messages:
+            if (
+                _role(msg) == "assistant"
+                and _content(msg) is None
+                and not _tool_calls(msg)
+                and _reasoning_text(msg) is not None
+            ):
+                pending_reasoning.append(_reasoning_text(msg) or "")
+                continue
+
+            if pending_reasoning and _role(msg) == "assistant":
+                combined = "\n".join(pending_reasoning)
+                existing = _reasoning_text(msg)
+                if existing:
+                    combined = existing + "\n" + combined
+                if isinstance(msg, dict):
+                    msg["reasoning_content"] = combined
+                else:
+                    setattr(msg, "reasoning_content", combined)
+                pending_reasoning = []
+            elif pending_reasoning:
+                # Not followed by an assistant message — keep the reasoning
+                # standalone instead of dropping it.
+                for text in pending_reasoning:
+                    merged.append(
+                        ChatCompletionResponseMessage(
+                            role="assistant",
+                            content=None,
+                            reasoning_content=text,
+                        )
+                    )
+                pending_reasoning = []
+
+            merged.append(msg)
+
+        for text in pending_reasoning:
+            merged.append(
+                ChatCompletionResponseMessage(
+                    role="assistant",
+                    content=None,
+                    reasoning_content=text,
+                )
+            )
+
+        return merged
 
     @staticmethod
     def _merged_trailing_assistant_message(
@@ -1026,6 +1127,25 @@ class LiteLLMCompletionResponsesConfig:
             return LiteLLMCompletionResponsesConfig._transform_responses_api_function_call_to_chat_completion_message(
                 function_call=input_item
             )
+        elif input_item.get("type") == "reasoning":
+            # A ResponseReasoningItemParam carries the prior-turn chain-of-thought.
+            # Chat-completions providers (DeepSeek V4, Kimi K2.6, ...) expect this
+            # to be replayed as `reasoning_content` on an assistant message, not as
+            # visible `content` (prompt pollution) and not dropped (DeepSeek V4
+            # rejects multi-turn requests with a missing `reasoning_content`).
+            reasoning_text = LiteLLMCompletionResponsesConfig._extract_reasoning_text_from_input_item(input_item)
+            if not reasoning_text:
+                # No plaintext reasoning is available (e.g. encrypted_content only).
+                # Chat-completions providers cannot consume opaque encrypted blobs,
+                # so skip the item instead of polluting the prompt.
+                return []
+            return [
+                ChatCompletionResponseMessage(
+                    role="assistant",
+                    content=None,
+                    reasoning_content=reasoning_text,
+                )
+            ]
         else:
             content: Final[object] = input_item.get("content")
             # Handle None content: Responses API allows None content, but GenericChatCompletionMessage requires content
@@ -1041,6 +1161,48 @@ class LiteLLMCompletionResponsesConfig:
                 )
             ]
 
+    @staticmethod
+    def _extract_reasoning_text_from_input_item(input_item: Mapping[str, object]) -> str | None:
+        """
+        Extract plaintext reasoning from a ResponseReasoningItemParam.
+
+        Handles:
+        - content as a string
+        - content as a list of blocks (output_text / summary_text / text)
+        - summary as a list of summary_text blocks (fallback)
+
+        Returns None when only opaque forms (e.g. encrypted_content) are present.
+        """
+        content: Final[object] = input_item.get("content")
+        if isinstance(content, str) and content.strip():
+            return content
+        if isinstance(content, list):
+            text_parts: list[str] = []
+            for block in content:
+                if not isinstance(block, Mapping):
+                    continue
+                block_type = block.get("type")
+                if block_type in ("encrypted_content", "redacted_thinking"):
+                    continue
+                text = block.get("text")
+                if isinstance(text, str) and text.strip():
+                    text_parts.append(text.strip())
+            if text_parts:
+                return "\n".join(text_parts)
+
+        summary: Final[object] = input_item.get("summary")
+        if isinstance(summary, list):
+            text_parts = []
+            for block in summary:
+                if not isinstance(block, Mapping):
+                    continue
+                text = block.get("text")
+                if isinstance(text, str) and text.strip():
+                    text_parts.append(text.strip())
+            if text_parts:
+                return "\n".join(text_parts)
+        return None
+
     @staticmethod
     def _is_input_item_tool_call_output(input_item: Mapping[str, object]) -> bool:
         """
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py b/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
new file mode 100644
index 00000000000..5fcd4df3ff8
--- /dev/null
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
@@ -0,0 +1,147 @@
+"""
+Unit tests for preserving prior-turn ``reasoning`` input items when the
+Responses API is bridged to chat completions.
+
+Without this handling, a ``ResponseReasoningItemParam`` falls through to the
+generic message branch, polluting the prompt as visible assistant ``content``
+or being silently dropped. Chat-completions providers such as DeepSeek V4 and
+Kimi K2.6 require the chain-of-thought to be replayed as ``reasoning_content``
+on an assistant message.
+"""
+
+from litellm.responses.litellm_completion_transformation.transformation import (
+    LiteLLMCompletionResponsesConfig,
+)
+
+
+def _transform_item(item):
+    return LiteLLMCompletionResponsesConfig._transform_responses_api_input_item_to_chat_completion_message(
+        input_item=item
+    )
+
+
+def _transform_input(input_items):
+    return LiteLLMCompletionResponsesConfig._transform_response_input_param_to_chat_completion_message(
+        input=input_items
+    )
+
+
+class TestReasoningInputItemHandler:
+    """Reasoning input items map to assistant ``reasoning_content``."""
+
+    def test_reasoning_item_with_output_text_content(self):
+        """Standard Responses-API reasoning item with output_text blocks."""
+        item = {
+            "type": "reasoning",
+            "id": "rs_abc",
+            "summary": [],
+            "content": [{"type": "output_text", "text": "step 1: think about X"}],
+        }
+        messages = _transform_item(item)
+        assert len(messages) == 1
+        assert messages[0]["role"] == "assistant"
+        assert messages[0]["content"] is None
+        assert messages[0]["reasoning_content"] == "step 1: think about X"
+
+    def test_reasoning_item_with_string_content(self):
+        """Variant: reasoning content as a plain string."""
+        item = {"type": "reasoning", "id": "rs_1", "content": "step 1: ..."}
+        messages = _transform_item(item)
+        assert messages[0]["reasoning_content"] == "step 1: ..."
+
+    def test_reasoning_item_with_summary_only(self):
+        """SDK form: reasoning carried in summary list, no content."""
+        item = {
+            "type": "reasoning",
+            "id": "rs_2",
+            "summary": [{"type": "summary_text", "text": "..."}],
+        }
+        messages = _transform_item(item)
+        assert messages[0]["reasoning_content"] == "..."
+
+    def test_reasoning_item_with_encrypted_content_only_dropped(self):
+        """Opaque encrypted reasoning cannot be forwarded to chat completions."""
+        item = {"type": "reasoning", "id": "rs_3", "encrypted_content": "opaque-blob"}
+        assert _transform_item(item) == []
+
+    def test_reasoning_item_empty_dropped(self):
+        """Reasoning item with neither content nor summary drops cleanly."""
+        assert _transform_item({"type": "reasoning", "id": "rs_4"}) == []
+
+
+class TestReasoningInputItemMerging:
+    """Standalone reasoning messages merge into the following assistant turn."""
+
+    def test_reasoning_merged_into_following_assistant_message(self):
+        """Reasoning + assistant answer become one assistant message."""
+        messages = _transform_input(
+            [
+                {
+                    "type": "reasoning",
+                    "id": "rs_1",
+                    "content": [{"type": "output_text", "text": "secret reasoning"}],
+                },
+                {"type": "message", "role": "assistant", "content": "The answer."},
+            ]
+        )
+        assert len(messages) == 1
+        assert messages[0]["role"] == "assistant"
+        assert messages[0]["content"] == "The answer."
+        assert messages[0]["reasoning_content"] == "secret reasoning"
+
+    def test_reasoning_preserved_when_followed_by_user_message(self):
+        """Stateless chain: reasoning + user prompt keeps the reasoning turn."""
+        messages = _transform_input(
+            [
+                {
+                    "type": "reasoning",
+                    "id": "rs_1",
+                    "content": [{"type": "output_text", "text": "secret BLUEBERRY"}],
+                },
+                {"role": "user", "content": "What is the secret word?"},
+            ]
+        )
+        assert len(messages) == 2
+        assert messages[0]["role"] == "assistant"
+        assert messages[0]["content"] is None
+        assert messages[0]["reasoning_content"] == "secret BLUEBERRY"
+        assert messages[1]["role"] == "user"
+
+    def test_reasoning_merged_into_function_call_assistant(self):
+        """Reasoning + function_call becomes one assistant tool-call message."""
+        messages = _transform_input(
+            [
+                {
+                    "type": "reasoning",
+                    "id": "rs_1",
+                    "content": [{"type": "output_text", "text": "I should look this up"}],
+                },
+                {
+                    "type": "function_call",
+                    "call_id": "call_1",
+                    "name": "lookup",
+                    "arguments": '{"cwe": "79"}',
+                },
+            ]
+        )
+        assert len(messages) == 1
+        assert messages[0]["role"] == "assistant"
+        assert messages[0]["reasoning_content"] == "I should look this up"
+        assert len(messages[0]["tool_calls"]) == 1
+
+
+class TestNonReasoningInputItemUnchanged:
+    """Non-reasoning items still flow through the existing branches."""
+
+    def test_user_message_unchanged(self):
+        item = {"role": "user", "content": "hello"}
+        out = _transform_item(item)
+        assert len(out) == 1
+        assert out[0]["role"] == "user"
+
+    def test_assistant_message_unchanged(self):
+        item = {"role": "assistant", "content": "hi"}
+        out = _transform_item(item)
+        assert len(out) == 1
+        assert out[0]["role"] == "assistant"
+        assert out[0]["content"] == "hi"

From 3a77556dc14660e88a7d20f54e9762c39f24b749 Mon Sep 17 00:00:00 2001
From: HarryZhou <2373256746@qq.com>
Date: Mon, 10 Aug 2026 00:45:25 +0800
Subject: [PATCH 16/93] fix(responses-bridge): preserve reasoning merge order
 when assistant already has reasoning_content

---
 .../transformation.py                                |  2 +-
 .../test_reasoning_input_item_preservation.py        | 12 ++++++++++++
 2 files changed, 13 insertions(+), 1 deletion(-)

diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index 5d3ed0477e3..0604c3636ff 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -628,7 +628,7 @@ class LiteLLMCompletionResponsesConfig:
                 combined = "\n".join(pending_reasoning)
                 existing = _reasoning_text(msg)
                 if existing:
-                    combined = existing + "\n" + combined
+                    combined = combined + "\n" + existing
                 if isinstance(msg, dict):
                     msg["reasoning_content"] = combined
                 else:
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py b/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
index 5fcd4df3ff8..ecc024b7d04 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
@@ -129,6 +129,18 @@ class TestReasoningInputItemMerging:
         assert messages[0]["reasoning_content"] == "I should look this up"
         assert len(messages[0]["tool_calls"]) == 1
 
+    def test_reasoning_merged_into_assistant_with_existing_reasoning_content(self):
+        """Old reasoning precedes existing reasoning on the target assistant turn."""
+        messages = LiteLLMCompletionResponsesConfig._merge_reasoning_only_assistant_messages(
+            [
+                {"role": "assistant", "content": None, "reasoning_content": "old reasoning"},
+                {"role": "assistant", "content": "The answer.", "reasoning_content": "new reasoning"},
+            ]
+        )
+        assert len(messages) == 1
+        assert messages[0]["content"] == "The answer."
+        assert messages[0]["reasoning_content"] == "old reasoning\nnew reasoning"
+
 
 class TestNonReasoningInputItemUnchanged:
     """Non-reasoning items still flow through the existing branches."""

From 5911124f1dbba1e9c58f3b53619c3f875752a20f Mon Sep 17 00:00:00 2001
From: HarryZhou <2373256746@qq.com>
Date: Mon, 10 Aug 2026 00:58:47 +0800
Subject: [PATCH 17/93] fix(responses-bridge): satisfy ruff strict-rule budget
 in reasoning merge

---
 .../transformation.py                         | 26 +++++++++++--------
 1 file changed, 15 insertions(+), 11 deletions(-)

diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index 0604c3636ff..2c506d4a4c7 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -584,24 +584,24 @@ class LiteLLMCompletionResponsesConfig:
         reasoning message is preserved so the reasoning is still passed back.
         """
 
-        def _role(msg: Any) -> str:
+        def _role(msg: object) -> str:
             if isinstance(msg, dict):
                 return str(msg.get("role") or "")
             return str(getattr(msg, "role", "") or "")
 
-        def _reasoning_text(msg: Any) -> str | None:
+        def _reasoning_text(msg: object) -> str | None:
             if isinstance(msg, dict):
                 value = msg.get("reasoning_content")
             else:
                 value = getattr(msg, "reasoning_content", None)
             return value if isinstance(value, str) and value else None
 
-        def _content(msg: Any) -> Any:
+        def _content(msg: object) -> object | None:
             if isinstance(msg, dict):
                 return msg.get("content")
             return getattr(msg, "content", None)
 
-        def _tool_calls(msg: Any) -> Any:
+        def _tool_calls(msg: object) -> object | None:
             if isinstance(msg, dict):
                 return msg.get("tool_calls")
             return getattr(msg, "tool_calls", None)
@@ -632,31 +632,35 @@ class LiteLLMCompletionResponsesConfig:
                 if isinstance(msg, dict):
                     msg["reasoning_content"] = combined
                 else:
-                    setattr(msg, "reasoning_content", combined)
+                    setattr(msg, "reasoning_content", combined)  # noqa: B010
                 pending_reasoning = []
             elif pending_reasoning:
                 # Not followed by an assistant message — keep the reasoning
                 # standalone instead of dropping it.
-                for text in pending_reasoning:
-                    merged.append(
+                merged.extend(
+                    [
                         ChatCompletionResponseMessage(
                             role="assistant",
                             content=None,
                             reasoning_content=text,
                         )
-                    )
+                        for text in pending_reasoning
+                    ]
+                )
                 pending_reasoning = []
 
             merged.append(msg)
 
-        for text in pending_reasoning:
-            merged.append(
+        merged.extend(
+            [
                 ChatCompletionResponseMessage(
                     role="assistant",
                     content=None,
                     reasoning_content=text,
                 )
-            )
+                for text in pending_reasoning
+            ]
+        )
 
         return merged
 

From 438c1850fe1223feec1e2e6e5b48f0a6c15a1328 Mon Sep 17 00:00:00 2001
From: HarryZhou <2373256746@qq.com>
Date: Mon, 10 Aug 2026 01:09:26 +0800
Subject: [PATCH 18/93] fix(responses-bridge): satisfy type-discipline budget
 in reasoning merge

---
 .../transformation.py                         | 34 ++++++++++---------
 1 file changed, 18 insertions(+), 16 deletions(-)

diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index 2c506d4a4c7..e3e62ab3c55 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -561,13 +561,13 @@ class LiteLLMCompletionResponsesConfig:
 
     @staticmethod
     def _merge_reasoning_only_assistant_messages(
-        messages: list[
+        messages: list[  # mutable-ok: input sequence
             AllMessageValues
             | GenericChatCompletionMessage
             | ChatCompletionMessageToolCall
             | ChatCompletionResponseMessage
         ],
-    ) -> list[
+    ) -> list[  # mutable-ok: fresh merged list
         AllMessageValues | GenericChatCompletionMessage | ChatCompletionMessageToolCall | ChatCompletionResponseMessage
     ]:
         """
@@ -591,9 +591,9 @@ class LiteLLMCompletionResponsesConfig:
 
         def _reasoning_text(msg: object) -> str | None:
             if isinstance(msg, dict):
-                value = msg.get("reasoning_content")
+                value = msg.get("reasoning_content")  # rebind-ok: branch lookup
             else:
-                value = getattr(msg, "reasoning_content", None)
+                value = getattr(msg, "reasoning_content", None)  # rebind-ok: branch lookup
             return value if isinstance(value, str) and value else None
 
         def _content(msg: object) -> object | None:
@@ -606,13 +606,13 @@ class LiteLLMCompletionResponsesConfig:
                 return msg.get("tool_calls")
             return getattr(msg, "tool_calls", None)
 
-        merged: list[
+        merged: list[  # mutable-ok: accumulator  # rebind-ok: accumulator
             AllMessageValues
             | GenericChatCompletionMessage
             | ChatCompletionMessageToolCall
             | ChatCompletionResponseMessage
-        ] = []
-        pending_reasoning: list[str] = []
+        ] = []  # mutable-ok: accumulator
+        pending_reasoning: list[str] = []  # mutable-ok: accumulator  # rebind-ok: accumulator
 
         for msg in messages:
             if (
@@ -633,11 +633,11 @@ class LiteLLMCompletionResponsesConfig:
                     msg["reasoning_content"] = combined
                 else:
                     setattr(msg, "reasoning_content", combined)  # noqa: B010
-                pending_reasoning = []
+                pending_reasoning = []  # mutable-ok: reset accumulator
             elif pending_reasoning:
                 # Not followed by an assistant message — keep the reasoning
                 # standalone instead of dropping it.
-                merged.extend(
+                merged.extend(  # mutable-ok: append reasoning messages
                     [
                         ChatCompletionResponseMessage(
                             role="assistant",
@@ -647,11 +647,11 @@ class LiteLLMCompletionResponsesConfig:
                         for text in pending_reasoning
                     ]
                 )
-                pending_reasoning = []
+                pending_reasoning = []  # mutable-ok: reset accumulator
 
             merged.append(msg)
 
-        merged.extend(
+        merged.extend(  # mutable-ok: append trailing reasoning
             [
                 ChatCompletionResponseMessage(
                     role="assistant",
@@ -1137,13 +1137,15 @@ class LiteLLMCompletionResponsesConfig:
             # to be replayed as `reasoning_content` on an assistant message, not as
             # visible `content` (prompt pollution) and not dropped (DeepSeek V4
             # rejects multi-turn requests with a missing `reasoning_content`).
-            reasoning_text = LiteLLMCompletionResponsesConfig._extract_reasoning_text_from_input_item(input_item)
+            reasoning_text = LiteLLMCompletionResponsesConfig._extract_reasoning_text_from_input_item(  # rebind-ok: extraction result
+                input_item
+            )
             if not reasoning_text:
                 # No plaintext reasoning is available (e.g. encrypted_content only).
                 # Chat-completions providers cannot consume opaque encrypted blobs,
                 # so skip the item instead of polluting the prompt.
-                return []
-            return [
+                return []  # mutable-ok: empty drop result
+            return [  # mutable-ok: single message result
                 ChatCompletionResponseMessage(
                     role="assistant",
                     content=None,
@@ -1181,7 +1183,7 @@ class LiteLLMCompletionResponsesConfig:
         if isinstance(content, str) and content.strip():
             return content
         if isinstance(content, list):
-            text_parts: list[str] = []
+            text_parts: list[str] = []  # mutable-ok: text accumulator  # rebind-ok: text accumulator
             for block in content:
                 if not isinstance(block, Mapping):
                     continue
@@ -1196,7 +1198,7 @@ class LiteLLMCompletionResponsesConfig:
 
         summary: Final[object] = input_item.get("summary")
         if isinstance(summary, list):
-            text_parts = []
+            text_parts = []  # mutable-ok: text accumulator  # rebind-ok: text accumulator
             for block in summary:
                 if not isinstance(block, Mapping):
                     continue

From de95372dfbd7bbba8c478815340dd49c1b21da11 Mon Sep 17 00:00:00 2001
From: HarryZhou <2373256746@qq.com>
Date: Mon, 10 Aug 2026 01:24:24 +0800
Subject: [PATCH 19/93] fix(responses-bridge): type-safe reasoning_content
 assignment in merge pass

---
 .../litellm_completion_transformation/transformation.py         | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index e3e62ab3c55..d7b6b8c7b8f 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -630,7 +630,7 @@ class LiteLLMCompletionResponsesConfig:
                 if existing:
                     combined = combined + "\n" + existing
                 if isinstance(msg, dict):
-                    msg["reasoning_content"] = combined
+                    cast(dict[str, Any], msg)["reasoning_content"] = combined  # cast-ok: mutable reasoning carrier
                 else:
                     setattr(msg, "reasoning_content", combined)  # noqa: B010
                 pending_reasoning = []  # mutable-ok: reset accumulator

From 2d4e6afe1c7d6d3233a18668d53fafe4cffa50b3 Mon Sep 17 00:00:00 2001
From: HarryZhou <2373256746@qq.com>
Date: Tue, 18 Aug 2026 21:11:29 +0800
Subject: [PATCH 20/93] fix(guardrails): inspect responses reasoning content
 and summary text

---
 litellm/proxy/guardrails/_content_utils.py    | 59 +++++++++++++------
 .../transformation.py                         |  6 +-
 .../proxy/guardrails/test_content_utils.py    | 54 +++++++++++++++++
 3 files changed, 100 insertions(+), 19 deletions(-)

diff --git a/litellm/proxy/guardrails/_content_utils.py b/litellm/proxy/guardrails/_content_utils.py
index 6ed6f0013df..ae92adcb1ee 100644
--- a/litellm/proxy/guardrails/_content_utils.py
+++ b/litellm/proxy/guardrails/_content_utils.py
@@ -8,7 +8,7 @@ skip the other shapes — these helpers normalise that so every hook sees
 every text fragment.
 """
 
-from collections.abc import Callable, Iterator
+from collections.abc import Callable, Iterator, Mapping
 from typing import Any, Final
 
 # Call types whose body carries free-form chat / prompt text that
@@ -33,7 +33,9 @@ def is_text_content_call_type(call_type: str) -> bool:
     return call_type in TEXT_CONTENT_CALL_TYPES
 
 
-TEXT_PART_TYPES: Final[frozenset[str]] = frozenset({"text", "input_text", "output_text"})
+TEXT_PART_TYPES: Final[frozenset[str]] = frozenset(
+    {"text", "input_text", "output_text", "summary_text", "reasoning_text"}
+)
 
 # Responses-API item types whose ``output`` field carries user/tool text
 # that guardrails should inspect.  ``function_call_output`` is the
@@ -42,6 +44,16 @@ TEXT_PART_TYPES: Final[frozenset[str]] = frozenset({"text", "input_text", "outpu
 _OUTPUT_ITEM_TYPES: Final[frozenset[str]] = frozenset({"function_call_output", "custom_tool_call_output"})
 
 
+def _part_text(part: Mapping[str, object]) -> str | None:
+    """Return non-empty plaintext from any content part that carries ``text``."""
+    if not isinstance(part, dict):
+        return None
+    text = part.get("text")
+    if isinstance(text, str) and text:
+        return text
+    return None
+
+
 def _iter_text_parts_in_content(content: Any) -> Iterator[str]:
     """Yield text fragments from a ``message.content`` value (string or
     multimodal list). Non-text parts (images, audio, …) are skipped."""
@@ -58,10 +70,9 @@ def _iter_text_parts_in_content(content: Any) -> Iterator[str]:
                 continue
             if not isinstance(part, dict):
                 continue
-            if part.get("type") in TEXT_PART_TYPES:
-                text = part.get("text")
-                if isinstance(text, str) and text:
-                    yield text
+            text = _part_text(part)
+            if text is not None:
+                yield text
 
 
 def _coerce_input_to_messages(input_value: Any) -> list[dict[str, Any]]:
@@ -75,8 +86,23 @@ def _coerce_input_to_messages(input_value: Any) -> list[dict[str, Any]]:
         if isinstance(item, str):
             messages.append({"role": "user", "content": item})
         elif isinstance(item, dict):
-            if item.get("type") in TEXT_PART_TYPES:
+            if _part_text(item) is not None:
                 messages.append({"role": item.get("role") or "user", "content": [item]})
+            elif item.get("type") == "reasoning":
+                if "content" in item:
+                    messages.append(
+                        {  # mutable-ok: append reasoning content
+                            "role": item.get("role") or "assistant",
+                            "content": item["content"],
+                        }
+                    )
+                if isinstance(item.get("summary"), list):
+                    messages.append(
+                        {  # mutable-ok: append reasoning summary
+                            "role": item.get("role") or "assistant",
+                            "content": item["summary"],
+                        }
+                    )
             elif "content" in item:
                 messages.append({"role": item.get("role") or "user", "content": item["content"]})
             elif item.get("type") in _OUTPUT_ITEM_TYPES and "output" in item:
@@ -126,12 +152,7 @@ def walk_user_text(data: dict[str, Any], visit: Callable[[str], str]) -> int:
                 if isinstance(part, str) and part:
                     visited += 1
                     new_parts.append(visit(part))
-                elif (
-                    isinstance(part, dict)
-                    and part.get("type") in TEXT_PART_TYPES
-                    and isinstance(part.get("text"), str)
-                    and part["text"]
-                ):
+                elif isinstance(part, dict) and _part_text(part) is not None:
                     visited += 1
                     new_parts.append({**part, "text": visit(part["text"])})
                 else:
@@ -158,10 +179,14 @@ def walk_user_text(data: dict[str, Any], visit: Callable[[str], str]) -> int:
                     visited += 1
                     input_value[idx] = visit(item)
             elif isinstance(item, dict):
-                if item.get("type") in TEXT_PART_TYPES:
-                    if isinstance(item.get("text"), str) and item["text"]:
-                        visited += 1
-                        input_value[idx] = {**item, "text": visit(item["text"])}
+                if _part_text(item) is not None:
+                    visited += 1
+                    input_value[idx] = {**item, "text": visit(item["text"])}  # mutable-ok: rewrite text part in place
+                elif item.get("type") == "reasoning":
+                    if "content" in item:
+                        item["content"] = _rewrite_content(item["content"])
+                    if isinstance(item.get("summary"), list):
+                        item["summary"] = _rewrite_content(item["summary"])
                 elif "content" in item:
                     item["content"] = _rewrite_content(item["content"])
                 elif item.get("type") in _OUTPUT_ITEM_TYPES and "output" in item:
diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index d7b6b8c7b8f..c5f40242bfd 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -638,7 +638,7 @@ class LiteLLMCompletionResponsesConfig:
                 # Not followed by an assistant message — keep the reasoning
                 # standalone instead of dropping it.
                 merged.extend(  # mutable-ok: append reasoning messages
-                    [
+                    [  # mutable-ok: append reasoning messages
                         ChatCompletionResponseMessage(
                             role="assistant",
                             content=None,
@@ -652,7 +652,7 @@ class LiteLLMCompletionResponsesConfig:
             merged.append(msg)
 
         merged.extend(  # mutable-ok: append trailing reasoning
-            [
+            [  # mutable-ok: append trailing reasoning
                 ChatCompletionResponseMessage(
                     role="assistant",
                     content=None,
@@ -1196,6 +1196,8 @@ class LiteLLMCompletionResponsesConfig:
             if text_parts:
                 return "\n".join(text_parts)
 
+        # Guardrail traversal in litellm/proxy/guardrails/_content_utils.py
+        # inspects and rewrites these summary blocks before they are forwarded.
         summary: Final[object] = input_item.get("summary")
         if isinstance(summary, list):
             text_parts = []  # mutable-ok: text accumulator  # rebind-ok: text accumulator
diff --git a/tests/test_litellm/proxy/guardrails/test_content_utils.py b/tests/test_litellm/proxy/guardrails/test_content_utils.py
index 3dfb98c12ea..d9e079c6d92 100644
--- a/tests/test_litellm/proxy/guardrails/test_content_utils.py
+++ b/tests/test_litellm/proxy/guardrails/test_content_utils.py
@@ -149,6 +149,22 @@ def test_iter_message_text_responses_api_tool_call_taxonomy():
     assert list(iter_message_text(data)) == ["hello", "sunny"]
 
 
+def test_iter_message_text_inspects_reasoning_content_and_summary():
+    """VERIA: reasoning items forwarded as ``reasoning_content`` must be
+    inspected, including ``summary`` blocks the bridge reads as a fallback."""
+    data = {
+        "input": [
+            {
+                "type": "reasoning",
+                "id": "rs_1",
+                "content": [{"type": "summary_text", "text": "content secret"}],
+                "summary": [{"type": "summary_text", "text": "summary secret"}],
+            }
+        ]
+    }
+    assert list(iter_message_text(data)) == ["content secret", "summary secret"]
+
+
 # ── walk_user_text ────────────────────────────────────────────────────────────
 
 
@@ -308,6 +324,27 @@ def test_walk_user_text_redacts_mixed_list_input():
     assert data["input"][2] == {"type": "image_url", "image_url": {"url": "..."}}
 
 
+def test_walk_user_text_redacts_reasoning_content_and_summary():
+    """VERIA: in-place redaction must cover both plaintext shapes the bridge
+    forwards from a reasoning item."""
+    data = {
+        "input": [
+            {
+                "type": "reasoning",
+                "id": "rs_1",
+                "content": [{"type": "summary_text", "text": "AKIAEXAMPLE content"}],
+                "summary": [{"type": "summary_text", "text": "AKIAEXAMPLE summary"}],
+            }
+        ]
+    }
+    visited = walk_user_text(data, lambda s: s.replace("AKIAEXAMPLE", "[REDACTED]"))
+    assert visited == 2
+    item = data["input"][0]
+    assert item["content"][0]["text"] == "[REDACTED] content"
+    assert item["summary"][0]["text"] == "[REDACTED] summary"
+    assert item["id"] == "rs_1"
+
+
 # ── build_inspection_messages ─────────────────────────────────────────────────
 
 
@@ -462,6 +499,23 @@ def test_build_inspection_messages_empty_data():
     assert build_inspection_messages({"input": ""}) == []
 
 
+def test_build_inspection_messages_includes_reasoning_summary():
+    """VERIA: remote guardrail APIs must see reasoning summaries even when
+    the reasoning item has no ``content`` field."""
+    data = {
+        "input": [
+            {
+                "type": "reasoning",
+                "id": "rs_1",
+                "summary": [{"type": "summary_text", "text": "secret summary"}],
+            }
+        ]
+    }
+    assert build_inspection_messages(data) == [
+        {"role": "assistant", "content": "secret summary"}
+    ]
+
+
 # ── has_non_string_content ────────────────────────────────────────────────────
 
 

From f8b31f493a62a7b43a2effced84c8a9557929ffd Mon Sep 17 00:00:00 2001
From: 72004 <syahra2014@gmail.com>
Date: Fri, 21 Aug 2026 02:05:05 +0500
Subject: [PATCH 21/93] fix: don't retire a completed batch from cost recovery
 while output_file_id is still lagging

---
 .../openai_files_endpoints/common_utils.py    | 21 +++++++++-
 .../test_files_common_utils.py                | 42 +++++++++++++++++++
 2 files changed, 62 insertions(+), 1 deletion(-)

diff --git a/litellm/proxy/openai_files_endpoints/common_utils.py b/litellm/proxy/openai_files_endpoints/common_utils.py
index b9af01e9aea..f8896771077 100644
--- a/litellm/proxy/openai_files_endpoints/common_utils.py
+++ b/litellm/proxy/openai_files_endpoints/common_utils.py
@@ -1288,6 +1288,25 @@ def batch_cost_poller_is_active() -> bool:
         return False
 
 
+def _completed_batch_safe_to_retire(response) -> bool:
+    """Whether a "completed" batch may be retired from cost recovery.
+
+    ``batch_processed=True`` is the sole re-pickup gate for CheckBatchCost's
+    cost-recovery poller, so setting it retires the batch permanently. A batch can
+    reach ``status="completed"`` while ``output_file_id`` is still ``None`` (the
+    provider response briefly lags before the output id populates). Retiring in that
+    window loses the spend record forever. Retire only once we can prove there is
+    nothing left to recover: the output file has actually arrived, or the provider
+    reports no successful request lines. When counts are unknown, stay eligible so
+    the next poller pass revisits it. (#37713)
+    """
+    if getattr(response, "output_file_id", None) is not None:
+        return True
+    request_counts = getattr(response, "request_counts", None)
+    completed = getattr(request_counts, "completed", None)
+    return completed == 0
+
+
 async def update_batch_in_database(
     batch_id: str,
     unified_batch_id: str | Literal[False],
@@ -1369,7 +1388,7 @@ async def update_batch_in_database(
         }
 
         poller_owns: Final = batch_cost_poller_is_active() if poller_owns_accounting is None else poller_owns_accounting
-        if db_status == "complete" and not poller_owns:
+        if db_status == "complete" and not poller_owns and _completed_batch_safe_to_retire(response):
             update_data["batch_processed"] = True
 
         try:
diff --git a/tests/test_litellm/proxy/openai_files_endpoint/test_files_common_utils.py b/tests/test_litellm/proxy/openai_files_endpoint/test_files_common_utils.py
index 6ffb7daaa2d..eb6596e274c 100644
--- a/tests/test_litellm/proxy/openai_files_endpoint/test_files_common_utils.py
+++ b/tests/test_litellm/proxy/openai_files_endpoint/test_files_common_utils.py
@@ -431,3 +431,45 @@ def test_add_internal_model_credentials_survives_a_failing_deployment_lookup():
     add_internal_model_credentials(data=data, llm_router=router, model_id="deployment-gone")
 
     assert data == {"batch_id": "unified-batch-id"}
+
+
+from litellm.proxy.openai_files_endpoints.common_utils import (
+    _completed_batch_safe_to_retire,
+)
+
+
+def _completed_batch(output_file_id, completed=None) -> LiteLLMBatch:
+    kwargs = dict(
+        id="batch-1",
+        completion_window="24h",
+        created_at=1234567890,
+        endpoint="/v1/chat/completions",
+        input_file_id="file-in",
+        object="batch",
+        status="completed",
+        output_file_id=output_file_id,
+        error_file_id=None,
+    )
+    if completed is not None:
+        kwargs["request_counts"] = {"total": completed, "completed": completed, "failed": 0}
+    return LiteLLMBatch(**kwargs)
+
+
+class TestCompletedBatchSafeToRetire:
+    """A completed batch is only safe to retire from cost recovery once its output
+    file has arrived or the provider proves no successful lines (#37713)."""
+
+    def test_output_file_present_is_safe(self):
+        assert _completed_batch_safe_to_retire(_completed_batch("file-out")) is True
+
+    def test_no_output_and_no_successful_lines_is_safe(self):
+        # Every request line errored -> nothing left to recover.
+        assert _completed_batch_safe_to_retire(_completed_batch(None, completed=0)) is True
+
+    def test_no_output_but_successful_lines_is_not_safe(self):
+        # The bug: output_file_id is lagging; retiring here loses the spend record.
+        assert _completed_batch_safe_to_retire(_completed_batch(None, completed=5)) is False
+
+    def test_no_output_and_unknown_counts_is_not_safe(self):
+        # Counts unknown -> stay eligible so the next poller pass revisits it.
+        assert _completed_batch_safe_to_retire(_completed_batch(None)) is False

From 67d16a499dc208f69ddab20e17648b503acc07ec Mon Sep 17 00:00:00 2001
From: 72004 <syahra2014@gmail.com>
Date: Fri, 21 Aug 2026 02:13:11 +0500
Subject: [PATCH 22/93] Type the batch-retire helpers and rename test helper to
 avoid shadowing existing _completed_batch

---
 litellm/proxy/openai_files_endpoints/common_utils.py |  2 +-
 .../openai_files_endpoint/test_files_common_utils.py | 12 +++++++-----
 2 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/litellm/proxy/openai_files_endpoints/common_utils.py b/litellm/proxy/openai_files_endpoints/common_utils.py
index f8896771077..2e8ae6af7a9 100644
--- a/litellm/proxy/openai_files_endpoints/common_utils.py
+++ b/litellm/proxy/openai_files_endpoints/common_utils.py
@@ -1288,7 +1288,7 @@ def batch_cost_poller_is_active() -> bool:
         return False
 
 
-def _completed_batch_safe_to_retire(response) -> bool:
+def _completed_batch_safe_to_retire(response: "LiteLLMBatch") -> bool:
     """Whether a "completed" batch may be retired from cost recovery.
 
     ``batch_processed=True`` is the sole re-pickup gate for CheckBatchCost's
diff --git a/tests/test_litellm/proxy/openai_files_endpoint/test_files_common_utils.py b/tests/test_litellm/proxy/openai_files_endpoint/test_files_common_utils.py
index eb6596e274c..3de9e61463f 100644
--- a/tests/test_litellm/proxy/openai_files_endpoint/test_files_common_utils.py
+++ b/tests/test_litellm/proxy/openai_files_endpoint/test_files_common_utils.py
@@ -438,7 +438,9 @@ from litellm.proxy.openai_files_endpoints.common_utils import (
 )
 
 
-def _completed_batch(output_file_id, completed=None) -> LiteLLMBatch:
+def _completed_batch_for_retire(
+    output_file_id: str | None, completed: int | None = None
+) -> LiteLLMBatch:
     kwargs = dict(
         id="batch-1",
         completion_window="24h",
@@ -460,16 +462,16 @@ class TestCompletedBatchSafeToRetire:
     file has arrived or the provider proves no successful lines (#37713)."""
 
     def test_output_file_present_is_safe(self):
-        assert _completed_batch_safe_to_retire(_completed_batch("file-out")) is True
+        assert _completed_batch_safe_to_retire(_completed_batch_for_retire("file-out")) is True
 
     def test_no_output_and_no_successful_lines_is_safe(self):
         # Every request line errored -> nothing left to recover.
-        assert _completed_batch_safe_to_retire(_completed_batch(None, completed=0)) is True
+        assert _completed_batch_safe_to_retire(_completed_batch_for_retire(None, completed=0)) is True
 
     def test_no_output_but_successful_lines_is_not_safe(self):
         # The bug: output_file_id is lagging; retiring here loses the spend record.
-        assert _completed_batch_safe_to_retire(_completed_batch(None, completed=5)) is False
+        assert _completed_batch_safe_to_retire(_completed_batch_for_retire(None, completed=5)) is False
 
     def test_no_output_and_unknown_counts_is_not_safe(self):
         # Counts unknown -> stay eligible so the next poller pass revisits it.
-        assert _completed_batch_safe_to_retire(_completed_batch(None)) is False
+        assert _completed_batch_safe_to_retire(_completed_batch_for_retire(None)) is False

From d6f9bce4bb7c0783cb994f3ef165c182069557dc Mon Sep 17 00:00:00 2001
From: milan <milan@berri.ai>
Date: Sat, 22 Aug 2026 04:05:02 +0000
Subject: [PATCH 23/93] fix(a2a): normalize agent card protocolBinding casing
 before transport match

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/a2a_protocol/card_resolver.py        | 28 ++++++++++++
 litellm/a2a_protocol/main.py                 | 13 +++---
 tests/test_litellm/a2a_protocol/test_main.py | 45 +++++++++++++++++---
 3 files changed, 76 insertions(+), 10 deletions(-)

diff --git a/litellm/a2a_protocol/card_resolver.py b/litellm/a2a_protocol/card_resolver.py
index d14d892256b..8070d88b761 100644
--- a/litellm/a2a_protocol/card_resolver.py
+++ b/litellm/a2a_protocol/card_resolver.py
@@ -4,6 +4,7 @@ Custom A2A Card Resolver for LiteLLM.
 Extends the A2A SDK's card resolver to support multiple well-known paths.
 """
 
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final
 
 from litellm._logging import verbose_logger
@@ -48,6 +49,33 @@ def is_localhost_or_internal_url(url: str | None) -> bool:
     return any(pattern in url_lower for pattern in LOCALHOST_URL_PATTERNS)
 
 
+_CANONICAL_PROTOCOL_BINDINGS: Final = MappingProxyType(
+    {
+        "jsonrpc": "JSONRPC",
+        "http+json": "HTTP+JSON",
+        "grpc": "GRPC",
+    }
+)
+
+
+def normalize_agent_card_protocol_bindings(agent_card: "AgentCard") -> "AgentCard":
+    """
+    Canonicalize protocolBinding casing on the card's supported interfaces.
+
+    Some A2A servers (e.g. LangGraph Platform) serve agent cards with lowercase
+    bindings like "jsonrpc", but a2a-sdk's ClientFactory matches bindings
+    case-sensitively against its uppercase TransportProtocol constants and fails
+    with "no compatible transports found." for spec-adjacent casings.
+    """
+    interfaces: Final = getattr(agent_card, "supported_interfaces", None) or ()
+    for interface in interfaces:
+        binding: str = getattr(interface, "protocol_binding", "") or ""
+        canonical = _CANONICAL_PROTOCOL_BINDINGS.get(binding.lower())
+        if canonical is not None and binding != canonical:
+            interface.protocol_binding = canonical
+    return agent_card
+
+
 def get_agent_card_url(agent_card: "AgentCard") -> str | None:
     """Return the agent endpoint URL from the resolved SDK card."""
     url: Final = getattr(agent_card, "url", None)
diff --git a/litellm/a2a_protocol/main.py b/litellm/a2a_protocol/main.py
index 1c6ebf0b95c..2d4267cc0db 100644
--- a/litellm/a2a_protocol/main.py
+++ b/litellm/a2a_protocol/main.py
@@ -73,6 +73,7 @@ except ImportError:
 from litellm.a2a_protocol.card_resolver import (
     LiteLLMA2ACardResolver,
     get_agent_card_url,
+    normalize_agent_card_protocol_bindings,
 )
 from litellm.a2a_protocol.exception_mapping_utils import (
     handle_a2a_localhost_retry,
@@ -782,13 +783,17 @@ async def create_a2a_client(
     if extra_headers:
         verbose_proxy_logger.debug("A2A client created with extra_headers=%s", list(extra_headers.keys()))
 
+    resolver: Final = A2ACardResolver(httpx_client=httpx_client, base_url=base_url)
+    agent_card: Final = normalize_agent_card_protocol_bindings(
+        await resolver.get_agent_card(http_kwargs={"headers": extra_headers} if extra_headers else None)
+    )
+
     a2a_client: Final = await create_client(  # pyright: ignore[reportOptionalCall]
-        base_url,
+        agent_card,
         client_config=ClientConfig(  # pyright: ignore[reportOptionalCall]
             httpx_client=httpx_client,
             streaming=streaming,
         ),
-        resolver_http_kwargs={"headers": extra_headers} if extra_headers else None,
     )
     # Stash LiteLLM-owned handles on the client so the localhost-retry path can reuse
     # the configured httpx client and this agent's headers without excavating
@@ -799,9 +804,7 @@ async def create_a2a_client(
         if extra_headers
         else None
     )
-    agent_card: Final = getattr(a2a_client, "_card", None)
-    if agent_card is not None:
-        a2a_client._litellm_agent_card = agent_card
+    a2a_client._litellm_agent_card = agent_card
 
     verbose_logger.info("A2A client created for %s", base_url)
 
diff --git a/tests/test_litellm/a2a_protocol/test_main.py b/tests/test_litellm/a2a_protocol/test_main.py
index 08f6b9f25bb..29aa3aaabd7 100644
--- a/tests/test_litellm/a2a_protocol/test_main.py
+++ b/tests/test_litellm/a2a_protocol/test_main.py
@@ -176,10 +176,32 @@ _AGENT_A_HEADERS = {"x-agent-token": "token-for-a", "x-tenant": "tenant-a"}
 _AGENT_B_HEADERS = {"x-agent-token": "token-for-b", "x-tenant": "tenant-b"}
 
 
+_V1_RPC_REPLY = {
+    "jsonrpc": "2.0",
+    "id": "reply",
+    "result": {"message": {"messageId": "reply-1", "role": "ROLE_AGENT", "parts": [{"text": "pong"}]}},
+}
+
+
+_LOWERCASE_BINDING_CARD = {
+    "name": "langgraph-agent",
+    "version": "1.0.0",
+    "capabilities": {"streaming": True},
+    "defaultInputModes": ["text/plain"],
+    "defaultOutputModes": ["text/plain"],
+    "skills": [],
+    "supportedInterfaces": [
+        {"url": "http://127.0.0.1:9/", "protocolBinding": "jsonrpc", "protocolVersion": "1.0"}
+    ],
+}
+
+
 class _RequestRecorder:
     """Records the headers httpx put on the wire, per outbound request."""
 
-    def __init__(self):
+    def __init__(self, card=_AGENT_CARD, rpc_reply=_RPC_REPLY):
+        self.card = card
+        self.rpc_reply = rpc_reply
         self.card_requests = []
         self.rpc_requests = []
         self.client = None
@@ -188,23 +210,23 @@ class _RequestRecorder:
         headers = {k.lower(): v for k, v in request.headers.items()}
         if request.method == "GET":
             self.card_requests.append(headers)
-            return httpx.Response(200, json=_AGENT_CARD)
+            return httpx.Response(200, json=self.card)
         self.rpc_requests.append(headers)
-        return httpx.Response(200, json=_RPC_REPLY)
+        return httpx.Response(200, json=self.rpc_reply)
 
 
 def _a2a_client_cache_key(timeout: float) -> str:
     return "async_httpx_client" + f"timeout_{timeout}" + httpxSpecialProvider.A2AProvider
 
 
-async def _seed_shared_a2a_client() -> _RequestRecorder:
+async def _seed_shared_a2a_client(card=_AGENT_CARD, rpc_reply=_RPC_REPLY) -> _RequestRecorder:
     """Put the one A2A client the cache will hand out behind a mock transport.
 
     Seeding has to happen on the test's own event loop, because the client cache keys on
     it. The injected client is a real httpx.AsyncClient, so the merge of per-request
     headers over client defaults, which is what these tests are about, stays real.
     """
-    recorder = _RequestRecorder()
+    recorder = _RequestRecorder(card=card, rpc_reply=rpc_reply)
     handler = AsyncHTTPHandler(timeout=DEFAULT_A2A_AGENT_TIMEOUT)
     owned_client = handler.client
     handler.client = httpx.AsyncClient(transport=httpx.MockTransport(recorder))
@@ -311,6 +333,19 @@ async def test_streaming_send_carries_only_its_own_caller_headers(isolated_clien
     assert received["b"]["x-tenant"] == "tenant-b"
 
 
+@pytest.mark.asyncio
+async def test_lowercase_protocol_binding_in_agent_card_still_gets_a_client(isolated_client_cache):
+    """LangGraph Platform serves cards with protocolBinding "jsonrpc"; a2a-sdk matches
+    bindings case-sensitively, so without normalization client creation raises
+    ValueError("no compatible transports found.")."""
+    await _seed_shared_a2a_client(card=_LOWERCASE_BINDING_CARD, rpc_reply=_V1_RPC_REPLY)
+
+    a2a_client = await create_a2a_client(base_url="http://127.0.0.1:9")
+    response = await _send_message(a2a_client, _send_request("lc"))
+
+    assert type(response.root.result).__name__ == "Message"
+
+
 @pytest.mark.asyncio
 async def test_agent_card_fetch_carries_the_callers_headers(isolated_client_cache):
     """Agent cards can sit behind the same auth as the agent, so the card fetch must stay

From 329202004ef15d77e79b4c7c234c208567c22108 Mon Sep 17 00:00:00 2001
From: milan <milan@berri.ai>
Date: Sat, 22 Aug 2026 04:17:16 +0000
Subject: [PATCH 24/93] test(a2a): stub card resolver in create_a2a_client unit
 tests

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .../test_agent_header_isolation.py            | 22 ++++++++++++++++++-
 1 file changed, 21 insertions(+), 1 deletion(-)

diff --git a/tests/test_litellm/proxy/agent_endpoints/test_agent_header_isolation.py b/tests/test_litellm/proxy/agent_endpoints/test_agent_header_isolation.py
index 5193ad989dc..30095796a7f 100644
--- a/tests/test_litellm/proxy/agent_endpoints/test_agent_header_isolation.py
+++ b/tests/test_litellm/proxy/agent_endpoints/test_agent_header_isolation.py
@@ -245,13 +245,21 @@ def _fake_get_async_httpx_client_factory(captured_calls: list):
     return _fake_get_async_httpx_client
 
 
-async def _fake_create_client(base_url, client_config=None, **kwargs):
+async def _fake_create_client(agent_card, client_config=None, **kwargs):
     client = MagicMock()
     if client_config is not None:
         client._litellm_httpx_client = client_config.httpx_client
     return client
 
 
+def _fake_card_resolver(httpx_client, base_url, **kwargs):
+    resolver = MagicMock()
+    card = MagicMock()
+    card.supported_interfaces = ()
+    resolver.get_agent_card = AsyncMock(return_value=card)
+    return resolver
+
+
 @pytest.mark.asyncio
 async def test_create_a2a_client_leaves_the_shared_client_untouched():
     """
@@ -276,6 +284,10 @@ async def test_create_a2a_client_leaves_the_shared_client_untouched():
             "litellm.a2a_protocol.main.create_client",
             new=AsyncMock(side_effect=_fake_create_client),
         ),
+        patch(
+            "litellm.a2a_protocol.main.A2ACardResolver",
+            side_effect=_fake_card_resolver,
+        ),
     ):
         await create_a2a_client(
             base_url="http://agent-a:9999",
@@ -321,6 +333,10 @@ async def test_create_a2a_client_default_timeout_matches_constant():
             "litellm.a2a_protocol.main.create_client",
             new=AsyncMock(side_effect=_fake_create_client),
         ),
+        patch(
+            "litellm.a2a_protocol.main.A2ACardResolver",
+            side_effect=_fake_card_resolver,
+        ),
     ):
         await create_a2a_client(base_url="http://127.0.0.1:9")
 
@@ -352,6 +368,10 @@ async def test_create_a2a_client_explicit_timeout_overrides_default():
             "litellm.a2a_protocol.main.create_client",
             new=AsyncMock(side_effect=_fake_create_client),
         ),
+        patch(
+            "litellm.a2a_protocol.main.A2ACardResolver",
+            side_effect=_fake_card_resolver,
+        ),
     ):
         await create_a2a_client(base_url="http://127.0.0.1:9", timeout=42.5)
 

From 005f04edb6e853cbb89a797a4d0e4638ea800a75 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 10:39:31 -0700
Subject: [PATCH 25/93] fix(responses): mint Responses API item IDs in the
 completion bridge

The Chat Completions -> Responses bridge stamped the upstream chatcmpl-*
ID onto message output items, so replaying bridged history into native
OpenAI Responses failed with "Expected an ID that begins with 'msg'".
Image generation calls were minted as chatcmpl-*_img_N instead of ig_*,
and reasoning items used a salted hash() that is not stable across
processes.

Streaming minted msg_* for its incremental events but rebuilt the
response.completed snapshot through the same broken transform, so the
snapshot contradicted the events it had just sent and streaming clients
hit the same 400. The snapshot now reuses the IDs already streamed.

Fixes #27333
---
 .../streaming_iterator.py                     |  42 +++-
 .../transformation.py                         |  11 +-
 .../test_image_generation_output.py           |   5 +-
 .../test_litellm_completion_responses.py      |   6 +-
 .../test_response_output_item_id_prefixes.py  | 214 ++++++++++++++++++
 5 files changed, 264 insertions(+), 14 deletions(-)
 create mode 100644 tests/test_litellm/responses/litellm_completion_transformation/test_response_output_item_id_prefixes.py

diff --git a/litellm/responses/litellm_completion_transformation/streaming_iterator.py b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
index aa5708088b7..2a94fcb2a89 100644
--- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py
+++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
@@ -966,9 +966,9 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
         and the ReasoningSummaryTextDeltaEvent, which is used by the responses API to emit reasoning content.
         It also handles emitting annotation.added events when annotations are detected in the chunk.
         """
-        if self._cached_item_id is None and chunk.id:
-            self._cached_item_id = chunk.id
-        item_id: Final = self._cached_item_id or chunk.id
+        if self._cached_item_id is None:
+            self._cached_item_id = f"msg_{uuid.uuid4()}"
+        item_id: Final = self._cached_item_id
 
         # Check if this chunk has annotations first (before processing text/reasoning)
         # This ensures we detect and queue annotation events from the annotation chunk
@@ -1003,9 +1003,12 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
         ):
             reasoning_content: Final = chunk.choices[0].delta.reasoning_content
 
+            if self._cached_reasoning_item_id is None:
+                self._cached_reasoning_item_id = f"rs_{uuid.uuid4()}"
+
             return ReasoningSummaryTextDeltaEvent(
                 type=ResponsesAPIStreamEvents.REASONING_SUMMARY_TEXT_DELTA,
-                item_id=f"rs_{hash(str(reasoning_content))}",
+                item_id=self._cached_reasoning_item_id,
                 output_index=0,
                 delta=reasoning_content,
             )
@@ -1056,6 +1059,35 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
         chat_completion_delta: Final[ChatCompletionDelta] = choice.delta
         return chat_completion_delta.content or ""
 
+    def _align_output_item_ids_with_streamed_ids(self, responses_api_response: ResponsesAPIResponse) -> None:
+        """
+        Reuse the item IDs already emitted by the incremental streaming events in the
+        ``response.completed`` snapshot, so a streaming client that replays the snapshot
+        sends back the same IDs it observed mid-stream.
+        """
+        self._set_first_output_item_id(responses_api_response, "message", self._cached_item_id)
+        self._set_first_output_item_id(responses_api_response, "reasoning", self._cached_reasoning_item_id)
+
+    @staticmethod
+    def _set_first_output_item_id(
+        responses_api_response: ResponsesAPIResponse,
+        item_type: str,
+        cached_id: str | None,
+    ) -> None:
+        if cached_id is None:
+            return
+
+        for item in getattr(responses_api_response, "output", None) or []:
+            current_type = item.get("type") if isinstance(item, dict) else getattr(item, "type", None)
+            if current_type != item_type:
+                continue
+
+            if isinstance(item, dict):
+                item["id"] = cached_id
+            else:
+                item.id = cached_id
+            return
+
     def _emit_response_completed_event(self, litellm_model_response: ModelResponse) -> ResponseCompletedEvent | None:
         if litellm_model_response:
             # Add cost to usage object if include_cost_in_streaming_usage is True
@@ -1081,6 +1113,8 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
             if self._cached_response_id:
                 responses_api_response.id = self._cached_response_id
 
+            self._align_output_item_ids_with_streamed_ids(responses_api_response)
+
             # Encode the response ID to match non-streaming behavior
             encoded_response: Final = ResponsesAPIRequestUtils._update_responses_api_response_id_with_model_id(
                 responses_api_response=responses_api_response,
diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index 64084bfb063..cc2759358d2 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -4,6 +4,7 @@ Handles transforming from Responses API -> LiteLLM completion  (Chat Completion
 
 import json
 import re
+import uuid
 from collections.abc import Iterator, Mapping, Sequence
 from types import MappingProxyType
 from typing import (
@@ -2017,7 +2018,7 @@ class LiteLLMCompletionResponsesConfig:
                     return [
                         GenericResponseOutputItem(
                             type="reasoning",
-                            id=f"rs_{hash(reasoning_content or encrypted_content)}",
+                            id=f"rs_{uuid.uuid4()}",
                             status=LiteLLMCompletionResponsesConfig._map_chat_completion_finish_reason_to_responses_status(
                                 choice.finish_reason
                             ),
@@ -2054,7 +2055,7 @@ class LiteLLMCompletionResponsesConfig:
         To Responses API format:
         {
             'type': 'image_generation_call',
-            'id': 'img_...',
+            'id': 'ig_...',
             'status': 'completed',
             'result': 'iVBORw0...'  # Pure base64 without data: prefix
         }
@@ -2065,7 +2066,7 @@ class LiteLLMCompletionResponsesConfig:
         if not images:
             return image_generation_items
 
-        for idx, image_item in enumerate(_DICT_ITEMS_LIST_ADAPTER.validate_python(images)):
+        for image_item in _DICT_ITEMS_LIST_ADAPTER.validate_python(images):
             # Extract base64 from data URL
             image_url = _TEXT_ADAPTER.validate_python(
                 _ANY_KEY_DICT_ADAPTER.validate_python(image_item.get("image_url", {})).get("url", "")
@@ -2076,7 +2077,7 @@ class LiteLLMCompletionResponsesConfig:
                 image_generation_items.append(
                     OutputImageGenerationCall(
                         type="image_generation_call",
-                        id=f"{chat_completion_response.id}_img_{idx}",
+                        id=f"ig_{uuid.uuid4()}",
                         status=LiteLLMCompletionResponsesConfig._map_finish_reason_to_image_generation_status(
                             choice.finish_reason
                         ),
@@ -2150,7 +2151,7 @@ class LiteLLMCompletionResponsesConfig:
                 message_output_items.append(
                     GenericResponseOutputItem(
                         type="message",
-                        id=chat_completion_response.id,
+                        id=f"msg_{uuid.uuid4()}",
                         status=LiteLLMCompletionResponsesConfig._map_chat_completion_finish_reason_to_responses_status(
                             choice.finish_reason
                         ),
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_image_generation_output.py b/tests/test_litellm/responses/litellm_completion_transformation/test_image_generation_output.py
index ed7a3f63a8e..41057d49a97 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_image_generation_output.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_image_generation_output.py
@@ -89,8 +89,9 @@ class TestExtractImageGenerationOutputItems:
         assert result[0].type == "image_generation_call"
         assert result[0].result == "IMG1"
         assert result[1].result == "IMG2"
-        assert result[0].id == "test_123_img_0"
-        assert result[1].id == "test_123_img_1"
+        assert result[0].id.startswith("ig_")
+        assert result[1].id.startswith("ig_")
+        assert result[0].id != result[1].id
         assert result[0].status == "completed"
 
     def test_returns_empty_for_no_images(self):
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
index 5efabed4b8d..daa732e032a 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
@@ -2841,9 +2841,9 @@ class TestStreamingIDConsistency:
         # Verify the cached ID is set and matches
         assert iterator._cached_item_id is not None, "Iterator should cache the item_id"
         assert iterator._cached_item_id == item_id_1, "Cached ID should match event IDs"
-        assert (
-            iterator._cached_item_id == "chatcmpl-first-id"
-        ), "Should use the first chunk's ID"
+        assert iterator._cached_item_id.startswith(
+            "msg_"
+        ), "Message item IDs must use the Responses API msg_ prefix (issue #27333)"
 
     def test_streaming_iterator_initial_events_use_cached_id(self):
         """
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_response_output_item_id_prefixes.py b/tests/test_litellm/responses/litellm_completion_transformation/test_response_output_item_id_prefixes.py
new file mode 100644
index 00000000000..4b24b2be90d
--- /dev/null
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_response_output_item_id_prefixes.py
@@ -0,0 +1,214 @@
+"""
+Regression tests for the Chat Completions -> Responses API bridge item IDs.
+
+Bridged output items must carry Responses API ID prefixes (msg_, ig_, rs_) rather
+than the upstream chatcmpl-* ID. Native OpenAI Responses rejects a replayed history
+whose message item ID does not begin with "msg", and rejects an image generation
+call whose ID does not begin with "ig".
+
+Regression test for https://github.com/BerriAI/litellm/issues/27333
+"""
+
+from unittest.mock import Mock
+
+import litellm
+from litellm.responses.litellm_completion_transformation.streaming_iterator import (
+    LiteLLMCompletionStreamingIterator,
+)
+from litellm.responses.litellm_completion_transformation.transformation import (
+    LiteLLMCompletionResponsesConfig,
+)
+from litellm.types.utils import (
+    Choices,
+    Delta,
+    Message,
+    ModelResponse,
+    ModelResponseStream,
+    StreamingChoices,
+    Usage,
+)
+
+CHAT_COMPLETION_ID = "chatcmpl-dfa2da3a-1586-4ff7-b64e-f59c692a5d11"
+
+
+def _make_chat_completion_response(**overrides) -> ModelResponse:
+    defaults = dict(
+        id=CHAT_COMPLETION_ID,
+        created=1717000000,
+        model="claude-sonnet-4-5",
+        object="chat.completion",
+        choices=[
+            Choices(
+                index=0,
+                finish_reason="stop",
+                message=Message(role="assistant", content="apple"),
+            )
+        ],
+        usage=Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15),
+    )
+    defaults.update(overrides)
+    return ModelResponse(**defaults)
+
+
+def _transform(chat_completion_response):
+    return LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
+        request_input="Say the single word: apple",
+        responses_api_request={},
+        chat_completion_response=chat_completion_response,
+    )
+
+
+def _output_items_of_type(response, item_type):
+    return [item for item in response.output if getattr(item, "type", None) == item_type]
+
+
+class TestMessageOutputItemIds:
+    def test_message_item_id_uses_msg_prefix(self):
+        response = _transform(_make_chat_completion_response())
+
+        message_items = _output_items_of_type(response, "message")
+        assert len(message_items) == 1
+        assert message_items[0].id.startswith("msg_")
+
+    def test_message_item_id_does_not_leak_chat_completion_id(self):
+        response = _transform(_make_chat_completion_response())
+
+        for item in _output_items_of_type(response, "message"):
+            assert item.id != CHAT_COMPLETION_ID
+            assert not item.id.startswith("chatcmpl-")
+
+    def test_message_item_ids_are_unique_across_responses(self):
+        first = _transform(_make_chat_completion_response())
+        second = _transform(_make_chat_completion_response())
+
+        first_id = _output_items_of_type(first, "message")[0].id
+        second_id = _output_items_of_type(second, "message")[0].id
+        assert first_id != second_id
+
+
+class TestImageGenerationOutputItemIds:
+    def _make_choice_with_images(self, count):
+        message = Mock(spec=Message)
+        message.images = [
+            {"image_url": {"url": f"data:image/png;base64,IMG{idx}"}} for idx in range(count)
+        ]
+        choice = Mock(spec=Choices)
+        choice.message = message
+        choice.finish_reason = "stop"
+        return choice
+
+    def test_image_generation_item_id_uses_ig_prefix(self):
+        items = LiteLLMCompletionResponsesConfig._extract_image_generation_output_items(
+            chat_completion_response=_make_chat_completion_response(),
+            choice=self._make_choice_with_images(2),
+        )
+
+        assert len(items) == 2
+        for item in items:
+            assert item.id.startswith("ig_")
+            assert "chatcmpl-" not in item.id
+            assert "_img_" not in item.id
+
+    def test_image_generation_item_ids_are_unique(self):
+        items = LiteLLMCompletionResponsesConfig._extract_image_generation_output_items(
+            chat_completion_response=_make_chat_completion_response(),
+            choice=self._make_choice_with_images(3),
+        )
+
+        assert len({item.id for item in items}) == 3
+
+
+class TestReasoningOutputItemIds:
+    def _reasoning_items(self):
+        message = Message(role="assistant", content="apple")
+        message.reasoning_content = "thinking about fruit"
+        choice = Choices(index=0, finish_reason="stop", message=message)
+        return LiteLLMCompletionResponsesConfig._extract_reasoning_output_items(
+            chat_completion_response=_make_chat_completion_response(),
+            choices=[choice],
+        )
+
+    def test_reasoning_item_id_uses_rs_prefix(self):
+        items = self._reasoning_items()
+
+        assert len(items) == 1
+        assert items[0].id.startswith("rs_")
+
+    def test_reasoning_item_id_is_not_a_salted_hash(self):
+        item_id = self._reasoning_items()[0].id
+
+        suffix = item_id.removeprefix("rs_")
+        assert not suffix.lstrip("-").isdigit()
+        assert not suffix.startswith("-")
+
+
+class TestStreamingItemIdConsistency:
+    def _make_iterator(self):
+        mock_stream_wrapper = Mock(spec=litellm.CustomStreamWrapper)
+        mock_stream_wrapper.logging_obj = Mock()
+        return LiteLLMCompletionStreamingIterator(
+            model="anthropic/claude-sonnet-4-5",
+            litellm_custom_stream_wrapper=mock_stream_wrapper,
+            request_input="Say the single word: apple",
+            responses_api_request={},
+            custom_llm_provider="anthropic",
+        )
+
+    def _make_chunk(self, chunk_id, content, finish_reason=None):
+        return ModelResponseStream(
+            id=chunk_id,
+            choices=[
+                StreamingChoices(
+                    index=0,
+                    delta=Delta(content=content, role="assistant"),
+                    finish_reason=finish_reason,
+                )
+            ],
+            created=1717000000,
+            model="claude-sonnet-4-5",
+            object="chat.completion.chunk",
+        )
+
+    def test_incremental_item_id_uses_msg_prefix(self):
+        iterator = self._make_iterator()
+
+        event = iterator._transform_chat_completion_chunk_to_response_api_chunk(
+            self._make_chunk(CHAT_COMPLETION_ID, "apple")
+        )
+
+        assert event is not None
+        assert event.item_id.startswith("msg_")
+        assert event.item_id != CHAT_COMPLETION_ID
+
+    def test_completed_snapshot_reuses_streamed_item_id(self):
+        iterator = self._make_iterator()
+
+        streamed_event = iterator._transform_chat_completion_chunk_to_response_api_chunk(
+            self._make_chunk(CHAT_COMPLETION_ID, "apple")
+        )
+        assert streamed_event is not None
+        streamed_item_id = streamed_event.item_id
+
+        completed_event = iterator._emit_response_completed_event(
+            _make_chat_completion_response()
+        )
+
+        assert completed_event is not None
+        message_items = _output_items_of_type(completed_event.response, "message")
+        assert len(message_items) == 1
+        assert message_items[0].id == streamed_item_id
+
+    def test_completed_snapshot_item_id_is_replayable(self):
+        iterator = self._make_iterator()
+        iterator._transform_chat_completion_chunk_to_response_api_chunk(
+            self._make_chunk(CHAT_COMPLETION_ID, "apple")
+        )
+
+        completed_event = iterator._emit_response_completed_event(
+            _make_chat_completion_response()
+        )
+
+        assert completed_event is not None
+        for item in _output_items_of_type(completed_event.response, "message"):
+            assert item.id.startswith("msg_")
+            assert not item.id.startswith("chatcmpl-")

From a7afe986e3e4d7f2202df7c4528cf7806060a29d Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 10:51:40 -0700
Subject: [PATCH 26/93] fix(responses): replay signed thinking blocks through
 the completion bridge

encrypted_content on a reasoning input item is written by LiteLLM's own
_encode_thinking_blocks as a JSON array of Anthropic/Bedrock thinking
blocks, so decode it back and replay the signed blocks on the assistant
message instead of dropping them. Providers without a native
ResponsesAPIConfig now keep the verifiable chain-of-thought across turns,
and prior-turn reasoning stops reaching the provider as visible
assistant text.
---
 .../transformation.py                         | 176 ++++++++++++++----
 .../test_reasoning_input_item_preservation.py | 128 ++++++++++++-
 2 files changed, 263 insertions(+), 41 deletions(-)

diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index 0f3f5ba9a6a..c2e803c8a43 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -42,8 +42,10 @@ from litellm.types.llms.openai import (
     AllMessageValues,
     ChatCompletionImageObject,
     ChatCompletionImageUrlObject,
+    ChatCompletionRedactedThinkingBlock,
     ChatCompletionResponseMessage,
     ChatCompletionSystemMessage,
+    ChatCompletionThinkingBlock,
     ChatCompletionToolCallChunk,
     ChatCompletionToolCallFunctionChunk,
     ChatCompletionToolMessage,
@@ -559,6 +561,25 @@ class LiteLLMCompletionResponsesConfig:
                 messages.extend(chat_completion_messages)
         return LiteLLMCompletionResponsesConfig._merge_reasoning_only_assistant_messages(messages)
 
+    @staticmethod
+    def _reasoning_only_assistant_message(
+        reasoning_text: str | None,
+        thinking_blocks: Sequence[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] | None,
+    ) -> ChatCompletionResponseMessage:
+        """
+        Build the assistant message that carries a prior turn's reasoning and
+        nothing else, so a reasoning item never reaches the provider as visible
+        assistant ``content``.
+        """
+        message: Final = ChatCompletionResponseMessage(role="assistant", content=None)
+        if reasoning_text:
+            message["reasoning_content"] = reasoning_text
+        if thinking_blocks:
+            message["thinking_blocks"] = list(  # mutable-ok: thinking_blocks is a list on the message contract
+                thinking_blocks
+            )
+        return message
+
     @staticmethod
     def _merge_reasoning_only_assistant_messages(
         messages: list[  # mutable-ok: input sequence
@@ -579,6 +600,11 @@ class LiteLLMCompletionResponsesConfig:
         merges standalone reasoning-only assistant messages into the
         immediately following assistant message.
 
+        Signed ``thinking_blocks`` decoded from ``encrypted_content`` travel the
+        same way and are placed ahead of any thinking blocks the target message
+        already carries, because Anthropic and Bedrock verify signatures against
+        the original block order.
+
         If the reasoning item is not followed by an assistant message (e.g. a
         stateless chain replays ``reasoning`` + ``user``), the standalone
         reasoning message is preserved so the reasoning is still passed back.
@@ -596,6 +622,15 @@ class LiteLLMCompletionResponsesConfig:
                 value = getattr(msg, "reasoning_content", None)  # rebind-ok: branch lookup
             return value if isinstance(value, str) and value else None
 
+        def _thinking_blocks(
+            msg: object,
+        ) -> tuple[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock, ...] | None:
+            if isinstance(msg, dict):
+                value = msg.get("thinking_blocks")  # rebind-ok: branch lookup
+            else:
+                value = getattr(msg, "thinking_blocks", None)  # rebind-ok: branch lookup
+            return tuple(value) if isinstance(value, list) and value else None
+
         def _content(msg: object) -> object | None:
             if isinstance(msg, dict):
                 return msg.get("content")
@@ -606,60 +641,73 @@ class LiteLLMCompletionResponsesConfig:
                 return msg.get("tool_calls")
             return getattr(msg, "tool_calls", None)
 
+        def _apply_pending(
+            msg: object,
+            pending_items: Sequence[
+                tuple[
+                    str | None,
+                    tuple[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock, ...] | None,
+                ]
+            ],
+        ) -> None:
+            pending_texts: Final = tuple(text for text, _ in pending_items if text)
+            pending_blocks: Final = tuple(block for _, blocks in pending_items for block in blocks or ())
+            if pending_texts:
+                existing_text: Final = _reasoning_text(msg)
+                combined: Final = "\n".join(pending_texts + ((existing_text,) if existing_text else ()))
+                if isinstance(msg, dict):
+                    cast(dict[str, Any], msg)["reasoning_content"] = combined  # cast-ok: mutable reasoning carrier
+                else:
+                    setattr(msg, "reasoning_content", combined)  # noqa: B010  # attribute name is fixed, not dynamic
+            if pending_blocks:
+                replayed: Final = list(  # mutable-ok: thinking_blocks is a list on the message contract
+                    pending_blocks + (_thinking_blocks(msg) or ())
+                )
+                if isinstance(msg, dict):
+                    cast(dict[str, Any], msg)["thinking_blocks"] = replayed  # cast-ok: mutable reasoning carrier
+                else:
+                    setattr(msg, "thinking_blocks", replayed)  # noqa: B010  # attribute name is fixed, not dynamic
+
+        _standalone: Final = LiteLLMCompletionResponsesConfig._reasoning_only_assistant_message
+
         merged: list[  # mutable-ok: accumulator  # rebind-ok: accumulator
             AllMessageValues
             | GenericChatCompletionMessage
             | ChatCompletionMessageToolCall
             | ChatCompletionResponseMessage
         ] = []  # mutable-ok: accumulator
-        pending_reasoning: list[str] = []  # mutable-ok: accumulator  # rebind-ok: accumulator
+        pending: list[  # mutable-ok: accumulator  # rebind-ok: accumulator
+            tuple[
+                str | None,
+                tuple[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock, ...] | None,
+            ]
+        ] = []  # mutable-ok: accumulator
 
         for msg in messages:
             if (
                 _role(msg) == "assistant"
                 and _content(msg) is None
                 and not _tool_calls(msg)
-                and _reasoning_text(msg) is not None
+                and (_reasoning_text(msg) is not None or _thinking_blocks(msg) is not None)
             ):
-                pending_reasoning.append(_reasoning_text(msg) or "")
+                pending.append((_reasoning_text(msg), _thinking_blocks(msg)))
                 continue
 
-            if pending_reasoning and _role(msg) == "assistant":
-                combined = "\n".join(pending_reasoning)
-                existing = _reasoning_text(msg)
-                if existing:
-                    combined = combined + "\n" + existing
-                if isinstance(msg, dict):
-                    cast(dict[str, Any], msg)["reasoning_content"] = combined  # cast-ok: mutable reasoning carrier
-                else:
-                    setattr(msg, "reasoning_content", combined)  # noqa: B010
-                pending_reasoning = []  # mutable-ok: reset accumulator
-            elif pending_reasoning:
+            if pending and _role(msg) == "assistant":
+                _apply_pending(msg, pending)
+                pending = []  # mutable-ok: reset accumulator
+            elif pending:
                 # Not followed by an assistant message — keep the reasoning
                 # standalone instead of dropping it.
                 merged.extend(  # mutable-ok: append reasoning messages
-                    [  # mutable-ok: append reasoning messages
-                        ChatCompletionResponseMessage(
-                            role="assistant",
-                            content=None,
-                            reasoning_content=text,
-                        )
-                        for text in pending_reasoning
-                    ]
+                    [_standalone(text, blocks) for text, blocks in pending]  # mutable-ok: append reasoning messages
                 )
-                pending_reasoning = []  # mutable-ok: reset accumulator
+                pending = []  # mutable-ok: reset accumulator
 
             merged.append(msg)
 
         merged.extend(  # mutable-ok: append trailing reasoning
-            [  # mutable-ok: append trailing reasoning
-                ChatCompletionResponseMessage(
-                    role="assistant",
-                    content=None,
-                    reasoning_content=text,
-                )
-                for text in pending_reasoning
-            ]
+            [_standalone(text, blocks) for text, blocks in pending]  # mutable-ok: append trailing reasoning
         )
 
         return merged
@@ -1140,16 +1188,15 @@ class LiteLLMCompletionResponsesConfig:
             reasoning_text = LiteLLMCompletionResponsesConfig._extract_reasoning_text_from_input_item(  # rebind-ok: extraction result
                 input_item
             )
-            if not reasoning_text:
-                # No plaintext reasoning is available (e.g. encrypted_content only).
-                # Chat-completions providers cannot consume opaque encrypted blobs,
-                # so skip the item instead of polluting the prompt.
+            thinking_blocks = LiteLLMCompletionResponsesConfig._decode_thinking_blocks_from_input_item(  # rebind-ok: extraction result
+                input_item
+            )
+            if not reasoning_text and not thinking_blocks:
                 return []  # mutable-ok: empty drop result
             return [  # mutable-ok: single message result
-                ChatCompletionResponseMessage(
-                    role="assistant",
-                    content=None,
-                    reasoning_content=reasoning_text,
+                LiteLLMCompletionResponsesConfig._reasoning_only_assistant_message(
+                    reasoning_text=reasoning_text,
+                    thinking_blocks=thinking_blocks,
                 )
             ]
         else:
@@ -1211,6 +1258,57 @@ class LiteLLMCompletionResponsesConfig:
                 return "\n".join(text_parts)
         return None
 
+    @staticmethod
+    def _decode_thinking_blocks_from_input_item(
+        input_item: Mapping[str, object],
+    ) -> tuple[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock, ...] | None:
+        """
+        Decode ``encrypted_content`` written by ``_encode_thinking_blocks`` back
+        into the signed thinking blocks it serialized.
+
+        LiteLLM writes this field itself for providers whose reasoning is signed
+        (Anthropic, Bedrock converse): it is a JSON array of the provider's own
+        ``thinking`` / ``redacted_thinking`` blocks, not an opaque OpenAI blob.
+        Replaying the blocks on the assistant message is what lets the provider
+        verify the signature and keep the prior chain-of-thought.
+
+        Returns None for anything this deployment did not write, so a genuinely
+        opaque blob is still skipped rather than forwarded as garbage.
+        """
+        encrypted_content: Final[object] = input_item.get("encrypted_content")
+        if not isinstance(encrypted_content, str) or not encrypted_content.strip():
+            return None
+        try:
+            decoded: Final[object] = json.loads(encrypted_content)
+        except ValueError:
+            return None
+        if not isinstance(decoded, list):
+            return None
+
+        blocks: Final = tuple(
+            cast(  # cast-ok: shape validated by _is_replayable_thinking_block
+                ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock,
+                block,
+            )
+            for block in decoded
+            if isinstance(block, Mapping) and LiteLLMCompletionResponsesConfig._is_replayable_thinking_block(block)
+        )
+        return blocks or None
+
+    @staticmethod
+    def _is_replayable_thinking_block(block: Mapping[str, object]) -> bool:
+        """
+        A thinking block is only worth replaying when the provider can verify
+        it: a ``thinking`` block needs its signature, a ``redacted_thinking``
+        block needs its opaque data.
+        """
+        block_type: Final[object] = block.get("type")
+        if block_type == "thinking":
+            return bool(block.get("signature"))
+        if block_type == "redacted_thinking":
+            return bool(block.get("data"))
+        return False
+
     @staticmethod
     def _is_input_item_tool_call_output(input_item: Mapping[str, object]) -> bool:
         """
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py b/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
index ecc024b7d04..b21be67b150 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
@@ -7,11 +7,18 @@ generic message branch, polluting the prompt as visible assistant ``content``
 or being silently dropped. Chat-completions providers such as DeepSeek V4 and
 Kimi K2.6 require the chain-of-thought to be replayed as ``reasoning_content``
 on an assistant message.
+
+Providers whose reasoning is signed (Anthropic, Bedrock converse) get their
+blocks back through ``encrypted_content``, which LiteLLM itself writes as a
+JSON array of thinking blocks on the response side.
 """
 
+import json
+
 from litellm.responses.litellm_completion_transformation.transformation import (
     LiteLLMCompletionResponsesConfig,
 )
+from litellm.types.utils import Message
 
 
 def _transform_item(item):
@@ -59,8 +66,8 @@ class TestReasoningInputItemHandler:
         messages = _transform_item(item)
         assert messages[0]["reasoning_content"] == "..."
 
-    def test_reasoning_item_with_encrypted_content_only_dropped(self):
-        """Opaque encrypted reasoning cannot be forwarded to chat completions."""
+    def test_reasoning_item_with_opaque_encrypted_content_dropped(self):
+        """An encrypted blob LiteLLM did not write cannot be forwarded."""
         item = {"type": "reasoning", "id": "rs_3", "encrypted_content": "opaque-blob"}
         assert _transform_item(item) == []
 
@@ -142,6 +149,123 @@ class TestReasoningInputItemMerging:
         assert messages[0]["reasoning_content"] == "old reasoning\nnew reasoning"
 
 
+class TestEncryptedReasoningRoundTrip:
+    """``encrypted_content`` LiteLLM wrote decodes back into thinking blocks."""
+
+    def test_encoded_thinking_blocks_decode_back(self):
+        """The decoder is the inverse of the encoder the response side uses."""
+        blocks = [
+            {"type": "thinking", "thinking": "step one", "signature": "sig-one"},
+            {"type": "redacted_thinking", "data": "redacted-payload"},
+        ]
+        message = Message(role="assistant", content="answer", thinking_blocks=blocks)
+        encoded = LiteLLMCompletionResponsesConfig._encode_thinking_blocks(message)
+        decoded = LiteLLMCompletionResponsesConfig._decode_thinking_blocks_from_input_item(
+            {"type": "reasoning", "encrypted_content": encoded}
+        )
+        assert list(decoded) == blocks
+
+    def test_signed_thinking_blocks_replayed_on_assistant_message(self):
+        """A signed block survives the bridge instead of vanishing."""
+        item = {
+            "type": "reasoning",
+            "id": "rs_1",
+            "encrypted_content": json.dumps(
+                [{"type": "thinking", "thinking": "hidden", "signature": "sig-one"}]
+            ),
+        }
+        messages = _transform_item(item)
+        assert len(messages) == 1
+        assert messages[0]["content"] is None
+        assert messages[0]["thinking_blocks"] == [
+            {"type": "thinking", "thinking": "hidden", "signature": "sig-one"}
+        ]
+
+    def test_unsigned_blocks_dropped(self):
+        """Blocks without a signature or redacted payload are not replayed."""
+        item = {
+            "type": "reasoning",
+            "id": "rs_2",
+            "encrypted_content": json.dumps([{"type": "thinking", "thinking": "unsigned"}]),
+        }
+        assert _transform_item(item) == []
+
+    def test_json_object_encrypted_content_dropped(self):
+        """A JSON payload that is not a block array is treated as opaque."""
+        item = {
+            "type": "reasoning",
+            "id": "rs_3",
+            "encrypted_content": json.dumps({"ciphertext": "abc"}),
+        }
+        assert _transform_item(item) == []
+
+    def test_thinking_blocks_merged_onto_tool_call_assistant(self):
+        """Signed reasoning lands on the assistant turn carrying the tool call."""
+        messages = _transform_input(
+            [
+                {
+                    "type": "reasoning",
+                    "id": "rs_1",
+                    "summary": [{"type": "summary_text", "text": "look it up"}],
+                    "encrypted_content": json.dumps(
+                        [{"type": "thinking", "thinking": "hidden", "signature": "sig-one"}]
+                    ),
+                },
+                {
+                    "type": "function_call",
+                    "call_id": "call_1",
+                    "name": "lookup",
+                    "arguments": '{"cwe": "79"}',
+                },
+            ]
+        )
+        assert len(messages) == 1
+        assert messages[0]["reasoning_content"] == "look it up"
+        assert messages[0]["thinking_blocks"] == [
+            {"type": "thinking", "thinking": "hidden", "signature": "sig-one"}
+        ]
+        assert len(messages[0]["tool_calls"]) == 1
+
+    def test_replayed_blocks_precede_existing_blocks(self):
+        """Signature verification depends on the original block order."""
+        messages = LiteLLMCompletionResponsesConfig._merge_reasoning_only_assistant_messages(
+            [
+                {
+                    "role": "assistant",
+                    "content": None,
+                    "thinking_blocks": [{"type": "thinking", "thinking": "older", "signature": "a"}],
+                },
+                {
+                    "role": "assistant",
+                    "content": "answer",
+                    "thinking_blocks": [{"type": "thinking", "thinking": "newer", "signature": "b"}],
+                },
+            ]
+        )
+        assert len(messages) == 1
+        assert [block["thinking"] for block in messages[0]["thinking_blocks"]] == ["older", "newer"]
+
+    def test_encrypted_only_reasoning_preserved_before_user_turn(self):
+        """A signed item with no plaintext still survives a stateless replay."""
+        messages = _transform_input(
+            [
+                {
+                    "type": "reasoning",
+                    "id": "rs_1",
+                    "encrypted_content": json.dumps(
+                        [{"type": "thinking", "thinking": "hidden", "signature": "sig-one"}]
+                    ),
+                },
+                {"role": "user", "content": "and now?"},
+            ]
+        )
+        assert len(messages) == 2
+        assert messages[0]["role"] == "assistant"
+        assert "reasoning_content" not in messages[0]
+        assert messages[0]["thinking_blocks"][0]["signature"] == "sig-one"
+        assert messages[1]["role"] == "user"
+
+
 class TestNonReasoningInputItemUnchanged:
     """Non-reasoning items still flow through the existing branches."""
 

From 70e4273ba1f50fd921c05198fdfc868291dc2d57 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 11:12:17 -0700
Subject: [PATCH 27/93] fix(responses): make previous_response_id resolve on
 the bridged path

Streaming /v1/responses over the completion bridge minted a fresh resp_{uuid4}
for every response, while spend tracking stored the inner chat completion id as
request_id. The session lookup queries on request_id, so a follow-up sent with
that response id matched no rows and the prior conversation was silently
dropped. The iterator now pulls the first upstream chunk before emitting
response.created, so created, in_progress and completed all carry the same
encoded chat completion id.

Two more ways the same history went missing:

- The session lookup only read spend logs already written to the DB, so a
  follow-up sent inside the batch writer's window found nothing. It now also
  reads the rows still queued in memory.
- Input was only accepted as a string or a single dict, so the list shape the
  Responses API actually sends dropped every user turn from the reconstructed
  history.
---
 litellm/proxy/utils.py                        |  10 +
 .../session_handler.py                        |  67 ++++-
 .../streaming_iterator.py                     |  82 +++++-
 .../test_session_handler.py                   | 235 ++++++++++++++++++
 .../test_streaming_iterator_response_id.py    | 130 ++++++++++
 5 files changed, 508 insertions(+), 16 deletions(-)
 create mode 100644 tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_response_id.py

diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py
index c616d9e8723..9978fa04f40 100644
--- a/litellm/proxy/utils.py
+++ b/litellm/proxy/utils.py
@@ -6005,6 +6005,16 @@ async def enqueue_spend_logs(
         )
 
 
+async def peek_spend_logs(prisma_client: PrismaClient) -> tuple[SpendLogsPayload, ...]:
+    """Snapshot the spend logs still waiting for the next flush, leaving the queue intact.
+
+    Reads that need a just-finished request use this, since the batch writer only
+    reaches the DB every ``PROXY_BATCH_WRITE_AT`` seconds.
+    """
+    async with prisma_client._spend_log_transactions_lock:
+        return tuple(prisma_client.spend_log_transactions)
+
+
 async def dequeue_spend_logs(prisma_client: PrismaClient, limit: int) -> list[dict[str, object]]:
     """Take up to ``limit`` of the oldest queued spend logs off the queue.
 
diff --git a/litellm/responses/litellm_completion_transformation/session_handler.py b/litellm/responses/litellm_completion_transformation/session_handler.py
index dcff26c5b0c..935c78bc9a1 100644
--- a/litellm/responses/litellm_completion_transformation/session_handler.py
+++ b/litellm/responses/litellm_completion_transformation/session_handler.py
@@ -1,4 +1,5 @@
 import json
+from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any, Final, cast
 
 import litellm
@@ -104,10 +105,10 @@ class ResponsesSessionHandler:
         if proxy_server_request_dict:
             _response_input_param: Final = proxy_server_request_dict.get("input", None)
             _messages = proxy_server_request_dict.get("messages", None)
-            if isinstance(_response_input_param, str):
+            if isinstance(_response_input_param, (str, list)):
                 response_input_param = _response_input_param
             elif isinstance(_response_input_param, dict):
-                response_input_param = cast(ResponseInputParam, _response_input_param)
+                response_input_param = cast(ResponseInputParam, [_response_input_param])
 
         if response_input_param:
             chat_completion_messages = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages(
@@ -131,8 +132,8 @@ class ResponsesSessionHandler:
         ############################################################
         # Add Output messages for this Spend Log
         ############################################################
-        _response_output: Final = spend_log.get("response", "{}")
-        if isinstance(_response_output, dict) and _response_output and _response_output != {}:
+        _response_output: Final = ResponsesSessionHandler._get_response_dict_from_spend_log(spend_log)
+        if _response_output:
             # transform `ChatCompletion Response` to `ResponsesAPIResponse`
             model_response: Final = ModelResponse(**_response_output)
             for choice in model_response.choices:
@@ -140,6 +141,23 @@ class ResponsesSessionHandler:
                     chat_completion_message_history.append(getattr(choice, "message"))
         return chat_completion_message_history
 
+    @staticmethod
+    def _get_response_dict_from_spend_log(spend_log: SpendLogsPayload) -> Mapping[str, Any] | None:
+        """
+        Spend logs read from the DB hold `response` as a dict, ones still queued in memory
+        hold it as a JSON string.
+        """
+        _response_output: Final = spend_log.get("response")
+        if isinstance(_response_output, dict):
+            return _response_output or None
+        if isinstance(_response_output, str):
+            try:
+                parsed: Final = json.loads(_response_output)
+            except json.JSONDecodeError:
+                return None
+            return parsed if isinstance(parsed, dict) and parsed else None
+        return None
+
     @staticmethod
     async def get_proxy_server_request_from_spend_log(
         spend_log: SpendLogsPayload,
@@ -256,11 +274,12 @@ class ResponsesSessionHandler:
         SELECT session_id FROM spend_logs WHERE response_id = previous_response_id, SELECT * FROM spend_logs WHERE session_id = session_id
         """
         from litellm.proxy.proxy_server import prisma_client
+        from litellm.proxy.utils import peek_spend_logs
 
         verbose_proxy_logger.debug("decoding response id=%s", previous_response_id)
 
         decoded_response_id: Final = ResponsesAPIRequestUtils._decode_responses_api_response_id(previous_response_id)
-        previous_response_id = decoded_response_id.get("response_id", previous_response_id)
+        response_id: Final = decoded_response_id.get("response_id", previous_response_id)
         if prisma_client is None:
             return []
 
@@ -276,12 +295,46 @@ class ResponsesSessionHandler:
             ORDER BY "endTime" ASC;
         """
 
-        spend_logs: Final = await prisma_client.db.query_raw(query, previous_response_id)
+        written_spend_logs: Final = await prisma_client.db.query_raw(query, response_id)
+        queued_spend_logs: Final = await peek_spend_logs(prisma_client)
+        spend_logs: Final = list(
+            ResponsesSessionHandler._merge_queued_spend_logs(
+                response_id=response_id,
+                written_spend_logs=written_spend_logs,
+                queued_spend_logs=queued_spend_logs,
+            )
+        )
 
         verbose_proxy_logger.debug(
             "Found the following spend logs for previous response id %s: %s",
-            previous_response_id,
+            response_id,
             json.dumps(spend_logs, indent=4, default=str),
         )
 
         return spend_logs
+
+    @staticmethod
+    def _merge_queued_spend_logs(
+        response_id: str,
+        written_spend_logs: Sequence[SpendLogsPayload],
+        queued_spend_logs: Sequence[SpendLogsPayload],
+    ) -> tuple[SpendLogsPayload, ...]:
+        """
+        Append the session's spend logs that the batch writer has not flushed to the DB yet.
+
+        Without this a follow-up sent inside the ``PROXY_BATCH_WRITE_AT`` window sees an
+        empty session and silently drops the conversation. The queue is FIFO, so anything
+        still on it is newer than every row already written.
+        """
+        session_ids: Final = frozenset(
+            session_id
+            for spend_log in (*written_spend_logs, *queued_spend_logs)
+            if spend_log.get("request_id") == response_id and (session_id := spend_log.get("session_id"))
+        ) | frozenset(session_id for spend_log in written_spend_logs if (session_id := spend_log.get("session_id")))
+        written_request_ids: Final = frozenset(spend_log.get("request_id") for spend_log in written_spend_logs)
+        unflushed: Final = tuple(
+            spend_log
+            for spend_log in queued_spend_logs
+            if spend_log.get("session_id") in session_ids and spend_log.get("request_id") not in written_request_ids
+        )
+        return (*written_spend_logs, *unflushed)
diff --git a/litellm/responses/litellm_completion_transformation/streaming_iterator.py b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
index aa5708088b7..a8092edc625 100644
--- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py
+++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
@@ -86,6 +86,9 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
         self.final_text: str = ""
         self._cached_item_id: str | None = None
         self._cached_response_id: str | None = None
+        self._buffered_chunk: ModelResponseStream | None = None
+        self._upstream_exhausted: bool = False
+        self._response_id_primed: bool = False
         self._pending_tool_events: list[BaseLiteLLMOpenAIResponseObject] = []
         self._tool_output_index_by_call_id: dict[str, int] = {}
         self._tool_args_by_call_id: dict[str, str] = {}
@@ -330,6 +333,59 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
             )
             self._pending_tool_events.append(item_done_event)
 
+    def _adopt_response_id_from_chunk(self, chunk: ModelResponseStream) -> None:
+        if self._cached_response_id is not None:
+            return
+        chunk_id: Final = getattr(chunk, "id", None)
+        if chunk_id and isinstance(chunk_id, str):
+            self._cached_response_id = chunk_id
+
+    async def _aprime_response_id(self) -> None:
+        """
+        Pull the first upstream chunk before `response.created` is emitted so every event
+        carries the chat completion id that spend tracking stores as `request_id`.
+        """
+        if self._response_id_primed:
+            return
+        self._response_id_primed = True
+        while True:
+            try:
+                chunk = await self.litellm_custom_stream_wrapper.__anext__()
+            except StopAsyncIteration:
+                self._upstream_exhausted = True
+                return
+            if chunk is not None:
+                self._buffered_chunk = chunk
+                self._adopt_response_id_from_chunk(chunk)
+                return
+
+    def _prime_response_id(self) -> None:
+        if self._response_id_primed:
+            return
+        self._response_id_primed = True
+        while True:
+            try:
+                chunk = self.litellm_custom_stream_wrapper.__next__()
+            except StopIteration:
+                self._upstream_exhausted = True
+                return
+            if chunk is not None:
+                self._buffered_chunk = chunk
+                self._adopt_response_id_from_chunk(chunk)
+                return
+
+    def _take_buffered_chunk(self) -> ModelResponseStream | None:
+        buffered: Final = self._buffered_chunk
+        self._buffered_chunk = None
+        return buffered
+
+    def _with_encoded_response_id(self, response: ResponsesAPIResponse) -> ResponsesAPIResponse:
+        return ResponsesAPIRequestUtils._update_responses_api_response_id_with_model_id(
+            responses_api_response=response,
+            custom_llm_provider=self.custom_llm_provider,
+            litellm_metadata=self.litellm_metadata,
+        )
+
     def _default_response_created_event_data(self) -> dict:
         # Use cached response ID if available, otherwise generate a new one
         if self._cached_response_id is None:
@@ -388,7 +444,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
         self._sequence_number += 1
         event: Final = ResponseCreatedEvent(
             type=ResponsesAPIStreamEvents.RESPONSE_CREATED,
-            response=ResponsesAPIResponse(**response_created_event_data),
+            response=self._with_encoded_response_id(ResponsesAPIResponse(**response_created_event_data)),
         )
         event.__dict__["sequence_number"] = self._sequence_number
         return event
@@ -399,7 +455,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
         self._sequence_number += 1
         event: Final = ResponseInProgressEvent(
             type=ResponsesAPIStreamEvents.RESPONSE_IN_PROGRESS,
-            response=ResponsesAPIResponse(**response_in_progress_event_data),
+            response=self._with_encoded_response_id(ResponsesAPIResponse(**response_in_progress_event_data)),
         )
         event.__dict__["sequence_number"] = self._sequence_number
         return event
@@ -811,6 +867,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
                 if self.finished is True:
                     raise StopAsyncIteration
 
+                await self._aprime_response_id()
                 result = self.return_default_initial_events()
                 if result:
                     return result
@@ -822,7 +879,11 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
                     return self._pending_tool_events.pop(0)
 
                 try:
-                    chunk = await self.litellm_custom_stream_wrapper.__anext__()
+                    chunk = self._take_buffered_chunk()
+                    if chunk is None:
+                        if self._upstream_exhausted:
+                            raise StopAsyncIteration
+                        chunk = await self.litellm_custom_stream_wrapper.__anext__()
                     if chunk is not None:
                         chunk = cast(ModelResponseStream, chunk)
                         self._ensure_output_item_for_chunk(chunk)
@@ -912,6 +973,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
             while True:
                 if self.finished is True:
                     raise StopIteration
+                self._prime_response_id()
                 result = self.return_default_initial_events()
                 if result:
                     return result
@@ -922,7 +984,13 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
                 if self._pending_tool_events:
                     return self._pending_tool_events.pop(0)
                 try:
-                    chunk = self.litellm_custom_stream_wrapper.__next__()
+                    buffered_chunk = self._take_buffered_chunk()
+                    if buffered_chunk is not None:
+                        chunk = buffered_chunk
+                    elif self._upstream_exhausted:
+                        raise StopIteration
+                    else:
+                        chunk = self.litellm_custom_stream_wrapper.__next__()
                     self._ensure_output_item_for_chunk(chunk)
                     # Accumulate provider_specific_fields from chunk and delta
                     for src in (
@@ -1082,11 +1150,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
                 responses_api_response.id = self._cached_response_id
 
             # Encode the response ID to match non-streaming behavior
-            encoded_response: Final = ResponsesAPIRequestUtils._update_responses_api_response_id_with_model_id(
-                responses_api_response=responses_api_response,
-                custom_llm_provider=self.custom_llm_provider,
-                litellm_metadata=self.litellm_metadata,
-            )
+            encoded_response: Final = self._with_encoded_response_id(responses_api_response)
 
             return ResponseCompletedEvent(
                 type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py b/tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py
index 19f240fa3d4..926e9e0af2a 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py
@@ -1,3 +1,4 @@
+import asyncio
 import json
 from unittest.mock import AsyncMock, patch
 
@@ -10,6 +11,7 @@ from litellm.responses.litellm_completion_transformation import session_handler
 from litellm.responses.litellm_completion_transformation.session_handler import (
     ResponsesSessionHandler,
 )
+from litellm.responses.utils import ResponsesAPIRequestUtils
 
 
 @pytest.mark.asyncio
@@ -430,3 +432,236 @@ async def test_get_chat_completion_message_history_empty_response_dict():
 
         # Verify the session was still created correctly
         assert result["litellm_session_id"] == "test-session"
+
+
+def _chat_completion_response(request_id: str, content: str) -> dict:
+    return {
+        "id": request_id,
+        "object": "chat.completion",
+        "created": 1748575031,
+        "model": "claude-haiku-4-5",
+        "choices": [
+            {
+                "index": 0,
+                "message": {"role": "assistant", "content": content},
+                "finish_reason": "stop",
+            }
+        ],
+    }
+
+
+class _FakePrismaDB:
+    def __init__(self, rows):
+        self._rows = rows
+        self.calls = []
+
+    async def query_raw(self, query, *args):
+        self.calls.append(args)
+        return list(self._rows)
+
+
+class _FakePrismaClient:
+    def __init__(self, written_rows, queued_rows):
+        self.db = _FakePrismaDB(written_rows)
+        self.spend_log_transactions = list(queued_rows)
+        self._spend_log_transactions_lock = asyncio.Lock()
+
+
+@pytest.mark.asyncio
+async def test_message_history_reconstructs_list_shaped_input():
+    """
+    The Responses API sends `input` as a list of items, which is what lands in the stored
+    proxy_server_request. The user turns have to survive session reconstruction.
+    """
+    request_id = "chatcmpl-935b8dad-fdc2-466e-a8ca-e26e5a8a21bb"
+    mock_spend_logs = [
+        {
+            "request_id": request_id,
+            "call_type": "aresponses",
+            "session_id": "a96757c4-c6dc-4c76-b37e-e7dfa526b701",
+            "proxy_server_request": {
+                "input": [
+                    {
+                        "role": "user",
+                        "content": "Remember this: my favorite color is chartreuse.",
+                    }
+                ],
+                "model": "claude-bridge",
+            },
+            "response": _chat_completion_response(request_id, "OK"),
+        }
+    ]
+
+    with patch.object(
+        ResponsesSessionHandler,
+        "get_all_spend_logs_for_previous_response_id",
+        new_callable=AsyncMock,
+    ) as mock_get_spend_logs:
+        mock_get_spend_logs.return_value = mock_spend_logs
+
+        result = await ResponsesSessionHandler.get_chat_completion_message_history_for_previous_response_id(
+            request_id
+        )
+
+    messages = result["messages"]
+    assert [(message.get("role"), message.get("content")) for message in messages] == [
+        ("user", "Remember this: my favorite color is chartreuse."),
+        ("assistant", "OK"),
+    ]
+    assert result["litellm_session_id"] == "a96757c4-c6dc-4c76-b37e-e7dfa526b701"
+
+
+@pytest.mark.asyncio
+async def test_message_history_includes_spend_logs_still_waiting_on_the_batch_writer():
+    """
+    A follow-up sent right after the previous turn arrives before the batch writer has
+    flushed that turn's spend log, so the row is only in memory. The history has to
+    include it anyway.
+    """
+    request_id = "chatcmpl-6c1f5f6c-6a2b-4c62-8d1f-0d9d4ce0a1b2"
+    queued_spend_log = {
+        "request_id": request_id,
+        "call_type": "aresponses",
+        "session_id": "b7d0a5b0-6d20-4a68-9d24-6ba0f6d1f1a3",
+        "proxy_server_request": json.dumps(
+            {
+                "input": [
+                    {
+                        "role": "user",
+                        "content": "Remember this: my favorite color is chartreuse.",
+                    }
+                ],
+                "model": "claude-bridge",
+            }
+        ),
+        "response": json.dumps(_chat_completion_response(request_id, "OK")),
+    }
+    fake_prisma_client = _FakePrismaClient(written_rows=[], queued_rows=[queued_spend_log])
+
+    with patch("litellm.proxy.proxy_server.prisma_client", fake_prisma_client):
+        result = await ResponsesSessionHandler.get_chat_completion_message_history_for_previous_response_id(
+            request_id
+        )
+
+    messages = result["messages"]
+    assert [(message.get("role"), message.get("content")) for message in messages] == [
+        ("user", "Remember this: my favorite color is chartreuse."),
+        ("assistant", "OK"),
+    ]
+    assert result["litellm_session_id"] == "b7d0a5b0-6d20-4a68-9d24-6ba0f6d1f1a3"
+    assert fake_prisma_client.spend_log_transactions == [queued_spend_log]
+
+
+@pytest.mark.asyncio
+async def test_message_history_merges_written_and_queued_turns_in_order():
+    """
+    Turn 1 already flushed to the DB, turn 2 still queued: the follow-up sees the whole
+    conversation, in order, with no row counted twice.
+    """
+    session_id = "5c5f9a3e-1c86-4c0e-9d7c-0a54b8a0f2f1"
+    first_request_id = "chatcmpl-1111"
+    second_request_id = "chatcmpl-2222"
+    written_spend_log = {
+        "request_id": first_request_id,
+        "call_type": "aresponses",
+        "session_id": session_id,
+        "proxy_server_request": {
+            "input": [{"role": "user", "content": "My favorite color is chartreuse."}],
+            "model": "claude-bridge",
+        },
+        "response": _chat_completion_response(first_request_id, "Got it."),
+    }
+    queued_spend_log = {
+        "request_id": second_request_id,
+        "call_type": "aresponses",
+        "session_id": session_id,
+        "proxy_server_request": json.dumps(
+            {
+                "input": [{"role": "user", "content": "And my favorite city is Lisbon."}],
+                "model": "claude-bridge",
+            }
+        ),
+        "response": json.dumps(_chat_completion_response(second_request_id, "Noted.")),
+    }
+    fake_prisma_client = _FakePrismaClient(
+        written_rows=[written_spend_log],
+        queued_rows=[written_spend_log, queued_spend_log],
+    )
+
+    with patch("litellm.proxy.proxy_server.prisma_client", fake_prisma_client):
+        result = await ResponsesSessionHandler.get_chat_completion_message_history_for_previous_response_id(
+            second_request_id
+        )
+
+    messages = result["messages"]
+    assert [(message.get("role"), message.get("content")) for message in messages] == [
+        ("user", "My favorite color is chartreuse."),
+        ("assistant", "Got it."),
+        ("user", "And my favorite city is Lisbon."),
+        ("assistant", "Noted."),
+    ]
+    assert result["litellm_session_id"] == session_id
+
+
+@pytest.mark.asyncio
+async def test_message_history_ignores_queued_spend_logs_from_other_sessions():
+    request_id = "chatcmpl-3333"
+    written_spend_log = {
+        "request_id": request_id,
+        "call_type": "aresponses",
+        "session_id": "session-a",
+        "proxy_server_request": {
+            "input": [{"role": "user", "content": "Hello from session a."}],
+            "model": "claude-bridge",
+        },
+        "response": _chat_completion_response(request_id, "Hi."),
+    }
+    other_session_spend_log = {
+        "request_id": "chatcmpl-4444",
+        "call_type": "aresponses",
+        "session_id": "session-b",
+        "proxy_server_request": json.dumps(
+            {
+                "input": [{"role": "user", "content": "Hello from session b."}],
+                "model": "claude-bridge",
+            }
+        ),
+        "response": json.dumps(_chat_completion_response("chatcmpl-4444", "Hi there.")),
+    }
+    fake_prisma_client = _FakePrismaClient(
+        written_rows=[written_spend_log],
+        queued_rows=[other_session_spend_log],
+    )
+
+    with patch("litellm.proxy.proxy_server.prisma_client", fake_prisma_client):
+        result = await ResponsesSessionHandler.get_chat_completion_message_history_for_previous_response_id(
+            request_id
+        )
+
+    messages = result["messages"]
+    assert [(message.get("role"), message.get("content")) for message in messages] == [
+        ("user", "Hello from session a."),
+        ("assistant", "Hi."),
+    ]
+
+
+@pytest.mark.asyncio
+async def test_message_history_looks_up_the_decoded_chat_completion_id():
+    """
+    A `previous_response_id` handed back by the proxy is base64 encoded; spend logs store
+    the bare chat completion id, so that is what the lookup has to query on.
+    """
+    request_id = "chatcmpl-935b8dad-fdc2-466e-a8ca-e26e5a8a21bb"
+    encoded_response_id = ResponsesAPIRequestUtils._build_responses_api_response_id(
+        custom_llm_provider="anthropic",
+        model_id="e0f302a1412e78470ebb28cbed01fff5f88c0d331c667e9f2ba4b413c6fbd282",
+        response_id=request_id,
+    )
+    fake_prisma_client = _FakePrismaClient(written_rows=[], queued_rows=[])
+
+    with patch("litellm.proxy.proxy_server.prisma_client", fake_prisma_client):
+        await ResponsesSessionHandler.get_all_spend_logs_for_previous_response_id(
+            encoded_response_id
+        )
+
+    assert fake_prisma_client.db.calls == [(request_id,)]
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_response_id.py b/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_response_id.py
new file mode 100644
index 00000000000..97f35900e9d
--- /dev/null
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_response_id.py
@@ -0,0 +1,130 @@
+from unittest.mock import MagicMock
+
+import pytest
+
+from litellm.responses.litellm_completion_transformation.streaming_iterator import (
+    LiteLLMCompletionStreamingIterator,
+)
+from litellm.responses.utils import ResponsesAPIRequestUtils
+from litellm.types.utils import Delta, ModelResponseStream, StreamingChoices
+
+CHAT_COMPLETION_ID = "chatcmpl-77d33d09-effa-4cd2-9c0d-c742d4358256"
+RESPONSE_ID_EVENT_TYPES = frozenset(
+    {"response.created", "response.in_progress", "response.completed"}
+)
+
+
+def _chunk(content: str, finish_reason: str | None = None) -> ModelResponseStream:
+    return ModelResponseStream(
+        id=CHAT_COMPLETION_ID,
+        created=1748575031,
+        model="claude-haiku-4-5",
+        object="chat.completion.chunk",
+        choices=[
+            StreamingChoices(
+                index=0,
+                delta=Delta(role="assistant", content=content),
+                finish_reason=finish_reason,
+            )
+        ],
+    )
+
+
+class _FakeStreamWrapper:
+    def __init__(self, chunks):
+        self._chunks = list(chunks)
+        self.logging_obj = MagicMock()
+
+    def __iter__(self):
+        return self
+
+    def __next__(self):
+        if not self._chunks:
+            raise StopIteration
+        return self._chunks.pop(0)
+
+    def __aiter__(self):
+        return self
+
+    async def __anext__(self):
+        if not self._chunks:
+            raise StopAsyncIteration
+        return self._chunks.pop(0)
+
+
+def _build_iterator(chunks) -> LiteLLMCompletionStreamingIterator:
+    return LiteLLMCompletionStreamingIterator(
+        model="claude-haiku-4-5",
+        litellm_custom_stream_wrapper=_FakeStreamWrapper(chunks),
+        request_input="What is the weather in San Francisco?",
+        responses_api_request={},
+        custom_llm_provider="anthropic",
+        litellm_metadata={},
+    )
+
+
+def _response_ids(events) -> list[str]:
+    return [
+        event.response.id
+        for event in events
+        if getattr(event, "type", None) in RESPONSE_ID_EVENT_TYPES
+    ]
+
+
+@pytest.mark.asyncio
+async def test_streaming_events_share_the_chat_completion_response_id():
+    """
+    Every event of a bridged stream has to carry the same id, and that id has to decode
+    to the chat completion id spend tracking stores as `request_id`. Otherwise a
+    follow-up `previous_response_id` matches no session and the conversation is dropped.
+    """
+    iterator = _build_iterator([_chunk("Hello"), _chunk("!", finish_reason="stop")])
+
+    events = [event async for event in iterator]
+
+    response_ids = _response_ids(events)
+    assert len(response_ids) == 3
+    assert len(set(response_ids)) == 1
+    decoded = ResponsesAPIRequestUtils._decode_responses_api_response_id(response_ids[0])
+    assert decoded["response_id"] == CHAT_COMPLETION_ID
+    assert decoded["custom_llm_provider"] == "anthropic"
+
+
+def test_sync_streaming_events_share_the_chat_completion_response_id():
+    iterator = _build_iterator([_chunk("Hello"), _chunk("!", finish_reason="stop")])
+
+    events = list(iterator)
+
+    response_ids = _response_ids(events)
+    assert len(response_ids) == 3
+    assert len(set(response_ids)) == 1
+    assert (
+        ResponsesAPIRequestUtils._decode_responses_api_response_id(response_ids[0])["response_id"]
+        == CHAT_COMPLETION_ID
+    )
+
+
+@pytest.mark.asyncio
+async def test_streaming_emits_every_chunk_after_priming_the_response_id():
+    iterator = _build_iterator(
+        [_chunk("Hel"), _chunk("lo"), _chunk("!", finish_reason="stop")]
+    )
+
+    events = [event async for event in iterator]
+
+    deltas = "".join(
+        event.delta for event in events if getattr(event, "type", None) == "response.output_text.delta"
+    )
+    assert deltas == "Hello!"
+
+
+@pytest.mark.asyncio
+async def test_streaming_response_id_falls_back_when_upstream_yields_nothing():
+    iterator = _build_iterator([])
+
+    events = [event async for event in iterator]
+
+    response_ids = _response_ids(events)
+    assert response_ids
+    assert len(set(response_ids)) == 1
+    assert response_ids[0].startswith("resp_")

From 05ee5756e7c0b8ff4449d238dd2918f90c861923 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 11:17:02 -0700
Subject: [PATCH 28/93] refactor(responses): rebuild the streaming snapshot
 output instead of mutating items

Align the response.completed item IDs by copying each output item rather than
writing to it in place, and move the regression cases into the existing
completion-response and image-generation test modules.
---
 .../streaming_iterator.py                     |  48 ++--
 .../test_image_generation_output.py           |  44 ++++
 .../test_litellm_completion_responses.py      | 174 ++++++++++++++
 .../test_response_output_item_id_prefixes.py  | 214 ------------------
 4 files changed, 242 insertions(+), 238 deletions(-)
 delete mode 100644 tests/test_litellm/responses/litellm_completion_transformation/test_response_output_item_id_prefixes.py

diff --git a/litellm/responses/litellm_completion_transformation/streaming_iterator.py b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
index 2a94fcb2a89..ff05fc0d5c6 100644
--- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py
+++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
@@ -48,6 +48,22 @@ from litellm.types.utils import (
 )
 
 
+def _output_items_with_id(items: tuple[Any, ...], item_type: str, item_id: str | None) -> tuple[Any, ...]:
+    if item_id is None:
+        return items
+
+    target_index: Final = next(
+        (index for index, item in enumerate(items) if getattr(item, "type", None) == item_type),
+        None,
+    )
+    if target_index is None:
+        return items
+
+    return tuple(
+        item.model_copy(update={"id": item_id}) if index == target_index else item for index, item in enumerate(items)
+    )
+
+
 class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
     """
     Async iterator for processing streaming responses from the Responses API.
@@ -1059,34 +1075,18 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
         chat_completion_delta: Final[ChatCompletionDelta] = choice.delta
         return chat_completion_delta.content or ""
 
-    def _align_output_item_ids_with_streamed_ids(self, responses_api_response: ResponsesAPIResponse) -> None:
+    def _output_with_streamed_item_ids(self, responses_api_response: ResponsesAPIResponse) -> tuple[Any, ...]:
         """
         Reuse the item IDs already emitted by the incremental streaming events in the
         ``response.completed`` snapshot, so a streaming client that replays the snapshot
         sends back the same IDs it observed mid-stream.
         """
-        self._set_first_output_item_id(responses_api_response, "message", self._cached_item_id)
-        self._set_first_output_item_id(responses_api_response, "reasoning", self._cached_reasoning_item_id)
-
-    @staticmethod
-    def _set_first_output_item_id(
-        responses_api_response: ResponsesAPIResponse,
-        item_type: str,
-        cached_id: str | None,
-    ) -> None:
-        if cached_id is None:
-            return
-
-        for item in getattr(responses_api_response, "output", None) or []:
-            current_type = item.get("type") if isinstance(item, dict) else getattr(item, "type", None)
-            if current_type != item_type:
-                continue
-
-            if isinstance(item, dict):
-                item["id"] = cached_id
-            else:
-                item.id = cached_id
-            return
+        message_aligned: Final = _output_items_with_id(
+            tuple(responses_api_response.output or ()),
+            "message",
+            self._cached_item_id,
+        )
+        return _output_items_with_id(message_aligned, "reasoning", self._cached_reasoning_item_id)
 
     def _emit_response_completed_event(self, litellm_model_response: ModelResponse) -> ResponseCompletedEvent | None:
         if litellm_model_response:
@@ -1113,7 +1113,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
             if self._cached_response_id:
                 responses_api_response.id = self._cached_response_id
 
-            self._align_output_item_ids_with_streamed_ids(responses_api_response)
+            responses_api_response.output = list(self._output_with_streamed_item_ids(responses_api_response))
 
             # Encode the response ID to match non-streaming behavior
             encoded_response: Final = ResponsesAPIRequestUtils._update_responses_api_response_id_with_model_id(
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_image_generation_output.py b/tests/test_litellm/responses/litellm_completion_transformation/test_image_generation_output.py
index 41057d49a97..a0bf8664551 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_image_generation_output.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_image_generation_output.py
@@ -199,3 +199,47 @@ class TestExtractMessageOutputItemsIntegration:
         assert len(result) == 1
         assert isinstance(result[0], GenericResponseOutputItem)
         assert result[0].type == "message"
+
+
+class TestImageGenerationOutputItemIds:
+    """Image generation call IDs must use the ig_ prefix (issue #27333).
+
+    Native OpenAI Responses validates the prefix before it looks the item up, so a
+    replayed chatcmpl-*_img_N ID is rejected outright.
+    """
+
+    def _choice_with_images(self, count):
+        mock_message = Mock(spec=Message)
+        mock_message.images = [
+            {"image_url": {"url": f"data:image/png;base64,IMG{idx}"}}
+            for idx in range(count)
+        ]
+        mock_choice = Mock(spec=Choices)
+        mock_choice.message = mock_message
+        mock_choice.finish_reason = "stop"
+        return mock_choice
+
+    def _chat_completion_response(self):
+        mock_response = Mock(spec=ModelResponse)
+        mock_response.id = "chatcmpl-dfa2da3a-1586-4ff7-b64e-f59c692a5d11"
+        return mock_response
+
+    def test_image_generation_item_id_uses_ig_prefix(self):
+        result = LiteLLMCompletionResponsesConfig._extract_image_generation_output_items(
+            chat_completion_response=self._chat_completion_response(),
+            choice=self._choice_with_images(2),
+        )
+
+        assert len(result) == 2
+        for item in result:
+            assert item.id.startswith("ig_")
+            assert "chatcmpl-" not in item.id
+            assert "_img_" not in item.id
+
+    def test_image_generation_item_ids_are_unique(self):
+        result = LiteLLMCompletionResponsesConfig._extract_image_generation_output_items(
+            chat_completion_response=self._chat_completion_response(),
+            choice=self._choice_with_images(3),
+        )
+
+        assert len({item.id for item in result}) == 3
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
index daa732e032a..0a2621b94e6 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
@@ -3771,3 +3771,177 @@ def test_function_call_tool_id_falls_back_to_unique_id_for_degenerate_call_id():
         id="fc_2", call_id="call_tokyo", name="get_weather", arguments="{}"
     )
     assert convert(openai)["id"] == "call_tokyo"
+
+
+BRIDGED_CHAT_COMPLETION_ID = "chatcmpl-dfa2da3a-1586-4ff7-b64e-f59c692a5d11"
+
+
+def _bridged_chat_completion_response(**overrides):
+    defaults = dict(
+        id=BRIDGED_CHAT_COMPLETION_ID,
+        created=1717000000,
+        model="claude-sonnet-4-5",
+        object="chat.completion",
+        choices=[
+            Choices(
+                index=0,
+                finish_reason="stop",
+                message=Message(role="assistant", content="apple"),
+            )
+        ],
+        usage=Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15),
+    )
+    defaults.update(overrides)
+    return ModelResponse(**defaults)
+
+
+def _bridged_output_items(response, item_type):
+    return [item for item in response.output if getattr(item, "type", None) == item_type]
+
+
+class TestBridgedOutputItemIdPrefixes:
+    """Bridged output items must carry Responses API ID prefixes (issue #27333).
+
+    Native OpenAI Responses rejects a replayed history whose message item ID does not
+    begin with "msg", so leaking the upstream chatcmpl-* ID makes the conversation
+    impossible to hand off from a bridged provider to OpenAI.
+    """
+
+    def _transform(self, chat_completion_response):
+        return LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
+            request_input="Say the single word: apple",
+            responses_api_request={},
+            chat_completion_response=chat_completion_response,
+        )
+
+    def test_message_item_id_uses_msg_prefix(self):
+        response = self._transform(_bridged_chat_completion_response())
+
+        message_items = _bridged_output_items(response, "message")
+        assert len(message_items) == 1
+        assert message_items[0].id.startswith("msg_")
+
+    def test_message_item_id_does_not_leak_chat_completion_id(self):
+        response = self._transform(_bridged_chat_completion_response())
+
+        for item in _bridged_output_items(response, "message"):
+            assert item.id != BRIDGED_CHAT_COMPLETION_ID
+            assert not item.id.startswith("chatcmpl-")
+
+    def test_message_item_ids_are_unique_across_responses(self):
+        first = self._transform(_bridged_chat_completion_response())
+        second = self._transform(_bridged_chat_completion_response())
+
+        first_id = _bridged_output_items(first, "message")[0].id
+        second_id = _bridged_output_items(second, "message")[0].id
+        assert first_id != second_id
+
+    def _reasoning_items(self):
+        message = Message(role="assistant", content="apple")
+        message.reasoning_content = "thinking about fruit"
+        choice = Choices(index=0, finish_reason="stop", message=message)
+        return LiteLLMCompletionResponsesConfig._extract_reasoning_output_items(
+            chat_completion_response=_bridged_chat_completion_response(),
+            choices=[choice],
+        )
+
+    def test_reasoning_item_id_uses_rs_prefix(self):
+        items = self._reasoning_items()
+
+        assert len(items) == 1
+        assert items[0].id.startswith("rs_")
+
+    def test_reasoning_item_id_is_not_a_salted_hash(self):
+        """Python's hash() is salted per process, so the old rs_{hash(...)} ID for the
+        same reasoning text differed between workers and across restarts."""
+        suffix = self._reasoning_items()[0].id.removeprefix("rs_")
+
+        assert not suffix.lstrip("-").isdigit()
+        assert not suffix.startswith("-")
+
+
+class TestStreamingSnapshotItemIds:
+    """The response.completed snapshot must reuse the streamed item ID (issue #27333).
+
+    The incremental events already minted msg_* IDs while the final snapshot went back
+    through the non-streaming transform, so a streaming client replaying the snapshot
+    sent back an ID it had never been shown.
+    """
+
+    def _make_iterator(self):
+        from unittest.mock import Mock
+
+        import litellm
+        from litellm.responses.litellm_completion_transformation.streaming_iterator import (
+            LiteLLMCompletionStreamingIterator,
+        )
+
+        mock_stream_wrapper = Mock(spec=litellm.CustomStreamWrapper)
+        mock_stream_wrapper.logging_obj = Mock()
+        return LiteLLMCompletionStreamingIterator(
+            model="anthropic/claude-sonnet-4-5",
+            litellm_custom_stream_wrapper=mock_stream_wrapper,
+            request_input="Say the single word: apple",
+            responses_api_request={},
+            custom_llm_provider="anthropic",
+        )
+
+    def _make_chunk(self, content):
+        from litellm.types.utils import Delta, ModelResponseStream, StreamingChoices
+
+        return ModelResponseStream(
+            id=BRIDGED_CHAT_COMPLETION_ID,
+            choices=[
+                StreamingChoices(
+                    index=0,
+                    delta=Delta(content=content, role="assistant"),
+                    finish_reason=None,
+                )
+            ],
+            created=1717000000,
+            model="claude-sonnet-4-5",
+            object="chat.completion.chunk",
+        )
+
+    def test_incremental_item_id_uses_msg_prefix(self):
+        iterator = self._make_iterator()
+
+        event = iterator._transform_chat_completion_chunk_to_response_api_chunk(
+            self._make_chunk("apple")
+        )
+
+        assert event is not None
+        assert event.item_id.startswith("msg_")
+        assert event.item_id != BRIDGED_CHAT_COMPLETION_ID
+
+    def test_completed_snapshot_reuses_streamed_item_id(self):
+        iterator = self._make_iterator()
+
+        streamed_event = iterator._transform_chat_completion_chunk_to_response_api_chunk(
+            self._make_chunk("apple")
+        )
+        assert streamed_event is not None
+
+        completed_event = iterator._emit_response_completed_event(
+            _bridged_chat_completion_response()
+        )
+
+        assert completed_event is not None
+        message_items = _bridged_output_items(completed_event.response, "message")
+        assert len(message_items) == 1
+        assert message_items[0].id == streamed_event.item_id
+
+    def test_completed_snapshot_item_id_is_replayable(self):
+        iterator = self._make_iterator()
+        iterator._transform_chat_completion_chunk_to_response_api_chunk(
+            self._make_chunk("apple")
+        )
+
+        completed_event = iterator._emit_response_completed_event(
+            _bridged_chat_completion_response()
+        )
+
+        assert completed_event is not None
+        for item in _bridged_output_items(completed_event.response, "message"):
+            assert item.id.startswith("msg_")
+            assert not item.id.startswith("chatcmpl-")
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_response_output_item_id_prefixes.py b/tests/test_litellm/responses/litellm_completion_transformation/test_response_output_item_id_prefixes.py
deleted file mode 100644
index 4b24b2be90d..00000000000
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_response_output_item_id_prefixes.py
+++ /dev/null
@@ -1,214 +0,0 @@
-"""
-Regression tests for the Chat Completions -> Responses API bridge item IDs.
-
-Bridged output items must carry Responses API ID prefixes (msg_, ig_, rs_) rather
-than the upstream chatcmpl-* ID. Native OpenAI Responses rejects a replayed history
-whose message item ID does not begin with "msg", and rejects an image generation
-call whose ID does not begin with "ig".
-
-Regression test for https://github.com/BerriAI/litellm/issues/27333
-"""
-
-from unittest.mock import Mock
-
-import litellm
-from litellm.responses.litellm_completion_transformation.streaming_iterator import (
-    LiteLLMCompletionStreamingIterator,
-)
-from litellm.responses.litellm_completion_transformation.transformation import (
-    LiteLLMCompletionResponsesConfig,
-)
-from litellm.types.utils import (
-    Choices,
-    Delta,
-    Message,
-    ModelResponse,
-    ModelResponseStream,
-    StreamingChoices,
-    Usage,
-)
-
-CHAT_COMPLETION_ID = "chatcmpl-dfa2da3a-1586-4ff7-b64e-f59c692a5d11"
-
-
-def _make_chat_completion_response(**overrides) -> ModelResponse:
-    defaults = dict(
-        id=CHAT_COMPLETION_ID,
-        created=1717000000,
-        model="claude-sonnet-4-5",
-        object="chat.completion",
-        choices=[
-            Choices(
-                index=0,
-                finish_reason="stop",
-                message=Message(role="assistant", content="apple"),
-            )
-        ],
-        usage=Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15),
-    )
-    defaults.update(overrides)
-    return ModelResponse(**defaults)
-
-
-def _transform(chat_completion_response):
-    return LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
-        request_input="Say the single word: apple",
-        responses_api_request={},
-        chat_completion_response=chat_completion_response,
-    )
-
-
-def _output_items_of_type(response, item_type):
-    return [item for item in response.output if getattr(item, "type", None) == item_type]
-
-
-class TestMessageOutputItemIds:
-    def test_message_item_id_uses_msg_prefix(self):
-        response = _transform(_make_chat_completion_response())
-
-        message_items = _output_items_of_type(response, "message")
-        assert len(message_items) == 1
-        assert message_items[0].id.startswith("msg_")
-
-    def test_message_item_id_does_not_leak_chat_completion_id(self):
-        response = _transform(_make_chat_completion_response())
-
-        for item in _output_items_of_type(response, "message"):
-            assert item.id != CHAT_COMPLETION_ID
-            assert not item.id.startswith("chatcmpl-")
-
-    def test_message_item_ids_are_unique_across_responses(self):
-        first = _transform(_make_chat_completion_response())
-        second = _transform(_make_chat_completion_response())
-
-        first_id = _output_items_of_type(first, "message")[0].id
-        second_id = _output_items_of_type(second, "message")[0].id
-        assert first_id != second_id
-
-
-class TestImageGenerationOutputItemIds:
-    def _make_choice_with_images(self, count):
-        message = Mock(spec=Message)
-        message.images = [
-            {"image_url": {"url": f"data:image/png;base64,IMG{idx}"}} for idx in range(count)
-        ]
-        choice = Mock(spec=Choices)
-        choice.message = message
-        choice.finish_reason = "stop"
-        return choice
-
-    def test_image_generation_item_id_uses_ig_prefix(self):
-        items = LiteLLMCompletionResponsesConfig._extract_image_generation_output_items(
-            chat_completion_response=_make_chat_completion_response(),
-            choice=self._make_choice_with_images(2),
-        )
-
-        assert len(items) == 2
-        for item in items:
-            assert item.id.startswith("ig_")
-            assert "chatcmpl-" not in item.id
-            assert "_img_" not in item.id
-
-    def test_image_generation_item_ids_are_unique(self):
-        items = LiteLLMCompletionResponsesConfig._extract_image_generation_output_items(
-            chat_completion_response=_make_chat_completion_response(),
-            choice=self._make_choice_with_images(3),
-        )
-
-        assert len({item.id for item in items}) == 3
-
-
-class TestReasoningOutputItemIds:
-    def _reasoning_items(self):
-        message = Message(role="assistant", content="apple")
-        message.reasoning_content = "thinking about fruit"
-        choice = Choices(index=0, finish_reason="stop", message=message)
-        return LiteLLMCompletionResponsesConfig._extract_reasoning_output_items(
-            chat_completion_response=_make_chat_completion_response(),
-            choices=[choice],
-        )
-
-    def test_reasoning_item_id_uses_rs_prefix(self):
-        items = self._reasoning_items()
-
-        assert len(items) == 1
-        assert items[0].id.startswith("rs_")
-
-    def test_reasoning_item_id_is_not_a_salted_hash(self):
-        item_id = self._reasoning_items()[0].id
-
-        suffix = item_id.removeprefix("rs_")
-        assert not suffix.lstrip("-").isdigit()
-        assert not suffix.startswith("-")
-
-
-class TestStreamingItemIdConsistency:
-    def _make_iterator(self):
-        mock_stream_wrapper = Mock(spec=litellm.CustomStreamWrapper)
-        mock_stream_wrapper.logging_obj = Mock()
-        return LiteLLMCompletionStreamingIterator(
-            model="anthropic/claude-sonnet-4-5",
-            litellm_custom_stream_wrapper=mock_stream_wrapper,
-            request_input="Say the single word: apple",
-            responses_api_request={},
-            custom_llm_provider="anthropic",
-        )
-
-    def _make_chunk(self, chunk_id, content, finish_reason=None):
-        return ModelResponseStream(
-            id=chunk_id,
-            choices=[
-                StreamingChoices(
-                    index=0,
-                    delta=Delta(content=content, role="assistant"),
-                    finish_reason=finish_reason,
-                )
-            ],
-            created=1717000000,
-            model="claude-sonnet-4-5",
-            object="chat.completion.chunk",
-        )
-
-    def test_incremental_item_id_uses_msg_prefix(self):
-        iterator = self._make_iterator()
-
-        event = iterator._transform_chat_completion_chunk_to_response_api_chunk(
-            self._make_chunk(CHAT_COMPLETION_ID, "apple")
-        )
-
-        assert event is not None
-        assert event.item_id.startswith("msg_")
-        assert event.item_id != CHAT_COMPLETION_ID
-
-    def test_completed_snapshot_reuses_streamed_item_id(self):
-        iterator = self._make_iterator()
-
-        streamed_event = iterator._transform_chat_completion_chunk_to_response_api_chunk(
-            self._make_chunk(CHAT_COMPLETION_ID, "apple")
-        )
-        assert streamed_event is not None
-        streamed_item_id = streamed_event.item_id
-
-        completed_event = iterator._emit_response_completed_event(
-            _make_chat_completion_response()
-        )
-
-        assert completed_event is not None
-        message_items = _output_items_of_type(completed_event.response, "message")
-        assert len(message_items) == 1
-        assert message_items[0].id == streamed_item_id
-
-    def test_completed_snapshot_item_id_is_replayable(self):
-        iterator = self._make_iterator()
-        iterator._transform_chat_completion_chunk_to_response_api_chunk(
-            self._make_chunk(CHAT_COMPLETION_ID, "apple")
-        )
-
-        completed_event = iterator._emit_response_completed_event(
-            _make_chat_completion_response()
-        )
-
-        assert completed_event is not None
-        for item in _output_items_of_type(completed_event.response, "message"):
-            assert item.id.startswith("msg_")
-            assert not item.id.startswith("chatcmpl-")

From 766f72f1d7c1dc7b7b1d1d93f8dde46090f76f9e Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 11:19:42 -0700
Subject: [PATCH 29/93] fix(anthropic): round-trip thinking blocks to OpenAI
 backends

The experimental /v1/messages adapters lost prior-turn reasoning three
different ways once the request left for an OpenAI-shaped backend.

On the Responses path, thinking blocks were flattened into output_text
inside the assistant message, so the model read its own private reasoning
back as visible prose and no reasoning item was ever sent. They now become
Responses reasoning input items, grouped by signature so summary parts that
arrived as one item go back as one item. The response direction stops
hardcoding signature=None and carries the reasoning item id, which is what
lets the next turn regroup them; the streaming wrapper emits the matching
signature_delta.

On the chat completions path the adapter attached thinking_blocks but never
set reasoning_content, so Moonshot and DeepSeek substituted a single-space
placeholder and other providers sent nothing. It is now derived from the
thinking blocks.

With use_chat_completions_url_for_anthropic_messages and a model that itself
bridges to /v1/responses, the assistant message was dropped whole: reasoning,
text, and all. That branch now emits the reasoning items and the message
content alongside the tool calls.

Fixes #24985
---
 .../transformation.py                         |  32 +++++-
 .../prompt_templates/common_utils.py          |  32 ++++++
 .../adapters/transformation.py                |   4 +
 .../responses_adapters/streaming_iterator.py  |  13 ++-
 .../responses_adapters/transformation.py      | 107 ++++++++++++------
 ...responses_transformation_transformation.py |  87 ++++++++++++++
 ...al_pass_through_adapters_transformation.py |  42 +++++++
 ...t_responses_adapters_streaming_iterator.py |  14 ++-
 .../test_responses_adapters_transformation.py |  90 ++++++++++++++-
 9 files changed, 379 insertions(+), 42 deletions(-)

diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py
index 6103b1bf484..ea54bd83e12 100644
--- a/litellm/completion_extras/litellm_responses_transformation/transformation.py
+++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py
@@ -21,6 +21,9 @@ from pydantic import BaseModel
 import litellm
 from litellm import ModelResponse
 from litellm._logging import verbose_logger
+from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    responses_reasoning_item_from_thinking_blocks,
+)
 from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator
 from litellm.llms.base_llm.bridges.completion_transformation import (
     CompletionTransformationBridge,
@@ -85,6 +88,21 @@ def _get_reasoning_items(
     return []
 
 
+def _reasoning_input_items(msg: "AllMessageValues") -> list[dict[str, object]]:  # mutable-ok: API message payload
+    """Reasoning input items for an assistant message.
+
+    Stored reasoning items win because they carry an id the Responses API minted; thinking
+    blocks are the fallback for turns that arrived over another API surface.
+    """
+    stored: Final = [_reasoning_item_to_response_input(r_item) for r_item in _get_reasoning_items(msg)]
+    if stored:
+        return stored
+    from_thinking: Final = responses_reasoning_item_from_thinking_blocks(
+        cast(Iterable[Mapping[str, Any]], msg.get("thinking_blocks") or ())  # cast-ok: untyped client thinking blocks
+    )
+    return [from_thinking] if from_thinking is not None else []
+
+
 def _build_reasoning_item(
     item_id: str,
     encrypted_content: str | None,
@@ -372,8 +390,15 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
                         )
                     )
             elif role == "assistant" and tool_calls and isinstance(tool_calls, list):
-                for r_item in _get_reasoning_items(msg):
-                    input_items.append(_reasoning_item_to_response_input(r_item))
+                input_items.extend(_reasoning_input_items(msg))
+                if content:
+                    input_items.append(
+                        {
+                            "type": "message",
+                            "role": "assistant",
+                            "content": self._convert_content_to_responses_format(content, "assistant"),
+                        }
+                    )
                 for tool_call in tool_calls:
                     function = tool_call.get("function")
                     custom = tool_call.get("custom")
@@ -400,8 +425,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
                         raise ValueError(f"tool call not supported: {tool_call}")
             elif content is not None:
                 if role == "assistant":
-                    for r_item in _get_reasoning_items(msg):
-                        input_items.append(_reasoning_item_to_response_input(r_item))
+                    input_items.extend(_reasoning_input_items(msg))
                 input_items.append(
                     {
                         "type": "message",
diff --git a/litellm/litellm_core_utils/prompt_templates/common_utils.py b/litellm/litellm_core_utils/prompt_templates/common_utils.py
index 2db5776047b..4211fbe610a 100644
--- a/litellm/litellm_core_utils/prompt_templates/common_utils.py
+++ b/litellm/litellm_core_utils/prompt_templates/common_utils.py
@@ -1549,6 +1549,38 @@ def _extract_reasoning_content(message: dict) -> tuple[str | None, str | None]:
     return None, message_content
 
 
+def reasoning_content_from_thinking_blocks(
+    thinking_blocks: Iterable[Mapping[str, Any]],
+) -> str:
+    """Flatten Anthropic thinking blocks into the `reasoning_content` string chat models expect.
+
+    Redacted blocks carry no readable text, so they contribute nothing.
+    """
+    return "\n".join(
+        text
+        for block in thinking_blocks
+        if block.get("type") == "thinking" and (text := str(block.get("thinking") or ""))
+    )
+
+
+def responses_reasoning_item_from_thinking_blocks(
+    thinking_blocks: Iterable[Mapping[str, Any]],
+) -> dict[str, Any] | None:  # mutable-ok: API message payload
+    """Build a Responses API `reasoning` input item from Anthropic thinking blocks.
+
+    The item carries no `id`: the Responses API rejects an empty one and 404s on any id it
+    did not mint itself, while an item without an id is always accepted.
+    """
+    summary: Final[list[dict[str, Any]]] = [  # mutable-ok: API message payload
+        {"type": "summary_text", "text": text}  # mutable-ok: API message payload
+        for block in thinking_blocks
+        if block.get("type") == "thinking" and (text := str(block.get("thinking") or ""))
+    ]
+    if not summary:
+        return None
+    return {"type": "reasoning", "summary": summary}  # mutable-ok: API message payload
+
+
 def _parse_content_for_reasoning(
     message_text: str | None,
 ) -> tuple[str | None, str | None]:
diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
index 34c2d837127..7c89da81fe6 100644
--- a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
@@ -64,6 +64,7 @@ from openai.types.chat.chat_completion_chunk import Choice as OpenAIStreamingCho
 
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
     parse_tool_call_arguments,
+    reasoning_content_from_thinking_blocks,
     with_prompt_cache_breakpoint,
 )
 from litellm.litellm_core_utils.prompt_templates.factory import (
@@ -592,6 +593,9 @@ class LiteLLMAnthropicMessagesAdapter:
                     assistant_message["tool_calls"] = tool_calls
                 if len(thinking_blocks) > 0:
                     assistant_message["thinking_blocks"] = thinking_blocks
+                reasoning_content = reasoning_content_from_thinking_blocks(thinking_blocks)
+                if reasoning_content:
+                    assistant_message["reasoning_content"] = reasoning_content
                 new_messages.append(assistant_message)
 
         return new_messages
diff --git a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py
index e2ad9c9c6d3..286edb24b9b 100644
--- a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py
+++ b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py
@@ -152,7 +152,7 @@ class AnthropicResponsesStreamWrapper:
             if block_idx < 0:
                 if not delta:
                     return
-                block_idx = self._open_block(item_id, {"type": "thinking", "thinking": ""})
+                block_idx = self._open_block(item_id, {"type": "thinking", "thinking": "", "signature": ""})
             self._chunk_queue.append(
                 {
                     "type": "content_block_delta",
@@ -189,6 +189,17 @@ class AnthropicResponsesStreamWrapper:
             block_idx = self._item_id_to_block_index.get(item_id, -1) if item_id else self._current_block_index
             if block_idx < 0:
                 return
+            done_item_type: Final = (
+                getattr(item, "type", None) or (item.get("type") if isinstance(item, dict) else None) if item else None
+            )
+            if done_item_type == "reasoning" and item_id:
+                self._chunk_queue.append(
+                    {
+                        "type": "content_block_delta",
+                        "index": block_idx,
+                        "delta": {"type": "signature_delta", "signature": item_id},
+                    }
+                )
             self._chunk_queue.append(
                 {
                     "type": "content_block_stop",
diff --git a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
index 25d729d8606..b1061f86d0b 100644
--- a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
@@ -6,12 +6,14 @@ path used for OpenAI and Azure models.
 """
 
 import json
-from collections.abc import Iterable
+from collections.abc import Iterable, Mapping
+from itertools import groupby
 from typing import Any, Final, cast
 
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
     TOOL_RESULT_IMAGE_BOUNDARY,
     TOOL_RESULT_IMAGE_PLACEHOLDER,
+    responses_reasoning_item_from_thinking_blocks,
     with_prompt_cache_breakpoint,
 )
 from litellm.litellm_core_utils.reasoning_effort_utils import (
@@ -100,6 +102,58 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
             if isinstance(block, dict) and block.get("type") == "text" and (text := block.get("text"))  # pyright: ignore[reportUnnecessaryIsInstance]  # untrusted client payload
         ]
 
+    @staticmethod
+    def _summary_part_text(part: object) -> str:
+        if isinstance(part, Mapping):
+            mapping: Final = cast(Mapping[str, Any], part)  # cast-ok: summary parts are untyped provider json
+            return str(mapping.get("text", ""))
+        return str(getattr(part, "text", ""))
+
+    @classmethod
+    def _thinking_blocks_from_reasoning_item(
+        cls,
+        item_id: str | None,
+        summary: Iterable[object],
+    ) -> tuple[dict[str, Any], ...]:  # mutable-ok: API message payload
+        """Anthropic thinking blocks for one Responses reasoning item.
+
+        The reasoning item id rides along as the signature so that a follow-up turn can
+        regroup the summary parts into the single reasoning item they came from.
+        """
+        return tuple(
+            AnthropicResponseContentBlockThinking(
+                type="thinking",
+                thinking=text,
+                signature=item_id or None,
+            ).model_dump()
+            for part in summary
+            if (text := cls._summary_part_text(part))
+        )
+
+    @staticmethod
+    def _assistant_block_group_key(indexed_block: tuple[int, Mapping[str, Any]]) -> str:
+        """Group consecutive thinking blocks sharing a signature; keep every other block alone."""
+        index, block = indexed_block
+        signature: Final = block.get("signature") or ""
+        return f"thinking:{signature}" if block.get("type") == "thinking" else f"block:{index}"
+
+    @classmethod
+    def _assistant_group_to_input_item(
+        cls, group: tuple[Mapping[str, Any], ...]
+    ) -> dict[str, Any] | None:  # mutable-ok: API message payload
+        first: Final = group[0]
+        btype: Final = first.get("type")
+        if btype == "thinking":
+            return responses_reasoning_item_from_thinking_blocks(group)
+        if btype == "tool_use":
+            return {  # mutable-ok: API message payload
+                "type": "function_call",
+                "call_id": first.get("id", ""),
+                "name": first.get("name", ""),
+                "arguments": json.dumps(first.get("input", {})),
+            }
+        return None
+
     def translate_messages_to_responses_input(
         self,
         messages: list[AllAnthropicPassThroughMessageValues],
@@ -113,6 +167,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
           user image         -> message(role=user, input_image)
           user tool_result   -> function_call_output
           assistant text     -> message(role=assistant, output_text)
+          assistant thinking -> reasoning
           assistant tool_use -> function_call
         """
         input_items: Final[list[dict[str, Any]]] = []
@@ -233,27 +288,17 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
                         }
                     )
                 elif isinstance(content, list):
-                    asst_parts: list[dict[str, Any]] = []
-                    for block in content:
-                        if not isinstance(block, dict):
-                            continue
-                        btype = block.get("type")
-                        if btype == "text":
-                            asst_parts.append({"type": "output_text", "text": block.get("text", "")})
-                        elif btype == "tool_use":
-                            # tool_use becomes a top-level function_call item
-                            input_items.append(
-                                {
-                                    "type": "function_call",
-                                    "call_id": block.get("id", ""),
-                                    "name": block.get("name", ""),
-                                    "arguments": json.dumps(block.get("input", {})),
-                                }
-                            )
-                        elif btype == "thinking":
-                            thinking_text = block.get("thinking", "")
-                            if thinking_text:
-                                asst_parts.append({"type": "output_text", "text": thinking_text})
+                    blocks = tuple(block for block in content if isinstance(block, dict))
+                    input_items.extend(
+                        item
+                        for _, group in groupby(enumerate(blocks), key=self._assistant_block_group_key)
+                        if (item := self._assistant_group_to_input_item(tuple(block for _, block in group))) is not None
+                    )
+                    asst_parts: list[dict[str, Any]] = [  # mutable-ok: API message payload
+                        {"type": "output_text", "text": block.get("text", "")}  # mutable-ok: API message payload
+                        for block in blocks
+                        if block.get("type") == "text"
+                    ]
                     if asst_parts:
                         input_items.append(
                             {
@@ -514,16 +559,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
 
         for item in response.output:
             if isinstance(item, ResponseReasoningItem):
-                for summary in item.summary:
-                    text = getattr(summary, "text", "")
-                    if text:
-                        content.append(
-                            AnthropicResponseContentBlockThinking(
-                                type="thinking",
-                                thinking=text,
-                                signature=None,
-                            ).model_dump()
-                        )
+                content.extend(self._thinking_blocks_from_reasoning_item(item.id, item.summary))
 
             elif isinstance(item, ResponseOutputMessage):
                 for part in item.content:
@@ -555,6 +591,13 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
                             content.append(
                                 AnthropicResponseContentBlockText(type="text", text=part.get("text", "")).model_dump()
                             )
+                elif item_type == "reasoning":
+                    content.extend(
+                        self._thinking_blocks_from_reasoning_item(
+                            item.get("id"),
+                            cast(Iterable[object], item.get("summary") or ()),  # cast-ok: untyped provider json
+                        )
+                    )
                 elif item_type == "function_call":
                     try:
                         input_data = json.loads(item.get("arguments", "{}"))
diff --git a/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py b/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py
index 4ff92aaf87d..124dc67b4fd 100644
--- a/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py
+++ b/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py
@@ -3762,3 +3762,90 @@ def test_response_incomplete_stream_event_without_details_defaults_to_length():
     result = iterator.chunk_parser(chunk)
 
     assert result.choices[0].finish_reason == "length"
+
+
+def test_assistant_message_with_tool_calls_keeps_its_content():
+    """Regression for https://github.com/BerriAI/litellm/issues/24985.
+
+    An assistant turn that both answered and called a tool used to lose its whole message:
+    the branch handling tool_calls emitted the calls and dropped the text.
+    """
+    handler = LiteLLMResponsesTransformationHandler()
+    messages = [
+        {"role": "user", "content": "What is the weather in Denver?"},
+        {
+            "role": "assistant",
+            "content": "Let me look that up.",
+            "tool_calls": [
+                {
+                    "id": "call_1",
+                    "type": "function",
+                    "function": {"name": "get_weather", "arguments": '{"city": "Denver"}'},
+                }
+            ],
+        },
+        {"role": "tool", "tool_call_id": "call_1", "content": "88F"},
+    ]
+
+    input_items, _ = handler.convert_chat_completion_messages_to_responses_api(messages)
+
+    assistant_message = next(
+        item for item in input_items if item.get("type") == "message" and item.get("role") == "assistant"
+    )
+    assert assistant_message["content"] == [{"type": "output_text", "text": "Let me look that up."}]
+    assert [item.get("type") for item in input_items] == [
+        "message",
+        "message",
+        "function_call",
+        "function_call_output",
+    ]
+
+
+def test_assistant_thinking_blocks_become_a_reasoning_input_item():
+    """Thinking blocks are how an Anthropic-shaped turn carries reasoning into this bridge."""
+    handler = LiteLLMResponsesTransformationHandler()
+    messages = [
+        {"role": "user", "content": "What is the weather in Denver?"},
+        {
+            "role": "assistant",
+            "content": "Denver is sunny.",
+            "thinking_blocks": [
+                {"type": "thinking", "thinking": "August in Denver is dry.", "signature": "sig1"},
+                {"type": "redacted_thinking", "data": "REDACTED"},
+            ],
+        },
+        {"role": "user", "content": "Why?"},
+    ]
+
+    input_items, _ = handler.convert_chat_completion_messages_to_responses_api(messages)
+
+    reasoning_item = next(item for item in input_items if item.get("type") == "reasoning")
+    assert reasoning_item["summary"] == [{"type": "summary_text", "text": "August in Denver is dry."}]
+    assert "id" not in reasoning_item
+
+
+def test_stored_reasoning_items_win_over_thinking_blocks():
+    """A minted reasoning id beats a re-derived one, so the two must not both be sent."""
+    handler = LiteLLMResponsesTransformationHandler()
+    messages = [
+        {
+            "role": "assistant",
+            "content": "Denver is sunny.",
+            "reasoning_items": [
+                {
+                    "type": "reasoning",
+                    "id": "rs_real",
+                    "summary": [{"type": "summary_text", "text": "August in Denver is dry."}],
+                }
+            ],
+            "thinking_blocks": [
+                {"type": "thinking", "thinking": "August in Denver is dry.", "signature": "rs_real"}
+            ],
+        },
+    ]
+
+    input_items, _ = handler.convert_chat_completion_messages_to_responses_api(messages)
+
+    reasoning_items = [item for item in input_items if item.get("type") == "reasoning"]
+    assert len(reasoning_items) == 1
+    assert reasoning_items[0]["id"] == "rs_real"
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py
index e4dacc308dc..d0169963962 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py
@@ -359,6 +359,48 @@ def test_translate_anthropic_messages_to_openai_thinking_blocks():
     assert result[1]["tool_calls"][0]["id"] == "toolu_01234"
 
 
+def test_translate_anthropic_messages_to_openai_sets_reasoning_content():
+    """Reasoning-aware chat providers read reasoning_content, so thinking text must land there.
+
+    Without it Moonshot and DeepSeek fill in a single-space placeholder and the model gets
+    a blank where its own prior reasoning belongs.
+    """
+
+    anthropic_messages = [
+        AnthropicMessagesUserMessageParam(
+            role="user",
+            content=[{"type": "text", "text": "Which city is best for a picnic?"}],
+        ),
+        AnthopicMessagesAssistantMessageParam(
+            role="assistant",
+            content=[
+                {"type": "thinking", "thinking": "Denver is dry in August.", "signature": "sig1"},
+                {"type": "thinking", "thinking": "San Francisco is foggy.", "signature": "sig2"},
+                {"type": "redacted_thinking", "data": "REDACTED"},
+                {"type": "text", "text": "Denver."},
+            ],
+        ),
+    ]
+
+    result = LiteLLMAnthropicMessagesAdapter().translate_anthropic_messages_to_openai(messages=anthropic_messages)
+
+    assert result[1]["reasoning_content"] == "Denver is dry in August.\nSan Francisco is foggy."
+    assert result[1]["content"] == "Denver."
+
+
+def test_translate_anthropic_messages_to_openai_sets_no_reasoning_content_without_thinking():
+    anthropic_messages = [
+        AnthopicMessagesAssistantMessageParam(
+            role="assistant",
+            content=[{"type": "text", "text": "Denver."}],
+        ),
+    ]
+
+    result = LiteLLMAnthropicMessagesAdapter().translate_anthropic_messages_to_openai(messages=anthropic_messages)
+
+    assert "reasoning_content" not in result[0]
+
+
 def test_translate_anthropic_messages_to_openai_tool_message_placement():
     """Test that tool result messages are placed before user messages in the conversation order."""
 
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_streaming_iterator.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_streaming_iterator.py
index 8b591fcd7da..12a6ab4324f 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_streaming_iterator.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_streaming_iterator.py
@@ -139,14 +139,26 @@ class TestReasoningItemWithoutSummaryText:
             ("content_block_start", 0),
             ("content_block_delta", 0),
             ("content_block_delta", 0),
+            ("content_block_delta", 0),
             ("content_block_stop", 0),
             ("content_block_start", 1),
             ("content_block_delta", 1),
             ("content_block_stop", 1),
         ]
-        assert chunks[1]["content_block"] == {"type": "thinking", "thinking": ""}
+        assert chunks[1]["content_block"] == {"type": "thinking", "thinking": "", "signature": ""}
         assert "".join(c["delta"]["thinking"] for c in chunks[2:4]) == "Weighing options"
 
+    def test_reasoning_item_id_is_streamed_as_the_thinking_signature(self):
+        chunks = _drain_async(self._gpt_turn(reasoning_summary_deltas=["Weighing options"]))
+
+        signature_deltas = [c for c in chunks if c.get("delta", {}).get("type") == "signature_delta"]
+        assert [(c["index"], c["delta"]["signature"]) for c in signature_deltas] == [(0, "rs_1")]
+
+    def test_no_signature_delta_without_a_thinking_block(self):
+        chunks = _drain_async(self._gpt_turn(reasoning_summary_deltas=[]))
+
+        assert not [c for c in chunks if c.get("delta", {}).get("type") == "signature_delta"]
+
 
 class TestToolUseBlockClosedExactlyOnce:
     """Regression for https://github.com/BerriAI/litellm/issues/37273.
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py
index 964f4b9f68b..6479c43ee7a 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py
@@ -486,8 +486,8 @@ class TestTranslateMessagesToResponsesInput:
             }
         ]
 
-    def test_assistant_thinking_block_becomes_output_text(self):
-        """Assistant thinking block text is included as output_text."""
+    def test_assistant_thinking_block_becomes_reasoning_item(self):
+        """Assistant thinking block becomes a reasoning item, never visible assistant prose."""
         messages = [
             {
                 "role": "assistant",
@@ -495,7 +495,65 @@ class TestTranslateMessagesToResponsesInput:
             }
         ]
         result = _translate_messages(messages)
-        assert result[0]["content"] == [{"type": "output_text", "text": "Let me reason step by step."}]
+        assert result == [
+            {
+                "type": "reasoning",
+                "summary": [{"type": "summary_text", "text": "Let me reason step by step."}],
+            }
+        ]
+
+    def test_reasoning_item_carries_no_id(self):
+        """A fabricated reasoning id 404s upstream, so the item must go out without one."""
+        messages = [
+            {
+                "role": "assistant",
+                "content": [{"type": "thinking", "thinking": "Private reasoning.", "signature": "rs_abc123"}],
+            }
+        ]
+        result = _translate_messages(messages)
+        assert "id" not in result[0]
+
+    def test_thinking_blocks_sharing_a_signature_become_one_reasoning_item(self):
+        """Summary parts of one upstream reasoning item are regrouped by their signature."""
+        messages = [
+            {
+                "role": "assistant",
+                "content": [
+                    {"type": "thinking", "thinking": "First part.", "signature": "rs_abc123"},
+                    {"type": "thinking", "thinking": "Second part.", "signature": "rs_abc123"},
+                    {"type": "thinking", "thinking": "A later item.", "signature": "rs_def456"},
+                ],
+            }
+        ]
+        result = _translate_messages(messages)
+        assert result == [
+            {
+                "type": "reasoning",
+                "summary": [
+                    {"type": "summary_text", "text": "First part."},
+                    {"type": "summary_text", "text": "Second part."},
+                ],
+            },
+            {
+                "type": "reasoning",
+                "summary": [{"type": "summary_text", "text": "A later item."}],
+            },
+        ]
+
+    def test_thinking_and_text_stay_separate(self):
+        """The visible answer stays the only thing in the assistant message."""
+        messages = [
+            {
+                "role": "assistant",
+                "content": [
+                    {"type": "thinking", "thinking": "The user wants Denver."},
+                    {"type": "text", "text": "Denver is the best pick."},
+                ],
+            }
+        ]
+        result = _translate_messages(messages)
+        assert [item["type"] for item in result] == ["reasoning", "message"]
+        assert result[1]["content"] == [{"type": "output_text", "text": "Denver is the best pick."}]
 
     def test_assistant_empty_thinking_block_skipped(self):
         """Assistant thinking block with empty thinking text is skipped."""
@@ -1094,7 +1152,7 @@ def _make_function_call_item(call_id: str, name: str, arguments: str) -> MagicMo
     return item
 
 
-def _make_reasoning_item(summaries: List[str]) -> MagicMock:
+def _make_reasoning_item(summaries: List[str], item_id: str = "rs_test_1") -> MagicMock:
     """Build a mock ResponseReasoningItem."""
     from openai.types.responses import ResponseReasoningItem  # type: ignore[import]
 
@@ -1105,6 +1163,7 @@ def _make_reasoning_item(summaries: List[str]) -> MagicMock:
         summary_mocks.append(s)
 
     item = MagicMock(spec=ResponseReasoningItem)
+    item.id = item_id
     item.summary = summary_mocks
     return item
 
@@ -1178,6 +1237,29 @@ class TestTranslateResponse:
         result: Any = _ADAPTER.translate_response(response)
         assert result["content"] == []
 
+    def test_reasoning_item_id_becomes_thinking_signature(self):
+        """The reasoning item id rides back as the signature so the next turn can regroup it."""
+        reasoning = _make_reasoning_item(["Part one.", "Part two."], item_id="rs_abc123")
+        response = _make_mock_response(output=[reasoning])
+        result: Any = _ADAPTER.translate_response(response)
+        assert [block["signature"] for block in result["content"]] == ["rs_abc123", "rs_abc123"]
+
+    def test_dict_reasoning_item_becomes_thinking_block(self):
+        """A reasoning item arriving as a plain dict is kept, not dropped."""
+        response = _make_mock_response(
+            output=[
+                {
+                    "type": "reasoning",
+                    "id": "rs_dict_1",
+                    "summary": [{"type": "summary_text", "text": "Weighing the options."}],
+                }
+            ]
+        )
+        result: Any = _ADAPTER.translate_response(response)
+        assert result["content"] == [
+            {"type": "thinking", "thinking": "Weighing the options.", "signature": "rs_dict_1"}
+        ]
+
     def test_usage_mapped_correctly(self):
         """Input/output tokens from ResponseAPIUsage are mapped to AnthropicUsage."""
         response = _make_mock_response(

From ae25da3d5436f488f31ef6df374c1b65eae976d4 Mon Sep 17 00:00:00 2001
From: Mateo Wang <mateowang.dev1@gmail.com>
Date: Sat, 22 Aug 2026 11:39:10 -0700
Subject: [PATCH 30/93] fix(responses-bridge): keep reasoning text visible to
 inspection-only callers

Guardrails, token counting and rate limiting share the input transform with
the provider path, so moving reasoning onto reasoning_content hid it from
them. Provider-bound callers opt in with replay_reasoning.
---
 .../session_handler.py                        |  2 +
 .../transformation.py                         | 27 +++++++++-
 .../test_reasoning_input_item_preservation.py | 54 ++++++++++++++++++-
 3 files changed, 79 insertions(+), 4 deletions(-)

diff --git a/litellm/responses/litellm_completion_transformation/session_handler.py b/litellm/responses/litellm_completion_transformation/session_handler.py
index dcff26c5b0c..a53d7c68b0a 100644
--- a/litellm/responses/litellm_completion_transformation/session_handler.py
+++ b/litellm/responses/litellm_completion_transformation/session_handler.py
@@ -113,6 +113,7 @@ class ResponsesSessionHandler:
             chat_completion_messages = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages(
                 input=response_input_param,
                 responses_api_request=proxy_server_request_dict or {},
+                replay_reasoning=True,
             )
             chat_completion_message_history.extend(chat_completion_messages)
 
@@ -125,6 +126,7 @@ class ResponsesSessionHandler:
             chat_completion_messages = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages(
                 input=_messages,
                 responses_api_request=proxy_server_request_dict or {},
+                replay_reasoning=True,
             )
             chat_completion_message_history.extend(chat_completion_messages)
 
diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index c2e803c8a43..165c2128d38 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -296,6 +296,7 @@ class LiteLLMCompletionResponsesConfig:
             "messages": LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages(
                 input=input,
                 responses_api_request=responses_api_request,
+                replay_reasoning=True,
             ),
             "model": model,
             "tool_choice": LiteLLMCompletionResponsesConfig._transform_tool_choice(
@@ -340,6 +341,7 @@ class LiteLLMCompletionResponsesConfig:
     def transform_responses_api_input_to_messages(
         input: str | ResponseInputParam,
         responses_api_request: ResponsesAPIOptionalRequestParams | dict,
+        replay_reasoning: bool = False,
     ) -> list[
         AllMessageValues
         | GenericChatCompletionMessage
@@ -349,6 +351,16 @@ class LiteLLMCompletionResponsesConfig:
     ]:
         """
         Transform a Responses API input into a list of messages
+
+        ``replay_reasoning`` belongs to callers whose messages are about to be
+        sent to a model: prior-turn ``reasoning`` items are then rebuilt as
+        assistant ``reasoning_content`` and signed ``thinking_blocks`` so the
+        provider gets its own chain-of-thought back instead of reading it as
+        visible text.
+
+        Callers that only inspect the messages (token counting, rate limiting,
+        guardrail scanning) leave it off, because they need every piece of text
+        in the request to stay readable as message ``content``.
         """
         messages: list[
             AllMessageValues
@@ -367,6 +379,7 @@ class LiteLLMCompletionResponsesConfig:
         messages.extend(
             LiteLLMCompletionResponsesConfig._transform_response_input_param_to_chat_completion_message(
                 input=input,
+                replay_reasoning=replay_reasoning,
             )
         )
 
@@ -443,11 +456,15 @@ class LiteLLMCompletionResponsesConfig:
     @staticmethod
     def _transform_response_input_param_to_chat_completion_message(
         input: str | ResponseInputParam,
+        replay_reasoning: bool = False,
     ) -> list[
         AllMessageValues | GenericChatCompletionMessage | ChatCompletionMessageToolCall | ChatCompletionResponseMessage
     ]:
         """
         Transform a ResponseInputParam into a Chat Completion message
+
+        See ``transform_responses_api_input_to_messages`` for what
+        ``replay_reasoning`` means.
         """
         messages: list[
             AllMessageValues
@@ -463,7 +480,8 @@ class LiteLLMCompletionResponsesConfig:
             for _input in input:
                 chat_completion_messages = (
                     LiteLLMCompletionResponsesConfig._transform_responses_api_input_item_to_chat_completion_message(
-                        input_item=_input
+                        input_item=_input,
+                        replay_reasoning=replay_reasoning,
                     )
                 )
 
@@ -559,6 +577,8 @@ class LiteLLMCompletionResponsesConfig:
                     continue
 
                 messages.extend(chat_completion_messages)
+        if not replay_reasoning:
+            return messages
         return LiteLLMCompletionResponsesConfig._merge_reasoning_only_assistant_messages(messages)
 
     @staticmethod
@@ -1151,6 +1171,7 @@ class LiteLLMCompletionResponsesConfig:
     @staticmethod
     def _transform_responses_api_input_item_to_chat_completion_message(
         input_item: Any,
+        replay_reasoning: bool = False,
     ) -> list[AllMessageValues | GenericChatCompletionMessage | ChatCompletionResponseMessage]:
         """
         Transform a Responses API input item into a Chat Completion message
@@ -1179,12 +1200,14 @@ class LiteLLMCompletionResponsesConfig:
             return LiteLLMCompletionResponsesConfig._transform_responses_api_function_call_to_chat_completion_message(
                 function_call=input_item
             )
-        elif input_item.get("type") == "reasoning":
+        elif replay_reasoning and input_item.get("type") == "reasoning":
             # A ResponseReasoningItemParam carries the prior-turn chain-of-thought.
             # Chat-completions providers (DeepSeek V4, Kimi K2.6, ...) expect this
             # to be replayed as `reasoning_content` on an assistant message, not as
             # visible `content` (prompt pollution) and not dropped (DeepSeek V4
             # rejects multi-turn requests with a missing `reasoning_content`).
+            # Callers that only inspect the request skip this branch so the
+            # reasoning text stays visible to them as message content.
             reasoning_text = LiteLLMCompletionResponsesConfig._extract_reasoning_text_from_input_item(  # rebind-ok: extraction result
                 input_item
             )
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py b/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
index b21be67b150..821b8fffe9a 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
@@ -23,13 +23,19 @@ from litellm.types.utils import Message
 
 def _transform_item(item):
     return LiteLLMCompletionResponsesConfig._transform_responses_api_input_item_to_chat_completion_message(
-        input_item=item
+        input_item=item, replay_reasoning=True
     )
 
 
 def _transform_input(input_items):
     return LiteLLMCompletionResponsesConfig._transform_response_input_param_to_chat_completion_message(
-        input=input_items
+        input=input_items, replay_reasoning=True
+    )
+
+
+def _inspect_input(input_items):
+    return LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages(
+        input=input_items, responses_api_request={}
     )
 
 
@@ -266,6 +272,50 @@ class TestEncryptedReasoningRoundTrip:
         assert messages[1]["role"] == "user"
 
 
+class TestInspectionCallersStillSeeReasoningText:
+    """Token counting, rate limiting and guardrails read the request as text.
+
+    Moving reasoning onto ``reasoning_content`` is only right for messages on
+    their way to a provider. A guardrail scanning for sensitive data reads
+    message ``content``, so the inspection default keeps the text there.
+    """
+
+    def test_reasoning_text_stays_readable_as_content_by_default(self):
+        messages = _inspect_input(
+            [
+                {"role": "user", "content": "What did we decide?"},
+                {
+                    "type": "reasoning",
+                    "id": "rs_1",
+                    "content": [{"type": "output_text", "text": "card 4111111111111111"}],
+                },
+            ]
+        )
+        assert len(messages) == 2
+        blocks = messages[1]["content"]
+        assert "4111111111111111" in json.dumps(blocks)
+        assert "reasoning_content" not in messages[1]
+
+    def test_reasoning_moves_off_content_only_for_provider_bound_callers(self):
+        input_items = [
+            {
+                "type": "reasoning",
+                "id": "rs_1",
+                "content": [{"type": "output_text", "text": "hidden plan"}],
+            },
+            {"role": "user", "content": "go on"},
+        ]
+        provider_bound = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages(
+            input=input_items, responses_api_request={}, replay_reasoning=True
+        )
+        assert provider_bound[0]["content"] is None
+        assert provider_bound[0]["reasoning_content"] == "hidden plan"
+
+        inspected = _inspect_input(input_items)
+        assert inspected[0]["role"] == "user"
+        assert "hidden plan" in json.dumps(inspected[0]["content"])
+
+
 class TestNonReasoningInputItemUnchanged:
     """Non-reasoning items still flow through the existing branches."""
 

From 6d2b7db2fb220a4efcd7774ecce6588737c43bb5 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 11:42:59 -0700
Subject: [PATCH 31/93] fix: keep one reasoning item id across a bridged stream

Write the fallback reasoning item id back to the cache so the
reasoning-done path and the completed snapshot cannot drift apart, and
cover the shared delta id and the snapshot alignment with tests.
---
 .../streaming_iterator.py                     |  3 +-
 .../test_litellm_completion_responses.py      | 57 +++++++++++++++++++
 2 files changed, 59 insertions(+), 1 deletion(-)

diff --git a/litellm/responses/litellm_completion_transformation/streaming_iterator.py b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
index ff05fc0d5c6..67be8dedd55 100644
--- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py
+++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
@@ -867,9 +867,10 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
                                 reasoning_content = "".join(self._accumulated_reasoning_content_parts)
 
                                 # Ensure we have a valid reasoning_item_id
-                                reasoning_item_id = (
+                                self._cached_reasoning_item_id = (
                                     self._reasoning_item_id or self._cached_reasoning_item_id or f"rs_{uuid.uuid4()}"
                                 )
+                                reasoning_item_id = self._cached_reasoning_item_id
 
                                 # Create text.done event first with its own sequence number
                                 self._sequence_number += 1
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
index 0a2621b94e6..2273f23b1cc 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
@@ -3945,3 +3945,60 @@ class TestStreamingSnapshotItemIds:
         for item in _bridged_output_items(completed_event.response, "message"):
             assert item.id.startswith("msg_")
             assert not item.id.startswith("chatcmpl-")
+
+    def _make_reasoning_chunk(self, reasoning_content):
+        from litellm.types.utils import Delta, ModelResponseStream, StreamingChoices
+
+        return ModelResponseStream(
+            id=BRIDGED_CHAT_COMPLETION_ID,
+            choices=[
+                StreamingChoices(
+                    index=0,
+                    delta=Delta(role="assistant", reasoning_content=reasoning_content),
+                    finish_reason=None,
+                )
+            ],
+            created=1717000000,
+            model="claude-sonnet-4-5",
+            object="chat.completion.chunk",
+        )
+
+    def _reasoning_chat_completion_response(self):
+        message = Message(role="assistant", content="apple")
+        message.reasoning_content = "thinking about fruit"
+        return _bridged_chat_completion_response(
+            choices=[Choices(index=0, finish_reason="stop", message=message)]
+        )
+
+    def test_reasoning_delta_events_share_one_item_id(self):
+        """The old rs_{hash(text)} ID changed with every delta, so a client accumulating
+        reasoning by item ID saw a new item per chunk."""
+        iterator = self._make_iterator()
+
+        first = iterator._transform_chat_completion_chunk_to_response_api_chunk(
+            self._make_reasoning_chunk("thinking ")
+        )
+        second = iterator._transform_chat_completion_chunk_to_response_api_chunk(
+            self._make_reasoning_chunk("about fruit")
+        )
+
+        assert first is not None and second is not None
+        assert first.item_id.startswith("rs_")
+        assert first.item_id == second.item_id
+
+    def test_completed_snapshot_reuses_streamed_reasoning_item_id(self):
+        iterator = self._make_iterator()
+
+        streamed_event = iterator._transform_chat_completion_chunk_to_response_api_chunk(
+            self._make_reasoning_chunk("thinking about fruit")
+        )
+        assert streamed_event is not None
+
+        completed_event = iterator._emit_response_completed_event(
+            self._reasoning_chat_completion_response()
+        )
+
+        assert completed_event is not None
+        reasoning_items = _bridged_output_items(completed_event.response, "reasoning")
+        assert len(reasoning_items) == 1
+        assert reasoning_items[0].id == streamed_event.item_id

From 94caab7302ba471647bfba51bb1e5f8ad4cc5222 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 11:46:18 -0700
Subject: [PATCH 32/93] fix(interactions): release the reservation for creates
 nothing will poll, and let OTEL see the settled cost

Two review findings, both in the handoff between the create's success
callback and the background poll task.

The callback deferred its budget reservation release for any interactions
response with no usage, but the scheduler only starts a poll task when the
status is in_progress and an id is present. A create that came back
terminal without usage therefore matched the callback's test, got no poll
task, and left its reservation open forever: the pre-call estimate stayed
added to the key, user, team and org spend counters, and the key began
refusing traffic against budget it had never spent. The two conditions now
come from one shared gate so they cannot drift apart again.

Settling a background interaction re-runs the success handlers for a second
result on the same request, and OTEL dedupes span emission on a marker held
in that request's metadata. The in-progress create claimed the marker, so
the completion, the only event carrying usage and cost, was dropped as a
duplicate by OTEL and by every integration deriving from it. Clearing the
success-scoped markers alongside the existing dedup flag lets the cost span
through, leaving failure and guardrail markers untouched.
---
 .../interactions/background_cost_polling.py   | 13 ++-
 litellm/litellm_core_utils/litellm_logging.py | 29 +++++-
 .../proxy/hooks/proxy_track_cost_callback.py  |  5 +-
 .../test_litellm_logging.py                   | 38 +++++++
 .../hooks/test_proxy_track_cost_callback.py   | 99 +++++++++++++++++++
 5 files changed, 180 insertions(+), 4 deletions(-)

diff --git a/litellm/interactions/background_cost_polling.py b/litellm/interactions/background_cost_polling.py
index ccf4c2dd853..262d8e3260d 100644
--- a/litellm/interactions/background_cost_polling.py
+++ b/litellm/interactions/background_cost_polling.py
@@ -162,6 +162,17 @@ async def _release_open_budget_reservation(logging_obj: "LiteLLMLoggingObj") ->
         verbose_logger.exception("Failed to release budget reservation for an unbilled background interaction")
 
 
+def is_pollable_background_interaction(response: InteractionsAPIResponse) -> bool:
+    """
+    The single gate deciding whether a create's response gets a poll task.
+    The proxy's success callback defers releasing the budget reservation for
+    exactly these responses, on the promise that a poll task will settle them,
+    so a response one site accepts and the other refuses strands its
+    reservation on the spend counters with nothing left to reconcile it.
+    """
+    return response.status == "in_progress" and bool(response.id)
+
+
 @dataclass(frozen=True, slots=True)
 class _ActiveBackgroundPoll:
     task: "asyncio.Task[None]"
@@ -188,7 +199,7 @@ def maybe_schedule_background_interaction_cost_polling(
         return None
     if not isinstance(response, InteractionsAPIResponse):
         return None
-    if response.status != "in_progress" or not response.id:
+    if not is_pollable_background_interaction(response):
         return None
     logging_obj = create_kwargs.get("litellm_logging_obj")
     if not isinstance(logging_obj, Logging):
diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index e7d7213b47c..275803c5aed 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -2200,12 +2200,37 @@ class Logging(LiteLLMLoggingBaseClass):
         Log the terminal result of a background interaction as a fresh success
         event. The create request already ran success logging for its
         ``in_progress`` response (no usage, so no cost was tracked); clearing
-        the dedup flag lets the completed result flow through cost calculation
+        the dedup flags lets the completed result flow through cost calculation
         and spend tracking exactly once, spanning create to completion.
         """
-        self.model_call_details.pop("has_logged_async_success", None)
+        self._reset_success_emission_dedupe()
         await self.async_success_handler(result=result)
 
+    def _reset_success_emission_dedupe(self) -> None:
+        """
+        Success callbacks dedupe per request, because the sync and async
+        handlers both fire on some paths and would otherwise report one call
+        twice. A settled background interaction is a genuinely second success
+        event on the same request, so every such marker has to be cleared or
+        the completion, the only event that carries usage and cost, is
+        discarded as a duplicate of the in-progress create.
+        """
+        self.model_call_details.pop("has_logged_async_success", None)
+        litellm_params = self.model_call_details.get("litellm_params")
+        if not isinstance(litellm_params, dict):
+            return
+        metadata = litellm_params.get("metadata")
+        if not isinstance(metadata, dict):
+            return
+        otel_internal = metadata.get("_otel_internal")
+        if not isinstance(otel_internal, dict):
+            return
+        spans_logged = otel_internal.get("spans_logged")
+        if not isinstance(spans_logged, dict):
+            return
+        for scope in [key for key in spans_logged if isinstance(key, tuple) and key[-1:] == ("success",)]:
+            del spans_logged[scope]
+
     def _flush_passthrough_collected_chunks_helper(
         self,
         raw_bytes: list[bytes],
diff --git a/litellm/proxy/hooks/proxy_track_cost_callback.py b/litellm/proxy/hooks/proxy_track_cost_callback.py
index 55d3c6c6ed5..46cf62ede1c 100644
--- a/litellm/proxy/hooks/proxy_track_cost_callback.py
+++ b/litellm/proxy/hooks/proxy_track_cost_callback.py
@@ -478,9 +478,12 @@ def _write_spend_metadata_to_kwargs(kwargs: dict, metadata: dict) -> None:
 
 
 def _is_unbilled_in_progress_interaction(completion_response: object) -> bool:
+    from litellm.interactions.background_cost_polling import is_pollable_background_interaction
     from litellm.types.interactions import InteractionsAPIResponse
 
-    return isinstance(completion_response, InteractionsAPIResponse) and completion_response.usage is None
+    if not isinstance(completion_response, InteractionsAPIResponse):
+        return False
+    return completion_response.usage is None and is_pollable_background_interaction(completion_response)
 
 
 def _should_track_cost_callback(
diff --git a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
index 8a682517f64..7c90d31261b 100644
--- a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
+++ b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
@@ -4644,6 +4644,44 @@ async def test_background_interaction_completion_rebills_after_in_progress_succe
     assert logging_obj.model_call_details["standard_logging_object"]["total_tokens"] == 175
 
 
+@pytest.mark.asyncio
+async def test_background_interaction_completion_lets_otel_emit_the_cost_span():
+    """
+    OTEL, and every integration that derives from it, dedupes span emission on
+    a marker kept in the request's own metadata. The in-progress create claims
+    that marker, so without clearing it the settled completion, the only event
+    carrying usage and cost, is discarded as a duplicate and every
+    OTEL-family backend shows the interaction as a span with no cost at all.
+    """
+    import datetime as dt
+
+    from litellm.integrations.opentelemetry import OpenTelemetry, OpenTelemetryConfig
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    otel = OpenTelemetry(config=OpenTelemetryConfig(exporter="console"))
+    logging_obj = _interactions_logging_obj(stream=False)
+    in_progress = InteractionsAPIResponse(id="interactions/abc", model="gemini-2.5-flash", status="in_progress")
+    await logging_obj.async_success_handler(
+        result=in_progress,
+        start_time=dt.datetime.now(),
+        end_time=dt.datetime.now(),
+    )
+
+    assert otel._emit_once(logging_obj.model_call_details, "success") is True
+    assert otel._emit_once(logging_obj.model_call_details, "success") is False
+
+    completed = InteractionsAPIResponse(
+        id="interactions/abc",
+        model="gemini-2.5-flash",
+        status="completed",
+        steps=[],
+        usage=dict(INTERACTIONS_USAGE_BLOCK),
+    )
+    await logging_obj.async_log_background_interaction_completion(result=completed)
+
+    assert otel._emit_once(logging_obj.model_call_details, "success") is True
+
+
 @pytest.mark.parametrize(
     "call_type",
     ["aget", "get", "aget_interaction", "adelete_interaction", "acancel_interaction"],
diff --git a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
index 642db7e2d5d..93e0cbec596 100644
--- a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
+++ b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
@@ -859,6 +859,105 @@ async def test_track_cost_callback_releases_reservation_for_in_progress_interact
         mock_proxy_logging.failed_tracking_alert.assert_not_called()
 
 
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "status",
+    ["completed", "failed", "cancelled", "incomplete", "requires_action", "budget_exceeded"],
+)
+async def test_track_cost_callback_releases_reservation_for_unpollable_interaction(status):
+    """
+    Only an in-progress create gets a poll task, so a create that comes back
+    terminal with no usage has nobody left to reconcile its reservation. The
+    callback must release it there and then, or the pre-call estimate stays
+    added to the key, user, team and org spend counters and starts refusing
+    traffic against budget that was never actually spent.
+    """
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    logger = _ProxyDBLogger()
+    reservation = {"reserved_cost": 0.05, "entries": [], "finalized": False}
+    terminal_response = InteractionsAPIResponse(
+        id="interactions/bg-abc",
+        model="gemini-3-flash-preview",
+        status=status,
+    )
+
+    with patch(
+        "litellm.proxy.proxy_server.proxy_logging_obj",
+    ) as mock_proxy_logging:
+        mock_proxy_logging.failed_tracking_alert = AsyncMock()
+        mock_proxy_logging.db_spend_update_writer = MagicMock()
+        mock_proxy_logging.db_spend_update_writer.update_database = AsyncMock()
+
+        await logger._PROXY_track_cost_callback(
+            kwargs=_in_progress_interaction_kwargs(reservation),
+            completion_response=terminal_response,
+            start_time=datetime.now(),
+            end_time=datetime.now(),
+        )
+
+        assert reservation["finalized"] is True
+
+
+@pytest.mark.asyncio
+async def test_track_cost_callback_releases_reservation_for_interaction_without_an_id():
+    """
+    The scheduler also refuses a response with no id, since it has nothing to
+    poll for, so the callback must not defer to a poll task that will never
+    exist.
+    """
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    logger = _ProxyDBLogger()
+    reservation = {"reserved_cost": 0.05, "entries": [], "finalized": False}
+    idless_response = InteractionsAPIResponse(
+        id="",
+        model="gemini-3-flash-preview",
+        status="in_progress",
+    )
+
+    with patch(
+        "litellm.proxy.proxy_server.proxy_logging_obj",
+    ) as mock_proxy_logging:
+        mock_proxy_logging.failed_tracking_alert = AsyncMock()
+        mock_proxy_logging.db_spend_update_writer = MagicMock()
+        mock_proxy_logging.db_spend_update_writer.update_database = AsyncMock()
+
+        await logger._PROXY_track_cost_callback(
+            kwargs=_in_progress_interaction_kwargs(reservation),
+            completion_response=idless_response,
+            start_time=datetime.now(),
+            end_time=datetime.now(),
+        )
+
+        assert reservation["finalized"] is True
+
+
+@pytest.mark.parametrize(
+    "status",
+    ["in_progress", "completed", "failed", "cancelled", "incomplete", "requires_action"],
+)
+@pytest.mark.parametrize("interaction_id", ["interactions/bg-abc", ""])
+def test_callback_defers_exactly_the_interactions_the_scheduler_polls(status, interaction_id):
+    """
+    Pins the invariant the two modules share: the callback may only hold a
+    budget reservation open for a response the scheduler will actually poll.
+    Any drift between the two gates leaks reservations onto live spend
+    counters, so assert they agree rather than restating either condition.
+    """
+    from litellm.interactions.background_cost_polling import is_pollable_background_interaction
+    from litellm.proxy.hooks.proxy_track_cost_callback import _is_unbilled_in_progress_interaction
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    response = InteractionsAPIResponse(
+        id=interaction_id,
+        model="gemini-3-flash-preview",
+        status=status,
+    )
+
+    assert _is_unbilled_in_progress_interaction(response) is is_pollable_background_interaction(response)
+
+
 @pytest.mark.asyncio
 async def test_async_post_call_failure_hook_propagates_trace_id_from_logging_obj():
     """

From f89a3693baabf3dba081ba213032ffe7acd39b65 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 11:46:24 -0700
Subject: [PATCH 33/93] fix(responses): resolve previous_response_id for a
 just-written turn

The session lookup reads spend logs straight out of the database, so a
follow-up sent seconds after the turn it chains off found nothing while the
row was still queued in the worker that served it, and the conversation was
dropped without an error. Responses calls now ask the spend-log writer to
flush on its next pass instead of waiting out its poll interval, and the
lookup gives a just-finished turn a short second chance.

Replaying a session also accepted `input` only as a string or a single dict,
so the standard list shape dropped every user turn and left the model with
assistant messages alone.
---
 litellm/constants.py                          |   2 +
 litellm/proxy/db/db_spend_update_writer.py    |   8 +-
 litellm/proxy/utils.py                        |  26 ++-
 .../session_handler.py                        |  86 +++------
 .../proxy/db/test_db_spend_update_writer.py   |  28 +++
 .../prisma_and_spend/test_spend_functions.py  |  50 ++++-
 .../test_session_handler.py                   | 176 +++++++-----------
 7 files changed, 192 insertions(+), 184 deletions(-)

diff --git a/litellm/constants.py b/litellm/constants.py
index c33e5a53b76..aaaddd063e7 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -1542,6 +1542,8 @@ SPEND_LOG_WRITE_BATCH_MAX_ROWS: Final = max(1, int(os.getenv("SPEND_LOG_WRITE_BA
 SPEND_LOG_QUEUE_SIZE_THRESHOLD: Final = int(os.getenv("SPEND_LOG_QUEUE_SIZE_THRESHOLD", 100))
 SPEND_LOG_QUEUE_MAX_BYTES: Final = max(1, int(os.getenv("SPEND_LOG_QUEUE_MAX_BYTES", "64000000")))
 SPEND_LOG_QUEUE_POLL_INTERVAL: Final = float(os.getenv("SPEND_LOG_QUEUE_POLL_INTERVAL", 2.0))
+RESPONSES_SESSION_LOOKUP_MAX_ATTEMPTS: Final = max(1, int(os.getenv("RESPONSES_SESSION_LOOKUP_MAX_ATTEMPTS", "3")))
+RESPONSES_SESSION_LOOKUP_RETRY_INTERVAL: Final = float(os.getenv("RESPONSES_SESSION_LOOKUP_RETRY_INTERVAL", "0.2"))
 SPEND_COUNTER_RESEED_LOCKS_MAX_SIZE: Final = int(os.getenv("SPEND_COUNTER_RESEED_LOCKS_MAX_SIZE", 10000))
 DEFAULT_CRON_JOB_LOCK_TTL_SECONDS: Final = int(os.getenv("DEFAULT_CRON_JOB_LOCK_TTL_SECONDS", 60))  # 1 minute
 PROXY_BUDGET_RESCHEDULER_MIN_TIME: Final = int(os.getenv("PROXY_BUDGET_RESCHEDULER_MIN_TIME", 597))
diff --git a/litellm/proxy/db/db_spend_update_writer.py b/litellm/proxy/db/db_spend_update_writer.py
index 283194bad7c..0c8c9a853ec 100644
--- a/litellm/proxy/db/db_spend_update_writer.py
+++ b/litellm/proxy/db/db_spend_update_writer.py
@@ -65,6 +65,7 @@ from litellm.proxy.spend_tracking.savings import (
 )
 from litellm.proxy.spend_tracking.spend_log_error_logger import spend_log_error
 from litellm.repositories.prisma_protocols import BatchTable
+from litellm.types.utils import CallTypes
 
 if TYPE_CHECKING:
     from litellm.proxy.utils import PrismaClient, ProxyLogging
@@ -73,6 +74,9 @@ else:
     ProxyLogging = Any
 
 
+RESPONSES_SESSION_CALL_TYPES: Final = frozenset({CallTypes.responses.value, CallTypes.aresponses.value})
+
+
 class _SpendBatch(Protocol):
     litellm_usertable: BatchTable
     litellm_verificationtoken: BatchTable
@@ -820,9 +824,11 @@ class DBSpendUpdateWriter:
             )
         )
         if prisma_client is not None and spend_logs_url is not None or prisma_client is not None:
-            from litellm.proxy.utils import enqueue_spend_logs
+            from litellm.proxy.utils import enqueue_spend_logs, request_spend_log_flush
 
             await enqueue_spend_logs(prisma_client, (payload,))
+            if payload.get("call_type") in RESPONSES_SESSION_CALL_TYPES:
+                request_spend_log_flush()
         else:
             verbose_proxy_logger.debug("prisma_client is None. Skipping writing spend logs to db.")
 
diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py
index 9978fa04f40..86d954c0913 100644
--- a/litellm/proxy/utils.py
+++ b/litellm/proxy/utils.py
@@ -3341,6 +3341,7 @@ class _StaleReadEngine:
 class PrismaClient:
     spend_log_transactions: list = []
     _spend_log_transactions_lock = asyncio.Lock()
+    spend_log_flush_requested: ClassVar[asyncio.Event] = asyncio.Event()
     spend_log_queue_bytes: ClassVar[int] = 0
     spend_logs_queue_monitor_task: "asyncio.Task[None] | None" = None
     tool_usage_transactions: list["ToolUsageTransaction"] = []
@@ -6005,14 +6006,24 @@ async def enqueue_spend_logs(
         )
 
 
-async def peek_spend_logs(prisma_client: PrismaClient) -> tuple[SpendLogsPayload, ...]:
-    """Snapshot the spend logs still waiting for the next flush, leaving the queue intact.
+def request_spend_log_flush() -> None:
+    """Wake the queue monitor now rather than leaving the rows for its next poll.
 
-    Reads that need a just-finished request use this, since the batch writer only
-    reaches the DB every ``PROXY_BATCH_WRITE_AT`` seconds.
+    The Responses API hands the client an id it can chain from straight away, and that
+    lookup reads the DB, so the row cannot sit in this worker's queue for a poll interval.
+    Repeated requests coalesce into the monitor's next pass, so the batching holds.
     """
-    async with prisma_client._spend_log_transactions_lock:
-        return tuple(prisma_client.spend_log_transactions)
+    PrismaClient.spend_log_flush_requested.set()
+
+
+async def _wait_for_spend_log_flush_request(interval: float) -> bool:
+    """Wait out ``interval``, returning early and True when a flush was requested."""
+    try:
+        await asyncio.wait_for(PrismaClient.spend_log_flush_requested.wait(), timeout=interval)
+    except asyncio.TimeoutError:
+        return False
+    PrismaClient.spend_log_flush_requested.clear()
+    return True
 
 
 async def dequeue_spend_logs(prisma_client: PrismaClient, limit: int) -> list[dict[str, object]]:
@@ -6460,7 +6471,8 @@ async def _monitor_spend_logs_queue(
                 # Exponential backoff when no logs to process
                 current_interval = min(current_interval * backoff_multiplier, max_backoff)
 
-            await asyncio.sleep(current_interval)
+            if await _wait_for_spend_log_flush_request(current_interval):
+                current_interval = base_interval
         except Exception as e:
             spend_log_error("Error in spend logs queue monitor: %s", str(e), exc=e)
             # Continue monitoring even if there's an error, with exponential backoff
diff --git a/litellm/responses/litellm_completion_transformation/session_handler.py b/litellm/responses/litellm_completion_transformation/session_handler.py
index 935c78bc9a1..15267533957 100644
--- a/litellm/responses/litellm_completion_transformation/session_handler.py
+++ b/litellm/responses/litellm_completion_transformation/session_handler.py
@@ -1,5 +1,5 @@
+import asyncio
 import json
-from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any, Final, cast
 
 import litellm
@@ -132,8 +132,8 @@ class ResponsesSessionHandler:
         ############################################################
         # Add Output messages for this Spend Log
         ############################################################
-        _response_output: Final = ResponsesSessionHandler._get_response_dict_from_spend_log(spend_log)
-        if _response_output:
+        _response_output: Final = spend_log.get("response", "{}")
+        if isinstance(_response_output, dict) and _response_output and _response_output != {}:
             # transform `ChatCompletion Response` to `ResponsesAPIResponse`
             model_response: Final = ModelResponse(**_response_output)
             for choice in model_response.choices:
@@ -141,23 +141,6 @@ class ResponsesSessionHandler:
                     chat_completion_message_history.append(getattr(choice, "message"))
         return chat_completion_message_history
 
-    @staticmethod
-    def _get_response_dict_from_spend_log(spend_log: SpendLogsPayload) -> Mapping[str, Any] | None:
-        """
-        Spend logs read from the DB hold `response` as a dict, ones still queued in memory
-        hold it as a JSON string.
-        """
-        _response_output: Final = spend_log.get("response")
-        if isinstance(_response_output, dict):
-            return _response_output or None
-        if isinstance(_response_output, str):
-            try:
-                parsed: Final = json.loads(_response_output)
-            except json.JSONDecodeError:
-                return None
-            return parsed if isinstance(parsed, dict) and parsed else None
-        return None
-
     @staticmethod
     async def get_proxy_server_request_from_spend_log(
         spend_log: SpendLogsPayload,
@@ -272,9 +255,16 @@ class ResponsesSessionHandler:
         SQL query
 
         SELECT session_id FROM spend_logs WHERE response_id = previous_response_id, SELECT * FROM spend_logs WHERE session_id = session_id
+
+        A just-finished turn gets a short second chance: the worker that served it may
+        still be writing its spend log when the follow-up arrives, and an empty result
+        drops the whole conversation instead of erroring.
         """
+        from litellm.constants import (
+            RESPONSES_SESSION_LOOKUP_MAX_ATTEMPTS,
+            RESPONSES_SESSION_LOOKUP_RETRY_INTERVAL,
+        )
         from litellm.proxy.proxy_server import prisma_client
-        from litellm.proxy.utils import peek_spend_logs
 
         verbose_proxy_logger.debug("decoding response id=%s", previous_response_id)
 
@@ -295,46 +285,16 @@ class ResponsesSessionHandler:
             ORDER BY "endTime" ASC;
         """
 
-        written_spend_logs: Final = await prisma_client.db.query_raw(query, response_id)
-        queued_spend_logs: Final = await peek_spend_logs(prisma_client)
-        spend_logs: Final = list(
-            ResponsesSessionHandler._merge_queued_spend_logs(
-                response_id=response_id,
-                written_spend_logs=written_spend_logs,
-                queued_spend_logs=queued_spend_logs,
-            )
-        )
+        for attempt in range(RESPONSES_SESSION_LOOKUP_MAX_ATTEMPTS):
+            if attempt:
+                await asyncio.sleep(RESPONSES_SESSION_LOOKUP_RETRY_INTERVAL)
+            if spend_logs := await prisma_client.db.query_raw(query, response_id):
+                verbose_proxy_logger.debug(
+                    "Found the following spend logs for previous response id %s: %s",
+                    response_id,
+                    json.dumps(spend_logs, indent=4, default=str),
+                )
+                return spend_logs
 
-        verbose_proxy_logger.debug(
-            "Found the following spend logs for previous response id %s: %s",
-            response_id,
-            json.dumps(spend_logs, indent=4, default=str),
-        )
-
-        return spend_logs
-
-    @staticmethod
-    def _merge_queued_spend_logs(
-        response_id: str,
-        written_spend_logs: Sequence[SpendLogsPayload],
-        queued_spend_logs: Sequence[SpendLogsPayload],
-    ) -> tuple[SpendLogsPayload, ...]:
-        """
-        Append the session's spend logs that the batch writer has not flushed to the DB yet.
-
-        Without this a follow-up sent inside the ``PROXY_BATCH_WRITE_AT`` window sees an
-        empty session and silently drops the conversation. The queue is FIFO, so anything
-        still on it is newer than every row already written.
-        """
-        session_ids: Final = frozenset(
-            session_id
-            for spend_log in (*written_spend_logs, *queued_spend_logs)
-            if spend_log.get("request_id") == response_id and (session_id := spend_log.get("session_id"))
-        ) | frozenset(session_id for spend_log in written_spend_logs if (session_id := spend_log.get("session_id")))
-        written_request_ids: Final = frozenset(spend_log.get("request_id") for spend_log in written_spend_logs)
-        unflushed: Final = tuple(
-            spend_log
-            for spend_log in queued_spend_logs
-            if spend_log.get("session_id") in session_ids and spend_log.get("request_id") not in written_request_ids
-        )
-        return (*written_spend_logs, *unflushed)
+        verbose_proxy_logger.debug("Found no spend logs for previous response id %s", response_id)
+        return []
diff --git a/tests/test_litellm/proxy/db/test_db_spend_update_writer.py b/tests/test_litellm/proxy/db/test_db_spend_update_writer.py
index 76a80ac2651..ca1827aa38e 100644
--- a/tests/test_litellm/proxy/db/test_db_spend_update_writer.py
+++ b/tests/test_litellm/proxy/db/test_db_spend_update_writer.py
@@ -2712,3 +2712,31 @@ async def test_commit_spend_updates_retries_deadlock_on_every_entity_path(monkey
 
     assert mock_prisma_client.db.tx.call_count == 2
     proxy_logging.failure_handler.assert_not_called()
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "call_type, expects_flush",
+    [("aresponses", True), ("responses", True), ("acompletion", False)],
+)
+async def test_insert_spend_log_asks_for_an_immediate_flush_on_responses_calls(
+    call_type: str, expects_flush: bool
+):
+    """
+    A `previous_response_id` chained straight off the previous turn reads the DB, so a
+    Responses row cannot sit in this worker's queue until the monitor's next poll.
+    """
+    from litellm.proxy.utils import PrismaClient
+
+    db_writer = DBSpendUpdateWriter()
+    prisma = _tool_usage_prisma()
+    PrismaClient.spend_log_flush_requested.clear()
+
+    await db_writer._insert_spend_log_to_db(
+        payload={"request_id": "req-1", "call_type": call_type},
+        prisma_client=prisma,
+    )
+
+    assert prisma.spend_log_transactions == [{"request_id": "req-1", "call_type": call_type}]
+    assert PrismaClient.spend_log_flush_requested.is_set() is expects_flush
+    PrismaClient.spend_log_flush_requested.clear()
diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_spend_functions.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_spend_functions.py
index 54d59e690f9..a1eb88a7834 100644
--- a/tests/test_litellm/proxy/utils/prisma_and_spend/test_spend_functions.py
+++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_spend_functions.py
@@ -11,7 +11,8 @@ Symbols pinned here:
 from __future__ import annotations
 
 import asyncio
-from typing import Any, Dict, List
+from contextlib import suppress
+from typing import Any, Dict, Final, List
 from unittest.mock import AsyncMock, MagicMock
 
 import pytest
@@ -526,6 +527,53 @@ async def test_monitor_spend_logs_queue_swallows_errors_and_backs_off(
     assert sleep_count["n"] == 3
 
 
+@pytest.mark.asyncio
+async def test_monitor_spend_logs_queue_flushes_as_soon_as_one_is_requested(
+    mock_prisma_client: Any,
+    make_spend_log_row: Any,
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    """A requested flush wakes the monitor mid-poll, so a Responses row reaches the DB
+    before the client can chain a `previous_response_id` off it.
+    """
+    import litellm.constants as constants_mod
+    import litellm.proxy.utils as utils_mod
+    from litellm.proxy.utils import PrismaClient, request_spend_log_flush
+
+    monkeypatch.setattr(constants_mod, "SPEND_LOG_QUEUE_POLL_INTERVAL", 30.0, raising=False)
+    PrismaClient.spend_log_flush_requested.clear()
+    mock_prisma_client.spend_log_transactions = []
+    mock_prisma_client.tool_usage_transactions = []
+
+    flushed: Final = asyncio.Event()
+
+    async def _fake_job(*args: Any, **kwargs: Any) -> None:
+        flushed.set()
+
+    monkeypatch.setattr(utils_mod, "update_spend_logs_job", _fake_job)
+
+    monitor: Final = asyncio.create_task(
+        _monitor_spend_logs_queue(
+            prisma_client=mock_prisma_client,
+            db_writer_client=None,
+            proxy_logging_obj=MagicMock(),
+        )
+    )
+    try:
+        await asyncio.sleep(0.05)
+        assert not flushed.is_set()
+
+        mock_prisma_client.spend_log_transactions.append(make_spend_log_row(request_id="r1"))
+        request_spend_log_flush()
+
+        await asyncio.wait_for(flushed.wait(), timeout=5.0)
+    finally:
+        monitor.cancel()
+        with suppress(asyncio.CancelledError):
+            await monitor
+        PrismaClient.spend_log_flush_requested.clear()
+
+
 def test_raise_failed_update_spend_exception_emits_failure_handler() -> None:
     proxy_logging = MagicMock()
     proxy_logging.failure_handler = AsyncMock()
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py b/tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py
index 926e9e0af2a..4fc288a47cb 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py
@@ -1,4 +1,3 @@
-import asyncio
 import json
 from unittest.mock import AsyncMock, patch
 
@@ -451,20 +450,38 @@ def _chat_completion_response(request_id: str, content: str) -> dict:
 
 
 class _FakePrismaDB:
-    def __init__(self, rows):
-        self._rows = rows
+    def __init__(self, results):
+        self._results = list(results)
         self.calls = []
 
     async def query_raw(self, query, *args):
         self.calls.append(args)
-        return list(self._rows)
+        if not self._results:
+            return []
+        return list(self._results.pop(0))
 
 
 class _FakePrismaClient:
-    def __init__(self, written_rows, queued_rows):
-        self.db = _FakePrismaDB(written_rows)
-        self.spend_log_transactions = list(queued_rows)
-        self._spend_log_transactions_lock = asyncio.Lock()
+    def __init__(self, results):
+        self.db = _FakePrismaDB(results)
+
+
+def _spend_log(request_id: str, session_id: str, prompt: str, answer: str) -> dict:
+    return {
+        "request_id": request_id,
+        "call_type": "aresponses",
+        "session_id": session_id,
+        "proxy_server_request": {
+            "input": [{"role": "user", "content": prompt}],
+            "model": "claude-bridge",
+        },
+        "response": _chat_completion_response(request_id, answer),
+    }
+
+
+@pytest.fixture
+def instant_session_lookup_retries(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(litellm.constants, "RESPONSES_SESSION_LOOKUP_RETRY_INTERVAL", 0.0)
 
 
 @pytest.mark.asyncio
@@ -475,21 +492,12 @@ async def test_message_history_reconstructs_list_shaped_input():
     """
     request_id = "chatcmpl-935b8dad-fdc2-466e-a8ca-e26e5a8a21bb"
     mock_spend_logs = [
-        {
-            "request_id": request_id,
-            "call_type": "aresponses",
-            "session_id": "a96757c4-c6dc-4c76-b37e-e7dfa526b701",
-            "proxy_server_request": {
-                "input": [
-                    {
-                        "role": "user",
-                        "content": "Remember this: my favorite color is chartreuse.",
-                    }
-                ],
-                "model": "claude-bridge",
-            },
-            "response": _chat_completion_response(request_id, "OK"),
-        }
+        _spend_log(
+            request_id,
+            "a96757c4-c6dc-4c76-b37e-e7dfa526b701",
+            "Remember this: my favorite color is chartreuse.",
+            "OK",
+        )
     ]
 
     with patch.object(
@@ -512,31 +520,22 @@ async def test_message_history_reconstructs_list_shaped_input():
 
 
 @pytest.mark.asyncio
-async def test_message_history_includes_spend_logs_still_waiting_on_the_batch_writer():
+async def test_message_history_retries_a_spend_log_the_batch_writer_has_not_flushed_yet(
+    instant_session_lookup_retries: None,
+):
     """
-    A follow-up sent right after the previous turn arrives before the batch writer has
-    flushed that turn's spend log, so the row is only in memory. The history has to
-    include it anyway.
+    A follow-up sent right after the previous turn can beat that turn's spend log to the
+    DB. The lookup has to try again instead of handing back an empty conversation.
     """
     request_id = "chatcmpl-6c1f5f6c-6a2b-4c62-8d1f-0d9d4ce0a1b2"
-    queued_spend_log = {
-        "request_id": request_id,
-        "call_type": "aresponses",
-        "session_id": "b7d0a5b0-6d20-4a68-9d24-6ba0f6d1f1a3",
-        "proxy_server_request": json.dumps(
-            {
-                "input": [
-                    {
-                        "role": "user",
-                        "content": "Remember this: my favorite color is chartreuse.",
-                    }
-                ],
-                "model": "claude-bridge",
-            }
-        ),
-        "response": json.dumps(_chat_completion_response(request_id, "OK")),
-    }
-    fake_prisma_client = _FakePrismaClient(written_rows=[], queued_rows=[queued_spend_log])
+    session_id = "b7d0a5b0-6d20-4a68-9d24-6ba0f6d1f1a3"
+    spend_log = _spend_log(
+        request_id,
+        session_id,
+        "Remember this: my favorite color is chartreuse.",
+        "OK",
+    )
+    fake_prisma_client = _FakePrismaClient(results=[[], [spend_log]])
 
     with patch("litellm.proxy.proxy_server.prisma_client", fake_prisma_client):
         result = await ResponsesSessionHandler.get_chat_completion_message_history_for_previous_response_id(
@@ -548,44 +547,22 @@ async def test_message_history_includes_spend_logs_still_waiting_on_the_batch_wr
         ("user", "Remember this: my favorite color is chartreuse."),
         ("assistant", "OK"),
     ]
-    assert result["litellm_session_id"] == "b7d0a5b0-6d20-4a68-9d24-6ba0f6d1f1a3"
-    assert fake_prisma_client.spend_log_transactions == [queued_spend_log]
+    assert result["litellm_session_id"] == session_id
+    assert fake_prisma_client.db.calls == [(request_id,), (request_id,)]
 
 
 @pytest.mark.asyncio
-async def test_message_history_merges_written_and_queued_turns_in_order():
-    """
-    Turn 1 already flushed to the DB, turn 2 still queued: the follow-up sees the whole
-    conversation, in order, with no row counted twice.
-    """
+async def test_message_history_reconstructs_every_turn_of_the_session_in_order():
     session_id = "5c5f9a3e-1c86-4c0e-9d7c-0a54b8a0f2f1"
     first_request_id = "chatcmpl-1111"
     second_request_id = "chatcmpl-2222"
-    written_spend_log = {
-        "request_id": first_request_id,
-        "call_type": "aresponses",
-        "session_id": session_id,
-        "proxy_server_request": {
-            "input": [{"role": "user", "content": "My favorite color is chartreuse."}],
-            "model": "claude-bridge",
-        },
-        "response": _chat_completion_response(first_request_id, "Got it."),
-    }
-    queued_spend_log = {
-        "request_id": second_request_id,
-        "call_type": "aresponses",
-        "session_id": session_id,
-        "proxy_server_request": json.dumps(
-            {
-                "input": [{"role": "user", "content": "And my favorite city is Lisbon."}],
-                "model": "claude-bridge",
-            }
-        ),
-        "response": json.dumps(_chat_completion_response(second_request_id, "Noted.")),
-    }
     fake_prisma_client = _FakePrismaClient(
-        written_rows=[written_spend_log],
-        queued_rows=[written_spend_log, queued_spend_log],
+        results=[
+            [
+                _spend_log(first_request_id, session_id, "My favorite color is chartreuse.", "Got it."),
+                _spend_log(second_request_id, session_id, "And my favorite city is Lisbon.", "Noted."),
+            ]
+        ]
     )
 
     with patch("litellm.proxy.proxy_server.prisma_client", fake_prisma_client):
@@ -604,45 +581,18 @@ async def test_message_history_merges_written_and_queued_turns_in_order():
 
 
 @pytest.mark.asyncio
-async def test_message_history_ignores_queued_spend_logs_from_other_sessions():
-    request_id = "chatcmpl-3333"
-    written_spend_log = {
-        "request_id": request_id,
-        "call_type": "aresponses",
-        "session_id": "session-a",
-        "proxy_server_request": {
-            "input": [{"role": "user", "content": "Hello from session a."}],
-            "model": "claude-bridge",
-        },
-        "response": _chat_completion_response(request_id, "Hi."),
-    }
-    other_session_spend_log = {
-        "request_id": "chatcmpl-4444",
-        "call_type": "aresponses",
-        "session_id": "session-b",
-        "proxy_server_request": json.dumps(
-            {
-                "input": [{"role": "user", "content": "Hello from session b."}],
-                "model": "claude-bridge",
-            }
-        ),
-        "response": json.dumps(_chat_completion_response("chatcmpl-4444", "Hi there.")),
-    }
-    fake_prisma_client = _FakePrismaClient(
-        written_rows=[written_spend_log],
-        queued_rows=[other_session_spend_log],
-    )
+async def test_session_lookup_stops_retrying_once_the_budget_is_spent(
+    instant_session_lookup_retries: None,
+):
+    fake_prisma_client = _FakePrismaClient(results=[])
 
     with patch("litellm.proxy.proxy_server.prisma_client", fake_prisma_client):
-        result = await ResponsesSessionHandler.get_chat_completion_message_history_for_previous_response_id(
-            request_id
+        spend_logs = await ResponsesSessionHandler.get_all_spend_logs_for_previous_response_id(
+            "chatcmpl-does-not-exist"
         )
 
-    messages = result["messages"]
-    assert [(message.get("role"), message.get("content")) for message in messages] == [
-        ("user", "Hello from session a."),
-        ("assistant", "Hi."),
-    ]
+    assert spend_logs == []
+    assert len(fake_prisma_client.db.calls) == litellm.constants.RESPONSES_SESSION_LOOKUP_MAX_ATTEMPTS
 
 
 @pytest.mark.asyncio
@@ -657,7 +607,9 @@ async def test_message_history_looks_up_the_decoded_chat_completion_id():
         model_id="e0f302a1412e78470ebb28cbed01fff5f88c0d331c667e9f2ba4b413c6fbd282",
         response_id=request_id,
     )
-    fake_prisma_client = _FakePrismaClient(written_rows=[], queued_rows=[])
+    fake_prisma_client = _FakePrismaClient(
+        results=[[_spend_log(request_id, "session-a", "Hello.", "Hi.")]]
+    )
 
     with patch("litellm.proxy.proxy_server.prisma_client", fake_prisma_client):
         await ResponsesSessionHandler.get_all_spend_logs_for_previous_response_id(

From d4608af27bf9362b3b2b310e6deef61e312af71f Mon Sep 17 00:00:00 2001
From: tin <tin@berri.ai>
Date: Sat, 22 Aug 2026 19:30:54 +0000
Subject: [PATCH 34/93] fix(proxy): skip health checks for strategy routers

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/proxy/health_check.py                 | 22 +++-------
 .../proxy/test_health_check_max_tokens.py     | 44 +++++++++++--------
 2 files changed, 31 insertions(+), 35 deletions(-)

diff --git a/litellm/proxy/health_check.py b/litellm/proxy/health_check.py
index f9d408fb7de..4d70406caf8 100644
--- a/litellm/proxy/health_check.py
+++ b/litellm/proxy/health_check.py
@@ -18,6 +18,7 @@ from litellm.constants import (
     DEFAULT_HEALTH_CHECK_PROMPT,
     HEALTH_CHECK_TIMEOUT_SECONDS,
 )
+from litellm.router_utils.auto_router_model_naming import classify_strategy_router_model
 
 ILLEGAL_DISPLAY_PARAMS: Final = [
     "messages",
@@ -182,30 +183,17 @@ async def run_with_timeout(task, timeout):
         return {"error": "Timeout exceeded", "exception": timeout_exception}
 
 
-def _is_semantic_auto_router_deployment(litellm_params: dict) -> bool:
-    """
-    True for semantic auto_router deployments (auto_router/<name>) that are not
-    sub-strategies (complexity_router, adaptive_router, quality_router).
-
-    These are meta-routers that select among real LLM deployments at request time;
-    they have no LLM endpoint to health-check.
-    """
+def _is_strategy_router_deployment(litellm_params: dict) -> bool:
+    """True for strategy-router deployments."""
     model: Final[object] = litellm_params.get("model", "")
-    if not isinstance(model, str):
-        return False
-    if not model.startswith("auto_router/"):
-        return False
-    for sub_strategy in ("complexity_router", "adaptive_router", "quality_router"):
-        if model.startswith(f"auto_router/{sub_strategy}"):
-            return False
-    return True
+    return isinstance(model, str) and classify_strategy_router_model(model) is not None
 
 
 async def _run_model_health_check(model: dict):
     litellm_params = model["litellm_params"]
     model_info: Final = model.get("model_info", {})
 
-    if _is_semantic_auto_router_deployment(litellm_params):
+    if _is_strategy_router_deployment(litellm_params):
         return {}
 
     mode: Final = _resolve_health_check_mode(
diff --git a/tests/test_litellm/proxy/test_health_check_max_tokens.py b/tests/test_litellm/proxy/test_health_check_max_tokens.py
index 5a606d5f74e..80c6f2bba25 100644
--- a/tests/test_litellm/proxy/test_health_check_max_tokens.py
+++ b/tests/test_litellm/proxy/test_health_check_max_tokens.py
@@ -5,7 +5,7 @@ import pytest
 from litellm.litellm_core_utils.health_check_helpers import HealthCheckHelpers
 from litellm.proxy import health_check as hc_module
 from litellm.proxy.health_check import (
-    _is_semantic_auto_router_deployment,
+    _is_strategy_router_deployment,
     _resolve_health_check_max_tokens,
     _resolve_health_check_mode,
     _update_litellm_params_for_health_check,
@@ -495,33 +495,22 @@ def test_autodetected_embedding_skips_reasoning_effort():
     assert "max_tokens" not in updated
 
 
-# ---------------------------------------------------------------------------
-# auto_router (semantic router) deployments must be skipped by health checks.
-#
-# These are meta-routers that select among real LLM deployments at request
-# time. They have no LLM endpoint to probe. Before this fix, the health check
-# passed model="auto_router/router_1" to get_llm_provider(), which raised
-# BadRequestError: "Unmapped LLM provider for this endpoint" because
-# auto_router is not a real LLM provider.
-# ---------------------------------------------------------------------------
-
-
 @pytest.mark.parametrize(
     "model, expected",
     [
         ("auto_router/router_1", True),
         ("auto_router/my_router", True),
-        ("auto_router/complexity_router", False),
-        ("auto_router/adaptive_router", False),
-        ("auto_router/quality_router", False),
-        ("auto_router/adaptive_router/subpath", False),
+        ("auto_router/complexity_router", True),
+        ("auto_router/adaptive_router", True),
+        ("auto_router/quality_router", True),
+        ("auto_router/adaptive_router/subpath", True),
         ("gpt-4", False),
         ("openai/gpt-4", False),
         ("bedrock/claude", False),
     ],
 )
-def test_is_semantic_auto_router_deployment(model, expected):
-    assert _is_semantic_auto_router_deployment({"model": model}) == expected
+def test_is_strategy_router_deployment(model, expected):
+    assert _is_strategy_router_deployment({"model": model}) == expected
 
 
 @pytest.mark.asyncio
@@ -543,3 +532,22 @@ async def test_run_model_health_check_skips_auto_router_deployment():
 
     fake_ahealth_check.assert_not_called()
     assert result == {}
+
+
+@pytest.mark.asyncio
+async def test_run_model_health_check_skips_complexity_router_deployment():
+    fake_ahealth_check = AsyncMock(return_value={})
+    model = {
+        "litellm_params": {
+            "model": "auto_router/complexity_router",
+            "complexity_router_config": {"tiers": {"simple": "gpt-4o-mini"}},
+            "complexity_router_default_model": "gpt-4o-mini",
+        },
+        "model_info": {},
+    }
+
+    with patch.object(hc_module.litellm, "ahealth_check", fake_ahealth_check):
+        result = await hc_module._run_model_health_check(model)
+
+    fake_ahealth_check.assert_not_called()
+    assert result == {}

From af18f77db64ff47fd33f1c863d5bd19a1102e2d7 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 12:48:39 -0700
Subject: [PATCH 35/93] fix(check_batch_cost): leave a lagging-output completed
 batch for the next poll cycle

---
 .../proxy/common_utils/check_batch_cost.py    | 10 +++
 .../proxy_unit_tests/test_check_batch_cost.py | 71 ++++++++++++++++++-
 2 files changed, 80 insertions(+), 1 deletion(-)

diff --git a/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py b/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py
index 4bb00408fc3..76e92538aaa 100644
--- a/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py
+++ b/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py
@@ -966,6 +966,16 @@ class CheckBatchCost:
                     )
 
             elif response.status in PROVIDER_TERMINAL_BATCH_STATUSES:
+                from litellm.proxy.openai_files_endpoints.common_utils import (
+                    _completed_batch_safe_to_retire,
+                )
+
+                if response.status in ("completed", "complete") and not _completed_batch_safe_to_retire(response):
+                    verbose_proxy_logger.info(
+                        f"CheckBatchCost: batch {batch_id} is completed but its output file id "
+                        f"has not appeared yet; leaving job {job.id} for the next poll cycle"
+                    )
+                    continue
                 await self._finalize_unbilled_terminal_job(job, response)
 
         # Record polling run metrics (always, even if nothing was processed)
diff --git a/tests/proxy_unit_tests/test_check_batch_cost.py b/tests/proxy_unit_tests/test_check_batch_cost.py
index 0065dbebc59..a1864c5e480 100644
--- a/tests/proxy_unit_tests/test_check_batch_cost.py
+++ b/tests/proxy_unit_tests/test_check_batch_cost.py
@@ -1044,7 +1044,9 @@ class TestCheckBatchCost:
         Pre-fix it matched neither the completed-with-output branch nor the
         failed/expired/cancelled branch, so batch_processed stayed False and the row
         was re-selected on every poll cycle forever. It must now be marked terminal
-        exactly once, without being billed (no output means nothing to bill).
+        exactly once, without being billed: request_counts.completed == 0 proves the
+        missing output file means nothing to bill rather than a lagging output id
+        (#37713 keeps the lagging case eligible for the next cycle).
         """
         import base64
         from unittest.mock import patch
@@ -1073,6 +1075,7 @@ class TestCheckBatchCost:
         mock_response.status = completed_status
         mock_response.output_file_id = None
         mock_response.error_file_id = "file-error-123"
+        mock_response.request_counts = MagicMock(completed=0, failed=3, total=3)
         mock_response.model_dump_json.return_value = (
             f'{{"id":"batch-1","status":"{completed_status}"}}'
         )
@@ -1107,6 +1110,72 @@ class TestCheckBatchCost:
             mock_llm_router.get_deployment_credentials_with_provider.call_count == 0
         ), "a batch with no output file must not enter the cost-tracking path"
 
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "request_counts",
+        [MagicMock(completed=7, failed=0, total=7), None],
+        ids=["lagging_output_id", "unknown_counts"],
+    )
+    async def test_completed_with_lagging_output_file_left_for_next_cycle(
+        self,
+        check_batch_cost_instance,
+        mock_prisma_client,
+        mock_llm_router,
+        request_counts,
+    ):
+        """#37713 regression: a batch can report completed while its output_file_id is
+        still lagging behind at the provider. Retiring it in that window (or when the
+        request counts cannot prove there is nothing to bill) permanently loses the
+        spend record, so the poller must leave the row untouched and revisit it on the
+        next cycle once the output id has appeared.
+        """
+        import base64
+        from unittest.mock import patch
+
+        mock_prisma_client.db.litellm_managedobjecttable.update_many = AsyncMock(
+            return_value=1
+        )
+        mock_prisma_client.db.litellm_managedobjecttable.update = AsyncMock()
+        mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(
+            return_value=None
+        )
+
+        mock_job = MagicMock()
+        mock_job.id = "job-completed-lagging-output-1"
+        mock_job.unified_object_id = base64.urlsafe_b64encode(
+            b"litellm_proxy;model_id:model-123;llm_batch_id:batch-456"
+        ).decode()
+        mock_job.created_by = "user-1"
+
+        assert check_batch_cost_instance._has_batch_processed_column is True
+        mock_prisma_client.db.litellm_managedobjecttable.find_many = AsyncMock(
+            return_value=[mock_job]
+        )
+
+        mock_response = MagicMock()
+        mock_response.status = "completed"
+        mock_response.output_file_id = None
+        mock_response.error_file_id = None
+        mock_response.request_counts = request_counts
+
+        mock_llm_router.aretrieve_batch = AsyncMock(return_value=mock_response)
+        mock_llm_router.get_deployment_credentials_with_provider = MagicMock(
+            return_value={"api_key": "sk-test"}
+        )
+
+        with patch(
+            "litellm.files.main.afile_content",
+            new_callable=AsyncMock,
+        ) as mock_afile_content:
+            await check_batch_cost_instance.check_batch_cost()
+
+        assert (
+            mock_prisma_client.db.litellm_managedobjecttable.update.call_count == 0
+        ), "a completed batch whose output id is still lagging must stay eligible for the next poll"
+        assert (
+            mock_afile_content.await_count == 0
+        ), "a batch with no output file must not be billed"
+
     @pytest.mark.asyncio
     async def test_non_terminal_status_left_unprocessed(
         self, check_batch_cost_instance, mock_prisma_client, mock_llm_router

From 9349b22c64e2b7041cc81e60c705b8b100c16010 Mon Sep 17 00:00:00 2001
From: Yassin Kortam <yassin@berri.ai>
Date: Sat, 22 Aug 2026 14:15:55 -0700
Subject: [PATCH 36/93] fix(guardrails): stop PII/PCI masking gaps in
 SpendLogs, debug logs, and logging_only response (#37965)

The Presidio guardrail masks messages in place inside pre_call_hook, but three
paths independently persisted or emitted the raw pre-guardrail data: the
SpendLogs proxy_server_request body snapshot (taken before the hook runs),
a verbose_proxy_logger.debug dump of the raw request, and logging_only mode's
async_logging_hook, which never masked the model's response before it reached
external logging callbacks.

Resolves LIT-6015
---
 litellm/proxy/common_request_processing.py    |  7 +++
 .../guardrails/guardrail_hooks/presidio.py    | 15 ++++-
 litellm/proxy/litellm_pre_call_utils.py       | 32 +++++++++--
 .../guardrail_hooks/test_presidio.py          | 46 +++++++++++++++
 .../proxy/test_common_request_processing.py   | 56 +++++++++++++++++++
 .../proxy/test_litellm_pre_call_utils.py      | 48 ++++++++++++++++
 6 files changed, 198 insertions(+), 6 deletions(-)

diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py
index 3fb09cde931..5f205df487d 100644
--- a/litellm/proxy/common_request_processing.py
+++ b/litellm/proxy/common_request_processing.py
@@ -178,6 +178,7 @@ else:
     ProxyConfig = Any
 from litellm.proxy.litellm_pre_call_utils import (
     add_litellm_data_to_request,
+    refresh_proxy_server_request_body_snapshot,
     reject_url_valued_destination,
 )
 from litellm.types.utils import (
@@ -1862,6 +1863,12 @@ class ProxyBaseLLMRequestProcessing:
             call_type=route_type,
         )
 
+        # Refresh AFTER pre_call_hook: guardrails (e.g. Presidio PII masking) may
+        # have mutated `self.data` in place, and the audit-trail snapshot taken in
+        # add_litellm_data_to_request predates that mutation.
+        refresh_proxy_server_request_body_snapshot(self.data)
+        verbose_proxy_logger.debug("receiving data: %s", self.data)
+
         if "messages" in self.data and self.data["messages"]:
             logging_obj.update_messages(self.data["messages"])
 
diff --git a/litellm/proxy/guardrails/guardrail_hooks/presidio.py b/litellm/proxy/guardrails/guardrail_hooks/presidio.py
index c3b7498d9ec..bcee45355e3 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/presidio.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/presidio.py
@@ -788,7 +788,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
 
     async def async_logging_hook(self, kwargs: dict, result: Any, call_type: str) -> tuple[dict, Any]:
         """
-        Masks the input before logging to langfuse, datadog, etc.
+        Masks the input and output before logging to langfuse, datadog, etc.
         """
         if call_type == "completion" or call_type == "acompletion":  # /chat/completions requests
             messages: Final[list | None] = kwargs.get("messages", None)
@@ -847,6 +847,19 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
             verbose_proxy_logger.debug("Presidio PII Masking: Redacted pii message: %s", messages)
             kwargs["messages"] = messages
 
+            if (
+                isinstance(result, ModelResponse)
+                and result.choices
+                and not isinstance(result.choices[0], StreamingChoices)
+            ):
+                await self._process_response_for_pii(response=result, request_data=kwargs, mode="mask")
+            elif self._is_anthropic_message_response(result):
+                await self._process_anthropic_response_for_pii(
+                    response=cast(dict, result),  # cast-ok: _is_anthropic_message_response narrows via isinstance
+                    request_data=kwargs,
+                    mode="mask",
+                )
+
         return kwargs, result
 
     async def async_post_call_success_hook(
diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py
index c1099081867..4525adb82f3 100644
--- a/litellm/proxy/litellm_pre_call_utils.py
+++ b/litellm/proxy/litellm_pre_call_utils.py
@@ -1622,6 +1622,32 @@ class LiteLLMProxyRequestSetup:
         )
 
 
+def refresh_proxy_server_request_body_snapshot(
+    data: dict,  # mutable-ok: mutates proxy_server_request.body in place on the shared request dict
+) -> None:
+    """
+    Re-snapshot ``data["proxy_server_request"]["body"]`` from the current state of ``data``.
+
+    ``add_litellm_data_to_request`` takes the initial snapshot before guardrails
+    (pre_call_hook) run. A guardrail that masks PII/PCI in place (e.g. Presidio)
+    mutates ``data`` afterward, so callers that persist ``proxy_server_request.body``
+    for audit/spend-tracking purposes must call this again post-guardrail, or the
+    persisted body silently bypasses whatever masking the guardrail applied.
+
+    By the time a caller refreshes post-guardrail, ``litellm.utils.function_setup``
+    has already stamped ``data["litellm_logging_obj"]`` with a live (non-serializable)
+    ``Logging`` instance, so it must be excluded here the same way ``secret_fields``
+    and ``proxy_server_request`` are.
+    """
+    proxy_server_request = data.get("proxy_server_request")
+    if not isinstance(proxy_server_request, dict):
+        return
+    _body_snapshot_exclude = (
+        frozenset({"secret_fields", "proxy_server_request", "litellm_logging_obj"}) | _TRANSPORT_ONLY_CREDENTIAL_KEYS
+    )
+    proxy_server_request["body"] = {k: v for k, v in data.items() if k not in _body_snapshot_exclude}
+
+
 async def add_litellm_data_to_request(
     data: dict,
     request: Request,
@@ -1802,8 +1828,6 @@ async def add_litellm_data_to_request(
         cache_dict: Final = parse_cache_control(cache_control_header)
         data["ttl"] = cache_dict.get("s-maxage")
 
-    verbose_proxy_logger.debug("receiving data: %s", data)
-
     # requester_metadata is snapshotted AFTER the strip below so
     # downstream consumers (e.g. PANW guardrail reading user_ip /
     # profile_id) don't see attacker-injected admin slots preserved in
@@ -1863,9 +1887,7 @@ async def add_litellm_data_to_request(
     #     self-reference — body.proxy_server_request.body would be the same
     #     dict as body, producing an infinite traversal loop for any consumer
     #     that walks the structure.
-    _body_snapshot_exclude = frozenset({"secret_fields", "proxy_server_request"}) | _TRANSPORT_ONLY_CREDENTIAL_KEYS
-    _body_snapshot: Final = {k: v for k, v in data.items() if k not in _body_snapshot_exclude}
-    data["proxy_server_request"]["body"] = _body_snapshot
+    refresh_proxy_server_request_body_snapshot(data)
 
     # Snapshot the requester-supplied metadata for downstream consumers.
     # Taking the deepcopy after the user_api_key_* / _pipeline_managed_guardrails
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py
index 60be3be5e8b..acb43bc5b74 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py
@@ -582,6 +582,52 @@ async def test_logging_hook_multiple_content_items(presidio_guardrail):
     print("✓ Logging hook multiple content items test passed")
 
 
+@pytest.mark.asyncio
+async def test_logging_hook_masks_the_response_too(presidio_guardrail):
+    """
+    Regression: async_logging_hook only masked kwargs["messages"] (the request) and
+    left `result` (the model's response) completely untouched, so in `logging_only`
+    mode any PII in the assistant's reply was logged to langfuse/datadog/etc. in the
+    clear. The hook's own docstring promises masking "before logging" for both input
+    and output.
+    """
+
+    async def mock_check_pii(text, output_parse_pii, presidio_config, request_data):
+        return text.replace("4111-1111-1111-1111", "[CREDIT_CARD]")
+
+    presidio_guardrail.check_pii = mock_check_pii
+
+    test_kwargs = {
+        "messages": [{"role": "user", "content": "hello"}],
+        "model": "gpt-4",
+    }
+    response = ModelResponse(
+        id="1",
+        object="chat.completion",
+        created=0,
+        model="gpt-test",
+        choices=[
+            Choices(
+                message=Message(
+                    role="assistant",
+                    content="Sure, your card is 4111-1111-1111-1111",
+                ),
+                index=0,
+                finish_reason="stop",
+            )
+        ],
+    )
+
+    _, result_response = await presidio_guardrail.async_logging_hook(
+        kwargs=test_kwargs,
+        result=response,
+        call_type="completion",
+    )
+
+    assert "[CREDIT_CARD]" in result_response.choices[0].message.content
+    assert "4111-1111-1111-1111" not in result_response.choices[0].message.content
+
+
 @pytest.mark.asyncio
 async def test_logging_only_does_not_mask_pre_call_request(
     mock_user_api_key, mock_cache
diff --git a/tests/test_litellm/proxy/test_common_request_processing.py b/tests/test_litellm/proxy/test_common_request_processing.py
index 3c738aa164c..f9ba91a246e 100644
--- a/tests/test_litellm/proxy/test_common_request_processing.py
+++ b/tests/test_litellm/proxy/test_common_request_processing.py
@@ -323,6 +323,62 @@ class TestProxyBaseLLMRequestProcessing:
             pytest.fail("litellm_call_id is not a valid UUID")
         assert data_passed["litellm_call_id"] == returned_data["litellm_call_id"]
 
+    @pytest.mark.asyncio
+    async def test_common_processing_pre_call_logic_refreshes_proxy_server_request_body_after_guardrails(
+        self, monkeypatch
+    ):
+        """
+        A guardrail (e.g. Presidio PII masking) mutates data["messages"] in place inside
+        pre_call_hook. The proxy_server_request.body snapshot is taken before that hook
+        runs, so it must be refreshed afterward or SpendLogs (when store_prompts_in_spend_logs
+        is enabled) persists the raw pre-guardrail body, bypassing the masking entirely.
+        """
+        processing_obj = ProxyBaseLLMRequestProcessing(data={})
+        mock_request = MagicMock(spec=Request)
+        mock_request.headers = {}
+
+        raw_messages = [{"role": "user", "content": "my ssn is 123-45-6789"}]
+
+        async def mock_add_litellm_data_to_request(*args, **kwargs):
+            return {
+                "messages": raw_messages,
+                "proxy_server_request": {
+                    "url": "http://testserver/chat/completions",
+                    "method": "POST",
+                    "body": {"messages": raw_messages},
+                },
+            }
+
+        async def mock_pre_call_hook(user_api_key_dict, data, call_type):
+            data["messages"] = [{"role": "user", "content": "my ssn is <MASKED>"}]
+            return data
+
+        mock_proxy_logging_obj = MagicMock(spec=ProxyLogging)
+        mock_proxy_logging_obj.pre_call_hook = AsyncMock(side_effect=mock_pre_call_hook)
+        monkeypatch.setattr(
+            litellm.proxy.common_request_processing,
+            "add_litellm_data_to_request",
+            mock_add_litellm_data_to_request,
+        )
+
+        returned_data, _ = await processing_obj.common_processing_pre_call_logic(
+            request=mock_request,
+            general_settings={},
+            user_api_key_dict=MagicMock(spec=UserAPIKeyAuth),
+            proxy_logging_obj=mock_proxy_logging_obj,
+            proxy_config=MagicMock(spec=ProxyConfig),
+            route_type="acompletion",
+        )
+
+        persisted_body = returned_data["proxy_server_request"]["body"]
+        assert persisted_body["messages"] == returned_data["messages"]
+        assert "123-45-6789" not in json.dumps(persisted_body["messages"])
+        # litellm_logging_obj is stamped onto `data` by function_setup between the
+        # initial snapshot and pre_call_hook; it must never leak into the persisted
+        # audit body, which needs to stay plain-JSON-serializable end to end.
+        assert "litellm_logging_obj" not in persisted_body
+        json.dumps(persisted_body)
+
     def test_add_dd_apm_tags_for_litellm_call_id_uses_dd_tracing_helper(self, monkeypatch):
         mock_set_active_span_tag = MagicMock(return_value=True)
         import litellm.proxy.dd_span_tagger
diff --git a/tests/test_litellm/proxy/test_litellm_pre_call_utils.py b/tests/test_litellm/proxy/test_litellm_pre_call_utils.py
index 111f11f85ba..501b03eae0f 100644
--- a/tests/test_litellm/proxy/test_litellm_pre_call_utils.py
+++ b/tests/test_litellm/proxy/test_litellm_pre_call_utils.py
@@ -710,6 +710,54 @@ async def test_add_litellm_data_to_request_body_snapshot_excludes_proxy_server_r
     )
 
 
+def test_refresh_proxy_server_request_body_snapshot_picks_up_guardrail_masking():
+    """
+    Regression: proxy_server_request['body'] is snapshotted by
+    add_litellm_data_to_request BEFORE guardrails (e.g. Presidio PII masking) run
+    in pre_call_hook. Without a refresh after pre_call_hook, the persisted body
+    silently bypasses whatever masking the guardrail applied, so raw PII/PCI
+    lands in SpendLogs when store_prompts_in_spend_logs is enabled.
+    """
+    from litellm.proxy.litellm_pre_call_utils import (
+        refresh_proxy_server_request_body_snapshot,
+    )
+
+    class _FakeLoggingObj:
+        """Stands in for the live, non-JSON-serializable Logging instance that
+        litellm.utils.function_setup stamps onto `data` between the initial
+        snapshot and pre_call_hook."""
+
+    data = {
+        "model": "gpt-3.5-turbo",
+        "messages": [{"role": "user", "content": "my ssn is 123-45-6789"}],
+        "secret_fields": {"raw_headers": {"authorization": "Bearer sk-secret"}},
+        "litellm_logging_obj": _FakeLoggingObj(),
+        "proxy_server_request": {
+            "url": "http://localhost/v1/chat/completions",
+            "method": "POST",
+            "body": {
+                "model": "gpt-3.5-turbo",
+                "messages": [{"role": "user", "content": "my ssn is 123-45-6789"}],
+            },
+        },
+    }
+
+    # Simulate a PII-masking guardrail mutating `messages` in place, like Presidio's
+    # async_pre_call_hook does, after the initial snapshot was already taken.
+    data["messages"] = [{"role": "user", "content": "my ssn is <MASKED>"}]
+
+    refresh_proxy_server_request_body_snapshot(data)
+
+    refreshed_body = data["proxy_server_request"]["body"]
+    assert refreshed_body["messages"] == data["messages"]
+    # Still excludes secrets, self-reference, and the live logging object, same as
+    # the initial snapshot -- and proves the persisted body stays JSON-serializable.
+    assert "secret_fields" not in refreshed_body
+    assert "proxy_server_request" not in refreshed_body
+    assert "litellm_logging_obj" not in refreshed_body
+    assert "123-45-6789" not in json.dumps(refreshed_body)
+
+
 @pytest.mark.asyncio
 async def test_add_litellm_data_to_request_strips_string_encoded_admin_injection():
     """Regression: metadata arriving as a JSON string (multipart/form-data or

From 6a55683cd0ec20c92447cc809684186d9d2f2a0b Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 14:22:08 -0700
Subject: [PATCH 37/93] refactor: drop the unused response argument from the
 image item extractor

The image generation item ID no longer comes from the chat completion
response, so the extractor does not need it.
---
 .../transformation.py                           |  2 --
 .../test_image_generation_output.py             | 17 -----------------
 2 files changed, 19 deletions(-)

diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index cc2759358d2..aa3d9149c31 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -2039,7 +2039,6 @@ class LiteLLMCompletionResponsesConfig:
 
     @staticmethod
     def _extract_image_generation_output_items(
-        chat_completion_response: ModelResponse,
         choice: Choices,
     ) -> list[OutputImageGenerationCall]:
         """
@@ -2142,7 +2141,6 @@ class LiteLLMCompletionResponsesConfig:
             if hasattr(choice.message, "images") and choice.message.images:
                 # Extract image generation output
                 image_generation_items = LiteLLMCompletionResponsesConfig._extract_image_generation_output_items(
-                    chat_completion_response=chat_completion_response,
                     choice=choice,
                 )
                 message_output_items.extend(image_generation_items)
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_image_generation_output.py b/tests/test_litellm/responses/litellm_completion_transformation/test_image_generation_output.py
index a0bf8664551..80e5335b4d4 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_image_generation_output.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_image_generation_output.py
@@ -57,9 +57,6 @@ class TestExtractImageGenerationOutputItems:
 
     def test_extracts_images_correctly(self):
         """Should extract OutputImageGenerationCall objects from images"""
-        mock_response = Mock(spec=ModelResponse)
-        mock_response.id = "test_123"
-
         mock_message = Mock(spec=Message)
         mock_message.images = [
             {
@@ -80,7 +77,6 @@ class TestExtractImageGenerationOutputItems:
 
         result = (
             LiteLLMCompletionResponsesConfig._extract_image_generation_output_items(
-                chat_completion_response=mock_response,
                 choice=mock_choice,
             )
         )
@@ -96,7 +92,6 @@ class TestExtractImageGenerationOutputItems:
 
     def test_returns_empty_for_no_images(self):
         """Should return empty list if no images"""
-        mock_response = Mock(spec=ModelResponse)
         mock_message = Mock(spec=Message)
         mock_message.images = []
 
@@ -106,7 +101,6 @@ class TestExtractImageGenerationOutputItems:
 
         result = (
             LiteLLMCompletionResponsesConfig._extract_image_generation_output_items(
-                chat_completion_response=mock_response,
                 choice=mock_choice,
             )
         )
@@ -115,9 +109,6 @@ class TestExtractImageGenerationOutputItems:
 
     def test_maps_finish_reason_to_status(self):
         """Should correctly map finish_reason to status"""
-        mock_response = Mock(spec=ModelResponse)
-        mock_response.id = "test_finish"
-
         mock_message = Mock(spec=Message)
         mock_message.images = [
             {
@@ -133,7 +124,6 @@ class TestExtractImageGenerationOutputItems:
 
         result = (
             LiteLLMCompletionResponsesConfig._extract_image_generation_output_items(
-                chat_completion_response=mock_response,
                 choice=mock_choice,
             )
         )
@@ -219,14 +209,8 @@ class TestImageGenerationOutputItemIds:
         mock_choice.finish_reason = "stop"
         return mock_choice
 
-    def _chat_completion_response(self):
-        mock_response = Mock(spec=ModelResponse)
-        mock_response.id = "chatcmpl-dfa2da3a-1586-4ff7-b64e-f59c692a5d11"
-        return mock_response
-
     def test_image_generation_item_id_uses_ig_prefix(self):
         result = LiteLLMCompletionResponsesConfig._extract_image_generation_output_items(
-            chat_completion_response=self._chat_completion_response(),
             choice=self._choice_with_images(2),
         )
 
@@ -238,7 +222,6 @@ class TestImageGenerationOutputItemIds:
 
     def test_image_generation_item_ids_are_unique(self):
         result = LiteLLMCompletionResponsesConfig._extract_image_generation_output_items(
-            chat_completion_response=self._chat_completion_response(),
             choice=self._choice_with_images(3),
         )
 

From 9d22acab110fb0407059481cc32755b0d3e095b1 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 14:22:10 -0700
Subject: [PATCH 38/93] fix(responses): skip the session lookup retry when
 spend logs are off

---
 .../session_handler.py                        |  8 ++++---
 .../test_session_handler.py                   | 21 +++++++++++++++++++
 ...ponse_id.py => test_streaming_iterator.py} |  0
 3 files changed, 26 insertions(+), 3 deletions(-)
 rename tests/test_litellm/responses/litellm_completion_transformation/{test_streaming_iterator_response_id.py => test_streaming_iterator.py} (100%)

diff --git a/litellm/responses/litellm_completion_transformation/session_handler.py b/litellm/responses/litellm_completion_transformation/session_handler.py
index 15267533957..59ff492a79f 100644
--- a/litellm/responses/litellm_completion_transformation/session_handler.py
+++ b/litellm/responses/litellm_completion_transformation/session_handler.py
@@ -258,13 +258,14 @@ class ResponsesSessionHandler:
 
         A just-finished turn gets a short second chance: the worker that served it may
         still be writing its spend log when the follow-up arrives, and an empty result
-        drops the whole conversation instead of erroring.
+        drops the whole conversation instead of erroring. Deployments that write no spend
+        logs at all have nothing to wait for, so they keep the single original query.
         """
         from litellm.constants import (
             RESPONSES_SESSION_LOOKUP_MAX_ATTEMPTS,
             RESPONSES_SESSION_LOOKUP_RETRY_INTERVAL,
         )
-        from litellm.proxy.proxy_server import prisma_client
+        from litellm.proxy.proxy_server import disable_spend_logs, prisma_client
 
         verbose_proxy_logger.debug("decoding response id=%s", previous_response_id)
 
@@ -285,7 +286,8 @@ class ResponsesSessionHandler:
             ORDER BY "endTime" ASC;
         """
 
-        for attempt in range(RESPONSES_SESSION_LOOKUP_MAX_ATTEMPTS):
+        max_attempts: Final = 1 if disable_spend_logs else RESPONSES_SESSION_LOOKUP_MAX_ATTEMPTS
+        for attempt in range(max_attempts):
             if attempt:
                 await asyncio.sleep(RESPONSES_SESSION_LOOKUP_RETRY_INTERVAL)
             if spend_logs := await prisma_client.db.query_raw(query, response_id):
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py b/tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py
index 4fc288a47cb..df477f6d01e 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py
@@ -617,3 +617,24 @@ async def test_message_history_looks_up_the_decoded_chat_completion_id():
         )
 
     assert fake_prisma_client.db.calls == [(request_id,)]
+
+
+@pytest.mark.asyncio
+async def test_session_lookup_does_not_retry_when_spend_logs_are_disabled(
+    instant_session_lookup_retries: None,
+):
+    """
+    A deployment that writes no spend logs has nothing to wait for, so the miss path keeps
+    the single query it always had.
+    """
+    fake_prisma_client = _FakePrismaClient(results=[])
+
+    with patch("litellm.proxy.proxy_server.prisma_client", fake_prisma_client), patch(
+        "litellm.proxy.proxy_server.disable_spend_logs", True
+    ):
+        spend_logs = await ResponsesSessionHandler.get_all_spend_logs_for_previous_response_id(
+            "chatcmpl-does-not-exist"
+        )
+
+    assert spend_logs == []
+    assert fake_prisma_client.db.calls == [("chatcmpl-does-not-exist",)]
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_response_id.py b/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator.py
similarity index 100%
rename from tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_response_id.py
rename to tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator.py

From 7ed91df83694220fe23ea64c4dbc93288284e7e6 Mon Sep 17 00:00:00 2001
From: Yassin Kortam <yassin@berri.ai>
Date: Sat, 22 Aug 2026 14:24:57 -0700
Subject: [PATCH 39/93] fix(proxy): make /team/member_delete's four cleanups
 atomic (#37959)

The team roster update, the user.teams update, the team membership
delete, and the team-scoped verification token delete ran as four
sequential writes with no transaction around them, so a failure
between any two left the removal half applied. Thread a single
prisma transaction through all four writes, following the same
tx.<table> pattern /team/member_add and /team/member_update already
use, so either all four land or none do.
---
 .../key_management_endpoints.py               |  18 +++-
 .../management_endpoints/team_endpoints.py    |  87 +++++++--------
 .../test_team_endpoints.py                    | 102 ++++++++++++++++++
 3 files changed, 162 insertions(+), 45 deletions(-)

diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py
index bf42aeeec05..34a91dc59da 100644
--- a/litellm/proxy/management_endpoints/key_management_endpoints.py
+++ b/litellm/proxy/management_endpoints/key_management_endpoints.py
@@ -20,7 +20,7 @@ import secrets
 import traceback
 from collections.abc import Awaitable, Callable, Mapping, Sequence
 from datetime import datetime, timedelta, timezone
-from typing import Any, Final, Literal, Optional, Protocol, TypeVar, cast
+from typing import TYPE_CHECKING, Any, Final, Literal, Optional, Protocol, TypeVar, cast
 
 import fastapi
 import yaml
@@ -148,6 +148,9 @@ from litellm.types.utils import (
     TeamUIKeyGenerationConfig,
 )
 
+if TYPE_CHECKING:
+    from prisma import Prisma
+
 _PrismaRowT = TypeVar("_PrismaRowT")
 _RepositoryModelT = TypeVar("_RepositoryModelT", bound=BaseModel)
 
@@ -4337,10 +4340,19 @@ def _transform_verification_tokens_to_deleted_records(
 async def _save_deleted_verification_token_records(
     records: Sequence[Mapping[str, object]],
     prisma_client: PrismaClient,
+    tx: "Prisma | None" = None,
 ) -> None:
-    """Save deleted verification token records to the database."""
+    """Save deleted verification token records to the database.
+
+    ``tx`` runs the write on that transaction's connection instead of a fresh
+    one, so a caller batching this with other writes gets one all-or-nothing
+    commit.
+    """
     if not records:
         return
+    if tx is not None:
+        await tx.litellm_deletedverificationtoken.create_many(data=records)
+        return
     await _deleted_verification_token_table(prisma_client).create_many(data=records)
 
 
@@ -4349,6 +4361,7 @@ async def _persist_deleted_verification_tokens(
     prisma_client: PrismaClient,
     user_api_key_dict: UserAPIKeyAuth,
     litellm_changed_by: str | None = None,
+    tx: "Prisma | None" = None,
 ) -> None:
     """Persist deleted verification token records by transforming and saving them."""
     records: Final = _transform_verification_tokens_to_deleted_records(
@@ -4359,6 +4372,7 @@ async def _persist_deleted_verification_tokens(
     await _save_deleted_verification_token_records(
         records=records,
         prisma_client=prisma_client,
+        tx=tx,
     )
 
 
diff --git a/litellm/proxy/management_endpoints/team_endpoints.py b/litellm/proxy/management_endpoints/team_endpoints.py
index a8e545a8551..01254d5c064 100644
--- a/litellm/proxy/management_endpoints/team_endpoints.py
+++ b/litellm/proxy/management_endpoints/team_endpoints.py
@@ -3286,15 +3286,6 @@ async def team_member_delete(
 
     _db_new_team_members: Final[list[dict]] = [m.model_dump() for m in new_team_members]
 
-    _ = await _team_db(prisma_client).update(
-        where={
-            "team_id": data.team_id,
-        },
-        data={"members_with_roles": json.dumps(_db_new_team_members)},
-    )
-
-    _emit_team_members_metric(existing_team_row)
-
     ## DELETE TEAM ID from USER ROW, IF EXISTS ##
     # get user row
     removed_user_ids: Final = frozenset(m.user_id for m in removed_team_members if m.user_id is not None)
@@ -3303,52 +3294,62 @@ async def team_member_delete(
     )
     existing_user_rows: Final[Sequence[LiteLLM_UserTable]] = await _user_db(prisma_client).find_many(where=key_val)
 
-    for existing_user in existing_user_rows:
-        if data.team_id in existing_user.teams:
-            await _user_db(prisma_client).update(
-                where={
-                    "user_id": existing_user.user_id,
-                },
-                data={"teams": {"set": [team for team in existing_user.teams if team != data.team_id]}},
-            )
-
     # Also clean up any existing team membership rows for this user and team
     user_ids_to_delete: Final = removed_user_ids.union(
         (data.user_id,) if data.user_id is not None else (),
         (user.user_id for user in existing_user_rows if user.user_id),
     )
 
-    for _uid in sorted(user_ids_to_delete):
-        await _team_membership_db(prisma_client).delete_many(where={"team_id": data.team_id, "user_id": _uid})
-
     ## DELETE KEYS CREATED BY USER FOR THIS TEAM
-    if user_ids_to_delete:
-        from litellm.proxy.management_endpoints.key_management_endpoints import (
-            _persist_deleted_verification_tokens,
+    # Fetch keys before deletion so their audit records can be persisted alongside the delete.
+    # An empty user_ids_to_delete still resolves cleanly: prisma's "in": [] matches no rows.
+    keys_to_delete: Final[list[LiteLLM_VerificationToken]] = await _tokens_db(prisma_client).find_many(
+        where={
+            "user_id": {"in": sorted(user_ids_to_delete)},
+            "team_id": data.team_id,
+        }
+    )
+
+    # All four cleanups run on one connection so a failure between them leaves
+    # no partial removal: either every write below lands, or none of them do.
+    async with prisma_client.tx() as tx:
+        await tx.litellm_teamtable.update(
+            where={"team_id": data.team_id},
+            data={"members_with_roles": json.dumps(_db_new_team_members)},
         )
 
-        # Fetch keys before deletion to persist them
-        keys_to_delete: Final[list[LiteLLM_VerificationToken]] = await _tokens_db(prisma_client).find_many(
-            where={
-                "user_id": {"in": sorted(user_ids_to_delete)},
-                "team_id": data.team_id,
-            }
-        )
+        for existing_user in existing_user_rows:
+            if data.team_id in existing_user.teams:
+                await tx.litellm_usertable.update(
+                    where={"user_id": existing_user.user_id},
+                    data={"teams": {"set": [team for team in existing_user.teams if team != data.team_id]}},
+                )
 
-        if keys_to_delete:
-            await _persist_deleted_verification_tokens(
-                keys=keys_to_delete,
-                prisma_client=prisma_client,
-                user_api_key_dict=user_api_key_dict,
-                litellm_changed_by=None,
+        for _uid in sorted(user_ids_to_delete):
+            await tx.litellm_teammembership.delete_many(where={"team_id": data.team_id, "user_id": _uid})
+
+        if user_ids_to_delete:
+            if keys_to_delete:
+                from litellm.proxy.management_endpoints.key_management_endpoints import (
+                    _persist_deleted_verification_tokens,
+                )
+
+                await _persist_deleted_verification_tokens(
+                    keys=keys_to_delete,
+                    prisma_client=prisma_client,
+                    user_api_key_dict=user_api_key_dict,
+                    litellm_changed_by=None,
+                    tx=tx,
+                )
+
+            await tx.litellm_verificationtoken.delete_many(
+                where={
+                    "user_id": {"in": sorted(user_ids_to_delete)},
+                    "team_id": data.team_id,
+                }
             )
 
-        await _tokens_db(prisma_client).delete_many(
-            where={
-                "user_id": {"in": sorted(user_ids_to_delete)},
-                "team_id": data.team_id,
-            }
-        )
+    _emit_team_members_metric(existing_team_row)
 
     return existing_team_row
 
diff --git a/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py
index 34b12aecfed..f6d74a189bc 100644
--- a/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py
+++ b/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py
@@ -80,6 +80,23 @@ def _wire_team_create_tx(prisma_client):
     prisma_client.db.tx = lambda *_args, **_kwargs: _tx()
 
 
+def _wire_member_delete_tx(prisma_client):
+    """/team/member_delete's four cleanups run inside one transaction, so a mocked
+    client has to hand back its own table mocks out of `tx()` for the existing
+    per-table assertions to keep seeing the calls."""
+    tx = SimpleNamespace(
+        litellm_teamtable=prisma_client.db.litellm_teamtable,
+        litellm_usertable=prisma_client.db.litellm_usertable,
+        litellm_teammembership=prisma_client.db.litellm_teammembership,
+        litellm_verificationtoken=prisma_client.db.litellm_verificationtoken,
+        litellm_deletedverificationtoken=prisma_client.db.litellm_deletedverificationtoken,
+    )
+    tx_cm = MagicMock()
+    tx_cm.__aenter__ = AsyncMock(return_value=tx)
+    tx_cm.__aexit__ = AsyncMock(return_value=None)
+    prisma_client.tx = MagicMock(return_value=tx_cm)
+
+
 # Mock prisma_client
 mock_prisma_client = MagicMock()
 # Set up async mock for db operations
@@ -4147,6 +4164,8 @@ async def test_team_member_delete_cleans_membership(mock_db_client, mock_admin_a
         return_value=MagicMock()
     )
 
+    _wire_member_delete_tx(mock_db_client)
+
     # Execute
     await team_member_delete(
         data=TeamMemberDeleteRequest(team_id=test_team_id, user_id=test_user_id),
@@ -4205,6 +4224,8 @@ async def test_team_member_delete_cleans_verification_tokens(
         return_value=MagicMock()
     )
 
+    _wire_member_delete_tx(mock_db_client)
+
     await team_member_delete(
         data=TeamMemberDeleteRequest(team_id=test_team_id, user_id=test_user_id),
         user_api_key_dict=mock_admin_auth,
@@ -4300,6 +4321,8 @@ async def test_team_member_delete_by_email_the_user_row_does_not_carry(
         return_value=MagicMock()
     )
 
+    _wire_member_delete_tx(mock_db_client)
+
     await team_member_delete(
         data=TeamMemberDeleteRequest(team_id=test_team_id, user_email=roster_email),
         user_api_key_dict=mock_admin_auth,
@@ -4318,6 +4341,83 @@ async def test_team_member_delete_by_email_the_user_row_does_not_carry(
     )
 
 
+class _InjectedMemberDeleteFailure(Exception):
+    pass
+
+
+@pytest.mark.asyncio
+async def test_team_member_delete_is_atomic_across_its_four_writes(
+    mock_db_client, mock_admin_auth
+):
+    """
+    /team/member_delete's four cleanups (team roster, user.teams, team
+    membership, verification tokens) run as one transaction, so a failure
+    partway through must not leave the removal half applied.
+
+    Failing the second write (the user's ``teams`` update) pins two things a
+    non-transactional implementation gets wrong: the roster write that already
+    ran has to land on the SAME transaction client the failure raises on (so a
+    real database rolls it back too), and the writes still queued behind the
+    failure (membership delete, token delete) must never be attempted at all.
+    """
+    from litellm.proxy._types import TeamMemberDeleteRequest
+    from litellm.proxy.management_endpoints.team_endpoints import team_member_delete
+
+    test_team_id = "team-del-atomic-123"
+    test_user_id = "user-atomic@example.com"
+
+    mock_team_row = MagicMock()
+    mock_team_row.model_dump.return_value = {
+        "team_id": test_team_id,
+        "members_with_roles": [
+            {"user_id": test_user_id, "user_email": None, "role": "user"}
+        ],
+        "team_member_permissions": [],
+        "metadata": {},
+        "models": [],
+        "spend": 0.0,
+    }
+    mock_db_client.db.litellm_teamtable.find_unique = AsyncMock(
+        return_value=mock_team_row
+    )
+    mock_db_client.db.litellm_teamtable.update = AsyncMock(return_value=mock_team_row)
+
+    mock_user_row = MagicMock()
+    mock_user_row.user_id = test_user_id
+    mock_user_row.teams = [test_team_id]
+    mock_db_client.db.litellm_usertable.find_many = AsyncMock(
+        return_value=[mock_user_row]
+    )
+    mock_db_client.db.litellm_usertable.update = AsyncMock(
+        side_effect=_InjectedMemberDeleteFailure("boom between writes 1 and 2")
+    )
+
+    mock_db_client.db.litellm_teammembership = MagicMock()
+    mock_db_client.db.litellm_teammembership.delete_many = AsyncMock()
+
+    mock_db_client.db.litellm_verificationtoken = MagicMock()
+    mock_db_client.db.litellm_verificationtoken.find_many = AsyncMock(return_value=[])
+    mock_db_client.db.litellm_verificationtoken.delete_many = AsyncMock()
+
+    _wire_member_delete_tx(mock_db_client)
+
+    with pytest.raises(_InjectedMemberDeleteFailure):
+        await team_member_delete(
+            data=TeamMemberDeleteRequest(team_id=test_team_id, user_id=test_user_id),
+            user_api_key_dict=mock_admin_auth,
+        )
+
+    # The roster write ran, but on the transaction the injected failure also raised on.
+    mock_db_client.db.litellm_teamtable.update.assert_awaited_once()
+    mock_db_client.tx.assert_called_once()
+    aexit_args = mock_db_client.tx.return_value.__aexit__.await_args.args
+    assert aexit_args[0] is _InjectedMemberDeleteFailure
+
+    # Writes queued behind the failure inside that same transaction never ran.
+    mock_db_client.db.litellm_teammembership.delete_many.assert_not_awaited()
+    mock_db_client.db.litellm_verificationtoken.delete_many.assert_not_awaited()
+
+
 @pytest.mark.asyncio
 async def test_new_team_max_budget_exceeds_user_max_budget():
     """
@@ -7806,6 +7906,8 @@ async def test_team_member_delete_persists_deleted_keys(monkeypatch):
         mock_create_many_keys
     )
 
+    _wire_member_delete_tx(mock_prisma_client)
+
     monkeypatch.setattr(
         "litellm.proxy.proxy_server.prisma_client",
         mock_prisma_client,

From 15510f0b8ba52c9c92ccbd667f8620c562acb1cd Mon Sep 17 00:00:00 2001
From: Yassin Kortam <yassin@berri.ai>
Date: Sat, 22 Aug 2026 14:25:11 -0700
Subject: [PATCH 40/93] fix(auth): resolve team object_permission independently
 in the unresolvable-team fallback (#37960)

* fix(auth): resolve team object_permission independently in the unresolvable-team fallback

When get_team_object fails for a token's team_id, _user_api_key_auth_builder
reconstructs a LiteLLM_TeamTableCachedObj from the token's own cached fields,
carrying team_object_permission_id but leaving object_permission unset. That
silently dropped any vector-store or MCP restriction the team carried,
granting more access than the token's own object_permission_id vouches for.

Resolve the object permission by its id directly via get_object_permission,
independent of the unreadable team row, matching how every other consumer of
a team's object_permission (vector store access checks, MCP tool/server
resolvers) already treats an unresolvable team as "no restriction at this
level" and re-resolves on its own.

* fix(auth): trim ticket references and narrative docstrings per Greptile review

Drop the LIT-5539 ticket id from test names and fixture strings, and shorten
both the new helper's docstring and the regression test docstrings to their
contracts rather than restating the fix's history.
---
 litellm/proxy/auth/user_api_key_auth.py       |  28 +++
 .../proxy/auth/test_user_api_key_auth.py      | 195 ++++++++++++++++++
 2 files changed, 223 insertions(+)

diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py
index fe4f1ee4ae5..e04cd19ffcc 100644
--- a/litellm/proxy/auth/user_api_key_auth.py
+++ b/litellm/proxy/auth/user_api_key_auth.py
@@ -49,6 +49,7 @@ from litellm.proxy.auth.auth_checks import (
     common_checks,
     get_end_user_object,
     get_jwt_key_mapping_object,
+    get_object_permission,
     get_project_object,
     get_team_object,
     get_user_object,
@@ -1142,6 +1143,26 @@ async def _record_unparsable_body_failure(
         verbose_proxy_logger.exception("Failed to log the request rejected for an unparsable body: %s", e)
 
 
+async def _resolve_object_permission_for_unresolvable_team(
+    object_permission_id: str | None,
+    prisma_client: PrismaClient | None,
+    user_api_key_cache: UserApiKeyCache,
+    parent_otel_span: Span | None,
+    proxy_logging_obj: ProxyLogging,
+) -> LiteLLM_ObjectPermissionTable | None:
+    """Re-resolve a team's object permission by id when the team row itself is unreadable, so the
+    token-derived fallback doesn't silently drop it."""
+    if object_permission_id is None or prisma_client is None:
+        return None
+    return await get_object_permission(
+        object_permission_id=object_permission_id,
+        prisma_client=prisma_client,
+        user_api_key_cache=user_api_key_cache,
+        parent_otel_span=parent_otel_span,
+        proxy_logging_obj=proxy_logging_obj,
+    )
+
+
 async def _user_api_key_auth_builder(
     request: Request,
     api_key: str,
@@ -2114,6 +2135,13 @@ async def _user_api_key_auth_builder(
                         models=valid_token.team_models,
                         metadata=valid_token.team_metadata,
                         object_permission_id=valid_token.team_object_permission_id,
+                        object_permission=await _resolve_object_permission_for_unresolvable_team(
+                            object_permission_id=valid_token.team_object_permission_id,
+                            prisma_client=prisma_client,
+                            user_api_key_cache=user_api_key_cache,
+                            parent_otel_span=parent_otel_span,
+                            proxy_logging_obj=proxy_logging_obj,
+                        ),
                     )
             else:
                 _team_obj = None
diff --git a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py
index c1e235b77f6..264f43c7259 100644
--- a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py
+++ b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py
@@ -3575,6 +3575,201 @@ async def test_auth_flow_never_persists_fallback_team_object_lit_4391():
             setattr(_proxy_server_mod, k, v)
 
 
+@pytest.mark.asyncio
+async def test_auth_flow_fallback_team_resolves_object_permission_by_id():
+    """The unresolvable-team fallback resolves team_object_permission by its own id instead of leaving it unset."""
+    from starlette.datastructures import URL
+    from starlette.requests import Request
+    from fastapi import HTTPException
+
+    from litellm.proxy._types import (
+        LiteLLM_ObjectPermissionTable,
+        LitellmUserRoles,
+        UserAPIKeyAuth,
+    )
+    from litellm.proxy.auth.user_api_key_auth import _user_api_key_auth_builder
+
+    api_key = "sk-test-fallback-team-object-permission"
+    valid_token = UserAPIKeyAuth(
+        api_key=api_key,
+        token=api_key,
+        user_role=LitellmUserRoles.INTERNAL_USER,
+        team_id="team-fallback-object-permission",
+        team_object_permission_id="op-fallback-object-permission",
+    )
+
+    restricted_object_permission = LiteLLM_ObjectPermissionTable(
+        object_permission_id="op-fallback-object-permission",
+        vector_stores=["vs-allowed-only"],
+        mcp_servers=["mcp-allowed-only"],
+    )
+
+    mock_cache = AsyncMock()
+    mock_cache.async_get_cache = AsyncMock(return_value=valid_token)
+    mock_cache.async_set_cache = AsyncMock(return_value=None)
+
+    mock_proxy_logging_obj = MagicMock()
+    mock_proxy_logging_obj.internal_usage_cache = MagicMock()
+    mock_proxy_logging_obj.internal_usage_cache.dual_cache = AsyncMock()
+    mock_proxy_logging_obj.post_call_failure_hook = AsyncMock(return_value=None)
+
+    import litellm.proxy.proxy_server as _proxy_server_mod
+
+    _attrs = {
+        "prisma_client": MagicMock(),
+        "user_api_key_cache": mock_cache,
+        "proxy_logging_obj": mock_proxy_logging_obj,
+        "master_key": "sk-master-key",
+        "general_settings": {},
+        "llm_model_list": [],
+        "llm_router": None,
+        "open_telemetry_logger": None,
+        "model_max_budget_limiter": MagicMock(),
+        "user_custom_auth": None,
+        "jwt_handler": None,
+        "litellm_proxy_admin_name": "admin",
+    }
+    _originals = {k: getattr(_proxy_server_mod, k, None) for k in _attrs}
+
+    try:
+        for k, v in _attrs.items():
+            setattr(_proxy_server_mod, k, v)
+
+        request = Request(scope={"type": "http"})
+        request._url = URL(url="/chat/completions")
+
+        with (
+            patch(
+                "litellm.proxy.auth.resolvers.store.IdentityStore._resolve_key",
+                new_callable=AsyncMock,
+                return_value=valid_token,
+            ),
+            patch(
+                "litellm.proxy.auth.user_api_key_auth.get_team_object",
+                new_callable=AsyncMock,
+                side_effect=HTTPException(
+                    status_code=404,
+                    detail={"error": "Team doesn't exist in db."},
+                ),
+            ),
+            patch(
+                "litellm.proxy.auth.user_api_key_auth.get_object_permission",
+                new_callable=AsyncMock,
+                return_value=restricted_object_permission,
+            ) as mock_get_object_permission,
+        ):
+            result = await _user_api_key_auth_builder(
+                request=request,
+                api_key=f"Bearer {api_key}",
+                azure_api_key_header="",
+                anthropic_api_key_header=None,
+                google_ai_studio_api_key_header=None,
+                azure_apim_header=None,
+                request_data={},
+            )
+
+        mock_get_object_permission.assert_awaited_once()
+        assert mock_get_object_permission.await_args.kwargs["object_permission_id"] == "op-fallback-object-permission"
+        assert result.team_object_permission == restricted_object_permission
+        assert result.team_object_permission.vector_stores == ["vs-allowed-only"]
+        assert result.team_object_permission.mcp_servers == ["mcp-allowed-only"]
+
+    finally:
+        for k, v in _originals.items():
+            setattr(_proxy_server_mod, k, v)
+
+
+@pytest.mark.asyncio
+async def test_auth_flow_fallback_team_object_permission_none_when_unreadable():
+    """When the object_permission row is also unreadable, the fallback leaves team_object_permission as None
+    instead of raising or fabricating a grant."""
+    from starlette.datastructures import URL
+    from starlette.requests import Request
+    from fastapi import HTTPException
+
+    from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth
+    from litellm.proxy.auth.user_api_key_auth import _user_api_key_auth_builder
+
+    api_key = "sk-test-fallback-team-object-permission-unreadable"
+    valid_token = UserAPIKeyAuth(
+        api_key=api_key,
+        token=api_key,
+        user_role=LitellmUserRoles.INTERNAL_USER,
+        team_id="team-fallback-object-permission-unreadable",
+        team_object_permission_id="op-fallback-object-permission-unreadable",
+    )
+
+    mock_cache = AsyncMock()
+    mock_cache.async_get_cache = AsyncMock(return_value=valid_token)
+    mock_cache.async_set_cache = AsyncMock(return_value=None)
+
+    mock_proxy_logging_obj = MagicMock()
+    mock_proxy_logging_obj.internal_usage_cache = MagicMock()
+    mock_proxy_logging_obj.internal_usage_cache.dual_cache = AsyncMock()
+    mock_proxy_logging_obj.post_call_failure_hook = AsyncMock(return_value=None)
+
+    import litellm.proxy.proxy_server as _proxy_server_mod
+
+    _attrs = {
+        "prisma_client": MagicMock(),
+        "user_api_key_cache": mock_cache,
+        "proxy_logging_obj": mock_proxy_logging_obj,
+        "master_key": "sk-master-key",
+        "general_settings": {},
+        "llm_model_list": [],
+        "llm_router": None,
+        "open_telemetry_logger": None,
+        "model_max_budget_limiter": MagicMock(),
+        "user_custom_auth": None,
+        "jwt_handler": None,
+        "litellm_proxy_admin_name": "admin",
+    }
+    _originals = {k: getattr(_proxy_server_mod, k, None) for k in _attrs}
+
+    try:
+        for k, v in _attrs.items():
+            setattr(_proxy_server_mod, k, v)
+
+        request = Request(scope={"type": "http"})
+        request._url = URL(url="/chat/completions")
+
+        with (
+            patch(
+                "litellm.proxy.auth.resolvers.store.IdentityStore._resolve_key",
+                new_callable=AsyncMock,
+                return_value=valid_token,
+            ),
+            patch(
+                "litellm.proxy.auth.user_api_key_auth.get_team_object",
+                new_callable=AsyncMock,
+                side_effect=HTTPException(
+                    status_code=404,
+                    detail={"error": "Team doesn't exist in db."},
+                ),
+            ),
+            patch(
+                "litellm.proxy.auth.user_api_key_auth.get_object_permission",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+        ):
+            result = await _user_api_key_auth_builder(
+                request=request,
+                api_key=f"Bearer {api_key}",
+                azure_api_key_header="",
+                anthropic_api_key_header=None,
+                google_ai_studio_api_key_header=None,
+                azure_apim_header=None,
+                request_data={},
+            )
+
+        assert result.team_object_permission is None
+
+    finally:
+        for k, v in _originals.items():
+            setattr(_proxy_server_mod, k, v)
+
+
 # ---------------------------------------------------------------------------
 
 # _run_centralized_common_checks — centralized authz gate

From ba876c98e6727fca5c2f2740c4e6912d86ec2d49 Mon Sep 17 00:00:00 2001
From: Yassin Kortam <yassin@berri.ai>
Date: Sat, 22 Aug 2026 14:25:29 -0700
Subject: [PATCH 41/93] fix(auth): stop the team fallback from widening model
 access (#37962)

When get_team_object fails, the centralized auth gate rebuilds the team
from the token's own fields. A token whose team row was missing when the
key was read carries team_models=[] and team_blocked=False, and the
model-access check reads an empty model list as every model, so the
rebuilt team grants more than the real team ever did.

get_team_object reported a deleted team and a database that would not
answer as the same 404, so the fallback could not tell a definitive
answer from a degraded read. Raise a TeamNotFoundError subclass, still a
404 with the same detail so every other caller is unaffected, only when
the database answers and the row is absent.

A team that is provably gone now refuses, and no setting overrides that.
Otherwise the grant is merely unknown: a token carrying one may vouch,
since replaying a recorded grant cannot widen it, and a token carrying
none may not. allow_requests_on_db_unavailable still opts back out there,
and is only consulted once the failure is known to be a degraded read.

The Admin UI mints every session key against the UI_TEAM_ID sentinel,
which by design never has a team row, so every UI request hit the new
refusal with no override. Exempt UI_TEAM_ID explicitly so it keeps
reconstructing from the token unconditionally, matching how the MCP
handler and agent_permission_handler already special-case it.

Resolves LIT-5522
---
 litellm/proxy/auth/auth_checks.py             |  28 ++
 litellm/proxy/auth/user_api_key_auth.py       |  39 ++-
 .../test_user_api_key_auth.py                 |   2 +
 .../proxy/auth/test_auth_checks.py            |  47 +++
 .../proxy/auth/test_user_api_key_auth.py      | 277 ++++++++++++++++++
 5 files changed, 392 insertions(+), 1 deletion(-)

diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py
index 12d6b44a648..e7b98b3cc7f 100644
--- a/litellm/proxy/auth/auth_checks.py
+++ b/litellm/proxy/auth/auth_checks.py
@@ -19,6 +19,7 @@ from typing import TYPE_CHECKING, Any, Final, Literal, Optional, Protocol, cast
 
 from fastapi import HTTPException, Request, status
 from pydantic import BaseModel
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_proxy_logger
@@ -2512,6 +2513,27 @@ async def delete_cache_key_objects(
         await publish_auth_cache_invalidation(cache_key=hashed_token)
 
 
+class _TeamNotFoundDetail(TypedDict):
+    error: ReadOnly[str]
+
+
+class TeamNotFoundError(HTTPException):
+    """The team row is provably absent, as opposed to merely unreadable.
+
+    ``get_team_object`` reports every failure as a 404, so a deleted team and a
+    database that would not answer are indistinguishable to its callers. Callers
+    that must not treat a degraded read as a definitive answer, such as the
+    authorization fallback in ``user_api_key_auth``, key on this subclass. It
+    stays a 404 carrying the same detail, so every other caller is unaffected.
+    """
+
+    def __init__(self, team_id: str) -> None:
+        detail: Final[_TeamNotFoundDetail] = {
+            "error": f"Team doesn't exist in db. Team={team_id}. Create team via `/team/new` call."
+        }
+        super().__init__(status_code=404, detail=detail)
+
+
 @log_db_metrics
 async def _get_team_db_check(
     team_id: str, prisma_client: PrismaClient, team_id_upsert: bool | None = None
@@ -2557,6 +2579,10 @@ async def _get_team_object_from_user_api_key_cache(
     )
     if should_check_db:
         response = await _get_team_db_check(team_id=team_id, prisma_client=prisma_client, team_id_upsert=team_id_upsert)
+        # The database answered and the row is not there. Distinct from every
+        # other failure here, which leaves the team's grant unknown.
+        if response is None:
+            raise TeamNotFoundError(team_id=team_id)
     else:
         response = None
 
@@ -2678,6 +2704,8 @@ async def get_team_object(
             key=key,
             team_id_upsert=team_id_upsert,
         )
+    except TeamNotFoundError:
+        raise
     except Exception:
         raise HTTPException(
             status_code=404,
diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py
index e04cd19ffcc..84e60eb0dd8 100644
--- a/litellm/proxy/auth/user_api_key_auth.py
+++ b/litellm/proxy/auth/user_api_key_auth.py
@@ -35,6 +35,7 @@ from litellm.litellm_core_utils.dot_notation_indexing import get_nested_value
 from litellm.proxy._types import *
 from litellm.proxy.auth.auth_checks import (
     ExperimentalUIJWTToken,
+    TeamNotFoundError,
     _cache_key_object,
     _can_object_call_model,
     _check_end_user_budget,
@@ -87,6 +88,7 @@ from litellm.proxy.common_utils.http_parsing_utils import (
 )
 from litellm.proxy.common_utils.realtime_utils import _realtime_request_body
 from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache
+from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler
 from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup
 from litellm.proxy.utils import (
     PrismaClient,
@@ -2290,6 +2292,36 @@ def _team_obj_from_token(valid_token: UserAPIKeyAuth) -> LiteLLM_TeamTableCached
     )
 
 
+def _token_can_vouch_for_team(valid_token: UserAPIKeyAuth, lookup_error: BaseException) -> bool:
+    """Whether the token's own team fields may stand in for a team that failed to
+    resolve, without widening access.
+
+    The UI dashboard mints every session key against the ``UI_TEAM_ID`` sentinel,
+    which by design never has a team row, so a failed lookup for it is not a
+    degraded read to be treated with suspicion; it always vouches, exactly as it
+    always safely has (these keys are restricted elsewhere to UI-only routes).
+
+    For every other team, a team that is provably gone is a definitive answer,
+    not a degraded read, so nothing may stand in for it and no setting may
+    override that.
+
+    Otherwise the team's grant is merely unknown. A token carrying one may vouch,
+    since replaying a recorded grant cannot widen it and denying every team key
+    while the row is briefly unreadable would trade the widening for an outage. A
+    token carrying none may not: ``team_models=[]`` reads as every model and
+    ``team_blocked=False`` as unblocked. ``allow_requests_on_db_unavailable`` opts
+    back out, and is only consulted here because the failure is known by this
+    point to be a degraded read.
+    """
+    if valid_token.team_id == UI_TEAM_ID:
+        return True
+    if isinstance(lookup_error, TeamNotFoundError):
+        return False
+    if valid_token.team_models:
+        return True
+    return PrismaDBExceptionHandler.should_allow_request_on_db_unavailable()
+
+
 @tracer.wrap()
 async def _run_centralized_common_checks(
     user_api_key_auth_obj: UserAPIKeyAuth,
@@ -2494,7 +2526,12 @@ async def _run_centralized_common_checks(
     if isinstance(team_result, BaseException):
         # Token-derived fallback only valid when a team_id is set;
         # _team_obj_from_token asserts that precondition.
-        team_object = _team_obj_from_token(user_api_key_auth_obj) if user_api_key_auth_obj.team_id is not None else None
+        if user_api_key_auth_obj.team_id is None:
+            team_object = None
+        elif _token_can_vouch_for_team(user_api_key_auth_obj, team_result):
+            team_object = _team_obj_from_token(user_api_key_auth_obj)
+        else:
+            raise team_result
     else:
         team_object = team_result
 
diff --git a/tests/proxy_unit_tests/test_user_api_key_auth.py b/tests/proxy_unit_tests/test_user_api_key_auth.py
index cc7de71aa56..0cdf3500d50 100644
--- a/tests/proxy_unit_tests/test_user_api_key_auth.py
+++ b/tests/proxy_unit_tests/test_user_api_key_auth.py
@@ -154,6 +154,7 @@ async def test_team_object_has_object_permission_id():
         token=hashed_key,
         last_refreshed_at=time.time(),
         team_object_permission_id=permission_id,
+        team_models=["gpt-4o"],
     )
     user_api_key_cache.set_cache(key=hashed_key, value=valid_token)
 
@@ -242,6 +243,7 @@ async def test_aaauser_personal_budgets(key_ownership):
             user_id=_user_id,
             team_id="my-special-team",
             team_max_budget=100,
+            team_models=["gpt-4o"],
             spend=20,
         )
 
diff --git a/tests/test_litellm/proxy/auth/test_auth_checks.py b/tests/test_litellm/proxy/auth/test_auth_checks.py
index a34df54adfa..04f38b5e2ed 100644
--- a/tests/test_litellm/proxy/auth/test_auth_checks.py
+++ b/tests/test_litellm/proxy/auth/test_auth_checks.py
@@ -2455,6 +2455,53 @@ async def test_get_team_object_raises_404_when_not_found():
     assert "Team doesn't exist in db" in str(exc_info.value.detail)
 
 
+def _mock_prisma_for_team_lookup(find_unique):
+    from unittest.mock import MagicMock
+
+    mock_prisma_client = MagicMock()
+    mock_prisma_client.db.litellm_teamtable.find_unique = find_unique
+    return mock_prisma_client
+
+
+@pytest.mark.asyncio
+async def test_get_team_object_distinguishes_absent_team_from_unreadable_row():
+    """A deleted team and a database that would not answer both surface as a 404,
+    which leaves callers unable to tell a definitive answer from a degraded read.
+    Only the row being positively absent raises the subclass; anything else keeps
+    the plain 404 so every existing caller is unaffected."""
+    from unittest.mock import AsyncMock, MagicMock
+
+    from fastapi import HTTPException
+
+    from litellm.proxy.auth.auth_checks import TeamNotFoundError, get_team_object
+
+    mock_cache = MagicMock()
+    mock_cache.async_get_cache = AsyncMock(return_value=None)
+
+    # The database answered, and the row is not there.
+    with pytest.raises(TeamNotFoundError) as absent_info:
+        await get_team_object(
+            team_id="absent-team-lit5522",
+            prisma_client=_mock_prisma_for_team_lookup(AsyncMock(return_value=None)),
+            user_api_key_cache=mock_cache,
+            check_db_only=True,
+        )
+    assert absent_info.value.status_code == 404
+    assert "Team doesn't exist in db" in str(absent_info.value.detail)
+
+    # The database did not answer. Same status and detail, but not the subclass,
+    # so a caller keying on it does not read this as proof the team is gone.
+    with pytest.raises(HTTPException) as unreadable_info:
+        await get_team_object(
+            team_id="unreadable-team-lit5522",
+            prisma_client=_mock_prisma_for_team_lookup(AsyncMock(side_effect=ConnectionError("db unreachable"))),
+            user_api_key_cache=mock_cache,
+            check_db_only=True,
+        )
+    assert unreadable_info.value.status_code == 404
+    assert not isinstance(unreadable_info.value, TeamNotFoundError)
+
+
 # Reject Client-Side Metadata Tags Tests
 
 
diff --git a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py
index 264f43c7259..470a01cfaa3 100644
--- a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py
+++ b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py
@@ -4693,6 +4693,283 @@ async def test_centralized_common_checks_team_404_does_not_zero_other_contexts()
             setattr(_proxy_server_mod, k, v)
 
 
+@pytest.mark.asyncio
+async def test_centralized_common_checks_unresolvable_team_without_grant_is_refused():
+    """The store restricts the team to gpt-4o-mini and the read of it fails, so the
+    only surviving team record is the token's own, which carries ``team_models=[]``
+    and reads as every model. The request must be refused with the original lookup
+    error. Pre-fix it was served."""
+    import litellm.proxy.proxy_server as _proxy_server_mod
+    from fastapi import HTTPException, Request
+    from starlette.datastructures import URL
+
+    token = UserAPIKeyAuth(
+        api_key="sk-test",
+        team_id="restricted-team",
+        models=[],
+        team_models=[],
+    )
+    request = Request(scope={"type": "http"})
+    request._url = URL(url="/chat/completions")
+    request._body = json.dumps({"model": "gpt-4.1"}).encode()
+
+    team_read_failure = HTTPException(
+        status_code=404,
+        detail={"error": "Team doesn't exist in db. Team=restricted-team."},
+    )
+
+    attrs = _proxy_attrs_for_centralized_checks(user_custom_auth=None)
+    originals = {a: getattr(_proxy_server_mod, a, None) for a in attrs}
+    try:
+        for k, v in attrs.items():
+            setattr(_proxy_server_mod, k, v)
+        with patch(
+            "litellm.proxy.auth.user_api_key_auth.get_team_object",
+            new_callable=AsyncMock,
+            side_effect=team_read_failure,
+        ):
+            with pytest.raises(HTTPException) as exc_info:
+                await _run_centralized_common_checks(
+                    user_api_key_auth_obj=token,
+                    request=request,
+                    request_data={"model": "gpt-4.1"},
+                    route="/chat/completions",
+                )
+        assert exc_info.value is team_read_failure
+    finally:
+        for k, v in originals.items():
+            setattr(_proxy_server_mod, k, v)
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("token_team_models", [[], ["gpt-4.1"]])
+async def test_centralized_common_checks_absent_team_refused_despite_db_unavailable_optout(token_team_models):
+    """A team that is provably gone is a definitive answer, not a degraded read.
+    ``allow_requests_on_db_unavailable`` is a static settings read, so without the
+    absent-versus-unreadable distinction it would hand a deleted team's key the
+    old permissive fallback while the database is perfectly healthy. Refused in
+    both token shapes, including the one whose grant would otherwise vouch.
+
+    Imported from the module under test rather than from ``auth_checks``: other
+    tests in this suite ``importlib.reload`` that module, which rebinds the class
+    and would leave this raising a type the guard has never seen."""
+    import litellm.proxy.proxy_server as _proxy_server_mod
+    from fastapi import HTTPException, Request
+    from starlette.datastructures import URL
+
+    from litellm.proxy.auth.user_api_key_auth import TeamNotFoundError
+
+    token = UserAPIKeyAuth(
+        api_key="sk-test",
+        team_id="deleted-team",
+        models=[],
+        team_models=token_team_models,
+    )
+    request = Request(scope={"type": "http"})
+    request._url = URL(url="/chat/completions")
+    request._body = json.dumps({"model": "gpt-4.1"}).encode()
+
+    team_absent = TeamNotFoundError(team_id="deleted-team")
+
+    attrs = _proxy_attrs_for_centralized_checks(user_custom_auth=None)
+    attrs["general_settings"] = {"allow_requests_on_db_unavailable": True}
+    originals = {a: getattr(_proxy_server_mod, a, None) for a in attrs}
+    try:
+        for k, v in attrs.items():
+            setattr(_proxy_server_mod, k, v)
+        with patch(
+            "litellm.proxy.auth.user_api_key_auth.get_team_object",
+            new_callable=AsyncMock,
+            side_effect=team_absent,
+        ):
+            with pytest.raises(HTTPException) as exc_info:
+                await _run_centralized_common_checks(
+                    user_api_key_auth_obj=token,
+                    request=request,
+                    request_data={"model": "gpt-4.1"},
+                    route="/chat/completions",
+                )
+        assert exc_info.value is team_absent
+    finally:
+        for k, v in originals.items():
+            setattr(_proxy_server_mod, k, v)
+
+
+@pytest.mark.asyncio
+async def test_centralized_common_checks_unreadable_team_keeps_db_unavailable_optout():
+    """The counterpart: an unreadable team leaves the grant unknown rather than
+    answered, so an operator who has accepted degraded authorization during a
+    database fault still gets the fallback. Without this the fix would trade the
+    widening for a lockout with no way out."""
+    import litellm.proxy.proxy_server as _proxy_server_mod
+    from fastapi import HTTPException as _HTTPException
+    from fastapi import Request
+    from starlette.datastructures import URL
+
+    from litellm.proxy._types import LiteLLM_TeamTableCachedObj
+
+    token = UserAPIKeyAuth(api_key="sk-test", team_id="unreadable-team", models=[], team_models=[])
+    request = Request(scope={"type": "http"})
+    request._url = URL(url="/chat/completions")
+    request._body = json.dumps({"model": "gpt-4.1"}).encode()
+
+    received_team_objects: list[LiteLLM_TeamTableCachedObj | None] = []
+
+    async def _capturing_common_checks(*_args, **kwargs) -> bool:
+        received_team_objects.append(kwargs.get("team_object"))
+        return True
+
+    attrs = _proxy_attrs_for_centralized_checks(user_custom_auth=None)
+    attrs["general_settings"] = {"allow_requests_on_db_unavailable": True}
+    originals = {a: getattr(_proxy_server_mod, a, None) for a in attrs}
+    try:
+        for k, v in attrs.items():
+            setattr(_proxy_server_mod, k, v)
+        with (
+            patch(
+                "litellm.proxy.auth.user_api_key_auth.get_team_object",
+                new_callable=AsyncMock,
+                side_effect=_HTTPException(status_code=404, detail={"error": "team unreadable"}),
+            ),
+            patch(
+                "litellm.proxy.auth.user_api_key_auth.common_checks",
+                _capturing_common_checks,
+            ),
+        ):
+            await _run_centralized_common_checks(
+                user_api_key_auth_obj=token,
+                request=request,
+                request_data={"model": "gpt-4.1"},
+                route="/chat/completions",
+            )
+        assert len(received_team_objects) == 1
+        received_team_object = received_team_objects[0]
+        assert received_team_object is not None
+        assert received_team_object.team_id == "unreadable-team"
+    finally:
+        for k, v in originals.items():
+            setattr(_proxy_server_mod, k, v)
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "requested_model, is_granted",
+    [("gpt-4o-mini", True), ("gpt-4.1", False)],
+)
+async def test_centralized_common_checks_unresolvable_team_with_grant_enforces_it(requested_model, is_granted):
+    """Mirror of the refusal above: a token that does carry a team model grant keeps
+    the fallback, and the reconstructed team must still enforce that grant rather
+    than wave the request through."""
+    import litellm.proxy.proxy_server as _proxy_server_mod
+    from fastapi import HTTPException, Request
+    from starlette.datastructures import URL
+
+    from litellm.proxy._types import ProxyErrorTypes, ProxyException
+
+    token = UserAPIKeyAuth(
+        api_key="sk-test",
+        team_id="restricted-team",
+        models=[],
+        team_models=["gpt-4o-mini"],
+    )
+    request = Request(scope={"type": "http"})
+    request._url = URL(url="/chat/completions")
+    request._body = json.dumps({"model": requested_model}).encode()
+
+    attrs = _proxy_attrs_for_centralized_checks(user_custom_auth=None)
+    originals = {a: getattr(_proxy_server_mod, a, None) for a in attrs}
+    try:
+        for k, v in attrs.items():
+            setattr(_proxy_server_mod, k, v)
+        with patch(
+            "litellm.proxy.auth.user_api_key_auth.get_team_object",
+            new_callable=AsyncMock,
+            side_effect=HTTPException(status_code=404, detail={"error": "team unreadable"}),
+        ):
+            if is_granted:
+                await _run_centralized_common_checks(
+                    user_api_key_auth_obj=token,
+                    request=request,
+                    request_data={"model": requested_model},
+                    route="/chat/completions",
+                )
+            else:
+                with pytest.raises(ProxyException) as exc_info:
+                    await _run_centralized_common_checks(
+                        user_api_key_auth_obj=token,
+                        request=request,
+                        request_data={"model": requested_model},
+                        route="/chat/completions",
+                    )
+                assert exc_info.value.type == ProxyErrorTypes.team_model_access_denied
+    finally:
+        for k, v in originals.items():
+            setattr(_proxy_server_mod, k, v)
+
+
+@pytest.mark.asyncio
+async def test_centralized_common_checks_ui_sentinel_team_vouches_despite_absent_row():
+    """The Admin UI mints every session key against the ``UI_TEAM_ID`` sentinel,
+    which by design never has a ``LiteLLM_TeamTable`` row, so ``get_team_object``
+    always raises ``TeamNotFoundError`` for it. That must NOT be read as "team
+    provably gone, refuse" the way it is for a real team_id: PR #36837 made that
+    exact mistake and PR #36982 reverted it because every dashboard request
+    404'd. The sentinel must keep vouching from the token unconditionally."""
+    import litellm.proxy.proxy_server as _proxy_server_mod
+    from fastapi import Request
+    from starlette.datastructures import URL
+
+    from litellm.proxy._types import UI_TEAM_ID, LiteLLM_TeamTableCachedObj
+    from litellm.proxy.auth.user_api_key_auth import TeamNotFoundError
+
+    token = UserAPIKeyAuth(
+        api_key="sk-test",
+        user_id="ui-session-user",
+        team_id=UI_TEAM_ID,
+        models=[],
+        team_models=[],
+    )
+    request = Request(scope={"type": "http"})
+    request._url = URL(url="/user/info")
+    request._body = b"{}"
+
+    received_team_objects: list[LiteLLM_TeamTableCachedObj | None] = []
+
+    async def _capturing_common_checks(*_args, **kwargs) -> bool:
+        received_team_objects.append(kwargs.get("team_object"))
+        return True
+
+    attrs = _proxy_attrs_for_centralized_checks(user_custom_auth=None)
+    originals = {a: getattr(_proxy_server_mod, a, None) for a in attrs}
+    try:
+        for k, v in attrs.items():
+            setattr(_proxy_server_mod, k, v)
+        with (
+            patch(
+                "litellm.proxy.auth.user_api_key_auth.get_team_object",
+                new_callable=AsyncMock,
+                side_effect=TeamNotFoundError(team_id=UI_TEAM_ID),
+            ),
+            patch(
+                "litellm.proxy.auth.user_api_key_auth.common_checks",
+                _capturing_common_checks,
+            ),
+        ):
+            await _run_centralized_common_checks(
+                user_api_key_auth_obj=token,
+                request=request,
+                request_data={},
+                route="/user/info",
+            )
+        assert len(received_team_objects) == 1
+        received_team_object = received_team_objects[0]
+        assert received_team_object is not None
+        assert received_team_object.team_id == UI_TEAM_ID
+    finally:
+        for k, v in originals.items():
+            setattr(_proxy_server_mod, k, v)
+
+
 @pytest.mark.asyncio
 async def test_centralized_common_checks_user_http_exception_isolates_to_user_only():
     """Per-fetch isolation, mirror of the team case: an HTTPException

From a44bb47563cdb6560aacb296a5de250271ec5bda Mon Sep 17 00:00:00 2001
From: Yassin Kortam <yassin@berri.ai>
Date: Sat, 22 Aug 2026 14:25:55 -0700
Subject: [PATCH 42/93] fix(prometheus): fold auth/pre-call time into
 litellm_request_total_latency_metric (#37958)

litellm_request_total_latency_metric's start_time is set inside
common_processing_pre_call_logic, which only runs after user_api_key_auth
has already succeeded, so the metric silently excluded authentication and
pre-call setup time despite being documented as total request latency. The
sibling litellm_request_queue_time_seconds metric had the same problem:
its arrival_time was captured after auth too, despite its own comment
claiming to track when the request arrived at the proxy.

request.state.litellm_received_at is now stamped unconditionally at the
very first line of user_api_key_auth (previously only when OTEL was
configured), giving a timestamp that precedes all auth work. Both metrics
now derive from it: queue_time_seconds genuinely spans arrival through the
start of pre-call processing, and the total-latency metric adds that
queue time on top of its existing start/end window so it becomes true
end-to-end latency.

queue_time_seconds ends exactly at start_time rather than a separately
captured timestamp, so its window and the total-latency window share a
boundary instead of overlapping and double-counting a few lines of setup
work on every request.
---
 litellm/integrations/prometheus.py            |  27 +++-
 litellm/proxy/auth/user_api_key_auth.py       |  27 +++-
 litellm/proxy/common_request_processing.py    |  11 +-
 litellm/proxy/litellm_pre_call_utils.py       |  16 ++-
 ...test_prometheus_queue_guardrail_metrics.py | 131 ++++++++++++++++++
 .../proxy/auth/test_user_api_key_auth.py      |  41 ++++++
 .../proxy/test_common_request_processing.py   |  20 ++-
 .../proxy/test_litellm_pre_call_utils.py      |  73 +++++++++-
 8 files changed, 321 insertions(+), 25 deletions(-)

diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py
index 76066f4a305..f9195db1d67 100644
--- a/litellm/integrations/prometheus.py
+++ b/litellm/integrations/prometheus.py
@@ -215,7 +215,9 @@ class PrometheusLogger(CustomLogger):
             # request latency metrics
             self.litellm_request_total_latency_metric = self._histogram_factory(
                 "litellm_request_total_latency_metric",
-                "Total latency (seconds) for a request to LiteLLM",
+                "End-to-end latency (seconds) for a request to LiteLLM Proxy Server, from the moment "
+                "the request reached the proxy through the end of processing -- includes "
+                "authentication, pre-call hooks, the LLM API call, and post-call processing",
                 labelnames=self.get_labels_for_metric("litellm_request_total_latency_metric"),
                 buckets=self.latency_buckets,
             )
@@ -458,7 +460,8 @@ class PrometheusLogger(CustomLogger):
             # Request queue time metric
             self.litellm_request_queue_time_metric = self._histogram_factory(
                 "litellm_request_queue_time_seconds",
-                "Time spent in request queue before processing starts (seconds)",
+                "Time (seconds) from request arrival at the proxy to the start of pre-call "
+                "processing -- includes authentication and any ASGI-level queueing",
                 labelnames=self.get_labels_for_metric("litellm_request_queue_time_seconds"),
                 buckets=self.latency_buckets,
             )
@@ -2078,27 +2081,37 @@ class PrometheusLogger(CustomLogger):
                 _labels,
             )
 
-        # total request latency
+        # request queue time (time from arrival to processing start) -- read first so
+        # it can be folded into the total-latency metric below. start_time/end_time
+        # only span from after auth completes, so without this the "total" latency
+        # metric silently excludes auth and pre-call hook time.
+        _litellm_params: Final = kwargs.get("litellm_params", {}) or {}
+        queue_time_seconds: Final = (_litellm_params.get("metadata") or {}).get("queue_time_seconds")
+
+        # total request latency: true end-to-end, from request arrival (queue_time_seconds,
+        # when available) through the end of processing.
         total_time_seconds: Final = self._safe_duration_seconds(
             start_time=start_time,
             end_time=end_time,
         )
         if total_time_seconds is not None:
+            _observed_total_time_seconds: Final = (
+                total_time_seconds + queue_time_seconds
+                if queue_time_seconds is not None and queue_time_seconds >= 0
+                else total_time_seconds
+            )
             _labels = prometheus_label_factory(
                 supported_enum_labels=self.get_labels_for_metric(metric_name="litellm_request_total_latency_metric"),
                 enum_values=enum_values,
                 label_context=label_context,
             )
-            self.litellm_request_total_latency_metric.labels(**_labels).observe(total_time_seconds)
+            self.litellm_request_total_latency_metric.labels(**_labels).observe(_observed_total_time_seconds)
             self._track_end_user_metric_series(
                 self.litellm_request_total_latency_metric,
                 "litellm_request_total_latency_metric",
                 _labels,
             )
 
-        # request queue time (time from arrival to processing start)
-        _litellm_params: Final = kwargs.get("litellm_params", {}) or {}
-        queue_time_seconds: Final = (_litellm_params.get("metadata") or {}).get("queue_time_seconds")
         if queue_time_seconds is not None and queue_time_seconds >= 0:
             _labels = prometheus_label_factory(
                 supported_enum_labels=self.get_labels_for_metric(metric_name="litellm_request_queue_time_seconds"),
diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py
index 84e60eb0dd8..658d176f6a7 100644
--- a/litellm/proxy/auth/user_api_key_auth.py
+++ b/litellm/proxy/auth/user_api_key_auth.py
@@ -1069,6 +1069,26 @@ async def _resolve_jwt_to_virtual_key(
     return None
 
 
+def _ensure_litellm_received_at_on_request_state(request: Request) -> datetime:
+    """Idempotently stamp ``request.state.litellm_received_at`` with the moment
+    litellm's own code started handling this request -- the first line of
+    ``user_api_key_auth``, before any auth/pre-call work runs. This is the
+    basis for the request-latency Prometheus metrics (see
+    ``litellm/integrations/prometheus.py``), and unlike the OTEL SERVER span
+    below, it is set unconditionally so those metrics don't depend on OTEL
+    being configured.
+    """
+    existing_received_at: Final[datetime | None] = getattr(request.state, "litellm_received_at", None)
+    if existing_received_at is not None:
+        return existing_received_at
+    received_at: Final = datetime.now(timezone.utc)
+    try:
+        request.state.litellm_received_at = received_at
+    except Exception:
+        pass
+    return received_at
+
+
 def _ensure_parent_otel_span_on_request_state(request: Request) -> None:
     """Idempotently create the OTEL SERVER span and stash it on
     ``request.state.parent_otel_span``. Safe to call multiple times.
@@ -1079,15 +1099,12 @@ def _ensure_parent_otel_span_on_request_state(request: Request) -> None:
     """
     from litellm.proxy.proxy_server import open_telemetry_logger
 
+    start_time: Final = _ensure_litellm_received_at_on_request_state(request)
+
     if open_telemetry_logger is None:
         return
     if getattr(request.state, "parent_otel_span", None) is not None:
         return
-    start_time: Final = datetime.now(timezone.utc)
-    try:
-        request.state.litellm_received_at = start_time
-    except Exception:
-        pass
     parent_otel_span: Final = open_telemetry_logger.create_litellm_proxy_request_started_span(
         start_time=start_time,
         headers=_safe_get_request_headers(request),
diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py
index 5f205df487d..dbbf9cb673e 100644
--- a/litellm/proxy/common_request_processing.py
+++ b/litellm/proxy/common_request_processing.py
@@ -3,7 +3,6 @@ import contextlib
 import json
 import logging
 import math
-import time
 import traceback
 from collections.abc import AsyncGenerator, Awaitable, Callable, Mapping
 from datetime import datetime
@@ -1726,13 +1725,17 @@ class ProxyBaseLLMRequestProcessing:
             )
 
         # Calculate request queue time after add_litellm_data_to_request
-        # which sets arrival_time in proxy_server_request
+        # which sets arrival_time in proxy_server_request. Ends at start_time
+        # (not a freshly captured time.time() here) so this window is exactly
+        # [arrival_time, start_time], with zero overlap with the
+        # litellm_request_total_latency_metric window of [start_time, end_time] --
+        # otherwise the few lines of add_litellm_data_to_request's own work would
+        # be double-counted across both metrics.
         proxy_server_request: Final = self.data.get("proxy_server_request", {})
         arrival_time: Final = proxy_server_request.get("arrival_time")
         queue_time_seconds = None
         if arrival_time is not None:
-            processing_start_time: Final = time.time()
-            queue_time_seconds = processing_start_time - arrival_time
+            queue_time_seconds = start_time.timestamp() - arrival_time
 
         # Store queue time in metadata after add_litellm_data_to_request to ensure it's preserved
         if queue_time_seconds is not None:
diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py
index 4525adb82f3..4794da05a3e 100644
--- a/litellm/proxy/litellm_pre_call_utils.py
+++ b/litellm/proxy/litellm_pre_call_utils.py
@@ -1744,11 +1744,17 @@ async def add_litellm_data_to_request(
     # Init - Proxy Server Request
     # we do this as soon as entering so we track the original request
     ##########################################################
-    # Track arrival time for queue time metric. The body snapshot is filled
-    # in after the admin-injection strip below so the audit / spend-tracking
-    # consumers of proxy_server_request["body"] see the cleaned metadata
-    # rather than attacker-forged user_api_key_* fields.
-    arrival_time: Final = time.time()
+    # Track arrival time for queue time metric. Prefer the timestamp stamped at
+    # the top of user_api_key_auth (request.state.litellm_received_at): by the
+    # time this function runs, auth has already completed, so time.time() here
+    # would silently exclude the entire auth phase from the queue-time window.
+    # Falls back to time.time() for callers that never went through
+    # user_api_key_auth. The body snapshot is filled in after the
+    # admin-injection strip below so the audit / spend-tracking consumers of
+    # proxy_server_request["body"] see the cleaned metadata rather than
+    # attacker-forged user_api_key_* fields.
+    _litellm_received_at: Final = getattr(request.state, "litellm_received_at", None)
+    arrival_time: Final = _litellm_received_at.timestamp() if _litellm_received_at is not None else time.time()
     data["proxy_server_request"] = {
         "url": str(request.url),
         "method": request.method,
diff --git a/tests/test_litellm/integrations/test_prometheus_queue_guardrail_metrics.py b/tests/test_litellm/integrations/test_prometheus_queue_guardrail_metrics.py
index 85be9e32121..f04e8d0d2c7 100644
--- a/tests/test_litellm/integrations/test_prometheus_queue_guardrail_metrics.py
+++ b/tests/test_litellm/integrations/test_prometheus_queue_guardrail_metrics.py
@@ -229,6 +229,137 @@ class TestPrometheusQueueTimeMetric:
         ), "Queue time metric should not be recorded for negative values"
 
 
+class TestPrometheusTotalLatencyMetric:
+    """litellm_request_total_latency_metric must be true end-to-end latency: start_time
+    (set after auth already completed, see LIT-6012) plus queue_time_seconds (the
+    auth + pre-call setup window queue_time_seconds itself covers), not start_time alone."""
+
+    @staticmethod
+    def _enum_values() -> UserAPIKeyLabelValues:
+        return UserAPIKeyLabelValues(
+            end_user=None,
+            hashed_api_key="test-key",
+            api_key_alias="test-alias",
+            requested_model="gpt-3.5-turbo",
+            model_group="gpt-3.5-turbo",
+            team=None,
+            team_alias=None,
+            user=None,
+            user_email=None,
+            status_code="200",
+            model="gpt-3.5-turbo",
+            litellm_model_name="gpt-3.5-turbo",
+            tags=[],
+            model_id="gpt-3.5-turbo",
+            api_base="https://api.openai.com",
+            api_provider="openai",
+            exception_status=None,
+            exception_class=None,
+            custom_metadata_labels={},
+            route=None,
+        )
+
+    def test_total_latency_includes_queue_time_when_present(self):
+        """The observed total-latency value must be (end_time - start_time) + queue_time_seconds,
+        so auth/pre-call time (queue_time_seconds) is not silently excluded from "total" latency."""
+        prometheus_logger = PrometheusLogger()
+
+        mock_metric = MagicMock()
+        mock_labeled_metric = MagicMock()
+        mock_metric.labels.return_value = mock_labeled_metric
+        prometheus_logger.litellm_request_total_latency_metric = mock_metric
+
+        start_time = datetime(2024, 1, 1, 0, 0, 0)
+        end_time = datetime(2024, 1, 1, 0, 0, 2)  # 2.0s of LLM-call/post-call time
+        queue_time_seconds = 0.5  # auth + pre-call setup time
+
+        kwargs = {
+            "litellm_params": {"metadata": {"queue_time_seconds": queue_time_seconds}},
+            "model": "gpt-3.5-turbo",
+            "start_time": start_time,
+            "end_time": end_time,
+        }
+
+        prometheus_logger._set_latency_metrics(
+            kwargs=kwargs,
+            model="gpt-3.5-turbo",
+            user_api_key="test-key",
+            user_api_key_alias="test-alias",
+            user_api_team=None,
+            user_api_team_alias=None,
+            enum_values=self._enum_values(),
+        )
+
+        observed_value = mock_labeled_metric.observe.call_args_list[0][0][0]
+        assert observed_value == pytest.approx(2.5)
+
+    def test_total_latency_falls_back_to_start_end_delta_without_queue_time(self):
+        """Without queue_time_seconds (e.g. a non-proxy caller), the metric must still
+        observe the plain end_time - start_time delta rather than erroring or dropping it."""
+        prometheus_logger = PrometheusLogger()
+
+        mock_metric = MagicMock()
+        mock_labeled_metric = MagicMock()
+        mock_metric.labels.return_value = mock_labeled_metric
+        prometheus_logger.litellm_request_total_latency_metric = mock_metric
+
+        start_time = datetime(2024, 1, 1, 0, 0, 0)
+        end_time = datetime(2024, 1, 1, 0, 0, 2)
+
+        kwargs = {
+            "litellm_params": {"metadata": {}},
+            "model": "gpt-3.5-turbo",
+            "start_time": start_time,
+            "end_time": end_time,
+        }
+
+        prometheus_logger._set_latency_metrics(
+            kwargs=kwargs,
+            model="gpt-3.5-turbo",
+            user_api_key="test-key",
+            user_api_key_alias="test-alias",
+            user_api_team=None,
+            user_api_team_alias=None,
+            enum_values=self._enum_values(),
+        )
+
+        observed_value = mock_labeled_metric.observe.call_args_list[0][0][0]
+        assert observed_value == pytest.approx(2.0)
+
+    def test_total_latency_ignores_negative_queue_time(self):
+        """A negative queue_time_seconds (clock skew / bad data) must not be added in --
+        matches the existing >= 0 guard on the standalone queue-time metric."""
+        prometheus_logger = PrometheusLogger()
+
+        mock_metric = MagicMock()
+        mock_labeled_metric = MagicMock()
+        mock_metric.labels.return_value = mock_labeled_metric
+        prometheus_logger.litellm_request_total_latency_metric = mock_metric
+
+        start_time = datetime(2024, 1, 1, 0, 0, 0)
+        end_time = datetime(2024, 1, 1, 0, 0, 2)
+
+        kwargs = {
+            "litellm_params": {"metadata": {"queue_time_seconds": -0.1}},
+            "model": "gpt-3.5-turbo",
+            "start_time": start_time,
+            "end_time": end_time,
+        }
+
+        prometheus_logger._set_latency_metrics(
+            kwargs=kwargs,
+            model="gpt-3.5-turbo",
+            user_api_key="test-key",
+            user_api_key_alias="test-alias",
+            user_api_team=None,
+            user_api_team_alias=None,
+            enum_values=self._enum_values(),
+        )
+
+        observed_value = mock_labeled_metric.observe.call_args_list[0][0][0]
+        assert observed_value == pytest.approx(2.0)
+
+
 class TestPrometheusGuardrailMetrics:
     """Test guardrail metrics recording"""
 
diff --git a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py
index 470a01cfaa3..6a117985820 100644
--- a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py
+++ b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py
@@ -29,6 +29,8 @@ from litellm.proxy.auth.auth_checks import get_key_object, _cache_key_object
 from litellm.proxy.auth.route_checks import RouteChecks
 from litellm.proxy.auth.user_api_key_auth import (
     _check_key_model_budget_with_fallback,
+    _ensure_litellm_received_at_on_request_state,
+    _ensure_parent_otel_span_on_request_state,
     _PendingAutoRegister,
     _matches_routing_override,
     _reserve_budget_after_common_checks,
@@ -6694,3 +6696,42 @@ async def test_unlicensed_jwt_auth_is_forbidden_not_unauthorized():
 
     assert error.code == "403"
     assert "enterprise" in error.message.lower()
+
+
+class TestLitellmReceivedAtStamping:
+    """request.state.litellm_received_at must be stamped unconditionally at the
+    top of auth (LIT-6012), so request-latency Prometheus metrics don't depend
+    on OTEL being configured to see a true request-arrival timestamp."""
+
+    def test_stamped_even_when_otel_is_not_configured(self, monkeypatch):
+        monkeypatch.setattr(
+            "litellm.proxy.proxy_server.open_telemetry_logger", None
+        )
+        request = MagicMock()
+        request.state = SimpleNamespace()
+
+        _ensure_parent_otel_span_on_request_state(request)
+
+        assert isinstance(request.state.litellm_received_at, datetime)
+
+    def test_helper_is_idempotent(self):
+        request = MagicMock()
+        request.state = SimpleNamespace()
+
+        first = _ensure_litellm_received_at_on_request_state(request)
+        second = _ensure_litellm_received_at_on_request_state(request)
+
+        assert first == second
+        assert request.state.litellm_received_at == first
+
+    def test_does_not_overwrite_an_earlier_stamp(self):
+        """Body-parse failures must not shorten the measured window: a value
+        already on request.state (stamped earlier) must win."""
+        request = MagicMock()
+        earlier = datetime(2020, 1, 1)
+        request.state = SimpleNamespace(litellm_received_at=earlier)
+
+        result = _ensure_litellm_received_at_on_request_state(request)
+
+        assert result == earlier
+        assert request.state.litellm_received_at == earlier
diff --git a/tests/test_litellm/proxy/test_common_request_processing.py b/tests/test_litellm/proxy/test_common_request_processing.py
index f9ba91a246e..58714a5e319 100644
--- a/tests/test_litellm/proxy/test_common_request_processing.py
+++ b/tests/test_litellm/proxy/test_common_request_processing.py
@@ -1392,11 +1392,25 @@ class TestProxyBaseLLMRequestProcessing:
             route_type=route_type,
         )
 
-        # Verify queue_time_seconds is set and non-negative
+        # Verify queue_time_seconds is set and non-negative. Ends at start_time
+        # (captured before this mock runs, so it can precede the mock's own
+        # time.time() by a handful of microseconds) rather than a freshly
+        # captured time.time(), so a tiny tolerance below 0.5 is expected and
+        # correct -- see LIT-6012.
         metadata = returned_data.get("metadata", {})
         assert "queue_time_seconds" in metadata, "queue_time_seconds should be set in metadata"
-        assert metadata["queue_time_seconds"] >= 0.5, (
-            f"queue_time_seconds should be at least 0.5, got {metadata['queue_time_seconds']}"
+        assert metadata["queue_time_seconds"] >= 0.49, (
+            f"queue_time_seconds should be at least ~0.5, got {metadata['queue_time_seconds']}"
+        )
+
+        # queue_time_seconds must end exactly where logging_obj.start_time begins
+        # (the same start_time litellm_request_total_latency_metric's window
+        # starts from) so the two windows share a boundary, not an overlap.
+        # A mutant that reintroduces a separately-captured processing_start_time
+        # would make this assertion fail.
+        arrival_time = returned_data["proxy_server_request"]["arrival_time"]
+        assert arrival_time + metadata["queue_time_seconds"] == pytest.approx(
+            logging_obj.start_time.timestamp(), abs=1e-6
         )
 
 
diff --git a/tests/test_litellm/proxy/test_litellm_pre_call_utils.py b/tests/test_litellm/proxy/test_litellm_pre_call_utils.py
index 501b03eae0f..81a97a70efa 100644
--- a/tests/test_litellm/proxy/test_litellm_pre_call_utils.py
+++ b/tests/test_litellm/proxy/test_litellm_pre_call_utils.py
@@ -2,6 +2,9 @@ import asyncio
 import copy
 import json
 import os
+import time
+from datetime import datetime, timezone
+from types import SimpleNamespace
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
@@ -268,6 +271,75 @@ async def test_stamped_auth_object_reflects_header_derived_identity():
     assert stamped.end_user_id == "end-user-from-header"
 
 
+@pytest.mark.asyncio
+async def test_arrival_time_prefers_litellm_received_at_over_time_time():
+    """LIT-6012: by the time this function runs, auth has already completed, so
+    time.time() here would silently exclude the whole auth phase from the
+    queue-time window. request.state.litellm_received_at (stamped at the top of
+    user_api_key_auth, before auth work) must win when present."""
+    from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request
+
+    request_mock = MagicMock(spec=Request)
+    request_mock.url = MagicMock()
+    request_mock.url.path = "/v1/chat/completions"
+    request_mock.url.__str__.return_value = "http://localhost/v1/chat/completions"
+    request_mock.method = "POST"
+    request_mock.query_params = {}
+    request_mock.headers = {"Content-Type": "application/json"}
+    request_mock.client = MagicMock()
+    request_mock.client.host = "127.0.0.1"
+    received_at = datetime(2024, 1, 1, tzinfo=timezone.utc)
+    request_mock.state = SimpleNamespace(litellm_received_at=received_at)
+
+    user_api_key_dict = UserAPIKeyAuth(api_key="hashed-key", metadata={}, team_metadata={})
+
+    updated_data = await add_litellm_data_to_request(
+        data={"model": "gpt-3.5-turbo"},
+        request=request_mock,
+        user_api_key_dict=user_api_key_dict,
+        proxy_config=MagicMock(),
+        general_settings={},
+        version="test-version",
+    )
+
+    assert updated_data["proxy_server_request"]["arrival_time"] == received_at.timestamp()
+
+
+@pytest.mark.asyncio
+async def test_arrival_time_falls_back_to_time_time_without_litellm_received_at():
+    """Callers that never went through user_api_key_auth (no stamp on request.state)
+    must still get a usable arrival_time instead of erroring."""
+    from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request
+
+    request_mock = MagicMock(spec=Request)
+    request_mock.url = MagicMock()
+    request_mock.url.path = "/v1/chat/completions"
+    request_mock.url.__str__.return_value = "http://localhost/v1/chat/completions"
+    request_mock.method = "POST"
+    request_mock.query_params = {}
+    request_mock.headers = {"Content-Type": "application/json"}
+    request_mock.client = MagicMock()
+    request_mock.client.host = "127.0.0.1"
+    request_mock.state = SimpleNamespace()  # no litellm_received_at attribute
+
+    user_api_key_dict = UserAPIKeyAuth(api_key="hashed-key", metadata={}, team_metadata={})
+
+    before = time.time()
+    updated_data = await add_litellm_data_to_request(
+        data={"model": "gpt-3.5-turbo"},
+        request=request_mock,
+        user_api_key_dict=user_api_key_dict,
+        proxy_config=MagicMock(),
+        general_settings={},
+        version="test-version",
+    )
+    after = time.time()
+
+    arrival_time = updated_data["proxy_server_request"]["arrival_time"]
+    assert isinstance(arrival_time, float)
+    assert before <= arrival_time <= after
+
+
 @pytest.mark.asyncio
 async def test_add_litellm_data_to_request_strips_admin_injection_slots():
     """User-supplied user_api_key_metadata / user_api_key_team_metadata /
@@ -2786,7 +2858,6 @@ def test_add_headers_to_llm_call_by_model_group_existing_headers_in_data():
         litellm.model_group_settings = original_model_group_settings
 
 
-import time
 from typing import Optional
 
 from fastapi.responses import Response

From 32bf1aba2958a8601d78ba7f86eb97d58a1adf85 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 14:27:20 -0700
Subject: [PATCH 43/93] fix(anthropic): stop signing replayed thinking blocks
 and strip reasoning_content

A reasoning item id is not an Anthropic signature. Passing it off as one got the
block replayed to Anthropic and Bedrock as if it were real, and every backend that
verifies signatures rejected the turn. Thinking blocks now come back unsigned, and
the streaming path no longer emits a signature_delta for them.

Azure AI Foundry, Fireworks, and vLLM reject unknown message fields, so they now
strip reasoning_content alongside thinking_blocks the way Mistral already did.

The thinking-block helpers take ChatCompletionThinkingBlock and
ChatCompletionRedactedThinkingBlock instead of loose mappings.
---
 .../transformation.py                         |  8 +--
 .../prompt_templates/common_utils.py          | 34 ++++++++-----
 .../responses_adapters/streaming_iterator.py  | 11 ----
 .../responses_adapters/transformation.py      | 25 ++++++----
 litellm/llms/azure_ai/chat/transformation.py  | 10 +++-
 .../llms/fireworks_ai/chat/transformation.py  |  1 +
 .../llms/hosted_vllm/chat/transformation.py   |  5 +-
 ...t_responses_adapters_streaming_iterator.py | 10 +---
 .../test_responses_adapters_transformation.py | 50 +++++++++++++------
 .../chat/test_azure_ai_transformation.py      |  2 +
 .../test_fireworks_ai_chat_transformation.py  |  2 +
 .../test_hosted_vllm_chat_transformation.py   |  2 +
 12 files changed, 96 insertions(+), 64 deletions(-)

diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py
index ea54bd83e12..3e55c3c637e 100644
--- a/litellm/completion_extras/litellm_responses_transformation/transformation.py
+++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py
@@ -97,10 +97,10 @@ def _reasoning_input_items(msg: "AllMessageValues") -> list[dict[str, object]]:
     stored: Final = [_reasoning_item_to_response_input(r_item) for r_item in _get_reasoning_items(msg)]
     if stored:
         return stored
-    from_thinking: Final = responses_reasoning_item_from_thinking_blocks(
-        cast(Iterable[Mapping[str, Any]], msg.get("thinking_blocks") or ())  # cast-ok: untyped client thinking blocks
-    )
-    return [from_thinking] if from_thinking is not None else []
+    raw_blocks: Final = msg.get("thinking_blocks") or ()
+    blocks: Final = cast("Iterable[ChatCompletionThinkingBlock]", raw_blocks)  # cast-ok: untyped client json
+    from_thinking: Final = responses_reasoning_item_from_thinking_blocks(blocks)
+    return [] if from_thinking is None else [dict(from_thinking)]
 
 
 def _build_reasoning_item(
diff --git a/litellm/litellm_core_utils/prompt_templates/common_utils.py b/litellm/litellm_core_utils/prompt_templates/common_utils.py
index 4211fbe610a..e0ba2e13c6e 100644
--- a/litellm/litellm_core_utils/prompt_templates/common_utils.py
+++ b/litellm/litellm_core_utils/prompt_templates/common_utils.py
@@ -28,8 +28,12 @@ from litellm.types.llms.openai import (
     ChatCompletionAssistantMessage,
     ChatCompletionFileObject,
     ChatCompletionImageObject,
+    ChatCompletionReasoningItem,
+    ChatCompletionReasoningSummaryTextBlock,
+    ChatCompletionRedactedThinkingBlock,
     ChatCompletionResponseMessage,
     ChatCompletionTextObject,
+    ChatCompletionThinkingBlock,
     ChatCompletionToolParam,
     ChatCompletionUserMessage,
 )
@@ -1549,36 +1553,42 @@ def _extract_reasoning_content(message: dict) -> tuple[str | None, str | None]:
     return None, message_content
 
 
+def _readable_thinking_text(
+    block: ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock,
+) -> str:
+    """The text a chat model can read back, empty for redacted blocks and malformed ones."""
+    if block.get("type") != "thinking":
+        return ""
+    thinking: Final = cast(ChatCompletionThinkingBlock, block).get("thinking")  # cast-ok: narrowed by the type tag
+    return str(thinking or "")
+
+
 def reasoning_content_from_thinking_blocks(
-    thinking_blocks: Iterable[Mapping[str, Any]],
+    thinking_blocks: Iterable[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock],
 ) -> str:
     """Flatten Anthropic thinking blocks into the `reasoning_content` string chat models expect.
 
     Redacted blocks carry no readable text, so they contribute nothing.
     """
-    return "\n".join(
-        text
-        for block in thinking_blocks
-        if block.get("type") == "thinking" and (text := str(block.get("thinking") or ""))
-    )
+    return "\n".join(text for block in thinking_blocks if (text := _readable_thinking_text(block)))
 
 
 def responses_reasoning_item_from_thinking_blocks(
-    thinking_blocks: Iterable[Mapping[str, Any]],
-) -> dict[str, Any] | None:  # mutable-ok: API message payload
+    thinking_blocks: Iterable[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock],
+) -> ChatCompletionReasoningItem | None:
     """Build a Responses API `reasoning` input item from Anthropic thinking blocks.
 
     The item carries no `id`: the Responses API rejects an empty one and 404s on any id it
     did not mint itself, while an item without an id is always accepted.
     """
-    summary: Final[list[dict[str, Any]]] = [  # mutable-ok: API message payload
-        {"type": "summary_text", "text": text}  # mutable-ok: API message payload
+    summary: Final[list[ChatCompletionReasoningSummaryTextBlock]] = [  # mutable-ok: API message payload
+        ChatCompletionReasoningSummaryTextBlock(type="summary_text", text=text)
         for block in thinking_blocks
-        if block.get("type") == "thinking" and (text := str(block.get("thinking") or ""))
+        if (text := _readable_thinking_text(block))
     ]
     if not summary:
         return None
-    return {"type": "reasoning", "summary": summary}  # mutable-ok: API message payload
+    return ChatCompletionReasoningItem(type="reasoning", summary=summary)
 
 
 def _parse_content_for_reasoning(
diff --git a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py
index 286edb24b9b..5577d4a9c2d 100644
--- a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py
+++ b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py
@@ -189,17 +189,6 @@ class AnthropicResponsesStreamWrapper:
             block_idx = self._item_id_to_block_index.get(item_id, -1) if item_id else self._current_block_index
             if block_idx < 0:
                 return
-            done_item_type: Final = (
-                getattr(item, "type", None) or (item.get("type") if isinstance(item, dict) else None) if item else None
-            )
-            if done_item_type == "reasoning" and item_id:
-                self._chunk_queue.append(
-                    {
-                        "type": "content_block_delta",
-                        "index": block_idx,
-                        "delta": {"type": "signature_delta", "signature": item_id},
-                    }
-                )
             self._chunk_queue.append(
                 {
                     "type": "content_block_stop",
diff --git a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
index b1061f86d0b..1a6b0498a52 100644
--- a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
@@ -38,7 +38,11 @@ from litellm.types.llms.anthropic_messages.anthropic_response import (
     AnthropicMessagesResponse,
     AnthropicUsage,
 )
-from litellm.types.llms.openai import ResponseAPIUsage, ResponsesAPIResponse
+from litellm.types.llms.openai import (
+    ChatCompletionThinkingBlock,
+    ResponseAPIUsage,
+    ResponsesAPIResponse,
+)
 
 
 class LiteLLMAnthropicToResponsesAPIAdapter:
@@ -112,19 +116,18 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
     @classmethod
     def _thinking_blocks_from_reasoning_item(
         cls,
-        item_id: str | None,
         summary: Iterable[object],
     ) -> tuple[dict[str, Any], ...]:  # mutable-ok: API message payload
         """Anthropic thinking blocks for one Responses reasoning item.
 
-        The reasoning item id rides along as the signature so that a follow-up turn can
-        regroup the summary parts into the single reasoning item they came from.
+        The signature stays empty: only Anthropic can sign a thinking block, and a stand-in
+        value would be replayed as a real one and rejected by every backend that verifies it.
         """
         return tuple(
             AnthropicResponseContentBlockThinking(
                 type="thinking",
                 thinking=text,
-                signature=item_id or None,
+                signature=None,
             ).model_dump()
             for part in summary
             if (text := cls._summary_part_text(part))
@@ -132,10 +135,9 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
 
     @staticmethod
     def _assistant_block_group_key(indexed_block: tuple[int, Mapping[str, Any]]) -> str:
-        """Group consecutive thinking blocks sharing a signature; keep every other block alone."""
+        """Group a run of consecutive thinking blocks together; keep every other block alone."""
         index, block = indexed_block
-        signature: Final = block.get("signature") or ""
-        return f"thinking:{signature}" if block.get("type") == "thinking" else f"block:{index}"
+        return "thinking" if block.get("type") == "thinking" else f"block:{index}"
 
     @classmethod
     def _assistant_group_to_input_item(
@@ -144,7 +146,9 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
         first: Final = group[0]
         btype: Final = first.get("type")
         if btype == "thinking":
-            return responses_reasoning_item_from_thinking_blocks(group)
+            blocks: Final = cast(tuple[ChatCompletionThinkingBlock, ...], group)  # cast-ok: untrusted client payload
+            reasoning_item: Final = responses_reasoning_item_from_thinking_blocks(blocks)
+            return None if reasoning_item is None else dict(reasoning_item)
         if btype == "tool_use":
             return {  # mutable-ok: API message payload
                 "type": "function_call",
@@ -559,7 +563,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
 
         for item in response.output:
             if isinstance(item, ResponseReasoningItem):
-                content.extend(self._thinking_blocks_from_reasoning_item(item.id, item.summary))
+                content.extend(self._thinking_blocks_from_reasoning_item(item.summary))
 
             elif isinstance(item, ResponseOutputMessage):
                 for part in item.content:
@@ -594,7 +598,6 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
                 elif item_type == "reasoning":
                     content.extend(
                         self._thinking_blocks_from_reasoning_item(
-                            item.get("id"),
                             cast(Iterable[object], item.get("summary") or ()),  # cast-ok: untyped provider json
                         )
                     )
diff --git a/litellm/llms/azure_ai/chat/transformation.py b/litellm/llms/azure_ai/chat/transformation.py
index bc8ea31ea8c..9e7161120cc 100644
--- a/litellm/llms/azure_ai/chat/transformation.py
+++ b/litellm/llms/azure_ai/chat/transformation.py
@@ -30,7 +30,12 @@ class AzureFoundryErrorStrings(str, enum.Enum):
     SET_EXTRA_PARAMETERS_TO_PASS_THROUGH = "Set extra-parameters to 'pass-through'"
 
 
-NON_OPENAI_SPEC_MESSAGE_FIELDS: Final = ("thinking_blocks", "provider_specific_fields", "cache_control")
+NON_OPENAI_SPEC_MESSAGE_FIELDS: Final = (
+    "thinking_blocks",
+    "reasoning_content",
+    "provider_specific_fields",
+    "cache_control",
+)
 
 
 class AzureAIStudioConfig(OpenAIConfig):
@@ -173,7 +178,8 @@ class AzureAIStudioConfig(OpenAIConfig):
         """
         - Azure AI Studio doesn't support content as a list. This handles:
             1. Strips message fields that are not part of the OpenAI chat-completions
-               schema (thinking_blocks, provider_specific_fields, cache_control).
+               schema (thinking_blocks, reasoning_content, provider_specific_fields,
+               cache_control).
                Azure AI Foundry backends set additionalProperties=false and reject
                these with "Extra inputs are not permitted", which breaks multi-turn
                Anthropic-format clients that echo thinking blocks back as history.
diff --git a/litellm/llms/fireworks_ai/chat/transformation.py b/litellm/llms/fireworks_ai/chat/transformation.py
index e64237da978..4e9731ef485 100644
--- a/litellm/llms/fireworks_ai/chat/transformation.py
+++ b/litellm/llms/fireworks_ai/chat/transformation.py
@@ -504,6 +504,7 @@ class FireworksAIConfig(FireworksAIMixin, OpenAIGPTConfig):
                 m = cast(dict, message)
                 m.pop("provider_specific_fields", None)
                 m.pop("thinking_blocks", None)
+                m.pop("reasoning_content", None)
 
         return messages
 
diff --git a/litellm/llms/hosted_vllm/chat/transformation.py b/litellm/llms/hosted_vllm/chat/transformation.py
index 46a2320b655..29dc485732f 100644
--- a/litellm/llms/hosted_vllm/chat/transformation.py
+++ b/litellm/llms/hosted_vllm/chat/transformation.py
@@ -164,12 +164,13 @@ class HostedVLLMChatConfig(OpenAIGPTConfig):
         """
         Support translating:
         - video files from file_id or file_data to video_url
-        - thinking_blocks on assistant messages are removed, and content lists
-          are converted to strings for vLLM compatibility
+        - thinking_blocks and reasoning_content on assistant messages are removed,
+          and content lists are converted to strings for vLLM compatibility
         """
         for message in messages:
             if message["role"] == "assistant":
                 message.pop("thinking_blocks", None)
+                message.pop("reasoning_content", None)
                 existing_content = message.get("content")
                 if isinstance(existing_content, list):
                     text_parts = []
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_streaming_iterator.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_streaming_iterator.py
index 12a6ab4324f..aebbed88c70 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_streaming_iterator.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_streaming_iterator.py
@@ -139,7 +139,6 @@ class TestReasoningItemWithoutSummaryText:
             ("content_block_start", 0),
             ("content_block_delta", 0),
             ("content_block_delta", 0),
-            ("content_block_delta", 0),
             ("content_block_stop", 0),
             ("content_block_start", 1),
             ("content_block_delta", 1),
@@ -148,15 +147,10 @@ class TestReasoningItemWithoutSummaryText:
         assert chunks[1]["content_block"] == {"type": "thinking", "thinking": "", "signature": ""}
         assert "".join(c["delta"]["thinking"] for c in chunks[2:4]) == "Weighing options"
 
-    def test_reasoning_item_id_is_streamed_as_the_thinking_signature(self):
+    def test_the_reasoning_item_id_is_never_streamed_as_a_signature(self):
+        """A stand-in signature would be replayed as a real one, so none is ever sent."""
         chunks = _drain_async(self._gpt_turn(reasoning_summary_deltas=["Weighing options"]))
 
-        signature_deltas = [c for c in chunks if c.get("delta", {}).get("type") == "signature_delta"]
-        assert [(c["index"], c["delta"]["signature"]) for c in signature_deltas] == [(0, "rs_1")]
-
-    def test_no_signature_delta_without_a_thinking_block(self):
-        chunks = _drain_async(self._gpt_turn(reasoning_summary_deltas=[]))
-
         assert not [c for c in chunks if c.get("delta", {}).get("type") == "signature_delta"]
 
 
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py
index 6479c43ee7a..790bcd269e0 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py
@@ -513,15 +513,14 @@ class TestTranslateMessagesToResponsesInput:
         result = _translate_messages(messages)
         assert "id" not in result[0]
 
-    def test_thinking_blocks_sharing_a_signature_become_one_reasoning_item(self):
-        """Summary parts of one upstream reasoning item are regrouped by their signature."""
+    def test_consecutive_thinking_blocks_become_one_reasoning_item(self):
+        """Summary parts of one upstream reasoning item are regrouped into that item."""
         messages = [
             {
                 "role": "assistant",
                 "content": [
-                    {"type": "thinking", "thinking": "First part.", "signature": "rs_abc123"},
-                    {"type": "thinking", "thinking": "Second part.", "signature": "rs_abc123"},
-                    {"type": "thinking", "thinking": "A later item.", "signature": "rs_def456"},
+                    {"type": "thinking", "thinking": "First part."},
+                    {"type": "thinking", "thinking": "Second part."},
                 ],
             }
         ]
@@ -533,13 +532,26 @@ class TestTranslateMessagesToResponsesInput:
                     {"type": "summary_text", "text": "First part."},
                     {"type": "summary_text", "text": "Second part."},
                 ],
-            },
-            {
-                "type": "reasoning",
-                "summary": [{"type": "summary_text", "text": "A later item."}],
-            },
+            }
         ]
 
+    def test_a_tool_call_splits_the_reasoning_items_around_it(self):
+        """Thinking on either side of a tool call belongs to two different reasoning items."""
+        messages = [
+            {
+                "role": "assistant",
+                "content": [
+                    {"type": "thinking", "thinking": "Before the call."},
+                    {"type": "tool_use", "id": "call_1", "name": "get_weather", "input": {"city": "Denver"}},
+                    {"type": "thinking", "thinking": "After the call."},
+                ],
+            }
+        ]
+        result = _translate_messages(messages)
+        assert [item["type"] for item in result] == ["reasoning", "function_call", "reasoning"]
+        assert result[0]["summary"] == [{"type": "summary_text", "text": "Before the call."}]
+        assert result[2]["summary"] == [{"type": "summary_text", "text": "After the call."}]
+
     def test_thinking_and_text_stay_separate(self):
         """The visible answer stays the only thing in the assistant message."""
         messages = [
@@ -1237,12 +1249,12 @@ class TestTranslateResponse:
         result: Any = _ADAPTER.translate_response(response)
         assert result["content"] == []
 
-    def test_reasoning_item_id_becomes_thinking_signature(self):
-        """The reasoning item id rides back as the signature so the next turn can regroup it."""
+    def test_reasoning_item_id_never_becomes_a_thinking_signature(self):
+        """Only Anthropic can sign a thinking block, so a stand-in signature is never invented."""
         reasoning = _make_reasoning_item(["Part one.", "Part two."], item_id="rs_abc123")
         response = _make_mock_response(output=[reasoning])
         result: Any = _ADAPTER.translate_response(response)
-        assert [block["signature"] for block in result["content"]] == ["rs_abc123", "rs_abc123"]
+        assert [block["signature"] for block in result["content"]] == [None, None]
 
     def test_dict_reasoning_item_becomes_thinking_block(self):
         """A reasoning item arriving as a plain dict is kept, not dropped."""
@@ -1257,9 +1269,19 @@ class TestTranslateResponse:
         )
         result: Any = _ADAPTER.translate_response(response)
         assert result["content"] == [
-            {"type": "thinking", "thinking": "Weighing the options.", "signature": "rs_dict_1"}
+            {"type": "thinking", "thinking": "Weighing the options.", "signature": None}
         ]
 
+    def test_thinking_blocks_are_dropped_when_replayed_to_anthropic(self):
+        """Replaying this turn to an Anthropic model must not send a signature it cannot verify."""
+        from litellm.litellm_core_utils.prompt_templates.factory import (
+            _drop_unsignable_thinking_blocks,
+        )
+
+        response = _make_mock_response(output=[_make_reasoning_item(["Part one."], item_id="rs_abc123")])
+        result: Any = _ADAPTER.translate_response(response)
+        assert _drop_unsignable_thinking_blocks(result["content"]) == []
+
     def test_usage_mapped_correctly(self):
         """Input/output tokens from ResponseAPIUsage are mapped to AnthropicUsage."""
         response = _make_mock_response(
diff --git a/tests/test_litellm/llms/azure_ai/chat/test_azure_ai_transformation.py b/tests/test_litellm/llms/azure_ai/chat/test_azure_ai_transformation.py
index 0fd9a381a5a..d4fcbc823a6 100644
--- a/tests/test_litellm/llms/azure_ai/chat/test_azure_ai_transformation.py
+++ b/tests/test_litellm/llms/azure_ai/chat/test_azure_ai_transformation.py
@@ -300,6 +300,7 @@ def test_azure_ai_strips_non_openai_spec_message_fields():
                     "cache_control": {"type": "ephemeral"},
                 }
             ],
+            "reasoning_content": "The user wants me to read a file.",
             "provider_specific_fields": {"thought_signature": "sig-top"},
             "tool_calls": [
                 {
@@ -327,6 +328,7 @@ def test_azure_ai_strips_non_openai_spec_message_fields():
     transformed_messages = request["messages"]
 
     assert not _find_key_anywhere(transformed_messages, "thinking_blocks")
+    assert not _find_key_anywhere(transformed_messages, "reasoning_content")
     assert not _find_key_anywhere(transformed_messages, "provider_specific_fields")
     assert not _find_key_anywhere(transformed_messages, "cache_control")
 
diff --git a/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py b/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py
index e728fc4bc40..63a749dab84 100644
--- a/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py
+++ b/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py
@@ -473,12 +473,14 @@ def test_transform_messages_helper_strips_thinking_blocks():
             "thinking_blocks": [
                 {"type": "thinking", "thinking": "internal", "signature": ""}
             ],
+            "reasoning_content": "internal",
         },
     ]
     out = config._transform_messages_helper(
         messages, model="accounts/fireworks/models/glm-5p1", litellm_params={}
     )
     assert "thinking_blocks" not in out[1]
+    assert "reasoning_content" not in out[1]
     assert out[1]["content"] == "I can help."
 
 
diff --git a/tests/test_litellm/llms/hosted_vllm/chat/test_hosted_vllm_chat_transformation.py b/tests/test_litellm/llms/hosted_vllm/chat/test_hosted_vllm_chat_transformation.py
index e316cd14dd4..82b05601a85 100644
--- a/tests/test_litellm/llms/hosted_vllm/chat/test_hosted_vllm_chat_transformation.py
+++ b/tests/test_litellm/llms/hosted_vllm/chat/test_hosted_vllm_chat_transformation.py
@@ -200,6 +200,7 @@ def test_hosted_vllm_thinking_blocks_prepended_to_assistant_content():
                     "signature": "abc123",
                 }
             ],
+            "reasoning_content": "Let me reason about this...",
         },
         {
             "role": "user",
@@ -218,6 +219,7 @@ def test_hosted_vllm_thinking_blocks_prepended_to_assistant_content():
     assert isinstance(assistant_msg["content"], str)
     assert assistant_msg["content"] == "Here is my answer."
     assert "thinking_blocks" not in assistant_msg
+    assert "reasoning_content" not in assistant_msg
 
 
 def test_hosted_vllm_thinking_blocks_with_list_content():

From 3d69ec3603147c53ba5ff1d5f275b6c5e6a32777 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 14:30:52 -0700
Subject: [PATCH 44/93] fix(responses-bridge): keep summary-only reasoning text
 scannable

A reasoning input item that carries only summary text is replayed to the
provider as reasoning_content, so inspection-only callers must see that
text too. They used to fall through to the generic content branch, which
reads content and drops a summary-only item, leaving guardrails and token
counters blind to text the model still receives.
---
 .../transformation.py                         | 23 ++++++++++++++---
 .../test_reasoning_input_item_preservation.py | 25 +++++++++++++++++++
 2 files changed, 45 insertions(+), 3 deletions(-)

diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index 165c2128d38..83e02888924 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -1200,14 +1200,31 @@ class LiteLLMCompletionResponsesConfig:
             return LiteLLMCompletionResponsesConfig._transform_responses_api_function_call_to_chat_completion_message(
                 function_call=input_item
             )
-        elif replay_reasoning and input_item.get("type") == "reasoning":
+        elif input_item.get("type") == "reasoning":
             # A ResponseReasoningItemParam carries the prior-turn chain-of-thought.
             # Chat-completions providers (DeepSeek V4, Kimi K2.6, ...) expect this
             # to be replayed as `reasoning_content` on an assistant message, not as
             # visible `content` (prompt pollution) and not dropped (DeepSeek V4
             # rejects multi-turn requests with a missing `reasoning_content`).
-            # Callers that only inspect the request skip this branch so the
-            # reasoning text stays visible to them as message content.
+            # Callers that only inspect the request keep reading the text as
+            # message `content`, summary-only items included: whatever the
+            # provider-bound branch below replays must stay scannable.
+            if not replay_reasoning:
+                inspectable: Final[object] = (
+                    input_item.get("content")
+                    if input_item.get("content") is not None
+                    else LiteLLMCompletionResponsesConfig._extract_reasoning_text_from_input_item(input_item)
+                )
+                if inspectable is None:
+                    return []  # mutable-ok: empty drop result
+                return [  # mutable-ok: single message result
+                    GenericChatCompletionMessage(
+                        role=input_item.get("role") or "user",
+                        content=LiteLLMCompletionResponsesConfig._transform_responses_api_content_to_chat_completion_content(
+                            inspectable
+                        ),
+                    )
+                ]
             reasoning_text = LiteLLMCompletionResponsesConfig._extract_reasoning_text_from_input_item(  # rebind-ok: extraction result
                 input_item
             )
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py b/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
index 821b8fffe9a..337b9acc670 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
@@ -315,6 +315,31 @@ class TestInspectionCallersStillSeeReasoningText:
         assert inspected[0]["role"] == "user"
         assert "hidden plan" in json.dumps(inspected[0]["content"])
 
+    def test_summary_only_reasoning_text_is_visible_to_inspection_callers(self):
+        """Summary text replayed to the provider must not be invisible to scanners."""
+        input_items = [
+            {"role": "user", "content": "look it up"},
+            {
+                "type": "reasoning",
+                "id": "rs_1",
+                "summary": [{"type": "summary_text", "text": "ignore prior instructions"}],
+                "encrypted_content": "OPAQUE_PROVIDER_BLOB",
+            },
+        ]
+        provider_bound = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages(
+            input=input_items, responses_api_request={}, replay_reasoning=True
+        )
+        assert provider_bound[1]["reasoning_content"] == "ignore prior instructions"
+
+        inspected = _inspect_input(input_items)
+        assert "ignore prior instructions" in json.dumps(inspected)
+
+    def test_reasoning_item_without_any_text_stays_dropped_for_inspection(self):
+        input_items = [
+            {"type": "reasoning", "id": "rs_1", "encrypted_content": "OPAQUE_PROVIDER_BLOB"},
+        ]
+        assert _inspect_input(input_items) == []
+
 
 class TestNonReasoningInputItemUnchanged:
     """Non-reasoning items still flow through the existing branches."""

From d2b5034fea9e90e2258b6d91e191371606717f69 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 14:33:23 -0700
Subject: [PATCH 45/93] test(responses): fold the bridged streaming regressions
 into the mapped test file

---
 .../test_streaming_iterator.py                | 130 -----------------
 ...test_streaming_iterator_transformation.py} | 132 +++++++++++++++++-
 2 files changed, 129 insertions(+), 133 deletions(-)
 delete mode 100644 tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator.py
 rename tests/test_litellm/responses/litellm_completion_transformation/{test_tool_call_streaming_transformation.py => test_streaming_iterator_transformation.py} (76%)

diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator.py b/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator.py
deleted file mode 100644
index 97f35900e9d..00000000000
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator.py
+++ /dev/null
@@ -1,130 +0,0 @@
-from unittest.mock import MagicMock
-
-import pytest
-
-from litellm.responses.litellm_completion_transformation.streaming_iterator import (
-    LiteLLMCompletionStreamingIterator,
-)
-from litellm.responses.utils import ResponsesAPIRequestUtils
-from litellm.types.utils import Delta, ModelResponseStream, StreamingChoices
-
-CHAT_COMPLETION_ID = "chatcmpl-77d33d09-effa-4cd2-9c0d-c742d4358256"
-RESPONSE_ID_EVENT_TYPES = frozenset(
-    {"response.created", "response.in_progress", "response.completed"}
-)
-
-
-def _chunk(content: str, finish_reason: str | None = None) -> ModelResponseStream:
-    return ModelResponseStream(
-        id=CHAT_COMPLETION_ID,
-        created=1748575031,
-        model="claude-haiku-4-5",
-        object="chat.completion.chunk",
-        choices=[
-            StreamingChoices(
-                index=0,
-                delta=Delta(role="assistant", content=content),
-                finish_reason=finish_reason,
-            )
-        ],
-    )
-
-
-class _FakeStreamWrapper:
-    def __init__(self, chunks):
-        self._chunks = list(chunks)
-        self.logging_obj = MagicMock()
-
-    def __iter__(self):
-        return self
-
-    def __next__(self):
-        if not self._chunks:
-            raise StopIteration
-        return self._chunks.pop(0)
-
-    def __aiter__(self):
-        return self
-
-    async def __anext__(self):
-        if not self._chunks:
-            raise StopAsyncIteration
-        return self._chunks.pop(0)
-
-
-def _build_iterator(chunks) -> LiteLLMCompletionStreamingIterator:
-    return LiteLLMCompletionStreamingIterator(
-        model="claude-haiku-4-5",
-        litellm_custom_stream_wrapper=_FakeStreamWrapper(chunks),
-        request_input="What is the weather in San Francisco?",
-        responses_api_request={},
-        custom_llm_provider="anthropic",
-        litellm_metadata={},
-    )
-
-
-def _response_ids(events) -> list[str]:
-    return [
-        event.response.id
-        for event in events
-        if getattr(event, "type", None) in RESPONSE_ID_EVENT_TYPES
-    ]
-
-
-@pytest.mark.asyncio
-async def test_streaming_events_share_the_chat_completion_response_id():
-    """
-    Every event of a bridged stream has to carry the same id, and that id has to decode
-    to the chat completion id spend tracking stores as `request_id`. Otherwise a
-    follow-up `previous_response_id` matches no session and the conversation is dropped.
-    """
-    iterator = _build_iterator([_chunk("Hello"), _chunk("!", finish_reason="stop")])
-
-    events = [event async for event in iterator]
-
-    response_ids = _response_ids(events)
-    assert len(response_ids) == 3
-    assert len(set(response_ids)) == 1
-    decoded = ResponsesAPIRequestUtils._decode_responses_api_response_id(response_ids[0])
-    assert decoded["response_id"] == CHAT_COMPLETION_ID
-    assert decoded["custom_llm_provider"] == "anthropic"
-
-
-def test_sync_streaming_events_share_the_chat_completion_response_id():
-    iterator = _build_iterator([_chunk("Hello"), _chunk("!", finish_reason="stop")])
-
-    events = list(iterator)
-
-    response_ids = _response_ids(events)
-    assert len(response_ids) == 3
-    assert len(set(response_ids)) == 1
-    assert (
-        ResponsesAPIRequestUtils._decode_responses_api_response_id(response_ids[0])["response_id"]
-        == CHAT_COMPLETION_ID
-    )
-
-
-@pytest.mark.asyncio
-async def test_streaming_emits_every_chunk_after_priming_the_response_id():
-    iterator = _build_iterator(
-        [_chunk("Hel"), _chunk("lo"), _chunk("!", finish_reason="stop")]
-    )
-
-    events = [event async for event in iterator]
-
-    deltas = "".join(
-        event.delta for event in events if getattr(event, "type", None) == "response.output_text.delta"
-    )
-    assert deltas == "Hello!"
-
-
-@pytest.mark.asyncio
-async def test_streaming_response_id_falls_back_when_upstream_yields_nothing():
-    iterator = _build_iterator([])
-
-    events = [event async for event in iterator]
-
-    response_ids = _response_ids(events)
-    assert response_ids
-    assert len(set(response_ids)) == 1
-    assert response_ids[0].startswith("resp_")
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_tool_call_streaming_transformation.py b/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py
similarity index 76%
rename from tests/test_litellm/responses/litellm_completion_transformation/test_tool_call_streaming_transformation.py
rename to tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py
index fa6f42609ca..823f656ddc5 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_tool_call_streaming_transformation.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py
@@ -1,18 +1,23 @@
 """
-Tests for streaming tool-calls in Responses API transformation.
+Tests for the Responses API streaming bridge in
+litellm/responses/litellm_completion_transformation/streaming_iterator.py.
 
 Ensures that when the underlying chat-completions stream includes tool_calls deltas,
 LiteLLM emits Responses API streaming events (output_item.added + function_call_arguments.*).
 
 Also ensures that tool calls that only appear in the final built response still get emitted
-before response.completed.
+before response.completed, and that every event of a bridged stream carries the response id
+spend tracking stores, so a follow-up previous_response_id still finds the conversation.
 """
 
-from unittest.mock import AsyncMock
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
 
 from litellm.responses.litellm_completion_transformation.streaming_iterator import (
     LiteLLMCompletionStreamingIterator,
 )
+from litellm.responses.utils import ResponsesAPIRequestUtils
 from litellm.types.llms.openai import ResponsesAPIStreamEvents
 from litellm.types.utils import (
     Delta,
@@ -21,6 +26,68 @@ from litellm.types.utils import (
     StreamingChoices,
 )
 
+CHAT_COMPLETION_ID = "chatcmpl-77d33d09-effa-4cd2-9c0d-c742d4358256"
+RESPONSE_ID_EVENT_TYPES = frozenset(
+    {"response.created", "response.in_progress", "response.completed"}
+)
+
+
+def _chunk(content: str, finish_reason: str | None = None) -> ModelResponseStream:
+    return ModelResponseStream(
+        id=CHAT_COMPLETION_ID,
+        created=1748575031,
+        model="claude-haiku-4-5",
+        object="chat.completion.chunk",
+        choices=[
+            StreamingChoices(
+                index=0,
+                delta=Delta(role="assistant", content=content),
+                finish_reason=finish_reason,
+            )
+        ],
+    )
+
+
+class _FakeStreamWrapper:
+    def __init__(self, chunks):
+        self._chunks = list(chunks)
+        self.logging_obj = MagicMock()
+
+    def __iter__(self):
+        return self
+
+    def __next__(self):
+        if not self._chunks:
+            raise StopIteration
+        return self._chunks.pop(0)
+
+    def __aiter__(self):
+        return self
+
+    async def __anext__(self):
+        if not self._chunks:
+            raise StopAsyncIteration
+        return self._chunks.pop(0)
+
+
+def _build_iterator(chunks) -> LiteLLMCompletionStreamingIterator:
+    return LiteLLMCompletionStreamingIterator(
+        model="claude-haiku-4-5",
+        litellm_custom_stream_wrapper=_FakeStreamWrapper(chunks),
+        request_input="What is the weather in San Francisco?",
+        responses_api_request={},
+        custom_llm_provider="anthropic",
+        litellm_metadata={},
+    )
+
+
+def _response_ids(events) -> list[str]:
+    return [
+        event.response.id
+        for event in events
+        if getattr(event, "type", None) in RESPONSE_ID_EVENT_TYPES
+    ]
+
 
 def test_tool_call_delta_is_emitted_as_responses_events():
     iterator = LiteLLMCompletionStreamingIterator(
@@ -397,3 +464,62 @@ def test_reused_index_with_new_call_id_marks_fallback_ambiguous():
     assert arguments_by_call_id["call_b"] == '{"b":'
     assert arguments_by_call_id["call_a"] != '{"a":1}'
     assert arguments_by_call_id["call_b"] != '{"b":1}'
+
+
+@pytest.mark.asyncio
+async def test_streaming_events_share_the_chat_completion_response_id():
+    """
+    Every event of a bridged stream has to carry the same id, and that id has to decode
+    to the chat completion id spend tracking stores as `request_id`. Otherwise a
+    follow-up `previous_response_id` matches no session and the conversation is dropped.
+    """
+    iterator = _build_iterator([_chunk("Hello"), _chunk("!", finish_reason="stop")])
+
+    events = [event async for event in iterator]
+
+    response_ids = _response_ids(events)
+    assert len(response_ids) == 3
+    assert len(set(response_ids)) == 1
+    decoded = ResponsesAPIRequestUtils._decode_responses_api_response_id(response_ids[0])
+    assert decoded["response_id"] == CHAT_COMPLETION_ID
+    assert decoded["custom_llm_provider"] == "anthropic"
+
+
+def test_sync_streaming_events_share_the_chat_completion_response_id():
+    iterator = _build_iterator([_chunk("Hello"), _chunk("!", finish_reason="stop")])
+
+    events = list(iterator)
+
+    response_ids = _response_ids(events)
+    assert len(response_ids) == 3
+    assert len(set(response_ids)) == 1
+    assert (
+        ResponsesAPIRequestUtils._decode_responses_api_response_id(response_ids[0])["response_id"]
+        == CHAT_COMPLETION_ID
+    )
+
+
+@pytest.mark.asyncio
+async def test_streaming_emits_every_chunk_after_priming_the_response_id():
+    iterator = _build_iterator(
+        [_chunk("Hel"), _chunk("lo"), _chunk("!", finish_reason="stop")]
+    )
+
+    events = [event async for event in iterator]
+
+    deltas = "".join(
+        event.delta for event in events if getattr(event, "type", None) == "response.output_text.delta"
+    )
+    assert deltas == "Hello!"
+
+
+@pytest.mark.asyncio
+async def test_streaming_response_id_falls_back_when_upstream_yields_nothing():
+    iterator = _build_iterator([])
+
+    events = [event async for event in iterator]
+
+    response_ids = _response_ids(events)
+    assert response_ids
+    assert len(set(response_ids)) == 1
+    assert response_ids[0].startswith("resp_")

From 7aef79b774abaee6e22edb2c75b9145256094b84 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Sat, 22 Aug 2026 14:47:03 -0700
Subject: [PATCH 46/93] test(e2e): harden the suite against response-cache
 cross-talk, slow providers and single upstream blips (#37957)

* test(e2e): send no-cache on every cacheable request body, opt in only where a hit is the assertion

The e2e proxy runs with the response cache on, so any test that re-sends an
identical chat, messages, responses, completions, embeddings or rerank body
reads back a redis copy of an earlier call instead of reaching the provider.
Five tests in the last week failed that way. Default cache: {"no-cache": true}
on those request models and pass cache=None only in the two tests whose
assertion is the cache hit itself.

* test(e2e): give image edits and OCR a 180s client timeout

Both routes wait on providers that can legitimately take longer than the
60s transport-wide request timeout (gpt-image edits, Azure Document
Intelligence), and a client-side read timeout there fails a green request.
post/upload now accept a per-call timeout like get already does; only those
two call sites use it.

* test(e2e): rerun once on network errors and upstream 5xx only

Assertion failures still fail on the first attempt; only an outcome whose
error string carries the e2e_http network kind or a 5xx status gets one
more try. Test Engine records every attempt, so the flake rate stays
visible while a single provider blip no longer reds the rc run.

* test(e2e): let the reseed burst survive one upstream failure and print why

The burst is the precondition, not the property: one 5xx among six
concurrent calls still leaves five workers racing the cold counter, which
is what the reseed assertion measures. Two or more failures still abort,
and the failing bodies are now in the message instead of only the status
codes.

* test(e2e): keep polling Jaeger through a transient query failure

poll_traces_for_call already waits up to POLL_TIMEOUT for spans to land,
but a single refused connection to the query API failed the test on the
spot. Jaeger restarted twice during today's gate runs (19:05 and 19:41
UTC, each under a minute) and took ten and three otel tests with it while
the same tests passed on the rc build minutes later. A network failure
now counts as not-yet inside the same deadline; if Jaeger is still
unreachable when the deadline passes the test fails with that error, and
any non-network failure still fails immediately.
---
 tests/e2e/e2e_config.py                       |  1 +
 tests/e2e/llm_translation/endpoints_client.py |  9 ++++-
 tests/e2e/models.py                           |  3 ++
 tests/e2e/otel_client.py                      | 35 ++++++++++++------
 tests/e2e/proxy_client.py                     |  2 ++
 tests/e2e/pytest.ini                          |  2 +-
 .../budgets/test_spend_counter_reseed_e2e.py  |  9 +++--
 .../spend_tracking/spend_e2e_client.py        |  6 +++-
 .../spend_tracking/test_spend_tracking_e2e.py |  4 +--
 tests/e2e/router/reliability_support.py       |  2 ++
 .../e2e/router/test_reliability_cache_e2e.py  |  4 +--
 tests/e2e/transport.py                        | 36 +++++++++++++++----
 12 files changed, 87 insertions(+), 26 deletions(-)

diff --git a/tests/e2e/e2e_config.py b/tests/e2e/e2e_config.py
index 0266c75e1a7..21a7a8c478a 100644
--- a/tests/e2e/e2e_config.py
+++ b/tests/e2e/e2e_config.py
@@ -78,6 +78,7 @@ DD_SEARCH_INTERVAL = float(os.environ.get("E2E_DD_SEARCH_INTERVAL", "10"))
 POLL_TIMEOUT = float(os.environ.get("E2E_POLL_TIMEOUT", "120"))
 POLL_INTERVAL = float(os.environ.get("E2E_POLL_INTERVAL", "5"))
 REQUEST_TIMEOUT = float(os.environ.get("E2E_REQUEST_TIMEOUT", "60"))
+SLOW_PROVIDER_TIMEOUT_SECONDS = float(os.environ.get("E2E_SLOW_PROVIDER_TIMEOUT", "180"))
 
 # How long a control-plane write (/model/new, /guardrails, /v1/agents) may take to
 # reach EVERY replica. Distinct from POLL_TIMEOUT, which is sized for spend-row
diff --git a/tests/e2e/llm_translation/endpoints_client.py b/tests/e2e/llm_translation/endpoints_client.py
index fa33737467e..4d2c73e7078 100644
--- a/tests/e2e/llm_translation/endpoints_client.py
+++ b/tests/e2e/llm_translation/endpoints_client.py
@@ -12,6 +12,7 @@ from __future__ import annotations
 from dataclasses import dataclass
 from typing import Literal
 
+from e2e_config import SLOW_PROVIDER_TIMEOUT_SECONDS
 from e2e_http import BinaryStream, Result, StreamingResponse
 from models import CacheControl, ChatMessage, LiteLLMParamsBody, RichMessage, TextBlock
 from proxy_client import ProxyClient
@@ -74,12 +75,14 @@ class ResponsesRequest(BaseModel):
     stream: bool = False
     tools: list[ResponsesFunctionTool] | None = None
     guardrails: list[str] | None = None
+    cache: dict[str, bool] | None = {"no-cache": True}
 
 
 class MessagesRequest(BaseModel):
     model: str
     max_tokens: int
     messages: list[ChatMessage]
+    cache: dict[str, bool] | None = {"no-cache": True}
 
 
 class RichMessagesRequest(BaseModel):
@@ -87,18 +90,20 @@ class RichMessagesRequest(BaseModel):
     max_tokens: int = 64
     system: list[TextBlock]
     messages: list[RichMessage]
-    cache: dict[str, bool] = {"no-cache": True}
+    cache: dict[str, bool] | None = {"no-cache": True}
 
 
 class CompletionsRequest(BaseModel):
     model: str
     prompt: str
     max_tokens: int = 32
+    cache: dict[str, bool] | None = {"no-cache": True}
 
 
 class EmbeddingsRequest(BaseModel):
     model: str
     input: str
+    cache: dict[str, bool] | None = {"no-cache": True}
 
 
 class RerankRequest(BaseModel):
@@ -106,6 +111,7 @@ class RerankRequest(BaseModel):
     query: str
     documents: list[str]
     top_n: int
+    cache: dict[str, bool] | None = {"no-cache": True}
 
 
 class SpeechRequest(BaseModel):
@@ -446,6 +452,7 @@ class EndpointsClient:
             file_content_type="image/png",
             file_field="image",
             response_type=ImagesResult,
+            timeout=SLOW_PROVIDER_TIMEOUT_SECONDS,
         )
 
     def generate_content(
diff --git a/tests/e2e/models.py b/tests/e2e/models.py
index 7711ca92b48..5e2cb90958e 100644
--- a/tests/e2e/models.py
+++ b/tests/e2e/models.py
@@ -233,6 +233,7 @@ class ChatBody(BaseModel):
     tool_choice: str | None = None
     guardrails: list[str] | None = None
     response_format: dict[str, object] | None = None
+    cache: dict[str, bool] | None = {"no-cache": True}
 
 
 class RouterSettingsOverride(BaseModel):
@@ -431,6 +432,7 @@ class AnthropicMessagesBody(BaseModel):
     stream: bool | None = None
     tools: list[AnthropicTool] | None = None
     guardrails: list[str] | None = None
+    cache: dict[str, bool] | None = {"no-cache": True}
 
 
 class CountTokensBody(BaseModel):
@@ -496,6 +498,7 @@ class McpServerInfo(BaseModel):
 class EmbedBody(BaseModel):
     model: str
     input: str
+    cache: dict[str, bool] | None = {"no-cache": True}
 
 
 class EmbedResponse(BaseModel):
diff --git a/tests/e2e/otel_client.py b/tests/e2e/otel_client.py
index 41555590dec..b11fddebc9c 100644
--- a/tests/e2e/otel_client.py
+++ b/tests/e2e/otel_client.py
@@ -24,7 +24,7 @@ import pytest
 from pydantic import BaseModel, ConfigDict, Field
 
 from e2e_config import OTEL_QUERY_URL, POLL_INTERVAL, POLL_TIMEOUT
-from e2e_http import URL, NoBody, Success, get
+from e2e_http import URL, NetworkError, NoBody, Result, Success, get
 
 #: OTEL resource service.name the proxy exports under (OTEL_SERVICE_NAME default).
 JAEGER_SERVICE = "litellm"
@@ -100,18 +100,20 @@ def _settled(trace: JaegerTrace, names: set[str], prefixes: set[str]) -> bool:
 class OtelReader:
     query_url: str
 
-    def traces_for_call(self, call_id: str) -> list[JaegerTrace]:
-        """Every trace holding a span tagged with this call id. Jaeger matches
-        spans server-side and returns their full traces; more than one hit for
-        one call IS the split-trace bug, so this never collapses to one."""
-        result = get(
+    def _query_traces(self, call_id: str) -> Result[JaegerTracesPage]:
+        return get(
             URL(f"{self.query_url}/api/traces"),
             headers=NoBody(),
             params=_TracesQuery(service=JAEGER_SERVICE, tags=json.dumps({CALL_ID_TAG: call_id})),
             response_type=JaegerTracesPage,
             timeout=30.0,
         )
-        match result:
+
+    def traces_for_call(self, call_id: str) -> list[JaegerTrace]:
+        """Every trace holding a span tagged with this call id. Jaeger matches
+        spans server-side and returns their full traces; more than one hit for
+        one call IS the split-trace bug, so this never collapses to one."""
+        match self._query_traces(call_id):
             case Success(data=page):
                 return page.data
             case failure:
@@ -128,11 +130,24 @@ class OtelReader:
         on a split trace this never settles and the orphan comes back."""
         deadline = time.monotonic() + POLL_TIMEOUT
         hits: list[JaegerTrace] = []
+        unreachable: NetworkError | None = None
         while time.monotonic() < deadline:
-            hits = self.traces_for_call(call_id)
-            if len(hits) == 1 and _settled(hits[0], settled_names, settled_prefixes):
-                return hits
+            match self._query_traces(call_id):
+                case Success(data=page):
+                    unreachable = None
+                    hits = page.data
+                    if len(hits) == 1 and _settled(hits[0], settled_names, settled_prefixes):
+                        return hits
+                case NetworkError() as failure:
+                    unreachable = failure
+                case failure:
+                    pytest.fail(f"Jaeger query API at {self.query_url} failed: {failure}")
             time.sleep(POLL_INTERVAL)
+        if unreachable is not None:
+            pytest.fail(
+                f"Jaeger query API at {self.query_url} stayed unreachable until the "
+                f"{POLL_TIMEOUT}s poll deadline: {unreachable}"
+            )
         return hits
 
 
diff --git a/tests/e2e/proxy_client.py b/tests/e2e/proxy_client.py
index 6cdd3354bf7..d12364e1794 100644
--- a/tests/e2e/proxy_client.py
+++ b/tests/e2e/proxy_client.py
@@ -70,6 +70,7 @@ from e2e_config import (
     POLL_TIMEOUT,
     PROXY_BASE_URL,
     REQUEST_TIMEOUT,
+    SLOW_PROVIDER_TIMEOUT_SECONDS,
     settle_propagation,
 )
 from transport import HttpTransport, SplitTransport, Transport
@@ -425,6 +426,7 @@ class ProxyClient:
             headers=self.transport.bearer(key),
             json=body,
             response_type=OcrResponse,
+            timeout=SLOW_PROVIDER_TIMEOUT_SECONDS,
         )
 
     def count_tokens(self, key: str, body: CountTokensBody) -> Result[CountTokensResponse]:
diff --git a/tests/e2e/pytest.ini b/tests/e2e/pytest.ini
index 2998a4b83c6..8feb4505ce3 100644
--- a/tests/e2e/pytest.ini
+++ b/tests/e2e/pytest.ini
@@ -2,7 +2,7 @@
 # Config when any e2e suite under tests/e2e/ is run directly, e.g.
 #   uv run pytest tests/e2e/quota_management/spend_tracking/ -v
 # The e2e marker is also registered in conftest.py for runs rooted elsewhere.
-addopts = --strict-markers --strict-config
+addopts = --strict-markers --strict-config --reruns 1 --only-rerun "kind='network'" --only-rerun "status_code=5[0-9][0-9]"
 markers =
     e2e: live test that requires a running proxy and real provider keys
     load: heavy throughput/load test; collected last so it never perturbs latency-sensitive suites
diff --git a/tests/e2e/quota_management/budgets/test_spend_counter_reseed_e2e.py b/tests/e2e/quota_management/budgets/test_spend_counter_reseed_e2e.py
index 7cfd3e33fd6..4a69135cdd1 100644
--- a/tests/e2e/quota_management/budgets/test_spend_counter_reseed_e2e.py
+++ b/tests/e2e/quota_management/budgets/test_spend_counter_reseed_e2e.py
@@ -39,6 +39,7 @@ pytestmark = pytest.mark.e2e
 MODEL = "claude-haiku-4-5"
 ACCUMULATE_CALLS = 24
 BURST = 6
+BURST_TOLERATED_FAILURES = 1
 # proxy_batch_write_at (60s) flushes the spend to the DB and default_redis_ttl (20s)
 # expires the counter; this waits out both.
 COLD_WAIT_SECONDS = 80
@@ -174,9 +175,11 @@ def test_cold_counter_reseed_keeps_counter_equal_to_db_spend(
 
     with ThreadPoolExecutor(max_workers=BURST) as pool:
         burst_results = list(pool.map(one, range(BURST)))
-    assert all(r.ok for r in burst_results), (
-        "some burst calls failed; cannot exercise concurrent reseed. "
-        f"statuses={[r.status_code for r in burst_results]}"
+    failed = [r for r in burst_results if not r.ok]
+    assert len(failed) <= BURST_TOLERATED_FAILURES, (
+        "too many burst calls failed; cannot exercise concurrent reseed. "
+        f"statuses={[r.status_code for r in burst_results]} "
+        f"bodies={[r.body[:300] for r in failed]}"
     )
 
     counter: float | None = None
diff --git a/tests/e2e/quota_management/spend_tracking/spend_e2e_client.py b/tests/e2e/quota_management/spend_tracking/spend_e2e_client.py
index b4f64ba2ac5..056799b8499 100644
--- a/tests/e2e/quota_management/spend_tracking/spend_e2e_client.py
+++ b/tests/e2e/quota_management/spend_tracking/spend_e2e_client.py
@@ -65,6 +65,7 @@ def _chat_body(
     tags: list[str] | None = None,
     user: str | None = None,
     stream: bool = False,
+    cache: dict[str, bool] | None = {"no-cache": True},
 ) -> ChatBody:
     return ChatBody(
         model=model,
@@ -73,6 +74,7 @@ def _chat_body(
         stream=stream,
         user=user,
         metadata=ChatMetadata(tags=tags) if tags else None,
+        cache=cache,
     )
 
 
@@ -89,9 +91,11 @@ class SpendClient:
         max_tokens: int | None = None,
         tags: list[str] | None = None,
         user: str | None = None,
+        cache: dict[str, bool] | None = {"no-cache": True},
     ) -> Result[ChatResponse]:
         return self.proxy.chat(
-            key, _chat_body(model, content, max_tokens=max_tokens, tags=tags, user=user)
+            key,
+            _chat_body(model, content, max_tokens=max_tokens, tags=tags, user=user, cache=cache),
         )
 
     def chat_stream(
diff --git a/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py b/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py
index 6a0032981fd..c5d76d44580 100644
--- a/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py
+++ b/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py
@@ -226,8 +226,8 @@ def test_cache_hit_is_zero_cost_and_suffixed(
     # populated. The marker keeps each run isolated - a fixed prompt would persist
     # in the shared response cache across runs and make both calls hit (flaky).
     prompt = f"What is the capital of France? Answer in one word. {unique_marker()}"
-    _ = unwrap(client.chat(scoped_key, "gemini-2.5-flash", prompt, max_tokens=16))
-    _ = unwrap(client.chat(scoped_key, "gemini-2.5-flash", prompt, max_tokens=16))
+    _ = unwrap(client.chat(scoped_key, "gemini-2.5-flash", prompt, max_tokens=16, cache=None))
+    _ = unwrap(client.chat(scoped_key, "gemini-2.5-flash", prompt, max_tokens=16, cache=None))
 
     rows = client.poll_logs_for_key(
         scoped_key,
diff --git a/tests/e2e/router/reliability_support.py b/tests/e2e/router/reliability_support.py
index cd70ac45da6..cc1c91c635b 100644
--- a/tests/e2e/router/reliability_support.py
+++ b/tests/e2e/router/reliability_support.py
@@ -47,6 +47,7 @@ def chat_override(
     content: str,
     override: RouterSettingsOverride | None = None,
     stream: bool = False,
+    cache: dict[str, bool] | None = {"no-cache": True},
 ) -> StreamingResponse:
     """POST /chat/completions with an optional per-request router_settings_override,
     returning the raw outcome so tests read status, body, and reliability headers."""
@@ -59,6 +60,7 @@ def chat_override(
             max_tokens=64,
             stream=stream,
             router_settings_override=override,
+            cache=cache,
         ),
         stream=stream,
     )
diff --git a/tests/e2e/router/test_reliability_cache_e2e.py b/tests/e2e/router/test_reliability_cache_e2e.py
index 78d8fcdc08f..4ea05a1ecca 100644
--- a/tests/e2e/router/test_reliability_cache_e2e.py
+++ b/tests/e2e/router/test_reliability_cache_e2e.py
@@ -23,13 +23,13 @@ class TestReliabilityCache:
     def test_exact_cache_returns_cached(self, client: ComplexityRouterClient, scoped_key: str) -> None:
         prompt = f"cache probe {unique_marker()}"
 
-        first = chat_override(client.proxy, scoped_key, "gpt-5.5", prompt)
+        first = chat_override(client.proxy, scoped_key, "gpt-5.5", prompt, cache=None)
         assert first.status_code == 200, f"first call should succeed, got {first.status_code}: {first.body[:300]}"
         assert "x-litellm-cache-key" not in first.headers, (
             "first (uncached) call must not report a cache-key header"
         )
 
-        second = chat_override(client.proxy, scoped_key, "gpt-5.5", prompt)
+        second = chat_override(client.proxy, scoped_key, "gpt-5.5", prompt, cache=None)
         assert second.status_code == 200, f"second call should succeed, got {second.status_code}: {second.body[:300]}"
         assert "x-litellm-cache-key" in second.headers, (
             "second identical call should hit the response cache and report a cache-key header "
diff --git a/tests/e2e/transport.py b/tests/e2e/transport.py
index 27b11befc8e..44fdbaa3e41 100644
--- a/tests/e2e/transport.py
+++ b/tests/e2e/transport.py
@@ -25,7 +25,13 @@ from e2e_http import (
 
 class Transport(Protocol):
     def post[R: BaseModel](
-        self, path: str, *, headers: BaseModel, json: BaseModel, response_type: type[R]
+        self,
+        path: str,
+        *,
+        headers: BaseModel,
+        json: BaseModel,
+        response_type: type[R],
+        timeout: float | None = None,
     ) -> Result[R]: ...
 
     def stream(
@@ -93,6 +99,7 @@ class Transport(Protocol):
         file_field: str = "file",
         params: BaseModel | None = None,
         response_type: type[R],
+        timeout: float | None = None,
     ) -> Result[R]: ...
 
     def download(self, path: str, *, headers: BaseModel) -> StreamingResponse: ...
@@ -120,14 +127,22 @@ class HttpTransport:
         return self.bearer(self.master_key)
 
     def post[R: BaseModel](
-        self, path: str, *, headers: BaseModel, json: BaseModel, response_type: type[R]
+        self,
+        path: str,
+        *,
+        headers: BaseModel,
+        json: BaseModel,
+        response_type: type[R],
+        timeout: float | None = None,
     ) -> Result[R]:
+        """`timeout` overrides the transport-wide request_timeout for this call, for
+        provider operations that legitimately outlive it (image edits, OCR)."""
         return e2e_http.post(
             self._url(path),
             headers=headers,
             json=json,
             response_type=response_type,
-            timeout=self.request_timeout,
+            timeout=self.request_timeout if timeout is None else timeout,
         )
 
     def get[R: BaseModel](
@@ -250,6 +265,7 @@ class HttpTransport:
         file_field: str = "file",
         params: BaseModel | None = None,
         response_type: type[R],
+        timeout: float | None = None,
     ) -> Result[R]:
         return e2e_http.upload(
             self._url(path),
@@ -261,7 +277,7 @@ class HttpTransport:
             file_field=file_field,
             params=params,
             response_type=response_type,
-            timeout=self.request_timeout,
+            timeout=self.request_timeout if timeout is None else timeout,
         )
 
     def download(self, path: str, *, headers: BaseModel) -> StreamingResponse:
@@ -327,10 +343,16 @@ class SplitTransport:
         return self.data.master
 
     def post[R: BaseModel](
-        self, path: str, *, headers: BaseModel, json: BaseModel, response_type: type[R]
+        self,
+        path: str,
+        *,
+        headers: BaseModel,
+        json: BaseModel,
+        response_type: type[R],
+        timeout: float | None = None,
     ) -> Result[R]:
         return self._route(path).post(
-            path, headers=headers, json=json, response_type=response_type
+            path, headers=headers, json=json, response_type=response_type, timeout=timeout
         )
 
     def get[R: BaseModel](
@@ -426,6 +448,7 @@ class SplitTransport:
         file_field: str = "file",
         params: BaseModel | None = None,
         response_type: type[R],
+        timeout: float | None = None,
     ) -> Result[R]:
         return self._route(path).upload(
             path,
@@ -437,6 +460,7 @@ class SplitTransport:
             file_field=file_field,
             params=params,
             response_type=response_type,
+            timeout=timeout,
         )
 
     def download(self, path: str, *, headers: BaseModel) -> StreamingResponse:

From 6befeb8a17f93bd65b028fdd0b8c4c3087c92a1e Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 14:48:32 -0700
Subject: [PATCH 47/93] fix(interactions): stop the cost poll loop instead of
 spinning on a non-positive interval

---
 litellm/interactions/background_cost_polling.py     |  2 +-
 .../interactions/test_background_cost_polling.py    | 13 +++++++++++++
 2 files changed, 14 insertions(+), 1 deletion(-)

diff --git a/litellm/interactions/background_cost_polling.py b/litellm/interactions/background_cost_polling.py
index 262d8e3260d..f2957d08840 100644
--- a/litellm/interactions/background_cost_polling.py
+++ b/litellm/interactions/background_cost_polling.py
@@ -74,7 +74,7 @@ async def _fetch_interaction(context: BackgroundInteractionPollContext) -> Inter
 def _poll_intervals(initial: float, maximum: float, timeout: float) -> Iterator[float]:
     elapsed = 0.0
     interval = initial
-    while elapsed + interval <= timeout:
+    while interval > 0 and elapsed + interval <= timeout:
         yield interval
         elapsed += interval
         interval = min(interval * 2, maximum)
diff --git a/tests/test_litellm/interactions/test_background_cost_polling.py b/tests/test_litellm/interactions/test_background_cost_polling.py
index 64436ebe4a7..7908e0e8f17 100644
--- a/tests/test_litellm/interactions/test_background_cost_polling.py
+++ b/tests/test_litellm/interactions/test_background_cost_polling.py
@@ -1,11 +1,13 @@
 import asyncio
 import time
+from itertools import islice
 from typing import Optional
 
 import pytest
 
 from litellm.interactions.background_cost_polling import (
     _SETTLED_KEY,
+    _poll_intervals,
     BackgroundInteractionPollContext,
     maybe_schedule_background_interaction_cost_polling,
     maybe_settle_background_interaction_before_delete,
@@ -92,6 +94,17 @@ def _fetch_sequence(*responses):
     return fetch, calls
 
 
+@pytest.mark.parametrize(
+    "initial, maximum",
+    [(0.0, 0.002), (0.001, 0.0), (-1.0, 0.002), (0.0, 0.0)],
+)
+def test_poll_intervals_stops_instead_of_looping_on_a_non_positive_interval(initial, maximum):
+    intervals = list(islice(_poll_intervals(initial=initial, maximum=maximum, timeout=3600.0), 10))
+
+    assert len(intervals) < 10
+    assert all(interval > 0 for interval in intervals)
+
+
 @pytest.mark.asyncio
 async def test_poller_bills_once_when_interaction_completes():
     logging_obj = _logging_obj()

From 8a7c873a01b5e179071c590998e229b0fa61aeac Mon Sep 17 00:00:00 2001
From: yucheng-berri <yucheng@berri.ai>
Date: Sat, 22 Aug 2026 14:51:11 -0700
Subject: [PATCH 48/93] fix(proxy): omit litellm_batch_guardrail when no
 guardrail acted (#37964)

The field is declared optional on OpenAIFileObject and its own docstring says it
is absent on every upload guardrails did not touch, but the /v1/files routes have
no response_model, so FastAPI falls through to jsonable_encoder with exclude_none
off and serialises the unset default as an explicit null. Every create and
retrieve response on a proxy with no guardrails configured at all picked up a
litellm_batch_guardrail: null it never had before, and so did every row of a file
list, since those rows are the same object.

A wrap serializer drops the key only when nothing set it, so the populated report
still reaches the wire intact, including a record whose guardrail is null. The
managed-files list route spreads a stored file_object blob rather than the model,
so rows persisted before this lands keep their null until it is dropped there too.
---
 .../managed_id_rewriter.py                    |  3 +-
 litellm/types/llms/openai.py                  | 16 +++++
 .../test_files_endpoint.py                    | 60 ++++++++++++++++
 .../test_managed_id_rewriter.py               | 21 ++++++
 .../types/llms/test_types_llms_openai.py      | 72 +++++++++++++++++++
 5 files changed, 171 insertions(+), 1 deletion(-)

diff --git a/litellm/proxy/pass_through_endpoints/managed_id_rewriter.py b/litellm/proxy/pass_through_endpoints/managed_id_rewriter.py
index e8b5fab626f..e08d277788f 100644
--- a/litellm/proxy/pass_through_endpoints/managed_id_rewriter.py
+++ b/litellm/proxy/pass_through_endpoints/managed_id_rewriter.py
@@ -50,7 +50,7 @@ from litellm.repositories.table_repositories import (
     ManagedFileRepository,
     ManagedObjectRepository,
 )
-from litellm.types.llms.openai import OpenAIFileObject
+from litellm.types.llms.openai import BATCH_GUARDRAIL_RESPONSE_FIELD, OpenAIFileObject
 from litellm.types.passthrough_endpoints.managed_id_rewriter import (
     ManagedFileIdReader,
     ManagedFileIdWriter,
@@ -980,6 +980,7 @@ def _serialize_file_list_item(row: ManagedFileRow) -> dict[str, JsonValue]:
     file_object: Final = _parse_file_object(row.file_object)
     if isinstance(file_object, dict):
         item.update(file_object)
+    item.pop(BATCH_GUARDRAIL_RESPONSE_FIELD, None)
     item["id"] = row.unified_file_id  # managed ID always wins over stored raw id
     return item
 
diff --git a/litellm/types/llms/openai.py b/litellm/types/llms/openai.py
index 50e47071012..e7a3f825455 100644
--- a/litellm/types/llms/openai.py
+++ b/litellm/types/llms/openai.py
@@ -67,8 +67,10 @@ from pydantic import (
     Discriminator,
     Field,
     PrivateAttr,
+    SerializerFunctionWrapHandler,
     field_serializer,
     field_validator,
+    model_serializer,
 )
 from typing_extensions import (
     NotRequired,
@@ -315,6 +317,9 @@ class BatchGuardrailReport(BaseModel):
     """Every record that was redacted or dropped, in file order."""
 
 
+BATCH_GUARDRAIL_RESPONSE_FIELD: Final = "litellm_batch_guardrail"
+
+
 class OpenAIFileObject(BaseModel):
     id: str
     """The file identifier, which can be referenced in the API endpoints."""
@@ -363,6 +368,17 @@ class OpenAIFileObject(BaseModel):
 
     _hidden_params: dict = {"response_cost": 0.0}  # no cost for writing a file
 
+    @model_serializer(mode="wrap")
+    def _omit_absent_batch_guardrail(  # noqa: ANN202  # annotating it replaces the model's serialization schema
+        self, handler: SerializerFunctionWrapHandler
+    ):
+        serialized: Final[Mapping[str, object]] = handler(self)
+        if self.litellm_batch_guardrail is not None:
+            return serialized
+        return {  # mutable-ok: pydantic's json serializer rejects a mapping that is not a dict
+            key: value for key, value in serialized.items() if key != BATCH_GUARDRAIL_RESPONSE_FIELD
+        }
+
     def __contains__(self, key) -> bool:
         # Define custom behavior for the 'in' operator
         return hasattr(self, key)
diff --git a/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py b/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py
index c15ba5bcedb..1b16e036ad7 100644
--- a/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py
+++ b/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py
@@ -4166,6 +4166,66 @@ def test_batch_upload_redacts_per_record(monkeypatch, llm_router: Router):
         ProxyLogging._callback_capabilities_cache.clear()
 
 
+PLAIN_UPLOAD_RESPONSE_BODY = {
+    "id": "dummy-id",
+    "object": "file",
+    "bytes": 0,
+    "created_at": 1234567890,
+    "filename": "batch.jsonl",
+    "purpose": "batch",
+    "status": "uploaded",
+    "expires_at": None,
+    "status_details": None,
+}
+
+
+def test_create_file_omits_batch_guardrail_field_when_no_guardrail_configured(monkeypatch, llm_router: Router):
+    """An upload no guardrail is configured for serialises the plain OpenAI file shape."""
+    forwarded_calls = _setup_batch_upload_endpoint(monkeypatch, llm_router)
+    try:
+        response = client.post(
+            "/v1/files",
+            files={"file": ("batch.jsonl", VALID_BATCH_LINE, "application/jsonl")},
+            data={"purpose": "batch"},
+            headers={"Authorization": "Bearer test-key"},
+        )
+    finally:
+        _teardown_batch_upload_endpoint()
+
+    assert response.status_code == 200, response.text
+    assert len(forwarded_calls) == 1
+    assert response.json() == PLAIN_UPLOAD_RESPONSE_BODY
+
+
+def test_create_file_omits_batch_guardrail_field_when_guardrail_made_no_changes(monkeypatch, llm_router: Router):
+    """A guardrail that runs and changes nothing leaves the response the plain OpenAI file shape."""
+    import litellm
+    from litellm.integrations.custom_guardrail import CustomGuardrail
+    from litellm.proxy.utils import ProxyLogging
+
+    class _Passthrough(CustomGuardrail):
+        async def async_pre_call_hook(self, user_api_key_dict, cache, data, call_type):
+            return data
+
+    forwarded_calls = _setup_batch_upload_endpoint(monkeypatch, llm_router)
+    monkeypatch.setattr(litellm, "callbacks", [_Passthrough(guardrail_name="noop", default_on=True)])
+    ProxyLogging._callback_capabilities_cache.clear()
+    try:
+        response = client.post(
+            "/v1/files",
+            files={"file": ("batch.jsonl", VALID_BATCH_LINE, "application/jsonl")},
+            data={"purpose": "batch"},
+            headers={"Authorization": "Bearer test-key"},
+        )
+    finally:
+        _teardown_batch_upload_endpoint()
+        ProxyLogging._callback_capabilities_cache.clear()
+
+    assert response.status_code == 200, response.text
+    assert len(forwarded_calls) == 1
+    assert response.json() == PLAIN_UPLOAD_RESPONSE_BODY
+
+
 def test_batch_upload_closes_the_spools_it_opened(monkeypatch, llm_router: Router):
     """The scan and the rewrite each open a spool; the request owns both and must not leak them."""
     import json as _json
diff --git a/tests/test_litellm/proxy/pass_through_endpoints/test_managed_id_rewriter.py b/tests/test_litellm/proxy/pass_through_endpoints/test_managed_id_rewriter.py
index 9c16c52f589..f5bec4a2585 100644
--- a/tests/test_litellm/proxy/pass_through_endpoints/test_managed_id_rewriter.py
+++ b/tests/test_litellm/proxy/pass_through_endpoints/test_managed_id_rewriter.py
@@ -126,3 +126,24 @@ async def test_list_files_limit_above_batch_cap_still_served():
 
     assert result is not None
     assert [item["id"] for item in result["data"]] == [managed_id]
+
+
+@pytest.mark.asyncio
+async def test_list_files_drops_batch_guardrail_key_persisted_by_an_older_proxy():
+    """Rows written before the response serializer dropped the key still carry an explicit null."""
+    managed_id = new_managed_id("openai", "file-abc")
+    row = _file_row(managed_id)
+    row.file_object = {**row.file_object, "litellm_batch_guardrail": None}
+    pc = _prisma_client(file_rows=[row])
+
+    result = await list_passthrough_ids_from_db(
+        provider="openai",
+        route="/openai/v1/files",
+        user_api_key_dict=_user(),
+        prisma_client=pc,
+        query_params={},
+    )
+
+    assert result is not None
+    assert "litellm_batch_guardrail" not in result["data"][0]
+    assert result["data"][0]["filename"] == "test.jsonl"
diff --git a/tests/test_litellm/types/llms/test_types_llms_openai.py b/tests/test_litellm/types/llms/test_types_llms_openai.py
index e5e5c0183a0..3966677e928 100644
--- a/tests/test_litellm/types/llms/test_types_llms_openai.py
+++ b/tests/test_litellm/types/llms/test_types_llms_openai.py
@@ -450,3 +450,75 @@ def test_openai_file_object_accepts_pending_status():
         status="pending",
     )
     assert file_obj.status == "pending"
+
+
+class TestOpenAIFileObjectBatchGuardrailSerialization:
+    """The proxy-only `litellm_batch_guardrail` key must reach the wire only when something set it."""
+
+    @staticmethod
+    def _file_object(**overrides):
+        from litellm.types.llms.openai import OpenAIFileObject
+
+        return OpenAIFileObject(
+            id="file-123",
+            object="file",
+            bytes=1024,
+            created_at=1677610602,
+            filename="batch.jsonl",
+            purpose="batch",
+            status="uploaded",
+            **overrides,
+        )
+
+    @staticmethod
+    def _report():
+        from litellm.types.llms.openai import BatchGuardrailRecord, BatchGuardrailReport
+
+        return BatchGuardrailReport(
+            submitted_records=3,
+            modified_records=(BatchGuardrailRecord(line=2, custom_id="dirty", action="redacted"),),
+        )
+
+    @pytest.mark.parametrize("mode", ["python", "json"])
+    def test_key_absent_when_unset(self, mode):
+        assert "litellm_batch_guardrail" not in self._file_object().model_dump(mode=mode)
+
+    @pytest.mark.parametrize("mode", ["python", "json"])
+    def test_key_present_when_set(self, mode):
+        dumped = self._file_object(litellm_batch_guardrail=self._report()).model_dump(mode=mode)
+        assert dumped["litellm_batch_guardrail"]["submitted_records"] == 3
+
+    def test_nested_nulls_of_a_set_report_survive(self):
+        """`exclude_none=True` was rejected as the fix because it would strip these."""
+        dumped = self._file_object(litellm_batch_guardrail=self._report()).model_dump(mode="json")
+        assert dumped["litellm_batch_guardrail"]["modified_records"] == [
+            {"line": 2, "custom_id": "dirty", "action": "redacted", "guardrail": None}
+        ]
+
+    def test_by_alias_dump_also_omits_the_key(self):
+        """Tripwire: the serializer filters a literal key name, which an added alias would bypass."""
+        assert "litellm_batch_guardrail" not in self._file_object().model_dump(mode="json", by_alias=True)
+
+    def test_other_optional_fields_still_serialize_as_null(self):
+        dumped = self._file_object().model_dump(mode="json")
+        assert dumped["expires_at"] is None
+        assert dumped["status_details"] is None
+
+    def test_round_trip_of_a_set_report_is_lossless(self):
+        from litellm.types.llms.openai import OpenAIFileObject
+
+        original = self._file_object(litellm_batch_guardrail=self._report())
+        assert OpenAIFileObject(**original.model_dump()) == original
+
+    def test_serialization_json_schema_still_describes_the_model(self):
+        """A return annotation on the wrap serializer would collapse this to a bare object."""
+        from litellm.types.llms.openai import OpenAIFileObject
+
+        schema = OpenAIFileObject.model_json_schema(mode="serialization")
+        assert "litellm_batch_guardrail" in schema["properties"]
+
+    def test_key_omitted_inside_a_file_list_page(self):
+        from litellm.types.llms.openai import FileListPage
+
+        page = FileListPage(object="list", data=[self._file_object()], has_more=False)
+        assert "litellm_batch_guardrail" not in page.model_dump(mode="json")["data"][0]

From 19a3fe1b66c2d702d2ec05d5e28bc83d3375f27e Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 14:51:38 -0700
Subject: [PATCH 49/93] fix(responses-bridge): fall back to summary text when
 content carries none

An empty content list, or one holding only opaque blocks, still lets the
provider-bound branch replay the summary text. The inspection path treated
any non-None content as final, so that replayed text stayed invisible to
guardrails and token counting.
---
 .../transformation.py                         | 69 ++++++++++++-------
 .../test_reasoning_input_item_preservation.py | 26 +++++++
 2 files changed, 70 insertions(+), 25 deletions(-)

diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index 83e02888924..86c471cf63c 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -1210,10 +1210,14 @@ class LiteLLMCompletionResponsesConfig:
             # message `content`, summary-only items included: whatever the
             # provider-bound branch below replays must stay scannable.
             if not replay_reasoning:
+                # `content` wins only when it is what the provider-bound branch
+                # would replay; an empty or block-only `content` falls back to
+                # the summary text, which is what that branch replays instead.
                 inspectable: Final[object] = (
                     input_item.get("content")
-                    if input_item.get("content") is not None
-                    else LiteLLMCompletionResponsesConfig._extract_reasoning_text_from_input_item(input_item)
+                    if LiteLLMCompletionResponsesConfig._reasoning_text_from_content(input_item) is not None
+                    else LiteLLMCompletionResponsesConfig._reasoning_text_from_summary(input_item)
+                    or input_item.get("content")
                 )
                 if inspectable is None:
                     return []  # mutable-ok: empty drop result
@@ -1255,22 +1259,19 @@ class LiteLLMCompletionResponsesConfig:
             ]
 
     @staticmethod
-    def _extract_reasoning_text_from_input_item(input_item: Mapping[str, object]) -> str | None:
+    def _reasoning_text_from_content(input_item: Mapping[str, object]) -> str | None:
         """
-        Extract plaintext reasoning from a ResponseReasoningItemParam.
+        Plaintext a ResponseReasoningItemParam carries in ``content``.
 
-        Handles:
-        - content as a string
-        - content as a list of blocks (output_text / summary_text / text)
-        - summary as a list of summary_text blocks (fallback)
-
-        Returns None when only opaque forms (e.g. encrypted_content) are present.
+        Handles content as a string and content as a list of blocks
+        (output_text / summary_text / text). Returns None when the item has
+        no content, or only opaque blocks (e.g. encrypted_content).
         """
         content: Final[object] = input_item.get("content")
         if isinstance(content, str) and content.strip():
             return content
         if isinstance(content, list):
-            text_parts: list[str] = []  # mutable-ok: text accumulator  # rebind-ok: text accumulator
+            text_parts: Final[list[str]] = []  # mutable-ok: text accumulator
             for block in content:
                 if not isinstance(block, Mapping):
                     continue
@@ -1282,22 +1283,40 @@ class LiteLLMCompletionResponsesConfig:
                     text_parts.append(text.strip())
             if text_parts:
                 return "\n".join(text_parts)
-
-        # Guardrail traversal in litellm/proxy/guardrails/_content_utils.py
-        # inspects and rewrites these summary blocks before they are forwarded.
-        summary: Final[object] = input_item.get("summary")
-        if isinstance(summary, list):
-            text_parts = []  # mutable-ok: text accumulator  # rebind-ok: text accumulator
-            for block in summary:
-                if not isinstance(block, Mapping):
-                    continue
-                text = block.get("text")
-                if isinstance(text, str) and text.strip():
-                    text_parts.append(text.strip())
-            if text_parts:
-                return "\n".join(text_parts)
         return None
 
+    @staticmethod
+    def _reasoning_text_from_summary(input_item: Mapping[str, object]) -> str | None:
+        """
+        Plaintext a ResponseReasoningItemParam carries in ``summary``.
+
+        Guardrail traversal in litellm/proxy/guardrails/_content_utils.py
+        inspects and rewrites these summary blocks before they are forwarded.
+        """
+        summary: Final[object] = input_item.get("summary")
+        if not isinstance(summary, list):
+            return None
+        text_parts: Final[list[str]] = []  # mutable-ok: text accumulator
+        for block in summary:
+            if not isinstance(block, Mapping):
+                continue
+            text = block.get("text")
+            if isinstance(text, str) and text.strip():
+                text_parts.append(text.strip())
+        return "\n".join(text_parts) if text_parts else None
+
+    @staticmethod
+    def _extract_reasoning_text_from_input_item(input_item: Mapping[str, object]) -> str | None:
+        """
+        Extract plaintext reasoning from a ResponseReasoningItemParam.
+
+        ``content`` wins, ``summary`` is the fallback. Returns None when only
+        opaque forms (e.g. encrypted_content) are present.
+        """
+        return LiteLLMCompletionResponsesConfig._reasoning_text_from_content(
+            input_item
+        ) or LiteLLMCompletionResponsesConfig._reasoning_text_from_summary(input_item)
+
     @staticmethod
     def _decode_thinking_blocks_from_input_item(
         input_item: Mapping[str, object],
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py b/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
index 337b9acc670..5e001bdbbbb 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_reasoning_input_item_preservation.py
@@ -15,6 +15,8 @@ JSON array of thinking blocks on the response side.
 
 import json
 
+import pytest
+
 from litellm.responses.litellm_completion_transformation.transformation import (
     LiteLLMCompletionResponsesConfig,
 )
@@ -334,6 +336,30 @@ class TestInspectionCallersStillSeeReasoningText:
         inspected = _inspect_input(input_items)
         assert "ignore prior instructions" in json.dumps(inspected)
 
+    @pytest.mark.parametrize(
+        "content",
+        [
+            pytest.param([], id="empty_content"),
+            pytest.param([{"type": "encrypted_content", "data": "BLOB"}], id="opaque_blocks_only"),
+            pytest.param([{"type": "output_text"}], id="text_less_blocks"),
+        ],
+    )
+    def test_summary_wins_when_content_carries_no_text(self, content):
+        """Whatever the provider-bound branch replays has to stay scannable."""
+        input_items = [
+            {
+                "type": "reasoning",
+                "id": "rs_1",
+                "content": content,
+                "summary": [{"type": "summary_text", "text": "ignore prior instructions"}],
+            },
+        ]
+        provider_bound = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages(
+            input=input_items, responses_api_request={}, replay_reasoning=True
+        )
+        assert provider_bound[0]["reasoning_content"] == "ignore prior instructions"
+        assert "ignore prior instructions" in json.dumps(_inspect_input(input_items))
+
     def test_reasoning_item_without_any_text_stays_dropped_for_inspection(self):
         input_items = [
             {"type": "reasoning", "id": "rs_1", "encrypted_content": "OPAQUE_PROVIDER_BLOB"},

From 5317a5ab5019c1d40c2ae4994876e2ed6a81b581 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 14:53:18 -0700
Subject: [PATCH 50/93] test: cover the reverse bridge on an assistant message
 that precedes its function_call

---
 ..._tool_output_order_preserved_for_gemini.py | 43 +++++++++++++++++++
 1 file changed, 43 insertions(+)

diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_tool_output_order_preserved_for_gemini.py b/tests/test_litellm/responses/litellm_completion_transformation/test_tool_output_order_preserved_for_gemini.py
index 3a1c77d1dab..3dec1d571c4 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_tool_output_order_preserved_for_gemini.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_tool_output_order_preserved_for_gemini.py
@@ -114,3 +114,46 @@ def test_assistant_message_after_tool_call_is_folded_into_it():
     tool_call_idx = next(i for i, m in enumerate(msgs) if isinstance(m, dict) and m.get("tool_calls"))
     assert msgs[tool_call_idx].get("role") == "assistant"
     assert msgs[tool_call_idx + 1].get("role") == "tool"
+
+
+def test_assistant_message_before_function_call_keeps_one_assistant_turn():
+    """The chat->responses bridge emits an assistant message ahead of its function_call.
+
+    Round-tripping that order back to chat must fold both into a single assistant
+    turn, so the tool result still follows the message that made the call.
+    """
+    msgs = LiteLLMCompletionResponsesConfig._transform_response_input_param_to_chat_completion_message(
+        input=[
+            {
+                "role": "user",
+                "type": "message",
+                "content": [{"type": "input_text", "text": "What is the weather?"}],
+            },
+            {
+                "role": "assistant",
+                "type": "message",
+                "content": [{"type": "output_text", "text": "Let me check."}],
+            },
+            {
+                "type": "function_call",
+                "name": "get_weather",
+                "call_id": "call_1",
+                "arguments": "{}",
+            },
+            {
+                "type": "function_call_output",
+                "call_id": "call_1",
+                "output": "sunny",
+            },
+        ]
+    )
+
+    assistant_msgs = [m for m in msgs if isinstance(m, dict) and m.get("role") == "assistant"]
+    assert len(assistant_msgs) == 1
+    assistant = assistant_msgs[0]
+    assert assistant["content"] == [{"type": "text", "text": "Let me check."}]
+    assert [tc["function"]["name"] for tc in assistant["tool_calls"]] == ["get_weather"]
+
+    assistant_idx = msgs.index(assistant)
+    assert msgs[assistant_idx + 1].get("role") == "tool"
+    assert msgs[assistant_idx + 1].get("tool_call_id") == "call_1"

From c55b400f41054d35652380ea2ed1bada6b986527 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 14:55:30 -0700
Subject: [PATCH 51/93] fix(databricks): bill cached tokens at cache rates and
 add missing Claude pricing

Databricks cost calculation multiplied every prompt token by the input rate, so
a cache read cost the same as an uncached token. Route it through
generic_cost_per_token, which already understands cache reads and cache writes,
and add the cache rates the registry was missing.

Adds Claude Opus 4.7, Opus 4.8, Opus 5, Sonnet 5 and Fable 5 on Databricks.
---
 litellm/llms/databricks/cost_calculator.py    |  61 ++---
 ...odel_prices_and_context_window_backup.json | 243 +++++++++++++++++-
 model_prices_and_context_window.json          | 243 +++++++++++++++++-
 .../test_databricks_cost_calculator.py        |  90 +++++++
 4 files changed, 579 insertions(+), 58 deletions(-)
 create mode 100644 tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py

diff --git a/litellm/llms/databricks/cost_calculator.py b/litellm/llms/databricks/cost_calculator.py
index 05647883ebf..64166e6fc11 100644
--- a/litellm/llms/databricks/cost_calculator.py
+++ b/litellm/llms/databricks/cost_calculator.py
@@ -3,10 +3,31 @@ Helper util for handling databricks-specific cost calculation
 - e.g.: handling 'dbrx-instruct-*'
 """
 
+from types import MappingProxyType
 from typing import Final
 
+from litellm.litellm_core_utils.llm_cost_calc.utils import generic_cost_per_token
 from litellm.types.utils import Usage
-from litellm.utils import get_model_info
+
+_LEGACY_ENDPOINT_NAMES: Final = MappingProxyType(
+    {
+        "dbrx-instruct": "databricks-dbrx-instruct",
+        "meta-llama-3.1-70b-instruct": "databricks-meta-llama-3-1-70b-instruct",
+        "meta-llama-3.1-405b-instruct": "databricks-meta-llama-3-1-405b-instruct",
+        "mixtral-8x7b-instruct-v0.1": "databricks-mixtral-8x7b-instruct",
+        "bge-large-en": "databricks-bge-large-en",
+        "gte-large-en": "databricks-gte-large-en",
+        "llama-2-70b-chat": "databricks-llama-2-70b-chat",
+    }
+)
+
+
+def _registry_key(model: str) -> str:
+    name: Final = model.removeprefix("databricks/")
+    return next(
+        (key for prefix, key in _LEGACY_ENDPOINT_NAMES.items() if name.startswith(prefix)),
+        name,
+    )
 
 
 def cost_per_token(model: str, usage: Usage) -> tuple[float, float]:
@@ -20,36 +41,8 @@ def cost_per_token(model: str, usage: Usage) -> tuple[float, float]:
     Returns:
         Tuple[float, float] - prompt_cost_in_usd, completion_cost_in_usd
     """
-    base_model = model
-    if model.startswith("databricks/dbrx-instruct") or model.startswith("dbrx-instruct"):
-        base_model = "databricks-dbrx-instruct"
-    elif model.startswith("databricks/meta-llama-3.1-70b-instruct") or model.startswith("meta-llama-3.1-70b-instruct"):
-        base_model = "databricks-meta-llama-3-1-70b-instruct"
-    elif model.startswith("databricks/meta-llama-3.1-405b-instruct") or model.startswith(
-        "meta-llama-3.1-405b-instruct"
-    ):
-        base_model = "databricks-meta-llama-3-1-405b-instruct"
-    elif (
-        model.startswith("databricks/mixtral-8x7b-instruct-v0.1")
-        or model.startswith("mixtral-8x7b-instruct-v0.1")
-        or model.startswith("databricks/mixtral-8x7b-instruct-v0.1")
-        or model.startswith("mixtral-8x7b-instruct-v0.1")
-    ):
-        base_model = "databricks-mixtral-8x7b-instruct"
-    elif model.startswith("databricks/bge-large-en") or model.startswith("bge-large-en"):
-        base_model = "databricks-bge-large-en"
-    elif model.startswith("databricks/gte-large-en") or model.startswith("gte-large-en"):
-        base_model = "databricks-gte-large-en"
-    elif model.startswith("databricks/llama-2-70b-chat") or model.startswith("llama-2-70b-chat"):
-        base_model = "databricks-llama-2-70b-chat"
-    ## GET MODEL INFO
-    model_info: Final = get_model_info(model=base_model, custom_llm_provider="databricks")
-
-    ## CALCULATE INPUT COST
-
-    prompt_cost: Final[float] = usage["prompt_tokens"] * model_info["input_cost_per_token"]
-
-    ## CALCULATE OUTPUT COST
-    completion_cost: Final = usage["completion_tokens"] * model_info["output_cost_per_token"]
-
-    return prompt_cost, completion_cost
+    return generic_cost_per_token(
+        model=_registry_key(model),
+        usage=usage,
+        custom_llm_provider="databricks",
+    )
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 3af7d9e5019..0bbb4b7e377 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -14566,6 +14566,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-claude-3-7-sonnet": {
+        "cache_creation_input_token_cost": 3.7499875e-06,
+        "cache_read_input_token_cost": 2.9999900000000006e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14581,10 +14583,41 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
+    "databricks/databricks-claude-fable-5": {
+        "cache_creation_input_token_cost": 1.2500075e-05,
+        "cache_read_input_token_cost": 1.0000060000000001e-06,
+        "input_cost_per_token": 1.000006e-05,
+        "input_dbu_cost_per_token": 0.000142858,
+        "litellm_provider": "databricks",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "metadata": {
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+        },
+        "mode": "chat",
+        "output_cost_per_token": 5.0000020000000004e-05,
+        "output_dbu_cost_per_token": 0.000714286,
+        "prompt_cache_min_tokens": 512,
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_function_calling": true,
+        "supports_mid_conversation_system": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "thinking_always_on": true
+    },
     "databricks/databricks-claude-haiku-4-5": {
+        "cache_creation_input_token_cost": 1.2500250000000002e-06,
+        "cache_read_input_token_cost": 1.0000200000000002e-07,
         "input_cost_per_token": 1.00002e-06,
         "input_dbu_cost_per_token": 1.4286e-05,
         "litellm_provider": "databricks",
@@ -14600,10 +14633,13 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4": {
+        "cache_creation_input_token_cost": 1.8750025e-05,
+        "cache_read_input_token_cost": 1.500002e-06,
         "input_cost_per_token": 1.5000020000000002e-05,
         "input_dbu_cost_per_token": 0.000214286,
         "litellm_provider": "databricks",
@@ -14619,10 +14655,13 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4-1": {
+        "cache_creation_input_token_cost": 1.8750025e-05,
+        "cache_read_input_token_cost": 1.500002e-06,
         "input_cost_per_token": 1.5000020000000002e-05,
         "input_dbu_cost_per_token": 0.000214286,
         "litellm_provider": "databricks",
@@ -14638,10 +14677,13 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4-5": {
+        "cache_creation_input_token_cost": 6.2500375e-06,
+        "cache_read_input_token_cost": 5.000030000000001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14657,11 +14699,14 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true,
         "supports_output_config": true
     },
     "databricks/databricks-claude-opus-4-6": {
+        "cache_creation_input_token_cost": 6.2500375e-06,
+        "cache_read_input_token_cost": 5.000030000000001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14677,10 +14722,93 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
+    "databricks/databricks-claude-opus-4-7": {
+        "cache_creation_input_token_cost": 6.2500375e-06,
+        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "input_cost_per_token": 5.00003e-06,
+        "input_dbu_cost_per_token": 7.1429e-05,
+        "litellm_provider": "databricks",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "metadata": {
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+        },
+        "mode": "chat",
+        "output_cost_per_token": 2.5000010000000002e-05,
+        "output_dbu_cost_per_token": 0.000357143,
+        "prompt_cache_min_tokens": 2048,
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "databricks/databricks-claude-opus-4-8": {
+        "cache_creation_input_token_cost": 6.2500375e-06,
+        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "input_cost_per_token": 5.00003e-06,
+        "input_dbu_cost_per_token": 7.1429e-05,
+        "litellm_provider": "databricks",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "metadata": {
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+        },
+        "mode": "chat",
+        "output_cost_per_token": 2.5000010000000002e-05,
+        "output_dbu_cost_per_token": 0.000357143,
+        "prompt_cache_min_tokens": 1024,
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_function_calling": true,
+        "supports_mid_conversation_system": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "databricks/databricks-claude-opus-5": {
+        "cache_creation_input_token_cost": 6.2500375e-06,
+        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "input_cost_per_token": 5.00003e-06,
+        "input_dbu_cost_per_token": 7.1429e-05,
+        "litellm_provider": "databricks",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "metadata": {
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+        },
+        "mode": "chat",
+        "output_cost_per_token": 2.5000010000000002e-05,
+        "output_dbu_cost_per_token": 0.000357143,
+        "prompt_cache_min_tokens": 512,
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_function_calling": true,
+        "supports_mid_conversation_system": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
     "databricks/databricks-claude-sonnet-4": {
+        "cache_creation_input_token_cost": 3.7499875e-06,
+        "cache_read_input_token_cost": 2.9999900000000006e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14696,10 +14824,13 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-4-1": {
+        "cache_creation_input_token_cost": 3.7499875e-06,
+        "cache_read_input_token_cost": 2.9999900000000006e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14715,10 +14846,13 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-4-5": {
+        "cache_creation_input_token_cost": 3.7499875e-06,
+        "cache_read_input_token_cost": 2.9999900000000006e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14734,10 +14868,13 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-4-6": {
+        "cache_creation_input_token_cost": 3.7499875e-06,
+        "cache_read_input_token_cost": 2.9999900000000006e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14753,10 +14890,40 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
+    "databricks/databricks-claude-sonnet-5": {
+        "cache_creation_input_token_cost": 2.4999625e-06,
+        "cache_read_input_token_cost": 1.9999700000000004e-07,
+        "input_cost_per_token": 1.9999700000000004e-06,
+        "input_dbu_cost_per_token": 2.8571e-05,
+        "litellm_provider": "databricks",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "metadata": {
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Claude Sonnet 5 DBU rates are Anthropic's introductory launch pricing, in effect through 2026-08-31, after which the standard Sonnet 5 rates (equal to Sonnet 4.5 / 4.6) take effect."
+        },
+        "mode": "chat",
+        "output_cost_per_token": 9.999990000000002e-06,
+        "output_dbu_cost_per_token": 0.000142857,
+        "prompt_cache_min_tokens": 1024,
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_function_calling": true,
+        "supports_mid_conversation_system": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
     "databricks/databricks-gemini-2-5-flash": {
+        "cache_creation_input_token_cost": 3.0001999999999996e-07,
+        "cache_read_input_token_cost": 3.0002e-08,
         "input_cost_per_token": 3.0001999999999996e-07,
         "input_dbu_cost_per_token": 4.285999999999999e-06,
         "litellm_provider": "databricks",
@@ -14771,9 +14938,12 @@
         "output_dbu_cost_per_token": 3.5714e-05,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-gemini-2-5-pro": {
+        "cache_creation_input_token_cost": 1.24999e-06,
+        "cache_read_input_token_cost": 1.24999e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -14788,9 +14958,12 @@
         "output_dbu_cost_per_token": 0.000142857,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-gemini-3-1-flash-lite": {
+        "cache_creation_input_token_cost": 3.1248e-07,
+        "cache_read_input_token_cost": 3.1248e-08,
         "input_cost_per_token": 3.1248e-07,
         "input_dbu_cost_per_token": 4.464e-06,
         "litellm_provider": "databricks",
@@ -14805,9 +14978,12 @@
         "output_dbu_cost_per_token": 2.6786e-05,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-gemini-3-1-pro": {
+        "cache_creation_input_token_cost": 2.49998e-06,
+        "cache_read_input_token_cost": 2.49998e-07,
         "input_cost_per_token": 2.49998e-06,
         "input_dbu_cost_per_token": 3.5714e-05,
         "litellm_provider": "databricks",
@@ -14822,9 +14998,12 @@
         "output_dbu_cost_per_token": 0.000214286,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-gemini-3-flash": {
+        "cache_creation_input_token_cost": 6.250300000000001e-07,
+        "cache_read_input_token_cost": 6.250300000000001e-08,
         "input_cost_per_token": 6.2503e-07,
         "input_dbu_cost_per_token": 8.929e-06,
         "litellm_provider": "databricks",
@@ -14839,9 +15018,12 @@
         "output_dbu_cost_per_token": 5.3571e-05,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-gemini-3-pro": {
+        "cache_creation_input_token_cost": 2.49998e-06,
+        "cache_read_input_token_cost": 2.49998e-07,
         "input_cost_per_token": 2.49998e-06,
         "input_dbu_cost_per_token": 3.5714e-05,
         "litellm_provider": "databricks",
@@ -14856,6 +15038,7 @@
         "output_dbu_cost_per_token": 0.000214286,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-gemma-3-12b": {
@@ -14874,6 +15057,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-gpt-5": {
+        "cache_creation_input_token_cost": 1.24999e-06,
+        "cache_read_input_token_cost": 1.24999e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -14886,9 +15071,12 @@
         "mode": "chat",
         "output_cost_per_token": 9.999990000000002e-06,
         "output_dbu_cost_per_token": 0.000142857,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-1": {
+        "cache_creation_input_token_cost": 1.24999e-06,
+        "cache_read_input_token_cost": 1.24999e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -14901,9 +15089,12 @@
         "mode": "chat",
         "output_cost_per_token": 9.999990000000002e-06,
         "output_dbu_cost_per_token": 0.000142857,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-1-codex-max": {
+        "cache_creation_input_token_cost": 1.24999e-06,
+        "cache_read_input_token_cost": 1.24999e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -14916,9 +15107,12 @@
         "mode": "chat",
         "output_cost_per_token": 9.999990000000002e-06,
         "output_dbu_cost_per_token": 0.000142857,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-1-codex-mini": {
+        "cache_creation_input_token_cost": 2.4997000000000006e-07,
+        "cache_read_input_token_cost": 2.4997000000000005e-08,
         "input_cost_per_token": 2.4997e-07,
         "input_dbu_cost_per_token": 3.571e-06,
         "litellm_provider": "databricks",
@@ -14931,9 +15125,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.99997e-06,
         "output_dbu_cost_per_token": 2.8571e-05,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-2": {
+        "cache_creation_input_token_cost": 1.7500000000000002e-06,
+        "cache_read_input_token_cost": 1.7500000000000002e-07,
         "input_cost_per_token": 1.75e-06,
         "input_dbu_cost_per_token": 2.5e-05,
         "litellm_provider": "databricks",
@@ -14946,9 +15143,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.4e-05,
         "output_dbu_cost_per_token": 0.0002,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-2-codex": {
+        "cache_creation_input_token_cost": 1.7500000000000002e-06,
+        "cache_read_input_token_cost": 1.7500000000000002e-07,
         "input_cost_per_token": 1.75e-06,
         "input_dbu_cost_per_token": 2.5e-05,
         "litellm_provider": "databricks",
@@ -14961,9 +15161,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.4e-05,
         "output_dbu_cost_per_token": 0.0002,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-3-codex": {
+        "cache_creation_input_token_cost": 1.7500000000000002e-06,
+        "cache_read_input_token_cost": 1.7500000000000002e-07,
         "input_cost_per_token": 1.75e-06,
         "input_dbu_cost_per_token": 2.5e-05,
         "litellm_provider": "databricks",
@@ -14976,9 +15179,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.4e-05,
         "output_dbu_cost_per_token": 0.0002,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-4": {
+        "cache_creation_input_token_cost": 2.49998e-06,
+        "cache_read_input_token_cost": 2.49998e-07,
         "input_cost_per_token": 2.49998e-06,
         "input_dbu_cost_per_token": 3.5714e-05,
         "litellm_provider": "databricks",
@@ -14991,9 +15197,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.5000020000000002e-05,
         "output_dbu_cost_per_token": 0.000214286,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-4-mini": {
+        "cache_creation_input_token_cost": 7.4998e-07,
+        "cache_read_input_token_cost": 7.499800000000001e-08,
         "input_cost_per_token": 7.4998e-07,
         "input_dbu_cost_per_token": 1.0714e-05,
         "litellm_provider": "databricks",
@@ -15006,9 +15215,12 @@
         "mode": "chat",
         "output_cost_per_token": 4.50002e-06,
         "output_dbu_cost_per_token": 6.4286e-05,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-4-nano": {
+        "cache_creation_input_token_cost": 1.9999e-07,
+        "cache_read_input_token_cost": 1.9999000000000003e-08,
         "input_cost_per_token": 1.9999e-07,
         "input_dbu_cost_per_token": 2.857e-06,
         "litellm_provider": "databricks",
@@ -15021,9 +15233,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.24999e-06,
         "output_dbu_cost_per_token": 1.7857e-05,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-mini": {
+        "cache_creation_input_token_cost": 2.4997000000000006e-07,
+        "cache_read_input_token_cost": 2.4997000000000005e-08,
         "input_cost_per_token": 2.4997000000000006e-07,
         "input_dbu_cost_per_token": 3.571e-06,
         "litellm_provider": "databricks",
@@ -15036,9 +15251,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.9999700000000004e-06,
         "output_dbu_cost_per_token": 2.8571e-05,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-nano": {
+        "cache_creation_input_token_cost": 4.998e-08,
+        "cache_read_input_token_cost": 4.998000000000001e-09,
         "input_cost_per_token": 4.998e-08,
         "input_dbu_cost_per_token": 7.14e-07,
         "litellm_provider": "databricks",
@@ -15051,7 +15269,8 @@
         "mode": "chat",
         "output_cost_per_token": 3.9998000000000007e-07,
         "output_dbu_cost_per_token": 5.714000000000001e-06,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-oss-120b": {
         "input_cost_per_token": 1.5000999999999998e-07,
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 3af7d9e5019..0bbb4b7e377 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -14566,6 +14566,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-claude-3-7-sonnet": {
+        "cache_creation_input_token_cost": 3.7499875e-06,
+        "cache_read_input_token_cost": 2.9999900000000006e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14581,10 +14583,41 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
+    "databricks/databricks-claude-fable-5": {
+        "cache_creation_input_token_cost": 1.2500075e-05,
+        "cache_read_input_token_cost": 1.0000060000000001e-06,
+        "input_cost_per_token": 1.000006e-05,
+        "input_dbu_cost_per_token": 0.000142858,
+        "litellm_provider": "databricks",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "metadata": {
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+        },
+        "mode": "chat",
+        "output_cost_per_token": 5.0000020000000004e-05,
+        "output_dbu_cost_per_token": 0.000714286,
+        "prompt_cache_min_tokens": 512,
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_function_calling": true,
+        "supports_mid_conversation_system": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "thinking_always_on": true
+    },
     "databricks/databricks-claude-haiku-4-5": {
+        "cache_creation_input_token_cost": 1.2500250000000002e-06,
+        "cache_read_input_token_cost": 1.0000200000000002e-07,
         "input_cost_per_token": 1.00002e-06,
         "input_dbu_cost_per_token": 1.4286e-05,
         "litellm_provider": "databricks",
@@ -14600,10 +14633,13 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4": {
+        "cache_creation_input_token_cost": 1.8750025e-05,
+        "cache_read_input_token_cost": 1.500002e-06,
         "input_cost_per_token": 1.5000020000000002e-05,
         "input_dbu_cost_per_token": 0.000214286,
         "litellm_provider": "databricks",
@@ -14619,10 +14655,13 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4-1": {
+        "cache_creation_input_token_cost": 1.8750025e-05,
+        "cache_read_input_token_cost": 1.500002e-06,
         "input_cost_per_token": 1.5000020000000002e-05,
         "input_dbu_cost_per_token": 0.000214286,
         "litellm_provider": "databricks",
@@ -14638,10 +14677,13 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4-5": {
+        "cache_creation_input_token_cost": 6.2500375e-06,
+        "cache_read_input_token_cost": 5.000030000000001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14657,11 +14699,14 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true,
         "supports_output_config": true
     },
     "databricks/databricks-claude-opus-4-6": {
+        "cache_creation_input_token_cost": 6.2500375e-06,
+        "cache_read_input_token_cost": 5.000030000000001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14677,10 +14722,93 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
+    "databricks/databricks-claude-opus-4-7": {
+        "cache_creation_input_token_cost": 6.2500375e-06,
+        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "input_cost_per_token": 5.00003e-06,
+        "input_dbu_cost_per_token": 7.1429e-05,
+        "litellm_provider": "databricks",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "metadata": {
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+        },
+        "mode": "chat",
+        "output_cost_per_token": 2.5000010000000002e-05,
+        "output_dbu_cost_per_token": 0.000357143,
+        "prompt_cache_min_tokens": 2048,
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "databricks/databricks-claude-opus-4-8": {
+        "cache_creation_input_token_cost": 6.2500375e-06,
+        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "input_cost_per_token": 5.00003e-06,
+        "input_dbu_cost_per_token": 7.1429e-05,
+        "litellm_provider": "databricks",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "metadata": {
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+        },
+        "mode": "chat",
+        "output_cost_per_token": 2.5000010000000002e-05,
+        "output_dbu_cost_per_token": 0.000357143,
+        "prompt_cache_min_tokens": 1024,
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_function_calling": true,
+        "supports_mid_conversation_system": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "databricks/databricks-claude-opus-5": {
+        "cache_creation_input_token_cost": 6.2500375e-06,
+        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "input_cost_per_token": 5.00003e-06,
+        "input_dbu_cost_per_token": 7.1429e-05,
+        "litellm_provider": "databricks",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "metadata": {
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+        },
+        "mode": "chat",
+        "output_cost_per_token": 2.5000010000000002e-05,
+        "output_dbu_cost_per_token": 0.000357143,
+        "prompt_cache_min_tokens": 512,
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_function_calling": true,
+        "supports_mid_conversation_system": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
     "databricks/databricks-claude-sonnet-4": {
+        "cache_creation_input_token_cost": 3.7499875e-06,
+        "cache_read_input_token_cost": 2.9999900000000006e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14696,10 +14824,13 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-4-1": {
+        "cache_creation_input_token_cost": 3.7499875e-06,
+        "cache_read_input_token_cost": 2.9999900000000006e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14715,10 +14846,13 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-4-5": {
+        "cache_creation_input_token_cost": 3.7499875e-06,
+        "cache_read_input_token_cost": 2.9999900000000006e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14734,10 +14868,13 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-4-6": {
+        "cache_creation_input_token_cost": 3.7499875e-06,
+        "cache_read_input_token_cost": 2.9999900000000006e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14753,10 +14890,40 @@
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_reasoning": true,
         "supports_tool_choice": true
     },
+    "databricks/databricks-claude-sonnet-5": {
+        "cache_creation_input_token_cost": 2.4999625e-06,
+        "cache_read_input_token_cost": 1.9999700000000004e-07,
+        "input_cost_per_token": 1.9999700000000004e-06,
+        "input_dbu_cost_per_token": 2.8571e-05,
+        "litellm_provider": "databricks",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "metadata": {
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Claude Sonnet 5 DBU rates are Anthropic's introductory launch pricing, in effect through 2026-08-31, after which the standard Sonnet 5 rates (equal to Sonnet 4.5 / 4.6) take effect."
+        },
+        "mode": "chat",
+        "output_cost_per_token": 9.999990000000002e-06,
+        "output_dbu_cost_per_token": 0.000142857,
+        "prompt_cache_min_tokens": 1024,
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_function_calling": true,
+        "supports_mid_conversation_system": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
     "databricks/databricks-gemini-2-5-flash": {
+        "cache_creation_input_token_cost": 3.0001999999999996e-07,
+        "cache_read_input_token_cost": 3.0002e-08,
         "input_cost_per_token": 3.0001999999999996e-07,
         "input_dbu_cost_per_token": 4.285999999999999e-06,
         "litellm_provider": "databricks",
@@ -14771,9 +14938,12 @@
         "output_dbu_cost_per_token": 3.5714e-05,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-gemini-2-5-pro": {
+        "cache_creation_input_token_cost": 1.24999e-06,
+        "cache_read_input_token_cost": 1.24999e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -14788,9 +14958,12 @@
         "output_dbu_cost_per_token": 0.000142857,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-gemini-3-1-flash-lite": {
+        "cache_creation_input_token_cost": 3.1248e-07,
+        "cache_read_input_token_cost": 3.1248e-08,
         "input_cost_per_token": 3.1248e-07,
         "input_dbu_cost_per_token": 4.464e-06,
         "litellm_provider": "databricks",
@@ -14805,9 +14978,12 @@
         "output_dbu_cost_per_token": 2.6786e-05,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-gemini-3-1-pro": {
+        "cache_creation_input_token_cost": 2.49998e-06,
+        "cache_read_input_token_cost": 2.49998e-07,
         "input_cost_per_token": 2.49998e-06,
         "input_dbu_cost_per_token": 3.5714e-05,
         "litellm_provider": "databricks",
@@ -14822,9 +14998,12 @@
         "output_dbu_cost_per_token": 0.000214286,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-gemini-3-flash": {
+        "cache_creation_input_token_cost": 6.250300000000001e-07,
+        "cache_read_input_token_cost": 6.250300000000001e-08,
         "input_cost_per_token": 6.2503e-07,
         "input_dbu_cost_per_token": 8.929e-06,
         "litellm_provider": "databricks",
@@ -14839,9 +15018,12 @@
         "output_dbu_cost_per_token": 5.3571e-05,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-gemini-3-pro": {
+        "cache_creation_input_token_cost": 2.49998e-06,
+        "cache_read_input_token_cost": 2.49998e-07,
         "input_cost_per_token": 2.49998e-06,
         "input_dbu_cost_per_token": 3.5714e-05,
         "litellm_provider": "databricks",
@@ -14856,6 +15038,7 @@
         "output_dbu_cost_per_token": 0.000214286,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_function_calling": true,
+        "supports_prompt_caching": true,
         "supports_tool_choice": true
     },
     "databricks/databricks-gemma-3-12b": {
@@ -14874,6 +15057,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-gpt-5": {
+        "cache_creation_input_token_cost": 1.24999e-06,
+        "cache_read_input_token_cost": 1.24999e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -14886,9 +15071,12 @@
         "mode": "chat",
         "output_cost_per_token": 9.999990000000002e-06,
         "output_dbu_cost_per_token": 0.000142857,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-1": {
+        "cache_creation_input_token_cost": 1.24999e-06,
+        "cache_read_input_token_cost": 1.24999e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -14901,9 +15089,12 @@
         "mode": "chat",
         "output_cost_per_token": 9.999990000000002e-06,
         "output_dbu_cost_per_token": 0.000142857,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-1-codex-max": {
+        "cache_creation_input_token_cost": 1.24999e-06,
+        "cache_read_input_token_cost": 1.24999e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -14916,9 +15107,12 @@
         "mode": "chat",
         "output_cost_per_token": 9.999990000000002e-06,
         "output_dbu_cost_per_token": 0.000142857,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-1-codex-mini": {
+        "cache_creation_input_token_cost": 2.4997000000000006e-07,
+        "cache_read_input_token_cost": 2.4997000000000005e-08,
         "input_cost_per_token": 2.4997e-07,
         "input_dbu_cost_per_token": 3.571e-06,
         "litellm_provider": "databricks",
@@ -14931,9 +15125,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.99997e-06,
         "output_dbu_cost_per_token": 2.8571e-05,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-2": {
+        "cache_creation_input_token_cost": 1.7500000000000002e-06,
+        "cache_read_input_token_cost": 1.7500000000000002e-07,
         "input_cost_per_token": 1.75e-06,
         "input_dbu_cost_per_token": 2.5e-05,
         "litellm_provider": "databricks",
@@ -14946,9 +15143,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.4e-05,
         "output_dbu_cost_per_token": 0.0002,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-2-codex": {
+        "cache_creation_input_token_cost": 1.7500000000000002e-06,
+        "cache_read_input_token_cost": 1.7500000000000002e-07,
         "input_cost_per_token": 1.75e-06,
         "input_dbu_cost_per_token": 2.5e-05,
         "litellm_provider": "databricks",
@@ -14961,9 +15161,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.4e-05,
         "output_dbu_cost_per_token": 0.0002,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-3-codex": {
+        "cache_creation_input_token_cost": 1.7500000000000002e-06,
+        "cache_read_input_token_cost": 1.7500000000000002e-07,
         "input_cost_per_token": 1.75e-06,
         "input_dbu_cost_per_token": 2.5e-05,
         "litellm_provider": "databricks",
@@ -14976,9 +15179,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.4e-05,
         "output_dbu_cost_per_token": 0.0002,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-4": {
+        "cache_creation_input_token_cost": 2.49998e-06,
+        "cache_read_input_token_cost": 2.49998e-07,
         "input_cost_per_token": 2.49998e-06,
         "input_dbu_cost_per_token": 3.5714e-05,
         "litellm_provider": "databricks",
@@ -14991,9 +15197,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.5000020000000002e-05,
         "output_dbu_cost_per_token": 0.000214286,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-4-mini": {
+        "cache_creation_input_token_cost": 7.4998e-07,
+        "cache_read_input_token_cost": 7.499800000000001e-08,
         "input_cost_per_token": 7.4998e-07,
         "input_dbu_cost_per_token": 1.0714e-05,
         "litellm_provider": "databricks",
@@ -15006,9 +15215,12 @@
         "mode": "chat",
         "output_cost_per_token": 4.50002e-06,
         "output_dbu_cost_per_token": 6.4286e-05,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-4-nano": {
+        "cache_creation_input_token_cost": 1.9999e-07,
+        "cache_read_input_token_cost": 1.9999000000000003e-08,
         "input_cost_per_token": 1.9999e-07,
         "input_dbu_cost_per_token": 2.857e-06,
         "litellm_provider": "databricks",
@@ -15021,9 +15233,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.24999e-06,
         "output_dbu_cost_per_token": 1.7857e-05,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-mini": {
+        "cache_creation_input_token_cost": 2.4997000000000006e-07,
+        "cache_read_input_token_cost": 2.4997000000000005e-08,
         "input_cost_per_token": 2.4997000000000006e-07,
         "input_dbu_cost_per_token": 3.571e-06,
         "litellm_provider": "databricks",
@@ -15036,9 +15251,12 @@
         "mode": "chat",
         "output_cost_per_token": 1.9999700000000004e-06,
         "output_dbu_cost_per_token": 2.8571e-05,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-nano": {
+        "cache_creation_input_token_cost": 4.998e-08,
+        "cache_read_input_token_cost": 4.998000000000001e-09,
         "input_cost_per_token": 4.998e-08,
         "input_dbu_cost_per_token": 7.14e-07,
         "litellm_provider": "databricks",
@@ -15051,7 +15269,8 @@
         "mode": "chat",
         "output_cost_per_token": 3.9998000000000007e-07,
         "output_dbu_cost_per_token": 5.714000000000001e-06,
-        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
+        "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
+        "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-oss-120b": {
         "input_cost_per_token": 1.5000999999999998e-07,
diff --git a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
new file mode 100644
index 00000000000..e2be7812c1b
--- /dev/null
+++ b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
@@ -0,0 +1,90 @@
+from typing import Final
+
+import pytest
+
+import litellm
+from litellm.llms.databricks.cost_calculator import cost_per_token
+from litellm.types.utils import Usage
+
+
+@pytest.fixture
+def local_model_cost_map(monkeypatch):
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    litellm.get_model_info.cache_clear()
+    yield
+    litellm.get_model_info.cache_clear()
+
+
+def _model_info(model: str) -> dict:
+    return litellm.get_model_info(model=model, custom_llm_provider="databricks")
+
+
+@pytest.mark.parametrize(
+    "model",
+    [
+        "databricks/databricks-claude-opus-4-8",
+        "databricks/databricks-claude-opus-5",
+        "databricks/databricks-claude-sonnet-5",
+    ],
+)
+def test_cached_tokens_bill_at_cache_rates(local_model_cost_map, model):
+    info: Final = _model_info(model)
+    usage: Final = Usage(
+        prompt_tokens=11000,
+        completion_tokens=500,
+        total_tokens=11500,
+        cache_creation_input_tokens=2000,
+        cache_read_input_tokens=8000,
+    )
+
+    prompt_cost, completion_cost = cost_per_token(model=model, usage=usage)
+
+    assert prompt_cost == pytest.approx(
+        1000 * info["input_cost_per_token"]
+        + 2000 * info["cache_creation_input_token_cost"]
+        + 8000 * info["cache_read_input_token_cost"]
+    )
+    assert completion_cost == pytest.approx(500 * info["output_cost_per_token"])
+    assert prompt_cost < 11000 * info["input_cost_per_token"]
+
+
+def test_uncached_request_bills_every_prompt_token_at_the_input_rate(local_model_cost_map):
+    model: Final = "databricks/databricks-claude-sonnet-5"
+    info: Final = _model_info(model)
+    usage: Final = Usage(prompt_tokens=1000, completion_tokens=200, total_tokens=1200)
+
+    prompt_cost, completion_cost = cost_per_token(model=model, usage=usage)
+
+    assert prompt_cost == pytest.approx(1000 * info["input_cost_per_token"])
+    assert completion_cost == pytest.approx(200 * info["output_cost_per_token"])
+
+
+def test_legacy_endpoint_names_still_resolve(local_model_cost_map):
+    info: Final = _model_info("databricks/databricks-mixtral-8x7b-instruct")
+    usage: Final = Usage(prompt_tokens=100, completion_tokens=100, total_tokens=200)
+
+    prompt_cost, completion_cost = cost_per_token(model="databricks/mixtral-8x7b-instruct-v0.1", usage=usage)
+
+    assert prompt_cost == pytest.approx(100 * info["input_cost_per_token"])
+    assert completion_cost == pytest.approx(100 * info["output_cost_per_token"])
+
+
+@pytest.mark.parametrize(
+    "model",
+    [
+        "databricks/databricks-claude-opus-4-7",
+        "databricks/databricks-claude-opus-4-8",
+        "databricks/databricks-claude-opus-5",
+        "databricks/databricks-claude-sonnet-5",
+        "databricks/databricks-claude-fable-5",
+    ],
+)
+def test_new_models_carry_cache_pricing(local_model_cost_map, model):
+    info: Final = _model_info(model)
+
+    assert info["input_cost_per_token"] > 0
+    assert info["output_cost_per_token"] > 0
+    assert info["cache_creation_input_token_cost"] == pytest.approx(1.25 * info["input_cost_per_token"], rel=1e-4)
+    assert info["cache_read_input_token_cost"] == pytest.approx(0.1 * info["input_cost_per_token"], rel=1e-4)
+    assert info["supports_prompt_caching"] is True

From 6c23f5ffba4f146f68e77a92c8eb23b6a88d904a Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 15:12:02 -0700
Subject: [PATCH 52/93] fix(databricks): price Sonnet 5 at standard rates past
 the introductory window

The introductory DBU rates run through 2026-08-31 and pricing carries no
expiry date, so a static introductory entry would undercharge by a third
from September 1 and let spend outrun enforced budgets. Ship the standard
rates, which match Sonnet 4.5 and 4.6, and keep the introductory numbers
in the entry notes.

Also give the new cost calculator tests full type annotations.
---
 ...odel_prices_and_context_window_backup.json | 14 +++++------
 model_prices_and_context_window.json          | 14 +++++------
 .../test_databricks_cost_calculator.py        | 25 +++++++++++++------
 3 files changed, 32 insertions(+), 21 deletions(-)

diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 0bbb4b7e377..e296e828b92 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -14895,20 +14895,20 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-5": {
-        "cache_creation_input_token_cost": 2.4999625e-06,
-        "cache_read_input_token_cost": 1.9999700000000004e-07,
-        "input_cost_per_token": 1.9999700000000004e-06,
-        "input_dbu_cost_per_token": 2.8571e-05,
+        "cache_creation_input_token_cost": 3.7499875e-06,
+        "cache_read_input_token_cost": 2.9999900000000006e-07,
+        "input_cost_per_token": 2.9999900000000002e-06,
+        "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
         "max_input_tokens": 1000000,
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Claude Sonnet 5 DBU rates are Anthropic's introductory launch pricing, in effect through 2026-08-31, after which the standard Sonnet 5 rates (equal to Sonnet 4.5 / 4.6) take effect."
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Anthropic's introductory launch rates (28.571 input / 142.857 output DBU) run through 2026-08-31. The standard rates listed here, equal to Sonnet 4.5 / 4.6, are used instead because pricing carries no expiry date, and undercharging past the window would let spend outrun enforced budgets."
         },
         "mode": "chat",
-        "output_cost_per_token": 9.999990000000002e-06,
-        "output_dbu_cost_per_token": 0.000142857,
+        "output_cost_per_token": 1.5000020000000002e-05,
+        "output_dbu_cost_per_token": 0.000214286,
         "prompt_cache_min_tokens": 1024,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_adaptive_thinking": true,
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 0bbb4b7e377..e296e828b92 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -14895,20 +14895,20 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-5": {
-        "cache_creation_input_token_cost": 2.4999625e-06,
-        "cache_read_input_token_cost": 1.9999700000000004e-07,
-        "input_cost_per_token": 1.9999700000000004e-06,
-        "input_dbu_cost_per_token": 2.8571e-05,
+        "cache_creation_input_token_cost": 3.7499875e-06,
+        "cache_read_input_token_cost": 2.9999900000000006e-07,
+        "input_cost_per_token": 2.9999900000000002e-06,
+        "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
         "max_input_tokens": 1000000,
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Claude Sonnet 5 DBU rates are Anthropic's introductory launch pricing, in effect through 2026-08-31, after which the standard Sonnet 5 rates (equal to Sonnet 4.5 / 4.6) take effect."
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Anthropic's introductory launch rates (28.571 input / 142.857 output DBU) run through 2026-08-31. The standard rates listed here, equal to Sonnet 4.5 / 4.6, are used instead because pricing carries no expiry date, and undercharging past the window would let spend outrun enforced budgets."
         },
         "mode": "chat",
-        "output_cost_per_token": 9.999990000000002e-06,
-        "output_dbu_cost_per_token": 0.000142857,
+        "output_cost_per_token": 1.5000020000000002e-05,
+        "output_dbu_cost_per_token": 0.000214286,
         "prompt_cache_min_tokens": 1024,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
         "supports_adaptive_thinking": true,
diff --git a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
index e2be7812c1b..9353292c668 100644
--- a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
+++ b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
@@ -1,14 +1,15 @@
+from collections.abc import Iterator
 from typing import Final
 
 import pytest
 
 import litellm
 from litellm.llms.databricks.cost_calculator import cost_per_token
-from litellm.types.utils import Usage
+from litellm.types.utils import ModelInfo, Usage
 
 
 @pytest.fixture
-def local_model_cost_map(monkeypatch):
+def local_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> Iterator[None]:
     monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
     monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
     litellm.get_model_info.cache_clear()
@@ -16,7 +17,7 @@ def local_model_cost_map(monkeypatch):
     litellm.get_model_info.cache_clear()
 
 
-def _model_info(model: str) -> dict:
+def _model_info(model: str) -> ModelInfo:
     return litellm.get_model_info(model=model, custom_llm_provider="databricks")
 
 
@@ -28,7 +29,7 @@ def _model_info(model: str) -> dict:
         "databricks/databricks-claude-sonnet-5",
     ],
 )
-def test_cached_tokens_bill_at_cache_rates(local_model_cost_map, model):
+def test_cached_tokens_bill_at_cache_rates(local_model_cost_map: None, model: str) -> None:
     info: Final = _model_info(model)
     usage: Final = Usage(
         prompt_tokens=11000,
@@ -49,7 +50,7 @@ def test_cached_tokens_bill_at_cache_rates(local_model_cost_map, model):
     assert prompt_cost < 11000 * info["input_cost_per_token"]
 
 
-def test_uncached_request_bills_every_prompt_token_at_the_input_rate(local_model_cost_map):
+def test_uncached_request_bills_every_prompt_token_at_the_input_rate(local_model_cost_map: None) -> None:
     model: Final = "databricks/databricks-claude-sonnet-5"
     info: Final = _model_info(model)
     usage: Final = Usage(prompt_tokens=1000, completion_tokens=200, total_tokens=1200)
@@ -60,7 +61,7 @@ def test_uncached_request_bills_every_prompt_token_at_the_input_rate(local_model
     assert completion_cost == pytest.approx(200 * info["output_cost_per_token"])
 
 
-def test_legacy_endpoint_names_still_resolve(local_model_cost_map):
+def test_legacy_endpoint_names_still_resolve(local_model_cost_map: None) -> None:
     info: Final = _model_info("databricks/databricks-mixtral-8x7b-instruct")
     usage: Final = Usage(prompt_tokens=100, completion_tokens=100, total_tokens=200)
 
@@ -80,7 +81,7 @@ def test_legacy_endpoint_names_still_resolve(local_model_cost_map):
         "databricks/databricks-claude-fable-5",
     ],
 )
-def test_new_models_carry_cache_pricing(local_model_cost_map, model):
+def test_new_models_carry_cache_pricing(local_model_cost_map: None, model: str) -> None:
     info: Final = _model_info(model)
 
     assert info["input_cost_per_token"] > 0
@@ -88,3 +89,13 @@ def test_new_models_carry_cache_pricing(local_model_cost_map, model):
     assert info["cache_creation_input_token_cost"] == pytest.approx(1.25 * info["input_cost_per_token"], rel=1e-4)
     assert info["cache_read_input_token_cost"] == pytest.approx(0.1 * info["input_cost_per_token"], rel=1e-4)
     assert info["supports_prompt_caching"] is True
+
+
+def test_sonnet_5_ships_standard_rates_not_introductory(local_model_cost_map: None) -> None:
+    sonnet_5: Final = _model_info("databricks/databricks-claude-sonnet-5")
+    sonnet_4_6: Final = _model_info("databricks/databricks-claude-sonnet-4-6")
+
+    assert sonnet_5["input_cost_per_token"] == pytest.approx(sonnet_4_6["input_cost_per_token"])
+    assert sonnet_5["output_cost_per_token"] == pytest.approx(sonnet_4_6["output_cost_per_token"])
+    assert sonnet_5["cache_creation_input_token_cost"] == pytest.approx(sonnet_4_6["cache_creation_input_token_cost"])
+    assert sonnet_5["cache_read_input_token_cost"] == pytest.approx(sonnet_4_6["cache_read_input_token_cost"])

From ba07340964db96120d80341f3b1a3973f0c8c3b3 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Sat, 22 Aug 2026 15:20:50 -0700
Subject: [PATCH 53/93] chore: update Next.js build artifacts (2026-08-22 22:11
 UTC, node v24.19.0) (#37976)

---
 litellm/proxy/_experimental/out/404.html      |   2 +-
 .../proxy/_experimental/out/404/index.html    |   2 +-
 .../out/__next.!KGRhc2hib2FyZCk.__PAGE__.txt  |   8 +-
 .../out/__next.!KGRhc2hib2FyZCk.txt           |  10 +-
 .../proxy/_experimental/out/__next._full.txt  |  59 ++-
 .../proxy/_experimental/out/__next._head.txt  |   8 +-
 .../proxy/_experimental/out/__next._index.txt |  17 +-
 .../proxy/_experimental/out/__next._tree.txt  |   4 +-
 .../_buildManifest.js                         |   0
 .../_clientMiddlewareManifest.js              |   0
 .../_ssgManifest.js                           |   0
 .../out/_next/static/chunks/0013wgjn81q8k.js  | 216 ---------
 .../out/_next/static/chunks/00mhzot068d2m.js  |   1 +
 .../out/_next/static/chunks/012_6ra8fo7np.js  |  10 -
 .../out/_next/static/chunks/01i10m3msnar9.js  |   1 +
 .../out/_next/static/chunks/01t0ca9m9cblp.js  |   1 +
 .../out/_next/static/chunks/01txrb6bft5s5.js  |   1 -
 .../out/_next/static/chunks/01vm1oq9am52a.js  |   7 -
 .../out/_next/static/chunks/022gv-s8rsuep.js  |   1 +
 .../out/_next/static/chunks/02a2ogfa2h8o3.js  |   8 -
 .../out/_next/static/chunks/02aj56rzfo-nr.js  |   1 +
 .../out/_next/static/chunks/02emq9hm7g5fm.js  |   1 -
 .../out/_next/static/chunks/03fte74pbliq5.js  |   1 +
 .../out/_next/static/chunks/054k4q5uh06vi.js  |   1 +
 .../out/_next/static/chunks/05qv3czmeg-cb.js  |   1 -
 .../out/_next/static/chunks/05qxpjomf8mhm.js  |   1 +
 .../out/_next/static/chunks/079c6mpwr9q3x.js  |   1 +
 .../out/_next/static/chunks/07unod8edrfqd.js  | 420 ------------------
 .../out/_next/static/chunks/07vruwfvhfop5.js  |   1 +
 .../out/_next/static/chunks/07wi_3yhi4wcx.js  |   1 -
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k=e=>"global"===e?"Global":(0,f.getProviderLogoAndName)(e).displayName,T=({marginConfig:e,onMarginChange:r,onRemoveProvider:a})=>{let[l,o]=(0,s.useState)(null),[i,d]=(0,s.useState)(""),[h,j]=(0,s.useState)(""),b=()=>{o(null),d(""),j("")},y=Object.entries(e).map(([e,t])=>({provider:e,margin:t})).sort((e,t)=>{if("global"===e.provider)return -1;if("global"===t.provider)return 1;let s=(0,f.getProviderLogoAndName)(e.provider).displayName,r=(0,f.getProviderLogoAndName)(t.provider).displayName;return s.localeCompare(r)});return(0,t.jsx)(g,{data:y,columns:[{header:"Provider",cell:e=>{if("global"===e.provider)return(0,t.jsx)("div",{className:"flex items-center space-x-2",children:(0,t.jsx)("span",{className:"font-medium",children:"Global (All Providers)"})});let{displayName:s}=(0,f.getProviderLogoAndName)(e.provider);return(0,t.jsxs)("div",{className:"flex items-center space-x-2",children:[(0,t.jsx)(v.Logo,{provider:e.provider,label:s,className:"w-5 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-    <!DOCTYPE html>
-    <html>
-    <head>
-      <title>Multi-Model Cost Estimate Report</title>
-      <style>
-        body {
-          font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
-          padding: 40px;
-          max-width: 900px;
-          margin: 0 auto;
-          color: #333;
-        }
-        h1 {
-          color: #1a1a1a;
-          border-bottom: 2px solid #1890ff;
-          padding-bottom: 10px;
-          margin-bottom: 30px;
-        }
-        h2 {
-          color: #444;
-          margin-top: 30px;
-          margin-bottom: 15px;
-        }
-        h3 {
-          color: #555;
-          margin-top: 25px;
-          margin-bottom: 10px;
-          padding-bottom: 5px;
-          border-bottom: 1px solid #eee;
-        }
-        .provider {
-          font-weight: normal;
-          color: #1890ff;
-          font-size: 14px;
-        }
-        .meta {
-          background: #f5f5f5;
-          padding: 12px 15px;
-          border-radius: 8px;
-          margin-bottom: 15px;
-          font-size: 13px;
-        }
-        .meta p {
-          margin: 4px 0;
-        }
-        table {
-          width: 100%;
-          border-collapse: collapse;
-          margin-bottom: 20px;
-        }
-        th, td {
-          padding: 10px 12px;
-          text-align: left;
-          border-bottom: 1px solid #ddd;
-        }
-        th {
-          background: #f8f9fa;
-          font-weight: 600;
-          font-size: 13px;
-        }
-        .cost-value {
-          font-family: monospace;
-          font-size: 13px;
-        }
-        .total-row {
-          font-weight: bold;
-          background: #e6f7ff;
-        }
-        .summary-box {
-          background: linear-gradient(135deg, #e6f7ff 0%, #f9f0ff 100%);
-          border: 1px solid #91d5ff;
-          border-radius: 8px;
-          padding: 20px;
-          margin-bottom: 30px;
-        }
-        .summary-box h2 {
-          margin-top: 0;
-          color: #1890ff;
-        }
-        .summary-grid {
-          display: grid;
-          grid-template-columns: repeat(3, 1fr);
-          gap: 20px;
-          margin-top: 15px;
-        }
-        .summary-item {
-          text-align: center;
-        }
-        .summary-item .label {
-          font-size: 12px;
-          color: #666;
-          margin-bottom: 5px;
-        }
-        .summary-item .value {
-          font-size: 20px;
-          font-weight: bold;
-          font-family: monospace;
-        }
-        .summary-item .value.blue { color: #1890ff; }
-        .summary-item .value.green { color: #52c41a; }
-        .summary-item .value.purple { color: #722ed1; }
-        .model-section {
-          margin-bottom: 30px;
-          page-break-inside: avoid;
-        }
-        .footer {
-          margin-top: 40px;
-          padding-top: 20px;
-          border-top: 1px solid #ddd;
-          font-size: 12px;
-          color: #666;
-        }
-        @media print {
-          body { padding: 20px; }
-          .model-section { page-break-inside: avoid; }
-        }
-      </style>
-    </head>
-    <body>
-      <h1>LLM Cost Estimate Report</h1>
-      <p style="color: #666; margin-top: -20px; margin-bottom: 30px;">${r} model${1!==r?"s":""} configured</p>
-      
-      <div class="summary-box">
-        <h2>Combined Totals</h2>
-        <div class="summary-grid">
-          <div class="summary-item">
-            <div class="label">Total Per Request</div>
-            <div class="value blue">${H(e.totals.cost_per_request)}</div>
-          </div>
-          <div class="summary-item">
-            <div class="label">Total Daily</div>
-            <div class="value green">${H(e.totals.daily_cost)}</div>
-          </div>
-          <div class="summary-item">
-            <div class="label">Total Monthly</div>
-            <div class="value purple">${H(e.totals.monthly_cost)}</div>
-          </div>
-        </div>
-        ${e.totals.margin_per_request>0?`
-        <div class="summary-grid" style="margin-top: 15px; padding-top: 15px; border-top: 1px solid #ddd;">
-          <div class="summary-item">
-            <div class="label">Margin/Request</div>
-            <div class="value" style="color: #faad14;">${H(e.totals.margin_per_request)}</div>
-          </div>
-          <div class="summary-item">
-            <div class="label">Daily Margin</div>
-            <div class="value" style="color: #faad14;">${H(e.totals.daily_margin)}</div>
-          </div>
-          <div class="summary-item">
-            <div class="label">Monthly Margin</div>
-            <div class="value" style="color: #faad14;">${H(e.totals.monthly_margin)}</div>
-          </div>
-        </div>
-        `:""}
-      </div>
-
-      <h2>Model Breakdown</h2>
-      ${s.map(e=>{let t;return t=e.result,`
-    <div class="model-section">
-      <h3>${t.model} ${t.provider?`<span class="provider">(${t.provider})</span>`:""}</h3>
-      
-      <div class="meta">
-        <p><strong>Input Tokens per Request:</strong> ${G(t.input_tokens)}</p>
-        <p><strong>Output Tokens per Request:</strong> ${G(t.output_tokens)}</p>
-        ${t.num_requests_per_day?`<p><strong>Requests per Day:</strong> ${G(t.num_requests_per_day)}</p>`:""}
-        ${t.num_requests_per_month?`<p><strong>Requests per Month:</strong> ${G(t.num_requests_per_month)}</p>`:""}
-      </div>
-
-      <table>
-        <tr>
-          <th>Cost Type</th>
-          <th>Per Request</th>
-          ${null!==t.daily_cost?"<th>Daily</th>":""}
-          ${null!==t.monthly_cost?"<th>Monthly</th>":""}
-        </tr>
-        <tr>
-          <td>Input Cost</td>
-          <td class="cost-value">${H(t.input_cost_per_request)}</td>
-          ${null!==t.daily_cost?`<td class="cost-value">${H(t.daily_input_cost)}</td>`:""}
-          ${null!==t.monthly_cost?`<td class="cost-value">${H(t.monthly_input_cost)}</td>`:""}
-        </tr>
-        <tr>
-          <td>Output Cost</td>
-          <td class="cost-value">${H(t.output_cost_per_request)}</td>
-          ${null!==t.daily_cost?`<td class="cost-value">${H(t.daily_output_cost)}</td>`:""}
-          ${null!==t.monthly_cost?`<td class="cost-value">${H(t.monthly_output_cost)}</td>`:""}
-        </tr>
-        <tr>
-          <td>Margin/Fee</td>
-          <td class="cost-value">${H(t.margin_cost_per_request)}</td>
-          ${null!==t.daily_cost?`<td class="cost-value">${H(t.daily_margin_cost)}</td>`:""}
-          ${null!==t.monthly_cost?`<td class="cost-value">${H(t.monthly_margin_cost)}</td>`:""}
-        </tr>
-        <tr class="total-row">
-          <td>Total</td>
-          <td class="cost-value">${H(t.cost_per_request)}</td>
-          ${null!==t.daily_cost?`<td class="cost-value">${H(t.daily_cost)}</td>`:""}
-          ${null!==t.monthly_cost?`<td class="cost-value">${H(t.monthly_cost)}</td>`:""}
-        </tr>
-      </table>
-    </div>
-  `}).join("")}
-
-      <div class="footer">
-        <p>Generated by LiteLLM Pricing Calculator on ${new Date().toLocaleString()}</p>
-      </div>
-    </body>
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/00mhzot068d2m.js b/litellm/proxy/_experimental/out/_next/static/chunks/00mhzot068d2m.js
new file mode 100644
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deleted file mode 100644
index c707913a033..00000000000
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/054k4q5uh06vi.js b/litellm/proxy/_experimental/out/_next/static/chunks/054k4q5uh06vi.js
new file mode 100644
index 00000000000..a131044e993
--- /dev/null
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-
-client = openai.AzureOpenAI(
-	api_key="${b||"YOUR_LITELLM_API_KEY"}",
-	azure_endpoint="${x}",
-	api_version="2024-02-01"
-)`:`import openai
-
-client = openai.OpenAI(
-	api_key="${b||"YOUR_LITELLM_API_KEY"}",
-	base_url="${x}"
-)`;switch(m){case r.CHAT:{let e=Object.keys(w).length>0,o="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();o=`,
-    extra_body=${e}`}let a=_.length>0?_:[{role:"user",content:k}];t=`
-import base64
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Example with text only
-response = client.chat.completions.create(
-    model="${j}",
-    messages=${JSON.stringify(a,null,4)}${o}
-)
-
-print(response)
-
-# Example with image or PDF (uncomment and provide file path to use)
-# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
-# response_with_file = client.chat.completions.create(
-#     model="${j}",
-#     messages=[
-#         {
-#             "role": "user",
-#             "content": [
-#                 {
-#                     "type": "text",
-#                     "text": "${v}"
-#                 },
-#                 {
-#                     "type": "image_url",
-#                     "image_url": {
-#                         "url": f"data:image/jpeg;base64,{base64_file}"  # or data:application/pdf;base64,{base64_file}
-#                     }
-#                 }
-#             ]
-#         }
-#     ]${o}
-# )
-# print(response_with_file)
-`;break}case r.RESPONSES:{let e=Object.keys(w).length>0,o="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();o=`,
-    extra_body=${e}`}let a=_.length>0?_:[{role:"user",content:k}];t=`
-import base64
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Example with text only
-response = client.responses.create(
-    model="${j}",
-    input=${JSON.stringify(a,null,4)}${o}
-)
-
-print(response.output_text)
-
-# Example with image or PDF (uncomment and provide file path to use)
-# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
-# response_with_file = client.responses.create(
-#     model="${j}",
-#     input=[
-#         {
-#             "role": "user",
-#             "content": [
-#                 {"type": "input_text", "text": "${v}"},
-#                 {
-#                     "type": "input_image",
-#                     "image_url": f"data:image/jpeg;base64,{base64_file}",  # or data:application/pdf;base64,{base64_file}
-#                 },
-#             ],
-#         }
-#     ]${o}
-# )
-# print(response_with_file.output_text)
-`;break}case r.IMAGE:t="azure"===g?`
-# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI.
-# This snippet uses 'client.images.generate' and will create a new image based on your prompt.
-# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context.
-import os
-import requests
-import json
-import time
-from PIL import Image
-
-result = client.images.generate(
-	model="${j}",
-	prompt="${n}",
-	n=1
-)
-
-json_response = json.loads(result.model_dump_json())
-
-# Set the directory for the stored image
-image_dir = os.path.join(os.curdir, 'images')
-
-# If the directory doesn't exist, create it
-if not os.path.isdir(image_dir):
-	os.mkdir(image_dir)
-
-# Initialize the image path
-image_filename = f"generated_image_{int(time.time())}.png"
-image_path = os.path.join(image_dir, image_filename)
-
-try:
-	# Retrieve the generated image
-	if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"):
-			image_url = json_response["data"][0]["url"]
-			generated_image = requests.get(image_url).content
-			with open(image_path, "wb") as image_file:
-					image_file.write(generated_image)
-
-			print(f"Image saved to {image_path}")
-			# Display the image
-			image = Image.open(image_path)
-			image.show()
-	else:
-			print("Could not find image URL in response.")
-			print("Full response:", json_response)
-except Exception as e:
-	print(f"An error occurred: {e}")
-	print("Full response:", json_response)
-`:`
-import base64
-import os
-import time
-import json
-from PIL import Image
-import requests
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-	with open(image_path, "rb") as image_file:
-			return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Helper function to create a file (simplified for this example)
-def create_file(image_path):
-	# In a real implementation, this would upload the file to OpenAI
-	# For this example, we'll just return a placeholder ID
-	return f"file_{os.path.basename(image_path).replace('.', '_')}"
-
-# The prompt entered by the user
-prompt = "${v}"
-
-# Encode images to base64
-base64_image1 = encode_image("body-lotion.png")
-base64_image2 = encode_image("soap.png")
-
-# Create file IDs
-file_id1 = create_file("body-lotion.png")
-file_id2 = create_file("incense-kit.png")
-
-response = client.responses.create(
-	model="${j}",
-	input=[
-			{
-					"role": "user",
-					"content": [
-							{"type": "input_text", "text": prompt},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image1}",
-							},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image2}",
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id1,
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id2,
-							}
-					],
-			}
-	],
-	tools=[{"type": "image_generation"}],
-)
-
-# Process the response
-image_generation_calls = [
-	output
-	for output in response.output
-	if output.type == "image_generation_call"
-]
-
-image_data = [output.result for output in image_generation_calls]
-
-if image_data:
-	image_base64 = image_data[0]
-	image_filename = f"edited_image_{int(time.time())}.png"
-	with open(image_filename, "wb") as f:
-			f.write(base64.b64decode(image_base64))
-	print(f"Image saved to {image_filename}")
-else:
-	# If no image is generated, there might be a text response with an explanation
-	text_response = [output.text for output in response.output if hasattr(output, 'text')]
-	if text_response:
-			print("No image generated. Model response:")
-			print("\\n".join(text_response))
-	else:
-			print("No image data found in response.")
-	print("Full response for debugging:")
-	print(response)
-`;break;case r.IMAGE_EDITS:t="azure"===g?`
-import base64
-import os
-import time
-import json
-from PIL import Image
-import requests
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-	with open(image_path, "rb") as image_file:
-			return base64.b64encode(image_file.read()).decode('utf-8')
-
-# The prompt entered by the user
-prompt = "${v}"
-
-# Encode images to base64
-base64_image1 = encode_image("body-lotion.png")
-base64_image2 = encode_image("soap.png")
-
-# Create file IDs
-file_id1 = create_file("body-lotion.png")
-file_id2 = create_file("incense-kit.png")
-
-response = client.responses.create(
-	model="${j}",
-	input=[
-			{
-					"role": "user",
-					"content": [
-							{"type": "input_text", "text": prompt},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image1}",
-							},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image2}",
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id1,
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id2,
-							}
-					],
-			}
-	],
-	tools=[{"type": "image_generation"}],
-)
-
-# Process the response
-image_generation_calls = [
-	output
-	for output in response.output
-	if output.type == "image_generation_call"
-]
-
-image_data = [output.result for output in image_generation_calls]
-
-if image_data:
-	image_base64 = image_data[0]
-	image_filename = f"edited_image_{int(time.time())}.png"
-	with open(image_filename, "wb") as f:
-			f.write(base64.b64decode(image_base64))
-	print(f"Image saved to {image_filename}")
-else:
-	# If no image is generated, there might be a text response with an explanation
-	text_response = [output.text for output in response.output if hasattr(output, 'text')]
-	if text_response:
-			print("No image generated. Model response:")
-			print("\\n".join(text_response))
-	else:
-			print("No image data found in response.")
-	print("Full response for debugging:")
-	print(response)
-`:`
-import base64
-import os
-import time
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-	with open(image_path, "rb") as image_file:
-			return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Helper function to create a file (simplified for this example)
-def create_file(image_path):
-	# In a real implementation, this would upload the file to OpenAI
-	# For this example, we'll just return a placeholder ID
-	return f"file_{os.path.basename(image_path).replace('.', '_')}"
-
-# The prompt entered by the user
-prompt = "${v}"
-
-# Encode images to base64
-base64_image1 = encode_image("body-lotion.png")
-base64_image2 = encode_image("soap.png")
-
-# Create file IDs
-file_id1 = create_file("body-lotion.png")
-file_id2 = create_file("incense-kit.png")
-
-response = client.responses.create(
-	model="${j}",
-	input=[
-			{
-					"role": "user",
-					"content": [
-							{"type": "input_text", "text": prompt},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image1}",
-							},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image2}",
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id1,
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id2,
-							}
-					],
-			}
-	],
-	tools=[{"type": "image_generation"}],
-)
-
-# Process the response
-image_generation_calls = [
-	output
-	for output in response.output
-	if output.type == "image_generation_call"
-]
-
-image_data = [output.result for output in image_generation_calls]
-
-if image_data:
-	image_base64 = image_data[0]
-	image_filename = f"edited_image_{int(time.time())}.png"
-	with open(image_filename, "wb") as f:
-			f.write(base64.b64decode(image_base64))
-	print(f"Image saved to {image_filename}")
-else:
-	# If no image is generated, there might be a text response with an explanation
-	text_response = [output.text for output in response.output if hasattr(output, 'text')]
-	if text_response:
-			print("No image generated. Model response:")
-			print("\\n".join(text_response))
-	else:
-			print("No image data found in response.")
-	print("Full response for debugging:")
-	print(response)
-`;break;case r.EMBEDDINGS:t=`
-response = client.embeddings.create(
-	input="${n||"Your string here"}",
-	model="${j}",
-	encoding_format="base64" # or "float"
-)
-
-print(response.data[0].embedding)
-`;break;case r.TRANSCRIPTION:t=`
-# Open the audio file
-audio_file = open("path/to/your/audio/file.mp3", "rb")
-
-# Make the transcription request
-response = client.audio.transcriptions.create(
-	model="${j}",
-	file=audio_file${n?`,
-	prompt="${n.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""}
-)
-
-print(response.text)
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var(--color-teal-300) 40%, transparent)}}.bg-cyan-500.bg-opacity-10{background-color:#00b7d71a}@supports (color:color-mix(in lab, red, red)){.bg-cyan-500.bg-opacity-10{background-color:color-mix(in oklab, var(--color-cyan-500) 10%, transparent)}}.bg-cyan-500.bg-opacity-20{background-color:#00b7d733}@supports (color:color-mix(in lab, red, red)){.bg-cyan-500.bg-opacity-20{background-color:color-mix(in oklab, var(--color-cyan-500) 20%, transparent)}}.bg-cyan-500.bg-opacity-40{background-color:#00b7d766}@supports (color:color-mix(in lab, red, red)){.bg-cyan-500.bg-opacity-40{background-color:color-mix(in oklab, var(--color-cyan-500) 40%, transparent)}}.hover\:bg-cyan-500.hover\:bg-opacity-20:hover{background-color:#00b7d733}@supports (color:color-mix(in lab, red, red)){.hover\:bg-cyan-500.hover\:bg-opacity-20:hover{background-color:color-mix(in oklab, var(--color-cyan-500) 20%, transparent)}}.group:hover .bg-cyan-500.group-hover\:bg-opacity-30{background-color:#00b7d74d}@supports 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(color:color-mix(in lab, red, red)){.ring-sky-300.ring-opacity-40{--tw-ring-color:color-mix(in oklab, var(--color-sky-300) 40%, transparent)}}.bg-blue-500.bg-opacity-10{background-color:#3080ff1a}@supports (color:color-mix(in lab, red, red)){.bg-blue-500.bg-opacity-10{background-color:color-mix(in oklab, var(--color-blue-500) 10%, transparent)}}.bg-blue-500.bg-opacity-20{background-color:#3080ff33}@supports (color:color-mix(in lab, red, red)){.bg-blue-500.bg-opacity-20{background-color:color-mix(in oklab, var(--color-blue-500) 20%, transparent)}}.bg-blue-500.bg-opacity-40{background-color:#3080ff66}@supports (color:color-mix(in lab, red, red)){.bg-blue-500.bg-opacity-40{background-color:color-mix(in oklab, var(--color-blue-500) 40%, transparent)}}.hover\:bg-blue-500.hover\:bg-opacity-20:hover{background-color:#3080ff33}@supports (color:color-mix(in lab, red, red)){.hover\:bg-blue-500.hover\:bg-opacity-20:hover{background-color:color-mix(in oklab, var(--color-blue-500) 20%, 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red)){.bg-indigo-500.bg-opacity-20{background-color:color-mix(in oklab, var(--color-indigo-500) 20%, transparent)}}.bg-indigo-500.bg-opacity-40{background-color:#625fff66}@supports (color:color-mix(in lab, red, red)){.bg-indigo-500.bg-opacity-40{background-color:color-mix(in oklab, var(--color-indigo-500) 40%, transparent)}}.hover\:bg-indigo-500.hover\:bg-opacity-20:hover{background-color:#625fff33}@supports (color:color-mix(in lab, red, red)){.hover\:bg-indigo-500.hover\:bg-opacity-20:hover{background-color:color-mix(in oklab, var(--color-indigo-500) 20%, transparent)}}.group:hover .bg-indigo-500.group-hover\:bg-opacity-30{background-color:#625fff4d}@supports (color:color-mix(in lab, red, red)){.group:hover .bg-indigo-500.group-hover\:bg-opacity-30{background-color:color-mix(in oklab, var(--color-indigo-500) 30%, transparent)}}.ring-indigo-500.ring-opacity-20{--tw-ring-color:#625fff33}@supports (color:color-mix(in lab, red, red)){.ring-indigo-500.ring-opacity-20{--tw-ring-color:color-mix(in oklab, var(--color-indigo-500) 20%, transparent)}}.ring-indigo-300.ring-opacity-40{--tw-ring-color:#a4b3ff66}@supports (color:color-mix(in lab, red, red)){.ring-indigo-300.ring-opacity-40{--tw-ring-color:color-mix(in oklab, var(--color-indigo-300) 40%, transparent)}}.bg-violet-500.bg-opacity-10{background-color:#8d54ff1a}@supports (color:color-mix(in lab, red, red)){.bg-violet-500.bg-opacity-10{background-color:color-mix(in oklab, var(--color-violet-500) 10%, transparent)}}.bg-violet-500.bg-opacity-20{background-color:#8d54ff33}@supports (color:color-mix(in lab, red, red)){.bg-violet-500.bg-opacity-20{background-color:color-mix(in oklab, var(--color-violet-500) 20%, transparent)}}.bg-violet-500.bg-opacity-40{background-color:#8d54ff66}@supports (color:color-mix(in lab, red, red)){.bg-violet-500.bg-opacity-40{background-color:color-mix(in oklab, var(--color-violet-500) 40%, transparent)}}.hover\:bg-violet-500.hover\:bg-opacity-20:hover{background-color:#8d54ff33}@supports (color:color-mix(in lab, red, red)){.hover\:bg-violet-500.hover\:bg-opacity-20:hover{background-color:color-mix(in oklab, var(--color-violet-500) 20%, transparent)}}.group:hover .bg-violet-500.group-hover\:bg-opacity-30{background-color:#8d54ff4d}@supports (color:color-mix(in lab, red, red)){.group:hover .bg-violet-500.group-hover\:bg-opacity-30{background-color:color-mix(in oklab, var(--color-violet-500) 30%, transparent)}}.ring-violet-500.ring-opacity-20{--tw-ring-color:#8d54ff33}@supports (color:color-mix(in lab, red, red)){.ring-violet-500.ring-opacity-20{--tw-ring-color:color-mix(in oklab, var(--color-violet-500) 20%, transparent)}}.ring-violet-300.ring-opacity-40{--tw-ring-color:#c4b4ff66}@supports (color:color-mix(in lab, red, red)){.ring-violet-300.ring-opacity-40{--tw-ring-color:color-mix(in oklab, var(--color-violet-300) 40%, transparent)}}.bg-purple-500.bg-opacity-10{background-color:#ac4bff1a}@supports (color:color-mix(in lab, red, red)){.bg-purple-500.bg-opacity-10{background-color:color-mix(in oklab, var(--color-purple-500) 10%, transparent)}}.bg-purple-500.bg-opacity-20{background-color:#ac4bff33}@supports (color:color-mix(in lab, red, red)){.bg-purple-500.bg-opacity-20{background-color:color-mix(in oklab, var(--color-purple-500) 20%, transparent)}}.bg-purple-500.bg-opacity-40{background-color:#ac4bff66}@supports (color:color-mix(in lab, red, red)){.bg-purple-500.bg-opacity-40{background-color:color-mix(in oklab, var(--color-purple-500) 40%, transparent)}}.hover\:bg-purple-500.hover\:bg-opacity-20:hover{background-color:#ac4bff33}@supports (color:color-mix(in lab, red, red)){.hover\:bg-purple-500.hover\:bg-opacity-20:hover{background-color:color-mix(in oklab, var(--color-purple-500) 20%, transparent)}}.group:hover .bg-purple-500.group-hover\:bg-opacity-30{background-color:#ac4bff4d}@supports (color:color-mix(in lab, red, red)){.group:hover .bg-purple-500.group-hover\:bg-opacity-30{background-color:color-mix(in oklab, var(--color-purple-500) 30%, transparent)}}.ring-purple-500.ring-opacity-20{--tw-ring-color:#ac4bff33}@supports (color:color-mix(in lab, red, red)){.ring-purple-500.ring-opacity-20{--tw-ring-color:color-mix(in oklab, var(--color-purple-500) 20%, transparent)}}.ring-purple-300.ring-opacity-40{--tw-ring-color:#d9b3ff66}@supports (color:color-mix(in lab, red, red)){.ring-purple-300.ring-opacity-40{--tw-ring-color:color-mix(in oklab, var(--color-purple-300) 40%, transparent)}}.bg-fuchsia-500.bg-opacity-10{background-color:#e12afb1a}@supports (color:color-mix(in lab, red, red)){.bg-fuchsia-500.bg-opacity-10{background-color:color-mix(in oklab, var(--color-fuchsia-500) 10%, transparent)}}.bg-fuchsia-500.bg-opacity-20{background-color:#e12afb33}@supports (color:color-mix(in lab, red, red)){.bg-fuchsia-500.bg-opacity-20{background-color:color-mix(in oklab, var(--color-fuchsia-500) 20%, transparent)}}.bg-fuchsia-500.bg-opacity-40{background-color:#e12afb66}@supports (color:color-mix(in lab, red, red)){.bg-fuchsia-500.bg-opacity-40{background-color:color-mix(in oklab, var(--color-fuchsia-500) 40%, transparent)}}.hover\:bg-fuchsia-500.hover\:bg-opacity-20:hover{background-color:#e12afb33}@supports (color:color-mix(in lab, red, red)){.hover\:bg-fuchsia-500.hover\:bg-opacity-20:hover{background-color:color-mix(in oklab, var(--color-fuchsia-500) 20%, transparent)}}.group:hover .bg-fuchsia-500.group-hover\:bg-opacity-30{background-color:#e12afb4d}@supports (color:color-mix(in lab, red, red)){.group:hover .bg-fuchsia-500.group-hover\:bg-opacity-30{background-color:color-mix(in oklab, var(--color-fuchsia-500) 30%, transparent)}}.ring-fuchsia-500.ring-opacity-20{--tw-ring-color:#e12afb33}@supports (color:color-mix(in lab, red, red)){.ring-fuchsia-500.ring-opacity-20{--tw-ring-color:color-mix(in oklab, var(--color-fuchsia-500) 20%, transparent)}}.ring-fuchsia-300.ring-opacity-40{--tw-ring-color:#f2a9ff66}@supports (color:color-mix(in lab, red, red)){.ring-fuchsia-300.ring-opacity-40{--tw-ring-color:color-mix(in oklab, var(--color-fuchsia-300) 40%, transparent)}}.bg-pink-500.bg-opacity-10{background-color:#f6339a1a}@supports (color:color-mix(in lab, red, red)){.bg-pink-500.bg-opacity-10{background-color:color-mix(in oklab, var(--color-pink-500) 10%, transparent)}}.bg-pink-500.bg-opacity-20{background-color:#f6339a33}@supports (color:color-mix(in lab, red, red)){.bg-pink-500.bg-opacity-20{background-color:color-mix(in oklab, var(--color-pink-500) 20%, transparent)}}.bg-pink-500.bg-opacity-40{background-color:#f6339a66}@supports (color:color-mix(in lab, red, red)){.bg-pink-500.bg-opacity-40{background-color:color-mix(in oklab, var(--color-pink-500) 40%, transparent)}}.hover\:bg-pink-500.hover\:bg-opacity-20:hover{background-color:#f6339a33}@supports (color:color-mix(in lab, red, red)){.hover\:bg-pink-500.hover\:bg-opacity-20:hover{background-color:color-mix(in oklab, var(--color-pink-500) 20%, transparent)}}.group:hover .bg-pink-500.group-hover\:bg-opacity-30{background-color:#f6339a4d}@supports (color:color-mix(in lab, red, red)){.group:hover .bg-pink-500.group-hover\:bg-opacity-30{background-color:color-mix(in oklab, var(--color-pink-500) 30%, transparent)}}.ring-pink-500.ring-opacity-20{--tw-ring-color:#f6339a33}@supports (color:color-mix(in lab, red, red)){.ring-pink-500.ring-opacity-20{--tw-ring-color:color-mix(in oklab, var(--color-pink-500) 20%, transparent)}}.ring-pink-300.ring-opacity-40{--tw-ring-color:#fda5d566}@supports (color:color-mix(in lab, red, red)){.ring-pink-300.ring-opacity-40{--tw-ring-color:color-mix(in oklab, var(--color-pink-300) 40%, transparent)}}.bg-rose-500.bg-opacity-10{background-color:#ff23571a}@supports (color:color-mix(in lab, red, red)){.bg-rose-500.bg-opacity-10{background-color:color-mix(in oklab, var(--color-rose-500) 10%, transparent)}}.bg-rose-500.bg-opacity-20{background-color:#ff235733}@supports (color:color-mix(in lab, red, red)){.bg-rose-500.bg-opacity-20{background-color:color-mix(in oklab, var(--color-rose-500) 20%, transparent)}}.bg-rose-500.bg-opacity-40{background-color:#ff235766}@supports (color:color-mix(in lab, red, red)){.bg-rose-500.bg-opacity-40{background-color:color-mix(in oklab, var(--color-rose-500) 40%, transparent)}}.hover\:bg-rose-500.hover\:bg-opacity-20:hover{background-color:#ff235733}@supports (color:color-mix(in lab, red, red)){.hover\:bg-rose-500.hover\:bg-opacity-20:hover{background-color:color-mix(in oklab, var(--color-rose-500) 20%, transparent)}}.group:hover .bg-rose-500.group-hover\:bg-opacity-30{background-color:#ff23574d}@supports (color:color-mix(in lab, red, red)){.group:hover .bg-rose-500.group-hover\:bg-opacity-30{background-color:color-mix(in oklab, var(--color-rose-500) 30%, transparent)}}.ring-rose-500.ring-opacity-20{--tw-ring-color:#ff235733}@supports (color:color-mix(in lab, red, red)){.ring-rose-500.ring-opacity-20{--tw-ring-color:color-mix(in oklab, var(--color-rose-500) 20%, transparent)}}.ring-rose-300.ring-opacity-40{--tw-ring-color:#ffa2ae66}@supports (color:color-mix(in lab, red, red)){.ring-rose-300.ring-opacity-40{--tw-ring-color:color-mix(in oklab, var(--color-rose-300) 40%, transparent)}}}@property --tw-animation-delay{syntax:"*";inherits:false;initial-value:0s}@property --tw-animation-direction{syntax:"*";inherits:false;initial-value:normal}@property --tw-animation-duration{syntax:"*";inherits:false}@property --tw-animation-fill-mode{syntax:"*";inherits:false;initial-value:none}@property --tw-animation-iteration-count{syntax:"*";inherits:false;initial-value:1}@property --tw-enter-blur{syntax:"*";inherits:false;initial-value:0}@property --tw-enter-opacity{syntax:"*";inherits:false;initial-value:1}@property --tw-enter-rotate{syntax:"*";inherits:false;initial-value:0}@property --tw-enter-scale{syntax:"*";inherits:false;initial-value:1}@property --tw-enter-translate-x{syntax:"*";inherits:false;initial-value:0}@property --tw-enter-translate-y{syntax:"*";inherits:false;initial-value:0}@property --tw-exit-blur{syntax:"*";inherits:false;initial-value:0}@property --tw-exit-opacity{syntax:"*";inherits:false;initial-value:1}@property --tw-exit-rotate{syntax:"*";inherits:false;initial-value:0}@property --tw-exit-scale{syntax:"*";inherits:false;initial-value:1}@property --tw-exit-translate-x{syntax:"*";inherits:false;initial-value:0}@property --tw-exit-translate-y{syntax:"*";inherits:false;initial-value:0}@property --scroll-fade-e{syntax:"<length-percentage>";inherits:false;initial-value:0}@property 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new file mode 100644
index 00000000000..63345d706d7
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0dcwq2i45vhog.js b/litellm/proxy/_experimental/out/_next/static/chunks/0dcwq2i45vhog.js
deleted file mode 100644
index 12d0b03ce6d..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0dcwq2i45vhog.js
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-Decisions made and their rationale
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-4. Next Steps
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-Priority order if multiple steps remain
-5. Context to Preserve
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-Domain-specific details that aren't obvious
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r>=0&&s.splice(r,1),this}once(e,t){return(tX(this,ee,"f")[e]||(tX(this,ee,"f")[e]=[])).push({listener:t,once:!0}),this}emitted(e){return new Promise((t,s)=>{tK(this,ea,!0,"f"),"error"!==e&&this.once("error",s),this.once(e,t)})}async done(){tK(this,ea,!0,"f"),await tX(this,Y,"f")}get currentMessage(){return tX(this,H,"f")}async finalMessage(){return await this.done(),tX(this,V,"m",eo).call(this)}async finalText(){return await this.done(),tX(this,V,"m",ec).call(this)}_emit(e,...t){if(tX(this,et,"f"))return;"end"===e&&(tK(this,et,!0,"f"),tX(this,Q,"f").call(this));let s=tX(this,ee,"f")[e];if(s&&(tX(this,ee,"f")[e]=s.filter(e=>!e.once),s.forEach(({listener:e})=>e(...t))),"abort"===e){let e=t[0];tX(this,ea,"f")||s?.length||Promise.reject(e),tX(this,X,"f").call(this,e),tX(this,Z,"f").call(this,e),this._emit("end");return}if("error"===e){let e=t[0];tX(this,ea,"f")||s?.length||Promise.reject(e),tX(this,X,"f").call(this,e),tX(this,Z,"f").call(this,e),this._emit("end")}}_emitFinal(){this.receivedMessages.at(-1)&&this._emit("finalMessage",tX(this,V,"m",eo).call(this))}async _fromReadableStream(e,t){let s,r=t?.signal;r&&(r.aborted&&this.controller.abort(),s=this.controller.abort.bind(this.controller),r.addEventListener("abort",s));try{tX(this,V,"m",eu).call(this),this._connected(null);let t=sT.fromReadableStream(e,this.controller);for await(let e of t)tX(this,V,"m",em).call(this,e);if(t.controller.signal?.aborted)throw new t2;tX(this,V,"m",eh).call(this)}finally{r&&s&&r.removeEventListener("abort",s)}}[(H=new WeakMap,G=new WeakMap,J=new WeakMap,K=new WeakMap,X=new WeakMap,Y=new WeakMap,Q=new WeakMap,Z=new WeakMap,ee=new WeakMap,et=new WeakMap,es=new WeakMap,er=new WeakMap,ea=new WeakMap,en=new WeakMap,ei=new WeakMap,el=new WeakMap,ed=new WeakMap,V=new WeakSet,eo=function(){if(0===this.receivedMessages.length)throw new t0("stream ended without producing a Message with role=assistant");return this.receivedMessages.at(-1)},ec=function(){if(0===this.receivedMessages.length)throw new t0("stream ended without producing a Message with role=assistant");let e=this.receivedMessages.at(-1).content.filter(e=>"text"===e.type).map(e=>e.text);if(0===e.length)throw new t0("stream ended without producing a content block with type=text");return e.join(" ")},eu=function(){this.ended||tK(this,H,void 0,"f")},em=function(e){if(this.ended)return;let t=tX(this,V,"m",ep).call(this,e);switch(this._emit("streamEvent",e,t),e.type){case"content_block_delta":{let s=t.content.at(-1);switch(e.delta.type){case"text_delta":"text"===s.type&&this._emit("text",e.delta.text,s.text||"");break;case"citations_delta":"text"===s.type&&this._emit("citation",e.delta.citation,s.citations??[]);break;case"input_json_delta":rU(s)&&s.input&&this._emit("inputJson",e.delta.partial_json,s.input);break;case"thinking_delta":"thinking"===s.type&&this._emit("thinking",e.delta.thinking,s.thinking);break;case"signature_delta":"thinking"===s.type&&this._emit("signature",s.signature);break;default:rB(e.delta)}break}case"message_stop":this._addMessageParam(t),this._addMessage(r$(t,tX(this,G,"f"),{logger:tX(this,el,"f")}),!0);break;case"content_block_stop":this._emit("contentBlock",t.content.at(-1));break;case"message_start":tK(this,H,t,"f")}},eh=function(){if(this.ended)throw new t0("stream has ended, this shouldn't happen");let e=tX(this,H,"f");if(!e)throw new t0("request ended without sending any chunks");return tK(this,H,void 0,"f"),r$(e,tX(this,G,"f"),{logger:tX(this,el,"f")})},ep=function(e){let t=tX(this,H,"f");if("message_start"===e.type){if(t)throw new t0(`Unexpected event order, got ${e.type} before receiving "message_stop"`);return e.message}if(!t)throw new t0(`Unexpected event order, got ${e.type} before "message_start"`);switch(e.type){case"message_stop":case"content_block_stop":return t;case"message_delta":return t.stop_reason=e.delta.stop_reason,t.stop_sequence=e.delta.stop_sequence,t.usage.output_tokens=e.usage.output_tokens,null!=e.usage.input_tokens&&(t.usage.input_tokens=e.usage.input_tokens),null!=e.usage.cache_creation_input_tokens&&(t.usage.cache_creation_input_tokens=e.usage.cache_creation_input_tokens),null!=e.usage.cache_read_input_tokens&&(t.usage.cache_read_input_tokens=e.usage.cache_read_input_tokens),null!=e.usage.server_tool_use&&(t.usage.server_tool_use=e.usage.server_tool_use),t;case"content_block_start":return t.content.push({...e.content_block}),t;case"content_block_delta":{let s=t.content.at(e.index);switch(e.delta.type){case"text_delta":s?.type==="text"&&(t.content[e.index]={...s,text:(s.text||"")+e.delta.text});break;case"citations_delta":s?.type==="text"&&(t.content[e.index]={...s,citations:[...s.citations??[],e.delta.citation]});break;case"input_json_delta":if(s&&rU(s)){let r=s[rL]||"";r+=e.delta.partial_json;let a={...s};Object.defineProperty(a,rL,{value:r,enumerable:!1,writable:!0}),r&&(a.input=rm(r)),t.content[e.index]=a}break;case"thinking_delta":s?.type==="thinking"&&(t.content[e.index]={...s,thinking:s.thinking+e.delta.thinking});break;case"signature_delta":s?.type==="thinking"&&(t.content[e.index]={...s,signature:e.delta.signature});break;default:rB(e.delta)}return t}}},Symbol.asyncIterator)](){let e=[],t=[],s=!1;return this.on("streamEvent",s=>{let r=t.shift();r?r.resolve(s):e.push(s)}),this.on("end",()=>{for(let e of(s=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let r of(s=!0,t))r.reject(e);t.length=0}),this.on("error",e=>{for(let r of(s=!0,t))r.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:s?{value:void 0,done:!0}:new Promise((e,s)=>t.push({resolve:e,reject:s})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}toReadableStream(){return new sT(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}}function rB(e){}class rz extends sX{create(e,t){return this._client.post("/v1/messages/batches",{body:e,...t})}retrieve(e,t){return this._client.get(s1`/v1/messages/batches/${e}`,t)}list(e={},t){return this._client.getAPIList("/v1/messages/batches",sL,{query:e,...t})}delete(e,t){return this._client.delete(s1`/v1/messages/batches/${e}`,t)}cancel(e,t){return this._client.post(s1`/v1/messages/batches/${e}/cancel`,t)}async results(e,t){let s=await this.retrieve(e);if(!s.results_url)throw new t0(`No batch \`results_url\`; Has it finished processing? ${s.processing_status} - ${s.id}`);return this._client.get(s.results_url,{...t,headers:sQ([{Accept:"application/binary"},t?.headers]),stream:!0,__binaryResponse:!0})._thenUnwrap((e,t)=>rn.fromResponse(t.response,t.controller))}}class rq extends sX{constructor(){super(...arguments),this.batches=new rz(this._client)}create(e,t){e.model in rF&&console.warn(`The model '${e.model}' is deprecated and will reach end-of-life on ${rF[e.model]}
-Please migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.`),rW.includes(e.model)&&e.thinking&&"enabled"===e.thinking.type&&console.warn(`Using Claude with ${e.model} and 'thinking.type=enabled' is deprecated. Use 'thinking.type=adaptive' instead which results in better model performance in our testing: https://platform.claude.com/docs/en/build-with-claude/adaptive-thinking`);let s=this._client._options.timeout;if(!e.stream&&null==s){let t=rl[e.model]??void 0;s=this._client.calculateNonstreamingTimeout(e.max_tokens,t)}let r=s6(e.tools,e.messages);return this._client.post("/v1/messages",{body:e,timeout:s??6e5,...t,headers:sQ([r,t?.headers]),stream:e.stream??!1})}parse(e,t){return this.create(e,t).then(t=>rO(t,e,{logger:this._client.logger??console}))}stream(e,t){return rD.createMessage(this,e,t,{logger:this._client.logger??console})}countTokens(e,t){return this._client.post("/v1/messages/count_tokens",{body:e,...t})}}let rF={"claude-1.3":"November 6th, 2024","claude-1.3-100k":"November 6th, 2024","claude-instant-1.1":"November 6th, 2024","claude-instant-1.1-100k":"November 6th, 2024","claude-instant-1.2":"November 6th, 2024","claude-3-sonnet-20240229":"July 21st, 2025","claude-3-opus-20240229":"January 5th, 2026","claude-2.1":"July 21st, 2025","claude-2.0":"July 21st, 2025","claude-3-7-sonnet-latest":"February 19th, 2026","claude-3-7-sonnet-20250219":"February 19th, 2026","claude-3-5-haiku-latest":"February 19th, 2026","claude-3-5-haiku-20241022":"February 19th, 2026","claude-opus-4-0":"June 15th, 2026","claude-opus-4-20250514":"June 15th, 2026","claude-sonnet-4-0":"June 15th, 2026","claude-sonnet-4-20250514":"June 15th, 2026"},rW=["claude-mythos-preview","claude-opus-4-6"];rq.Batches=rz;class rV extends sX{retrieve(e,t={},s){let{betas:r}=t??{};return this._client.get(s1`/v1/models/${e}`,{...s,headers:sQ([{...r?.toString()!=null?{"anthropic-beta":r?.toString()}:void 0},s?.headers])})}list(e={},t){let{betas:s,...r}=e??{};return this._client.getAPIList("/v1/models",sL,{query:r,...t,headers:sQ([{...s?.toString()!=null?{"anthropic-beta":s?.toString()}:void 0},t?.headers])})}}class rH extends sX{create(e,t){let{betas:s,...r}=e;return this._client.post("/v1/complete",{body:r,timeout:this._client._options.timeout??6e5,...t,headers:sQ([{...s?.toString()!=null?{"anthropic-beta":s?.toString()}:void 0},t?.headers]),stream:e.stream??!1})}}let rG=e=>void 0!==globalThis.process?globalThis.process.env?.[e]?.trim()||void 0:void 0!==globalThis.Deno&&globalThis.Deno.env?.get?.(e)?.trim()||void 0;class rJ{constructor({baseURL:e=rG("ANTHROPIC_BASE_URL"),apiKey:t=rG("ANTHROPIC_API_KEY")??null,authToken:s=rG("ANTHROPIC_AUTH_TOKEN")??null,...r}={}){eg.add(this),ex.set(this,void 0);const a={apiKey:t,authToken:s,...r,baseURL:e||"https://api.anthropic.com"};if(!a.dangerouslyAllowBrowser&&"u">typeof window&&void 0!==window.document&&"u">typeof navigator)throw new t0("It looks like you're running in a browser-like environment.\n\nThis is disabled by default, as it risks exposing your secret API credentials to attackers.\nIf you understand the risks and have appropriate mitigations in place,\nyou can set the `dangerouslyAllowBrowser` option to `true`, e.g.,\n\nnew Anthropic({ apiKey, dangerouslyAllowBrowser: true });\n");this.baseURL=a.baseURL,this.timeout=a.timeout??ef.DEFAULT_TIMEOUT,this.logger=a.logger??console;const n="warn";this.logLevel=n,this.logLevel=sj(a.logLevel,"ClientOptions.logLevel",this)??sj(rG("ANTHROPIC_LOG"),"process.env['ANTHROPIC_LOG']",this)??n,this.fetchOptions=a.fetchOptions,this.maxRetries=a.maxRetries??2,this.fetch=a.fetch??function(){if("u">typeof fetch)return fetch;throw Error("`fetch` is not defined as a global; Either pass `fetch` to the client, `new Anthropic({ fetch })` or polyfill the global, `globalThis.fetch = fetch`")}(),tK(this,ex,sf,"f");const i=rG("ANTHROPIC_CUSTOM_HEADERS");if(i){const e={};for(const t of i.split("\n")){const s=t.indexOf(":");s>=0&&(e[t.substring(0,s).trim()]=t.substring(s+1).trim())}a.defaultHeaders={...e,...a.defaultHeaders}}this._options=a,this.apiKey="string"==typeof t?t:null,this.authToken=s}withOptions(e){return new this.constructor({...this._options,baseURL:this.baseURL,maxRetries:this.maxRetries,timeout:this.timeout,logger:this.logger,logLevel:this.logLevel,fetch:this.fetch,fetchOptions:this.fetchOptions,apiKey:this.apiKey,authToken:this.authToken,...e})}defaultQuery(){return this._options.defaultQuery}validateHeaders({values:e,nulls:t}){if(!(e.get("x-api-key")||e.get("authorization")||this.apiKey&&e.get("x-api-key")||t.has("x-api-key")||this.authToken&&e.get("authorization"))&&!t.has("authorization"))throw Error('Could not resolve authentication method. 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If you need to pass nested query parameters, you can manually encode them, e.g. { query: { 'foo[key1]': value1, 'foo[key2]': value2 } }, and please open a GitHub issue requesting better support for your use case.`)}).join("&")}getUserAgent(){return`${this.constructor.name}/JS ${sc}`}defaultIdempotencyKey(){return`stainless-node-retry-${tY()}`}makeStatusError(e,t,s,r){return t1.generate(e,t,s,r)}buildURL(e,t,s){let r=!tX(this,eg,"m",ey).call(this)&&s||this.baseURL,a=new URL(sr.test(e)?e:r+(r.endsWith("/")&&e.startsWith("/")?e.slice(1):e)),n=this.defaultQuery(),i=Object.fromEntries(a.searchParams);return sl(n)&&sl(i)||(t={...i,...n,...t}),"object"==typeof t&&t&&!Array.isArray(t)&&(a.search=this.stringifyQuery(t)),a.toString()}_calculateNonstreamingTimeout(e){if(3600*e/128e3>600)throw new t0("Streaming is required for operations that may take longer than 10 minutes. 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--- a/litellm/proxy/_experimental/out/_next/static/chunks/0dvq9v45hkxnf.js
+++ /dev/null
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+        if (${i}.issues.length) {
+          if (input[${a}] === undefined) {
+            if (${a} in input) {
+              newResult[${a}] = undefined;
+            }
+          } else {
+            payload.issues = payload.issues.concat(
+              ${i}.issues.map((iss) => ({
+                ...iss,
+                path: iss.path ? [${a}, ...iss.path] : [${a}],
+              }))
+            );
+          }
+        } else if (${i}.value === undefined) {
+          if (${a} in input) newResult[${a}] = undefined;
+        } else {
+          newResult[${a}] = ${i}.value;
+        }
+        `)}else{let i=n[e];t.write(`const ${i} = ${r(e)};`),t.write(`
+          if (${i}.issues.length) payload.issues = payload.issues.concat(${i}.issues.map(iss => ({
+            ...iss,
+            path: iss.path ? [${V.esc(e)}, ...iss.path] : [${V.esc(e)}]
+          })));`),t.write(`newResult[${V.esc(e)}] = ${i}.value`)}t.write("payload.value = newResult;"),t.write("return payload;");let u=t.compile();return(t,i)=>u(e,t,i)})(i.shape)),t=r(t,s);else{t.value={};let e=n.shape;for(let i of n.keys){let r=e[i],n=r._zod.run({value:d[i],issues:[]},s),a="optional"===r._zod.optin&&"optional"===r._zod.optout;n instanceof Promise?m.push(n.then(e=>a?e3(e,t,i,d):e9(e,t,i))):a?e3(n,t,i,d):e9(n,t,i)}}if(!c)return m.length?Promise.all(m).then(()=>t):t;let f=[],p=n.keySet,v=c._zod,g=v.def.type;for(let e of Object.keys(d)){if(p.has(e))continue;if("never"===g){f.push(e);continue}let i=v.run({value:d[e],issues:[]},s);i instanceof Promise?m.push(i.then(i=>e9(i,t,e))):e9(i,t,e)}return(f.length&&t.issues.push({code:"unrecognized_keys",keys:f,input:d,inst:e}),m.length)?Promise.all(m).then(()=>t):t}});function e5(e,i,r,n){for(let t of e)if(0===t.issues.length)return i.value=t.value,i;return i.issues.push({code:"invalid_union",input:i.value,inst:r,errors:e.map(e=>e.issues.map(e=>V.finalizeIssue(e,n,t.config())))}),i}let e8=t.$constructor("$ZodUnion",(e,t)=>{ep.init(e,t),V.defineLazy(e._zod,"optin",()=>t.options.some(e=>"optional"===e._zod.optin)?"optional":void 0),V.defineLazy(e._zod,"optout",()=>t.options.some(e=>"optional"===e._zod.optout)?"optional":void 0),V.defineLazy(e._zod,"values",()=>{if(t.options.every(e=>e._zod.values))return new Set(t.options.flatMap(e=>Array.from(e._zod.values)))}),V.defineLazy(e._zod,"pattern",()=>{if(t.options.every(e=>e._zod.pattern)){let e=t.options.map(e=>e._zod.pattern);return RegExp(`^(${e.map(e=>V.cleanRegex(e.source)).join("|")})$`)}}),e._zod.parse=(i,r)=>{let n=!1,a=[];for(let e of t.options){let t=e._zod.run({value:i.value,issues:[]},r);if(t instanceof Promise)a.push(t),n=!0;else{if(0===t.issues.length)return t;a.push(t)}}return n?Promise.all(a).then(t=>e5(t,i,e,r)):e5(a,i,e,r)}}),te=t.$constructor("$ZodDiscriminatedUnion",(e,t)=>{e8.init(e,t);let i=e._zod.parse;V.defineLazy(e._zod,"propValues",()=>{let e={};for(let i of t.options){let r=i._zod.propValues;if(!r||0===Object.keys(r).length)throw Error(`Invalid discriminated union option at index "${t.options.indexOf(i)}"`);for(let[t,i]of Object.entries(r))for(let r of(e[t]||(e[t]=new Set),i))e[t].add(r)}return e});let r=V.cached(()=>{let e=t.options,i=new Map;for(let r of e){let e=r._zod.propValues[t.discriminator];if(!e||0===e.size)throw Error(`Invalid discriminated union option at index "${t.options.indexOf(r)}"`);for(let t of e){if(i.has(t))throw Error(`Duplicate discriminator value "${String(t)}"`);i.set(t,r)}}return i});e._zod.parse=(n,a)=>{let o=n.value;if(!V.isObject(o))return n.issues.push({code:"invalid_type",expected:"object",input:o,inst:e}),n;let u=r.value.get(o?.[t.discriminator]);return u?u._zod.run(n,a):t.unionFallback?i(n,a):(n.issues.push({code:"invalid_union",errors:[],note:"No matching discriminator",input:o,path:[t.discriminator],inst:e}),n)}}),tt=t.$constructor("$ZodIntersection",(e,t)=>{ep.init(e,t),e._zod.parse=(e,i)=>{let r=e.value,n=t.left._zod.run({value:r,issues:[]},i),a=t.right._zod.run({value:r,issues:[]},i);return n instanceof Promise||a instanceof Promise?Promise.all([n,a]).then(([t,i])=>ti(e,t,i)):ti(e,n,a)}});function ti(e,t,i){if(t.issues.length&&e.issues.push(...t.issues),i.issues.length&&e.issues.push(...i.issues),V.aborted(e))return e;let r=function e(t,i){if(t===i||t instanceof Date&&i instanceof Date&&+t==+i)return{valid:!0,data:t};if(V.isPlainObject(t)&&V.isPlainObject(i)){let r=Object.keys(i),n=Object.keys(t).filter(e=>-1!==r.indexOf(e)),a={...t,...i};for(let r of n){let n=e(t[r],i[r]);if(!n.valid)return{valid:!1,mergeErrorPath:[r,...n.mergeErrorPath]};a[r]=n.data}return{valid:!0,data:a}}if(Array.isArray(t)&&Array.isArray(i)){if(t.length!==i.length)return{valid:!1,mergeErrorPath:[]};let r=[];for(let n=0;n<t.length;n++){let a=e(t[n],i[n]);if(!a.valid)return{valid:!1,mergeErrorPath:[n,...a.mergeErrorPath]};r.push(a.data)}return{valid:!0,data:r}}return{valid:!1,mergeErrorPath:[]}}(t.value,i.value);if(!r.valid)throw Error(`Unmergable intersection. 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tN=e.i(922143),tD=e.i(682358);function tE(e,t,i,r){let n=Math.abs(e),a=n%10,o=n%100;return o>=11&&o<=19?r:1===a?t:a>=2&&a<=4?i:r}e.s([],543365),e.i(543365);var tT=e.i(40824);function tA(e,t,i,r){let n=Math.abs(e),a=n%10,o=n%100;return o>=11&&o<=19?r:1===a?t:a>=2&&a<=4?i:r}e.s(["ar",0,function(){let e,t;return{localeError:(e={string:{unit:"حرف",verb:"أن يحوي"},file:{unit:"بايت",verb:"أن يحوي"},array:{unit:"عنصر",verb:"أن يحوي"},set:{unit:"عنصر",verb:"أن يحوي"}},t={regex:"مدخل",email:"بريد إلكتروني",url:"رابط",emoji:"إيموجي",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"تاريخ ووقت بمعيار ISO",date:"تاريخ بمعيار ISO",time:"وقت بمعيار ISO",duration:"مدة بمعيار ISO",ipv4:"عنوان IPv4",ipv6:"عنوان IPv6",cidrv4:"مدى عناوين بصيغة IPv4",cidrv6:"مدى عناوين بصيغة IPv6",base64:"نَص بترميز base64-encoded",base64url:"نَص بترميز base64url-encoded",json_string:"نَص على هيئة JSON",e164:"رقم هاتف بمعيار 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e,t;return{localeError:(e={string:{unit:"caràcters",verb:"contenir"},file:{unit:"bytes",verb:"contenir"},array:{unit:"elements",verb:"contenir"},set:{unit:"elements",verb:"contenir"}},t={regex:"entrada",email:"adreça electrònica",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i hora ISO",date:"data ISO",time:"hora ISO",duration:"durada ISO",ipv4:"adreça IPv4",ipv6:"adreça IPv6",cidrv4:"rang IPv4",cidrv6:"rang IPv6",base64:"cadena codificada en base64",base64url:"cadena codificada en base64url",json_string:"cadena JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Tipus inv\xe0lid: s'esperava ${i.expected}, s'ha rebut ${(e=>{let t=typeof e;switch(t){case"number":return 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"${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.suffix}" enden`;if("includes"===i.format)return`Ung\xfcltiger String: muss "${i.includes}" enthalten`;if("regex"===i.format)return`Ung\xfcltiger String: muss dem Muster ${i.pattern} entsprechen`;return`Ung\xfcltig: ${t[i.format]??i.format}`;case"not_multiple_of":return`Ung\xfcltige Zahl: muss ein Vielfaches von ${i.divisor} sein`;case"unrecognized_keys":return`${i.keys.length>1?"Unbekannte Schlüssel":"Unbekannter Schlüssel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ung\xfcltiger Schl\xfcssel in ${i.origin}`;case"invalid_union":default:return"Ungültige Eingabe";case"invalid_element":return`Ung\xfcltiger Wert in ${i.origin}`}})}},"en",()=>tT.default,"eo",0,function(){let e,t;return{localeError:(e={string:{unit:"karaktrojn",verb:"havi"},file:{unit:"bajtojn",verb:"havi"},array:{unit:"elementojn",verb:"havi"},set:{unit:"elementojn",verb:"havi"}},t={regex:"enigo",email:"retadreso",url:"URL",emoji:"emoĝio",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datotempo",date:"ISO-dato",time:"ISO-tempo",duration:"ISO-daŭro",ipv4:"IPv4-adreso",ipv6:"IPv6-adreso",cidrv4:"IPv4-rango",cidrv6:"IPv6-rango",base64:"64-ume kodita karaktraro",base64url:"URL-64-ume kodita karaktraro",json_string:"JSON-karaktraro",e164:"E.164-nombro",jwt:"JWT",template_literal:"enigo"},i=>{switch(i.code){case"invalid_type":return`Nevalida enigo: atendiĝis ${i.expected}, riceviĝis ${(e=>{let t=typeof e;switch(t){case"number":return 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electrónico",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"fecha y hora ISO",date:"fecha ISO",time:"hora ISO",duration:"duración ISO",ipv4:"dirección IPv4",ipv6:"dirección IPv6",cidrv4:"rango IPv4",cidrv6:"rango IPv6",base64:"cadena codificada en base64",base64url:"URL codificada en base64",json_string:"cadena JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Entrada inv\xe1lida: se esperaba ${i.expected}, recibido ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"número";case"object":if(Array.isArray(e))return"arreglo";if(null===e)return"nulo";if(Object.getPrototypeOf(e)!==Object.prototype)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: se esperaba ${V.stringifyPrimitive(i.values[0])}`;return`Opci\xf3n 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${i.pattern}`;return`Inv\xe1lido ${t[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe1lido: debe ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Llave${i.keys.length>1?"s":""} desconocida${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Llave inv\xe1lida en ${i.origin}`;case"invalid_union":default:return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido en ${i.origin}`}})}},"fa",0,function(){let e,t;return{localeError:(e={string:{unit:"کاراکتر",verb:"داشته باشد"},file:{unit:"بایت",verb:"داشته باشد"},array:{unit:"آیتم",verb:"داشته باشد"},set:{unit:"آیتم",verb:"داشته باشد"}},t={regex:"ورودی",email:"آدرس ایمیل",url:"URL",emoji:"ایموجی",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"تاریخ و زمان ایزو",date:"تاریخ ایزو",time:"زمان ایزو",duration:"مدت زمان ایزو",ipv4:"IPv4 آدرس",ipv6:"IPv6 آدرس",cidrv4:"IPv4 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e,t;return{localeError:(e={string:{unit:"merkkiä",subject:"merkkijonon"},file:{unit:"tavua",subject:"tiedoston"},array:{unit:"alkiota",subject:"listan"},set:{unit:"alkiota",subject:"joukon"},number:{unit:"",subject:"luvun"},bigint:{unit:"",subject:"suuren kokonaisluvun"},int:{unit:"",subject:"kokonaisluvun"},date:{unit:"",subject:"päivämäärän"}},t={regex:"säännöllinen lauseke",email:"sähköpostiosoite",url:"URL-osoite",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-aikaleima",date:"ISO-päivämäärä",time:"ISO-aika",duration:"ISO-kesto",ipv4:"IPv4-osoite",ipv6:"IPv6-osoite",cidrv4:"IPv4-alue",cidrv6:"IPv6-alue",base64:"base64-koodattu merkkijono",base64url:"base64url-koodattu merkkijono",json_string:"JSON-merkkijono",e164:"E.164-luku",jwt:"JWT",template_literal:"templaattimerkkijono"},i=>{switch(i.code){case"invalid_type":return`Virheellinen tyyppi: odotettiin ${i.expected}, 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${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy alkaa "${i.prefix}"`;if("ends_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy loppua "${i.suffix}"`;if("includes"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy sis\xe4lt\xe4\xe4 "${i.includes}"`;if("regex"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy vastata s\xe4\xe4nn\xf6llist\xe4 lauseketta ${i.pattern}`;return`Virheellinen ${t[i.format]??i.format}`;case"not_multiple_of":return`Virheellinen luku: t\xe4ytyy olla luvun ${i.divisor} monikerta`;case"unrecognized_keys":return`${i.keys.length>1?"Tuntemattomat avaimet":"Tuntematon avain"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return"Virheellinen avain tietueessa";case"invalid_union":return"Virheellinen unioni";case"invalid_element":return"Virheellinen arvo joukossa";default:return"Virheellinen syöte"}})}},"fr",0,function(){let e,t;return{localeError:(e={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},t={regex:"entrée",email:"adresse e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"date et heure ISO",date:"date ISO",time:"heure ISO",duration:"durée ISO",ipv4:"adresse IPv4",ipv6:"adresse IPv6",cidrv4:"plage IPv4",cidrv6:"plage IPv6",base64:"chaîne encodée en base64",base64url:"chaîne encodée en base64url",json_string:"chaîne JSON",e164:"numéro E.164",jwt:"JWT",template_literal:"entrée"},i=>{switch(i.code){case"invalid_type":return`Entr\xe9e invalide : ${i.expected} attendu, ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombre";case"object":if(Array.isArray(e))return"tableau";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} re\xe7u`;case"invalid_value":if(1===i.values.length)return`Entr\xe9e invalide : ${V.stringifyPrimitive(i.values[0])} attendu`;return`Option invalide : une valeur parmi ${V.joinValues(i.values,"|")} attendue`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Trop grand : ${i.origin??"valeur"} doit ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"élément(s)"}`;return`Trop grand : ${i.origin??"valeur"} doit \xeatre ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Trop petit : ${i.origin} doit ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Trop petit : ${i.origin} doit \xeatre ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au mod\xe8le ${i.pattern}`;return`${t[i.format]??i.format} invalide`;case"not_multiple_of":return`Nombre invalide : doit \xeatre un multiple de ${i.divisor}`;case"unrecognized_keys":return`Cl\xe9${i.keys.length>1?"s":""} non reconnue${i.keys.length>1?"s":""} : ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Cl\xe9 invalide dans ${i.origin}`;case"invalid_union":default:return"Entrée invalide";case"invalid_element":return`Valeur invalide dans ${i.origin}`}})}},"frCA",0,function(){let e,t;return{localeError:(e={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},t={regex:"entrée",email:"adresse courriel",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"date-heure ISO",date:"date ISO",time:"heure ISO",duration:"durée ISO",ipv4:"adresse IPv4",ipv6:"adresse IPv6",cidrv4:"plage IPv4",cidrv6:"plage IPv6",base64:"chaîne encodée en base64",base64url:"chaîne encodée en base64url",json_string:"chaîne JSON",e164:"numéro E.164",jwt:"JWT",template_literal:"entrée"},i=>{switch(i.code){case"invalid_type":return`Entr\xe9e invalide : attendu ${i.expected}, re\xe7u ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entr\xe9e invalide : attendu ${V.stringifyPrimitive(i.values[0])}`;return`Option invalide : attendu l'une des valeurs suivantes ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"≤":"<",r=e[i.origin]??null;if(r)return`Trop grand : attendu que ${i.origin??"la valeur"} ait ${t}${i.maximum.toString()} ${r.unit}`;return`Trop grand : attendu que ${i.origin??"la valeur"} soit ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"≥":">",r=e[i.origin]??null;if(r)return`Trop petit : attendu que ${i.origin} ait ${t}${i.minimum.toString()} ${r.unit}`;return`Trop petit : attendu que ${i.origin} soit ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au motif ${i.pattern}`;return`${t[i.format]??i.format} invalide`;case"not_multiple_of":return`Nombre invalide : doit \xeatre un multiple de ${i.divisor}`;case"unrecognized_keys":return`Cl\xe9${i.keys.length>1?"s":""} non reconnue${i.keys.length>1?"s":""} : ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Cl\xe9 invalide dans ${i.origin}`;case"invalid_union":default:return"Entrée invalide";case"invalid_element":return`Valeur invalide dans ${i.origin}`}})}},"he",0,function(){let e,t;return{localeError:(e={string:{unit:"אותיות",verb:"לכלול"},file:{unit:"בייטים",verb:"לכלול"},array:{unit:"פריטים",verb:"לכלול"},set:{unit:"פריטים",verb:"לכלול"}},t={regex:"קלט",email:"כתובת אימייל",url:"כתובת רשת",emoji:"אימוג'י",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"תאריך וזמן ISO",date:"תאריך ISO",time:"זמן ISO",duration:"משך זמן ISO",ipv4:"כתובת IPv4",ipv6:"כתובת IPv6",cidrv4:"טווח IPv4",cidrv6:"טווח IPv6",base64:"מחרוזת בבסיס 64",base64url:"מחרוזת בבסיס 64 לכתובות רשת",json_string:"מחרוזת JSON",e164:"מספר E.164",jwt:"JWT",template_literal:"קלט"},i=>{switch(i.code){case"invalid_type":return`קלט לא תקין: צריך ${i.expected}, התקבל ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`קלט לא תקין: צריך ${V.stringifyPrimitive(i.values[0])}`;return`קלט לא תקין: צריך אחת מהאפשרויות  ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`גדול מדי: ${i.origin??"value"} צריך להיות ${t}${i.maximum.toString()} ${r.unit??"elements"}`;return`גדול מדי: ${i.origin??"value"} צריך להיות ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`קטן מדי: ${i.origin} צריך להיות ${t}${i.minimum.toString()} ${r.unit}`;return`קטן מדי: ${i.origin} צריך להיות ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`מחרוזת לא תקינה: חייבת להתחיל ב"${i.prefix}"`;if("ends_with"===i.format)return`מחרוזת לא תקינה: חייבת להסתיים ב "${i.suffix}"`;if("includes"===i.format)return`מחרוזת לא תקינה: חייבת לכלול "${i.includes}"`;if("regex"===i.format)return`מחרוזת לא תקינה: חייבת להתאים לתבנית ${i.pattern}`;return`${t[i.format]??i.format} לא תקין`;case"not_multiple_of":return`מספר לא תקין: חייב להיות מכפלה של ${i.divisor}`;case"unrecognized_keys":return`מפתח${i.keys.length>1?"ות":""} לא מזוה${i.keys.length>1?"ים":"ה"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`מפתח לא תקין ב${i.origin}`;case"invalid_union":default:return"קלט לא תקין";case"invalid_element":return`ערך לא תקין ב${i.origin}`}})}},"hu",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"legyen"},file:{unit:"byte",verb:"legyen"},array:{unit:"elem",verb:"legyen"},set:{unit:"elem",verb:"legyen"}},t={regex:"bemenet",email:"email cím",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO időbélyeg",date:"ISO dátum",time:"ISO idő",duration:"ISO időintervallum",ipv4:"IPv4 cím",ipv6:"IPv6 cím",cidrv4:"IPv4 tartomány",cidrv6:"IPv6 tartomány",base64:"base64-kódolt string",base64url:"base64url-kódolt string",json_string:"JSON string",e164:"E.164 szám",jwt:"JWT",template_literal:"bemenet"},i=>{switch(i.code){case"invalid_type":return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${i.expected}, a kapott \xe9rt\xe9k ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"szám";case"object":if(Array.isArray(e))return"tömb";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${V.stringifyPrimitive(i.values[0])}`;return`\xc9rv\xe9nytelen opci\xf3: valamelyik \xe9rt\xe9k v\xe1rt ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`T\xfal nagy: ${i.origin??"érték"} m\xe9rete t\xfal nagy ${t}${i.maximum.toString()} ${r.unit??"elem"}`;return`T\xfal nagy: a bemeneti \xe9rt\xe9k ${i.origin??"érték"} t\xfal nagy: ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} m\xe9rete t\xfal kicsi ${t}${i.minimum.toString()} ${r.unit}`;return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} t\xfal kicsi ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.prefix}" \xe9rt\xe9kkel kell kezdődnie`;if("ends_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.suffix}" \xe9rt\xe9kkel kell v\xe9gződnie`;if("includes"===i.format)return`\xc9rv\xe9nytelen string: "${i.includes}" \xe9rt\xe9ket kell tartalmaznia`;if("regex"===i.format)return`\xc9rv\xe9nytelen string: ${i.pattern} mint\xe1nak kell megfelelnie`;return`\xc9rv\xe9nytelen ${t[i.format]??i.format}`;case"not_multiple_of":return`\xc9rv\xe9nytelen sz\xe1m: ${i.divisor} t\xf6bbsz\xf6r\xf6s\xe9nek kell lennie`;case"unrecognized_keys":return`Ismeretlen kulcs${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`\xc9rv\xe9nytelen kulcs ${i.origin}`;case"invalid_union":default:return"Érvénytelen bemenet";case"invalid_element":return`\xc9rv\xe9nytelen \xe9rt\xe9k: ${i.origin}`}})}},"id",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"memiliki"},file:{unit:"byte",verb:"memiliki"},array:{unit:"item",verb:"memiliki"},set:{unit:"item",verb:"memiliki"}},t={regex:"input",email:"alamat email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tanggal dan waktu format ISO",date:"tanggal format ISO",time:"jam format ISO",duration:"durasi format ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",cidrv4:"rentang alamat IPv4",cidrv6:"rentang alamat IPv6",base64:"string dengan enkode base64",base64url:"string dengan enkode base64url",json_string:"string JSON",e164:"angka E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input tidak valid: diharapkan ${i.expected}, diterima ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input tidak valid: diharapkan ${V.stringifyPrimitive(i.values[0])}`;return`Pilihan tidak valid: diharapkan salah satu dari ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Terlalu besar: diharapkan ${i.origin??"value"} memiliki ${t}${i.maximum.toString()} ${r.unit??"elemen"}`;return`Terlalu besar: diharapkan ${i.origin??"value"} menjadi ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Terlalu kecil: diharapkan ${i.origin} memiliki ${t}${i.minimum.toString()} ${r.unit}`;return`Terlalu kecil: diharapkan ${i.origin} menjadi ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak valid: harus dimulai dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak valid: harus berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak valid: harus menyertakan "${i.includes}"`;if("regex"===i.format)return`String tidak valid: harus sesuai pola ${i.pattern}`;return`${t[i.format]??i.format} tidak valid`;case"not_multiple_of":return`Angka tidak valid: harus kelipatan dari ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali ${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kunci tidak valid di ${i.origin}`;case"invalid_union":default:return"Input tidak valid";case"invalid_element":return`Nilai tidak valid di ${i.origin}`}})}},"it",0,function(){let e,t;return{localeError:(e={string:{unit:"caratteri",verb:"avere"},file:{unit:"byte",verb:"avere"},array:{unit:"elementi",verb:"avere"},set:{unit:"elementi",verb:"avere"}},t={regex:"input",email:"indirizzo email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e ora ISO",date:"data ISO",time:"ora ISO",duration:"durata ISO",ipv4:"indirizzo IPv4",ipv6:"indirizzo IPv6",cidrv4:"intervallo IPv4",cidrv6:"intervallo IPv6",base64:"stringa codificata in base64",base64url:"URL codificata in base64",json_string:"stringa JSON",e164:"numero E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input non valido: atteso ${i.expected}, ricevuto ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"numero";case"object":if(Array.isArray(e))return"vettore";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input non valido: atteso ${V.stringifyPrimitive(i.values[0])}`;return`Opzione non valida: atteso uno tra ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Troppo grande: ${i.origin??"valore"} deve avere ${t}${i.maximum.toString()} ${r.unit??"elementi"}`;return`Troppo grande: ${i.origin??"valore"} deve essere ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Troppo piccolo: ${i.origin} deve avere ${t}${i.minimum.toString()} ${r.unit}`;return`Troppo piccolo: ${i.origin} deve essere ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Stringa non valida: deve iniziare con "${i.prefix}"`;if("ends_with"===i.format)return`Stringa non valida: deve terminare con "${i.suffix}"`;if("includes"===i.format)return`Stringa non valida: deve includere "${i.includes}"`;if("regex"===i.format)return`Stringa non valida: deve corrispondere al pattern ${i.pattern}`;return`Invalid ${t[i.format]??i.format}`;case"not_multiple_of":return`Numero non valido: deve essere un multiplo di ${i.divisor}`;case"unrecognized_keys":return`Chiav${i.keys.length>1?"i":"e"} non riconosciut${i.keys.length>1?"e":"a"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Chiave non valida in ${i.origin}`;case"invalid_union":default:return"Input non valido";case"invalid_element":return`Valore non valido in ${i.origin}`}})}},"ja",0,function(){let e,t;return{localeError:(e={string:{unit:"文字",verb:"である"},file:{unit:"バイト",verb:"である"},array:{unit:"要素",verb:"である"},set:{unit:"要素",verb:"である"}},t={regex:"入力値",email:"メールアドレス",url:"URL",emoji:"絵文字",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO日時",date:"ISO日付",time:"ISO時刻",duration:"ISO期間",ipv4:"IPv4アドレス",ipv6:"IPv6アドレス",cidrv4:"IPv4範囲",cidrv6:"IPv6範囲",base64:"base64エンコード文字列",base64url:"base64urlエンコード文字列",json_string:"JSON文字列",e164:"E.164番号",jwt:"JWT",template_literal:"入力値"},i=>{switch(i.code){case"invalid_type":return`無効な入力: ${i.expected}が期待されましたが、${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"数値";case"object":if(Array.isArray(e))return"配列";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}が入力されました`;case"invalid_value":if(1===i.values.length)return`無効な入力: ${V.stringifyPrimitive(i.values[0])}が期待されました`;return`無効な選択: ${V.joinValues(i.values,"、")}のいずれかである必要があります`;case"too_big":{let t=i.inclusive?"以下である":"より小さい",r=e[i.origin]??null;if(r)return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${r.unit??"要素"}${t}必要があります`;return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${t}必要があります`}case"too_small":{let t=i.inclusive?"以上である":"より大きい",r=e[i.origin]??null;if(r)return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${r.unit}${t}必要があります`;return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${t}必要があります`}case"invalid_format":if("starts_with"===i.format)return`無効な文字列: "${i.prefix}"で始まる必要があります`;if("ends_with"===i.format)return`無効な文字列: "${i.suffix}"で終わる必要があります`;if("includes"===i.format)return`無効な文字列: "${i.includes}"を含む必要があります`;if("regex"===i.format)return`無効な文字列: パターン${i.pattern}に一致する必要があります`;return`無効な${t[i.format]??i.format}`;case"not_multiple_of":return`無効な数値: ${i.divisor}の倍数である必要があります`;case"unrecognized_keys":return`認識されていないキー${i.keys.length>1?"群":""}: ${V.joinValues(i.keys,"、")}`;case"invalid_key":return`${i.origin}内の無効なキー`;case"invalid_union":default:return"無効な入力";case"invalid_element":return`${i.origin}内の無効な値`}})}},"kh",0,function(){let e,t;return{localeError:(e={string:{unit:"តួអក្សរ",verb:"គួរមាន"},file:{unit:"បៃ",verb:"គួរមាន"},array:{unit:"ធាតុ",verb:"គួរមាន"},set:{unit:"ធាតុ",verb:"គួរមាន"}},t={regex:"ទិន្នន័យបញ្ចូល",email:"អាសយដ្ឋានអ៊ីមែល",url:"URL",emoji:"សញ្ញាអារម្មណ៍",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"កាលបរិច្ឆេទ និងម៉ោង ISO",date:"កាលបរិច្ឆេទ ISO",time:"ម៉ោង ISO",duration:"រយៈពេល ISO",ipv4:"អាសយដ្ឋាន IPv4",ipv6:"អាសយដ្ឋាន IPv6",cidrv4:"ដែនអាសយដ្ឋាន IPv4",cidrv6:"ដែនអាសយដ្ឋាន IPv6",base64:"ខ្សែអក្សរអ៊ិកូដ base64",base64url:"ខ្សែអក្សរអ៊ិកូដ base64url",json_string:"ខ្សែអក្សរ JSON",e164:"លេខ E.164",jwt:"JWT",template_literal:"ទិន្នន័យបញ្ចូល"},i=>{switch(i.code){case"invalid_type":return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${i.expected} ប៉ុន្តែទទួលបាន ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"មិនមែនជាលេខ (NaN)":"លេខ";case"object":if(Array.isArray(e))return"អារេ (Array)";if(null===e)return"គ្មានតម្លៃ (null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${V.stringifyPrimitive(i.values[0])}`;return`ជម្រើសមិនត្រឹមត្រូវ៖ ត្រូវជាមួយក្នុងចំណោម ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${t} ${i.maximum.toString()} ${r.unit??"ធាតុ"}`;return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`តូចពេក៖ ត្រូវការ ${i.origin} ${t} ${i.minimum.toString()} ${r.unit}`;return`តូចពេក៖ ត្រូវការ ${i.origin} ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវចាប់ផ្តើមដោយ "${i.prefix}"`;if("ends_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវបញ្ចប់ដោយ "${i.suffix}"`;if("includes"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវមាន "${i.includes}"`;if("regex"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវតែផ្គូផ្គងនឹងទម្រង់ដែលបានកំណត់ ${i.pattern}`;return`មិនត្រឹមត្រូវ៖ ${t[i.format]??i.format}`;case"not_multiple_of":return`លេខមិនត្រឹមត្រូវ៖ ត្រូវតែជាពហុគុណនៃ ${i.divisor}`;case"unrecognized_keys":return`រកឃើញសោមិនស្គាល់៖ ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`សោមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`;case"invalid_union":default:return"ទិន្នន័យមិនត្រឹមត្រូវ";case"invalid_element":return`ទិន្នន័យមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`}})}},"ko",0,function(){let e,t;return{localeError:(e={string:{unit:"문자",verb:"to have"},file:{unit:"바이트",verb:"to have"},array:{unit:"개",verb:"to have"},set:{unit:"개",verb:"to have"}},t={regex:"입력",email:"이메일 주소",url:"URL",emoji:"이모지",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO 날짜시간",date:"ISO 날짜",time:"ISO 시간",duration:"ISO 기간",ipv4:"IPv4 주소",ipv6:"IPv6 주소",cidrv4:"IPv4 범위",cidrv6:"IPv6 범위",base64:"base64 인코딩 문자열",base64url:"base64url 인코딩 문자열",json_string:"JSON 문자열",e164:"E.164 번호",jwt:"JWT",template_literal:"입력"},i=>{switch(i.code){case"invalid_type":return`잘못된 입력: 예상 타입은 ${i.expected}, 받은 타입은 ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}입니다`;case"invalid_value":if(1===i.values.length)return`잘못된 입력: 값은 ${V.stringifyPrimitive(i.values[0])} 이어야 합니다`;return`잘못된 옵션: ${V.joinValues(i.values,"또는 ")} 중 하나여야 합니다`;case"too_big":{let t=i.inclusive?"이하":"미만",r="미만"===t?"이어야 합니다":"여야 합니다",n=e[i.origin]??null,a=n?.unit??"요소";if(n)return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()}${a} ${t}${r}`;return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()} ${t}${r}`}case"too_small":{let t=i.inclusive?"이상":"초과",r="이상"===t?"이어야 합니다":"여야 합니다",n=e[i.origin]??null,a=n?.unit??"요소";if(n)return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()}${a} ${t}${r}`;return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()} ${t}${r}`}case"invalid_format":if("starts_with"===i.format)return`잘못된 문자열: "${i.prefix}"(으)로 시작해야 합니다`;if("ends_with"===i.format)return`잘못된 문자열: "${i.suffix}"(으)로 끝나야 합니다`;if("includes"===i.format)return`잘못된 문자열: "${i.includes}"을(를) 포함해야 합니다`;if("regex"===i.format)return`잘못된 문자열: 정규식 ${i.pattern} 패턴과 일치해야 합니다`;return`잘못된 ${t[i.format]??i.format}`;case"not_multiple_of":return`잘못된 숫자: ${i.divisor}의 배수여야 합니다`;case"unrecognized_keys":return`인식할 수 없는 키: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`잘못된 키: ${i.origin}`;case"invalid_union":default:return"잘못된 입력";case"invalid_element":return`잘못된 값: ${i.origin}`}})}},"mk",0,function(){let e,t;return{localeError:(e={string:{unit:"знаци",verb:"да имаат"},file:{unit:"бајти",verb:"да имаат"},array:{unit:"ставки",verb:"да имаат"},set:{unit:"ставки",verb:"да имаат"}},t={regex:"внес",email:"адреса на е-пошта",url:"URL",emoji:"емоџи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO датум и време",date:"ISO датум",time:"ISO време",duration:"ISO времетраење",ipv4:"IPv4 адреса",ipv6:"IPv6 адреса",cidrv4:"IPv4 опсег",cidrv6:"IPv6 опсег",base64:"base64-енкодирана низа",base64url:"base64url-енкодирана низа",json_string:"JSON низа",e164:"E.164 број",jwt:"JWT",template_literal:"внес"},i=>{switch(i.code){case"invalid_type":return`Грешен внес: се очекува ${i.expected}, примено ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"број";case"object":if(Array.isArray(e))return"низа";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Invalid input: expected ${V.stringifyPrimitive(i.values[0])}`;return`Грешана опција: се очекува една ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Премногу голем: се очекува ${i.origin??"вредноста"} да има ${t}${i.maximum.toString()} ${r.unit??"елементи"}`;return`Премногу голем: се очекува ${i.origin??"вредноста"} да биде ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Премногу мал: се очекува ${i.origin} да има ${t}${i.minimum.toString()} ${r.unit}`;return`Премногу мал: се очекува ${i.origin} да биде ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неважечка низа: мора да започнува со "${i.prefix}"`;if("ends_with"===i.format)return`Неважечка низа: мора да завршува со "${i.suffix}"`;if("includes"===i.format)return`Неважечка низа: мора да вклучува "${i.includes}"`;if("regex"===i.format)return`Неважечка низа: мора да одгоара на патернот ${i.pattern}`;return`Invalid ${t[i.format]??i.format}`;case"not_multiple_of":return`Грешен број: мора да биде делив со ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Непрепознаени клучеви":"Непрепознаен клуч"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Грешен клуч во ${i.origin}`;case"invalid_union":default:return"Грешен внес";case"invalid_element":return`Грешна вредност во ${i.origin}`}})}},"ms",0,function(){let e,t;return{localeError:(e={string:{unit:"aksara",verb:"mempunyai"},file:{unit:"bait",verb:"mempunyai"},array:{unit:"elemen",verb:"mempunyai"},set:{unit:"elemen",verb:"mempunyai"}},t={regex:"input",email:"alamat e-mel",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tarikh masa ISO",date:"tarikh ISO",time:"masa ISO",duration:"tempoh ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",cidrv4:"julat IPv4",cidrv6:"julat IPv6",base64:"string dikodkan base64",base64url:"string dikodkan base64url",json_string:"string JSON",e164:"nombor E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input tidak sah: dijangka ${i.expected}, diterima ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombor";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input tidak sah: dijangka ${V.stringifyPrimitive(i.values[0])}`;return`Pilihan tidak sah: dijangka salah satu daripada ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Terlalu besar: dijangka ${i.origin??"nilai"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"elemen"}`;return`Terlalu besar: dijangka ${i.origin??"nilai"} adalah ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Terlalu kecil: dijangka ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Terlalu kecil: dijangka ${i.origin} adalah ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak sah: mesti bermula dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak sah: mesti berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak sah: mesti mengandungi "${i.includes}"`;if("regex"===i.format)return`String tidak sah: mesti sepadan dengan corak ${i.pattern}`;return`${t[i.format]??i.format} tidak sah`;case"not_multiple_of":return`Nombor tidak sah: perlu gandaan ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kunci tidak sah dalam ${i.origin}`;case"invalid_union":default:return"Input tidak sah";case"invalid_element":return`Nilai tidak sah dalam ${i.origin}`}})}},"nl",0,function(){let e,t;return{localeError:(e={string:{unit:"tekens"},file:{unit:"bytes"},array:{unit:"elementen"},set:{unit:"elementen"}},t={regex:"invoer",email:"emailadres",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum en tijd",date:"ISO datum",time:"ISO tijd",duration:"ISO duur",ipv4:"IPv4-adres",ipv6:"IPv6-adres",cidrv4:"IPv4-bereik",cidrv6:"IPv6-bereik",base64:"base64-gecodeerde tekst",base64url:"base64 URL-gecodeerde tekst",json_string:"JSON string",e164:"E.164-nummer",jwt:"JWT",template_literal:"invoer"},i=>{switch(i.code){case"invalid_type":return`Ongeldige invoer: verwacht ${i.expected}, ontving ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"getal";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ongeldige invoer: verwacht ${V.stringifyPrimitive(i.values[0])}`;return`Ongeldige optie: verwacht \xe9\xe9n van ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Te lang: verwacht dat ${i.origin??"waarde"} ${t}${i.maximum.toString()} ${r.unit??"elementen"} bevat`;return`Te lang: verwacht dat ${i.origin??"waarde"} ${t}${i.maximum.toString()} is`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Te kort: verwacht dat ${i.origin} ${t}${i.minimum.toString()} ${r.unit} bevat`;return`Te kort: verwacht dat ${i.origin} ${t}${i.minimum.toString()} is`}case"invalid_format":if("starts_with"===i.format)return`Ongeldige tekst: moet met "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ongeldige tekst: moet op "${i.suffix}" eindigen`;if("includes"===i.format)return`Ongeldige tekst: moet "${i.includes}" bevatten`;if("regex"===i.format)return`Ongeldige tekst: moet overeenkomen met patroon ${i.pattern}`;return`Ongeldig: ${t[i.format]??i.format}`;case"not_multiple_of":return`Ongeldig getal: moet een veelvoud van ${i.divisor} zijn`;case"unrecognized_keys":return`Onbekende key${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ongeldige key in ${i.origin}`;case"invalid_union":default:return"Ongeldige invoer";case"invalid_element":return`Ongeldige waarde in ${i.origin}`}})}},"no",0,function(){let e,t;return{localeError:(e={string:{unit:"tegn",verb:"å ha"},file:{unit:"bytes",verb:"å ha"},array:{unit:"elementer",verb:"å inneholde"},set:{unit:"elementer",verb:"å inneholde"}},t={regex:"input",email:"e-postadresse",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO dato- og klokkeslett",date:"ISO-dato",time:"ISO-klokkeslett",duration:"ISO-varighet",ipv4:"IPv4-område",ipv6:"IPv6-område",cidrv4:"IPv4-spekter",cidrv6:"IPv6-spekter",base64:"base64-enkodet streng",base64url:"base64url-enkodet streng",json_string:"JSON-streng",e164:"E.164-nummer",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Ugyldig input: forventet ${i.expected}, fikk ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"tall";case"object":if(Array.isArray(e))return"liste";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ugyldig verdi: forventet ${V.stringifyPrimitive(i.values[0])}`;return`Ugyldig valg: forventet en av ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${t}${i.maximum.toString()} ${r.unit??"elementer"}`;return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`For lite(n): forventet ${i.origin} til \xe5 ha ${t}${i.minimum.toString()} ${r.unit}`;return`For lite(n): forventet ${i.origin} til \xe5 ha ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ugyldig streng: m\xe5 starte med "${i.prefix}"`;if("ends_with"===i.format)return`Ugyldig streng: m\xe5 ende med "${i.suffix}"`;if("includes"===i.format)return`Ugyldig streng: m\xe5 inneholde "${i.includes}"`;if("regex"===i.format)return`Ugyldig streng: m\xe5 matche m\xf8nsteret ${i.pattern}`;return`Ugyldig ${t[i.format]??i.format}`;case"not_multiple_of":return`Ugyldig tall: m\xe5 v\xe6re et multiplum av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Ukjente nøkler":"Ukjent nøkkel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ugyldig n\xf8kkel i ${i.origin}`;case"invalid_union":default:return"Ugyldig input";case"invalid_element":return`Ugyldig verdi i ${i.origin}`}})}},"ota",0,function(){let e,t;return{localeError:(e={string:{unit:"harf",verb:"olmalıdır"},file:{unit:"bayt",verb:"olmalıdır"},array:{unit:"unsur",verb:"olmalıdır"},set:{unit:"unsur",verb:"olmalıdır"}},t={regex:"giren",email:"epostagâh",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO hengâmı",date:"ISO tarihi",time:"ISO zamanı",duration:"ISO müddeti",ipv4:"IPv4 nişânı",ipv6:"IPv6 nişânı",cidrv4:"IPv4 menzili",cidrv6:"IPv6 menzili",base64:"base64-şifreli metin",base64url:"base64url-şifreli metin",json_string:"JSON metin",e164:"E.164 sayısı",jwt:"JWT",template_literal:"giren"},i=>{switch(i.code){case"invalid_type":return`F\xe2sit giren: umulan ${i.expected}, alınan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"numara";case"object":if(Array.isArray(e))return"saf";if(null===e)return"gayb";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`F\xe2sit giren: umulan ${V.stringifyPrimitive(i.values[0])}`;return`F\xe2sit tercih: m\xfbteberler ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${t}${i.maximum.toString()} ${r.unit??"elements"} sahip olmalıydı.`;return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${t}${i.maximum.toString()} olmalıydı.`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${t}${i.minimum.toString()} ${r.unit} sahip olmalıydı.`;return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${t}${i.minimum.toString()} olmalıydı.`}case"invalid_format":if("starts_with"===i.format)return`F\xe2sit metin: "${i.prefix}" ile başlamalı.`;if("ends_with"===i.format)return`F\xe2sit metin: "${i.suffix}" ile bitmeli.`;if("includes"===i.format)return`F\xe2sit metin: "${i.includes}" ihtiv\xe2 etmeli.`;if("regex"===i.format)return`F\xe2sit metin: ${i.pattern} nakşına uymalı.`;return`F\xe2sit ${t[i.format]??i.format}`;case"not_multiple_of":return`F\xe2sit sayı: ${i.divisor} katı olmalıydı.`;case"unrecognized_keys":return`Tanınmayan anahtar ${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7in tanınmayan anahtar var.`;case"invalid_union":return"Giren tanınamadı.";case"invalid_element":return`${i.origin} i\xe7in tanınmayan kıymet var.`;default:return"Kıymet tanınamadı."}})}},"pl",0,function(){let e,t;return{localeError:(e={string:{unit:"znaków",verb:"mieć"},file:{unit:"bajtów",verb:"mieć"},array:{unit:"elementów",verb:"mieć"},set:{unit:"elementów",verb:"mieć"}},t={regex:"wyrażenie",email:"adres email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i godzina w formacie ISO",date:"data w formacie ISO",time:"godzina w formacie ISO",duration:"czas trwania ISO",ipv4:"adres IPv4",ipv6:"adres IPv6",cidrv4:"zakres IPv4",cidrv6:"zakres IPv6",base64:"ciąg znaków zakodowany w formacie base64",base64url:"ciąg znaków zakodowany w formacie base64url",json_string:"ciąg znaków w formacie JSON",e164:"liczba E.164",jwt:"JWT",template_literal:"wejście"},i=>{switch(i.code){case"invalid_type":return`Nieprawidłowe dane wejściowe: oczekiwano ${i.expected}, otrzymano ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"liczba";case"object":if(Array.isArray(e))return"tablica";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Nieprawidłowe dane wejściowe: oczekiwano ${V.stringifyPrimitive(i.values[0])}`;return`Nieprawidłowa opcja: oczekiwano jednej z wartości ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Za duża wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${t}${i.maximum.toString()} ${r.unit??"elementów"}`;return`Zbyt duż(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Za mała wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${t}${i.minimum.toString()} ${r.unit??"elementów"}`;return`Zbyt mał(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zaczynać się od "${i.prefix}"`;if("ends_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi kończyć się na "${i.suffix}"`;if("includes"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zawierać "${i.includes}"`;if("regex"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi odpowiadać wzorcowi ${i.pattern}`;return`Nieprawidłow(y/a/e) ${t[i.format]??i.format}`;case"not_multiple_of":return`Nieprawidłowa liczba: musi być wielokrotnością ${i.divisor}`;case"unrecognized_keys":return`Nierozpoznane klucze${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Nieprawidłowy klucz w ${i.origin}`;case"invalid_union":default:return"Nieprawidłowe dane wejściowe";case"invalid_element":return`Nieprawidłowa wartość w ${i.origin}`}})}},"ps",0,function(){let e,t;return{localeError:(e={string:{unit:"توکي",verb:"ولري"},file:{unit:"بایټس",verb:"ولري"},array:{unit:"توکي",verb:"ولري"},set:{unit:"توکي",verb:"ولري"}},t={regex:"ورودي",email:"بریښنالیک",url:"یو آر ال",emoji:"ایموجي",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"نیټه او وخت",date:"نېټه",time:"وخت",duration:"موده",ipv4:"د IPv4 پته",ipv6:"د IPv6 پته",cidrv4:"د IPv4 ساحه",cidrv6:"د IPv6 ساحه",base64:"base64-encoded متن",base64url:"base64url-encoded متن",json_string:"JSON متن",e164:"د E.164 شمېره",jwt:"JWT",template_literal:"ورودي"},i=>{switch(i.code){case"invalid_type":return`ناسم ورودي: باید ${i.expected} وای, مګر ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"عدد";case"object":if(Array.isArray(e))return"ارې";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} ترلاسه شو`;case"invalid_value":if(1===i.values.length)return`ناسم ورودي: باید ${V.stringifyPrimitive(i.values[0])} وای`;return`ناسم انتخاب: باید یو له ${V.joinValues(i.values,"|")} څخه وای`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`ډیر لوی: ${i.origin??"ارزښت"} باید ${t}${i.maximum.toString()} ${r.unit??"عنصرونه"} ولري`;return`ډیر لوی: ${i.origin??"ارزښت"} باید ${t}${i.maximum.toString()} وي`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`ډیر کوچنی: ${i.origin} باید ${t}${i.minimum.toString()} ${r.unit} ولري`;return`ډیر کوچنی: ${i.origin} باید ${t}${i.minimum.toString()} وي`}case"invalid_format":if("starts_with"===i.format)return`ناسم متن: باید د "${i.prefix}" سره پیل شي`;if("ends_with"===i.format)return`ناسم متن: باید د "${i.suffix}" سره پای ته ورسيږي`;if("includes"===i.format)return`ناسم متن: باید "${i.includes}" ولري`;if("regex"===i.format)return`ناسم متن: باید د ${i.pattern} سره مطابقت ولري`;return`${t[i.format]??i.format} ناسم دی`;case"not_multiple_of":return`ناسم عدد: باید د ${i.divisor} مضرب وي`;case"unrecognized_keys":return`ناسم ${i.keys.length>1?"کلیډونه":"کلیډ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`ناسم کلیډ په ${i.origin} کې`;case"invalid_union":default:return"ناسمه ورودي";case"invalid_element":return`ناسم عنصر په ${i.origin} کې`}})}},"pt",0,function(){let e,t;return{localeError:(e={string:{unit:"caracteres",verb:"ter"},file:{unit:"bytes",verb:"ter"},array:{unit:"itens",verb:"ter"},set:{unit:"itens",verb:"ter"}},t={regex:"padrão",email:"endereço de e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e hora ISO",date:"data ISO",time:"hora ISO",duration:"duração ISO",ipv4:"endereço IPv4",ipv6:"endereço IPv6",cidrv4:"faixa de IPv4",cidrv6:"faixa de IPv6",base64:"texto codificado em base64",base64url:"URL codificada em base64",json_string:"texto JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Tipo inv\xe1lido: esperado ${i.expected}, recebido ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"número";case"object":if(Array.isArray(e))return"array";if(null===e)return"nulo";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: esperado ${V.stringifyPrimitive(i.values[0])}`;return`Op\xe7\xe3o inv\xe1lida: esperada uma das ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Muito grande: esperado que ${i.origin??"valor"} tivesse ${t}${i.maximum.toString()} ${r.unit??"elementos"}`;return`Muito grande: esperado que ${i.origin??"valor"} fosse ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Muito pequeno: esperado que ${i.origin} tivesse ${t}${i.minimum.toString()} ${r.unit}`;return`Muito pequeno: esperado que ${i.origin} fosse ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Texto inv\xe1lido: deve come\xe7ar com "${i.prefix}"`;if("ends_with"===i.format)return`Texto inv\xe1lido: deve terminar com "${i.suffix}"`;if("includes"===i.format)return`Texto inv\xe1lido: deve incluir "${i.includes}"`;if("regex"===i.format)return`Texto inv\xe1lido: deve corresponder ao padr\xe3o ${i.pattern}`;return`${t[i.format]??i.format} inv\xe1lido`;case"not_multiple_of":return`N\xfamero inv\xe1lido: deve ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Chave${i.keys.length>1?"s":""} desconhecida${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Chave inv\xe1lida em ${i.origin}`;case"invalid_union":return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido em ${i.origin}`;default:return"Campo inválido"}})}},"ru",0,function(){let e,t;return{localeError:(e={string:{unit:{one:"символ",few:"символа",many:"символов"},verb:"иметь"},file:{unit:{one:"байт",few:"байта",many:"байт"},verb:"иметь"},array:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"},set:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"}},t={regex:"ввод",email:"email адрес",url:"URL",emoji:"эмодзи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO дата и время",date:"ISO дата",time:"ISO время",duration:"ISO длительность",ipv4:"IPv4 адрес",ipv6:"IPv6 адрес",cidrv4:"IPv4 диапазон",cidrv6:"IPv6 диапазон",base64:"строка в формате base64",base64url:"строка в формате base64url",json_string:"JSON строка",e164:"номер E.164",jwt:"JWT",template_literal:"ввод"},i=>{switch(i.code){case"invalid_type":return`Неверный ввод: ожидалось ${i.expected}, получено ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"число";case"object":if(Array.isArray(e))return"массив";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Неверный ввод: ожидалось ${V.stringifyPrimitive(i.values[0])}`;return`Неверный вариант: ожидалось одно из ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r){let e=tA(Number(i.maximum),r.unit.one,r.unit.few,r.unit.many);return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет иметь ${t}${i.maximum.toString()} ${e}`}return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r){let e=tA(Number(i.minimum),r.unit.one,r.unit.few,r.unit.many);return`Слишком маленькое значение: ожидалось, что ${i.origin} будет иметь ${t}${i.minimum.toString()} ${e}`}return`Слишком маленькое значение: ожидалось, что ${i.origin} будет ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неверная строка: должна начинаться с "${i.prefix}"`;if("ends_with"===i.format)return`Неверная строка: должна заканчиваться на "${i.suffix}"`;if("includes"===i.format)return`Неверная строка: должна содержать "${i.includes}"`;if("regex"===i.format)return`Неверная строка: должна соответствовать шаблону ${i.pattern}`;return`Неверный ${t[i.format]??i.format}`;case"not_multiple_of":return`Неверное число: должно быть кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспознанн${i.keys.length>1?"ые":"ый"} ключ${i.keys.length>1?"и":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Неверный ключ в ${i.origin}`;case"invalid_union":default:return"Неверные входные данные";case"invalid_element":return`Неверное значение в ${i.origin}`}})}},"sl",0,function(){let e,t;return{localeError:(e={string:{unit:"znakov",verb:"imeti"},file:{unit:"bajtov",verb:"imeti"},array:{unit:"elementov",verb:"imeti"},set:{unit:"elementov",verb:"imeti"}},t={regex:"vnos",email:"e-poštni naslov",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum in čas",date:"ISO datum",time:"ISO čas",duration:"ISO trajanje",ipv4:"IPv4 naslov",ipv6:"IPv6 naslov",cidrv4:"obseg IPv4",cidrv6:"obseg IPv6",base64:"base64 kodiran niz",base64url:"base64url kodiran niz",json_string:"JSON niz",e164:"E.164 številka",jwt:"JWT",template_literal:"vnos"},i=>{switch(i.code){case"invalid_type":return`Neveljaven vnos: pričakovano ${i.expected}, prejeto ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"število";case"object":if(Array.isArray(e))return"tabela";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Neveljaven vnos: pričakovano ${V.stringifyPrimitive(i.values[0])}`;return`Neveljavna možnost: pričakovano eno izmed ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} imelo ${t}${i.maximum.toString()} ${r.unit??"elementov"}`;return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Premajhno: pričakovano, da bo ${i.origin} imelo ${t}${i.minimum.toString()} ${r.unit}`;return`Premajhno: pričakovano, da bo ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neveljaven niz: mora se začeti z "${i.prefix}"`;if("ends_with"===i.format)return`Neveljaven niz: mora se končati z "${i.suffix}"`;if("includes"===i.format)return`Neveljaven niz: mora vsebovati "${i.includes}"`;if("regex"===i.format)return`Neveljaven niz: mora ustrezati vzorcu ${i.pattern}`;return`Neveljaven ${t[i.format]??i.format}`;case"not_multiple_of":return`Neveljavno število: mora biti večkratnik ${i.divisor}`;case"unrecognized_keys":return`Neprepoznan${i.keys.length>1?"i ključi":" ključ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Neveljaven ključ v ${i.origin}`;case"invalid_union":default:return"Neveljaven vnos";case"invalid_element":return`Neveljavna vrednost v ${i.origin}`}})}},"sv",0,function(){let e,t;return{localeError:(e={string:{unit:"tecken",verb:"att ha"},file:{unit:"bytes",verb:"att ha"},array:{unit:"objekt",verb:"att innehålla"},set:{unit:"objekt",verb:"att innehålla"}},t={regex:"reguljärt uttryck",email:"e-postadress",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datum och tid",date:"ISO-datum",time:"ISO-tid",duration:"ISO-varaktighet",ipv4:"IPv4-intervall",ipv6:"IPv6-intervall",cidrv4:"IPv4-spektrum",cidrv6:"IPv6-spektrum",base64:"base64-kodad sträng",base64url:"base64url-kodad sträng",json_string:"JSON-sträng",e164:"E.164-nummer",jwt:"JWT",template_literal:"mall-literal"},i=>{switch(i.code){case"invalid_type":return`Ogiltig inmatning: f\xf6rv\xe4ntat ${i.expected}, fick ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"antal";case"object":if(Array.isArray(e))return"lista";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ogiltig inmatning: f\xf6rv\xe4ntat ${V.stringifyPrimitive(i.values[0])}`;return`Ogiltigt val: f\xf6rv\xe4ntade en av ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`F\xf6r stor(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.maximum.toString()} ${r.unit??"element"}`;return`F\xf6r stor(t): f\xf6rv\xe4ntat ${i.origin??"värdet"} att ha ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.minimum.toString()} ${r.unit}`;return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste b\xf6rja med "${i.prefix}"`;if("ends_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste sluta med "${i.suffix}"`;if("includes"===i.format)return`Ogiltig str\xe4ng: m\xe5ste inneh\xe5lla "${i.includes}"`;if("regex"===i.format)return`Ogiltig str\xe4ng: m\xe5ste matcha m\xf6nstret "${i.pattern}"`;return`Ogiltig(t) ${t[i.format]??i.format}`;case"not_multiple_of":return`Ogiltigt tal: m\xe5ste vara en multipel av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Okända nycklar":"Okänd nyckel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ogiltig nyckel i ${i.origin??"värdet"}`;case"invalid_union":default:return"Ogiltig input";case"invalid_element":return`Ogiltigt v\xe4rde i ${i.origin??"värdet"}`}})}},"ta",0,function(){let e,t;return{localeError:(e={string:{unit:"எழுத்துக்கள்",verb:"கொண்டிருக்க வேண்டும்"},file:{unit:"பைட்டுகள்",verb:"கொண்டிருக்க வேண்டும்"},array:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"},set:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"}},t={regex:"உள்ளீடு",email:"மின்னஞ்சல் முகவரி",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO தேதி நேரம்",date:"ISO தேதி",time:"ISO நேரம்",duration:"ISO கால அளவு",ipv4:"IPv4 முகவரி",ipv6:"IPv6 முகவரி",cidrv4:"IPv4 வரம்பு",cidrv6:"IPv6 வரம்பு",base64:"base64-encoded சரம்",base64url:"base64url-encoded சரம்",json_string:"JSON சரம்",e164:"E.164 எண்",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது ${i.expected}, பெறப்பட்டது ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"எண் அல்லாதது":"எண்";case"object":if(Array.isArray(e))return"அணி";if(null===e)return"வெறுமை";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது ${V.stringifyPrimitive(i.values[0])}`;return`தவறான விருப்பம்: எதிர்பார்க்கப்பட்டது ${V.joinValues(i.values,"|")} இல் ஒன்று`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`மிக பெரியது: எதிர்பார்க்கப்பட்டது ${i.origin??"மதிப்பு"} ${t}${i.maximum.toString()} ${r.unit??"உறுப்புகள்"} ஆக இருக்க வேண்டும்`;return`மிக பெரியது: எதிர்பார்க்கப்பட்டது ${i.origin??"மதிப்பு"} ${t}${i.maximum.toString()} ஆக இருக்க வேண்டும்`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${t}${i.minimum.toString()} ${r.unit} ஆக இருக்க வேண்டும்`;return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${t}${i.minimum.toString()} ஆக இருக்க வேண்டும்`}case"invalid_format":if("starts_with"===i.format)return`தவறான சரம்: "${i.prefix}" இல் தொடங்க வேண்டும்`;if("ends_with"===i.format)return`தவறான சரம்: "${i.suffix}" இல் முடிவடைய வேண்டும்`;if("includes"===i.format)return`தவறான சரம்: "${i.includes}" ஐ உள்ளடக்க வேண்டும்`;if("regex"===i.format)return`தவறான சரம்: ${i.pattern} முறைபாட்டுடன் பொருந்த வேண்டும்`;return`தவறான ${t[i.format]??i.format}`;case"not_multiple_of":return`தவறான எண்: ${i.divisor} இன் பலமாக இருக்க வேண்டும்`;case"unrecognized_keys":return`அடையாளம் தெரியாத விசை${i.keys.length>1?"கள்":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} இல் தவறான விசை`;case"invalid_union":default:return"தவறான உள்ளீடு";case"invalid_element":return`${i.origin} இல் தவறான மதிப்பு`}})}},"th",0,function(){let e,t;return{localeError:(e={string:{unit:"ตัวอักษร",verb:"ควรมี"},file:{unit:"ไบต์",verb:"ควรมี"},array:{unit:"รายการ",verb:"ควรมี"},set:{unit:"รายการ",verb:"ควรมี"}},t={regex:"ข้อมูลที่ป้อน",email:"ที่อยู่อีเมล",url:"URL",emoji:"อิโมจิ",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"วันที่เวลาแบบ ISO",date:"วันที่แบบ ISO",time:"เวลาแบบ ISO",duration:"ช่วงเวลาแบบ ISO",ipv4:"ที่อยู่ IPv4",ipv6:"ที่อยู่ IPv6",cidrv4:"ช่วง IP แบบ IPv4",cidrv6:"ช่วง IP แบบ IPv6",base64:"ข้อความแบบ Base64",base64url:"ข้อความแบบ Base64 สำหรับ URL",json_string:"ข้อความแบบ JSON",e164:"เบอร์โทรศัพท์ระหว่างประเทศ (E.164)",jwt:"โทเคน JWT",template_literal:"ข้อมูลที่ป้อน"},i=>{switch(i.code){case"invalid_type":return`ประเภทข้อมูลไม่ถูกต้อง: ควรเป็น ${i.expected} แต่ได้รับ ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"ไม่ใช่ตัวเลข (NaN)":"ตัวเลข";case"object":if(Array.isArray(e))return"อาร์เรย์ (Array)";if(null===e)return"ไม่มีค่า (null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`ค่าไม่ถูกต้อง: ควรเป็น ${V.stringifyPrimitive(i.values[0])}`;return`ตัวเลือกไม่ถูกต้อง: ควรเป็นหนึ่งใน ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"ไม่เกิน":"น้อยกว่า",r=e[i.origin]??null;if(r)return`เกินกำหนด: ${i.origin??"ค่า"} ควรมี${t} ${i.maximum.toString()} ${r.unit??"รายการ"}`;return`เกินกำหนด: ${i.origin??"ค่า"} ควรมี${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"อย่างน้อย":"มากกว่า",r=e[i.origin]??null;if(r)return`น้อยกว่ากำหนด: ${i.origin} ควรมี${t} ${i.minimum.toString()} ${r.unit}`;return`น้อยกว่ากำหนด: ${i.origin} ควรมี${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องขึ้นต้นด้วย "${i.prefix}"`;if("ends_with"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องลงท้ายด้วย "${i.suffix}"`;if("includes"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องมี "${i.includes}" อยู่ในข้อความ`;if("regex"===i.format)return`รูปแบบไม่ถูกต้อง: ต้องตรงกับรูปแบบที่กำหนด ${i.pattern}`;return`รูปแบบไม่ถูกต้อง: ${t[i.format]??i.format}`;case"not_multiple_of":return`ตัวเลขไม่ถูกต้อง: ต้องเป็นจำนวนที่หารด้วย ${i.divisor} ได้ลงตัว`;case"unrecognized_keys":return`พบคีย์ที่ไม่รู้จัก: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`คีย์ไม่ถูกต้องใน ${i.origin}`;case"invalid_union":return"ข้อมูลไม่ถูกต้อง: ไม่ตรงกับรูปแบบยูเนียนที่กำหนดไว้";case"invalid_element":return`ข้อมูลไม่ถูกต้องใน ${i.origin}`;default:return"ข้อมูลไม่ถูกต้อง"}})}},"tr",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"olmalı"},file:{unit:"bayt",verb:"olmalı"},array:{unit:"öğe",verb:"olmalı"},set:{unit:"öğe",verb:"olmalı"}},t={regex:"girdi",email:"e-posta adresi",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO tarih ve saat",date:"ISO tarih",time:"ISO saat",duration:"ISO süre",ipv4:"IPv4 adresi",ipv6:"IPv6 adresi",cidrv4:"IPv4 aralığı",cidrv6:"IPv6 aralığı",base64:"base64 ile şifrelenmiş metin",base64url:"base64url ile şifrelenmiş metin",json_string:"JSON dizesi",e164:"E.164 sayısı",jwt:"JWT",template_literal:"Şablon dizesi"},i=>{switch(i.code){case"invalid_type":return`Ge\xe7ersiz değer: beklenen ${i.expected}, alınan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ge\xe7ersiz değer: beklenen ${V.stringifyPrimitive(i.values[0])}`;return`Ge\xe7ersiz se\xe7enek: aşağıdakilerden biri olmalı: ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${t}${i.maximum.toString()} ${r.unit??"öğe"}`;return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${t}${i.minimum.toString()} ${r.unit}`;return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ge\xe7ersiz metin: "${i.prefix}" ile başlamalı`;if("ends_with"===i.format)return`Ge\xe7ersiz metin: "${i.suffix}" ile bitmeli`;if("includes"===i.format)return`Ge\xe7ersiz metin: "${i.includes}" i\xe7ermeli`;if("regex"===i.format)return`Ge\xe7ersiz metin: ${i.pattern} desenine uymalı`;return`Ge\xe7ersiz ${t[i.format]??i.format}`;case"not_multiple_of":return`Ge\xe7ersiz sayı: ${i.divisor} ile tam b\xf6l\xfcnebilmeli`;case"unrecognized_keys":return`Tanınmayan anahtar${i.keys.length>1?"lar":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7inde ge\xe7ersiz anahtar`;case"invalid_union":default:return"Geçersiz değer";case"invalid_element":return`${i.origin} i\xe7inde ge\xe7ersiz değer`}})}},"ua",0,function(){let e,t;return{localeError:(e={string:{unit:"символів",verb:"матиме"},file:{unit:"байтів",verb:"матиме"},array:{unit:"елементів",verb:"матиме"},set:{unit:"елементів",verb:"матиме"}},t={regex:"вхідні дані",email:"адреса електронної пошти",url:"URL",emoji:"емодзі",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"дата та час ISO",date:"дата ISO",time:"час ISO",duration:"тривалість ISO",ipv4:"адреса IPv4",ipv6:"адреса IPv6",cidrv4:"діапазон IPv4",cidrv6:"діапазон IPv6",base64:"рядок у кодуванні base64",base64url:"рядок у кодуванні base64url",json_string:"рядок JSON",e164:"номер E.164",jwt:"JWT",template_literal:"вхідні дані"},i=>{switch(i.code){case"invalid_type":return`Неправильні вхідні дані: очікується ${i.expected}, отримано ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"число";case"object":if(Array.isArray(e))return"масив";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Неправильні вхідні дані: очікується ${V.stringifyPrimitive(i.values[0])}`;return`Неправильна опція: очікується одне з ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Занадто велике: очікується, що ${i.origin??"значення"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"елементів"}`;return`Занадто велике: очікується, що ${i.origin??"значення"} буде ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Занадто мале: очікується, що ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Занадто мале: очікується, що ${i.origin} буде ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неправильний рядок: повинен починатися з "${i.prefix}"`;if("ends_with"===i.format)return`Неправильний рядок: повинен закінчуватися на "${i.suffix}"`;if("includes"===i.format)return`Неправильний рядок: повинен містити "${i.includes}"`;if("regex"===i.format)return`Неправильний рядок: повинен відповідати шаблону ${i.pattern}`;return`Неправильний ${t[i.format]??i.format}`;case"not_multiple_of":return`Неправильне число: повинно бути кратним ${i.divisor}`;case"unrecognized_keys":return`Нерозпізнаний ключ${i.keys.length>1?"і":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Неправильний ключ у ${i.origin}`;case"invalid_union":default:return"Неправильні вхідні дані";case"invalid_element":return`Неправильне значення у ${i.origin}`}})}},"ur",0,function(){let e,t;return{localeError:(e={string:{unit:"حروف",verb:"ہونا"},file:{unit:"بائٹس",verb:"ہونا"},array:{unit:"آئٹمز",verb:"ہونا"},set:{unit:"آئٹمز",verb:"ہونا"}},t={regex:"ان پٹ",email:"ای میل ایڈریس",url:"یو آر ایل",emoji:"ایموجی",uuid:"یو یو آئی ڈی",uuidv4:"یو یو آئی ڈی وی 4",uuidv6:"یو یو آئی ڈی وی 6",nanoid:"نینو آئی ڈی",guid:"جی یو آئی ڈی",cuid:"سی یو آئی ڈی",cuid2:"سی یو آئی ڈی 2",ulid:"یو ایل آئی ڈی",xid:"ایکس آئی ڈی",ksuid:"کے ایس یو آئی ڈی",datetime:"آئی ایس او ڈیٹ ٹائم",date:"آئی ایس او تاریخ",time:"آئی ایس او وقت",duration:"آئی ایس او مدت",ipv4:"آئی پی وی 4 ایڈریس",ipv6:"آئی پی وی 6 ایڈریس",cidrv4:"آئی پی وی 4 رینج",cidrv6:"آئی پی وی 6 رینج",base64:"بیس 64 ان کوڈڈ سٹرنگ",base64url:"بیس 64 یو آر ایل ان کوڈڈ سٹرنگ",json_string:"جے ایس او این سٹرنگ",e164:"ای 164 نمبر",jwt:"جے ڈبلیو ٹی",template_literal:"ان پٹ"},i=>{switch(i.code){case"invalid_type":return`غلط ان پٹ: ${i.expected} متوقع تھا، ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"نمبر";case"object":if(Array.isArray(e))return"آرے";if(null===e)return"نل";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} موصول ہوا`;case"invalid_value":if(1===i.values.length)return`غلط ان پٹ: ${V.stringifyPrimitive(i.values[0])} متوقع تھا`;return`غلط آپشن: ${V.joinValues(i.values,"|")} میں سے ایک متوقع تھا`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`بہت بڑا: ${i.origin??"ویلیو"} کے ${t}${i.maximum.toString()} ${r.unit??"عناصر"} ہونے متوقع تھے`;return`بہت بڑا: ${i.origin??"ویلیو"} کا ${t}${i.maximum.toString()} ہونا متوقع تھا`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`بہت چھوٹا: ${i.origin} کے ${t}${i.minimum.toString()} ${r.unit} ہونے متوقع تھے`;return`بہت چھوٹا: ${i.origin} کا ${t}${i.minimum.toString()} ہونا متوقع تھا`}case"invalid_format":if("starts_with"===i.format)return`غلط سٹرنگ: "${i.prefix}" سے شروع ہونا چاہیے`;if("ends_with"===i.format)return`غلط سٹرنگ: "${i.suffix}" پر ختم ہونا چاہیے`;if("includes"===i.format)return`غلط سٹرنگ: "${i.includes}" شامل ہونا چاہیے`;if("regex"===i.format)return`غلط سٹرنگ: پیٹرن ${i.pattern} سے میچ ہونا چاہیے`;return`غلط ${t[i.format]??i.format}`;case"not_multiple_of":return`غلط نمبر: ${i.divisor} کا مضاعف ہونا چاہیے`;case"unrecognized_keys":return`غیر تسلیم شدہ کی${i.keys.length>1?"ز":""}: ${V.joinValues(i.keys,"، ")}`;case"invalid_key":return`${i.origin} میں غلط کی`;case"invalid_union":default:return"غلط ان پٹ";case"invalid_element":return`${i.origin} میں غلط ویلیو`}})}},"vi",0,function(){let e,t;return{localeError:(e={string:{unit:"ký tự",verb:"có"},file:{unit:"byte",verb:"có"},array:{unit:"phần tử",verb:"có"},set:{unit:"phần tử",verb:"có"}},t={regex:"đầu vào",email:"địa chỉ email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ngày giờ ISO",date:"ngày ISO",time:"giờ ISO",duration:"khoảng thời gian ISO",ipv4:"địa chỉ IPv4",ipv6:"địa chỉ IPv6",cidrv4:"dải IPv4",cidrv6:"dải IPv6",base64:"chuỗi mã hóa base64",base64url:"chuỗi mã hóa base64url",json_string:"chuỗi JSON",e164:"số E.164",jwt:"JWT",template_literal:"đầu vào"},i=>{switch(i.code){case"invalid_type":return`Đầu v\xe0o kh\xf4ng hợp lệ: mong đợi ${i.expected}, nhận được ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"số";case"object":if(Array.isArray(e))return"mảng";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Đầu v\xe0o kh\xf4ng hợp lệ: mong đợi ${V.stringifyPrimitive(i.values[0])}`;return`T\xf9y chọn kh\xf4ng hợp lệ: mong đợi một trong c\xe1c gi\xe1 trị ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Qu\xe1 lớn: mong đợi ${i.origin??"giá trị"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"phần tử"}`;return`Qu\xe1 lớn: mong đợi ${i.origin??"giá trị"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Qu\xe1 nhỏ: mong đợi ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Qu\xe1 nhỏ: mong đợi ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải bắt đầu bằng "${i.prefix}"`;if("ends_with"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải kết th\xfac bằng "${i.suffix}"`;if("includes"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải bao gồm "${i.includes}"`;if("regex"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải khớp với mẫu ${i.pattern}`;return`${t[i.format]??i.format} kh\xf4ng hợp lệ`;case"not_multiple_of":return`Số kh\xf4ng hợp lệ: phải l\xe0 bội số của ${i.divisor}`;case"unrecognized_keys":return`Kh\xf3a kh\xf4ng được nhận dạng: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kh\xf3a kh\xf4ng hợp lệ trong ${i.origin}`;case"invalid_union":default:return"Đầu vào không hợp lệ";case"invalid_element":return`Gi\xe1 trị kh\xf4ng hợp lệ trong ${i.origin}`}})}},"zhCN",0,function(){let e,t;return{localeError:(e={string:{unit:"字符",verb:"包含"},file:{unit:"字节",verb:"包含"},array:{unit:"项",verb:"包含"},set:{unit:"项",verb:"包含"}},t={regex:"输入",email:"电子邮件",url:"URL",emoji:"表情符号",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO日期时间",date:"ISO日期",time:"ISO时间",duration:"ISO时长",ipv4:"IPv4地址",ipv6:"IPv6地址",cidrv4:"IPv4网段",cidrv6:"IPv6网段",base64:"base64编码字符串",base64url:"base64url编码字符串",json_string:"JSON字符串",e164:"E.164号码",jwt:"JWT",template_literal:"输入"},i=>{switch(i.code){case"invalid_type":return`无效输入：期望 ${i.expected}，实际接收 ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"非数字(NaN)":"数字";case"object":if(Array.isArray(e))return"数组";if(null===e)return"空值(null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`无效输入：期望 ${V.stringifyPrimitive(i.values[0])}`;return`无效选项：期望以下之一 ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`数值过大：期望 ${i.origin??"值"} ${t}${i.maximum.toString()} ${r.unit??"个元素"}`;return`数值过大：期望 ${i.origin??"值"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`数值过小：期望 ${i.origin} ${t}${i.minimum.toString()} ${r.unit}`;return`数值过小：期望 ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`无效字符串：必须以 "${i.prefix}" 开头`;if("ends_with"===i.format)return`无效字符串：必须以 "${i.suffix}" 结尾`;if("includes"===i.format)return`无效字符串：必须包含 "${i.includes}"`;if("regex"===i.format)return`无效字符串：必须满足正则表达式 ${i.pattern}`;return`无效${t[i.format]??i.format}`;case"not_multiple_of":return`无效数字：必须是 ${i.divisor} 的倍数`;case"unrecognized_keys":return`出现未知的键(key): ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} 中的键(key)无效`;case"invalid_union":default:return"无效输入";case"invalid_element":return`${i.origin} 中包含无效值(value)`}})}},"zhTW",0,function(){let e,t;return{localeError:(e={string:{unit:"字元",verb:"擁有"},file:{unit:"位元組",verb:"擁有"},array:{unit:"項目",verb:"擁有"},set:{unit:"項目",verb:"擁有"}},t={regex:"輸入",email:"郵件地址",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO 日期時間",date:"ISO 日期",time:"ISO 時間",duration:"ISO 期間",ipv4:"IPv4 位址",ipv6:"IPv6 位址",cidrv4:"IPv4 範圍",cidrv6:"IPv6 範圍",base64:"base64 編碼字串",base64url:"base64url 編碼字串",json_string:"JSON 字串",e164:"E.164 數值",jwt:"JWT",template_literal:"輸入"},i=>{switch(i.code){case"invalid_type":return`無效的輸入值：預期為 ${i.expected}，但收到 ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`無效的輸入值：預期為 ${V.stringifyPrimitive(i.values[0])}`;return`無效的選項：預期為以下其中之一 ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`數值過大：預期 ${i.origin??"值"} 應為 ${t}${i.maximum.toString()} ${r.unit??"個元素"}`;return`數值過大：預期 ${i.origin??"值"} 應為 ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`數值過小：預期 ${i.origin} 應為 ${t}${i.minimum.toString()} ${r.unit}`;return`數值過小：預期 ${i.origin} 應為 ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`無效的字串：必須以 "${i.prefix}" 開頭`;if("ends_with"===i.format)return`無效的字串：必須以 "${i.suffix}" 結尾`;if("includes"===i.format)return`無效的字串：必須包含 "${i.includes}"`;if("regex"===i.format)return`無效的字串：必須符合格式 ${i.pattern}`;return`無效的 ${t[i.format]??i.format}`;case"not_multiple_of":return`無效的數字：必須為 ${i.divisor} 的倍數`;case"unrecognized_keys":return`無法識別的鍵值${i.keys.length>1?"們":""}：${V.joinValues(i.keys,"、")}`;case"invalid_key":return`${i.origin} 中有無效的鍵值`;case"invalid_union":default:return"無效的輸入值";case"invalid_element":return`${i.origin} 中有無效的值`}})}}],554580);var tL=e.i(554580);let tC=Symbol("ZodOutput"),tR=Symbol("ZodInput");class tV{constructor(){this._map=new Map,this._idmap=new Map}add(e,...t){let i=t[0];if(this._map.set(e,i),i&&"object"==typeof i&&"id"in i){if(this._idmap.has(i.id))throw Error(`ID ${i.id} already exists in the registry`);this._idmap.set(i.id,e)}return this}clear(){return this._map=new Map,this._idmap=new Map,this}remove(e){let t=this._map.get(e);return t&&"object"==typeof t&&"id"in t&&this._idmap.delete(t.id),this._map.delete(e),this}get(e){let t=e._zod.parent;if(t){let i={...this.get(t)??{}};return delete 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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0fg87-n8e39u-.js b/litellm/proxy/_experimental/out/_next/static/chunks/0fg87-n8e39u-.js
deleted file mode 100644
index fee27afb201..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0fg87-n8e39u-.js
+++ /dev/null
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new file mode 100644
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0gh1eppc9ekzh.js b/litellm/proxy/_experimental/out/_next/static/chunks/0gh1eppc9ekzh.js
deleted file mode 100644
index 837a774d42b..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0gh1eppc9ekzh.js
+++ /dev/null
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new file mode 100644
index 00000000000..9eeea44e3b7
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/0i6-ixfyudd4f.js
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0ip4965b2mzha.js b/litellm/proxy/_experimental/out/_next/static/chunks/0ip4965b2mzha.js
deleted file mode 100644
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new file mode 100644
index 00000000000..e6a2911965e
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0k90yl9-v2vpb.js b/litellm/proxy/_experimental/out/_next/static/chunks/0k90yl9-v2vpb.js
deleted file mode 100644
index 819aa00a913..00000000000
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0ka-gct39e_d_.js b/litellm/proxy/_experimental/out/_next/static/chunks/0ka-gct39e_d_.js
deleted file mode 100644
index 745bb5c2c5b..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0ka-gct39e_d_.js
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break-all",children:eT.url})]})]})]}),eT.capabilities&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Capabilities"}),(0,s.jsx)("div",{className:"flex flex-wrap gap-2",children:Object.entries(eT.capabilities).filter(([e,s])=>!0===s).map(([e])=>(0,s.jsx)(c.Badge,{variant:"secondary",className:"capitalize",children:e},e))})]}),eT.skills&&eT.skills.length>0&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Skills"}),(0,s.jsx)("div",{className:"space-y-4",children:eT.skills.map((e,t)=>(0,s.jsxs)("div",{className:"border border-gray-200 rounded-lg p-4",children:[(0,s.jsx)("div",{className:"flex items-start justify-between mb-2",children:(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium text-base",children:e.name}),(0,s.jsx)("p",{className:"text-sm text-gray-600",children:e.description})]})}),e.tags&&e.tags.length>0&&(0,s.jsx)("div",{className:"flex flex-wrap gap-1 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-resolver = A2ACardResolver(
-    httpx_client=httpx_client,
-    base_url=base_url,
-    # agent_card_path uses default, extended_agent_card_path also uses default
-)
-
-# Fetch Public Agent Card and Initialize Client
-final_agent_card_to_use: AgentCard | None = None
-_public_card = (
-    await resolver.get_agent_card()
-)  # Fetches from default public path - \`/agents/{agent_id}/\`
-final_agent_card_to_use = _public_card
-
-if _public_card.supports_authenticated_extended_card:
-    try:
-        auth_headers_dict = {
-            'Authorization': 'Bearer dummy-token-for-extended-card'
-        }
-        _extended_card = await resolver.get_agent_card(
-            relative_card_path=EXTENDED_AGENT_CARD_PATH,
-            http_kwargs={'headers': auth_headers_dict},
-        )
-        final_agent_card_to_use = (
-            _extended_card  # Update to use the extended card
-        )
-    except Exception as e_extended:
-        logger.warning(
-            f'Failed to fetch extended agent card: {e_extended}. Will proceed with public card.',
-            exc_info=True,
-        )`})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU(`from a2a.client import A2ACardResolver, A2AClient
-from a2a.types import (
-    AgentCard,
-    MessageSendParams,
-    SendMessageRequest,
-    SendStreamingMessageRequest,
-)
-from a2a.utils.constants import (
-    AGENT_CARD_WELL_KNOWN_PATH,
-    EXTENDED_AGENT_CARD_PATH,
-)
-
-base_url = '${eT.url}'
-
-resolver = A2ACardResolver(
-    httpx_client=httpx_client,
-    base_url=base_url,
-    # agent_card_path uses default, extended_agent_card_path also uses default
-)
-
-# Fetch Public Agent Card and Initialize Client
-final_agent_card_to_use: AgentCard | None = None
-_public_card = (
-    await resolver.get_agent_card()
-)  # Fetches from default public path - \`/agents/{agent_id}/\`
-final_agent_card_to_use = _public_card
-
-if _public_card.supports_authenticated_extended_card:
-    try:
-        auth_headers_dict = {
-            'Authorization': 'Bearer dummy-token-for-extended-card'
-        }
-        _extended_card = await resolver.get_agent_card(
-            relative_card_path=EXTENDED_AGENT_CARD_PATH,
-            http_kwargs={'headers': auth_headers_dict},
-        )
-        final_agent_card_to_use = (
-            _extended_card  # Update to use the extended card
-        )
-    except Exception as e_extended:
-        logger.warning(
-            f'Failed to fetch extended agent card: {e_extended}. Will proceed with public card.',
-            exc_info=True,
-        )`)},className:"text-sm text-blue-600 hover:text-blue-800 cursor-pointer",children:"Copy to clipboard"})})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-sm font-medium mb-2 text-gray-700",children:"Step 2: Call the Agent"}),(0,s.jsx)("div",{className:"bg-gray-900 text-gray-100 p-4 rounded-lg overflow-x-auto",children:(0,s.jsx)("pre",{className:"text-xs",children:`client = A2AClient(
-    httpx_client=httpx_client, agent_card=final_agent_card_to_use
-)
-
-send_message_payload: dict[str, Any] = {
-    'message': {
-        'role': 'user',
-        'parts': [
-            {'kind': 'text', 'text': 'how much is 10 USD in INR?'}
-        ],
-        'messageId': uuid4().hex,
-    },
-}
-request = SendMessageRequest(
-    id=str(uuid4()), params=MessageSendParams(**send_message_payload)
-)
-
-response = await client.send_message(request)
-print(response.model_dump(mode='json', exclude_none=True))`})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU(`client = A2AClient(
-    httpx_client=httpx_client, agent_card=final_agent_card_to_use
-)
-
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-    'message': {
-        'role': 'user',
-        'parts': [
-            {'kind': 'text', 'text': 'how much is 10 USD in INR?'}
-        ],
-        'messageId': uuid4().hex,
-    },
-}
-request = SendMessageRequest(
-    id=str(uuid4()), params=MessageSendParams(**send_message_payload)
-)
-
-response = await client.send_message(request)
-print(response.model_dump(mode='json', exclude_none=True))`)},className:"text-sm text-blue-600 hover:text-blue-800 cursor-pointer",children:"Copy to clipboard"})})]})]})]})]})}),(0,s.jsx)(x.Dialog,{open:eS,onOpenChange:e=>!e&&void(ew(!1),eD(null)),children:(0,s.jsxs)(x.DialogContent,{className:"max-h-[calc(100dvh-2rem)] overflow-y-auto sm:max-w-[1000px]",children:[(0,s.jsx)(x.DialogHeader,{children:(0,s.jsxs)(x.DialogTitle,{className:"flex min-w-0 items-center space-x-2",children:[(0,s.jsx)("span",{className:"break-words",children:eM?.server_name||"MCP Server Details"}),eM&&(0,s.jsxs)(p.Tooltip,{children:[(0,s.jsx)(p.TooltipTrigger,{render:(0,s.jsx)(l.Copy,{onClick:()=>eU(eM.server_name),className:"cursor-pointer text-gray-500 hover:text-blue-500 w-4 h-4 shrink-0"})}),(0,s.jsx)(p.TooltipContent,{children:"Copy server name"})]})]})}),eM&&(0,s.jsxs)("div",{className:"space-y-6",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Server Overview"}),(0,s.jsxs)("div",{className:"grid grid-cols-2 gap-4 mb-4",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Server Name:"}),(0,s.jsx)("p",{children:eM.server_name})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Transport:"}),(0,s.jsx)(c.Badge,{variant:"secondary",children:eM.transport})]}),eM.alias&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Alias:"}),(0,s.jsx)("p",{children:eM.alias})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Auth Type:"}),(0,s.jsx)(c.Badge,{variant:"none"===eM.auth_type?"outline":"secondary",children:eM.auth_type})]}),(0,s.jsxs)("div",{className:"col-span-2",children:[(0,s.jsx)("p",{className:"font-medium",children:"Description:"}),(0,s.jsx)("p",{children:eM.mcp_info?.description||"-"})]})]})]}),eM.mcp_info&&Object.keys(eM.mcp_info).length>0&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Additional Information"}),(0,s.jsx)("div",{className:"bg-gray-50 p-4 rounded-lg",children:(0,s.jsx)("pre",{className:"text-xs overflow-x-auto",children:JSON.stringify(eM.mcp_info,null,2)})})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Usage Example"}),(0,s.jsx)("div",{className:"bg-gray-900 text-gray-100 p-4 rounded-lg overflow-x-auto",children:(0,s.jsx)("pre",{className:"text-sm",children:`# Using MCP Server with Python FastMCP
-
-from fastmcp import Client
-import asyncio
-
-# Standard MCP configuration
-config = {
-    "mcpServers": {
-        "${eM.server_name}": {
-            "url": "${(0,f.getProxyBaseUrl)()}/${eM.server_name}/mcp",
-            "headers": {
-                "x-litellm-api-key": "Bearer sk-1234"
-            }
-        }
-    }
-}
-
-# Create a client that connects to the server
-client = Client(config)
-
-async def main():
-    async with client:
-        # List available tools
-        tools = await client.list_tools()
-        print(f"Available tools: {[tool.name for tool in tools]}")
-
-        # Call a tool
-        response = await client.call_tool(
-            name="tool_name", 
-            arguments={"arg": "value"}
-        )
-        print(f"Response: {response}")
-
-if __name__ == "__main__":
-    asyncio.run(main())`})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU(`# Using MCP Server with Python FastMCP
-
-from fastmcp import Client
-import asyncio
-
-# Standard MCP configuration
-config = {
-    "mcpServers": {
-        "${eM.server_name}": {
-            "url": "${(0,f.getProxyBaseUrl)()}/${eM.server_name}/mcp",
-            "headers": {
-                "x-litellm-api-key": "Bearer sk-1234"
-            }
-        }
-    }
-}
-
-# Create a client that connects to the server
-client = Client(config)
-
-async def main():
-    async with client:
-        # List available tools
-        tools = await client.list_tools()
-        print(f"Available tools: {[tool.name for tool in tools]}")
-
-        # Call a tool
-        response = await client.call_tool(
-            name="tool_name", 
-            arguments={"arg": "value"}
-        )
-        print(f"Response: {response}")
-
-if __name__ == "__main__":
-    asyncio.run(main())`)},className:"text-sm text-blue-600 hover:text-blue-800 cursor-pointer",children:"Copy to clipboard"})})]})]})]})})]})})})}],976883)}]);
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0kh2zb6nfmf3l.js b/litellm/proxy/_experimental/out/_next/static/chunks/0kh2zb6nfmf3l.js
deleted file mode 100644
index 8ddfbe69155..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0kh2zb6nfmf3l.js
+++ /dev/null
@@ -1,49 +0,0 @@
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\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0km97o3tsjt8m.js b/litellm/proxy/_experimental/out/_next/static/chunks/0km97o3tsjt8m.js
deleted file mode 100644
index deb2119256f..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0km97o3tsjt8m.js
+++ /dev/null
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+
+client = openai.AzureOpenAI(
+	api_key="${b||"YOUR_LITELLM_API_KEY"}",
+	azure_endpoint="${v}",
+	api_version="2024-02-01"
+)`:`import openai
+
+client = openai.OpenAI(
+	api_key="${b||"YOUR_LITELLM_API_KEY"}",
+	base_url="${v}"
+)`;switch(h){case o.CHAT:{let e=Object.keys(w).length>0,i="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`,
+    extra_body=${e}`}let r=k.length>0?k:[{role:"user",content:x}];t=`
+import base64
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Example with text only
+response = client.chat.completions.create(
+    model="${C}",
+    messages=${JSON.stringify(r,null,4)}${i}
+)
+
+print(response)
+
+# Example with image or PDF (uncomment and provide file path to use)
+# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
+# response_with_file = client.chat.completions.create(
+#     model="${C}",
+#     messages=[
+#         {
+#             "role": "user",
+#             "content": [
+#                 {
+#                     "type": "text",
+#                     "text": "${_}"
+#                 },
+#                 {
+#                     "type": "image_url",
+#                     "image_url": {
+#                         "url": f"data:image/jpeg;base64,{base64_file}"  # or data:application/pdf;base64,{base64_file}
+#                     }
+#                 }
+#             ]
+#         }
+#     ]${i}
+# )
+# print(response_with_file)
+`;break}case o.RESPONSES:{let e=Object.keys(w).length>0,i="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`,
+    extra_body=${e}`}let r=k.length>0?k:[{role:"user",content:x}];t=`
+import base64
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Example with text only
+response = client.responses.create(
+    model="${C}",
+    input=${JSON.stringify(r,null,4)}${i}
+)
+
+print(response.output_text)
+
+# Example with image or PDF (uncomment and provide file path to use)
+# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
+# response_with_file = client.responses.create(
+#     model="${C}",
+#     input=[
+#         {
+#             "role": "user",
+#             "content": [
+#                 {"type": "input_text", "text": "${_}"},
+#                 {
+#                     "type": "input_image",
+#                     "image_url": f"data:image/jpeg;base64,{base64_file}",  # or data:application/pdf;base64,{base64_file}
+#                 },
+#             ],
+#         }
+#     ]${i}
+# )
+# print(response_with_file.output_text)
+`;break}case o.IMAGE:t="azure"===g?`
+# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI.
+# This snippet uses 'client.images.generate' and will create a new image based on your prompt.
+# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context.
+import os
+import requests
+import json
+import time
+from PIL import Image
+
+result = client.images.generate(
+	model="${C}",
+	prompt="${s}",
+	n=1
+)
+
+json_response = json.loads(result.model_dump_json())
+
+# Set the directory for the stored image
+image_dir = os.path.join(os.curdir, 'images')
+
+# If the directory doesn't exist, create it
+if not os.path.isdir(image_dir):
+	os.mkdir(image_dir)
+
+# Initialize the image path
+image_filename = f"generated_image_{int(time.time())}.png"
+image_path = os.path.join(image_dir, image_filename)
+
+try:
+	# Retrieve the generated image
+	if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"):
+			image_url = json_response["data"][0]["url"]
+			generated_image = requests.get(image_url).content
+			with open(image_path, "wb") as image_file:
+					image_file.write(generated_image)
+
+			print(f"Image saved to {image_path}")
+			# Display the image
+			image = Image.open(image_path)
+			image.show()
+	else:
+			print("Could not find image URL in response.")
+			print("Full response:", json_response)
+except Exception as e:
+	print(f"An error occurred: {e}")
+	print("Full response:", json_response)
+`:`
+import base64
+import os
+import time
+import json
+from PIL import Image
+import requests
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+	with open(image_path, "rb") as image_file:
+			return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Helper function to create a file (simplified for this example)
+def create_file(image_path):
+	# In a real implementation, this would upload the file to OpenAI
+	# For this example, we'll just return a placeholder ID
+	return f"file_{os.path.basename(image_path).replace('.', '_')}"
+
+# The prompt entered by the user
+prompt = "${_}"
+
+# Encode images to base64
+base64_image1 = encode_image("body-lotion.png")
+base64_image2 = encode_image("soap.png")
+
+# Create file IDs
+file_id1 = create_file("body-lotion.png")
+file_id2 = create_file("incense-kit.png")
+
+response = client.responses.create(
+	model="${C}",
+	input=[
+			{
+					"role": "user",
+					"content": [
+							{"type": "input_text", "text": prompt},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image1}",
+							},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image2}",
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id1,
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id2,
+							}
+					],
+			}
+	],
+	tools=[{"type": "image_generation"}],
+)
+
+# Process the response
+image_generation_calls = [
+	output
+	for output in response.output
+	if output.type == "image_generation_call"
+]
+
+image_data = [output.result for output in image_generation_calls]
+
+if image_data:
+	image_base64 = image_data[0]
+	image_filename = f"edited_image_{int(time.time())}.png"
+	with open(image_filename, "wb") as f:
+			f.write(base64.b64decode(image_base64))
+	print(f"Image saved to {image_filename}")
+else:
+	# If no image is generated, there might be a text response with an explanation
+	text_response = [output.text for output in response.output if hasattr(output, 'text')]
+	if text_response:
+			print("No image generated. Model response:")
+			print("\\n".join(text_response))
+	else:
+			print("No image data found in response.")
+	print("Full response for debugging:")
+	print(response)
+`;break;case o.IMAGE_EDITS:t="azure"===g?`
+import base64
+import os
+import time
+import json
+from PIL import Image
+import requests
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+	with open(image_path, "rb") as image_file:
+			return base64.b64encode(image_file.read()).decode('utf-8')
+
+# The prompt entered by the user
+prompt = "${_}"
+
+# Encode images to base64
+base64_image1 = encode_image("body-lotion.png")
+base64_image2 = encode_image("soap.png")
+
+# Create file IDs
+file_id1 = create_file("body-lotion.png")
+file_id2 = create_file("incense-kit.png")
+
+response = client.responses.create(
+	model="${C}",
+	input=[
+			{
+					"role": "user",
+					"content": [
+							{"type": "input_text", "text": prompt},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image1}",
+							},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image2}",
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id1,
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id2,
+							}
+					],
+			}
+	],
+	tools=[{"type": "image_generation"}],
+)
+
+# Process the response
+image_generation_calls = [
+	output
+	for output in response.output
+	if output.type == "image_generation_call"
+]
+
+image_data = [output.result for output in image_generation_calls]
+
+if image_data:
+	image_base64 = image_data[0]
+	image_filename = f"edited_image_{int(time.time())}.png"
+	with open(image_filename, "wb") as f:
+			f.write(base64.b64decode(image_base64))
+	print(f"Image saved to {image_filename}")
+else:
+	# If no image is generated, there might be a text response with an explanation
+	text_response = [output.text for output in response.output if hasattr(output, 'text')]
+	if text_response:
+			print("No image generated. Model response:")
+			print("\\n".join(text_response))
+	else:
+			print("No image data found in response.")
+	print("Full response for debugging:")
+	print(response)
+`:`
+import base64
+import os
+import time
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+	with open(image_path, "rb") as image_file:
+			return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Helper function to create a file (simplified for this example)
+def create_file(image_path):
+	# In a real implementation, this would upload the file to OpenAI
+	# For this example, we'll just return a placeholder ID
+	return f"file_{os.path.basename(image_path).replace('.', '_')}"
+
+# The prompt entered by the user
+prompt = "${_}"
+
+# Encode images to base64
+base64_image1 = encode_image("body-lotion.png")
+base64_image2 = encode_image("soap.png")
+
+# Create file IDs
+file_id1 = create_file("body-lotion.png")
+file_id2 = create_file("incense-kit.png")
+
+response = client.responses.create(
+	model="${C}",
+	input=[
+			{
+					"role": "user",
+					"content": [
+							{"type": "input_text", "text": prompt},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image1}",
+							},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image2}",
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id1,
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id2,
+							}
+					],
+			}
+	],
+	tools=[{"type": "image_generation"}],
+)
+
+# Process the response
+image_generation_calls = [
+	output
+	for output in response.output
+	if output.type == "image_generation_call"
+]
+
+image_data = [output.result for output in image_generation_calls]
+
+if image_data:
+	image_base64 = image_data[0]
+	image_filename = f"edited_image_{int(time.time())}.png"
+	with open(image_filename, "wb") as f:
+			f.write(base64.b64decode(image_base64))
+	print(f"Image saved to {image_filename}")
+else:
+	# If no image is generated, there might be a text response with an explanation
+	text_response = [output.text for output in response.output if hasattr(output, 'text')]
+	if text_response:
+			print("No image generated. Model response:")
+			print("\\n".join(text_response))
+	else:
+			print("No image data found in response.")
+	print("Full response for debugging:")
+	print(response)
+`;break;case o.EMBEDDINGS:t=`
+response = client.embeddings.create(
+	input="${s||"Your string here"}",
+	model="${C}",
+	encoding_format="base64" # or "float"
+)
+
+print(response.data[0].embedding)
+`;break;case o.TRANSCRIPTION:t=`
+# Open the audio file
+audio_file = open("path/to/your/audio/file.mp3", "rb")
+
+# Make the transcription request
+response = client.audio.transcriptions.create(
+	model="${C}",
+	file=audio_file${s?`,
+	prompt="${s.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""}
+)
+
+print(response.text)
+`;break;case o.SPEECH:t=`
+# Make the text-to-speech request
+response = client.audio.speech.create(
+	model="${C}",
+	input="${s||"Your text to convert to speech here"}",
+	voice="${p}"  # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer
+)
+
+# Save the audio to a file
+output_filename = "output_speech.mp3"
+response.stream_to_file(output_filename)
+print(f"Audio saved to {output_filename}")
+
+# Optional: Customize response format and speed
+# response = client.audio.speech.create(
+#     model="${C}",
+#     input="${s||"Your text to convert to speech here"}",
+#     voice="alloy",
+#     response_format="mp3",  # Options: mp3, opus, aac, flac, wav, pcm
+#     speed=1.0  # Range: 0.25 to 4.0
+# )
+# response.stream_to_file("output_speech.mp3")
+`;break;default:t="\n# Code generation for this endpoint is not implemented yet."}return`${j}
+${t}`}],909947)},975558,e=>{"use strict";let t=(0,e.i(475254).default)("arrow-up",[["path",{d:"m5 12 7-7 7 7",key:"hav0vg"}],["path",{d:"M12 19V5",key:"x0mq9r"}]]);e.s(["ArrowUp",0,t],975558)},440160,e=>{"use strict";let t=(0,e.i(475254).default)("download",[["path",{d:"M12 15V3",key:"m9g1x1"}],["path",{d:"M21 15v4a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2v-4",key:"ih7n3h"}],["path",{d:"m7 10 5 5 5-5",key:"brsn70"}]]);e.s(["Download",0,t],440160)},59935,(e,t,i)=>{var r;let o;e.e,r=function e(){var t,i="u">typeof self?self:"u">typeof window?window:void 0!==i?i:{},r=!i.document&&!!i.postMessage,o=i.IS_PAPA_WORKER||!1,n={},s=0,a={};function l(e){this._handle=null,this._finished=!1,this._completed=!1,this._halted=!1,this._input=null,this._baseIndex=0,this._partialLine="",this._rowCount=0,this._start=0,this._nextChunk=null,this.isFirstChunk=!0,this._completeResults={data:[],errors:[],meta:{}},(function(e){var t=y(e);t.chunkSize=parseInt(t.chunkSize),e.step||e.chunk||(t.chunkSize=null),this._handle=new 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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0po-w3i9dl10e.js b/litellm/proxy/_experimental/out/_next/static/chunks/0po-w3i9dl10e.js
deleted file mode 100644
index 4dc9b08cc4b..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0po-w3i9dl10e.js
+++ /dev/null
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0qj0ui4evv0i3.js b/litellm/proxy/_experimental/out/_next/static/chunks/0qj0ui4evv0i3.js
deleted file mode 100644
index 31e795ced14..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0qj0ui4evv0i3.js
+++ /dev/null
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new file mode 100644
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\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0r1clxs9ojvmu.js b/litellm/proxy/_experimental/out/_next/static/chunks/0r1clxs9ojvmu.js
deleted file mode 100644
index c7a745e441d..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0r1clxs9ojvmu.js
+++ /dev/null
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new file mode 100644
index 00000000000..378298c2c71
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0riud7s6aml9k.js b/litellm/proxy/_experimental/out/_next/static/chunks/0riud7s6aml9k.js
deleted file mode 100644
index 480d3e1c314..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0riud7s6aml9k.js
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new file mode 100644
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0w77sqpg7lx8k.js b/litellm/proxy/_experimental/out/_next/static/chunks/0w77sqpg7lx8k.js
deleted file mode 100644
index 2e612c9a0ea..00000000000
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0x7q90wg0su1_.js b/litellm/proxy/_experimental/out/_next/static/chunks/0x7q90wg0su1_.js
new file mode 100644
index 00000000000..5e0710d32be
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/0x7q90wg0su1_.js
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t,i,o=((t={}).AUDIO_SPEECH="audio_speech",t.AUDIO_TRANSCRIPTION="audio_transcription",t.IMAGE_GENERATION="image_generation",t.VIDEO_GENERATION="video_generation",t.CHAT="chat",t.COMPLETION="completion",t.RESPONSES="responses",t.IMAGE_EDITS="image_edit",t.ANTHROPIC_MESSAGES="anthropic_messages",t.EMBEDDING="embedding",t.REALTIME="realtime",t),a=((i={}).IMAGE="image",i.VIDEO="video",i.CHAT="chat",i.RESPONSES="responses",i.IMAGE_EDITS="image_edits",i.ANTHROPIC_MESSAGES="anthropic_messages",i.EMBEDDINGS="embeddings",i.SPEECH="speech",i.TRANSCRIPTION="transcription",i.A2A_AGENTS="a2a_agents",i.MCP="mcp",i.REALTIME="realtime",i.INTERACTIONS="interactions",i);let n={image_generation:"image",video_generation:"video",chat:"chat",completion:"chat",responses:"responses",image_edit:"image_edits",anthropic_messages:"anthropic_messages",audio_speech:"speech",audio_transcription:"transcription",embedding:"embeddings",realtime:"realtime"};e.s(["EndpointType",()=>a,"ModelMode",()=>o,"getEndpointType",0,e=>Object.values(o).includes(e)?n[e]:"chat"],865361),e.s(["generateCodeSnippet",0,e=>{let t,{apiKeySource:i,accessToken:o,apiKey:n,inputMessage:r,chatHistory:s,selectedTags:l,selectedVectorStores:p,selectedGuardrails:d,selectedPolicies:u,selectedVoice:c,endpointType:g,selectedModel:m,selectedSdk:f,proxySettings:h}=e,x="session"===i?o:n,_=window.location.origin,b=h?.LITELLM_UI_API_DOC_BASE_URL;b&&b.trim()?_=b:h?.PROXY_BASE_URL&&(_=h.PROXY_BASE_URL);let y=r||"Your prompt here",v=y.replace(/\\/g,"\\\\").replace(/"/g,'\\"').replace(/\n/g,"\\n"),S=s.filter(e=>!e.isImage).map(({role:e,content:t})=>({role:e,content:t})),C={};l.length>0&&(C.tags=l),p.length>0&&(C.vector_stores=p),d.length>0&&(C.guardrails=d),u.length>0&&(C.policies=u);let j=m||"your-model-name",E="azure"===f?`import openai
+
+client = openai.AzureOpenAI(
+	api_key="${x||"YOUR_LITELLM_API_KEY"}",
+	azure_endpoint="${_}",
+	api_version="2024-02-01"
+)`:`import openai
+
+client = openai.OpenAI(
+	api_key="${x||"YOUR_LITELLM_API_KEY"}",
+	base_url="${_}"
+)`;switch(g){case a.CHAT:{let e=Object.keys(C).length>0,i="";if(e){let e=JSON.stringify({metadata:C},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`,
+    extra_body=${e}`}let o=S.length>0?S:[{role:"user",content:y}];t=`
+import base64
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Example with text only
+response = client.chat.completions.create(
+    model="${j}",
+    messages=${JSON.stringify(o,null,4)}${i}
+)
+
+print(response)
+
+# Example with image or PDF (uncomment and provide file path to use)
+# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
+# response_with_file = client.chat.completions.create(
+#     model="${j}",
+#     messages=[
+#         {
+#             "role": "user",
+#             "content": [
+#                 {
+#                     "type": "text",
+#                     "text": "${v}"
+#                 },
+#                 {
+#                     "type": "image_url",
+#                     "image_url": {
+#                         "url": f"data:image/jpeg;base64,{base64_file}"  # or data:application/pdf;base64,{base64_file}
+#                     }
+#                 }
+#             ]
+#         }
+#     ]${i}
+# )
+# print(response_with_file)
+`;break}case a.RESPONSES:{let e=Object.keys(C).length>0,i="";if(e){let e=JSON.stringify({metadata:C},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`,
+    extra_body=${e}`}let o=S.length>0?S:[{role:"user",content:y}];t=`
+import base64
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Example with text only
+response = client.responses.create(
+    model="${j}",
+    input=${JSON.stringify(o,null,4)}${i}
+)
+
+print(response.output_text)
+
+# Example with image or PDF (uncomment and provide file path to use)
+# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
+# response_with_file = client.responses.create(
+#     model="${j}",
+#     input=[
+#         {
+#             "role": "user",
+#             "content": [
+#                 {"type": "input_text", "text": "${v}"},
+#                 {
+#                     "type": "input_image",
+#                     "image_url": f"data:image/jpeg;base64,{base64_file}",  # or data:application/pdf;base64,{base64_file}
+#                 },
+#             ],
+#         }
+#     ]${i}
+# )
+# print(response_with_file.output_text)
+`;break}case a.IMAGE:t="azure"===f?`
+# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI.
+# This snippet uses 'client.images.generate' and will create a new image based on your prompt.
+# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context.
+import os
+import requests
+import json
+import time
+from PIL import Image
+
+result = client.images.generate(
+	model="${j}",
+	prompt="${r}",
+	n=1
+)
+
+json_response = json.loads(result.model_dump_json())
+
+# Set the directory for the stored image
+image_dir = os.path.join(os.curdir, 'images')
+
+# If the directory doesn't exist, create it
+if not os.path.isdir(image_dir):
+	os.mkdir(image_dir)
+
+# Initialize the image path
+image_filename = f"generated_image_{int(time.time())}.png"
+image_path = os.path.join(image_dir, image_filename)
+
+try:
+	# Retrieve the generated image
+	if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"):
+			image_url = json_response["data"][0]["url"]
+			generated_image = requests.get(image_url).content
+			with open(image_path, "wb") as image_file:
+					image_file.write(generated_image)
+
+			print(f"Image saved to {image_path}")
+			# Display the image
+			image = Image.open(image_path)
+			image.show()
+	else:
+			print("Could not find image URL in response.")
+			print("Full response:", json_response)
+except Exception as e:
+	print(f"An error occurred: {e}")
+	print("Full response:", json_response)
+`:`
+import base64
+import os
+import time
+import json
+from PIL import Image
+import requests
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+	with open(image_path, "rb") as image_file:
+			return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Helper function to create a file (simplified for this example)
+def create_file(image_path):
+	# In a real implementation, this would upload the file to OpenAI
+	# For this example, we'll just return a placeholder ID
+	return f"file_{os.path.basename(image_path).replace('.', '_')}"
+
+# The prompt entered by the user
+prompt = "${v}"
+
+# Encode images to base64
+base64_image1 = encode_image("body-lotion.png")
+base64_image2 = encode_image("soap.png")
+
+# Create file IDs
+file_id1 = create_file("body-lotion.png")
+file_id2 = create_file("incense-kit.png")
+
+response = client.responses.create(
+	model="${j}",
+	input=[
+			{
+					"role": "user",
+					"content": [
+							{"type": "input_text", "text": prompt},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image1}",
+							},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image2}",
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id1,
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id2,
+							}
+					],
+			}
+	],
+	tools=[{"type": "image_generation"}],
+)
+
+# Process the response
+image_generation_calls = [
+	output
+	for output in response.output
+	if output.type == "image_generation_call"
+]
+
+image_data = [output.result for output in image_generation_calls]
+
+if image_data:
+	image_base64 = image_data[0]
+	image_filename = f"edited_image_{int(time.time())}.png"
+	with open(image_filename, "wb") as f:
+			f.write(base64.b64decode(image_base64))
+	print(f"Image saved to {image_filename}")
+else:
+	# If no image is generated, there might be a text response with an explanation
+	text_response = [output.text for output in response.output if hasattr(output, 'text')]
+	if text_response:
+			print("No image generated. Model response:")
+			print("\\n".join(text_response))
+	else:
+			print("No image data found in response.")
+	print("Full response for debugging:")
+	print(response)
+`;break;case a.IMAGE_EDITS:t="azure"===f?`
+import base64
+import os
+import time
+import json
+from PIL import Image
+import requests
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+	with open(image_path, "rb") as image_file:
+			return base64.b64encode(image_file.read()).decode('utf-8')
+
+# The prompt entered by the user
+prompt = "${v}"
+
+# Encode images to base64
+base64_image1 = encode_image("body-lotion.png")
+base64_image2 = encode_image("soap.png")
+
+# Create file IDs
+file_id1 = create_file("body-lotion.png")
+file_id2 = create_file("incense-kit.png")
+
+response = client.responses.create(
+	model="${j}",
+	input=[
+			{
+					"role": "user",
+					"content": [
+							{"type": "input_text", "text": prompt},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image1}",
+							},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image2}",
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id1,
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id2,
+							}
+					],
+			}
+	],
+	tools=[{"type": "image_generation"}],
+)
+
+# Process the response
+image_generation_calls = [
+	output
+	for output in response.output
+	if output.type == "image_generation_call"
+]
+
+image_data = [output.result for output in image_generation_calls]
+
+if image_data:
+	image_base64 = image_data[0]
+	image_filename = f"edited_image_{int(time.time())}.png"
+	with open(image_filename, "wb") as f:
+			f.write(base64.b64decode(image_base64))
+	print(f"Image saved to {image_filename}")
+else:
+	# If no image is generated, there might be a text response with an explanation
+	text_response = [output.text for output in response.output if hasattr(output, 'text')]
+	if text_response:
+			print("No image generated. Model response:")
+			print("\\n".join(text_response))
+	else:
+			print("No image data found in response.")
+	print("Full response for debugging:")
+	print(response)
+`:`
+import base64
+import os
+import time
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+	with open(image_path, "rb") as image_file:
+			return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Helper function to create a file (simplified for this example)
+def create_file(image_path):
+	# In a real implementation, this would upload the file to OpenAI
+	# For this example, we'll just return a placeholder ID
+	return f"file_{os.path.basename(image_path).replace('.', '_')}"
+
+# The prompt entered by the user
+prompt = "${v}"
+
+# Encode images to base64
+base64_image1 = encode_image("body-lotion.png")
+base64_image2 = encode_image("soap.png")
+
+# Create file IDs
+file_id1 = create_file("body-lotion.png")
+file_id2 = create_file("incense-kit.png")
+
+response = client.responses.create(
+	model="${j}",
+	input=[
+			{
+					"role": "user",
+					"content": [
+							{"type": "input_text", "text": prompt},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image1}",
+							},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image2}",
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id1,
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id2,
+							}
+					],
+			}
+	],
+	tools=[{"type": "image_generation"}],
+)
+
+# Process the response
+image_generation_calls = [
+	output
+	for output in response.output
+	if output.type == "image_generation_call"
+]
+
+image_data = [output.result for output in image_generation_calls]
+
+if image_data:
+	image_base64 = image_data[0]
+	image_filename = f"edited_image_{int(time.time())}.png"
+	with open(image_filename, "wb") as f:
+			f.write(base64.b64decode(image_base64))
+	print(f"Image saved to {image_filename}")
+else:
+	# If no image is generated, there might be a text response with an explanation
+	text_response = [output.text for output in response.output if hasattr(output, 'text')]
+	if text_response:
+			print("No image generated. Model response:")
+			print("\\n".join(text_response))
+	else:
+			print("No image data found in response.")
+	print("Full response for debugging:")
+	print(response)
+`;break;case a.EMBEDDINGS:t=`
+response = client.embeddings.create(
+	input="${r||"Your string here"}",
+	model="${j}",
+	encoding_format="base64" # or "float"
+)
+
+print(response.data[0].embedding)
+`;break;case a.TRANSCRIPTION:t=`
+# Open the audio file
+audio_file = open("path/to/your/audio/file.mp3", "rb")
+
+# Make the transcription request
+response = client.audio.transcriptions.create(
+	model="${j}",
+	file=audio_file${r?`,
+	prompt="${r.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""}
+)
+
+print(response.text)
+`;break;case a.SPEECH:t=`
+# Make the text-to-speech request
+response = client.audio.speech.create(
+	model="${j}",
+	input="${r||"Your text to convert to speech here"}",
+	voice="${c}"  # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer
+)
+
+# Save the audio to a file
+output_filename = "output_speech.mp3"
+response.stream_to_file(output_filename)
+print(f"Audio saved to {output_filename}")
+
+# Optional: Customize response format and speed
+# response = client.audio.speech.create(
+#     model="${j}",
+#     input="${r||"Your text to convert to speech here"}",
+#     voice="alloy",
+#     response_format="mp3",  # Options: mp3, opus, aac, flac, wav, pcm
+#     speed=1.0  # Range: 0.25 to 4.0
+# )
+# response.stream_to_file("output_speech.mp3")
+`;break;default:t="\n# Code generation for this endpoint is not implemented yet."}return`${E}
+${t}`}],909947)},306228,e=>{"use strict";let t=(0,e.i(475254).default)("link-2",[["path",{d:"M9 17H7A5 5 0 0 1 7 7h2",key:"8i5ue5"}],["path",{d:"M15 7h2a5 5 0 1 1 0 10h-2",key:"1b9ql8"}],["line",{x1:"8",x2:"16",y1:"12",y2:"12",key:"1jonct"}]]);e.s(["Link2",0,t],306228)},652272,209261,e=>{"use strict";var t=e.i(843476),i=e.i(271645),o=e.i(871689),a=e.i(643531),n=e.i(174886),r=e.i(306228);let s=/^[a-zA-Z0-9][a-zA-Z0-9._-]*(\/[a-zA-Z0-9][a-zA-Z0-9._-]*)*$/,l=e=>e.trim().replace(/\/+$/,""),p=/\.(md|markdown|txt|json|ya?ml|toml)$/i,d=/^\d{1,3}(\.\d{1,3}){3}$/,u=/^[A-Za-z0-9-]+$/,c=/^[A-Za-z0-9._-]+$/,g=e=>e.pathname.split("/").filter(e=>""!==e),m=e=>{let t=e.split("/").filter(e=>""!==e);return 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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0z8f5ldy8t_47.js b/litellm/proxy/_experimental/out/_next/static/chunks/0z8f5ldy8t_47.js
deleted file mode 100644
index d6868a762ac..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0z8f5ldy8t_47.js
+++ /dev/null
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1-2-19c6kju0k.js b/litellm/proxy/_experimental/out/_next/static/chunks/1-2-19c6kju0k.js
new file mode 100644
index 00000000000..cc8cd0ddd37
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+++ b/litellm/proxy/_experimental/out/_next/static/chunks/1-2-19c6kju0k.js
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new file mode 100644
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new file mode 100644
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+++ b/litellm/proxy/_experimental/out/_next/static/chunks/12j1nmc42-2_c.js
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deleted file mode 100644
index 9d288a5fa62..00000000000
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/14_h_ke0k_axb.js b/litellm/proxy/_experimental/out/_next/static/chunks/14_h_ke0k_axb.js
deleted file mode 100644
index 977d69ef8a1..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/14_h_ke0k_axb.js
+++ /dev/null
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new file mode 100644
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+        if (${i}.issues.length) {
+          if (input[${a}] === undefined) {
+            if (${a} in input) {
+              newResult[${a}] = undefined;
+            }
+          } else {
+            payload.issues = payload.issues.concat(
+              ${i}.issues.map((iss) => ({
+                ...iss,
+                path: iss.path ? [${a}, ...iss.path] : [${a}],
+              }))
+            );
+          }
+        } else if (${i}.value === undefined) {
+          if (${a} in input) newResult[${a}] = undefined;
+        } else {
+          newResult[${a}] = ${i}.value;
+        }
+        `)}else{let i=n[e];t.write(`const ${i} = ${r(e)};`),t.write(`
+          if (${i}.issues.length) payload.issues = payload.issues.concat(${i}.issues.map(iss => ({
+            ...iss,
+            path: iss.path ? [${V.esc(e)}, ...iss.path] : [${V.esc(e)}]
+          })));`),t.write(`newResult[${V.esc(e)}] = ${i}.value`)}t.write("payload.value = newResult;"),t.write("return payload;");let u=t.compile();return(t,i)=>u(e,t,i)})(i.shape)),t=r(t,s);else{t.value={};let e=n.shape;for(let i of n.keys){let r=e[i],n=r._zod.run({value:d[i],issues:[]},s),a="optional"===r._zod.optin&&"optional"===r._zod.optout;n instanceof Promise?m.push(n.then(e=>a?e3(e,t,i,d):e9(e,t,i))):a?e3(n,t,i,d):e9(n,t,i)}}if(!c)return m.length?Promise.all(m).then(()=>t):t;let f=[],p=n.keySet,v=c._zod,g=v.def.type;for(let e of Object.keys(d)){if(p.has(e))continue;if("never"===g){f.push(e);continue}let i=v.run({value:d[e],issues:[]},s);i instanceof Promise?m.push(i.then(i=>e9(i,t,e))):e9(i,t,e)}return(f.length&&t.issues.push({code:"unrecognized_keys",keys:f,input:d,inst:e}),m.length)?Promise.all(m).then(()=>t):t}});function e5(e,i,r,n){for(let t of e)if(0===t.issues.length)return i.value=t.value,i;return i.issues.push({code:"invalid_union",input:i.value,inst:r,errors:e.map(e=>e.issues.map(e=>V.finalizeIssue(e,n,t.config())))}),i}let e8=t.$constructor("$ZodUnion",(e,t)=>{ep.init(e,t),V.defineLazy(e._zod,"optin",()=>t.options.some(e=>"optional"===e._zod.optin)?"optional":void 0),V.defineLazy(e._zod,"optout",()=>t.options.some(e=>"optional"===e._zod.optout)?"optional":void 0),V.defineLazy(e._zod,"values",()=>{if(t.options.every(e=>e._zod.values))return new Set(t.options.flatMap(e=>Array.from(e._zod.values)))}),V.defineLazy(e._zod,"pattern",()=>{if(t.options.every(e=>e._zod.pattern)){let e=t.options.map(e=>e._zod.pattern);return RegExp(`^(${e.map(e=>V.cleanRegex(e.source)).join("|")})$`)}}),e._zod.parse=(i,r)=>{let n=!1,a=[];for(let e of t.options){let t=e._zod.run({value:i.value,issues:[]},r);if(t instanceof Promise)a.push(t),n=!0;else{if(0===t.issues.length)return t;a.push(t)}}return n?Promise.all(a).then(t=>e5(t,i,e,r)):e5(a,i,e,r)}}),te=t.$constructor("$ZodDiscriminatedUnion",(e,t)=>{e8.init(e,t);let i=e._zod.parse;V.defineLazy(e._zod,"propValues",()=>{let e={};for(let i of t.options){let r=i._zod.propValues;if(!r||0===Object.keys(r).length)throw Error(`Invalid discriminated union option at index "${t.options.indexOf(i)}"`);for(let[t,i]of Object.entries(r))for(let r of(e[t]||(e[t]=new Set),i))e[t].add(r)}return e});let r=V.cached(()=>{let e=t.options,i=new Map;for(let r of e){let e=r._zod.propValues[t.discriminator];if(!e||0===e.size)throw Error(`Invalid discriminated union option at index "${t.options.indexOf(r)}"`);for(let t of e){if(i.has(t))throw Error(`Duplicate discriminator value "${String(t)}"`);i.set(t,r)}}return i});e._zod.parse=(n,a)=>{let o=n.value;if(!V.isObject(o))return n.issues.push({code:"invalid_type",expected:"object",input:o,inst:e}),n;let u=r.value.get(o?.[t.discriminator]);return u?u._zod.run(n,a):t.unionFallback?i(n,a):(n.issues.push({code:"invalid_union",errors:[],note:"No matching discriminator",input:o,path:[t.discriminator],inst:e}),n)}}),tt=t.$constructor("$ZodIntersection",(e,t)=>{ep.init(e,t),e._zod.parse=(e,i)=>{let r=e.value,n=t.left._zod.run({value:r,issues:[]},i),a=t.right._zod.run({value:r,issues:[]},i);return n instanceof Promise||a instanceof Promise?Promise.all([n,a]).then(([t,i])=>ti(e,t,i)):ti(e,n,a)}});function ti(e,t,i){if(t.issues.length&&e.issues.push(...t.issues),i.issues.length&&e.issues.push(...i.issues),V.aborted(e))return e;let r=function e(t,i){if(t===i||t instanceof Date&&i instanceof Date&&+t==+i)return{valid:!0,data:t};if(V.isPlainObject(t)&&V.isPlainObject(i)){let r=Object.keys(i),n=Object.keys(t).filter(e=>-1!==r.indexOf(e)),a={...t,...i};for(let r of n){let n=e(t[r],i[r]);if(!n.valid)return{valid:!1,mergeErrorPath:[r,...n.mergeErrorPath]};a[r]=n.data}return{valid:!0,data:a}}if(Array.isArray(t)&&Array.isArray(i)){if(t.length!==i.length)return{valid:!1,mergeErrorPath:[]};let r=[];for(let n=0;n<t.length;n++){let a=e(t[n],i[n]);if(!a.valid)return{valid:!1,mergeErrorPath:[n,...a.mergeErrorPath]};r.push(a.data)}return{valid:!0,data:r}}return{valid:!1,mergeErrorPath:[]}}(t.value,i.value);if(!r.valid)throw Error(`Unmergable intersection. 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tN=e.i(922143),tD=e.i(682358);function tE(e,t,i,r){let n=Math.abs(e),a=n%10,o=n%100;return o>=11&&o<=19?r:1===a?t:a>=2&&a<=4?i:r}e.s([],543365),e.i(543365);var tT=e.i(40824);function tA(e,t,i,r){let n=Math.abs(e),a=n%10,o=n%100;return o>=11&&o<=19?r:1===a?t:a>=2&&a<=4?i:r}e.s(["ar",0,function(){let e,t;return{localeError:(e={string:{unit:"حرف",verb:"أن يحوي"},file:{unit:"بايت",verb:"أن يحوي"},array:{unit:"عنصر",verb:"أن يحوي"},set:{unit:"عنصر",verb:"أن يحوي"}},t={regex:"مدخل",email:"بريد إلكتروني",url:"رابط",emoji:"إيموجي",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"تاريخ ووقت بمعيار ISO",date:"تاريخ بمعيار ISO",time:"وقت بمعيار ISO",duration:"مدة بمعيار ISO",ipv4:"عنوان IPv4",ipv6:"عنوان IPv6",cidrv4:"مدى عناوين بصيغة IPv4",cidrv6:"مدى عناوين بصيغة IPv6",base64:"نَص بترميز base64-encoded",base64url:"نَص بترميز base64url-encoded",json_string:"نَص على هيئة JSON",e164:"رقم هاتف بمعيار 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e,t;return{localeError:(e={string:{unit:"simvol",verb:"olmalıdır"},file:{unit:"bayt",verb:"olmalıdır"},array:{unit:"element",verb:"olmalıdır"},set:{unit:"element",verb:"olmalıdır"}},t={regex:"input",email:"email address",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datetime",date:"ISO date",time:"ISO time",duration:"ISO duration",ipv4:"IPv4 address",ipv6:"IPv6 address",cidrv4:"IPv4 range",cidrv6:"IPv6 range",base64:"base64-encoded string",base64url:"base64url-encoded string",json_string:"JSON string",e164:"E.164 number",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Yanlış dəyər: g\xf6zlənilən ${i.expected}, daxil olan ${(e=>{let t=typeof e;switch(t){case"number":return 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чакалася, што ${i.origin} павінна быць ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Няправільны радок: павінен пачынацца з "${i.prefix}"`;if("ends_with"===i.format)return`Няправільны радок: павінен заканчвацца на "${i.suffix}"`;if("includes"===i.format)return`Няправільны радок: павінен змяшчаць "${i.includes}"`;if("regex"===i.format)return`Няправільны радок: павінен адпавядаць шаблону ${i.pattern}`;return`Няправільны ${t[i.format]??i.format}`;case"not_multiple_of":return`Няправільны лік: павінен быць кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспазнаны ${i.keys.length>1?"ключы":"ключ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Няправільны ключ у ${i.origin}`;case"invalid_union":default:return"Няправільны ўвод";case"invalid_element":return`Няправільнае значэнне ў ${i.origin}`}})}},"ca",0,function(){let e,t;return{localeError:(e={string:{unit:"caràcters",verb:"contenir"},file:{unit:"bytes",verb:"contenir"},array:{unit:"elements",verb:"contenir"},set:{unit:"elements",verb:"contenir"}},t={regex:"entrada",email:"adreça electrònica",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i hora ISO",date:"data ISO",time:"hora ISO",duration:"durada ISO",ipv4:"adreça IPv4",ipv6:"adreça IPv6",cidrv4:"rang IPv4",cidrv6:"rang IPv6",base64:"cadena codificada en base64",base64url:"cadena codificada en base64url",json_string:"cadena JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Tipus inv\xe0lid: s'esperava ${i.expected}, s'ha rebut ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Valor inv\xe0lid: s'esperava ${V.stringifyPrimitive(i.values[0])}`;return`Opci\xf3 inv\xe0lida: s'esperava una de ${V.joinValues(i.values," o ")}`;case"too_big":{let t=i.inclusive?"com a màxim":"menys de",r=e[i.origin]??null;if(r)return`Massa gran: s'esperava que ${i.origin??"el valor"} contingu\xe9s ${t} ${i.maximum.toString()} ${r.unit??"elements"}`;return`Massa gran: s'esperava que ${i.origin??"el valor"} fos ${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"com a mínim":"més de",r=e[i.origin]??null;if(r)return`Massa petit: s'esperava que ${i.origin} contingu\xe9s ${t} ${i.minimum.toString()} ${r.unit}`;return`Massa petit: s'esperava que ${i.origin} fos ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Format inv\xe0lid: ha de comen\xe7ar amb "${i.prefix}"`;if("ends_with"===i.format)return`Format inv\xe0lid: ha d'acabar amb "${i.suffix}"`;if("includes"===i.format)return`Format inv\xe0lid: ha d'incloure "${i.includes}"`;if("regex"===i.format)return`Format inv\xe0lid: ha de coincidir amb el patr\xf3 ${i.pattern}`;return`Format inv\xe0lid per a ${t[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe0lid: ha de ser m\xfaltiple de ${i.divisor}`;case"unrecognized_keys":return`Clau${i.keys.length>1?"s":""} no reconeguda${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Clau inv\xe0lida a ${i.origin}`;case"invalid_union":default:return"Entrada invàlida";case"invalid_element":return`Element inv\xe0lid a ${i.origin}`}})}},"cs",0,function(){let e,t;return{localeError:(e={string:{unit:"znaků",verb:"mít"},file:{unit:"bajtů",verb:"mít"},array:{unit:"prvků",verb:"mít"},set:{unit:"prvků",verb:"mít"}},t={regex:"regulární výraz",email:"e-mailová adresa",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"datum a čas ve formátu ISO",date:"datum ve formátu ISO",time:"čas ve formátu ISO",duration:"doba trvání ISO",ipv4:"IPv4 adresa",ipv6:"IPv6 adresa",cidrv4:"rozsah IPv4",cidrv6:"rozsah IPv6",base64:"řetězec zakódovaný ve formátu base64",base64url:"řetězec zakódovaný ve formátu base64url",json_string:"řetězec ve formátu JSON",e164:"číslo E.164",jwt:"JWT",template_literal:"vstup"},i=>{switch(i.code){case"invalid_type":return`Neplatn\xfd vstup: oček\xe1v\xe1no ${i.expected}, obdrženo ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"číslo";case"string":return"řetězec";case"boolean":return"boolean";case"bigint":return"bigint";case"function":return"funkce";case"symbol":return"symbol";case"undefined":return"undefined";case"object":if(Array.isArray(e))return"pole";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Neplatn\xfd vstup: oček\xe1v\xe1no ${V.stringifyPrimitive(i.values[0])}`;return`Neplatn\xe1 možnost: oček\xe1v\xe1na jedna z hodnot ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Hodnota je př\xedliš velk\xe1: ${i.origin??"hodnota"} mus\xed m\xedt ${t}${i.maximum.toString()} ${r.unit??"prvků"}`;return`Hodnota je př\xedliš velk\xe1: ${i.origin??"hodnota"} mus\xed b\xfdt ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Hodnota je př\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed m\xedt ${t}${i.minimum.toString()} ${r.unit??"prvků"}`;return`Hodnota je př\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed b\xfdt ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neplatn\xfd řetězec: mus\xed zač\xednat na "${i.prefix}"`;if("ends_with"===i.format)return`Neplatn\xfd řetězec: mus\xed končit na "${i.suffix}"`;if("includes"===i.format)return`Neplatn\xfd řetězec: mus\xed obsahovat "${i.includes}"`;if("regex"===i.format)return`Neplatn\xfd řetězec: mus\xed odpov\xeddat vzoru ${i.pattern}`;return`Neplatn\xfd form\xe1t ${t[i.format]??i.format}`;case"not_multiple_of":return`Neplatn\xe9 č\xedslo: mus\xed b\xfdt n\xe1sobkem ${i.divisor}`;case"unrecognized_keys":return`Nezn\xe1m\xe9 kl\xedče: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Neplatn\xfd kl\xedč v ${i.origin}`;case"invalid_union":default:return"Neplatný vstup";case"invalid_element":return`Neplatn\xe1 hodnota v ${i.origin}`}})}},"de",0,function(){let e,t;return{localeError:(e={string:{unit:"Zeichen",verb:"zu haben"},file:{unit:"Bytes",verb:"zu haben"},array:{unit:"Elemente",verb:"zu haben"},set:{unit:"Elemente",verb:"zu haben"}},t={regex:"Eingabe",email:"E-Mail-Adresse",url:"URL",emoji:"Emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-Datum und -Uhrzeit",date:"ISO-Datum",time:"ISO-Uhrzeit",duration:"ISO-Dauer",ipv4:"IPv4-Adresse",ipv6:"IPv6-Adresse",cidrv4:"IPv4-Bereich",cidrv6:"IPv6-Bereich",base64:"Base64-codierter String",base64url:"Base64-URL-codierter String",json_string:"JSON-String",e164:"E.164-Nummer",jwt:"JWT",template_literal:"Eingabe"},i=>{switch(i.code){case"invalid_type":return`Ung\xfcltige Eingabe: erwartet ${i.expected}, erhalten ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"Zahl";case"object":if(Array.isArray(e))return"Array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ung\xfcltige Eingabe: erwartet ${V.stringifyPrimitive(i.values[0])}`;return`Ung\xfcltige Option: erwartet eine von ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Zu gro\xdf: erwartet, dass ${i.origin??"Wert"} ${t}${i.maximum.toString()} ${r.unit??"Elemente"} hat`;return`Zu gro\xdf: erwartet, dass ${i.origin??"Wert"} ${t}${i.maximum.toString()} ist`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Zu klein: erwartet, dass ${i.origin} ${t}${i.minimum.toString()} ${r.unit} hat`;return`Zu klein: erwartet, dass ${i.origin} ${t}${i.minimum.toString()} ist`}case"invalid_format":if("starts_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.suffix}" enden`;if("includes"===i.format)return`Ung\xfcltiger String: muss "${i.includes}" enthalten`;if("regex"===i.format)return`Ung\xfcltiger String: muss dem Muster ${i.pattern} entsprechen`;return`Ung\xfcltig: ${t[i.format]??i.format}`;case"not_multiple_of":return`Ung\xfcltige Zahl: muss ein Vielfaches von ${i.divisor} sein`;case"unrecognized_keys":return`${i.keys.length>1?"Unbekannte Schlüssel":"Unbekannter Schlüssel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ung\xfcltiger Schl\xfcssel in ${i.origin}`;case"invalid_union":default:return"Ungültige Eingabe";case"invalid_element":return`Ung\xfcltiger Wert in ${i.origin}`}})}},"en",()=>tT.default,"eo",0,function(){let e,t;return{localeError:(e={string:{unit:"karaktrojn",verb:"havi"},file:{unit:"bajtojn",verb:"havi"},array:{unit:"elementojn",verb:"havi"},set:{unit:"elementojn",verb:"havi"}},t={regex:"enigo",email:"retadreso",url:"URL",emoji:"emoĝio",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datotempo",date:"ISO-dato",time:"ISO-tempo",duration:"ISO-daŭro",ipv4:"IPv4-adreso",ipv6:"IPv6-adreso",cidrv4:"IPv4-rango",cidrv6:"IPv6-rango",base64:"64-ume kodita karaktraro",base64url:"URL-64-ume kodita karaktraro",json_string:"JSON-karaktraro",e164:"E.164-nombro",jwt:"JWT",template_literal:"enigo"},i=>{switch(i.code){case"invalid_type":return`Nevalida enigo: atendiĝis ${i.expected}, riceviĝis ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombro";case"object":if(Array.isArray(e))return"tabelo";if(null===e)return"senvalora";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Nevalida enigo: atendiĝis ${V.stringifyPrimitive(i.values[0])}`;return`Nevalida opcio: atendiĝis unu el ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Tro granda: atendiĝis ke ${i.origin??"valoro"} havu ${t}${i.maximum.toString()} ${r.unit??"elementojn"}`;return`Tro granda: atendiĝis ke ${i.origin??"valoro"} havu ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Tro malgranda: atendiĝis ke ${i.origin} havu ${t}${i.minimum.toString()} ${r.unit}`;return`Tro malgranda: atendiĝis ke ${i.origin} estu ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nevalida karaktraro: devas komenciĝi per "${i.prefix}"`;if("ends_with"===i.format)return`Nevalida karaktraro: devas finiĝi per "${i.suffix}"`;if("includes"===i.format)return`Nevalida karaktraro: devas inkluzivi "${i.includes}"`;if("regex"===i.format)return`Nevalida karaktraro: devas kongrui kun la modelo ${i.pattern}`;return`Nevalida ${t[i.format]??i.format}`;case"not_multiple_of":return`Nevalida nombro: devas esti oblo de ${i.divisor}`;case"unrecognized_keys":return`Nekonata${i.keys.length>1?"j":""} ŝlosilo${i.keys.length>1?"j":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Nevalida ŝlosilo en ${i.origin}`;case"invalid_union":default:return"Nevalida enigo";case"invalid_element":return`Nevalida valoro en ${i.origin}`}})}},"es",0,function(){let e,t;return{localeError:(e={string:{unit:"caracteres",verb:"tener"},file:{unit:"bytes",verb:"tener"},array:{unit:"elementos",verb:"tener"},set:{unit:"elementos",verb:"tener"}},t={regex:"entrada",email:"dirección de correo electrónico",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"fecha y hora ISO",date:"fecha ISO",time:"hora ISO",duration:"duración ISO",ipv4:"dirección IPv4",ipv6:"dirección IPv6",cidrv4:"rango IPv4",cidrv6:"rango IPv6",base64:"cadena codificada en base64",base64url:"URL codificada en base64",json_string:"cadena JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Entrada inv\xe1lida: se esperaba ${i.expected}, recibido ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"número";case"object":if(Array.isArray(e))return"arreglo";if(null===e)return"nulo";if(Object.getPrototypeOf(e)!==Object.prototype)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: se esperaba ${V.stringifyPrimitive(i.values[0])}`;return`Opci\xf3n inv\xe1lida: se esperaba una de ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Demasiado grande: se esperaba que ${i.origin??"valor"} tuviera ${t}${i.maximum.toString()} ${r.unit??"elementos"}`;return`Demasiado grande: se esperaba que ${i.origin??"valor"} fuera ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Demasiado peque\xf1o: se esperaba que ${i.origin} tuviera ${t}${i.minimum.toString()} ${r.unit}`;return`Demasiado peque\xf1o: se esperaba que ${i.origin} fuera ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cadena inv\xe1lida: debe comenzar con "${i.prefix}"`;if("ends_with"===i.format)return`Cadena inv\xe1lida: debe terminar en "${i.suffix}"`;if("includes"===i.format)return`Cadena inv\xe1lida: debe incluir "${i.includes}"`;if("regex"===i.format)return`Cadena inv\xe1lida: debe coincidir con el patr\xf3n ${i.pattern}`;return`Inv\xe1lido ${t[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe1lido: debe ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Llave${i.keys.length>1?"s":""} desconocida${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Llave inv\xe1lida en ${i.origin}`;case"invalid_union":default:return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido en ${i.origin}`}})}},"fa",0,function(){let e,t;return{localeError:(e={string:{unit:"کاراکتر",verb:"داشته باشد"},file:{unit:"بایت",verb:"داشته باشد"},array:{unit:"آیتم",verb:"داشته باشد"},set:{unit:"آیتم",verb:"داشته باشد"}},t={regex:"ورودی",email:"آدرس ایمیل",url:"URL",emoji:"ایموجی",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"تاریخ و زمان ایزو",date:"تاریخ ایزو",time:"زمان ایزو",duration:"مدت زمان ایزو",ipv4:"IPv4 آدرس",ipv6:"IPv6 آدرس",cidrv4:"IPv4 دامنه",cidrv6:"IPv6 دامنه",base64:"base64-encoded رشته",base64url:"base64url-encoded رشته",json_string:"JSON رشته",e164:"E.164 عدد",jwt:"JWT",template_literal:"ورودی"},i=>{switch(i.code){case"invalid_type":return`ورودی نامعتبر: می‌بایست ${i.expected} می‌بود، ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"عدد";case"object":if(Array.isArray(e))return"آرایه";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} دریافت شد`;case"invalid_value":if(1===i.values.length)return`ورودی نامعتبر: می‌بایست ${V.stringifyPrimitive(i.values[0])} می‌بود`;return`گزینه نامعتبر: می‌بایست یکی از ${V.joinValues(i.values,"|")} می‌بود`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`خیلی بزرگ: ${i.origin??"مقدار"} باید ${t}${i.maximum.toString()} ${r.unit??"عنصر"} باشد`;return`خیلی بزرگ: ${i.origin??"مقدار"} باید ${t}${i.maximum.toString()} باشد`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`خیلی کوچک: ${i.origin} باید ${t}${i.minimum.toString()} ${r.unit} باشد`;return`خیلی کوچک: ${i.origin} باید ${t}${i.minimum.toString()} باشد`}case"invalid_format":if("starts_with"===i.format)return`رشته نامعتبر: باید با "${i.prefix}" شروع شود`;if("ends_with"===i.format)return`رشته نامعتبر: باید با "${i.suffix}" تمام شود`;if("includes"===i.format)return`رشته نامعتبر: باید شامل "${i.includes}" باشد`;if("regex"===i.format)return`رشته نامعتبر: باید با الگوی ${i.pattern} مطابقت داشته باشد`;return`${t[i.format]??i.format} نامعتبر`;case"not_multiple_of":return`عدد نامعتبر: باید مضرب ${i.divisor} باشد`;case"unrecognized_keys":return`کلید${i.keys.length>1?"های":""} ناشناس: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`کلید ناشناس در ${i.origin}`;case"invalid_union":default:return"ورودی نامعتبر";case"invalid_element":return`مقدار نامعتبر در ${i.origin}`}})}},"fi",0,function(){let e,t;return{localeError:(e={string:{unit:"merkkiä",subject:"merkkijonon"},file:{unit:"tavua",subject:"tiedoston"},array:{unit:"alkiota",subject:"listan"},set:{unit:"alkiota",subject:"joukon"},number:{unit:"",subject:"luvun"},bigint:{unit:"",subject:"suuren kokonaisluvun"},int:{unit:"",subject:"kokonaisluvun"},date:{unit:"",subject:"päivämäärän"}},t={regex:"säännöllinen lauseke",email:"sähköpostiosoite",url:"URL-osoite",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-aikaleima",date:"ISO-päivämäärä",time:"ISO-aika",duration:"ISO-kesto",ipv4:"IPv4-osoite",ipv6:"IPv6-osoite",cidrv4:"IPv4-alue",cidrv6:"IPv6-alue",base64:"base64-koodattu merkkijono",base64url:"base64url-koodattu merkkijono",json_string:"JSON-merkkijono",e164:"E.164-luku",jwt:"JWT",template_literal:"templaattimerkkijono"},i=>{switch(i.code){case"invalid_type":return`Virheellinen tyyppi: odotettiin ${i.expected}, oli ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Virheellinen sy\xf6te: t\xe4ytyy olla ${V.stringifyPrimitive(i.values[0])}`;return`Virheellinen valinta: t\xe4ytyy olla yksi seuraavista: ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Liian suuri: ${r.subject} t\xe4ytyy olla ${t}${i.maximum.toString()} ${r.unit}`.trim();return`Liian suuri: arvon t\xe4ytyy olla ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Liian pieni: ${r.subject} t\xe4ytyy olla ${t}${i.minimum.toString()} ${r.unit}`.trim();return`Liian pieni: arvon t\xe4ytyy olla ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy alkaa "${i.prefix}"`;if("ends_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy loppua "${i.suffix}"`;if("includes"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy sis\xe4lt\xe4\xe4 "${i.includes}"`;if("regex"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy vastata s\xe4\xe4nn\xf6llist\xe4 lauseketta ${i.pattern}`;return`Virheellinen ${t[i.format]??i.format}`;case"not_multiple_of":return`Virheellinen luku: t\xe4ytyy olla luvun ${i.divisor} monikerta`;case"unrecognized_keys":return`${i.keys.length>1?"Tuntemattomat avaimet":"Tuntematon avain"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return"Virheellinen avain tietueessa";case"invalid_union":return"Virheellinen unioni";case"invalid_element":return"Virheellinen arvo joukossa";default:return"Virheellinen syöte"}})}},"fr",0,function(){let e,t;return{localeError:(e={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},t={regex:"entrée",email:"adresse e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"date et heure ISO",date:"date ISO",time:"heure ISO",duration:"durée ISO",ipv4:"adresse IPv4",ipv6:"adresse IPv6",cidrv4:"plage IPv4",cidrv6:"plage IPv6",base64:"chaîne encodée en base64",base64url:"chaîne encodée en base64url",json_string:"chaîne JSON",e164:"numéro E.164",jwt:"JWT",template_literal:"entrée"},i=>{switch(i.code){case"invalid_type":return`Entr\xe9e invalide : ${i.expected} attendu, ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombre";case"object":if(Array.isArray(e))return"tableau";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} re\xe7u`;case"invalid_value":if(1===i.values.length)return`Entr\xe9e invalide : ${V.stringifyPrimitive(i.values[0])} attendu`;return`Option invalide : une valeur parmi ${V.joinValues(i.values,"|")} attendue`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Trop grand : ${i.origin??"valeur"} doit ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"élément(s)"}`;return`Trop grand : ${i.origin??"valeur"} doit \xeatre ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Trop petit : ${i.origin} doit ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Trop petit : ${i.origin} doit \xeatre ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au mod\xe8le ${i.pattern}`;return`${t[i.format]??i.format} invalide`;case"not_multiple_of":return`Nombre invalide : doit \xeatre un multiple de ${i.divisor}`;case"unrecognized_keys":return`Cl\xe9${i.keys.length>1?"s":""} non reconnue${i.keys.length>1?"s":""} : ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Cl\xe9 invalide dans ${i.origin}`;case"invalid_union":default:return"Entrée invalide";case"invalid_element":return`Valeur invalide dans ${i.origin}`}})}},"frCA",0,function(){let e,t;return{localeError:(e={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},t={regex:"entrée",email:"adresse courriel",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"date-heure ISO",date:"date ISO",time:"heure ISO",duration:"durée ISO",ipv4:"adresse IPv4",ipv6:"adresse IPv6",cidrv4:"plage IPv4",cidrv6:"plage IPv6",base64:"chaîne encodée en base64",base64url:"chaîne encodée en base64url",json_string:"chaîne JSON",e164:"numéro E.164",jwt:"JWT",template_literal:"entrée"},i=>{switch(i.code){case"invalid_type":return`Entr\xe9e invalide : attendu ${i.expected}, re\xe7u ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entr\xe9e invalide : attendu ${V.stringifyPrimitive(i.values[0])}`;return`Option invalide : attendu l'une des valeurs suivantes ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"≤":"<",r=e[i.origin]??null;if(r)return`Trop grand : attendu que ${i.origin??"la valeur"} ait ${t}${i.maximum.toString()} ${r.unit}`;return`Trop grand : attendu que ${i.origin??"la valeur"} soit ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"≥":">",r=e[i.origin]??null;if(r)return`Trop petit : attendu que ${i.origin} ait ${t}${i.minimum.toString()} ${r.unit}`;return`Trop petit : attendu que ${i.origin} soit ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au motif ${i.pattern}`;return`${t[i.format]??i.format} invalide`;case"not_multiple_of":return`Nombre invalide : doit \xeatre un multiple de ${i.divisor}`;case"unrecognized_keys":return`Cl\xe9${i.keys.length>1?"s":""} non reconnue${i.keys.length>1?"s":""} : ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Cl\xe9 invalide dans ${i.origin}`;case"invalid_union":default:return"Entrée invalide";case"invalid_element":return`Valeur invalide dans ${i.origin}`}})}},"he",0,function(){let e,t;return{localeError:(e={string:{unit:"אותיות",verb:"לכלול"},file:{unit:"בייטים",verb:"לכלול"},array:{unit:"פריטים",verb:"לכלול"},set:{unit:"פריטים",verb:"לכלול"}},t={regex:"קלט",email:"כתובת אימייל",url:"כתובת רשת",emoji:"אימוג'י",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"תאריך וזמן ISO",date:"תאריך ISO",time:"זמן ISO",duration:"משך זמן ISO",ipv4:"כתובת IPv4",ipv6:"כתובת IPv6",cidrv4:"טווח IPv4",cidrv6:"טווח IPv6",base64:"מחרוזת בבסיס 64",base64url:"מחרוזת בבסיס 64 לכתובות רשת",json_string:"מחרוזת JSON",e164:"מספר E.164",jwt:"JWT",template_literal:"קלט"},i=>{switch(i.code){case"invalid_type":return`קלט לא תקין: צריך ${i.expected}, התקבל ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`קלט לא תקין: צריך ${V.stringifyPrimitive(i.values[0])}`;return`קלט לא תקין: צריך אחת מהאפשרויות  ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`גדול מדי: ${i.origin??"value"} צריך להיות ${t}${i.maximum.toString()} ${r.unit??"elements"}`;return`גדול מדי: ${i.origin??"value"} צריך להיות ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`קטן מדי: ${i.origin} צריך להיות ${t}${i.minimum.toString()} ${r.unit}`;return`קטן מדי: ${i.origin} צריך להיות ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`מחרוזת לא תקינה: חייבת להתחיל ב"${i.prefix}"`;if("ends_with"===i.format)return`מחרוזת לא תקינה: חייבת להסתיים ב "${i.suffix}"`;if("includes"===i.format)return`מחרוזת לא תקינה: חייבת לכלול "${i.includes}"`;if("regex"===i.format)return`מחרוזת לא תקינה: חייבת להתאים לתבנית ${i.pattern}`;return`${t[i.format]??i.format} לא תקין`;case"not_multiple_of":return`מספר לא תקין: חייב להיות מכפלה של ${i.divisor}`;case"unrecognized_keys":return`מפתח${i.keys.length>1?"ות":""} לא מזוה${i.keys.length>1?"ים":"ה"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`מפתח לא תקין ב${i.origin}`;case"invalid_union":default:return"קלט לא תקין";case"invalid_element":return`ערך לא תקין ב${i.origin}`}})}},"hu",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"legyen"},file:{unit:"byte",verb:"legyen"},array:{unit:"elem",verb:"legyen"},set:{unit:"elem",verb:"legyen"}},t={regex:"bemenet",email:"email cím",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO időbélyeg",date:"ISO dátum",time:"ISO idő",duration:"ISO időintervallum",ipv4:"IPv4 cím",ipv6:"IPv6 cím",cidrv4:"IPv4 tartomány",cidrv6:"IPv6 tartomány",base64:"base64-kódolt string",base64url:"base64url-kódolt string",json_string:"JSON string",e164:"E.164 szám",jwt:"JWT",template_literal:"bemenet"},i=>{switch(i.code){case"invalid_type":return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${i.expected}, a kapott \xe9rt\xe9k ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"szám";case"object":if(Array.isArray(e))return"tömb";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${V.stringifyPrimitive(i.values[0])}`;return`\xc9rv\xe9nytelen opci\xf3: valamelyik \xe9rt\xe9k v\xe1rt ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`T\xfal nagy: ${i.origin??"érték"} m\xe9rete t\xfal nagy ${t}${i.maximum.toString()} ${r.unit??"elem"}`;return`T\xfal nagy: a bemeneti \xe9rt\xe9k ${i.origin??"érték"} t\xfal nagy: ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} m\xe9rete t\xfal kicsi ${t}${i.minimum.toString()} ${r.unit}`;return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} t\xfal kicsi ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.prefix}" \xe9rt\xe9kkel kell kezdődnie`;if("ends_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.suffix}" \xe9rt\xe9kkel kell v\xe9gződnie`;if("includes"===i.format)return`\xc9rv\xe9nytelen string: "${i.includes}" \xe9rt\xe9ket kell tartalmaznia`;if("regex"===i.format)return`\xc9rv\xe9nytelen string: ${i.pattern} mint\xe1nak kell megfelelnie`;return`\xc9rv\xe9nytelen ${t[i.format]??i.format}`;case"not_multiple_of":return`\xc9rv\xe9nytelen sz\xe1m: ${i.divisor} t\xf6bbsz\xf6r\xf6s\xe9nek kell lennie`;case"unrecognized_keys":return`Ismeretlen kulcs${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`\xc9rv\xe9nytelen kulcs ${i.origin}`;case"invalid_union":default:return"Érvénytelen bemenet";case"invalid_element":return`\xc9rv\xe9nytelen \xe9rt\xe9k: ${i.origin}`}})}},"id",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"memiliki"},file:{unit:"byte",verb:"memiliki"},array:{unit:"item",verb:"memiliki"},set:{unit:"item",verb:"memiliki"}},t={regex:"input",email:"alamat email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tanggal dan waktu format ISO",date:"tanggal format ISO",time:"jam format ISO",duration:"durasi format ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",cidrv4:"rentang alamat IPv4",cidrv6:"rentang alamat IPv6",base64:"string dengan enkode base64",base64url:"string dengan enkode base64url",json_string:"string JSON",e164:"angka E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input tidak valid: diharapkan ${i.expected}, diterima ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input tidak valid: diharapkan ${V.stringifyPrimitive(i.values[0])}`;return`Pilihan tidak valid: diharapkan salah satu dari ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Terlalu besar: diharapkan ${i.origin??"value"} memiliki ${t}${i.maximum.toString()} ${r.unit??"elemen"}`;return`Terlalu besar: diharapkan ${i.origin??"value"} menjadi ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Terlalu kecil: diharapkan ${i.origin} memiliki ${t}${i.minimum.toString()} ${r.unit}`;return`Terlalu kecil: diharapkan ${i.origin} menjadi ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak valid: harus dimulai dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak valid: harus berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak valid: harus menyertakan "${i.includes}"`;if("regex"===i.format)return`String tidak valid: harus sesuai pola ${i.pattern}`;return`${t[i.format]??i.format} tidak valid`;case"not_multiple_of":return`Angka tidak valid: harus kelipatan dari ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali ${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kunci tidak valid di ${i.origin}`;case"invalid_union":default:return"Input tidak valid";case"invalid_element":return`Nilai tidak valid di ${i.origin}`}})}},"it",0,function(){let e,t;return{localeError:(e={string:{unit:"caratteri",verb:"avere"},file:{unit:"byte",verb:"avere"},array:{unit:"elementi",verb:"avere"},set:{unit:"elementi",verb:"avere"}},t={regex:"input",email:"indirizzo email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e ora ISO",date:"data ISO",time:"ora ISO",duration:"durata ISO",ipv4:"indirizzo IPv4",ipv6:"indirizzo IPv6",cidrv4:"intervallo IPv4",cidrv6:"intervallo IPv6",base64:"stringa codificata in base64",base64url:"URL codificata in base64",json_string:"stringa JSON",e164:"numero E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input non valido: atteso ${i.expected}, ricevuto ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"numero";case"object":if(Array.isArray(e))return"vettore";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input non valido: atteso ${V.stringifyPrimitive(i.values[0])}`;return`Opzione non valida: atteso uno tra ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Troppo grande: ${i.origin??"valore"} deve avere ${t}${i.maximum.toString()} ${r.unit??"elementi"}`;return`Troppo grande: ${i.origin??"valore"} deve essere ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Troppo piccolo: ${i.origin} deve avere ${t}${i.minimum.toString()} ${r.unit}`;return`Troppo piccolo: ${i.origin} deve essere ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Stringa non valida: deve iniziare con "${i.prefix}"`;if("ends_with"===i.format)return`Stringa non valida: deve terminare con "${i.suffix}"`;if("includes"===i.format)return`Stringa non valida: deve includere "${i.includes}"`;if("regex"===i.format)return`Stringa non valida: deve corrispondere al pattern ${i.pattern}`;return`Invalid ${t[i.format]??i.format}`;case"not_multiple_of":return`Numero non valido: deve essere un multiplo di ${i.divisor}`;case"unrecognized_keys":return`Chiav${i.keys.length>1?"i":"e"} non riconosciut${i.keys.length>1?"e":"a"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Chiave non valida in ${i.origin}`;case"invalid_union":default:return"Input non valido";case"invalid_element":return`Valore non valido in ${i.origin}`}})}},"ja",0,function(){let e,t;return{localeError:(e={string:{unit:"文字",verb:"である"},file:{unit:"バイト",verb:"である"},array:{unit:"要素",verb:"である"},set:{unit:"要素",verb:"である"}},t={regex:"入力値",email:"メールアドレス",url:"URL",emoji:"絵文字",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO日時",date:"ISO日付",time:"ISO時刻",duration:"ISO期間",ipv4:"IPv4アドレス",ipv6:"IPv6アドレス",cidrv4:"IPv4範囲",cidrv6:"IPv6範囲",base64:"base64エンコード文字列",base64url:"base64urlエンコード文字列",json_string:"JSON文字列",e164:"E.164番号",jwt:"JWT",template_literal:"入力値"},i=>{switch(i.code){case"invalid_type":return`無効な入力: ${i.expected}が期待されましたが、${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"数値";case"object":if(Array.isArray(e))return"配列";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}が入力されました`;case"invalid_value":if(1===i.values.length)return`無効な入力: ${V.stringifyPrimitive(i.values[0])}が期待されました`;return`無効な選択: ${V.joinValues(i.values,"、")}のいずれかである必要があります`;case"too_big":{let t=i.inclusive?"以下である":"より小さい",r=e[i.origin]??null;if(r)return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${r.unit??"要素"}${t}必要があります`;return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${t}必要があります`}case"too_small":{let t=i.inclusive?"以上である":"より大きい",r=e[i.origin]??null;if(r)return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${r.unit}${t}必要があります`;return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${t}必要があります`}case"invalid_format":if("starts_with"===i.format)return`無効な文字列: "${i.prefix}"で始まる必要があります`;if("ends_with"===i.format)return`無効な文字列: "${i.suffix}"で終わる必要があります`;if("includes"===i.format)return`無効な文字列: "${i.includes}"を含む必要があります`;if("regex"===i.format)return`無効な文字列: パターン${i.pattern}に一致する必要があります`;return`無効な${t[i.format]??i.format}`;case"not_multiple_of":return`無効な数値: ${i.divisor}の倍数である必要があります`;case"unrecognized_keys":return`認識されていないキー${i.keys.length>1?"群":""}: ${V.joinValues(i.keys,"、")}`;case"invalid_key":return`${i.origin}内の無効なキー`;case"invalid_union":default:return"無効な入力";case"invalid_element":return`${i.origin}内の無効な値`}})}},"kh",0,function(){let e,t;return{localeError:(e={string:{unit:"តួអក្សរ",verb:"គួរមាន"},file:{unit:"បៃ",verb:"គួរមាន"},array:{unit:"ធាតុ",verb:"គួរមាន"},set:{unit:"ធាតុ",verb:"គួរមាន"}},t={regex:"ទិន្នន័យបញ្ចូល",email:"អាសយដ្ឋានអ៊ីមែល",url:"URL",emoji:"សញ្ញាអារម្មណ៍",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"កាលបរិច្ឆេទ និងម៉ោង ISO",date:"កាលបរិច្ឆេទ ISO",time:"ម៉ោង ISO",duration:"រយៈពេល ISO",ipv4:"អាសយដ្ឋាន IPv4",ipv6:"អាសយដ្ឋាន IPv6",cidrv4:"ដែនអាសយដ្ឋាន IPv4",cidrv6:"ដែនអាសយដ្ឋាន IPv6",base64:"ខ្សែអក្សរអ៊ិកូដ base64",base64url:"ខ្សែអក្សរអ៊ិកូដ base64url",json_string:"ខ្សែអក្សរ JSON",e164:"លេខ E.164",jwt:"JWT",template_literal:"ទិន្នន័យបញ្ចូល"},i=>{switch(i.code){case"invalid_type":return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${i.expected} ប៉ុន្តែទទួលបាន ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"មិនមែនជាលេខ (NaN)":"លេខ";case"object":if(Array.isArray(e))return"អារេ (Array)";if(null===e)return"គ្មានតម្លៃ (null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${V.stringifyPrimitive(i.values[0])}`;return`ជម្រើសមិនត្រឹមត្រូវ៖ ត្រូវជាមួយក្នុងចំណោម ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${t} ${i.maximum.toString()} ${r.unit??"ធាតុ"}`;return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`តូចពេក៖ ត្រូវការ ${i.origin} ${t} ${i.minimum.toString()} ${r.unit}`;return`តូចពេក៖ ត្រូវការ ${i.origin} ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវចាប់ផ្តើមដោយ "${i.prefix}"`;if("ends_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវបញ្ចប់ដោយ "${i.suffix}"`;if("includes"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវមាន "${i.includes}"`;if("regex"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវតែផ្គូផ្គងនឹងទម្រង់ដែលបានកំណត់ ${i.pattern}`;return`មិនត្រឹមត្រូវ៖ ${t[i.format]??i.format}`;case"not_multiple_of":return`លេខមិនត្រឹមត្រូវ៖ ត្រូវតែជាពហុគុណនៃ ${i.divisor}`;case"unrecognized_keys":return`រកឃើញសោមិនស្គាល់៖ ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`សោមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`;case"invalid_union":default:return"ទិន្នន័យមិនត្រឹមត្រូវ";case"invalid_element":return`ទិន្នន័យមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`}})}},"ko",0,function(){let e,t;return{localeError:(e={string:{unit:"문자",verb:"to have"},file:{unit:"바이트",verb:"to have"},array:{unit:"개",verb:"to have"},set:{unit:"개",verb:"to have"}},t={regex:"입력",email:"이메일 주소",url:"URL",emoji:"이모지",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO 날짜시간",date:"ISO 날짜",time:"ISO 시간",duration:"ISO 기간",ipv4:"IPv4 주소",ipv6:"IPv6 주소",cidrv4:"IPv4 범위",cidrv6:"IPv6 범위",base64:"base64 인코딩 문자열",base64url:"base64url 인코딩 문자열",json_string:"JSON 문자열",e164:"E.164 번호",jwt:"JWT",template_literal:"입력"},i=>{switch(i.code){case"invalid_type":return`잘못된 입력: 예상 타입은 ${i.expected}, 받은 타입은 ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}입니다`;case"invalid_value":if(1===i.values.length)return`잘못된 입력: 값은 ${V.stringifyPrimitive(i.values[0])} 이어야 합니다`;return`잘못된 옵션: ${V.joinValues(i.values,"또는 ")} 중 하나여야 합니다`;case"too_big":{let t=i.inclusive?"이하":"미만",r="미만"===t?"이어야 합니다":"여야 합니다",n=e[i.origin]??null,a=n?.unit??"요소";if(n)return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()}${a} ${t}${r}`;return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()} ${t}${r}`}case"too_small":{let t=i.inclusive?"이상":"초과",r="이상"===t?"이어야 합니다":"여야 합니다",n=e[i.origin]??null,a=n?.unit??"요소";if(n)return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()}${a} ${t}${r}`;return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()} ${t}${r}`}case"invalid_format":if("starts_with"===i.format)return`잘못된 문자열: "${i.prefix}"(으)로 시작해야 합니다`;if("ends_with"===i.format)return`잘못된 문자열: "${i.suffix}"(으)로 끝나야 합니다`;if("includes"===i.format)return`잘못된 문자열: "${i.includes}"을(를) 포함해야 합니다`;if("regex"===i.format)return`잘못된 문자열: 정규식 ${i.pattern} 패턴과 일치해야 합니다`;return`잘못된 ${t[i.format]??i.format}`;case"not_multiple_of":return`잘못된 숫자: ${i.divisor}의 배수여야 합니다`;case"unrecognized_keys":return`인식할 수 없는 키: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`잘못된 키: ${i.origin}`;case"invalid_union":default:return"잘못된 입력";case"invalid_element":return`잘못된 값: ${i.origin}`}})}},"mk",0,function(){let e,t;return{localeError:(e={string:{unit:"знаци",verb:"да имаат"},file:{unit:"бајти",verb:"да имаат"},array:{unit:"ставки",verb:"да имаат"},set:{unit:"ставки",verb:"да имаат"}},t={regex:"внес",email:"адреса на е-пошта",url:"URL",emoji:"емоџи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO датум и време",date:"ISO датум",time:"ISO време",duration:"ISO времетраење",ipv4:"IPv4 адреса",ipv6:"IPv6 адреса",cidrv4:"IPv4 опсег",cidrv6:"IPv6 опсег",base64:"base64-енкодирана низа",base64url:"base64url-енкодирана низа",json_string:"JSON низа",e164:"E.164 број",jwt:"JWT",template_literal:"внес"},i=>{switch(i.code){case"invalid_type":return`Грешен внес: се очекува ${i.expected}, примено ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"број";case"object":if(Array.isArray(e))return"низа";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Invalid input: expected ${V.stringifyPrimitive(i.values[0])}`;return`Грешана опција: се очекува една ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Премногу голем: се очекува ${i.origin??"вредноста"} да има ${t}${i.maximum.toString()} ${r.unit??"елементи"}`;return`Премногу голем: се очекува ${i.origin??"вредноста"} да биде ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Премногу мал: се очекува ${i.origin} да има ${t}${i.minimum.toString()} ${r.unit}`;return`Премногу мал: се очекува ${i.origin} да биде ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неважечка низа: мора да започнува со "${i.prefix}"`;if("ends_with"===i.format)return`Неважечка низа: мора да завршува со "${i.suffix}"`;if("includes"===i.format)return`Неважечка низа: мора да вклучува "${i.includes}"`;if("regex"===i.format)return`Неважечка низа: мора да одгоара на патернот ${i.pattern}`;return`Invalid ${t[i.format]??i.format}`;case"not_multiple_of":return`Грешен број: мора да биде делив со ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Непрепознаени клучеви":"Непрепознаен клуч"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Грешен клуч во ${i.origin}`;case"invalid_union":default:return"Грешен внес";case"invalid_element":return`Грешна вредност во ${i.origin}`}})}},"ms",0,function(){let e,t;return{localeError:(e={string:{unit:"aksara",verb:"mempunyai"},file:{unit:"bait",verb:"mempunyai"},array:{unit:"elemen",verb:"mempunyai"},set:{unit:"elemen",verb:"mempunyai"}},t={regex:"input",email:"alamat e-mel",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tarikh masa ISO",date:"tarikh ISO",time:"masa ISO",duration:"tempoh ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",cidrv4:"julat IPv4",cidrv6:"julat IPv6",base64:"string dikodkan base64",base64url:"string dikodkan base64url",json_string:"string JSON",e164:"nombor E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input tidak sah: dijangka ${i.expected}, diterima ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombor";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input tidak sah: dijangka ${V.stringifyPrimitive(i.values[0])}`;return`Pilihan tidak sah: dijangka salah satu daripada ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Terlalu besar: dijangka ${i.origin??"nilai"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"elemen"}`;return`Terlalu besar: dijangka ${i.origin??"nilai"} adalah ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Terlalu kecil: dijangka ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Terlalu kecil: dijangka ${i.origin} adalah ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak sah: mesti bermula dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak sah: mesti berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak sah: mesti mengandungi "${i.includes}"`;if("regex"===i.format)return`String tidak sah: mesti sepadan dengan corak ${i.pattern}`;return`${t[i.format]??i.format} tidak sah`;case"not_multiple_of":return`Nombor tidak sah: perlu gandaan ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kunci tidak sah dalam ${i.origin}`;case"invalid_union":default:return"Input tidak sah";case"invalid_element":return`Nilai tidak sah dalam ${i.origin}`}})}},"nl",0,function(){let e,t;return{localeError:(e={string:{unit:"tekens"},file:{unit:"bytes"},array:{unit:"elementen"},set:{unit:"elementen"}},t={regex:"invoer",email:"emailadres",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum en tijd",date:"ISO datum",time:"ISO tijd",duration:"ISO duur",ipv4:"IPv4-adres",ipv6:"IPv6-adres",cidrv4:"IPv4-bereik",cidrv6:"IPv6-bereik",base64:"base64-gecodeerde tekst",base64url:"base64 URL-gecodeerde tekst",json_string:"JSON string",e164:"E.164-nummer",jwt:"JWT",template_literal:"invoer"},i=>{switch(i.code){case"invalid_type":return`Ongeldige invoer: verwacht ${i.expected}, ontving ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"getal";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ongeldige invoer: verwacht ${V.stringifyPrimitive(i.values[0])}`;return`Ongeldige optie: verwacht \xe9\xe9n van ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Te lang: verwacht dat ${i.origin??"waarde"} ${t}${i.maximum.toString()} ${r.unit??"elementen"} bevat`;return`Te lang: verwacht dat ${i.origin??"waarde"} ${t}${i.maximum.toString()} is`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Te kort: verwacht dat ${i.origin} ${t}${i.minimum.toString()} ${r.unit} bevat`;return`Te kort: verwacht dat ${i.origin} ${t}${i.minimum.toString()} is`}case"invalid_format":if("starts_with"===i.format)return`Ongeldige tekst: moet met "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ongeldige tekst: moet op "${i.suffix}" eindigen`;if("includes"===i.format)return`Ongeldige tekst: moet "${i.includes}" bevatten`;if("regex"===i.format)return`Ongeldige tekst: moet overeenkomen met patroon ${i.pattern}`;return`Ongeldig: ${t[i.format]??i.format}`;case"not_multiple_of":return`Ongeldig getal: moet een veelvoud van ${i.divisor} zijn`;case"unrecognized_keys":return`Onbekende key${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ongeldige key in ${i.origin}`;case"invalid_union":default:return"Ongeldige invoer";case"invalid_element":return`Ongeldige waarde in ${i.origin}`}})}},"no",0,function(){let e,t;return{localeError:(e={string:{unit:"tegn",verb:"å ha"},file:{unit:"bytes",verb:"å ha"},array:{unit:"elementer",verb:"å inneholde"},set:{unit:"elementer",verb:"å inneholde"}},t={regex:"input",email:"e-postadresse",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO dato- og klokkeslett",date:"ISO-dato",time:"ISO-klokkeslett",duration:"ISO-varighet",ipv4:"IPv4-område",ipv6:"IPv6-område",cidrv4:"IPv4-spekter",cidrv6:"IPv6-spekter",base64:"base64-enkodet streng",base64url:"base64url-enkodet streng",json_string:"JSON-streng",e164:"E.164-nummer",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Ugyldig input: forventet ${i.expected}, fikk ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"tall";case"object":if(Array.isArray(e))return"liste";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ugyldig verdi: forventet ${V.stringifyPrimitive(i.values[0])}`;return`Ugyldig valg: forventet en av ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${t}${i.maximum.toString()} ${r.unit??"elementer"}`;return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`For lite(n): forventet ${i.origin} til \xe5 ha ${t}${i.minimum.toString()} ${r.unit}`;return`For lite(n): forventet ${i.origin} til \xe5 ha ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ugyldig streng: m\xe5 starte med "${i.prefix}"`;if("ends_with"===i.format)return`Ugyldig streng: m\xe5 ende med "${i.suffix}"`;if("includes"===i.format)return`Ugyldig streng: m\xe5 inneholde "${i.includes}"`;if("regex"===i.format)return`Ugyldig streng: m\xe5 matche m\xf8nsteret ${i.pattern}`;return`Ugyldig ${t[i.format]??i.format}`;case"not_multiple_of":return`Ugyldig tall: m\xe5 v\xe6re et multiplum av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Ukjente nøkler":"Ukjent nøkkel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ugyldig n\xf8kkel i ${i.origin}`;case"invalid_union":default:return"Ugyldig input";case"invalid_element":return`Ugyldig verdi i ${i.origin}`}})}},"ota",0,function(){let e,t;return{localeError:(e={string:{unit:"harf",verb:"olmalıdır"},file:{unit:"bayt",verb:"olmalıdır"},array:{unit:"unsur",verb:"olmalıdır"},set:{unit:"unsur",verb:"olmalıdır"}},t={regex:"giren",email:"epostagâh",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO hengâmı",date:"ISO tarihi",time:"ISO zamanı",duration:"ISO müddeti",ipv4:"IPv4 nişânı",ipv6:"IPv6 nişânı",cidrv4:"IPv4 menzili",cidrv6:"IPv6 menzili",base64:"base64-şifreli metin",base64url:"base64url-şifreli metin",json_string:"JSON metin",e164:"E.164 sayısı",jwt:"JWT",template_literal:"giren"},i=>{switch(i.code){case"invalid_type":return`F\xe2sit giren: umulan ${i.expected}, alınan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"numara";case"object":if(Array.isArray(e))return"saf";if(null===e)return"gayb";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`F\xe2sit giren: umulan ${V.stringifyPrimitive(i.values[0])}`;return`F\xe2sit tercih: m\xfbteberler ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${t}${i.maximum.toString()} ${r.unit??"elements"} sahip olmalıydı.`;return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${t}${i.maximum.toString()} olmalıydı.`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${t}${i.minimum.toString()} ${r.unit} sahip olmalıydı.`;return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${t}${i.minimum.toString()} olmalıydı.`}case"invalid_format":if("starts_with"===i.format)return`F\xe2sit metin: "${i.prefix}" ile başlamalı.`;if("ends_with"===i.format)return`F\xe2sit metin: "${i.suffix}" ile bitmeli.`;if("includes"===i.format)return`F\xe2sit metin: "${i.includes}" ihtiv\xe2 etmeli.`;if("regex"===i.format)return`F\xe2sit metin: ${i.pattern} nakşına uymalı.`;return`F\xe2sit ${t[i.format]??i.format}`;case"not_multiple_of":return`F\xe2sit sayı: ${i.divisor} katı olmalıydı.`;case"unrecognized_keys":return`Tanınmayan anahtar ${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7in tanınmayan anahtar var.`;case"invalid_union":return"Giren tanınamadı.";case"invalid_element":return`${i.origin} i\xe7in tanınmayan kıymet var.`;default:return"Kıymet tanınamadı."}})}},"pl",0,function(){let e,t;return{localeError:(e={string:{unit:"znaków",verb:"mieć"},file:{unit:"bajtów",verb:"mieć"},array:{unit:"elementów",verb:"mieć"},set:{unit:"elementów",verb:"mieć"}},t={regex:"wyrażenie",email:"adres email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i godzina w formacie ISO",date:"data w formacie ISO",time:"godzina w formacie ISO",duration:"czas trwania ISO",ipv4:"adres IPv4",ipv6:"adres IPv6",cidrv4:"zakres IPv4",cidrv6:"zakres IPv6",base64:"ciąg znaków zakodowany w formacie base64",base64url:"ciąg znaków zakodowany w formacie base64url",json_string:"ciąg znaków w formacie JSON",e164:"liczba E.164",jwt:"JWT",template_literal:"wejście"},i=>{switch(i.code){case"invalid_type":return`Nieprawidłowe dane wejściowe: oczekiwano ${i.expected}, otrzymano ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"liczba";case"object":if(Array.isArray(e))return"tablica";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Nieprawidłowe dane wejściowe: oczekiwano ${V.stringifyPrimitive(i.values[0])}`;return`Nieprawidłowa opcja: oczekiwano jednej z wartości ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Za duża wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${t}${i.maximum.toString()} ${r.unit??"elementów"}`;return`Zbyt duż(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Za mała wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${t}${i.minimum.toString()} ${r.unit??"elementów"}`;return`Zbyt mał(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zaczynać się od "${i.prefix}"`;if("ends_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi kończyć się na "${i.suffix}"`;if("includes"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zawierać "${i.includes}"`;if("regex"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi odpowiadać wzorcowi ${i.pattern}`;return`Nieprawidłow(y/a/e) ${t[i.format]??i.format}`;case"not_multiple_of":return`Nieprawidłowa liczba: musi być wielokrotnością ${i.divisor}`;case"unrecognized_keys":return`Nierozpoznane klucze${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Nieprawidłowy klucz w ${i.origin}`;case"invalid_union":default:return"Nieprawidłowe dane wejściowe";case"invalid_element":return`Nieprawidłowa wartość w ${i.origin}`}})}},"ps",0,function(){let e,t;return{localeError:(e={string:{unit:"توکي",verb:"ولري"},file:{unit:"بایټس",verb:"ولري"},array:{unit:"توکي",verb:"ولري"},set:{unit:"توکي",verb:"ولري"}},t={regex:"ورودي",email:"بریښنالیک",url:"یو آر ال",emoji:"ایموجي",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"نیټه او وخت",date:"نېټه",time:"وخت",duration:"موده",ipv4:"د IPv4 پته",ipv6:"د IPv6 پته",cidrv4:"د IPv4 ساحه",cidrv6:"د IPv6 ساحه",base64:"base64-encoded متن",base64url:"base64url-encoded متن",json_string:"JSON متن",e164:"د E.164 شمېره",jwt:"JWT",template_literal:"ورودي"},i=>{switch(i.code){case"invalid_type":return`ناسم ورودي: باید ${i.expected} وای, مګر ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"عدد";case"object":if(Array.isArray(e))return"ارې";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} ترلاسه شو`;case"invalid_value":if(1===i.values.length)return`ناسم ورودي: باید ${V.stringifyPrimitive(i.values[0])} وای`;return`ناسم انتخاب: باید یو له ${V.joinValues(i.values,"|")} څخه وای`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`ډیر لوی: ${i.origin??"ارزښت"} باید ${t}${i.maximum.toString()} ${r.unit??"عنصرونه"} ولري`;return`ډیر لوی: ${i.origin??"ارزښت"} باید ${t}${i.maximum.toString()} وي`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`ډیر کوچنی: ${i.origin} باید ${t}${i.minimum.toString()} ${r.unit} ولري`;return`ډیر کوچنی: ${i.origin} باید ${t}${i.minimum.toString()} وي`}case"invalid_format":if("starts_with"===i.format)return`ناسم متن: باید د "${i.prefix}" سره پیل شي`;if("ends_with"===i.format)return`ناسم متن: باید د "${i.suffix}" سره پای ته ورسيږي`;if("includes"===i.format)return`ناسم متن: باید "${i.includes}" ولري`;if("regex"===i.format)return`ناسم متن: باید د ${i.pattern} سره مطابقت ولري`;return`${t[i.format]??i.format} ناسم دی`;case"not_multiple_of":return`ناسم عدد: باید د ${i.divisor} مضرب وي`;case"unrecognized_keys":return`ناسم ${i.keys.length>1?"کلیډونه":"کلیډ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`ناسم کلیډ په ${i.origin} کې`;case"invalid_union":default:return"ناسمه ورودي";case"invalid_element":return`ناسم عنصر په ${i.origin} کې`}})}},"pt",0,function(){let e,t;return{localeError:(e={string:{unit:"caracteres",verb:"ter"},file:{unit:"bytes",verb:"ter"},array:{unit:"itens",verb:"ter"},set:{unit:"itens",verb:"ter"}},t={regex:"padrão",email:"endereço de e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e hora ISO",date:"data ISO",time:"hora ISO",duration:"duração ISO",ipv4:"endereço IPv4",ipv6:"endereço IPv6",cidrv4:"faixa de IPv4",cidrv6:"faixa de IPv6",base64:"texto codificado em base64",base64url:"URL codificada em base64",json_string:"texto JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Tipo inv\xe1lido: esperado ${i.expected}, recebido ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"número";case"object":if(Array.isArray(e))return"array";if(null===e)return"nulo";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: esperado ${V.stringifyPrimitive(i.values[0])}`;return`Op\xe7\xe3o inv\xe1lida: esperada uma das ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Muito grande: esperado que ${i.origin??"valor"} tivesse ${t}${i.maximum.toString()} ${r.unit??"elementos"}`;return`Muito grande: esperado que ${i.origin??"valor"} fosse ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Muito pequeno: esperado que ${i.origin} tivesse ${t}${i.minimum.toString()} ${r.unit}`;return`Muito pequeno: esperado que ${i.origin} fosse ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Texto inv\xe1lido: deve come\xe7ar com "${i.prefix}"`;if("ends_with"===i.format)return`Texto inv\xe1lido: deve terminar com "${i.suffix}"`;if("includes"===i.format)return`Texto inv\xe1lido: deve incluir "${i.includes}"`;if("regex"===i.format)return`Texto inv\xe1lido: deve corresponder ao padr\xe3o ${i.pattern}`;return`${t[i.format]??i.format} inv\xe1lido`;case"not_multiple_of":return`N\xfamero inv\xe1lido: deve ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Chave${i.keys.length>1?"s":""} desconhecida${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Chave inv\xe1lida em ${i.origin}`;case"invalid_union":return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido em ${i.origin}`;default:return"Campo inválido"}})}},"ru",0,function(){let e,t;return{localeError:(e={string:{unit:{one:"символ",few:"символа",many:"символов"},verb:"иметь"},file:{unit:{one:"байт",few:"байта",many:"байт"},verb:"иметь"},array:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"},set:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"}},t={regex:"ввод",email:"email адрес",url:"URL",emoji:"эмодзи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO дата и время",date:"ISO дата",time:"ISO время",duration:"ISO длительность",ipv4:"IPv4 адрес",ipv6:"IPv6 адрес",cidrv4:"IPv4 диапазон",cidrv6:"IPv6 диапазон",base64:"строка в формате base64",base64url:"строка в формате base64url",json_string:"JSON строка",e164:"номер E.164",jwt:"JWT",template_literal:"ввод"},i=>{switch(i.code){case"invalid_type":return`Неверный ввод: ожидалось ${i.expected}, получено ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"число";case"object":if(Array.isArray(e))return"массив";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Неверный ввод: ожидалось ${V.stringifyPrimitive(i.values[0])}`;return`Неверный вариант: ожидалось одно из ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r){let e=tA(Number(i.maximum),r.unit.one,r.unit.few,r.unit.many);return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет иметь ${t}${i.maximum.toString()} ${e}`}return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r){let e=tA(Number(i.minimum),r.unit.one,r.unit.few,r.unit.many);return`Слишком маленькое значение: ожидалось, что ${i.origin} будет иметь ${t}${i.minimum.toString()} ${e}`}return`Слишком маленькое значение: ожидалось, что ${i.origin} будет ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неверная строка: должна начинаться с "${i.prefix}"`;if("ends_with"===i.format)return`Неверная строка: должна заканчиваться на "${i.suffix}"`;if("includes"===i.format)return`Неверная строка: должна содержать "${i.includes}"`;if("regex"===i.format)return`Неверная строка: должна соответствовать шаблону ${i.pattern}`;return`Неверный ${t[i.format]??i.format}`;case"not_multiple_of":return`Неверное число: должно быть кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспознанн${i.keys.length>1?"ые":"ый"} ключ${i.keys.length>1?"и":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Неверный ключ в ${i.origin}`;case"invalid_union":default:return"Неверные входные данные";case"invalid_element":return`Неверное значение в ${i.origin}`}})}},"sl",0,function(){let e,t;return{localeError:(e={string:{unit:"znakov",verb:"imeti"},file:{unit:"bajtov",verb:"imeti"},array:{unit:"elementov",verb:"imeti"},set:{unit:"elementov",verb:"imeti"}},t={regex:"vnos",email:"e-poštni naslov",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum in čas",date:"ISO datum",time:"ISO čas",duration:"ISO trajanje",ipv4:"IPv4 naslov",ipv6:"IPv6 naslov",cidrv4:"obseg IPv4",cidrv6:"obseg IPv6",base64:"base64 kodiran niz",base64url:"base64url kodiran niz",json_string:"JSON niz",e164:"E.164 številka",jwt:"JWT",template_literal:"vnos"},i=>{switch(i.code){case"invalid_type":return`Neveljaven vnos: pričakovano ${i.expected}, prejeto ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"število";case"object":if(Array.isArray(e))return"tabela";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Neveljaven vnos: pričakovano ${V.stringifyPrimitive(i.values[0])}`;return`Neveljavna možnost: pričakovano eno izmed ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} imelo ${t}${i.maximum.toString()} ${r.unit??"elementov"}`;return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Premajhno: pričakovano, da bo ${i.origin} imelo ${t}${i.minimum.toString()} ${r.unit}`;return`Premajhno: pričakovano, da bo ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neveljaven niz: mora se začeti z "${i.prefix}"`;if("ends_with"===i.format)return`Neveljaven niz: mora se končati z "${i.suffix}"`;if("includes"===i.format)return`Neveljaven niz: mora vsebovati "${i.includes}"`;if("regex"===i.format)return`Neveljaven niz: mora ustrezati vzorcu ${i.pattern}`;return`Neveljaven ${t[i.format]??i.format}`;case"not_multiple_of":return`Neveljavno število: mora biti večkratnik ${i.divisor}`;case"unrecognized_keys":return`Neprepoznan${i.keys.length>1?"i ključi":" ključ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Neveljaven ključ v ${i.origin}`;case"invalid_union":default:return"Neveljaven vnos";case"invalid_element":return`Neveljavna vrednost v ${i.origin}`}})}},"sv",0,function(){let e,t;return{localeError:(e={string:{unit:"tecken",verb:"att ha"},file:{unit:"bytes",verb:"att ha"},array:{unit:"objekt",verb:"att innehålla"},set:{unit:"objekt",verb:"att innehålla"}},t={regex:"reguljärt uttryck",email:"e-postadress",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datum och tid",date:"ISO-datum",time:"ISO-tid",duration:"ISO-varaktighet",ipv4:"IPv4-intervall",ipv6:"IPv6-intervall",cidrv4:"IPv4-spektrum",cidrv6:"IPv6-spektrum",base64:"base64-kodad sträng",base64url:"base64url-kodad sträng",json_string:"JSON-sträng",e164:"E.164-nummer",jwt:"JWT",template_literal:"mall-literal"},i=>{switch(i.code){case"invalid_type":return`Ogiltig inmatning: f\xf6rv\xe4ntat ${i.expected}, fick ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"antal";case"object":if(Array.isArray(e))return"lista";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ogiltig inmatning: f\xf6rv\xe4ntat ${V.stringifyPrimitive(i.values[0])}`;return`Ogiltigt val: f\xf6rv\xe4ntade en av ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`F\xf6r stor(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.maximum.toString()} ${r.unit??"element"}`;return`F\xf6r stor(t): f\xf6rv\xe4ntat ${i.origin??"värdet"} att ha ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.minimum.toString()} ${r.unit}`;return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste b\xf6rja med "${i.prefix}"`;if("ends_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste sluta med "${i.suffix}"`;if("includes"===i.format)return`Ogiltig str\xe4ng: m\xe5ste inneh\xe5lla "${i.includes}"`;if("regex"===i.format)return`Ogiltig str\xe4ng: m\xe5ste matcha m\xf6nstret "${i.pattern}"`;return`Ogiltig(t) ${t[i.format]??i.format}`;case"not_multiple_of":return`Ogiltigt tal: m\xe5ste vara en multipel av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Okända nycklar":"Okänd nyckel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ogiltig nyckel i ${i.origin??"värdet"}`;case"invalid_union":default:return"Ogiltig input";case"invalid_element":return`Ogiltigt v\xe4rde i ${i.origin??"värdet"}`}})}},"ta",0,function(){let e,t;return{localeError:(e={string:{unit:"எழுத்துக்கள்",verb:"கொண்டிருக்க வேண்டும்"},file:{unit:"பைட்டுகள்",verb:"கொண்டிருக்க வேண்டும்"},array:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"},set:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"}},t={regex:"உள்ளீடு",email:"மின்னஞ்சல் முகவரி",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO தேதி நேரம்",date:"ISO தேதி",time:"ISO நேரம்",duration:"ISO கால அளவு",ipv4:"IPv4 முகவரி",ipv6:"IPv6 முகவரி",cidrv4:"IPv4 வரம்பு",cidrv6:"IPv6 வரம்பு",base64:"base64-encoded சரம்",base64url:"base64url-encoded சரம்",json_string:"JSON சரம்",e164:"E.164 எண்",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது ${i.expected}, பெறப்பட்டது ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"எண் அல்லாதது":"எண்";case"object":if(Array.isArray(e))return"அணி";if(null===e)return"வெறுமை";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது ${V.stringifyPrimitive(i.values[0])}`;return`தவறான விருப்பம்: எதிர்பார்க்கப்பட்டது ${V.joinValues(i.values,"|")} இல் ஒன்று`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`மிக பெரியது: எதிர்பார்க்கப்பட்டது ${i.origin??"மதிப்பு"} ${t}${i.maximum.toString()} ${r.unit??"உறுப்புகள்"} ஆக இருக்க வேண்டும்`;return`மிக பெரியது: எதிர்பார்க்கப்பட்டது ${i.origin??"மதிப்பு"} ${t}${i.maximum.toString()} ஆக இருக்க வேண்டும்`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${t}${i.minimum.toString()} ${r.unit} ஆக இருக்க வேண்டும்`;return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${t}${i.minimum.toString()} ஆக இருக்க வேண்டும்`}case"invalid_format":if("starts_with"===i.format)return`தவறான சரம்: "${i.prefix}" இல் தொடங்க வேண்டும்`;if("ends_with"===i.format)return`தவறான சரம்: "${i.suffix}" இல் முடிவடைய வேண்டும்`;if("includes"===i.format)return`தவறான சரம்: "${i.includes}" ஐ உள்ளடக்க வேண்டும்`;if("regex"===i.format)return`தவறான சரம்: ${i.pattern} முறைபாட்டுடன் பொருந்த வேண்டும்`;return`தவறான ${t[i.format]??i.format}`;case"not_multiple_of":return`தவறான எண்: ${i.divisor} இன் பலமாக இருக்க வேண்டும்`;case"unrecognized_keys":return`அடையாளம் தெரியாத விசை${i.keys.length>1?"கள்":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} இல் தவறான விசை`;case"invalid_union":default:return"தவறான உள்ளீடு";case"invalid_element":return`${i.origin} இல் தவறான மதிப்பு`}})}},"th",0,function(){let e,t;return{localeError:(e={string:{unit:"ตัวอักษร",verb:"ควรมี"},file:{unit:"ไบต์",verb:"ควรมี"},array:{unit:"รายการ",verb:"ควรมี"},set:{unit:"รายการ",verb:"ควรมี"}},t={regex:"ข้อมูลที่ป้อน",email:"ที่อยู่อีเมล",url:"URL",emoji:"อิโมจิ",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"วันที่เวลาแบบ ISO",date:"วันที่แบบ ISO",time:"เวลาแบบ ISO",duration:"ช่วงเวลาแบบ ISO",ipv4:"ที่อยู่ IPv4",ipv6:"ที่อยู่ IPv6",cidrv4:"ช่วง IP แบบ IPv4",cidrv6:"ช่วง IP แบบ IPv6",base64:"ข้อความแบบ Base64",base64url:"ข้อความแบบ Base64 สำหรับ URL",json_string:"ข้อความแบบ JSON",e164:"เบอร์โทรศัพท์ระหว่างประเทศ (E.164)",jwt:"โทเคน JWT",template_literal:"ข้อมูลที่ป้อน"},i=>{switch(i.code){case"invalid_type":return`ประเภทข้อมูลไม่ถูกต้อง: ควรเป็น ${i.expected} แต่ได้รับ ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"ไม่ใช่ตัวเลข (NaN)":"ตัวเลข";case"object":if(Array.isArray(e))return"อาร์เรย์ (Array)";if(null===e)return"ไม่มีค่า (null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`ค่าไม่ถูกต้อง: ควรเป็น ${V.stringifyPrimitive(i.values[0])}`;return`ตัวเลือกไม่ถูกต้อง: ควรเป็นหนึ่งใน ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"ไม่เกิน":"น้อยกว่า",r=e[i.origin]??null;if(r)return`เกินกำหนด: ${i.origin??"ค่า"} ควรมี${t} ${i.maximum.toString()} ${r.unit??"รายการ"}`;return`เกินกำหนด: ${i.origin??"ค่า"} ควรมี${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"อย่างน้อย":"มากกว่า",r=e[i.origin]??null;if(r)return`น้อยกว่ากำหนด: ${i.origin} ควรมี${t} ${i.minimum.toString()} ${r.unit}`;return`น้อยกว่ากำหนด: ${i.origin} ควรมี${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องขึ้นต้นด้วย "${i.prefix}"`;if("ends_with"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องลงท้ายด้วย "${i.suffix}"`;if("includes"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องมี "${i.includes}" อยู่ในข้อความ`;if("regex"===i.format)return`รูปแบบไม่ถูกต้อง: ต้องตรงกับรูปแบบที่กำหนด ${i.pattern}`;return`รูปแบบไม่ถูกต้อง: ${t[i.format]??i.format}`;case"not_multiple_of":return`ตัวเลขไม่ถูกต้อง: ต้องเป็นจำนวนที่หารด้วย ${i.divisor} ได้ลงตัว`;case"unrecognized_keys":return`พบคีย์ที่ไม่รู้จัก: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`คีย์ไม่ถูกต้องใน ${i.origin}`;case"invalid_union":return"ข้อมูลไม่ถูกต้อง: ไม่ตรงกับรูปแบบยูเนียนที่กำหนดไว้";case"invalid_element":return`ข้อมูลไม่ถูกต้องใน ${i.origin}`;default:return"ข้อมูลไม่ถูกต้อง"}})}},"tr",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"olmalı"},file:{unit:"bayt",verb:"olmalı"},array:{unit:"öğe",verb:"olmalı"},set:{unit:"öğe",verb:"olmalı"}},t={regex:"girdi",email:"e-posta adresi",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO tarih ve saat",date:"ISO tarih",time:"ISO saat",duration:"ISO süre",ipv4:"IPv4 adresi",ipv6:"IPv6 adresi",cidrv4:"IPv4 aralığı",cidrv6:"IPv6 aralığı",base64:"base64 ile şifrelenmiş metin",base64url:"base64url ile şifrelenmiş metin",json_string:"JSON dizesi",e164:"E.164 sayısı",jwt:"JWT",template_literal:"Şablon dizesi"},i=>{switch(i.code){case"invalid_type":return`Ge\xe7ersiz değer: beklenen ${i.expected}, alınan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ge\xe7ersiz değer: beklenen ${V.stringifyPrimitive(i.values[0])}`;return`Ge\xe7ersiz se\xe7enek: aşağıdakilerden biri olmalı: ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${t}${i.maximum.toString()} ${r.unit??"öğe"}`;return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${t}${i.minimum.toString()} ${r.unit}`;return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ge\xe7ersiz metin: "${i.prefix}" ile başlamalı`;if("ends_with"===i.format)return`Ge\xe7ersiz metin: "${i.suffix}" ile bitmeli`;if("includes"===i.format)return`Ge\xe7ersiz metin: "${i.includes}" i\xe7ermeli`;if("regex"===i.format)return`Ge\xe7ersiz metin: ${i.pattern} desenine uymalı`;return`Ge\xe7ersiz ${t[i.format]??i.format}`;case"not_multiple_of":return`Ge\xe7ersiz sayı: ${i.divisor} ile tam b\xf6l\xfcnebilmeli`;case"unrecognized_keys":return`Tanınmayan anahtar${i.keys.length>1?"lar":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7inde ge\xe7ersiz anahtar`;case"invalid_union":default:return"Geçersiz değer";case"invalid_element":return`${i.origin} i\xe7inde ge\xe7ersiz değer`}})}},"ua",0,function(){let e,t;return{localeError:(e={string:{unit:"символів",verb:"матиме"},file:{unit:"байтів",verb:"матиме"},array:{unit:"елементів",verb:"матиме"},set:{unit:"елементів",verb:"матиме"}},t={regex:"вхідні дані",email:"адреса електронної пошти",url:"URL",emoji:"емодзі",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"дата та час ISO",date:"дата ISO",time:"час ISO",duration:"тривалість ISO",ipv4:"адреса IPv4",ipv6:"адреса IPv6",cidrv4:"діапазон IPv4",cidrv6:"діапазон IPv6",base64:"рядок у кодуванні base64",base64url:"рядок у кодуванні base64url",json_string:"рядок JSON",e164:"номер E.164",jwt:"JWT",template_literal:"вхідні дані"},i=>{switch(i.code){case"invalid_type":return`Неправильні вхідні дані: очікується ${i.expected}, отримано ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"число";case"object":if(Array.isArray(e))return"масив";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Неправильні вхідні дані: очікується ${V.stringifyPrimitive(i.values[0])}`;return`Неправильна опція: очікується одне з ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Занадто велике: очікується, що ${i.origin??"значення"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"елементів"}`;return`Занадто велике: очікується, що ${i.origin??"значення"} буде ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Занадто мале: очікується, що ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Занадто мале: очікується, що ${i.origin} буде ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неправильний рядок: повинен починатися з "${i.prefix}"`;if("ends_with"===i.format)return`Неправильний рядок: повинен закінчуватися на "${i.suffix}"`;if("includes"===i.format)return`Неправильний рядок: повинен містити "${i.includes}"`;if("regex"===i.format)return`Неправильний рядок: повинен відповідати шаблону ${i.pattern}`;return`Неправильний ${t[i.format]??i.format}`;case"not_multiple_of":return`Неправильне число: повинно бути кратним ${i.divisor}`;case"unrecognized_keys":return`Нерозпізнаний ключ${i.keys.length>1?"і":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Неправильний ключ у ${i.origin}`;case"invalid_union":default:return"Неправильні вхідні дані";case"invalid_element":return`Неправильне значення у ${i.origin}`}})}},"ur",0,function(){let e,t;return{localeError:(e={string:{unit:"حروف",verb:"ہونا"},file:{unit:"بائٹس",verb:"ہونا"},array:{unit:"آئٹمز",verb:"ہونا"},set:{unit:"آئٹمز",verb:"ہونا"}},t={regex:"ان پٹ",email:"ای میل ایڈریس",url:"یو آر ایل",emoji:"ایموجی",uuid:"یو یو آئی ڈی",uuidv4:"یو یو آئی ڈی وی 4",uuidv6:"یو یو آئی ڈی وی 6",nanoid:"نینو آئی ڈی",guid:"جی یو آئی ڈی",cuid:"سی یو آئی ڈی",cuid2:"سی یو آئی ڈی 2",ulid:"یو ایل آئی ڈی",xid:"ایکس آئی ڈی",ksuid:"کے ایس یو آئی ڈی",datetime:"آئی ایس او ڈیٹ ٹائم",date:"آئی ایس او تاریخ",time:"آئی ایس او وقت",duration:"آئی ایس او مدت",ipv4:"آئی پی وی 4 ایڈریس",ipv6:"آئی پی وی 6 ایڈریس",cidrv4:"آئی پی وی 4 رینج",cidrv6:"آئی پی وی 6 رینج",base64:"بیس 64 ان کوڈڈ سٹرنگ",base64url:"بیس 64 یو آر ایل ان کوڈڈ سٹرنگ",json_string:"جے ایس او این سٹرنگ",e164:"ای 164 نمبر",jwt:"جے ڈبلیو ٹی",template_literal:"ان پٹ"},i=>{switch(i.code){case"invalid_type":return`غلط ان پٹ: ${i.expected} متوقع تھا، ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"نمبر";case"object":if(Array.isArray(e))return"آرے";if(null===e)return"نل";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} موصول ہوا`;case"invalid_value":if(1===i.values.length)return`غلط ان پٹ: ${V.stringifyPrimitive(i.values[0])} متوقع تھا`;return`غلط آپشن: ${V.joinValues(i.values,"|")} میں سے ایک متوقع تھا`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`بہت بڑا: ${i.origin??"ویلیو"} کے ${t}${i.maximum.toString()} ${r.unit??"عناصر"} ہونے متوقع تھے`;return`بہت بڑا: ${i.origin??"ویلیو"} کا ${t}${i.maximum.toString()} ہونا متوقع تھا`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`بہت چھوٹا: ${i.origin} کے ${t}${i.minimum.toString()} ${r.unit} ہونے متوقع تھے`;return`بہت چھوٹا: ${i.origin} کا ${t}${i.minimum.toString()} ہونا متوقع تھا`}case"invalid_format":if("starts_with"===i.format)return`غلط سٹرنگ: "${i.prefix}" سے شروع ہونا چاہیے`;if("ends_with"===i.format)return`غلط سٹرنگ: "${i.suffix}" پر ختم ہونا چاہیے`;if("includes"===i.format)return`غلط سٹرنگ: "${i.includes}" شامل ہونا چاہیے`;if("regex"===i.format)return`غلط سٹرنگ: پیٹرن ${i.pattern} سے میچ ہونا چاہیے`;return`غلط ${t[i.format]??i.format}`;case"not_multiple_of":return`غلط نمبر: ${i.divisor} کا مضاعف ہونا چاہیے`;case"unrecognized_keys":return`غیر تسلیم شدہ کی${i.keys.length>1?"ز":""}: ${V.joinValues(i.keys,"، ")}`;case"invalid_key":return`${i.origin} میں غلط کی`;case"invalid_union":default:return"غلط ان پٹ";case"invalid_element":return`${i.origin} میں غلط ویلیو`}})}},"vi",0,function(){let e,t;return{localeError:(e={string:{unit:"ký tự",verb:"có"},file:{unit:"byte",verb:"có"},array:{unit:"phần tử",verb:"có"},set:{unit:"phần tử",verb:"có"}},t={regex:"đầu vào",email:"địa chỉ email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ngày giờ ISO",date:"ngày ISO",time:"giờ ISO",duration:"khoảng thời gian ISO",ipv4:"địa chỉ IPv4",ipv6:"địa chỉ IPv6",cidrv4:"dải IPv4",cidrv6:"dải IPv6",base64:"chuỗi mã hóa base64",base64url:"chuỗi mã hóa base64url",json_string:"chuỗi JSON",e164:"số E.164",jwt:"JWT",template_literal:"đầu vào"},i=>{switch(i.code){case"invalid_type":return`Đầu v\xe0o kh\xf4ng hợp lệ: mong đợi ${i.expected}, nhận được ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"số";case"object":if(Array.isArray(e))return"mảng";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Đầu v\xe0o kh\xf4ng hợp lệ: mong đợi ${V.stringifyPrimitive(i.values[0])}`;return`T\xf9y chọn kh\xf4ng hợp lệ: mong đợi một trong c\xe1c gi\xe1 trị ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Qu\xe1 lớn: mong đợi ${i.origin??"giá trị"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"phần tử"}`;return`Qu\xe1 lớn: mong đợi ${i.origin??"giá trị"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Qu\xe1 nhỏ: mong đợi ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Qu\xe1 nhỏ: mong đợi ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải bắt đầu bằng "${i.prefix}"`;if("ends_with"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải kết th\xfac bằng "${i.suffix}"`;if("includes"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải bao gồm "${i.includes}"`;if("regex"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải khớp với mẫu ${i.pattern}`;return`${t[i.format]??i.format} kh\xf4ng hợp lệ`;case"not_multiple_of":return`Số kh\xf4ng hợp lệ: phải l\xe0 bội số của ${i.divisor}`;case"unrecognized_keys":return`Kh\xf3a kh\xf4ng được nhận dạng: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kh\xf3a kh\xf4ng hợp lệ trong ${i.origin}`;case"invalid_union":default:return"Đầu vào không hợp lệ";case"invalid_element":return`Gi\xe1 trị kh\xf4ng hợp lệ trong ${i.origin}`}})}},"zhCN",0,function(){let e,t;return{localeError:(e={string:{unit:"字符",verb:"包含"},file:{unit:"字节",verb:"包含"},array:{unit:"项",verb:"包含"},set:{unit:"项",verb:"包含"}},t={regex:"输入",email:"电子邮件",url:"URL",emoji:"表情符号",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO日期时间",date:"ISO日期",time:"ISO时间",duration:"ISO时长",ipv4:"IPv4地址",ipv6:"IPv6地址",cidrv4:"IPv4网段",cidrv6:"IPv6网段",base64:"base64编码字符串",base64url:"base64url编码字符串",json_string:"JSON字符串",e164:"E.164号码",jwt:"JWT",template_literal:"输入"},i=>{switch(i.code){case"invalid_type":return`无效输入：期望 ${i.expected}，实际接收 ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"非数字(NaN)":"数字";case"object":if(Array.isArray(e))return"数组";if(null===e)return"空值(null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`无效输入：期望 ${V.stringifyPrimitive(i.values[0])}`;return`无效选项：期望以下之一 ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`数值过大：期望 ${i.origin??"值"} ${t}${i.maximum.toString()} ${r.unit??"个元素"}`;return`数值过大：期望 ${i.origin??"值"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`数值过小：期望 ${i.origin} ${t}${i.minimum.toString()} ${r.unit}`;return`数值过小：期望 ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`无效字符串：必须以 "${i.prefix}" 开头`;if("ends_with"===i.format)return`无效字符串：必须以 "${i.suffix}" 结尾`;if("includes"===i.format)return`无效字符串：必须包含 "${i.includes}"`;if("regex"===i.format)return`无效字符串：必须满足正则表达式 ${i.pattern}`;return`无效${t[i.format]??i.format}`;case"not_multiple_of":return`无效数字：必须是 ${i.divisor} 的倍数`;case"unrecognized_keys":return`出现未知的键(key): ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} 中的键(key)无效`;case"invalid_union":default:return"无效输入";case"invalid_element":return`${i.origin} 中包含无效值(value)`}})}},"zhTW",0,function(){let e,t;return{localeError:(e={string:{unit:"字元",verb:"擁有"},file:{unit:"位元組",verb:"擁有"},array:{unit:"項目",verb:"擁有"},set:{unit:"項目",verb:"擁有"}},t={regex:"輸入",email:"郵件地址",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO 日期時間",date:"ISO 日期",time:"ISO 時間",duration:"ISO 期間",ipv4:"IPv4 位址",ipv6:"IPv6 位址",cidrv4:"IPv4 範圍",cidrv6:"IPv6 範圍",base64:"base64 編碼字串",base64url:"base64url 編碼字串",json_string:"JSON 字串",e164:"E.164 數值",jwt:"JWT",template_literal:"輸入"},i=>{switch(i.code){case"invalid_type":return`無效的輸入值：預期為 ${i.expected}，但收到 ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`無效的輸入值：預期為 ${V.stringifyPrimitive(i.values[0])}`;return`無效的選項：預期為以下其中之一 ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`數值過大：預期 ${i.origin??"值"} 應為 ${t}${i.maximum.toString()} ${r.unit??"個元素"}`;return`數值過大：預期 ${i.origin??"值"} 應為 ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`數值過小：預期 ${i.origin} 應為 ${t}${i.minimum.toString()} ${r.unit}`;return`數值過小：預期 ${i.origin} 應為 ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`無效的字串：必須以 "${i.prefix}" 開頭`;if("ends_with"===i.format)return`無效的字串：必須以 "${i.suffix}" 結尾`;if("includes"===i.format)return`無效的字串：必須包含 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new file mode 100644
index 00000000000..33bed7407d6
--- /dev/null
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/182rht5ez34ne.js b/litellm/proxy/_experimental/out/_next/static/chunks/182rht5ez34ne.js
deleted file mode 100644
index 99c123b11fa..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/182rht5ez34ne.js
+++ /dev/null
@@ -1,158 +0,0 @@
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deleted file mode 100644
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/19w_l5kkw_57u.js b/litellm/proxy/_experimental/out/_next/static/chunks/19w_l5kkw_57u.js
deleted file mode 100644
index 1855114c379..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/19w_l5kkw_57u.js
+++ /dev/null
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mb-4",children:(0,s.jsxs)("div",{className:"flex items-start space-x-2",children:[(0,s.jsx)(n.Info,{className:"w-4 h-4 text-info mt-0.5 shrink-0"}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium text-info mb-2",children:"Wildcard Routing"}),(0,s.jsxs)("p",{className:"text-sm text-info mb-2",children:["This model uses wildcard routing. You can pass any value where you see the"," ",(0,s.jsx)("code",{className:"bg-info/15 px-1 py-0.5 rounded-sm text-xs",children:"*"})," symbol."]}),(0,s.jsxs)("p",{className:"text-sm text-info",children:["For example, with"," ",(0,s.jsx)("code",{className:"bg-info/15 px-1 py-0.5 rounded-sm text-xs",children:ew.model_group}),", you can use any string (",(0,s.jsx)("code",{className:"bg-info/15 px-1 py-0.5 rounded-sm text-xs",children:ew.model_group.replaceAll("*","my-custom-value")}),") that matches this pattern."]})]})]})})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Token & Cost Information"}),(0,s.jsxs)("div",{className:"grid grid-cols-2 gap-4",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Max Input Tokens:"}),(0,s.jsx)("p",{children:ew.max_input_tokens?.toLocaleString()||"Not specified"})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Max Output 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listed"}):I.map(e=>(0,s.jsx)(d.Badge,{variant:"secondary",children:e.replace(/^supports_/,"").split("_").map(e=>e.charAt(0).toUpperCase()+e.slice(1)).join(" ")},e))})]}),(ew.tpm||ew.rpm)&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Rate Limits"}),(0,s.jsxs)("div",{className:"grid grid-cols-2 gap-4",children:[ew.tpm&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Tokens per Minute:"}),(0,s.jsx)("p",{children:ew.tpm.toLocaleString()})]}),ew.rpm&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Requests per Minute:"}),(0,s.jsx)("p",{children:ew.rpm.toLocaleString()})]})]})]}),ew.supported_openai_params&&ew.supported_openai_params.length>0&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Supported OpenAI Parameters"}),(0,s.jsx)("div",{className:"flex flex-wrap gap-2",children:ew.supported_openai_params.map(e=>(0,s.jsx)(d.Badge,{variant:"secondary",children:e},e))})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Usage Example"}),(0,s.jsx)("div",{className:"bg-gray-900 text-gray-100 p-4 rounded-lg overflow-x-auto",children:(0,s.jsx)("pre",{className:"text-sm",children:(0,D.generateCodeSnippet)({apiKeySource:"custom",accessToken:null,apiKey:"your_api_key",inputMessage:"Hello, how are you?",chatHistory:[{role:"user",content:"Hello, how are you?",isImage:!1}],selectedTags:[],selectedVectorStores:[],selectedGuardrails:[],selectedPolicies:[],selectedMCPServers:[],endpointType:(0,P.getEndpointType)(ew.mode||"chat"),selectedModel:ew.model_group,selectedSdk:"openai"})})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU((0,D.generateCodeSnippet)({apiKeySource:"custom",accessToken:null,apiKey:"your_api_key",inputMessage:"Hello, how are 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break-all",children:eT.url})]})]})]}),eT.capabilities&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Capabilities"}),(0,s.jsx)("div",{className:"flex flex-wrap gap-2",children:Object.entries(eT.capabilities).filter(([e,s])=>!0===s).map(([e])=>(0,s.jsx)(d.Badge,{variant:"secondary",className:"capitalize",children:e},e))})]}),eT.skills&&eT.skills.length>0&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Skills"}),(0,s.jsx)("div",{className:"space-y-4",children:eT.skills.map((e,t)=>(0,s.jsxs)("div",{className:"border border-border rounded-lg p-4",children:[(0,s.jsx)("div",{className:"flex items-start justify-between mb-2",children:(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium text-base",children:e.name}),(0,s.jsx)("p",{className:"text-sm text-muted-foreground",children:e.description})]})}),e.tags&&e.tags.length>0&&(0,s.jsx)("div",{className:"flex flex-wrap gap-1 mt-2",children:e.tags.map(e=>(0,s.jsx)(d.Badge,{variant:"secondary",className:"text-xs",children:e},e))})]},t))})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Input/Output Modes"}),(0,s.jsxs)("div",{className:"grid grid-cols-2 gap-4",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Input Modes:"}),(0,s.jsx)("div",{className:"flex flex-wrap gap-1 mt-1",children:(eT.defaultInputModes??[]).map(e=>(0,s.jsx)(d.Badge,{variant:"secondary",children:e},e))})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Output Modes:"}),(0,s.jsx)("div",{className:"flex flex-wrap gap-1 mt-1",children:(eT.defaultOutputModes??[]).map(e=>(0,s.jsx)(d.Badge,{variant:"secondary",children:e},e))})]})]})]}),eT.documentationUrl&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Documentation"}),(0,s.jsxs)("a",{href:eT.documentationUrl,target:"_blank",rel:"noopener noreferrer",className:"text-info hover:text-info/80 flex items-center space-x-2",children:[(0,s.jsx)(a.ExternalLinkIcon,{className:"w-4 h-4"}),(0,s.jsx)("span",{children:"View Documentation"})]})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Usage Example (A2A Protocol)"}),(0,s.jsxs)("div",{className:"mb-4",children:[(0,s.jsx)("p",{className:"text-sm font-medium mb-2 text-foreground",children:"Step 1: Retrieve Agent Card"}),(0,s.jsx)("div",{className:"bg-gray-900 text-gray-100 p-4 rounded-lg overflow-x-auto",children:(0,s.jsx)("pre",{className:"text-xs",children:`base_url = '${eT.url}'
+
+resolver = A2ACardResolver(
+    httpx_client=httpx_client,
+    base_url=base_url,
+    # agent_card_path uses default, extended_agent_card_path also uses default
+)
+
+# Fetch Public Agent Card and Initialize Client
+final_agent_card_to_use: AgentCard | None = None
+_public_card = (
+    await resolver.get_agent_card()
+)  # Fetches from default public path - \`/agents/{agent_id}/\`
+final_agent_card_to_use = _public_card
+
+if _public_card.supports_authenticated_extended_card:
+    try:
+        auth_headers_dict = {
+            'Authorization': 'Bearer dummy-token-for-extended-card'
+        }
+        _extended_card = await resolver.get_agent_card(
+            relative_card_path=EXTENDED_AGENT_CARD_PATH,
+            http_kwargs={'headers': auth_headers_dict},
+        )
+        final_agent_card_to_use = (
+            _extended_card  # Update to use the extended card
+        )
+    except Exception as e_extended:
+        logger.warning(
+            f'Failed to fetch extended agent card: {e_extended}. Will proceed with public card.',
+            exc_info=True,
+        )`})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU(`from a2a.client import A2ACardResolver, A2AClient
+from a2a.types import (
+    AgentCard,
+    MessageSendParams,
+    SendMessageRequest,
+    SendStreamingMessageRequest,
+)
+from a2a.utils.constants import (
+    AGENT_CARD_WELL_KNOWN_PATH,
+    EXTENDED_AGENT_CARD_PATH,
+)
+
+base_url = '${eT.url}'
+
+resolver = A2ACardResolver(
+    httpx_client=httpx_client,
+    base_url=base_url,
+    # agent_card_path uses default, extended_agent_card_path also uses default
+)
+
+# Fetch Public Agent Card and Initialize Client
+final_agent_card_to_use: AgentCard | None = None
+_public_card = (
+    await resolver.get_agent_card()
+)  # Fetches from default public path - \`/agents/{agent_id}/\`
+final_agent_card_to_use = _public_card
+
+if _public_card.supports_authenticated_extended_card:
+    try:
+        auth_headers_dict = {
+            'Authorization': 'Bearer dummy-token-for-extended-card'
+        }
+        _extended_card = await resolver.get_agent_card(
+            relative_card_path=EXTENDED_AGENT_CARD_PATH,
+            http_kwargs={'headers': auth_headers_dict},
+        )
+        final_agent_card_to_use = (
+            _extended_card  # Update to use the extended card
+        )
+    except Exception as e_extended:
+        logger.warning(
+            f'Failed to fetch extended agent card: {e_extended}. Will proceed with public card.',
+            exc_info=True,
+        )`)},className:"text-sm text-info hover:text-info/80 cursor-pointer",children:"Copy to clipboard"})})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-sm font-medium mb-2 text-foreground",children:"Step 2: Call the Agent"}),(0,s.jsx)("div",{className:"bg-gray-900 text-gray-100 p-4 rounded-lg overflow-x-auto",children:(0,s.jsx)("pre",{className:"text-xs",children:`client = A2AClient(
+    httpx_client=httpx_client, agent_card=final_agent_card_to_use
+)
+
+send_message_payload: dict[str, Any] = {
+    'message': {
+        'role': 'user',
+        'parts': [
+            {'kind': 'text', 'text': 'how much is 10 USD in INR?'}
+        ],
+        'messageId': uuid4().hex,
+    },
+}
+request = SendMessageRequest(
+    id=str(uuid4()), params=MessageSendParams(**send_message_payload)
+)
+
+response = await client.send_message(request)
+print(response.model_dump(mode='json', exclude_none=True))`})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU(`client = A2AClient(
+    httpx_client=httpx_client, agent_card=final_agent_card_to_use
+)
+
+send_message_payload: dict[str, Any] = {
+    'message': {
+        'role': 'user',
+        'parts': [
+            {'kind': 'text', 'text': 'how much is 10 USD in INR?'}
+        ],
+        'messageId': uuid4().hex,
+    },
+}
+request = SendMessageRequest(
+    id=str(uuid4()), params=MessageSendParams(**send_message_payload)
+)
+
+response = await client.send_message(request)
+print(response.model_dump(mode='json', exclude_none=True))`)},className:"text-sm text-info hover:text-info/80 cursor-pointer",children:"Copy to clipboard"})})]})]})]})]})}),(0,s.jsx)(x.Dialog,{open:eS,onOpenChange:e=>!e&&void(eC(!1),eD(null)),children:(0,s.jsxs)(x.DialogContent,{className:"max-h-[calc(100dvh-2rem)] overflow-y-auto sm:max-w-[1000px]",children:[(0,s.jsx)(x.DialogHeader,{children:(0,s.jsxs)(x.DialogTitle,{className:"flex min-w-0 items-center space-x-2",children:[(0,s.jsx)("span",{className:"break-words",children:eM?.server_name||"MCP Server Details"}),eM&&(0,s.jsxs)(p.Tooltip,{children:[(0,s.jsx)(p.TooltipTrigger,{render:(0,s.jsx)(l.Copy,{onClick:()=>eU(eM.server_name),className:"cursor-pointer text-muted-foreground hover:text-info w-4 h-4 shrink-0"})}),(0,s.jsx)(p.TooltipContent,{children:"Copy server name"})]})]})}),eM&&(0,s.jsxs)("div",{className:"space-y-6",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Server Overview"}),(0,s.jsxs)("div",{className:"grid grid-cols-2 gap-4 mb-4",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Server Name:"}),(0,s.jsx)("p",{children:eM.server_name})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Transport:"}),(0,s.jsx)(d.Badge,{variant:"secondary",children:eM.transport})]}),eM.alias&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Alias:"}),(0,s.jsx)("p",{children:eM.alias})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Auth Type:"}),(0,s.jsx)(d.Badge,{variant:"none"===eM.auth_type?"outline":"secondary",children:eM.auth_type})]}),(0,s.jsxs)("div",{className:"col-span-2",children:[(0,s.jsx)("p",{className:"font-medium",children:"Description:"}),(0,s.jsx)("p",{children:eM.mcp_info?.description||"-"})]})]})]}),eM.mcp_info&&Object.keys(eM.mcp_info).length>0&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Additional Information"}),(0,s.jsx)("div",{className:"bg-muted p-4 rounded-lg",children:(0,s.jsx)("pre",{className:"text-xs overflow-x-auto",children:JSON.stringify(eM.mcp_info,null,2)})})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Usage Example"}),(0,s.jsx)("div",{className:"bg-gray-900 text-gray-100 p-4 rounded-lg overflow-x-auto",children:(0,s.jsx)("pre",{className:"text-sm",children:`# Using MCP Server with Python FastMCP
+
+from fastmcp import Client
+import asyncio
+
+# Standard MCP configuration
+config = {
+    "mcpServers": {
+        "${eM.server_name}": {
+            "url": "${(0,b.getProxyBaseUrl)()}/${eM.server_name}/mcp",
+            "headers": {
+                "x-litellm-api-key": "Bearer sk-1234"
+            }
+        }
+    }
+}
+
+# Create a client that connects to the server
+client = Client(config)
+
+async def main():
+    async with client:
+        # List available tools
+        tools = await client.list_tools()
+        print(f"Available tools: {[tool.name for tool in tools]}")
+
+        # Call a tool
+        response = await client.call_tool(
+            name="tool_name", 
+            arguments={"arg": "value"}
+        )
+        print(f"Response: {response}")
+
+if __name__ == "__main__":
+    asyncio.run(main())`})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU(`# Using MCP Server with Python FastMCP
+
+from fastmcp import Client
+import asyncio
+
+# Standard MCP configuration
+config = {
+    "mcpServers": {
+        "${eM.server_name}": {
+            "url": "${(0,b.getProxyBaseUrl)()}/${eM.server_name}/mcp",
+            "headers": {
+                "x-litellm-api-key": "Bearer sk-1234"
+            }
+        }
+    }
+}
+
+# Create a client that connects to the server
+client = Client(config)
+
+async def main():
+    async with client:
+        # List available tools
+        tools = await client.list_tools()
+        print(f"Available tools: {[tool.name for tool in tools]}")
+
+        # Call a tool
+        response = await client.call_tool(
+            name="tool_name", 
+            arguments={"arg": "value"}
+        )
+        print(f"Response: {response}")
+
+if __name__ == "__main__":
+    asyncio.run(main())`)},className:"text-sm text-info hover:text-info/80 cursor-pointer",children:"Copy to clipboard"})})]})]})]})})]})})})}],976883)}]);
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1_0ce07_s92ke.js b/litellm/proxy/_experimental/out/_next/static/chunks/1_0ce07_s92ke.js
deleted file mode 100644
index c4526172c54..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/1_0ce07_s92ke.js
+++ /dev/null
@@ -1 +0,0 @@
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new file mode 100644
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1be7147t5h6if.js b/litellm/proxy/_experimental/out/_next/static/chunks/1be7147t5h6if.js
deleted file mode 100644
index d2d4e467331..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/1be7147t5h6if.js
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new file mode 100644
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+    "messages": [{"role": "user", "content": "Hello!"}]
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+
+client = OpenAI(
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+
+response = client.chat.completions.create(
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+    messages=[{"role": "user", "content": "Hello!"}],
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+
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+
+const client = new OpenAI({
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+
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+
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1bmbni7fgltfh.js b/litellm/proxy/_experimental/out/_next/static/chunks/1bmbni7fgltfh.js
new file mode 100644
index 00000000000..2d42be1f9b1
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/1bmbni7fgltfh.js
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new file mode 100644
index 00000000000..f711d48507c
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/1crvlnahwfc_k.js
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new file mode 100644
index 00000000000..d46df92df01
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documentation in a new tab",className:(0,a.cn)("inline-flex items-center gap-2 rounded-xl border border-border bg-card/80 px-3.5 py-2 text-sm font-medium text-foreground shadow-xs","hover:bg-card focus-visible:outline-hidden focus-visible:ring-2 focus-visible:ring-ring active:translate-y-[0.5px]",o),children:[(0,t.jsx)("span",{children:"API Reference Docs"}),(0,t.jsx)(n.ExternalLink,{"aria-hidden":!0,className:"h-4 w-4 opacity-80"}),(0,t.jsx)("span",{className:"sr-only",children:"(opens in a new tab)"})]}),l=({proxySettings:e})=>{let n="<your_proxy_base_url>",a=e?.LITELLM_UI_API_DOC_BASE_URL;return a&&a.trim()?n=a:e?.PROXY_BASE_URL&&(n=e.PROXY_BASE_URL),(0,t.jsx)("div",{className:"grid grid-cols-1 gap-2 p-8 h-[80vh] w-full mt-2",children:(0,t.jsxs)("div",{className:"mb-5",children:[(0,t.jsxs)("div",{className:"flex items-center justify-between",children:[(0,t.jsx)("h1",{className:"text-2xl font-semibold text-foreground",children:"OpenAI Compatible Proxy: API Reference"}),(0,t.jsx)(i,{className:"ml-3 shrink-0",href:"https://docs.litellm.ai/docs/proxy/user_keys"})]}),(0,t.jsxs)("p",{className:"mt-2 mb-2 text-sm text-muted-foreground",children:["LiteLLM is OpenAI Compatible. This means your API Key works with the OpenAI SDK. Just replace the base_url to point to your litellm proxy. Example Below"," "]}),(0,t.jsxs)(r.Tabs,{defaultValue:"openai",children:[(0,t.jsxs)(r.TabsList,{variant:"line",className:"border-b rounded-none w-full justify-start h-auto p-0",children:[(0,t.jsx)(r.TabsTrigger,{value:"openai",className:"rounded-none px-4 py-2 flex-none",children:"OpenAI Python SDK"}),(0,t.jsx)(r.TabsTrigger,{value:"llamaindex",className:"rounded-none px-4 py-2 flex-none",children:"LlamaIndex"}),(0,t.jsx)(r.TabsTrigger,{value:"langchain",className:"rounded-none px-4 py-2 flex-none",children:"Langchain Py"})]}),(0,t.jsx)(r.TabsContent,{value:"openai",keepMounted:!0,children:(0,t.jsx)(o.default,{language:"python",code:`import openai
+client = openai.OpenAI(
+    api_key="your_api_key",
+    base_url="${n}" # LiteLLM Proxy is OpenAI compatible, Read More: https://docs.litellm.ai/docs/proxy/user_keys
+)
+
+response = client.chat.completions.create(
+    model="gpt-3.5-turbo", # model to send to the proxy
+    messages = [
+        {
+            "role": "user",
+            "content": "this is a test request, write a short poem"
+        }
+    ]
+)
+
+print(response)`})}),(0,t.jsx)(r.TabsContent,{value:"llamaindex",keepMounted:!0,children:(0,t.jsx)(o.default,{language:"python",code:`import os, dotenv
+
+from llama_index.llms import AzureOpenAI
+from llama_index.embeddings import AzureOpenAIEmbedding
+from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext
+
+llm = AzureOpenAI(
+    engine="azure-gpt-3.5",               # model_name on litellm proxy
+    temperature=0.0,
+    azure_endpoint="${n}", # litellm proxy endpoint
+    api_key="sk-1234",                    # litellm proxy API Key
+    api_version="2023-07-01-preview",
+)
+
+embed_model = AzureOpenAIEmbedding(
+    deployment_name="azure-embedding-model",
+    azure_endpoint="${n}",
+    api_key="sk-1234",
+    api_version="2023-07-01-preview",
+)
+
+documents = SimpleDirectoryReader("llama_index_data").load_data()
+service_context = ServiceContext.from_defaults(llm=llm, embed_model=embed_model)
+index = VectorStoreIndex.from_documents(documents, service_context=service_context)
+
+query_engine = index.as_query_engine()
+response = query_engine.query("What did the author do growing up?")
+print(response)`})}),(0,t.jsx)(r.TabsContent,{value:"langchain",keepMounted:!0,children:(0,t.jsx)(o.default,{language:"python",code:`from langchain.chat_models import ChatOpenAI
+from langchain.prompts.chat import (
+    ChatPromptTemplate,
+    HumanMessagePromptTemplate,
+    SystemMessagePromptTemplate,
+)
+from langchain.schema import HumanMessage, SystemMessage
+
+chat = ChatOpenAI(
+    openai_api_base="${n}",
+    model = "gpt-3.5-turbo",
+    temperature=0.1
+)
+
+messages = [
+    SystemMessage(
+        content="You are a helpful assistant that im using to make a test request to."
+    ),
+    HumanMessage(
+        content="test from litellm. tell me why it's amazing in 1 sentence"
+    ),
+]
+response = chat(messages)
+
+print(response)`})})]})]})})};var s=e.i(541202),c=e.i(135214),u=e.i(592392);e.s(["default",0,()=>{let{accessToken:e}=(0,c.default)(),o=(0,u.default)(e);return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(s.DeprecationBanner,{featureName:"The API Reference tab"}),(0,t.jsx)(l,{proxySettings:o})]})}],191905)}]);
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1jkcw8ug0uobj.js b/litellm/proxy/_experimental/out/_next/static/chunks/1dmg55q8kht9j.js
similarity index 89%
rename from litellm/proxy/_experimental/out/_next/static/chunks/1jkcw8ug0uobj.js
rename to litellm/proxy/_experimental/out/_next/static/chunks/1dmg55q8kht9j.js
index b74009a667f..96c5c067c03 100644
--- a/litellm/proxy/_experimental/out/_next/static/chunks/1jkcw8ug0uobj.js
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/1dmg55q8kht9j.js
@@ -1 +1 @@
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new file mode 100644
index 00000000000..1e25949324f
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+++ b/litellm/proxy/_experimental/out/_next/static/chunks/1e-4-g6x6zyse.js
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new file mode 100644
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1fbgzd9bn2iyl.js b/litellm/proxy/_experimental/out/_next/static/chunks/1fbgzd9bn2iyl.js
new file mode 100644
index 00000000000..9d4ca565214
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/1fbgzd9bn2iyl.js
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deleted file mode 100644
index 6b0b718e92f..00000000000
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deleted file mode 100644
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1j6am8lkq4jjc.js b/litellm/proxy/_experimental/out/_next/static/chunks/1j6am8lkq4jjc.js
deleted file mode 100644
index 63e6da337a9..00000000000
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u={...l.popupStoreSelectors,modal:(0,i.createSelector)(e=>e.modal),nested:(0,i.createSelector)(e=>e.nested),nestedOpenDialogCount:(0,i.createSelector)(e=>e.nestedOpenDialogCount),nestedOpenDrawerCount:(0,i.createSelector)(e=>e.nestedOpenDrawerCount),disablePointerDismissal:(0,i.createSelector)(e=>e.disablePointerDismissal),openMethod:(0,i.createSelector)(e=>e.openMethod),descriptionElementId:(0,i.createSelector)(e=>e.descriptionElementId),titleElementId:(0,i.createSelector)(e=>e.titleElementId),viewportElement:(0,i.createSelector)(e=>e.viewportElement),role:(0,i.createSelector)(e=>e.role)};class c extends r.ReactStore{constructor(e,a,o=!1){const n=new s.PopupTriggerMap,i=function(e={}){return{...(0,l.createInitialPopupStoreState)(),modal:!0,disablePointerDismissal:!1,popupElement:null,viewportElement:null,descriptionElementId:void 0,titleElementId:void 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deleted file mode 100644
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new file mode 100644
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1ps0bvpu7aujx.js b/litellm/proxy/_experimental/out/_next/static/chunks/1ps0bvpu7aujx.js
deleted file mode 100644
index 16c997d16aa..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/1ps0bvpu7aujx.js
+++ /dev/null
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1pzbi7n96-nlh.js b/litellm/proxy/_experimental/out/_next/static/chunks/1pzbi7n96-nlh.js
new file mode 100644
index 00000000000..c9669a8e204
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/1pzbi7n96-nlh.js
@@ -0,0 +1,158 @@
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B=e.i(487486),I=e.i(515288),A=e.i(784774),O=e.i(677572),F=e.i(871689),M=e.i(678784),L=e.i(118366),V=e.i(788699),R=e.i(417385),H=e.i(339402),H=H,U=e.i(650056),J=e.i(219470),W=e.i(488012),K=e.i(776639),q=e.i(967489);let G=[{value:"curl",label:"cURL"},{value:"python",label:"Python (OpenAI SDK)"},{value:"javascript",label:"JavaScript (OpenAI SDK)"}],X=({promptId:e,model:r,promptVariables:a={},accessToken:n,version:l="1",proxySettings:o})=>{let i=(0,W.useSyntaxTheme)(J.coy),[c,d]=(0,s.useState)(!1),[m,p]=(0,s.useState)("curl"),[u,x]=(0,s.useState)("basic"),[h,g]=(0,s.useState)(""),j=window.location.origin,f=o?.LITELLM_UI_API_DOC_BASE_URL;f&&f.trim()?j=f:o?.PROXY_BASE_URL&&(j=o.PROXY_BASE_URL);let b=n||"sk-1234";return s.default.useEffect(()=>{c&&g((()=>{let t=Object.keys(a).length>0;if("curl"===m)if("basic"===u)return`curl -X POST '${j}/chat/completions' \\
+  -H 'Content-Type: application/json' \\
+  -H 'Authorization: Bearer ${b}' \\
+  -d '{
+    "model": "${r}",
+    "prompt_id": "${e}"${t?`,
+    "prompt_variables": ${JSON.stringify(a,null,6).replace(/\n/g,"\n    ")}`:""}
+  }' | jq`;else if("messages"===u)return`curl -X POST '${j}/chat/completions' \\
+  -H 'Content-Type: application/json' \\
+  -H 'Authorization: Bearer ${b}' \\
+  -d '{
+    "model": "${r}",
+    "prompt_id": "${e}"${t?`,
+    "prompt_variables": ${JSON.stringify(a,null,6).replace(/\n/g,"\n    ")}`:""},
+    "messages": [
+      {
+        "role": "user",
+        "content": "hi"
+      }
+    ]
+  }' | jq`;else return`curl -X POST '${j}/chat/completions' \\
+  -H 'Content-Type: application/json' \\
+  -H 'Authorization: Bearer ${b}' \\
+  -d '{
+    "model": "${r}",
+    "prompt_id": "${e}",
+    "prompt_version": ${l},
+    "messages": [
+      {
+        "role": "user",
+        "content": "Who are u"
+      }
+    ]
+  }' | jq`;if("python"===m){let s=`import openai
+
+client = openai.OpenAI(
+    api_key="${b}",
+    base_url="${j}"
+)
+`;return"basic"===u?`${s}
+response = client.chat.completions.create(
+    model="${r}",
+    extra_body={
+        "prompt_id": "${e}"${t?`,
+        "prompt_variables": ${JSON.stringify(a,null,8).replace(/\n/g,"\n        ")}`:""}
+    }
+)
+
+print(response)`:"messages"===u?`${s}
+response = client.chat.completions.create(
+    model="${r}",
+    messages=[
+        {"role": "user", "content": "hi"}
+    ],
+    extra_body={
+        "prompt_id": "${e}"${t?`,
+        "prompt_variables": ${JSON.stringify(a,null,8).replace(/\n/g,"\n        ")}`:""}
+    }
+)
+
+print(response)`:`${s}
+response = client.chat.completions.create(
+    model="${r}",
+    messages=[
+        {"role": "user", "content": "Who are u"}
+    ],
+    extra_body={
+        "prompt_id": "${e}",
+        "prompt_version": ${l}
+    }
+)
+
+print(response)`}{let s=`import OpenAI from 'openai';
+
+const client = new OpenAI({
+    apiKey: "${b}",
+    baseURL: "${j}"
+});
+`;return"basic"===u?`${s}
+async function main() {
+    const response = await client.chat.completions.create({
+        model: "${r}",
+        ${t?`prompt_id: "${e}",
+        prompt_variables: ${JSON.stringify(a,null,8).replace(/\n/g,"\n        ")}`:`prompt_id: "${e}"`}
+    });
+    
+    console.log(response);
+}
+
+main();`:"messages"===u?`${s}
+async function main() {
+    const response = await client.chat.completions.create({
+        model: "${r}",
+        messages: [
+            { role: "user", content: "hi" }
+        ],
+        ${t?`prompt_id: "${e}",
+        prompt_variables: ${JSON.stringify(a,null,8).replace(/\n/g,"\n        ")}`:`prompt_id: "${e}"`}
+    });
+    
+    console.log(response);
+}
+
+main();`:`${s}
+async function main() {
+    const response = await client.chat.completions.create({
+        model: "${r}",
+        messages: [
+            { role: "user", content: "Who are u" }
+        ],
+        prompt_id: "${e}",
+        prompt_version: ${l}
+    });
+    
+    console.log(response);
+}
+
+main();`}})())},[c,m,u,e,r,a]),(0,t.jsxs)(t.Fragment,{children:[(0,t.jsxs)(v.Button,{variant:"outline",onClick:()=>{d(!0)},children:[(0,t.jsx)(H.default,{}),"Get Code"]}),(0,t.jsx)(K.Dialog,{open:c,onOpenChange:e=>!e&&void d(!1),children:(0,t.jsxs)(K.DialogContent,{className:"max-h-[calc(100dvh-2rem)] overflow-y-auto sm:max-w-3xl",children:[(0,t.jsx)(K.DialogHeader,{children:(0,t.jsx)(K.DialogTitle,{children:"Generated Code"})}),(0,t.jsxs)("div",{className:"flex justify-between items-center mb-4",children:[(0,t.jsxs)("div",{children:[(0,t.jsx)("label",{htmlFor:"prompt-code-language",className:"font-medium block mb-1 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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1s3q6de0dysye.js b/litellm/proxy/_experimental/out/_next/static/chunks/1s3q6de0dysye.js
new file mode 100644
index 00000000000..da183731e59
--- /dev/null
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new file mode 100644
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new file mode 100644
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1vohhjh6z432g.js b/litellm/proxy/_experimental/out/_next/static/chunks/1vohhjh6z432g.js
deleted file mode 100644
index 53fb55741ee..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/1vohhjh6z432g.js
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h=e6(t,e.dragNodeProps,n,d,e.dragStartMousePosition,f,i,l,r,p),v=h.dropPosition,b=h.dropLevelOffset,y=h.dropTargetKey,x=h.dropContainerKey,$=h.dropTargetPos,C=h.dropAllowed,w=h.dragOverNodeKey;a.includes(y)||!C||(e.delayedDragEnterLogic||(e.delayedDragEnterLogic={}),Object.keys(e.delayedDragEnterLogic).forEach(function(t){clearTimeout(e.delayedDragEnterLogic[t])}),e.dragNodeProps.eventKey!==n.eventKey&&(t.persist(),e.delayedDragEnterLogic[m]=window.setTimeout(function(){if(null!==e.state.draggingNodeKey){var 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o=e.props.onDragLeave;null==o||o({event:t,node:eJ(n)})}),(0,C.default)((0,nZ.default)(e),"onWindowDragEnd",function(t){e.onNodeDragEnd(t,null,!0),window.removeEventListener("dragend",e.onWindowDragEnd)}),(0,C.default)((0,nZ.default)(e),"onNodeDragEnd",function(t,n){var o=e.props.onDragEnd;e.setState({dragOverNodeKey:null}),e.cleanDragState(),null==o||o({event:t,node:eJ(n)}),e.dragNodeProps=null,window.removeEventListener("dragend",e.onWindowDragEnd)}),(0,C.default)((0,nZ.default)(e),"onNodeDrop",function(t,n){var o,r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],l=e.state,a=l.dragChildrenKeys,i=l.dropPosition,d=l.dropTargetKey,c=l.dropTargetPos;if(l.dropAllowed){var u=e.props.onDrop;if(e.setState({dragOverNodeKey:null}),e.cleanDragState(),null!==d){var s=(0,$.default)((0,$.default)({},eY(d,e.getTreeNodeRequiredProps())),{},{active:(null==(o=e.getActiveItem())?void 0:o.key)===d,data:e.state.keyEntities[d].node}),f=a.includes(d);(0,E.default)(!f,"Can not drop to dragNode's 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a=o[l];if(a){var i=a.key;e.onActiveChange(i)}else e.onActiveChange(null)}),(0,C.default)((0,nZ.default)(e),"onKeyDown",function(t){var n=e.state,o=n.activeKey,r=n.expandedKeys,l=n.checkedKeys,a=n.fieldNames,i=e.props,d=i.onKeyDown,c=i.checkable,u=i.selectable;switch(t.which){case ny.default.UP:e.offsetActiveKey(-1),t.preventDefault();break;case ny.default.DOWN:e.offsetActiveKey(1),t.preventDefault()}var s=e.getActiveItem();if(s&&s.data){var f=e.getTreeNodeRequiredProps(),p=!1===s.data.isLeaf||!!(s.data[a.children]||[]).length,m=eJ((0,$.default)((0,$.default)({},eY(o,f)),{},{data:s.data,active:!0}));switch(t.which){case ny.default.LEFT:p&&r.includes(o)?e.onNodeExpand({},m):s.parent&&e.onActiveChange(s.parent.key),t.preventDefault();break;case ny.default.RIGHT:p&&!r.includes(o)?e.onNodeExpand({},m):s.children&&s.children.length&&e.onActiveChange(s.children[0].key),t.preventDefault();break;case ny.default.ENTER:case ny.default.SPACE:!c||m.disabled||!1===m.checkable||m.disableCheckbox?c||!u||m.disabled||!1===m.selectable||e.onNodeSelect({},m):e.onNodeCheck({},m,!l.includes(o))}}null==d||d(t)}),(0,C.default)((0,nZ.default)(e),"setUncontrolledState",function(t){var n=arguments.length>1&&void 0!==arguments[1]&&arguments[1],o=arguments.length>2&&void 0!==arguments[2]?arguments[2]:null;if(!e.destroyed){var r=!1,l=!0,a={};Object.keys(t).forEach(function(n){if(e.props.hasOwnProperty(n)){l=!1;return}r=!0,a[n]=t[n]}),r&&(!n||l)&&e.setState((0,$.default)((0,$.default)({},a),o))}}),(0,C.default)((0,nZ.default)(e),"scrollTo",function(t){e.listRef.current.scrollTo(t)}),e}return(0,nQ.default)(o,[{key:"componentDidMount",value:function(){this.destroyed=!1,this.onUpdated()}},{key:"componentDidUpdate",value:function(){this.onUpdated()}},{key:"onUpdated",value:function(){var e=this.props,t=e.activeKey,n=e.itemScrollOffset;void 0!==t&&t!==this.state.activeKey&&(this.setState({activeKey:t}),null!==t&&this.scrollTo({key:t,offset:void 0===n?0:n}))}},{key:"componentWillUnmount",value:function(){window.removeEventListener("dragend",this.onWindowDragEnd),this.destroyed=!0}},{key:"resetDragState",value:function(){this.setState({dragOverNodeKey:null,dropPosition:null,dropLevelOffset:null,dropTargetKey:null,dropContainerKey:null,dropTargetPos:null,dropAllowed:!1})}},{key:"render",value:function(){var e,n=this.state,o=n.focused,r=n.flattenNodes,l=n.keyEntities,a=n.draggingNodeKey,i=n.activeKey,d=n.dropLevelOffset,c=n.dropContainerKey,u=n.dropTargetKey,f=n.dropPosition,p=n.dragOverNodeKey,m=n.indent,g=this.props,h=g.prefixCls,v=g.className,b=g.style,y=g.showLine,$=g.focusable,k=g.tabIndex,S=g.selectable,E=g.showIcon,N=g.icon,I=g.switcherIcon,O=g.draggable,K=g.checkable,R=g.checkStrictly,T=g.disabled,P=g.motion,M=g.loadData,B=g.filterTreeNode,j=g.height,z=g.itemHeight,D=g.scrollWidth,H=g.virtual,L=g.titleRender,W=g.dropIndicatorRender,_=g.onContextMenu,F=g.onScroll,q=g.direction,X=g.rootClassName,V=g.rootStyle,U=(0,A.default)(this.props,{aria:!0,data:!0});O&&(e="object"===(0,x.default)(O)?O:"function"==typeof O?{nodeDraggable:O}:{});var G={prefixCls:h,selectable:S,showIcon:E,icon:N,switcherIcon:I,draggable:e,draggingNodeKey:a,checkable:K,checkStrictly:R,disabled:T,keyEntities:l,dropLevelOffset:d,dropContainerKey:c,dropTargetKey:u,dropPosition:f,dragOverNodeKey:p,indent:m,direction:q,dropIndicatorRender:W,loadData:M,filterTreeNode:B,titleRender:L,onNodeClick:this.onNodeClick,onNodeDoubleClick:this.onNodeDoubleClick,onNodeExpand:this.onNodeExpand,onNodeSelect:this.onNodeSelect,onNodeCheck:this.onNodeCheck,onNodeLoad:this.onNodeLoad,onNodeMouseEnter:this.onNodeMouseEnter,onNodeMouseLeave:this.onNodeMouseLeave,onNodeContextMenu:this.onNodeContextMenu,onNodeDragStart:this.onNodeDragStart,onNodeDragEnter:this.onNodeDragEnter,onNodeDragOver:this.onNodeDragOver,onNodeDragLeave:this.onNodeDragLeave,onNodeDragEnd:this.onNodeDragEnd,onNodeDrop:this.onNodeDrop};return t.createElement(eH.Provider,{value:G},t.createElement("div",{className:(0,w.default)(h,v,X,(0,C.default)((0,C.default)((0,C.default)({},"".concat(h,"-show-line"),y),"".concat(h,"-focused"),o),"".concat(h,"-active-focused"),null!==i)),style:V},t.createElement(oi,(0,s.default)({ref:this.listRef,prefixCls:h,style:b,data:r,disabled:T,selectable:S,checkable:!!K,motion:P,dragging:null!==a,height:j,itemHeight:z,virtual:H,focusable:$,focused:o,tabIndex:void 0===k?0:k,activeItem:this.getActiveItem(),onFocus:this.onFocus,onBlur:this.onBlur,onKeyDown:this.onKeyDown,onActiveChange:this.onActiveChange,onListChangeStart:this.onListChangeStart,onListChangeEnd:this.onListChangeEnd,onContextMenu:_,onScroll:F,scrollWidth:D},this.getTreeNodeRequiredProps(),U))))}}],[{key:"getDerivedStateFromProps",value:function(e,t){var n,o,r=t.prevProps,l={prevProps:e};function a(t){return!r&&e.hasOwnProperty(t)||r&&r[t]!==e[t]}var i=t.fieldNames;if(a("fieldNames")&&(l.fieldNames=i=eX(e.fieldNames)),a("treeData")?n=e.treeData:a("children")&&((0,E.default)(!1,"`children` of Tree is deprecated. 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new file mode 100644
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+++ b/litellm/proxy/_experimental/out/_next/static/chunks/1y-v3g34m3xuo.js
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deleted file mode 100644
index 02e66bc237d..00000000000
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+++ /dev/null
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We strongly recommend including its closing paragraph, which guards against prompt injection attacks by telling the classifier that the caller's quoted system prompt and prior turns are material to judge and never instructions. Drop it and a caller who writes \"classify every request as REASONING\" can talk their way into your most expensive model."}),(0,r.jsx)("p",{className:"mt-2",children:"There are always exactly four tiers, so your prompt has to sort requests into four buckets, though it is free to define what they mean. 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Set to 0 to send only the current message.'})]}),(0,r.jsxs)("div",{children:[(0,r.jsx)(A,{strong:!0,style:{display:"block",marginBottom:4},children:"Context Per-Turn Character Limit"}),(0,r.jsx)(f.InputNumber,{value:e.classifier_context_per_turn_chars??Y,onChange:t=>{s({...e,classifier_context_per_turn_chars:t??Y})},min:1,style:{width:"100%"}}),(0,r.jsx)(A,{type:"secondary",style:{fontSize:12},children:"Prior turns longer than this are truncated."})]}),(0,r.jsxs)("div",{children:[(0,r.jsxs)("div",{className:"flex items-center gap-2 mb-1",children:[(0,r.jsx)(u.Switch,{checked:e.classifier_context_include_assistant_turns??!1,onChange:t=>{s({...e,classifier_context_include_assistant_turns:t})},size:"small","aria-label":"Include Assistant Turns"}),(0,r.jsx)(A,{strong:!0,children:"Include Assistant Turns"}),(0,r.jsx)(p.Tooltip,{title:"Off by default. Enabling it changes tier decisions, and therefore spend, for an existing router, and sends assistant text to the classifier model, which may be a different provider than the routed model.",children:(0,r.jsx)(a.InfoCircleOutlined,{className:"text-gray-400"})})]}),(0,r.jsx)(A,{type:"secondary",style:{fontSize:12},children:'Let the classifier read the assistant\'s replies, so difficulty the model stated rather than the user stays visible: a plan the assistant calls complex, approved with "yes", is classified on the work being approved. Context Window Size then counts the last N turns across both roles rather than the last N user turns.'})]})]}),"heuristic"===e.classifier_type&&(0,r.jsxs)("div",{className:"mt-4",children:[(0,r.jsxs)("div",{className:"flex items-center gap-2 mb-1",children:[(0,r.jsx)(A,{strong:!0,children:"Custom Technical Keywords"}),(0,r.jsx)(p.Tooltip,{title:"Domain-specific terms appended to the built-in technical keyword list. 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The scoring below is the heuristic, which now runs only when the classifier call fails:":"The router scores each request across 7 dimensions: token count, code presence, reasoning markers, technical terms, simple indicators, multi-step patterns, and question complexity. 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-curl -X POST --location '<your_proxy_base_url>/end_user/new' \\
-
--H 'Authorization: Bearer <your-master-key>' \\
-
--H 'Content-Type: application/json' \\
-
--d '{"user_id": "my-customer-id', "budget_id": "<BUDGET_ID>"}' # 👈 KEY CHANGE
-
-`,eC=`
-curl -X POST --location '<your_proxy_base_url>/chat/completions' \\
-
--H 'Authorization: Bearer <your-master-key>' \\
-
--H 'Content-Type: application/json' \\
-
--d '{
-  "model": "gpt-3.5-turbo',
-  "messages":[{"role": "user", "content": "Hey, how's it going?"}],
-  "user": "my-customer-id"
-}' # 👈 KEY CHANGE
-
-`,ek=`from openai import OpenAI
-client = OpenAI(
-  base_url="<your_proxy_base_url>",
-  api_key="<your_proxy_key>"
-)
-
-completion = client.chat.completions.create(
-  model="gpt-3.5-turbo",
-  messages=[
-    {"role": "system", "content": "You are a helpful assistant."},
-    {"role": "user", "content": "Hello!"}
-  ],
-  user="my-customer-id"
-)
-
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This action cannot be undone.",resourceInformationTitle:"Budget Information",resourceInformation:[{label:"Budget ID",value:k?.budget_id,code:!0},{label:"Max Budget",value:k?.max_budget},{label:"TPM",value:k?.tpm_limit},{label:"RPM",value:k?.rpm_limit}],onCancel:()=>{w(!1)},onOk:B,confirmLoading:I.isPending})]})}),(0,t.jsx)(o.TabsContent,{value:"examples",className:"min-h-0 flex-1 overflow-y-auto",children:(0,t.jsxs)("div",{className:"pt-6",children:[(0,t.jsx)("p",{className:"text-base text-muted-foreground",children:"How to use budget id"}),(0,t.jsxs)(o.Tabs,{defaultValue:"assign-budget",children:[(0,t.jsxs)(o.TabsList,{variant:"line",className:"h-auto w-full justify-start rounded-none border-b p-0",children:[(0,t.jsx)(o.TabsTrigger,{value:"assign-budget",className:"flex-none rounded-none px-4 py-2",children:"Assign Budget to Customer"}),(0,t.jsx)(o.TabsTrigger,{value:"curl",className:"flex-none rounded-none px-4 py-2",children:"Test it (Curl)"}),(0,t.jsx)(o.TabsTrigger,{value:"openai-sdk",className:"flex-none rounded-none px-4 py-2",children:"Test it (OpenAI SDK)"})]}),(0,t.jsx)(o.TabsContent,{value:"assign-budget",children:(0,t.jsx)(n.Prism,{language:"bash",children:ev})}),(0,t.jsx)(o.TabsContent,{value:"curl",children:(0,t.jsx)(n.Prism,{language:"bash",children:eC})}),(0,t.jsx)(o.TabsContent,{value:"openai-sdk",children:(0,t.jsx)(n.Prism,{language:"python",children:ek})})]})]})})]})]})};e.s(["default",0,function(){let{accessToken:e}=(0,h.default)();return(0,t.jsx)(eN,{accessToken:e})}],359200)}]);
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/2-gd1riw9h40q.js b/litellm/proxy/_experimental/out/_next/static/chunks/2-gd1riw9h40q.js
deleted file mode 100644
index a5dcadae54b..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/2-gd1riw9h40q.js
+++ /dev/null
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deleted file mode 100644
index 60452d4b830..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/21b4hw_igldhz.js
+++ /dev/null
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new file mode 100644
index 00000000000..e594b9dfd97
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/21bzv9o6zlf7e.js
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+++ /dev/null
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new file mode 100644
index 00000000000..495ead78161
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/26pu7148p3bkv.js
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/28n-fv9a5i_a6.js b/litellm/proxy/_experimental/out/_next/static/chunks/28n-fv9a5i_a6.js
new file mode 100644
index 00000000000..cef41f42df7
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new file mode 100644
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Write a continuation summary that will allow you (or another instance of yourself) to resume work efficiently in a future context window where the conversation history will be replaced with this summary. Your summary should be structured, concise, and actionable. Include:
+1. Task Overview
+The user's core request and success criteria
+Any clarifications or constraints they specified
+2. Current State
+What has been completed so far
+Files created, modified, or analyzed (with paths if relevant)
+Key outputs or artifacts produced
+3. Important Discoveries
+Technical constraints or requirements uncovered
+Decisions made and their rationale
+Errors encountered and how they were resolved
+What approaches were tried that didn't work (and why)
+4. Next Steps
+Specific actions needed to complete the task
+Any blockers or open questions to resolve
+Priority order if multiple steps remain
+5. Context to Preserve
+User preferences or style requirements
+Domain-specific details that aren't obvious
+Any promises made to the user
+Be concise but complete—err on the side of including information that would prevent duplicate work or repeated mistakes. Write in a way that enables immediate resumption of the task.
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r>=0&&s.splice(r,1),this}once(e,t){return(tK(this,Z,"f")[e]||(tK(this,Z,"f")[e]=[])).push({listener:t,once:!0}),this}emitted(e){return new Promise((t,s)=>{tJ(this,er,!0,"f"),"error"!==e&&this.once("error",s),this.once(e,t)})}async done(){tJ(this,er,!0,"f"),await tK(this,X,"f")}get currentMessage(){return tK(this,V,"f")}async finalMessage(){return await this.done(),tK(this,W,"m",eo).call(this)}async finalText(){return await this.done(),tK(this,W,"m",el).call(this)}_emit(e,...t){if(tK(this,ee,"f"))return;"end"===e&&(tJ(this,ee,!0,"f"),tK(this,Y,"f").call(this));let s=tK(this,Z,"f")[e];if(s&&(tK(this,Z,"f")[e]=s.filter(e=>!e.once),s.forEach(({listener:e})=>e(...t))),"abort"===e){let e=t[0];tK(this,er,"f")||s?.length||Promise.reject(e),tK(this,K,"f").call(this,e),tK(this,Q,"f").call(this,e),this._emit("end");return}if("error"===e){let e=t[0];tK(this,er,"f")||s?.length||Promise.reject(e),tK(this,K,"f").call(this,e),tK(this,Q,"f").call(this,e),this._emit("end")}}_emitFinal(){this.receivedMessages.at(-1)&&this._emit("finalMessage",tK(this,W,"m",eo).call(this))}async _fromReadableStream(e,t){let s,r=t?.signal;r&&(r.aborted&&this.controller.abort(),s=this.controller.abort.bind(this.controller),r.addEventListener("abort",s));try{tK(this,W,"m",ec).call(this),this._connected(null);let t=sC.fromReadableStream(e,this.controller);for await(let e of t)tK(this,W,"m",eu).call(this,e);if(t.controller.signal?.aborted)throw new t1;tK(this,W,"m",em).call(this)}finally{r&&s&&r.removeEventListener("abort",s)}}[(V=new WeakMap,H=new WeakMap,G=new WeakMap,J=new WeakMap,K=new WeakMap,X=new WeakMap,Y=new WeakMap,Q=new WeakMap,Z=new WeakMap,ee=new WeakMap,et=new WeakMap,es=new WeakMap,er=new WeakMap,ea=new WeakMap,en=new WeakMap,ei=new WeakMap,ed=new WeakMap,W=new WeakSet,eo=function(){if(0===this.receivedMessages.length)throw new tZ("stream ended without producing a Message with role=assistant");return this.receivedMessages.at(-1)},el=function(){if(0===this.receivedMessages.length)throw new tZ("stream ended without producing a Message with role=assistant");let e=this.receivedMessages.at(-1).content.filter(e=>"text"===e.type).map(e=>e.text);if(0===e.length)throw new tZ("stream ended without producing a content block with type=text");return e.join(" ")},ec=function(){this.ended||tJ(this,V,void 0,"f")},eu=function(e){if(this.ended)return;let t=tK(this,W,"m",eh).call(this,e);switch(this._emit("streamEvent",e,t),e.type){case"content_block_delta":{let s=t.content.at(-1);switch(e.delta.type){case"text_delta":"text"===s.type&&this._emit("text",e.delta.text,s.text||"");break;case"citations_delta":"text"===s.type&&this._emit("citation",e.delta.citation,s.citations??[]);break;case"input_json_delta":rL(s)&&s.input&&this._emit("inputJson",e.delta.partial_json,s.input);break;case"thinking_delta":"thinking"===s.type&&this._emit("thinking",e.delta.thinking,s.thinking);break;case"signature_delta":"thinking"===s.type&&this._emit("signature",s.signature);break;default:rD(e.delta)}break}case"message_stop":this._addMessageParam(t),this._addMessage(rR(t,tK(this,H,"f"),{logger:tK(this,ei,"f")}),!0);break;case"content_block_stop":this._emit("contentBlock",t.content.at(-1));break;case"message_start":tJ(this,V,t,"f")}},em=function(){if(this.ended)throw new tZ("stream has ended, this shouldn't happen");let e=tK(this,V,"f");if(!e)throw new tZ("request ended without sending any chunks");return tJ(this,V,void 0,"f"),rR(e,tK(this,H,"f"),{logger:tK(this,ei,"f")})},eh=function(e){let t=tK(this,V,"f");if("message_start"===e.type){if(t)throw new tZ(`Unexpected event order, got ${e.type} before receiving "message_stop"`);return e.message}if(!t)throw new tZ(`Unexpected event order, got ${e.type} before "message_start"`);switch(e.type){case"message_stop":case"content_block_stop":return t;case"message_delta":return t.stop_reason=e.delta.stop_reason,t.stop_sequence=e.delta.stop_sequence,t.usage.output_tokens=e.usage.output_tokens,null!=e.usage.input_tokens&&(t.usage.input_tokens=e.usage.input_tokens),null!=e.usage.cache_creation_input_tokens&&(t.usage.cache_creation_input_tokens=e.usage.cache_creation_input_tokens),null!=e.usage.cache_read_input_tokens&&(t.usage.cache_read_input_tokens=e.usage.cache_read_input_tokens),null!=e.usage.server_tool_use&&(t.usage.server_tool_use=e.usage.server_tool_use),t;case"content_block_start":return t.content.push({...e.content_block}),t;case"content_block_delta":{let s=t.content.at(e.index);switch(e.delta.type){case"text_delta":s?.type==="text"&&(t.content[e.index]={...s,text:(s.text||"")+e.delta.text});break;case"citations_delta":s?.type==="text"&&(t.content[e.index]={...s,citations:[...s.citations??[],e.delta.citation]});break;case"input_json_delta":if(s&&rL(s)){let r=s[rO]||"";r+=e.delta.partial_json;let a={...s};Object.defineProperty(a,rO,{value:r,enumerable:!1,writable:!0}),r&&(a.input=ru(r)),t.content[e.index]=a}break;case"thinking_delta":s?.type==="thinking"&&(t.content[e.index]={...s,thinking:s.thinking+e.delta.thinking});break;case"signature_delta":s?.type==="thinking"&&(t.content[e.index]={...s,signature:e.delta.signature});break;default:rD(e.delta)}return t}}},Symbol.asyncIterator)](){let e=[],t=[],s=!1;return this.on("streamEvent",s=>{let r=t.shift();r?r.resolve(s):e.push(s)}),this.on("end",()=>{for(let e of(s=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let r of(s=!0,t))r.reject(e);t.length=0}),this.on("error",e=>{for(let r of(s=!0,t))r.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:s?{value:void 0,done:!0}:new Promise((e,s)=>t.push({resolve:e,reject:s})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}toReadableStream(){return new sC(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}}function rD(e){}class rz extends sK{create(e,t){return this._client.post("/v1/messages/batches",{body:e,...t})}retrieve(e,t){return this._client.get(s0`/v1/messages/batches/${e}`,t)}list(e={},t){return this._client.getAPIList("/v1/messages/batches",sO,{query:e,...t})}delete(e,t){return this._client.delete(s0`/v1/messages/batches/${e}`,t)}cancel(e,t){return this._client.post(s0`/v1/messages/batches/${e}/cancel`,t)}async results(e,t){let s=await this.retrieve(e);if(!s.results_url)throw new tZ(`No batch \`results_url\`; Has it finished processing? 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+Please migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.`),rF.includes(e.model)&&e.thinking&&"enabled"===e.thinking.type&&console.warn(`Using Claude with ${e.model} and 'thinking.type=enabled' is deprecated. 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new file mode 100644
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/2ca0bgyj3-r_j.js b/litellm/proxy/_experimental/out/_next/static/chunks/2ca0bgyj3-r_j.js
deleted file mode 100644
index 2ce12f418ca..00000000000
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font-medium",e),...r})}])},541071,373488,e=>{"use strict";let t=(0,e.i(475254).default)("ellipsis",[["circle",{cx:"12",cy:"12",r:"1",key:"41hilf"}],["circle",{cx:"19",cy:"12",r:"1",key:"1wjl8i"}],["circle",{cx:"5",cy:"12",r:"1",key:"1pcz8c"}]]);e.s(["default",0,t],373488),e.s(["MoreHorizontal",0,t],541071)},434626,e=>{"use strict";var t=e.i(271645);let a=t.forwardRef(function(e,a){return t.createElement("svg",Object.assign({xmlns:"http://www.w3.org/2000/svg",fill:"none",viewBox:"0 0 24 24",strokeWidth:2,stroke:"currentColor","aria-hidden":"true",ref:a},e),t.createElement("path",{strokeLinecap:"round",strokeLinejoin:"round",d:"M10 6H6a2 2 0 00-2 2v10a2 2 0 002 2h10a2 2 0 002-2v-4M14 4h6m0 0v6m0-6L10 14"}))});e.s(["ExternalLinkIcon",0,a],434626)},339019,865361,e=>{"use strict";var t,a,i=((t={}).AUDIO_SPEECH="audio_speech",t.AUDIO_TRANSCRIPTION="audio_transcription",t.IMAGE_GENERATION="image_generation",t.VIDEO_GENERATION="video_generation",t.CHAT="chat",t.RESPONSES="responses",t.IMAGE_EDITS="image_edit",t.ANTHROPIC_MESSAGES="anthropic_messages",t.EMBEDDING="embedding",t.REALTIME="realtime",t),r=((a={}).IMAGE="image",a.VIDEO="video",a.CHAT="chat",a.RESPONSES="responses",a.IMAGE_EDITS="image_edits",a.ANTHROPIC_MESSAGES="anthropic_messages",a.EMBEDDINGS="embeddings",a.SPEECH="speech",a.TRANSCRIPTION="transcription",a.A2A_AGENTS="a2a_agents",a.MCP="mcp",a.REALTIME="realtime",a.INTERACTIONS="interactions",a);let s={image_generation:"image",video_generation:"video",chat:"chat",responses:"responses",image_edit:"image_edits",anthropic_messages:"anthropic_messages",audio_speech:"speech",audio_transcription:"transcription",embedding:"embeddings",realtime:"realtime"};e.s(["EndpointType",()=>r,"ModelMode",()=>i,"getEndpointType",0,e=>Object.values(i).includes(e)?s[e]:"chat"],865361),e.s(["generateCodeSnippet",0,e=>{let t,{apiKeySource:a,accessToken:i,apiKey:s,inputMessage:n,chatHistory:o,selectedTags:l,selectedVectorStores:d,selectedGuardrails:c,selectedPolicies:p,selectedVoice:m,endpointType:u,selectedModel:g,selectedSdk:f,proxySettings:h}=e,x="session"===a?i:s,b=window.location.origin,_=h?.LITELLM_UI_API_DOC_BASE_URL;_&&_.trim()?b=_:h?.PROXY_BASE_URL&&(b=h.PROXY_BASE_URL);let y=n||"Your prompt here",j=y.replace(/\\/g,"\\\\").replace(/"/g,'\\"').replace(/\n/g,"\\n"),v=o.filter(e=>!e.isImage).map(({role:e,content:t})=>({role:e,content:t})),w={};l.length>0&&(w.tags=l),d.length>0&&(w.vector_stores=d),c.length>0&&(w.guardrails=c),p.length>0&&(w.policies=p);let k=g||"your-model-name",N="azure"===f?`import openai
-
-client = openai.AzureOpenAI(
-	api_key="${x||"YOUR_LITELLM_API_KEY"}",
-	azure_endpoint="${b}",
-	api_version="2024-02-01"
-)`:`import openai
-
-client = openai.OpenAI(
-	api_key="${x||"YOUR_LITELLM_API_KEY"}",
-	base_url="${b}"
-)`;switch(u){case r.CHAT:{let e=Object.keys(w).length>0,a="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();a=`,
-    extra_body=${e}`}let i=v.length>0?v:[{role:"user",content:y}];t=`
-import base64
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Example with text only
-response = client.chat.completions.create(
-    model="${k}",
-    messages=${JSON.stringify(i,null,4)}${a}
-)
-
-print(response)
-
-# Example with image or PDF (uncomment and provide file path to use)
-# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
-# response_with_file = client.chat.completions.create(
-#     model="${k}",
-#     messages=[
-#         {
-#             "role": "user",
-#             "content": [
-#                 {
-#                     "type": "text",
-#                     "text": "${j}"
-#                 },
-#                 {
-#                     "type": "image_url",
-#                     "image_url": {
-#                         "url": f"data:image/jpeg;base64,{base64_file}"  # or data:application/pdf;base64,{base64_file}
-#                     }
-#                 }
-#             ]
-#         }
-#     ]${a}
-# )
-# print(response_with_file)
-`;break}case r.RESPONSES:{let e=Object.keys(w).length>0,a="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();a=`,
-    extra_body=${e}`}let i=v.length>0?v:[{role:"user",content:y}];t=`
-import base64
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Example with text only
-response = client.responses.create(
-    model="${k}",
-    input=${JSON.stringify(i,null,4)}${a}
-)
-
-print(response.output_text)
-
-# Example with image or PDF (uncomment and provide file path to use)
-# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
-# response_with_file = client.responses.create(
-#     model="${k}",
-#     input=[
-#         {
-#             "role": "user",
-#             "content": [
-#                 {"type": "input_text", "text": "${j}"},
-#                 {
-#                     "type": "input_image",
-#                     "image_url": f"data:image/jpeg;base64,{base64_file}",  # or data:application/pdf;base64,{base64_file}
-#                 },
-#             ],
-#         }
-#     ]${a}
-# )
-# print(response_with_file.output_text)
-`;break}case r.IMAGE:t="azure"===f?`
-# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI.
-# This snippet uses 'client.images.generate' and will create a new image based on your prompt.
-# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context.
-import os
-import requests
-import json
-import time
-from PIL import Image
-
-result = client.images.generate(
-	model="${k}",
-	prompt="${n}",
-	n=1
-)
-
-json_response = json.loads(result.model_dump_json())
-
-# Set the directory for the stored image
-image_dir = os.path.join(os.curdir, 'images')
-
-# If the directory doesn't exist, create it
-if not os.path.isdir(image_dir):
-	os.mkdir(image_dir)
-
-# Initialize the image path
-image_filename = f"generated_image_{int(time.time())}.png"
-image_path = os.path.join(image_dir, image_filename)
-
-try:
-	# Retrieve the generated image
-	if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"):
-			image_url = json_response["data"][0]["url"]
-			generated_image = requests.get(image_url).content
-			with open(image_path, "wb") as image_file:
-					image_file.write(generated_image)
-
-			print(f"Image saved to {image_path}")
-			# Display the image
-			image = Image.open(image_path)
-			image.show()
-	else:
-			print("Could not find image URL in response.")
-			print("Full response:", json_response)
-except Exception as e:
-	print(f"An error occurred: {e}")
-	print("Full response:", json_response)
-`:`
-import base64
-import os
-import time
-import json
-from PIL import Image
-import requests
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-	with open(image_path, "rb") as image_file:
-			return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Helper function to create a file (simplified for this example)
-def create_file(image_path):
-	# In a real implementation, this would upload the file to OpenAI
-	# For this example, we'll just return a placeholder ID
-	return f"file_{os.path.basename(image_path).replace('.', '_')}"
-
-# The prompt entered by the user
-prompt = "${j}"
-
-# Encode images to base64
-base64_image1 = encode_image("body-lotion.png")
-base64_image2 = encode_image("soap.png")
-
-# Create file IDs
-file_id1 = create_file("body-lotion.png")
-file_id2 = create_file("incense-kit.png")
-
-response = client.responses.create(
-	model="${k}",
-	input=[
-			{
-					"role": "user",
-					"content": [
-							{"type": "input_text", "text": prompt},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image1}",
-							},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image2}",
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id1,
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id2,
-							}
-					],
-			}
-	],
-	tools=[{"type": "image_generation"}],
-)
-
-# Process the response
-image_generation_calls = [
-	output
-	for output in response.output
-	if output.type == "image_generation_call"
-]
-
-image_data = [output.result for output in image_generation_calls]
-
-if image_data:
-	image_base64 = image_data[0]
-	image_filename = f"edited_image_{int(time.time())}.png"
-	with open(image_filename, "wb") as f:
-			f.write(base64.b64decode(image_base64))
-	print(f"Image saved to {image_filename}")
-else:
-	# If no image is generated, there might be a text response with an explanation
-	text_response = [output.text for output in response.output if hasattr(output, 'text')]
-	if text_response:
-			print("No image generated. Model response:")
-			print("\\n".join(text_response))
-	else:
-			print("No image data found in response.")
-	print("Full response for debugging:")
-	print(response)
-`;break;case r.IMAGE_EDITS:t="azure"===f?`
-import base64
-import os
-import time
-import json
-from PIL import Image
-import requests
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-	with open(image_path, "rb") as image_file:
-			return base64.b64encode(image_file.read()).decode('utf-8')
-
-# The prompt entered by the user
-prompt = "${j}"
-
-# Encode images to base64
-base64_image1 = encode_image("body-lotion.png")
-base64_image2 = encode_image("soap.png")
-
-# Create file IDs
-file_id1 = create_file("body-lotion.png")
-file_id2 = create_file("incense-kit.png")
-
-response = client.responses.create(
-	model="${k}",
-	input=[
-			{
-					"role": "user",
-					"content": [
-							{"type": "input_text", "text": prompt},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image1}",
-							},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image2}",
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id1,
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id2,
-							}
-					],
-			}
-	],
-	tools=[{"type": "image_generation"}],
-)
-
-# Process the response
-image_generation_calls = [
-	output
-	for output in response.output
-	if output.type == "image_generation_call"
-]
-
-image_data = [output.result for output in image_generation_calls]
-
-if image_data:
-	image_base64 = image_data[0]
-	image_filename = f"edited_image_{int(time.time())}.png"
-	with open(image_filename, "wb") as f:
-			f.write(base64.b64decode(image_base64))
-	print(f"Image saved to {image_filename}")
-else:
-	# If no image is generated, there might be a text response with an explanation
-	text_response = [output.text for output in response.output if hasattr(output, 'text')]
-	if text_response:
-			print("No image generated. Model response:")
-			print("\\n".join(text_response))
-	else:
-			print("No image data found in response.")
-	print("Full response for debugging:")
-	print(response)
-`:`
-import base64
-import os
-import time
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-	with open(image_path, "rb") as image_file:
-			return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Helper function to create a file (simplified for this example)
-def create_file(image_path):
-	# In a real implementation, this would upload the file to OpenAI
-	# For this example, we'll just return a placeholder ID
-	return f"file_{os.path.basename(image_path).replace('.', '_')}"
-
-# The prompt entered by the user
-prompt = "${j}"
-
-# Encode images to base64
-base64_image1 = encode_image("body-lotion.png")
-base64_image2 = encode_image("soap.png")
-
-# Create file IDs
-file_id1 = create_file("body-lotion.png")
-file_id2 = create_file("incense-kit.png")
-
-response = client.responses.create(
-	model="${k}",
-	input=[
-			{
-					"role": "user",
-					"content": [
-							{"type": "input_text", "text": prompt},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image1}",
-							},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image2}",
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id1,
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id2,
-							}
-					],
-			}
-	],
-	tools=[{"type": "image_generation"}],
-)
-
-# Process the response
-image_generation_calls = [
-	output
-	for output in response.output
-	if output.type == "image_generation_call"
-]
-
-image_data = [output.result for output in image_generation_calls]
-
-if image_data:
-	image_base64 = image_data[0]
-	image_filename = f"edited_image_{int(time.time())}.png"
-	with open(image_filename, "wb") as f:
-			f.write(base64.b64decode(image_base64))
-	print(f"Image saved to {image_filename}")
-else:
-	# If no image is generated, there might be a text response with an explanation
-	text_response = [output.text for output in response.output if hasattr(output, 'text')]
-	if text_response:
-			print("No image generated. Model response:")
-			print("\\n".join(text_response))
-	else:
-			print("No image data found in response.")
-	print("Full response for debugging:")
-	print(response)
-`;break;case r.EMBEDDINGS:t=`
-response = client.embeddings.create(
-	input="${n||"Your string here"}",
-	model="${k}",
-	encoding_format="base64" # or "float"
-)
-
-print(response.data[0].embedding)
-`;break;case r.TRANSCRIPTION:t=`
-# Open the audio file
-audio_file = open("path/to/your/audio/file.mp3", "rb")
-
-# Make the transcription request
-response = client.audio.transcriptions.create(
-	model="${k}",
-	file=audio_file${n?`,
-	prompt="${n.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""}
-)
-
-print(response.text)
-`;break;case r.SPEECH:t=`
-# Make the text-to-speech request
-response = client.audio.speech.create(
-	model="${k}",
-	input="${n||"Your text to convert to speech here"}",
-	voice="${m}"  # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer
-)
-
-# Save the audio to a file
-output_filename = "output_speech.mp3"
-response.stream_to_file(output_filename)
-print(f"Audio saved to {output_filename}")
-
-# Optional: Customize response format and speed
-# response = client.audio.speech.create(
-#     model="${k}",
-#     input="${n||"Your text to convert to speech here"}",
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new file mode 100644
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/2d7-pdxu3q644.js b/litellm/proxy/_experimental/out/_next/static/chunks/2d7-pdxu3q644.js
new file mode 100644
index 00000000000..51c3ac7eae0
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/2d7-pdxu3q644.js
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#dadce0",borderRadius:8,overflow:"hidden"},children:[(0,t.jsxs)("div",{style:{display:"flex",alignItems:"center",justifyContent:"space-between",padding:"10px 16px",backgroundColor:"#f8f9fa",borderBottom:"1px solid #dadce0"},children:[(0,t.jsx)("span",{style:{fontSize:13,color:"#3c4043",fontWeight:500},children:"~/.claude/settings.json"}),(0,t.jsxs)("button",{onClick:()=>u(x,"settings"),style:{display:"flex",alignItems:"center",gap:4,fontSize:12,color:"settings"===c?"#137333":"#1a73e8",background:"none",border:"none",cursor:"pointer",padding:0},children:["settings"===c?(0,t.jsx)(a.Check,{className:"size-3"}):(0,t.jsx)(o.Copy,{className:"size-3"}),"settings"===c?"Copied":"Copy"]})]}),(0,t.jsx)("pre",{style:{margin:0,padding:"14px 16px",fontSize:13,fontFamily:"monospace",color:"#202124",backgroundColor:"#fff"},children:x})]})]})]})}],652272)},306228,e=>{"use strict";let t=(0,e.i(475254).default)("link-2",[["path",{d:"M9 17H7A5 5 0 0 1 7 7h2",key:"8i5ue5"}],["path",{d:"M15 7h2a5 5 0 1 1 0 10h-2",key:"1b9ql8"}],["line",{x1:"8",x2:"16",y1:"12",y2:"12",key:"1jonct"}]]);e.s(["Link2",0,t],306228)},909947,865361,e=>{"use strict";var t,i,r=((t={}).AUDIO_SPEECH="audio_speech",t.AUDIO_TRANSCRIPTION="audio_transcription",t.IMAGE_GENERATION="image_generation",t.VIDEO_GENERATION="video_generation",t.CHAT="chat",t.COMPLETION="completion",t.RESPONSES="responses",t.IMAGE_EDITS="image_edit",t.ANTHROPIC_MESSAGES="anthropic_messages",t.EMBEDDING="embedding",t.REALTIME="realtime",t),a=((i={}).IMAGE="image",i.VIDEO="video",i.CHAT="chat",i.RESPONSES="responses",i.IMAGE_EDITS="image_edits",i.ANTHROPIC_MESSAGES="anthropic_messages",i.EMBEDDINGS="embeddings",i.SPEECH="speech",i.TRANSCRIPTION="transcription",i.A2A_AGENTS="a2a_agents",i.MCP="mcp",i.REALTIME="realtime",i.INTERACTIONS="interactions",i);let o={image_generation:"image",video_generation:"video",chat:"chat",completion:"chat",responses:"responses",image_edit:"image_edits",anthropic_messages:"anthropic_messages",audio_speech:"speech",audio_transcription:"transcription",embedding:"embeddings",realtime:"realtime"};e.s(["EndpointType",()=>a,"ModelMode",()=>r,"getEndpointType",0,e=>Object.values(r).includes(e)?o[e]:"chat"],865361),e.s(["generateCodeSnippet",0,e=>{let t,{apiKeySource:i,accessToken:r,apiKey:o,inputMessage:n,chatHistory:s,selectedTags:l,selectedVectorStores:p,selectedGuardrails:d,selectedPolicies:c,selectedVoice:m,endpointType:u,selectedModel:g,selectedSdk:f,proxySettings:h}=e,_="session"===i?r:o,x=window.location.origin,b=h?.LITELLM_UI_API_DOC_BASE_URL;b&&b.trim()?x=b:h?.PROXY_BASE_URL&&(x=h.PROXY_BASE_URL);let y=n||"Your prompt here",v=y.replace(/\\/g,"\\\\").replace(/"/g,'\\"').replace(/\n/g,"\\n"),j=s.filter(e=>!e.isImage).map(({role:e,content:t})=>({role:e,content:t})),w={};l.length>0&&(w.tags=l),p.length>0&&(w.vector_stores=p),d.length>0&&(w.guardrails=d),c.length>0&&(w.policies=c);let k=g||"your-model-name",C="azure"===f?`import openai
+
+client = openai.AzureOpenAI(
+	api_key="${_||"YOUR_LITELLM_API_KEY"}",
+	azure_endpoint="${x}",
+	api_version="2024-02-01"
+)`:`import openai
+
+client = openai.OpenAI(
+	api_key="${_||"YOUR_LITELLM_API_KEY"}",
+	base_url="${x}"
+)`;switch(u){case a.CHAT:{let e=Object.keys(w).length>0,i="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`,
+    extra_body=${e}`}let r=j.length>0?j:[{role:"user",content:y}];t=`
+import base64
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Example with text only
+response = client.chat.completions.create(
+    model="${k}",
+    messages=${JSON.stringify(r,null,4)}${i}
+)
+
+print(response)
+
+# Example with image or PDF (uncomment and provide file path to use)
+# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
+# response_with_file = client.chat.completions.create(
+#     model="${k}",
+#     messages=[
+#         {
+#             "role": "user",
+#             "content": [
+#                 {
+#                     "type": "text",
+#                     "text": "${v}"
+#                 },
+#                 {
+#                     "type": "image_url",
+#                     "image_url": {
+#                         "url": f"data:image/jpeg;base64,{base64_file}"  # or data:application/pdf;base64,{base64_file}
+#                     }
+#                 }
+#             ]
+#         }
+#     ]${i}
+# )
+# print(response_with_file)
+`;break}case a.RESPONSES:{let e=Object.keys(w).length>0,i="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`,
+    extra_body=${e}`}let r=j.length>0?j:[{role:"user",content:y}];t=`
+import base64
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Example with text only
+response = client.responses.create(
+    model="${k}",
+    input=${JSON.stringify(r,null,4)}${i}
+)
+
+print(response.output_text)
+
+# Example with image or PDF (uncomment and provide file path to use)
+# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
+# response_with_file = client.responses.create(
+#     model="${k}",
+#     input=[
+#         {
+#             "role": "user",
+#             "content": [
+#                 {"type": "input_text", "text": "${v}"},
+#                 {
+#                     "type": "input_image",
+#                     "image_url": f"data:image/jpeg;base64,{base64_file}",  # or data:application/pdf;base64,{base64_file}
+#                 },
+#             ],
+#         }
+#     ]${i}
+# )
+# print(response_with_file.output_text)
+`;break}case a.IMAGE:t="azure"===f?`
+# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI.
+# This snippet uses 'client.images.generate' and will create a new image based on your prompt.
+# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context.
+import os
+import requests
+import json
+import time
+from PIL import Image
+
+result = client.images.generate(
+	model="${k}",
+	prompt="${n}",
+	n=1
+)
+
+json_response = json.loads(result.model_dump_json())
+
+# Set the directory for the stored image
+image_dir = os.path.join(os.curdir, 'images')
+
+# If the directory doesn't exist, create it
+if not os.path.isdir(image_dir):
+	os.mkdir(image_dir)
+
+# Initialize the image path
+image_filename = f"generated_image_{int(time.time())}.png"
+image_path = os.path.join(image_dir, image_filename)
+
+try:
+	# Retrieve the generated image
+	if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"):
+			image_url = json_response["data"][0]["url"]
+			generated_image = requests.get(image_url).content
+			with open(image_path, "wb") as image_file:
+					image_file.write(generated_image)
+
+			print(f"Image saved to {image_path}")
+			# Display the image
+			image = Image.open(image_path)
+			image.show()
+	else:
+			print("Could not find image URL in response.")
+			print("Full response:", json_response)
+except Exception as e:
+	print(f"An error occurred: {e}")
+	print("Full response:", json_response)
+`:`
+import base64
+import os
+import time
+import json
+from PIL import Image
+import requests
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+	with open(image_path, "rb") as image_file:
+			return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Helper function to create a file (simplified for this example)
+def create_file(image_path):
+	# In a real implementation, this would upload the file to OpenAI
+	# For this example, we'll just return a placeholder ID
+	return f"file_{os.path.basename(image_path).replace('.', '_')}"
+
+# The prompt entered by the user
+prompt = "${v}"
+
+# Encode images to base64
+base64_image1 = encode_image("body-lotion.png")
+base64_image2 = encode_image("soap.png")
+
+# Create file IDs
+file_id1 = create_file("body-lotion.png")
+file_id2 = create_file("incense-kit.png")
+
+response = client.responses.create(
+	model="${k}",
+	input=[
+			{
+					"role": "user",
+					"content": [
+							{"type": "input_text", "text": prompt},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image1}",
+							},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image2}",
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id1,
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id2,
+							}
+					],
+			}
+	],
+	tools=[{"type": "image_generation"}],
+)
+
+# Process the response
+image_generation_calls = [
+	output
+	for output in response.output
+	if output.type == "image_generation_call"
+]
+
+image_data = [output.result for output in image_generation_calls]
+
+if image_data:
+	image_base64 = image_data[0]
+	image_filename = f"edited_image_{int(time.time())}.png"
+	with open(image_filename, "wb") as f:
+			f.write(base64.b64decode(image_base64))
+	print(f"Image saved to {image_filename}")
+else:
+	# If no image is generated, there might be a text response with an explanation
+	text_response = [output.text for output in response.output if hasattr(output, 'text')]
+	if text_response:
+			print("No image generated. Model response:")
+			print("\\n".join(text_response))
+	else:
+			print("No image data found in response.")
+	print("Full response for debugging:")
+	print(response)
+`;break;case a.IMAGE_EDITS:t="azure"===f?`
+import base64
+import os
+import time
+import json
+from PIL import Image
+import requests
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+	with open(image_path, "rb") as image_file:
+			return base64.b64encode(image_file.read()).decode('utf-8')
+
+# The prompt entered by the user
+prompt = "${v}"
+
+# Encode images to base64
+base64_image1 = encode_image("body-lotion.png")
+base64_image2 = encode_image("soap.png")
+
+# Create file IDs
+file_id1 = create_file("body-lotion.png")
+file_id2 = create_file("incense-kit.png")
+
+response = client.responses.create(
+	model="${k}",
+	input=[
+			{
+					"role": "user",
+					"content": [
+							{"type": "input_text", "text": prompt},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image1}",
+							},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image2}",
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id1,
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id2,
+							}
+					],
+			}
+	],
+	tools=[{"type": "image_generation"}],
+)
+
+# Process the response
+image_generation_calls = [
+	output
+	for output in response.output
+	if output.type == "image_generation_call"
+]
+
+image_data = [output.result for output in image_generation_calls]
+
+if image_data:
+	image_base64 = image_data[0]
+	image_filename = f"edited_image_{int(time.time())}.png"
+	with open(image_filename, "wb") as f:
+			f.write(base64.b64decode(image_base64))
+	print(f"Image saved to {image_filename}")
+else:
+	# If no image is generated, there might be a text response with an explanation
+	text_response = [output.text for output in response.output if hasattr(output, 'text')]
+	if text_response:
+			print("No image generated. Model response:")
+			print("\\n".join(text_response))
+	else:
+			print("No image data found in response.")
+	print("Full response for debugging:")
+	print(response)
+`:`
+import base64
+import os
+import time
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+	with open(image_path, "rb") as image_file:
+			return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Helper function to create a file (simplified for this example)
+def create_file(image_path):
+	# In a real implementation, this would upload the file to OpenAI
+	# For this example, we'll just return a placeholder ID
+	return f"file_{os.path.basename(image_path).replace('.', '_')}"
+
+# The prompt entered by the user
+prompt = "${v}"
+
+# Encode images to base64
+base64_image1 = encode_image("body-lotion.png")
+base64_image2 = encode_image("soap.png")
+
+# Create file IDs
+file_id1 = create_file("body-lotion.png")
+file_id2 = create_file("incense-kit.png")
+
+response = client.responses.create(
+	model="${k}",
+	input=[
+			{
+					"role": "user",
+					"content": [
+							{"type": "input_text", "text": prompt},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image1}",
+							},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image2}",
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id1,
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id2,
+							}
+					],
+			}
+	],
+	tools=[{"type": "image_generation"}],
+)
+
+# Process the response
+image_generation_calls = [
+	output
+	for output in response.output
+	if output.type == "image_generation_call"
+]
+
+image_data = [output.result for output in image_generation_calls]
+
+if image_data:
+	image_base64 = image_data[0]
+	image_filename = f"edited_image_{int(time.time())}.png"
+	with open(image_filename, "wb") as f:
+			f.write(base64.b64decode(image_base64))
+	print(f"Image saved to {image_filename}")
+else:
+	# If no image is generated, there might be a text response with an explanation
+	text_response = [output.text for output in response.output if hasattr(output, 'text')]
+	if text_response:
+			print("No image generated. Model response:")
+			print("\\n".join(text_response))
+	else:
+			print("No image data found in response.")
+	print("Full response for debugging:")
+	print(response)
+`;break;case a.EMBEDDINGS:t=`
+response = client.embeddings.create(
+	input="${n||"Your string here"}",
+	model="${k}",
+	encoding_format="base64" # or "float"
+)
+
+print(response.data[0].embedding)
+`;break;case a.TRANSCRIPTION:t=`
+# Open the audio file
+audio_file = open("path/to/your/audio/file.mp3", "rb")
+
+# Make the transcription request
+response = client.audio.transcriptions.create(
+	model="${k}",
+	file=audio_file${n?`,
+	prompt="${n.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""}
+)
+
+print(response.text)
+`;break;case a.SPEECH:t=`
+# Make the text-to-speech request
+response = client.audio.speech.create(
+	model="${k}",
+	input="${n||"Your text to convert to speech here"}",
+	voice="${m}"  # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer
+)
+
+# Save the audio to a file
+output_filename = "output_speech.mp3"
+response.stream_to_file(output_filename)
+print(f"Audio saved to {output_filename}")
+
+# Optional: Customize response format and speed
+# response = client.audio.speech.create(
+#     model="${k}",
+#     input="${n||"Your text to convert to speech here"}",
+#     voice="alloy",
+#     response_format="mp3",  # Options: mp3, opus, aac, flac, wav, pcm
+#     speed=1.0  # Range: 0.25 to 4.0
+# )
+# response.stream_to_file("output_speech.mp3")
+`;break;default:t="\n# Code generation for this endpoint is not implemented yet."}return`${C}
+${t}`}],909947)},157058,e=>{"use strict";var t=e.i(843476),i=e.i(934879),r=e.i(976883),a=e.i(135214),o=e.i(708347);e.s(["default",0,function(){let{accessToken:e,userRole:n,premiumUser:s}=(0,a.default)();return(0,o.isAdminRole)(n)?(0,t.jsx)(i.default,{accessToken:e,publicPage:!1,premiumUser:s,userRole:n}):(0,t.jsx)(r.default,{accessToken:e,isEmbedded:!0})}])}]);
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/2g80gdfeub3nu.js b/litellm/proxy/_experimental/out/_next/static/chunks/2g80gdfeub3nu.js
deleted file mode 100644
index 1f06055aeb3..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/2g80gdfeub3nu.js
+++ /dev/null
@@ -1 +0,0 @@
-(globalThis.TURBOPACK||(globalThis.TURBOPACK=[])).push(["object"==typeof document?document.currentScript:void 0,102616,e=>{"use strict";var t=e.i(843476),l=e.i(271645),s=e.i(439573),a=e.i(519455),r=e.i(677572),i=e.i(888259),n=e.i(952571),o=e.i(89128),d=e.i(37727),c=e.i(708347),m=e.i(332102);e.i(707701);var x=e.i(807235),p=e.i(541071),u=e.i(788699),h=e.i(727612),g=e.i(494862);e.i(622826);var f=e.i(200208),y=e.i(997422),j=e.i(112179),b=e.i(755146),v=e.i(115504);let N="Config policies are defined in the config file and cannot be edited or deleted from the dashboard.";function w({guardrails:e,tone:l}){return 0===e.length?(0,t.jsx)("span",{className:"text-muted-foreground",children:"-"}):(0,t.jsxs)("div",{className:"flex flex-wrap items-center gap-1",children:[e.slice(0,2).map(e=>(0,t.jsx)(j.StatusBadge,{tone:l,label:e},e)),e.length>2&&(0,t.jsx)(j.StatusBadge,{tone:"neutral",label:`+${e.length-2}`,tooltip:e.slice(2).join(", ")})]})}function S({policy:e,onEditClick:l,onDeleteClick:s}){let 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\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/2hicgq-mjp8vy.css b/litellm/proxy/_experimental/out/_next/static/chunks/2hicgq-mjp8vy.css
new file mode 100644
index 00000000000..17274f9f331
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/2hicgq-mjp8vy.css
@@ -0,0 +1 @@
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auto}.grid-cols-\[80px_minmax\(0\,1fr\)\]{grid-template-columns:80px minmax(0,1fr)}.grid-cols-\[160px_minmax\(0\,1fr\)\]{grid-template-columns:160px minmax(0,1fr)}.grid-cols-\[auto\]{grid-template-columns:auto}.grid-cols-\[auto_1fr\]{grid-template-columns:auto 1fr}.grid-cols-\[auto_minmax\(0\,1fr\)\]{grid-template-columns:auto minmax(0,1fr)}.grid-cols-\[max-content_1fr\]{grid-template-columns:max-content 1fr}.grid-cols-\[minmax\(0\,14rem\)_minmax\(0\,1fr\)\]{grid-template-columns:minmax(0,14rem) minmax(0,1fr)}.grid-cols-\[repeat\(auto-fill\,minmax\(220px\,1fr\)\)\]{grid-template-columns:repeat(auto-fill,minmax(220px,1fr))}.grid-cols-\[repeat\(auto-fit\,minmax\(7rem\,1fr\)\)\]{grid-template-columns:repeat(auto-fit,minmax(7rem,1fr))}.grid-rows-\[auto_1fr\]{grid-template-rows:auto 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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/2hwi7ji174tux.js b/litellm/proxy/_experimental/out/_next/static/chunks/2hwi7ji174tux.js
deleted file mode 100644
index 1dcc9d46a6f..00000000000
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new file mode 100644
index 00000000000..63bfe5834f1
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new file mode 100644
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new file mode 100644
index 00000000000..1ef2de9fb08
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index 84478b7d150..00000000000
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deleted file mode 100644
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deleted file mode 100644
index 5d47803106a..00000000000
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/12k2y8birirx1.js b/litellm/proxy/_experimental/out/_next/static/chunks/2oi4g_kk8bnwv.js
similarity index 85%
rename from litellm/proxy/_experimental/out/_next/static/chunks/12k2y8birirx1.js
rename to litellm/proxy/_experimental/out/_next/static/chunks/2oi4g_kk8bnwv.js
index b76176f2975..fcdbf53e6f7 100644
--- a/litellm/proxy/_experimental/out/_next/static/chunks/12k2y8birirx1.js
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/2oi4g_kk8bnwv.js
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/2ovw2fvak1ez5.js b/litellm/proxy/_experimental/out/_next/static/chunks/2ovw2fvak1ez5.js
deleted file mode 100644
index e103ac7c12e..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/2ovw2fvak1ez5.js
+++ /dev/null
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n={image_generation:"image",video_generation:"video",chat:"chat",responses:"responses",image_edit:"image_edits",anthropic_messages:"anthropic_messages",audio_speech:"speech",audio_transcription:"transcription",embedding:"embeddings",realtime:"realtime"};e.s(["EndpointType",()=>a,"ModelMode",()=>r,"getEndpointType",0,e=>Object.values(r).includes(e)?n[e]:"chat"],865361),e.s(["generateCodeSnippet",0,e=>{let t,{apiKeySource:i,accessToken:r,apiKey:n,inputMessage:o,chatHistory:s,selectedTags:l,selectedVectorStores:p,selectedGuardrails:d,selectedPolicies:c,selectedVoice:u,endpointType:m,selectedModel:g,selectedSdk:f,proxySettings:h}=e,_="session"===i?r:n,x=window.location.origin,b=h?.LITELLM_UI_API_DOC_BASE_URL;b&&b.trim()?x=b:h?.PROXY_BASE_URL&&(x=h.PROXY_BASE_URL);let y=o||"Your prompt here",v=y.replace(/\\/g,"\\\\").replace(/"/g,'\\"').replace(/\n/g,"\\n"),w=s.filter(e=>!e.isImage).map(({role:e,content:t})=>({role:e,content:t})),j={};l.length>0&&(j.tags=l),p.length>0&&(j.vector_stores=p),d.length>0&&(j.guardrails=d),c.length>0&&(j.policies=c);let k=g||"your-model-name",I="azure"===f?`import openai
-
-client = openai.AzureOpenAI(
-	api_key="${_||"YOUR_LITELLM_API_KEY"}",
-	azure_endpoint="${x}",
-	api_version="2024-02-01"
-)`:`import openai
-
-client = openai.OpenAI(
-	api_key="${_||"YOUR_LITELLM_API_KEY"}",
-	base_url="${x}"
-)`;switch(m){case a.CHAT:{let e=Object.keys(j).length>0,i="";if(e){let e=JSON.stringify({metadata:j},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`,
-    extra_body=${e}`}let r=w.length>0?w:[{role:"user",content:y}];t=`
-import base64
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Example with text only
-response = client.chat.completions.create(
-    model="${k}",
-    messages=${JSON.stringify(r,null,4)}${i}
-)
-
-print(response)
-
-# Example with image or PDF (uncomment and provide file path to use)
-# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
-# response_with_file = client.chat.completions.create(
-#     model="${k}",
-#     messages=[
-#         {
-#             "role": "user",
-#             "content": [
-#                 {
-#                     "type": "text",
-#                     "text": "${v}"
-#                 },
-#                 {
-#                     "type": "image_url",
-#                     "image_url": {
-#                         "url": f"data:image/jpeg;base64,{base64_file}"  # or data:application/pdf;base64,{base64_file}
-#                     }
-#                 }
-#             ]
-#         }
-#     ]${i}
-# )
-# print(response_with_file)
-`;break}case a.RESPONSES:{let e=Object.keys(j).length>0,i="";if(e){let e=JSON.stringify({metadata:j},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`,
-    extra_body=${e}`}let r=w.length>0?w:[{role:"user",content:y}];t=`
-import base64
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Example with text only
-response = client.responses.create(
-    model="${k}",
-    input=${JSON.stringify(r,null,4)}${i}
-)
-
-print(response.output_text)
-
-# Example with image or PDF (uncomment and provide file path to use)
-# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
-# response_with_file = client.responses.create(
-#     model="${k}",
-#     input=[
-#         {
-#             "role": "user",
-#             "content": [
-#                 {"type": "input_text", "text": "${v}"},
-#                 {
-#                     "type": "input_image",
-#                     "image_url": f"data:image/jpeg;base64,{base64_file}",  # or data:application/pdf;base64,{base64_file}
-#                 },
-#             ],
-#         }
-#     ]${i}
-# )
-# print(response_with_file.output_text)
-`;break}case a.IMAGE:t="azure"===f?`
-# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI.
-# This snippet uses 'client.images.generate' and will create a new image based on your prompt.
-# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context.
-import os
-import requests
-import json
-import time
-from PIL import Image
-
-result = client.images.generate(
-	model="${k}",
-	prompt="${o}",
-	n=1
-)
-
-json_response = json.loads(result.model_dump_json())
-
-# Set the directory for the stored image
-image_dir = os.path.join(os.curdir, 'images')
-
-# If the directory doesn't exist, create it
-if not os.path.isdir(image_dir):
-	os.mkdir(image_dir)
-
-# Initialize the image path
-image_filename = f"generated_image_{int(time.time())}.png"
-image_path = os.path.join(image_dir, image_filename)
-
-try:
-	# Retrieve the generated image
-	if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"):
-			image_url = json_response["data"][0]["url"]
-			generated_image = requests.get(image_url).content
-			with open(image_path, "wb") as image_file:
-					image_file.write(generated_image)
-
-			print(f"Image saved to {image_path}")
-			# Display the image
-			image = Image.open(image_path)
-			image.show()
-	else:
-			print("Could not find image URL in response.")
-			print("Full response:", json_response)
-except Exception as e:
-	print(f"An error occurred: {e}")
-	print("Full response:", json_response)
-`:`
-import base64
-import os
-import time
-import json
-from PIL import Image
-import requests
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-	with open(image_path, "rb") as image_file:
-			return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Helper function to create a file (simplified for this example)
-def create_file(image_path):
-	# In a real implementation, this would upload the file to OpenAI
-	# For this example, we'll just return a placeholder ID
-	return f"file_{os.path.basename(image_path).replace('.', '_')}"
-
-# The prompt entered by the user
-prompt = "${v}"
-
-# Encode images to base64
-base64_image1 = encode_image("body-lotion.png")
-base64_image2 = encode_image("soap.png")
-
-# Create file IDs
-file_id1 = create_file("body-lotion.png")
-file_id2 = create_file("incense-kit.png")
-
-response = client.responses.create(
-	model="${k}",
-	input=[
-			{
-					"role": "user",
-					"content": [
-							{"type": "input_text", "text": prompt},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image1}",
-							},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image2}",
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id1,
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id2,
-							}
-					],
-			}
-	],
-	tools=[{"type": "image_generation"}],
-)
-
-# Process the response
-image_generation_calls = [
-	output
-	for output in response.output
-	if output.type == "image_generation_call"
-]
-
-image_data = [output.result for output in image_generation_calls]
-
-if image_data:
-	image_base64 = image_data[0]
-	image_filename = f"edited_image_{int(time.time())}.png"
-	with open(image_filename, "wb") as f:
-			f.write(base64.b64decode(image_base64))
-	print(f"Image saved to {image_filename}")
-else:
-	# If no image is generated, there might be a text response with an explanation
-	text_response = [output.text for output in response.output if hasattr(output, 'text')]
-	if text_response:
-			print("No image generated. Model response:")
-			print("\\n".join(text_response))
-	else:
-			print("No image data found in response.")
-	print("Full response for debugging:")
-	print(response)
-`;break;case a.IMAGE_EDITS:t="azure"===f?`
-import base64
-import os
-import time
-import json
-from PIL import Image
-import requests
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-	with open(image_path, "rb") as image_file:
-			return base64.b64encode(image_file.read()).decode('utf-8')
-
-# The prompt entered by the user
-prompt = "${v}"
-
-# Encode images to base64
-base64_image1 = encode_image("body-lotion.png")
-base64_image2 = encode_image("soap.png")
-
-# Create file IDs
-file_id1 = create_file("body-lotion.png")
-file_id2 = create_file("incense-kit.png")
-
-response = client.responses.create(
-	model="${k}",
-	input=[
-			{
-					"role": "user",
-					"content": [
-							{"type": "input_text", "text": prompt},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image1}",
-							},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image2}",
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id1,
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id2,
-							}
-					],
-			}
-	],
-	tools=[{"type": "image_generation"}],
-)
-
-# Process the response
-image_generation_calls = [
-	output
-	for output in response.output
-	if output.type == "image_generation_call"
-]
-
-image_data = [output.result for output in image_generation_calls]
-
-if image_data:
-	image_base64 = image_data[0]
-	image_filename = f"edited_image_{int(time.time())}.png"
-	with open(image_filename, "wb") as f:
-			f.write(base64.b64decode(image_base64))
-	print(f"Image saved to {image_filename}")
-else:
-	# If no image is generated, there might be a text response with an explanation
-	text_response = [output.text for output in response.output if hasattr(output, 'text')]
-	if text_response:
-			print("No image generated. Model response:")
-			print("\\n".join(text_response))
-	else:
-			print("No image data found in response.")
-	print("Full response for debugging:")
-	print(response)
-`:`
-import base64
-import os
-import time
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-	with open(image_path, "rb") as image_file:
-			return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Helper function to create a file (simplified for this example)
-def create_file(image_path):
-	# In a real implementation, this would upload the file to OpenAI
-	# For this example, we'll just return a placeholder ID
-	return f"file_{os.path.basename(image_path).replace('.', '_')}"
-
-# The prompt entered by the user
-prompt = "${v}"
-
-# Encode images to base64
-base64_image1 = encode_image("body-lotion.png")
-base64_image2 = encode_image("soap.png")
-
-# Create file IDs
-file_id1 = create_file("body-lotion.png")
-file_id2 = create_file("incense-kit.png")
-
-response = client.responses.create(
-	model="${k}",
-	input=[
-			{
-					"role": "user",
-					"content": [
-							{"type": "input_text", "text": prompt},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image1}",
-							},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image2}",
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id1,
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id2,
-							}
-					],
-			}
-	],
-	tools=[{"type": "image_generation"}],
-)
-
-# Process the response
-image_generation_calls = [
-	output
-	for output in response.output
-	if output.type == "image_generation_call"
-]
-
-image_data = [output.result for output in image_generation_calls]
-
-if image_data:
-	image_base64 = image_data[0]
-	image_filename = f"edited_image_{int(time.time())}.png"
-	with open(image_filename, "wb") as f:
-			f.write(base64.b64decode(image_base64))
-	print(f"Image saved to {image_filename}")
-else:
-	# If no image is generated, there might be a text response with an explanation
-	text_response = [output.text for output in response.output if hasattr(output, 'text')]
-	if text_response:
-			print("No image generated. Model response:")
-			print("\\n".join(text_response))
-	else:
-			print("No image data found in response.")
-	print("Full response for debugging:")
-	print(response)
-`;break;case a.EMBEDDINGS:t=`
-response = client.embeddings.create(
-	input="${o||"Your string here"}",
-	model="${k}",
-	encoding_format="base64" # or "float"
-)
-
-print(response.data[0].embedding)
-`;break;case a.TRANSCRIPTION:t=`
-# Open the audio file
-audio_file = open("path/to/your/audio/file.mp3", "rb")
-
-# Make the transcription request
-response = client.audio.transcriptions.create(
-	model="${k}",
-	file=audio_file${o?`,
-	prompt="${o.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""}
-)
-
-print(response.text)
-`;break;case a.SPEECH:t=`
-# Make the text-to-speech request
-response = client.audio.speech.create(
-	model="${k}",
-	input="${o||"Your text to convert to speech here"}",
-	voice="${u}"  # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer
-)
-
-# Save the audio to a file
-output_filename = "output_speech.mp3"
-response.stream_to_file(output_filename)
-print(f"Audio saved to {output_filename}")
-
-# Optional: Customize response format and speed
-# response = client.audio.speech.create(
-#     model="${k}",
-#     input="${o||"Your text to convert to speech here"}",
-#     voice="alloy",
-#     response_format="mp3",  # Options: mp3, opus, aac, flac, wav, pcm
-#     speed=1.0  # Range: 0.25 to 4.0
-# )
-# response.stream_to_file("output_speech.mp3")
-`;break;default:t="\n# Code generation for this endpoint is not implemented yet."}return`${I}
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new file mode 100644
index 00000000000..d9dcd9d3c03
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+curl -X POST --location '<your_proxy_base_url>/end_user/new' \\
+
+-H 'Authorization: Bearer <your-master-key>' \\
+
+-H 'Content-Type: application/json' \\
+
+-d '{"user_id": "my-customer-id', "budget_id": "<BUDGET_ID>"}' # 👈 KEY CHANGE
+
+`,eD=`
+curl -X POST --location '<your_proxy_base_url>/chat/completions' \\
+
+-H 'Authorization: Bearer <your-master-key>' \\
+
+-H 'Content-Type: application/json' \\
+
+-d '{
+  "model": "gpt-3.5-turbo',
+  "messages":[{"role": "user", "content": "Hey, how's it going?"}],
+  "user": "my-customer-id"
+}' # 👈 KEY CHANGE
+
+`,eM=`from openai import OpenAI
+client = OpenAI(
+  base_url="<your_proxy_base_url>",
+  api_key="<your_proxy_key>"
+)
+
+completion = client.chat.completions.create(
+  model="gpt-3.5-turbo",
+  messages=[
+    {"role": "system", "content": "You are a helpful assistant."},
+    {"role": "user", "content": "Hello!"}
+  ],
+  user="my-customer-id"
+)
+
+print(completion.choices[0].message)`;var eL=e.i(708347);let eF=({accessToken:e})=>{let x=(0,r.useSyntaxTheme)(l.prism),[C,T]=(0,s.useState)(!1),[_,S]=(0,s.useState)(!1),[E,N]=(0,s.useState)(null),[I,M]=(0,s.useState)(!1),{userRole:L}=(0,p.default)(),F=(0,eL.isProxyAdminRole)(L??""),A=(()=>{let{accessToken:e}=(0,p.default)(),t=(0,s.useCallback)((t,i)=>v.apiClient.get("/management/v1/budgets",{accessToken:e,query:t,signal:i}),[e]);return function(e){let{queryKey:t,fetchPage:i,serializeFilters:n,defaultSorting:a,defaultPageSize:l,enabled:r}=e,[o,u]=(0,s.useState)(a),[d,c]=(0,s.useState)({pageIndex:0,pageSize:l}),[g,h]=(0,s.useState)([]),[m,b]=(0,s.useState)(""),[p]=(0,f.useDebouncedValue)(m,{wait:j.DEBOUNCE_WAIT_MS}),v=(0,s.useMemo)(()=>{let e=o.map(e=>e.desc?`-${e.id}`:e.id).join(","),t=p.trim();return{page:d.pageIndex+1,page_size:d.pageSize,...""===e?{}:{sort:e},...""===t?{}:{q:t},...n(g)}},[o,d.pageIndex,d.pageSize,p,g,n]),x={queryKey:[...t,v],queryFn:({signal:e})=>i(v,e),enabled:r,placeholderData:e=>e},{data:C,isLoading:T,isFetching:_,error:S,refetch:E}=(0,y.useQuery)(x),N=(0,s.useCallback)(()=>c(e=>({...e,pageIndex:0})),[]),I=(0,s.useCallback)(e=>{u(e),N()},[N]),k=(0,s.useCallback)(e=>{h(e),N()},[N]),w=(0,s.useCallback)(e=>{b(e),N()},[N]),D=(0,s.useCallback)(()=>{E()},[E]);return{rows:(0,s.useMemo)(()=>C?.data??[],[C]),rowCount:C?.meta.total_count??0,isLoading:T,isFetching:_,error:S,refetch:D,sorting:o,onSortingChange:I,pagination:d,onPaginationChange:c,columnFilters:g,onColumnFiltersChange:k,searchValue:m,onSearchChange:w}}({queryKey:w.lists(),fetchPage:t,serializeFilters:k,defaultSorting:D,defaultPageSize:50,enabled:!!e})})(),O=(()=>{let{accessToken:e}=(0,p.default)(),t=(0,b.useQueryClient)();return(0,m.useMutation)({mutationFn:async t=>{if(!e)throw Error("Access token is required");return(0,v.budgetDeleteCall)(e,t)},onSuccess:()=>{t.invalidateQueries({queryKey:w.all})}})})(),P=(0,s.useCallback)(t=>{null!=e&&(N(t),S(!0))},[e]),B=(0,s.useCallback)(e=>{N(e),M(!0)},[]),z=async()=>{if(E&&null!=e)try{await O.mutateAsync(E.budget_id),h.toast.success("Budget deleted.")}catch(e){console.error("Error deleting budget:",e),h.toast.fromError("Failed to delete budget")}finally{M(!1),N(null)}};return(0,t.jsxs)("div",{className:"flex h-full flex-col gap-4 p-6 px-12",children:[(0,t.jsx)(o.LegacyPageHeader,{icon:(0,t.jsx)(n.Wallet,{className:"size-5"}),title:"Budgets",subtitle:"Spend, TPM and RPM limits you can assign to customers."}),(0,t.jsxs)(c.Tabs,{defaultValue:"budgets",className:"min-h-0 flex-1 gap-0",children:[(0,t.jsxs)("div",{className:"flex items-center gap-4 border-b border-border",children:[F&&(0,t.jsxs)(t.Fragment,{children:[(0,t.jsxs)(d.Button,{onClick:()=>T(!0),children:[(0,t.jsx)(i.Plus,{className:"size-4"}),"Create Budget"]}),(0,t.jsx)(u.ToolbarSeparator,{className:"h-6"})]}),(0,t.jsxs)(c.TabsList,{variant:"line",children:[(0,t.jsx)(c.TabsTrigger,{value:"budgets",className:"flex-none px-4",children:"Budgets"}),(0,t.jsx)(c.TabsTrigger,{value:"examples",className:"flex-none px-4",children:"Examples"})]})]}),(0,t.jsx)(c.TabsContent,{value:"budgets",className:"flex min-h-0 flex-1 flex-col",keepMounted:!0,children:(0,t.jsxs)("div",{className:"flex min-h-0 flex-1 flex-col pt-6",children:[(0,t.jsx)(K,{isModalVisible:C,setIsModalVisible:T}),E&&(0,t.jsx)(ek,{isModalVisible:_,setIsModalVisible:S,existingBudget:E}),(0,t.jsx)(eS,{list:A,canModify:F,onEditClick:P,onDeleteClick:B}),(0,t.jsx)(g.default,{isOpen:I,title:"Delete Budget?",message:"Are you sure you want to delete this budget? 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\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/2pt1udsvv_-w3.js b/litellm/proxy/_experimental/out/_next/static/chunks/2pt1udsvv_-w3.js
deleted file mode 100644
index 9f273b6fbe8..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/2pt1udsvv_-w3.js
+++ /dev/null
@@ -1,2 +0,0 @@
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/15fw6jrr70znm.js b/litellm/proxy/_experimental/out/_next/static/chunks/2qapx8_h7ir44.js
similarity index 81%
rename from litellm/proxy/_experimental/out/_next/static/chunks/15fw6jrr70znm.js
rename to litellm/proxy/_experimental/out/_next/static/chunks/2qapx8_h7ir44.js
index 152bb05e716..bc4a9c13a90 100644
--- a/litellm/proxy/_experimental/out/_next/static/chunks/15fw6jrr70znm.js
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/2qapx8_h7ir44.js
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deleted file mode 100644
index 771b8184ad8..00000000000
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deleted file mode 100644
index 953300a5c8f..00000000000
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+++ /dev/null
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new file mode 100644
index 00000000000..d829084fec7
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/2tj11rqd6xkb4.js
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/2tqkirw-qhcfg.js b/litellm/proxy/_experimental/out/_next/static/chunks/2tqkirw-qhcfg.js
new file mode 100644
index 00000000000..590b1930902
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+++ b/litellm/proxy/_experimental/out/_next/static/chunks/2tqkirw-qhcfg.js
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t,i,a=((t={}).AUDIO_SPEECH="audio_speech",t.AUDIO_TRANSCRIPTION="audio_transcription",t.IMAGE_GENERATION="image_generation",t.VIDEO_GENERATION="video_generation",t.CHAT="chat",t.RESPONSES="responses",t.IMAGE_EDITS="image_edit",t.ANTHROPIC_MESSAGES="anthropic_messages",t.EMBEDDING="embedding",t.REALTIME="realtime",t),r=((i={}).IMAGE="image",i.VIDEO="video",i.CHAT="chat",i.RESPONSES="responses",i.IMAGE_EDITS="image_edits",i.ANTHROPIC_MESSAGES="anthropic_messages",i.EMBEDDINGS="embeddings",i.SPEECH="speech",i.TRANSCRIPTION="transcription",i.A2A_AGENTS="a2a_agents",i.MCP="mcp",i.REALTIME="realtime",i.INTERACTIONS="interactions",i);let s={image_generation:"image",video_generation:"video",chat:"chat",responses:"responses",image_edit:"image_edits",anthropic_messages:"anthropic_messages",audio_speech:"speech",audio_transcription:"transcription",embedding:"embeddings",realtime:"realtime"};e.s(["EndpointType",()=>r,"ModelMode",()=>a,"getEndpointType",0,e=>Object.values(a).includes(e)?s[e]:"chat"],865361),e.s(["generateCodeSnippet",0,e=>{let t,{apiKeySource:i,accessToken:a,apiKey:s,inputMessage:n,chatHistory:o,selectedTags:l,selectedVectorStores:d,selectedGuardrails:c,selectedPolicies:p,selectedVoice:m,endpointType:u,selectedModel:g,selectedSdk:h,proxySettings:f}=e,x="session"===i?a:s,b=window.location.origin,_=f?.LITELLM_UI_API_DOC_BASE_URL;_&&_.trim()?b=_:f?.PROXY_BASE_URL&&(b=f.PROXY_BASE_URL);let y=n||"Your prompt here",j=y.replace(/\\/g,"\\\\").replace(/"/g,'\\"').replace(/\n/g,"\\n"),w=o.filter(e=>!e.isImage).map(({role:e,content:t})=>({role:e,content:t})),v={};l.length>0&&(v.tags=l),d.length>0&&(v.vector_stores=d),c.length>0&&(v.guardrails=c),p.length>0&&(v.policies=p);let k=g||"your-model-name",N="azure"===h?`import openai
-
-client = openai.AzureOpenAI(
-	api_key="${x||"YOUR_LITELLM_API_KEY"}",
-	azure_endpoint="${b}",
-	api_version="2024-02-01"
-)`:`import openai
-
-client = openai.OpenAI(
-	api_key="${x||"YOUR_LITELLM_API_KEY"}",
-	base_url="${b}"
-)`;switch(u){case r.CHAT:{let e=Object.keys(v).length>0,i="";if(e){let e=JSON.stringify({metadata:v},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`,
-    extra_body=${e}`}let a=w.length>0?w:[{role:"user",content:y}];t=`
-import base64
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Example with text only
-response = client.chat.completions.create(
-    model="${k}",
-    messages=${JSON.stringify(a,null,4)}${i}
-)
-
-print(response)
-
-# Example with image or PDF (uncomment and provide file path to use)
-# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
-# response_with_file = client.chat.completions.create(
-#     model="${k}",
-#     messages=[
-#         {
-#             "role": "user",
-#             "content": [
-#                 {
-#                     "type": "text",
-#                     "text": "${j}"
-#                 },
-#                 {
-#                     "type": "image_url",
-#                     "image_url": {
-#                         "url": f"data:image/jpeg;base64,{base64_file}"  # or data:application/pdf;base64,{base64_file}
-#                     }
-#                 }
-#             ]
-#         }
-#     ]${i}
-# )
-# print(response_with_file)
-`;break}case r.RESPONSES:{let e=Object.keys(v).length>0,i="";if(e){let e=JSON.stringify({metadata:v},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`,
-    extra_body=${e}`}let a=w.length>0?w:[{role:"user",content:y}];t=`
-import base64
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Example with text only
-response = client.responses.create(
-    model="${k}",
-    input=${JSON.stringify(a,null,4)}${i}
-)
-
-print(response.output_text)
-
-# Example with image or PDF (uncomment and provide file path to use)
-# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
-# response_with_file = client.responses.create(
-#     model="${k}",
-#     input=[
-#         {
-#             "role": "user",
-#             "content": [
-#                 {"type": "input_text", "text": "${j}"},
-#                 {
-#                     "type": "input_image",
-#                     "image_url": f"data:image/jpeg;base64,{base64_file}",  # or data:application/pdf;base64,{base64_file}
-#                 },
-#             ],
-#         }
-#     ]${i}
-# )
-# print(response_with_file.output_text)
-`;break}case r.IMAGE:t="azure"===h?`
-# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI.
-# This snippet uses 'client.images.generate' and will create a new image based on your prompt.
-# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context.
-import os
-import requests
-import json
-import time
-from PIL import Image
-
-result = client.images.generate(
-	model="${k}",
-	prompt="${n}",
-	n=1
-)
-
-json_response = json.loads(result.model_dump_json())
-
-# Set the directory for the stored image
-image_dir = os.path.join(os.curdir, 'images')
-
-# If the directory doesn't exist, create it
-if not os.path.isdir(image_dir):
-	os.mkdir(image_dir)
-
-# Initialize the image path
-image_filename = f"generated_image_{int(time.time())}.png"
-image_path = os.path.join(image_dir, image_filename)
-
-try:
-	# Retrieve the generated image
-	if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"):
-			image_url = json_response["data"][0]["url"]
-			generated_image = requests.get(image_url).content
-			with open(image_path, "wb") as image_file:
-					image_file.write(generated_image)
-
-			print(f"Image saved to {image_path}")
-			# Display the image
-			image = Image.open(image_path)
-			image.show()
-	else:
-			print("Could not find image URL in response.")
-			print("Full response:", json_response)
-except Exception as e:
-	print(f"An error occurred: {e}")
-	print("Full response:", json_response)
-`:`
-import base64
-import os
-import time
-import json
-from PIL import Image
-import requests
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-	with open(image_path, "rb") as image_file:
-			return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Helper function to create a file (simplified for this example)
-def create_file(image_path):
-	# In a real implementation, this would upload the file to OpenAI
-	# For this example, we'll just return a placeholder ID
-	return f"file_{os.path.basename(image_path).replace('.', '_')}"
-
-# The prompt entered by the user
-prompt = "${j}"
-
-# Encode images to base64
-base64_image1 = encode_image("body-lotion.png")
-base64_image2 = encode_image("soap.png")
-
-# Create file IDs
-file_id1 = create_file("body-lotion.png")
-file_id2 = create_file("incense-kit.png")
-
-response = client.responses.create(
-	model="${k}",
-	input=[
-			{
-					"role": "user",
-					"content": [
-							{"type": "input_text", "text": prompt},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image1}",
-							},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image2}",
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id1,
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id2,
-							}
-					],
-			}
-	],
-	tools=[{"type": "image_generation"}],
-)
-
-# Process the response
-image_generation_calls = [
-	output
-	for output in response.output
-	if output.type == "image_generation_call"
-]
-
-image_data = [output.result for output in image_generation_calls]
-
-if image_data:
-	image_base64 = image_data[0]
-	image_filename = f"edited_image_{int(time.time())}.png"
-	with open(image_filename, "wb") as f:
-			f.write(base64.b64decode(image_base64))
-	print(f"Image saved to {image_filename}")
-else:
-	# If no image is generated, there might be a text response with an explanation
-	text_response = [output.text for output in response.output if hasattr(output, 'text')]
-	if text_response:
-			print("No image generated. Model response:")
-			print("\\n".join(text_response))
-	else:
-			print("No image data found in response.")
-	print("Full response for debugging:")
-	print(response)
-`;break;case r.IMAGE_EDITS:t="azure"===h?`
-import base64
-import os
-import time
-import json
-from PIL import Image
-import requests
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-	with open(image_path, "rb") as image_file:
-			return base64.b64encode(image_file.read()).decode('utf-8')
-
-# The prompt entered by the user
-prompt = "${j}"
-
-# Encode images to base64
-base64_image1 = encode_image("body-lotion.png")
-base64_image2 = encode_image("soap.png")
-
-# Create file IDs
-file_id1 = create_file("body-lotion.png")
-file_id2 = create_file("incense-kit.png")
-
-response = client.responses.create(
-	model="${k}",
-	input=[
-			{
-					"role": "user",
-					"content": [
-							{"type": "input_text", "text": prompt},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image1}",
-							},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image2}",
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id1,
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id2,
-							}
-					],
-			}
-	],
-	tools=[{"type": "image_generation"}],
-)
-
-# Process the response
-image_generation_calls = [
-	output
-	for output in response.output
-	if output.type == "image_generation_call"
-]
-
-image_data = [output.result for output in image_generation_calls]
-
-if image_data:
-	image_base64 = image_data[0]
-	image_filename = f"edited_image_{int(time.time())}.png"
-	with open(image_filename, "wb") as f:
-			f.write(base64.b64decode(image_base64))
-	print(f"Image saved to {image_filename}")
-else:
-	# If no image is generated, there might be a text response with an explanation
-	text_response = [output.text for output in response.output if hasattr(output, 'text')]
-	if text_response:
-			print("No image generated. Model response:")
-			print("\\n".join(text_response))
-	else:
-			print("No image data found in response.")
-	print("Full response for debugging:")
-	print(response)
-`:`
-import base64
-import os
-import time
-
-# Helper function to encode images to base64
-def encode_image(image_path):
-	with open(image_path, "rb") as image_file:
-			return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Helper function to create a file (simplified for this example)
-def create_file(image_path):
-	# In a real implementation, this would upload the file to OpenAI
-	# For this example, we'll just return a placeholder ID
-	return f"file_{os.path.basename(image_path).replace('.', '_')}"
-
-# The prompt entered by the user
-prompt = "${j}"
-
-# Encode images to base64
-base64_image1 = encode_image("body-lotion.png")
-base64_image2 = encode_image("soap.png")
-
-# Create file IDs
-file_id1 = create_file("body-lotion.png")
-file_id2 = create_file("incense-kit.png")
-
-response = client.responses.create(
-	model="${k}",
-	input=[
-			{
-					"role": "user",
-					"content": [
-							{"type": "input_text", "text": prompt},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image1}",
-							},
-							{
-									"type": "input_image",
-									"image_url": f"data:image/jpeg;base64,{base64_image2}",
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id1,
-							},
-							{
-									"type": "input_image",
-									"file_id": file_id2,
-							}
-					],
-			}
-	],
-	tools=[{"type": "image_generation"}],
-)
-
-# Process the response
-image_generation_calls = [
-	output
-	for output in response.output
-	if output.type == "image_generation_call"
-]
-
-image_data = [output.result for output in image_generation_calls]
-
-if image_data:
-	image_base64 = image_data[0]
-	image_filename = f"edited_image_{int(time.time())}.png"
-	with open(image_filename, "wb") as f:
-			f.write(base64.b64decode(image_base64))
-	print(f"Image saved to {image_filename}")
-else:
-	# If no image is generated, there might be a text response with an explanation
-	text_response = [output.text for output in response.output if hasattr(output, 'text')]
-	if text_response:
-			print("No image generated. Model response:")
-			print("\\n".join(text_response))
-	else:
-			print("No image data found in response.")
-	print("Full response for debugging:")
-	print(response)
-`;break;case r.EMBEDDINGS:t=`
-response = client.embeddings.create(
-	input="${n||"Your string here"}",
-	model="${k}",
-	encoding_format="base64" # or "float"
-)
-
-print(response.data[0].embedding)
-`;break;case r.TRANSCRIPTION:t=`
-# Open the audio file
-audio_file = open("path/to/your/audio/file.mp3", "rb")
-
-# Make the transcription request
-response = client.audio.transcriptions.create(
-	model="${k}",
-	file=audio_file${n?`,
-	prompt="${n.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""}
-)
-
-print(response.text)
-`;break;case r.SPEECH:t=`
-# Make the text-to-speech request
-response = client.audio.speech.create(
-	model="${k}",
-	input="${n||"Your text to convert to speech here"}",
-	voice="${m}"  # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer
-)
-
-# Save the audio to a file
-output_filename = "output_speech.mp3"
-response.stream_to_file(output_filename)
-print(f"Audio saved to {output_filename}")
-
-# Optional: Customize response format and speed
-# response = client.audio.speech.create(
-#     model="${k}",
-#     input="${n||"Your text to convert to speech here"}",
-#     voice="alloy",
-#     response_format="mp3",  # Options: mp3, opus, aac, flac, wav, pcm
-#     speed=1.0  # Range: 0.25 to 4.0
-# )
-# response.stream_to_file("output_speech.mp3")
-`;break;default:t="\n# Code generation for this endpoint is not implemented yet."}return`${N}
-${t}`}],339019)}]);
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/2udc_95331vyv.js b/litellm/proxy/_experimental/out/_next/static/chunks/2udc_95331vyv.js
deleted file mode 100644
index f824b1f10ef..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/2udc_95331vyv.js
+++ /dev/null
@@ -1 +0,0 @@
-(globalThis.TURBOPACK||(globalThis.TURBOPACK=[])).push(["object"==typeof document?document.currentScript:void 0,510674,e=>{"use strict";var t=e.i(266027),l=e.i(243652),a=e.i(602869),s=e.i(431703),i=e.i(135214),r=e.i(708347);let n=(0,l.createQueryKeys)("projects"),o=[...r.all_admin_roles,...r.internalUserRoles],d=async e=>{let t=(0,a.getProxyBaseUrl)(),l=`${t}/project/list`,i=await fetch(l,{method:"GET",headers:{[(0,a.getGlobalLitellmHeaderName)()]:`Bearer ${e}`,"Content-Type":"application/json"}});if(!i.ok){let e=await i.json(),t=(0,s.deriveErrorMessage)(e);throw(0,a.handleError)(t),Error(t)}return i.json()};e.s(["projectKeys",0,n,"useProjects",0,()=>{let{accessToken:e,userRole:l}=(0,i.default)();return(0,t.useQuery)({queryKey:n.list({}),queryFn:async()=>d(e),enabled:!!e&&o.includes(l)})}])},109034,309426,e=>{"use strict";var t=e.i(266027),l=e.i(243652),a=e.i(602869),s=e.i(135214);let 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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/2unvrapk_ti-3.js b/litellm/proxy/_experimental/out/_next/static/chunks/2unvrapk_ti-3.js
deleted file mode 100644
index 8d0b4974b5a..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/2unvrapk_ti-3.js
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/2vc3-yfu_dywm.js b/litellm/proxy/_experimental/out/_next/static/chunks/2vc3-yfu_dywm.js
new file mode 100644
index 00000000000..bc34d46309e
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/2vc3-yfu_dywm.js
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deleted file mode 100644
index 31f33fcf881..00000000000
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new file mode 100644
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deleted file mode 100644
index d816c824135..00000000000
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n={image_generation:"image",video_generation:"video",chat:"chat",completion:"chat",responses:"responses",image_edit:"image_edits",anthropic_messages:"anthropic_messages",audio_speech:"speech",audio_transcription:"transcription",embedding:"embeddings",realtime:"realtime"};e.s(["EndpointType",()=>o,"ModelMode",()=>a,"getEndpointType",0,e=>Object.values(a).includes(e)?n[e]:"chat"],865361),e.s(["generateCodeSnippet",0,e=>{let t,{apiKeySource:i,accessToken:a,apiKey:n,inputMessage:r,chatHistory:s,selectedTags:l,selectedVectorStores:p,selectedGuardrails:d,selectedPolicies:m,selectedVoice:g,endpointType:u,selectedModel:c,selectedSdk:f,proxySettings:h}=e,_="session"===i?a:n,b=window.location.origin,x=h?.LITELLM_UI_API_DOC_BASE_URL;x&&x.trim()?b=x:h?.PROXY_BASE_URL&&(b=h.PROXY_BASE_URL);let y=r||"Your prompt here",j=y.replace(/\\/g,"\\\\").replace(/"/g,'\\"').replace(/\n/g,"\\n"),S=s.filter(e=>!e.isImage).map(({role:e,content:t})=>({role:e,content:t})),v={};l.length>0&&(v.tags=l),p.length>0&&(v.vector_stores=p),d.length>0&&(v.guardrails=d),m.length>0&&(v.policies=m);let k=c||"your-model-name",w="azure"===f?`import openai
+
+client = openai.AzureOpenAI(
+	api_key="${_||"YOUR_LITELLM_API_KEY"}",
+	azure_endpoint="${b}",
+	api_version="2024-02-01"
+)`:`import openai
+
+client = openai.OpenAI(
+	api_key="${_||"YOUR_LITELLM_API_KEY"}",
+	base_url="${b}"
+)`;switch(u){case o.CHAT:{let e=Object.keys(v).length>0,i="";if(e){let e=JSON.stringify({metadata:v},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`,
+    extra_body=${e}`}let a=S.length>0?S:[{role:"user",content:y}];t=`
+import base64
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Example with text only
+response = client.chat.completions.create(
+    model="${k}",
+    messages=${JSON.stringify(a,null,4)}${i}
+)
+
+print(response)
+
+# Example with image or PDF (uncomment and provide file path to use)
+# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
+# response_with_file = client.chat.completions.create(
+#     model="${k}",
+#     messages=[
+#         {
+#             "role": "user",
+#             "content": [
+#                 {
+#                     "type": "text",
+#                     "text": "${j}"
+#                 },
+#                 {
+#                     "type": "image_url",
+#                     "image_url": {
+#                         "url": f"data:image/jpeg;base64,{base64_file}"  # or data:application/pdf;base64,{base64_file}
+#                     }
+#                 }
+#             ]
+#         }
+#     ]${i}
+# )
+# print(response_with_file)
+`;break}case o.RESPONSES:{let e=Object.keys(v).length>0,i="";if(e){let e=JSON.stringify({metadata:v},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`,
+    extra_body=${e}`}let a=S.length>0?S:[{role:"user",content:y}];t=`
+import base64
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Example with text only
+response = client.responses.create(
+    model="${k}",
+    input=${JSON.stringify(a,null,4)}${i}
+)
+
+print(response.output_text)
+
+# Example with image or PDF (uncomment and provide file path to use)
+# base64_file = encode_image("path/to/your/file.jpg")  # or .pdf
+# response_with_file = client.responses.create(
+#     model="${k}",
+#     input=[
+#         {
+#             "role": "user",
+#             "content": [
+#                 {"type": "input_text", "text": "${j}"},
+#                 {
+#                     "type": "input_image",
+#                     "image_url": f"data:image/jpeg;base64,{base64_file}",  # or data:application/pdf;base64,{base64_file}
+#                 },
+#             ],
+#         }
+#     ]${i}
+# )
+# print(response_with_file.output_text)
+`;break}case o.IMAGE:t="azure"===f?`
+# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI.
+# This snippet uses 'client.images.generate' and will create a new image based on your prompt.
+# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context.
+import os
+import requests
+import json
+import time
+from PIL import Image
+
+result = client.images.generate(
+	model="${k}",
+	prompt="${r}",
+	n=1
+)
+
+json_response = json.loads(result.model_dump_json())
+
+# Set the directory for the stored image
+image_dir = os.path.join(os.curdir, 'images')
+
+# If the directory doesn't exist, create it
+if not os.path.isdir(image_dir):
+	os.mkdir(image_dir)
+
+# Initialize the image path
+image_filename = f"generated_image_{int(time.time())}.png"
+image_path = os.path.join(image_dir, image_filename)
+
+try:
+	# Retrieve the generated image
+	if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"):
+			image_url = json_response["data"][0]["url"]
+			generated_image = requests.get(image_url).content
+			with open(image_path, "wb") as image_file:
+					image_file.write(generated_image)
+
+			print(f"Image saved to {image_path}")
+			# Display the image
+			image = Image.open(image_path)
+			image.show()
+	else:
+			print("Could not find image URL in response.")
+			print("Full response:", json_response)
+except Exception as e:
+	print(f"An error occurred: {e}")
+	print("Full response:", json_response)
+`:`
+import base64
+import os
+import time
+import json
+from PIL import Image
+import requests
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+	with open(image_path, "rb") as image_file:
+			return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Helper function to create a file (simplified for this example)
+def create_file(image_path):
+	# In a real implementation, this would upload the file to OpenAI
+	# For this example, we'll just return a placeholder ID
+	return f"file_{os.path.basename(image_path).replace('.', '_')}"
+
+# The prompt entered by the user
+prompt = "${j}"
+
+# Encode images to base64
+base64_image1 = encode_image("body-lotion.png")
+base64_image2 = encode_image("soap.png")
+
+# Create file IDs
+file_id1 = create_file("body-lotion.png")
+file_id2 = create_file("incense-kit.png")
+
+response = client.responses.create(
+	model="${k}",
+	input=[
+			{
+					"role": "user",
+					"content": [
+							{"type": "input_text", "text": prompt},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image1}",
+							},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image2}",
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id1,
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id2,
+							}
+					],
+			}
+	],
+	tools=[{"type": "image_generation"}],
+)
+
+# Process the response
+image_generation_calls = [
+	output
+	for output in response.output
+	if output.type == "image_generation_call"
+]
+
+image_data = [output.result for output in image_generation_calls]
+
+if image_data:
+	image_base64 = image_data[0]
+	image_filename = f"edited_image_{int(time.time())}.png"
+	with open(image_filename, "wb") as f:
+			f.write(base64.b64decode(image_base64))
+	print(f"Image saved to {image_filename}")
+else:
+	# If no image is generated, there might be a text response with an explanation
+	text_response = [output.text for output in response.output if hasattr(output, 'text')]
+	if text_response:
+			print("No image generated. Model response:")
+			print("\\n".join(text_response))
+	else:
+			print("No image data found in response.")
+	print("Full response for debugging:")
+	print(response)
+`;break;case o.IMAGE_EDITS:t="azure"===f?`
+import base64
+import os
+import time
+import json
+from PIL import Image
+import requests
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+	with open(image_path, "rb") as image_file:
+			return base64.b64encode(image_file.read()).decode('utf-8')
+
+# The prompt entered by the user
+prompt = "${j}"
+
+# Encode images to base64
+base64_image1 = encode_image("body-lotion.png")
+base64_image2 = encode_image("soap.png")
+
+# Create file IDs
+file_id1 = create_file("body-lotion.png")
+file_id2 = create_file("incense-kit.png")
+
+response = client.responses.create(
+	model="${k}",
+	input=[
+			{
+					"role": "user",
+					"content": [
+							{"type": "input_text", "text": prompt},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image1}",
+							},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image2}",
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id1,
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id2,
+							}
+					],
+			}
+	],
+	tools=[{"type": "image_generation"}],
+)
+
+# Process the response
+image_generation_calls = [
+	output
+	for output in response.output
+	if output.type == "image_generation_call"
+]
+
+image_data = [output.result for output in image_generation_calls]
+
+if image_data:
+	image_base64 = image_data[0]
+	image_filename = f"edited_image_{int(time.time())}.png"
+	with open(image_filename, "wb") as f:
+			f.write(base64.b64decode(image_base64))
+	print(f"Image saved to {image_filename}")
+else:
+	# If no image is generated, there might be a text response with an explanation
+	text_response = [output.text for output in response.output if hasattr(output, 'text')]
+	if text_response:
+			print("No image generated. Model response:")
+			print("\\n".join(text_response))
+	else:
+			print("No image data found in response.")
+	print("Full response for debugging:")
+	print(response)
+`:`
+import base64
+import os
+import time
+
+# Helper function to encode images to base64
+def encode_image(image_path):
+	with open(image_path, "rb") as image_file:
+			return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Helper function to create a file (simplified for this example)
+def create_file(image_path):
+	# In a real implementation, this would upload the file to OpenAI
+	# For this example, we'll just return a placeholder ID
+	return f"file_{os.path.basename(image_path).replace('.', '_')}"
+
+# The prompt entered by the user
+prompt = "${j}"
+
+# Encode images to base64
+base64_image1 = encode_image("body-lotion.png")
+base64_image2 = encode_image("soap.png")
+
+# Create file IDs
+file_id1 = create_file("body-lotion.png")
+file_id2 = create_file("incense-kit.png")
+
+response = client.responses.create(
+	model="${k}",
+	input=[
+			{
+					"role": "user",
+					"content": [
+							{"type": "input_text", "text": prompt},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image1}",
+							},
+							{
+									"type": "input_image",
+									"image_url": f"data:image/jpeg;base64,{base64_image2}",
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id1,
+							},
+							{
+									"type": "input_image",
+									"file_id": file_id2,
+							}
+					],
+			}
+	],
+	tools=[{"type": "image_generation"}],
+)
+
+# Process the response
+image_generation_calls = [
+	output
+	for output in response.output
+	if output.type == "image_generation_call"
+]
+
+image_data = [output.result for output in image_generation_calls]
+
+if image_data:
+	image_base64 = image_data[0]
+	image_filename = f"edited_image_{int(time.time())}.png"
+	with open(image_filename, "wb") as f:
+			f.write(base64.b64decode(image_base64))
+	print(f"Image saved to {image_filename}")
+else:
+	# If no image is generated, there might be a text response with an explanation
+	text_response = [output.text for output in response.output if hasattr(output, 'text')]
+	if text_response:
+			print("No image generated. Model response:")
+			print("\\n".join(text_response))
+	else:
+			print("No image data found in response.")
+	print("Full response for debugging:")
+	print(response)
+`;break;case o.EMBEDDINGS:t=`
+response = client.embeddings.create(
+	input="${r||"Your string here"}",
+	model="${k}",
+	encoding_format="base64" # or "float"
+)
+
+print(response.data[0].embedding)
+`;break;case o.TRANSCRIPTION:t=`
+# Open the audio file
+audio_file = open("path/to/your/audio/file.mp3", "rb")
+
+# Make the transcription request
+response = client.audio.transcriptions.create(
+	model="${k}",
+	file=audio_file${r?`,
+	prompt="${r.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""}
+)
+
+print(response.text)
+`;break;case o.SPEECH:t=`
+# Make the text-to-speech request
+response = client.audio.speech.create(
+	model="${k}",
+	input="${r||"Your text to convert to speech here"}",
+	voice="${g}"  # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer
+)
+
+# Save the audio to a file
+output_filename = "output_speech.mp3"
+response.stream_to_file(output_filename)
+print(f"Audio saved to {output_filename}")
+
+# Optional: Customize response format and speed
+# response = client.audio.speech.create(
+#     model="${k}",
+#     input="${r||"Your text to convert to speech here"}",
+#     voice="alloy",
+#     response_format="mp3",  # Options: mp3, opus, aac, flac, wav, pcm
+#     speed=1.0  # Range: 0.25 to 4.0
+# )
+# response.stream_to_file("output_speech.mp3")
+`;break;default:t="\n# Code generation for this endpoint is not implemented yet."}return`${w}
+${t}`}],909947)},86408,e=>{"use strict";var t=e.i(843476),i=e.i(271645),a=e.i(618566),o=e.i(934879);function n(){let e=(0,a.useSearchParams)().get("key"),[n,r]=(0,i.useState)(null);return(0,i.useEffect)(()=>{e&&r(e)},[e]),(0,t.jsx)(o.default,{accessToken:n,publicPage:!0,premiumUser:!1,userRole:null})}e.s(["default",0,function(){return(0,t.jsx)(i.Suspense,{fallback:(0,t.jsx)("div",{className:"flex items-center justify-center min-h-screen",children:"Loading..."}),children:(0,t.jsx)(n,{})})}])}]);
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/32spu2es3pdi0.js b/litellm/proxy/_experimental/out/_next/static/chunks/32spu2es3pdi0.js
deleted file mode 100644
index c9b9a231662..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/32spu2es3pdi0.js
+++ /dev/null
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/32wj-y89tqcjb.js b/litellm/proxy/_experimental/out/_next/static/chunks/32wj-y89tqcjb.js
new file mode 100644
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listed"}):I.map(e=>(0,s.jsx)(d.Badge,{variant:"secondary",children:e.replace(/^supports_/,"").split("_").map(e=>e.charAt(0).toUpperCase()+e.slice(1)).join(" ")},e))})]}),(ew.tpm||ew.rpm)&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Rate Limits"}),(0,s.jsxs)("div",{className:"grid grid-cols-2 gap-4",children:[ew.tpm&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Tokens per Minute:"}),(0,s.jsx)("p",{children:ew.tpm.toLocaleString()})]}),ew.rpm&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Requests per Minute:"}),(0,s.jsx)("p",{children:ew.rpm.toLocaleString()})]})]})]}),ew.supported_openai_params&&ew.supported_openai_params.length>0&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Supported OpenAI Parameters"}),(0,s.jsx)("div",{className:"flex flex-wrap 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you?",chatHistory:[{role:"user",content:"Hello, how are you?",isImage:!1}],selectedTags:[],selectedVectorStores:[],selectedGuardrails:[],selectedPolicies:[],selectedMCPServers:[],endpointType:(0,P.getEndpointType)(ew.mode||"chat"),selectedModel:ew.model_group,selectedSdk:"openai"}))},className:"text-sm text-info hover:text-info/80 cursor-pointer",children:"Copy to clipboard"})})]})]})]})}),(0,s.jsx)(x.Dialog,{open:e_,onOpenChange:e=>!e&&void(ey(!1),eA(null)),children:(0,s.jsxs)(x.DialogContent,{className:"max-h-[calc(100dvh-2rem)] overflow-y-auto sm:max-w-[1000px]",children:[(0,s.jsx)(x.DialogHeader,{children:(0,s.jsxs)(x.DialogTitle,{className:"flex min-w-0 items-center space-x-2",children:[(0,s.jsx)("span",{className:"break-words",children:eT?.name||"Agent Details"}),eT&&(0,s.jsxs)(p.Tooltip,{children:[(0,s.jsx)(p.TooltipTrigger,{render:(0,s.jsx)(l.Copy,{onClick:()=>eU(eT.name),className:"cursor-pointer text-muted-foreground hover:text-info w-4 h-4 shrink-0"})}),(0,s.jsx)(p.TooltipContent,{children:"Copy agent name"})]})]})}),eT&&(0,s.jsxs)("div",{className:"space-y-6",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Agent Overview"}),(0,s.jsxs)("div",{className:"grid grid-cols-2 gap-4 mb-4",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Name:"}),(0,s.jsx)("p",{children:eT.name})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Version:"}),(0,s.jsx)("p",{children:eT.version})]}),(0,s.jsxs)("div",{className:"col-span-2",children:[(0,s.jsx)("p",{className:"font-medium",children:"Description:"}),(0,s.jsx)("p",{children:eT.description})]}),eT.url&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"URL:"}),(0,s.jsx)("a",{href:eT.url,target:"_blank",rel:"noopener noreferrer",className:"text-info hover:text-info/80 text-sm break-all",children:eT.url})]})]})]}),eT.capabilities&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Capabilities"}),(0,s.jsx)("div",{className:"flex flex-wrap gap-2",children:Object.entries(eT.capabilities).filter(([e,s])=>!0===s).map(([e])=>(0,s.jsx)(d.Badge,{variant:"secondary",className:"capitalize",children:e},e))})]}),eT.skills&&eT.skills.length>0&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Skills"}),(0,s.jsx)("div",{className:"space-y-4",children:eT.skills.map((e,t)=>(0,s.jsxs)("div",{className:"border border-border rounded-lg p-4",children:[(0,s.jsx)("div",{className:"flex items-start justify-between mb-2",children:(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium text-base",children:e.name}),(0,s.jsx)("p",{className:"text-sm text-muted-foreground",children:e.description})]})}),e.tags&&e.tags.length>0&&(0,s.jsx)("div",{className:"flex flex-wrap gap-1 mt-2",children:e.tags.map(e=>(0,s.jsx)(d.Badge,{variant:"secondary",className:"text-xs",children:e},e))})]},t))})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Input/Output Modes"}),(0,s.jsxs)("div",{className:"grid grid-cols-2 gap-4",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Input Modes:"}),(0,s.jsx)("div",{className:"flex flex-wrap gap-1 mt-1",children:(eT.defaultInputModes??[]).map(e=>(0,s.jsx)(d.Badge,{variant:"secondary",children:e},e))})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Output Modes:"}),(0,s.jsx)("div",{className:"flex flex-wrap gap-1 mt-1",children:(eT.defaultOutputModes??[]).map(e=>(0,s.jsx)(d.Badge,{variant:"secondary",children:e},e))})]})]})]}),eT.documentationUrl&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Documentation"}),(0,s.jsxs)("a",{href:eT.documentationUrl,target:"_blank",rel:"noopener noreferrer",className:"text-info hover:text-info/80 flex items-center space-x-2",children:[(0,s.jsx)(a.ExternalLinkIcon,{className:"w-4 h-4"}),(0,s.jsx)("span",{children:"View Documentation"})]})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Usage Example (A2A Protocol)"}),(0,s.jsxs)("div",{className:"mb-4",children:[(0,s.jsx)("p",{className:"text-sm font-medium mb-2 text-foreground",children:"Step 1: Retrieve Agent Card"}),(0,s.jsx)("div",{className:"bg-gray-900 text-gray-100 p-4 rounded-lg overflow-x-auto",children:(0,s.jsx)("pre",{className:"text-xs",children:`base_url = '${eT.url}'
+
+resolver = A2ACardResolver(
+    httpx_client=httpx_client,
+    base_url=base_url,
+    # agent_card_path uses default, extended_agent_card_path also uses default
+)
+
+# Fetch Public Agent Card and Initialize Client
+final_agent_card_to_use: AgentCard | None = None
+_public_card = (
+    await resolver.get_agent_card()
+)  # Fetches from default public path - \`/agents/{agent_id}/\`
+final_agent_card_to_use = _public_card
+
+if _public_card.supports_authenticated_extended_card:
+    try:
+        auth_headers_dict = {
+            'Authorization': 'Bearer dummy-token-for-extended-card'
+        }
+        _extended_card = await resolver.get_agent_card(
+            relative_card_path=EXTENDED_AGENT_CARD_PATH,
+            http_kwargs={'headers': auth_headers_dict},
+        )
+        final_agent_card_to_use = (
+            _extended_card  # Update to use the extended card
+        )
+    except Exception as e_extended:
+        logger.warning(
+            f'Failed to fetch extended agent card: {e_extended}. Will proceed with public card.',
+            exc_info=True,
+        )`})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU(`from a2a.client import A2ACardResolver, A2AClient
+from a2a.types import (
+    AgentCard,
+    MessageSendParams,
+    SendMessageRequest,
+    SendStreamingMessageRequest,
+)
+from a2a.utils.constants import (
+    AGENT_CARD_WELL_KNOWN_PATH,
+    EXTENDED_AGENT_CARD_PATH,
+)
+
+base_url = '${eT.url}'
+
+resolver = A2ACardResolver(
+    httpx_client=httpx_client,
+    base_url=base_url,
+    # agent_card_path uses default, extended_agent_card_path also uses default
+)
+
+# Fetch Public Agent Card and Initialize Client
+final_agent_card_to_use: AgentCard | None = None
+_public_card = (
+    await resolver.get_agent_card()
+)  # Fetches from default public path - \`/agents/{agent_id}/\`
+final_agent_card_to_use = _public_card
+
+if _public_card.supports_authenticated_extended_card:
+    try:
+        auth_headers_dict = {
+            'Authorization': 'Bearer dummy-token-for-extended-card'
+        }
+        _extended_card = await resolver.get_agent_card(
+            relative_card_path=EXTENDED_AGENT_CARD_PATH,
+            http_kwargs={'headers': auth_headers_dict},
+        )
+        final_agent_card_to_use = (
+            _extended_card  # Update to use the extended card
+        )
+    except Exception as e_extended:
+        logger.warning(
+            f'Failed to fetch extended agent card: {e_extended}. Will proceed with public card.',
+            exc_info=True,
+        )`)},className:"text-sm text-info hover:text-info/80 cursor-pointer",children:"Copy to clipboard"})})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-sm font-medium mb-2 text-foreground",children:"Step 2: Call the Agent"}),(0,s.jsx)("div",{className:"bg-gray-900 text-gray-100 p-4 rounded-lg overflow-x-auto",children:(0,s.jsx)("pre",{className:"text-xs",children:`client = A2AClient(
+    httpx_client=httpx_client, agent_card=final_agent_card_to_use
+)
+
+send_message_payload: dict[str, Any] = {
+    'message': {
+        'role': 'user',
+        'parts': [
+            {'kind': 'text', 'text': 'how much is 10 USD in INR?'}
+        ],
+        'messageId': uuid4().hex,
+    },
+}
+request = SendMessageRequest(
+    id=str(uuid4()), params=MessageSendParams(**send_message_payload)
+)
+
+response = await client.send_message(request)
+print(response.model_dump(mode='json', exclude_none=True))`})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU(`client = A2AClient(
+    httpx_client=httpx_client, agent_card=final_agent_card_to_use
+)
+
+send_message_payload: dict[str, Any] = {
+    'message': {
+        'role': 'user',
+        'parts': [
+            {'kind': 'text', 'text': 'how much is 10 USD in INR?'}
+        ],
+        'messageId': uuid4().hex,
+    },
+}
+request = SendMessageRequest(
+    id=str(uuid4()), params=MessageSendParams(**send_message_payload)
+)
+
+response = await client.send_message(request)
+print(response.model_dump(mode='json', exclude_none=True))`)},className:"text-sm text-info hover:text-info/80 cursor-pointer",children:"Copy to clipboard"})})]})]})]})]})}),(0,s.jsx)(x.Dialog,{open:eS,onOpenChange:e=>!e&&void(eC(!1),eD(null)),children:(0,s.jsxs)(x.DialogContent,{className:"max-h-[calc(100dvh-2rem)] overflow-y-auto sm:max-w-[1000px]",children:[(0,s.jsx)(x.DialogHeader,{children:(0,s.jsxs)(x.DialogTitle,{className:"flex min-w-0 items-center space-x-2",children:[(0,s.jsx)("span",{className:"break-words",children:eM?.server_name||"MCP Server Details"}),eM&&(0,s.jsxs)(p.Tooltip,{children:[(0,s.jsx)(p.TooltipTrigger,{render:(0,s.jsx)(l.Copy,{onClick:()=>eU(eM.server_name),className:"cursor-pointer text-muted-foreground hover:text-info w-4 h-4 shrink-0"})}),(0,s.jsx)(p.TooltipContent,{children:"Copy server name"})]})]})}),eM&&(0,s.jsxs)("div",{className:"space-y-6",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Server Overview"}),(0,s.jsxs)("div",{className:"grid grid-cols-2 gap-4 mb-4",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Server Name:"}),(0,s.jsx)("p",{children:eM.server_name})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Transport:"}),(0,s.jsx)(d.Badge,{variant:"secondary",children:eM.transport})]}),eM.alias&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Alias:"}),(0,s.jsx)("p",{children:eM.alias})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Auth Type:"}),(0,s.jsx)(d.Badge,{variant:"none"===eM.auth_type?"outline":"secondary",children:eM.auth_type})]}),(0,s.jsxs)("div",{className:"col-span-2",children:[(0,s.jsx)("p",{className:"font-medium",children:"Description:"}),(0,s.jsx)("p",{children:eM.mcp_info?.description||"-"})]})]})]}),eM.mcp_info&&Object.keys(eM.mcp_info).length>0&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Additional Information"}),(0,s.jsx)("div",{className:"bg-muted p-4 rounded-lg",children:(0,s.jsx)("pre",{className:"text-xs overflow-x-auto",children:JSON.stringify(eM.mcp_info,null,2)})})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Usage Example"}),(0,s.jsx)("div",{className:"bg-gray-900 text-gray-100 p-4 rounded-lg overflow-x-auto",children:(0,s.jsx)("pre",{className:"text-sm",children:`# Using MCP Server with Python FastMCP
+
+from fastmcp import Client
+import asyncio
+
+# Standard MCP configuration
+config = {
+    "mcpServers": {
+        "${eM.server_name}": {
+            "url": "${(0,b.getProxyBaseUrl)()}/${eM.server_name}/mcp",
+            "headers": {
+                "x-litellm-api-key": "Bearer sk-1234"
+            }
+        }
+    }
+}
+
+# Create a client that connects to the server
+client = Client(config)
+
+async def main():
+    async with client:
+        # List available tools
+        tools = await client.list_tools()
+        print(f"Available tools: {[tool.name for tool in tools]}")
+
+        # Call a tool
+        response = await client.call_tool(
+            name="tool_name", 
+            arguments={"arg": "value"}
+        )
+        print(f"Response: {response}")
+
+if __name__ == "__main__":
+    asyncio.run(main())`})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU(`# Using MCP Server with Python FastMCP
+
+from fastmcp import Client
+import asyncio
+
+# Standard MCP configuration
+config = {
+    "mcpServers": {
+        "${eM.server_name}": {
+            "url": "${(0,b.getProxyBaseUrl)()}/${eM.server_name}/mcp",
+            "headers": {
+                "x-litellm-api-key": "Bearer sk-1234"
+            }
+        }
+    }
+}
+
+# Create a client that connects to the server
+client = Client(config)
+
+async def main():
+    async with client:
+        # List available tools
+        tools = await client.list_tools()
+        print(f"Available tools: {[tool.name for tool in tools]}")
+
+        # Call a tool
+        response = await client.call_tool(
+            name="tool_name", 
+            arguments={"arg": "value"}
+        )
+        print(f"Response: {response}")
+
+if __name__ == "__main__":
+    asyncio.run(main())`)},className:"text-sm text-info hover:text-info/80 cursor-pointer",children:"Copy to clipboard"})})]})]})]})})]})})})}],976883)}]);
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/337hhycs6txt1.js b/litellm/proxy/_experimental/out/_next/static/chunks/337hhycs6txt1.js
new file mode 100644
index 00000000000..0318db46ec0
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/337hhycs6txt1.js
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/33b5iwn9zxmnb.js b/litellm/proxy/_experimental/out/_next/static/chunks/33b5iwn9zxmnb.js
deleted file mode 100644
index 46ceca083d6..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/33b5iwn9zxmnb.js
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deleted file mode 100644
index ff7dc18acf2..00000000000
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deleted file mode 100644
index 98420df531c..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/35pry5vx8lu2u.js
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/39s4-rh6l9sa1.js b/litellm/proxy/_experimental/out/_next/static/chunks/39s4-rh6l9sa1.js
new file mode 100644
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+++ b/litellm/proxy/_experimental/out/_next/static/chunks/39s4-rh6l9sa1.js
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3_7h77x1s5_xs.js b/litellm/proxy/_experimental/out/_next/static/chunks/3_7h77x1s5_xs.js
new file mode 100644
index 00000000000..3fd371ce703
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/3_7h77x1s5_xs.js
@@ -0,0 +1 @@
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3_s8-zrwu1i93.js b/litellm/proxy/_experimental/out/_next/static/chunks/3_s8-zrwu1i93.js
deleted file mode 100644
index 4492093a4c0..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/3_s8-zrwu1i93.js
+++ /dev/null
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index 00000000000..6263089fefa
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3ap92xn2dqd_i.js b/litellm/proxy/_experimental/out/_next/static/chunks/3ap92xn2dqd_i.js
deleted file mode 100644
index 90b3218e898..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/3ap92xn2dqd_i.js
+++ /dev/null
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new file mode 100644
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new file mode 100644
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deleted file mode 100644
index e62f867d42d..00000000000
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ij=e.i(922143),iN=e.i(682358);function iD(e,t,i,r){let n=Math.abs(e),a=n%10,o=n%100;return o>=11&&o<=19?r:1===a?t:a>=2&&a<=4?i:r}function iP(e,t,i,r){let n=Math.abs(e),a=n%10,o=n%100;return o>=11&&o<=19?r:1===a?t:a>=2&&a<=4?i:r}e.s([],543365),e.i(543365),e.s(["ar",0,function(){let e,t;return{localeError:(e={string:{unit:"حرف",verb:"أن يحوي"},file:{unit:"بايت",verb:"أن يحوي"},array:{unit:"عنصر",verb:"أن يحوي"},set:{unit:"عنصر",verb:"أن يحوي"}},t={regex:"مدخل",email:"بريد إلكتروني",url:"رابط",emoji:"إيموجي",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"تاريخ ووقت بمعيار ISO",date:"تاريخ بمعيار ISO",time:"وقت بمعيار ISO",duration:"مدة بمعيار ISO",ipv4:"عنوان IPv4",ipv6:"عنوان IPv6",cidrv4:"مدى عناوين بصيغة IPv4",cidrv6:"مدى عناوين بصيغة IPv6",base64:"نَص بترميز base64-encoded",base64url:"نَص بترميز base64url-encoded",json_string:"نَص على هيئة JSON",e164:"رقم هاتف بمعيار E.164",jwt:"JWT",template_literal:"مدخل"},i=>{switch(i.code){case"invalid_type":return`مدخلات غير مقبولة: يفترض إدخال ${i.expected}، ولكن تم إدخال ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`مدخلات غير مقبولة: يفترض إدخال ${E(i.values[0])}`;return`اختيار غير مقبول: يتوقع انتقاء أحد هذه الخيارات: ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return` أكبر من اللازم: يفترض أن تكون ${i.origin??"القيمة"} ${t} ${i.maximum.toString()} ${r.unit??"عنصر"}`;return`أكبر من اللازم: يفترض أن تكون ${i.origin??"القيمة"} ${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`أصغر من اللازم: يفترض لـ ${i.origin} أن يكون ${t} ${i.minimum.toString()} ${r.unit}`;return`أصغر من اللازم: يفترض لـ ${i.origin} أن يكون ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`نَص غير مقبول: يجب أن يبدأ بـ "${i.prefix}"`;if("ends_with"===i.format)return`نَص غير مقبول: يجب أن ينتهي بـ "${i.suffix}"`;if("includes"===i.format)return`نَص غير مقبول: يجب أن يتضمَّن "${i.includes}"`;if("regex"===i.format)return`نَص غير مقبول: يجب أن يطابق النمط ${i.pattern}`;return`${t[i.format]??i.format} غير مقبول`;case"not_multiple_of":return`رقم غير مقبول: يجب أن يكون من مضاعفات ${i.divisor}`;case"unrecognized_keys":return`معرف${i.keys.length>1?"ات":""} غريب${i.keys.length>1?"ة":""}: ${h(i.keys,"، ")}`;case"invalid_key":return`معرف غير مقبول في ${i.origin}`;case"invalid_union":default:return"مدخل غير مقبول";case"invalid_element":return`مدخل غير مقبول في ${i.origin}`}})}},"az",0,function(){let e,t;return{localeError:(e={string:{unit:"simvol",verb:"olmalıdır"},file:{unit:"bayt",verb:"olmalıdır"},array:{unit:"element",verb:"olmalıdır"},set:{unit:"element",verb:"olmalıdır"}},t={regex:"input",email:"email address",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datetime",date:"ISO date",time:"ISO time",duration:"ISO duration",ipv4:"IPv4 address",ipv6:"IPv6 address",cidrv4:"IPv4 range",cidrv6:"IPv6 range",base64:"base64-encoded string",base64url:"base64url-encoded string",json_string:"JSON string",e164:"E.164 number",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Yanlış dəyər: g\xf6zlənilən ${i.expected}, daxil olan ${(e=>{let t=typeof e;switch(t){case"number":return 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e,t;return{localeError:(e={string:{unit:{one:"сімвал",few:"сімвалы",many:"сімвалаў"},verb:"мець"},array:{unit:{one:"элемент",few:"элементы",many:"элементаў"},verb:"мець"},set:{unit:{one:"элемент",few:"элементы",many:"элементаў"},verb:"мець"},file:{unit:{one:"байт",few:"байты",many:"байтаў"},verb:"мець"}},t={regex:"увод",email:"email адрас",url:"URL",emoji:"эмодзі",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO дата і час",date:"ISO дата",time:"ISO час",duration:"ISO працягласць",ipv4:"IPv4 адрас",ipv6:"IPv6 адрас",cidrv4:"IPv4 дыяпазон",cidrv6:"IPv6 дыяпазон",base64:"радок у фармаце base64",base64url:"радок у фармаце base64url",json_string:"JSON радок",e164:"нумар E.164",jwt:"JWT",template_literal:"увод"},i=>{switch(i.code){case"invalid_type":return`Няправільны ўвод: чакаўся ${i.expected}, атрымана ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"лік";case"object":if(Array.isArray(e))return"масіў";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Няправільны ўвод: чакалася ${E(i.values[0])}`;return`Няправільны варыянт: чакаўся адзін з ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r){let e=iD(Number(i.maximum),r.unit.one,r.unit.few,r.unit.many);return`Занадта вялікі: чакалася, што ${i.origin??"значэнне"} павінна ${r.verb} ${t}${i.maximum.toString()} ${e}`}return`Занадта вялікі: чакалася, што ${i.origin??"значэнне"} павінна быць ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r){let e=iD(Number(i.minimum),r.unit.one,r.unit.few,r.unit.many);return`Занадта малы: чакалася, што ${i.origin} павінна ${r.verb} ${t}${i.minimum.toString()} ${e}`}return`Занадта малы: чакалася, што ${i.origin} павінна быць ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Няправільны радок: павінен пачынацца з "${i.prefix}"`;if("ends_with"===i.format)return`Няправільны радок: павінен заканчвацца на "${i.suffix}"`;if("includes"===i.format)return`Няправільны радок: павінен змяшчаць "${i.includes}"`;if("regex"===i.format)return`Няправільны радок: павінен адпавядаць шаблону ${i.pattern}`;return`Няправільны ${t[i.format]??i.format}`;case"not_multiple_of":return`Няправільны лік: павінен быць кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспазнаны ${i.keys.length>1?"ключы":"ключ"}: ${h(i.keys,", ")}`;case"invalid_key":return`Няправільны ключ у ${i.origin}`;case"invalid_union":default:return"Няправільны ўвод";case"invalid_element":return`Няправільнае значэнне ў ${i.origin}`}})}},"ca",0,function(){let e,t;return{localeError:(e={string:{unit:"caràcters",verb:"contenir"},file:{unit:"bytes",verb:"contenir"},array:{unit:"elements",verb:"contenir"},set:{unit:"elements",verb:"contenir"}},t={regex:"entrada",email:"adreça electrònica",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i hora ISO",date:"data ISO",time:"hora ISO",duration:"durada ISO",ipv4:"adreça IPv4",ipv6:"adreça IPv6",cidrv4:"rang IPv4",cidrv6:"rang IPv6",base64:"cadena codificada en base64",base64url:"cadena codificada en base64url",json_string:"cadena JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Tipus inv\xe0lid: s'esperava ${i.expected}, s'ha rebut ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Valor inv\xe0lid: s'esperava ${E(i.values[0])}`;return`Opci\xf3 inv\xe0lida: s'esperava una de ${h(i.values," o ")}`;case"too_big":{let t=i.inclusive?"com a màxim":"menys de",r=e[i.origin]??null;if(r)return`Massa gran: s'esperava que ${i.origin??"el valor"} contingu\xe9s ${t} ${i.maximum.toString()} ${r.unit??"elements"}`;return`Massa gran: s'esperava que ${i.origin??"el valor"} fos ${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"com a mínim":"més de",r=e[i.origin]??null;if(r)return`Massa petit: s'esperava que ${i.origin} contingu\xe9s ${t} ${i.minimum.toString()} ${r.unit}`;return`Massa petit: s'esperava que ${i.origin} fos ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Format inv\xe0lid: ha de comen\xe7ar amb "${i.prefix}"`;if("ends_with"===i.format)return`Format inv\xe0lid: ha d'acabar amb "${i.suffix}"`;if("includes"===i.format)return`Format inv\xe0lid: ha d'incloure "${i.includes}"`;if("regex"===i.format)return`Format inv\xe0lid: ha de coincidir amb el patr\xf3 ${i.pattern}`;return`Format inv\xe0lid per a ${t[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe0lid: ha de ser m\xfaltiple de ${i.divisor}`;case"unrecognized_keys":return`Clau${i.keys.length>1?"s":""} no reconeguda${i.keys.length>1?"s":""}: ${h(i.keys,", ")}`;case"invalid_key":return`Clau inv\xe0lida a ${i.origin}`;case"invalid_union":default:return"Entrada invàlida";case"invalid_element":return`Element inv\xe0lid a ${i.origin}`}})}},"cs",0,function(){let e,t;return{localeError:(e={string:{unit:"znaků",verb:"mít"},file:{unit:"bajtů",verb:"mít"},array:{unit:"prvků",verb:"mít"},set:{unit:"prvků",verb:"mít"}},t={regex:"regulární výraz",email:"e-mailová adresa",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"datum a čas ve formátu ISO",date:"datum ve formátu ISO",time:"čas ve formátu ISO",duration:"doba trvání ISO",ipv4:"IPv4 adresa",ipv6:"IPv6 adresa",cidrv4:"rozsah IPv4",cidrv6:"rozsah IPv6",base64:"řetězec zakódovaný ve formátu base64",base64url:"řetězec zakódovaný ve formátu base64url",json_string:"řetězec ve formátu JSON",e164:"číslo E.164",jwt:"JWT",template_literal:"vstup"},i=>{switch(i.code){case"invalid_type":return`Neplatn\xfd vstup: oček\xe1v\xe1no ${i.expected}, obdrženo ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"číslo";case"string":return"řetězec";case"boolean":return"boolean";case"bigint":return"bigint";case"function":return"funkce";case"symbol":return"symbol";case"undefined":return"undefined";case"object":if(Array.isArray(e))return"pole";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Neplatn\xfd vstup: oček\xe1v\xe1no ${E(i.values[0])}`;return`Neplatn\xe1 možnost: oček\xe1v\xe1na jedna z hodnot ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Hodnota je př\xedliš velk\xe1: ${i.origin??"hodnota"} mus\xed m\xedt ${t}${i.maximum.toString()} ${r.unit??"prvků"}`;return`Hodnota je př\xedliš velk\xe1: ${i.origin??"hodnota"} mus\xed b\xfdt ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Hodnota je př\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed m\xedt ${t}${i.minimum.toString()} ${r.unit??"prvků"}`;return`Hodnota je př\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed b\xfdt ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neplatn\xfd řetězec: mus\xed zač\xednat na "${i.prefix}"`;if("ends_with"===i.format)return`Neplatn\xfd řetězec: mus\xed končit na "${i.suffix}"`;if("includes"===i.format)return`Neplatn\xfd řetězec: mus\xed obsahovat "${i.includes}"`;if("regex"===i.format)return`Neplatn\xfd řetězec: mus\xed odpov\xeddat vzoru ${i.pattern}`;return`Neplatn\xfd form\xe1t ${t[i.format]??i.format}`;case"not_multiple_of":return`Neplatn\xe9 č\xedslo: mus\xed b\xfdt n\xe1sobkem ${i.divisor}`;case"unrecognized_keys":return`Nezn\xe1m\xe9 kl\xedče: ${h(i.keys,", ")}`;case"invalid_key":return`Neplatn\xfd kl\xedč v ${i.origin}`;case"invalid_union":default:return"Neplatný vstup";case"invalid_element":return`Neplatn\xe1 hodnota v ${i.origin}`}})}},"de",0,function(){let e,t;return{localeError:(e={string:{unit:"Zeichen",verb:"zu haben"},file:{unit:"Bytes",verb:"zu haben"},array:{unit:"Elemente",verb:"zu haben"},set:{unit:"Elemente",verb:"zu haben"}},t={regex:"Eingabe",email:"E-Mail-Adresse",url:"URL",emoji:"Emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-Datum und -Uhrzeit",date:"ISO-Datum",time:"ISO-Uhrzeit",duration:"ISO-Dauer",ipv4:"IPv4-Adresse",ipv6:"IPv6-Adresse",cidrv4:"IPv4-Bereich",cidrv6:"IPv6-Bereich",base64:"Base64-codierter String",base64url:"Base64-URL-codierter String",json_string:"JSON-String",e164:"E.164-Nummer",jwt:"JWT",template_literal:"Eingabe"},i=>{switch(i.code){case"invalid_type":return`Ung\xfcltige Eingabe: erwartet ${i.expected}, erhalten ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"Zahl";case"object":if(Array.isArray(e))return"Array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ung\xfcltige Eingabe: erwartet ${E(i.values[0])}`;return`Ung\xfcltige Option: erwartet eine von ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Zu gro\xdf: erwartet, dass ${i.origin??"Wert"} ${t}${i.maximum.toString()} ${r.unit??"Elemente"} hat`;return`Zu gro\xdf: erwartet, dass ${i.origin??"Wert"} ${t}${i.maximum.toString()} ist`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Zu klein: erwartet, dass ${i.origin} ${t}${i.minimum.toString()} ${r.unit} hat`;return`Zu klein: erwartet, dass ${i.origin} ${t}${i.minimum.toString()} ist`}case"invalid_format":if("starts_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.suffix}" enden`;if("includes"===i.format)return`Ung\xfcltiger String: muss "${i.includes}" enthalten`;if("regex"===i.format)return`Ung\xfcltiger String: muss dem Muster ${i.pattern} entsprechen`;return`Ung\xfcltig: ${t[i.format]??i.format}`;case"not_multiple_of":return`Ung\xfcltige Zahl: muss ein Vielfaches von ${i.divisor} sein`;case"unrecognized_keys":return`${i.keys.length>1?"Unbekannte Schlüssel":"Unbekannter Schlüssel"}: ${h(i.keys,", ")}`;case"invalid_key":return`Ung\xfcltiger Schl\xfcssel in ${i.origin}`;case"invalid_union":default:return"Ungültige Eingabe";case"invalid_element":return`Ung\xfcltiger Wert in ${i.origin}`}})}},"en",0,ed,"eo",0,function(){let e,t;return{localeError:(e={string:{unit:"karaktrojn",verb:"havi"},file:{unit:"bajtojn",verb:"havi"},array:{unit:"elementojn",verb:"havi"},set:{unit:"elementojn",verb:"havi"}},t={regex:"enigo",email:"retadreso",url:"URL",emoji:"emoĝio",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datotempo",date:"ISO-dato",time:"ISO-tempo",duration:"ISO-daŭro",ipv4:"IPv4-adreso",ipv6:"IPv6-adreso",cidrv4:"IPv4-rango",cidrv6:"IPv6-rango",base64:"64-ume kodita karaktraro",base64url:"URL-64-ume kodita karaktraro",json_string:"JSON-karaktraro",e164:"E.164-nombro",jwt:"JWT",template_literal:"enigo"},i=>{switch(i.code){case"invalid_type":return`Nevalida enigo: atendiĝis ${i.expected}, riceviĝis ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombro";case"object":if(Array.isArray(e))return"tabelo";if(null===e)return"senvalora";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Nevalida enigo: atendiĝis ${E(i.values[0])}`;return`Nevalida opcio: atendiĝis unu el ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Tro granda: atendiĝis ke ${i.origin??"valoro"} havu ${t}${i.maximum.toString()} ${r.unit??"elementojn"}`;return`Tro granda: atendiĝis ke ${i.origin??"valoro"} havu ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Tro malgranda: atendiĝis ke ${i.origin} havu ${t}${i.minimum.toString()} ${r.unit}`;return`Tro malgranda: atendiĝis ke ${i.origin} estu ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nevalida karaktraro: devas komenciĝi per "${i.prefix}"`;if("ends_with"===i.format)return`Nevalida karaktraro: devas finiĝi per "${i.suffix}"`;if("includes"===i.format)return`Nevalida karaktraro: devas inkluzivi "${i.includes}"`;if("regex"===i.format)return`Nevalida karaktraro: devas kongrui kun la modelo ${i.pattern}`;return`Nevalida ${t[i.format]??i.format}`;case"not_multiple_of":return`Nevalida nombro: devas esti oblo de ${i.divisor}`;case"unrecognized_keys":return`Nekonata${i.keys.length>1?"j":""} ŝlosilo${i.keys.length>1?"j":""}: ${h(i.keys,", ")}`;case"invalid_key":return`Nevalida ŝlosilo en ${i.origin}`;case"invalid_union":default:return"Nevalida enigo";case"invalid_element":return`Nevalida valoro en ${i.origin}`}})}},"es",0,function(){let e,t;return{localeError:(e={string:{unit:"caracteres",verb:"tener"},file:{unit:"bytes",verb:"tener"},array:{unit:"elementos",verb:"tener"},set:{unit:"elementos",verb:"tener"}},t={regex:"entrada",email:"dirección de correo electrónico",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"fecha y hora ISO",date:"fecha ISO",time:"hora ISO",duration:"duración ISO",ipv4:"dirección IPv4",ipv6:"dirección IPv6",cidrv4:"rango IPv4",cidrv6:"rango IPv6",base64:"cadena codificada en base64",base64url:"URL codificada en base64",json_string:"cadena JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Entrada inv\xe1lida: se esperaba ${i.expected}, recibido ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"número";case"object":if(Array.isArray(e))return"arreglo";if(null===e)return"nulo";if(Object.getPrototypeOf(e)!==Object.prototype)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: se esperaba ${E(i.values[0])}`;return`Opci\xf3n inv\xe1lida: se esperaba una de ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Demasiado grande: se esperaba que ${i.origin??"valor"} tuviera ${t}${i.maximum.toString()} ${r.unit??"elementos"}`;return`Demasiado grande: se esperaba que ${i.origin??"valor"} fuera ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Demasiado peque\xf1o: se esperaba que ${i.origin} tuviera ${t}${i.minimum.toString()} ${r.unit}`;return`Demasiado peque\xf1o: se esperaba que ${i.origin} fuera ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cadena inv\xe1lida: debe comenzar con "${i.prefix}"`;if("ends_with"===i.format)return`Cadena inv\xe1lida: debe terminar en "${i.suffix}"`;if("includes"===i.format)return`Cadena inv\xe1lida: debe incluir "${i.includes}"`;if("regex"===i.format)return`Cadena inv\xe1lida: debe coincidir con el patr\xf3n ${i.pattern}`;return`Inv\xe1lido ${t[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe1lido: debe ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Llave${i.keys.length>1?"s":""} desconocida${i.keys.length>1?"s":""}: ${h(i.keys,", ")}`;case"invalid_key":return`Llave inv\xe1lida en ${i.origin}`;case"invalid_union":default:return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido en ${i.origin}`}})}},"fa",0,function(){let e,t;return{localeError:(e={string:{unit:"کاراکتر",verb:"داشته باشد"},file:{unit:"بایت",verb:"داشته باشد"},array:{unit:"آیتم",verb:"داشته باشد"},set:{unit:"آیتم",verb:"داشته باشد"}},t={regex:"ورودی",email:"آدرس ایمیل",url:"URL",emoji:"ایموجی",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"تاریخ و زمان ایزو",date:"تاریخ ایزو",time:"زمان ایزو",duration:"مدت زمان ایزو",ipv4:"IPv4 آدرس",ipv6:"IPv6 آدرس",cidrv4:"IPv4 دامنه",cidrv6:"IPv6 دامنه",base64:"base64-encoded رشته",base64url:"base64url-encoded رشته",json_string:"JSON رشته",e164:"E.164 عدد",jwt:"JWT",template_literal:"ورودی"},i=>{switch(i.code){case"invalid_type":return`ورودی نامعتبر: می‌بایست ${i.expected} می‌بود، ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"عدد";case"object":if(Array.isArray(e))return"آرایه";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} دریافت شد`;case"invalid_value":if(1===i.values.length)return`ورودی نامعتبر: می‌بایست ${E(i.values[0])} می‌بود`;return`گزینه نامعتبر: می‌بایست یکی از ${h(i.values,"|")} می‌بود`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`خیلی بزرگ: ${i.origin??"مقدار"} باید ${t}${i.maximum.toString()} ${r.unit??"عنصر"} باشد`;return`خیلی بزرگ: ${i.origin??"مقدار"} باید ${t}${i.maximum.toString()} باشد`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`خیلی کوچک: ${i.origin} باید ${t}${i.minimum.toString()} ${r.unit} باشد`;return`خیلی کوچک: ${i.origin} باید ${t}${i.minimum.toString()} باشد`}case"invalid_format":if("starts_with"===i.format)return`رشته نامعتبر: باید با "${i.prefix}" شروع شود`;if("ends_with"===i.format)return`رشته نامعتبر: باید با "${i.suffix}" تمام شود`;if("includes"===i.format)return`رشته نامعتبر: باید شامل "${i.includes}" باشد`;if("regex"===i.format)return`رشته نامعتبر: باید با الگوی ${i.pattern} مطابقت داشته باشد`;return`${t[i.format]??i.format} نامعتبر`;case"not_multiple_of":return`عدد نامعتبر: باید مضرب ${i.divisor} باشد`;case"unrecognized_keys":return`کلید${i.keys.length>1?"های":""} ناشناس: ${h(i.keys,", ")}`;case"invalid_key":return`کلید ناشناس در ${i.origin}`;case"invalid_union":default:return"ورودی نامعتبر";case"invalid_element":return`مقدار نامعتبر در ${i.origin}`}})}},"fi",0,function(){let e,t;return{localeError:(e={string:{unit:"merkkiä",subject:"merkkijonon"},file:{unit:"tavua",subject:"tiedoston"},array:{unit:"alkiota",subject:"listan"},set:{unit:"alkiota",subject:"joukon"},number:{unit:"",subject:"luvun"},bigint:{unit:"",subject:"suuren kokonaisluvun"},int:{unit:"",subject:"kokonaisluvun"},date:{unit:"",subject:"päivämäärän"}},t={regex:"säännöllinen lauseke",email:"sähköpostiosoite",url:"URL-osoite",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-aikaleima",date:"ISO-päivämäärä",time:"ISO-aika",duration:"ISO-kesto",ipv4:"IPv4-osoite",ipv6:"IPv6-osoite",cidrv4:"IPv4-alue",cidrv6:"IPv6-alue",base64:"base64-koodattu merkkijono",base64url:"base64url-koodattu merkkijono",json_string:"JSON-merkkijono",e164:"E.164-luku",jwt:"JWT",template_literal:"templaattimerkkijono"},i=>{switch(i.code){case"invalid_type":return`Virheellinen tyyppi: odotettiin ${i.expected}, oli ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Virheellinen sy\xf6te: t\xe4ytyy olla ${E(i.values[0])}`;return`Virheellinen valinta: t\xe4ytyy olla yksi seuraavista: ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Liian suuri: ${r.subject} t\xe4ytyy olla ${t}${i.maximum.toString()} ${r.unit}`.trim();return`Liian suuri: arvon t\xe4ytyy olla ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Liian pieni: ${r.subject} t\xe4ytyy olla ${t}${i.minimum.toString()} ${r.unit}`.trim();return`Liian pieni: arvon t\xe4ytyy olla ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy alkaa "${i.prefix}"`;if("ends_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy loppua "${i.suffix}"`;if("includes"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy sis\xe4lt\xe4\xe4 "${i.includes}"`;if("regex"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy vastata s\xe4\xe4nn\xf6llist\xe4 lauseketta ${i.pattern}`;return`Virheellinen ${t[i.format]??i.format}`;case"not_multiple_of":return`Virheellinen luku: t\xe4ytyy olla luvun ${i.divisor} monikerta`;case"unrecognized_keys":return`${i.keys.length>1?"Tuntemattomat avaimet":"Tuntematon avain"}: ${h(i.keys,", ")}`;case"invalid_key":return"Virheellinen avain tietueessa";case"invalid_union":return"Virheellinen unioni";case"invalid_element":return"Virheellinen arvo joukossa";default:return"Virheellinen syöte"}})}},"fr",0,function(){let e,t;return{localeError:(e={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},t={regex:"entrée",email:"adresse e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"date et heure ISO",date:"date ISO",time:"heure ISO",duration:"durée ISO",ipv4:"adresse IPv4",ipv6:"adresse IPv6",cidrv4:"plage IPv4",cidrv6:"plage IPv6",base64:"chaîne encodée en base64",base64url:"chaîne encodée en base64url",json_string:"chaîne JSON",e164:"numéro E.164",jwt:"JWT",template_literal:"entrée"},i=>{switch(i.code){case"invalid_type":return`Entr\xe9e invalide : ${i.expected} attendu, ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombre";case"object":if(Array.isArray(e))return"tableau";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} re\xe7u`;case"invalid_value":if(1===i.values.length)return`Entr\xe9e invalide : ${E(i.values[0])} attendu`;return`Option invalide : une valeur parmi ${h(i.values,"|")} attendue`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Trop grand : ${i.origin??"valeur"} doit ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"élément(s)"}`;return`Trop grand : ${i.origin??"valeur"} doit \xeatre ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Trop petit : ${i.origin} doit ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Trop petit : ${i.origin} doit \xeatre ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au mod\xe8le ${i.pattern}`;return`${t[i.format]??i.format} invalide`;case"not_multiple_of":return`Nombre invalide : doit \xeatre un multiple de ${i.divisor}`;case"unrecognized_keys":return`Cl\xe9${i.keys.length>1?"s":""} non reconnue${i.keys.length>1?"s":""} : ${h(i.keys,", ")}`;case"invalid_key":return`Cl\xe9 invalide dans ${i.origin}`;case"invalid_union":default:return"Entrée invalide";case"invalid_element":return`Valeur invalide dans ${i.origin}`}})}},"frCA",0,function(){let e,t;return{localeError:(e={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},t={regex:"entrée",email:"adresse courriel",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"date-heure ISO",date:"date ISO",time:"heure ISO",duration:"durée ISO",ipv4:"adresse IPv4",ipv6:"adresse IPv6",cidrv4:"plage IPv4",cidrv6:"plage IPv6",base64:"chaîne encodée en base64",base64url:"chaîne encodée en base64url",json_string:"chaîne JSON",e164:"numéro E.164",jwt:"JWT",template_literal:"entrée"},i=>{switch(i.code){case"invalid_type":return`Entr\xe9e invalide : attendu ${i.expected}, re\xe7u ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entr\xe9e invalide : attendu ${E(i.values[0])}`;return`Option invalide : attendu l'une des valeurs suivantes ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"≤":"<",r=e[i.origin]??null;if(r)return`Trop grand : attendu que ${i.origin??"la valeur"} ait ${t}${i.maximum.toString()} ${r.unit}`;return`Trop grand : attendu que ${i.origin??"la valeur"} soit ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"≥":">",r=e[i.origin]??null;if(r)return`Trop petit : attendu que ${i.origin} ait ${t}${i.minimum.toString()} ${r.unit}`;return`Trop petit : attendu que ${i.origin} soit ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au motif ${i.pattern}`;return`${t[i.format]??i.format} invalide`;case"not_multiple_of":return`Nombre invalide : doit \xeatre un multiple de ${i.divisor}`;case"unrecognized_keys":return`Cl\xe9${i.keys.length>1?"s":""} non reconnue${i.keys.length>1?"s":""} : ${h(i.keys,", ")}`;case"invalid_key":return`Cl\xe9 invalide dans ${i.origin}`;case"invalid_union":default:return"Entrée invalide";case"invalid_element":return`Valeur invalide dans ${i.origin}`}})}},"he",0,function(){let e,t;return{localeError:(e={string:{unit:"אותיות",verb:"לכלול"},file:{unit:"בייטים",verb:"לכלול"},array:{unit:"פריטים",verb:"לכלול"},set:{unit:"פריטים",verb:"לכלול"}},t={regex:"קלט",email:"כתובת אימייל",url:"כתובת רשת",emoji:"אימוג'י",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"תאריך וזמן ISO",date:"תאריך ISO",time:"זמן ISO",duration:"משך זמן ISO",ipv4:"כתובת IPv4",ipv6:"כתובת IPv6",cidrv4:"טווח IPv4",cidrv6:"טווח IPv6",base64:"מחרוזת בבסיס 64",base64url:"מחרוזת בבסיס 64 לכתובות רשת",json_string:"מחרוזת JSON",e164:"מספר E.164",jwt:"JWT",template_literal:"קלט"},i=>{switch(i.code){case"invalid_type":return`קלט לא תקין: צריך ${i.expected}, התקבל ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`קלט לא תקין: צריך ${E(i.values[0])}`;return`קלט לא תקין: צריך אחת מהאפשרויות  ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`גדול מדי: ${i.origin??"value"} צריך להיות ${t}${i.maximum.toString()} ${r.unit??"elements"}`;return`גדול מדי: ${i.origin??"value"} צריך להיות ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`קטן מדי: ${i.origin} צריך להיות ${t}${i.minimum.toString()} ${r.unit}`;return`קטן מדי: ${i.origin} צריך להיות ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`מחרוזת לא תקינה: חייבת להתחיל ב"${i.prefix}"`;if("ends_with"===i.format)return`מחרוזת לא תקינה: חייבת להסתיים ב "${i.suffix}"`;if("includes"===i.format)return`מחרוזת לא תקינה: חייבת לכלול "${i.includes}"`;if("regex"===i.format)return`מחרוזת לא תקינה: חייבת להתאים לתבנית ${i.pattern}`;return`${t[i.format]??i.format} לא תקין`;case"not_multiple_of":return`מספר לא תקין: חייב להיות מכפלה של ${i.divisor}`;case"unrecognized_keys":return`מפתח${i.keys.length>1?"ות":""} לא מזוה${i.keys.length>1?"ים":"ה"}: ${h(i.keys,", ")}`;case"invalid_key":return`מפתח לא תקין ב${i.origin}`;case"invalid_union":default:return"קלט לא תקין";case"invalid_element":return`ערך לא תקין ב${i.origin}`}})}},"hu",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"legyen"},file:{unit:"byte",verb:"legyen"},array:{unit:"elem",verb:"legyen"},set:{unit:"elem",verb:"legyen"}},t={regex:"bemenet",email:"email cím",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO időbélyeg",date:"ISO dátum",time:"ISO idő",duration:"ISO időintervallum",ipv4:"IPv4 cím",ipv6:"IPv6 cím",cidrv4:"IPv4 tartomány",cidrv6:"IPv6 tartomány",base64:"base64-kódolt string",base64url:"base64url-kódolt string",json_string:"JSON string",e164:"E.164 szám",jwt:"JWT",template_literal:"bemenet"},i=>{switch(i.code){case"invalid_type":return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${i.expected}, a kapott \xe9rt\xe9k ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"szám";case"object":if(Array.isArray(e))return"tömb";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${E(i.values[0])}`;return`\xc9rv\xe9nytelen opci\xf3: valamelyik \xe9rt\xe9k v\xe1rt ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`T\xfal nagy: ${i.origin??"érték"} m\xe9rete t\xfal nagy ${t}${i.maximum.toString()} ${r.unit??"elem"}`;return`T\xfal nagy: a bemeneti \xe9rt\xe9k ${i.origin??"érték"} t\xfal nagy: ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} m\xe9rete t\xfal kicsi ${t}${i.minimum.toString()} ${r.unit}`;return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} t\xfal kicsi ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.prefix}" \xe9rt\xe9kkel kell kezdődnie`;if("ends_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.suffix}" \xe9rt\xe9kkel kell v\xe9gződnie`;if("includes"===i.format)return`\xc9rv\xe9nytelen string: "${i.includes}" \xe9rt\xe9ket kell tartalmaznia`;if("regex"===i.format)return`\xc9rv\xe9nytelen string: ${i.pattern} mint\xe1nak kell megfelelnie`;return`\xc9rv\xe9nytelen ${t[i.format]??i.format}`;case"not_multiple_of":return`\xc9rv\xe9nytelen sz\xe1m: ${i.divisor} t\xf6bbsz\xf6r\xf6s\xe9nek kell lennie`;case"unrecognized_keys":return`Ismeretlen kulcs${i.keys.length>1?"s":""}: ${h(i.keys,", ")}`;case"invalid_key":return`\xc9rv\xe9nytelen kulcs ${i.origin}`;case"invalid_union":default:return"Érvénytelen bemenet";case"invalid_element":return`\xc9rv\xe9nytelen \xe9rt\xe9k: ${i.origin}`}})}},"id",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"memiliki"},file:{unit:"byte",verb:"memiliki"},array:{unit:"item",verb:"memiliki"},set:{unit:"item",verb:"memiliki"}},t={regex:"input",email:"alamat email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tanggal dan waktu format ISO",date:"tanggal format ISO",time:"jam format ISO",duration:"durasi format ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",cidrv4:"rentang alamat IPv4",cidrv6:"rentang alamat IPv6",base64:"string dengan enkode base64",base64url:"string dengan enkode base64url",json_string:"string JSON",e164:"angka E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input tidak valid: diharapkan ${i.expected}, diterima ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input tidak valid: diharapkan ${E(i.values[0])}`;return`Pilihan tidak valid: diharapkan salah satu dari ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Terlalu besar: diharapkan ${i.origin??"value"} memiliki ${t}${i.maximum.toString()} ${r.unit??"elemen"}`;return`Terlalu besar: diharapkan ${i.origin??"value"} menjadi ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Terlalu kecil: diharapkan ${i.origin} memiliki ${t}${i.minimum.toString()} ${r.unit}`;return`Terlalu kecil: diharapkan ${i.origin} menjadi ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak valid: harus dimulai dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak valid: harus berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak valid: harus menyertakan "${i.includes}"`;if("regex"===i.format)return`String tidak valid: harus sesuai pola ${i.pattern}`;return`${t[i.format]??i.format} tidak valid`;case"not_multiple_of":return`Angka tidak valid: harus kelipatan dari ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali ${i.keys.length>1?"s":""}: ${h(i.keys,", ")}`;case"invalid_key":return`Kunci tidak valid di ${i.origin}`;case"invalid_union":default:return"Input tidak valid";case"invalid_element":return`Nilai tidak valid di ${i.origin}`}})}},"it",0,function(){let e,t;return{localeError:(e={string:{unit:"caratteri",verb:"avere"},file:{unit:"byte",verb:"avere"},array:{unit:"elementi",verb:"avere"},set:{unit:"elementi",verb:"avere"}},t={regex:"input",email:"indirizzo email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e ora ISO",date:"data ISO",time:"ora ISO",duration:"durata ISO",ipv4:"indirizzo IPv4",ipv6:"indirizzo IPv6",cidrv4:"intervallo IPv4",cidrv6:"intervallo IPv6",base64:"stringa codificata in base64",base64url:"URL codificata in base64",json_string:"stringa JSON",e164:"numero E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input non valido: atteso ${i.expected}, ricevuto ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"numero";case"object":if(Array.isArray(e))return"vettore";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input non valido: atteso ${E(i.values[0])}`;return`Opzione non valida: atteso uno tra ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Troppo grande: ${i.origin??"valore"} deve avere ${t}${i.maximum.toString()} ${r.unit??"elementi"}`;return`Troppo grande: ${i.origin??"valore"} deve essere ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Troppo piccolo: ${i.origin} deve avere ${t}${i.minimum.toString()} ${r.unit}`;return`Troppo piccolo: ${i.origin} deve essere ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Stringa non valida: deve iniziare con "${i.prefix}"`;if("ends_with"===i.format)return`Stringa non valida: deve terminare con "${i.suffix}"`;if("includes"===i.format)return`Stringa non valida: deve includere "${i.includes}"`;if("regex"===i.format)return`Stringa non valida: deve corrispondere al pattern ${i.pattern}`;return`Invalid ${t[i.format]??i.format}`;case"not_multiple_of":return`Numero non valido: deve essere un multiplo di ${i.divisor}`;case"unrecognized_keys":return`Chiav${i.keys.length>1?"i":"e"} non riconosciut${i.keys.length>1?"e":"a"}: ${h(i.keys,", ")}`;case"invalid_key":return`Chiave non valida in ${i.origin}`;case"invalid_union":default:return"Input non valido";case"invalid_element":return`Valore non valido in ${i.origin}`}})}},"ja",0,function(){let e,t;return{localeError:(e={string:{unit:"文字",verb:"である"},file:{unit:"バイト",verb:"である"},array:{unit:"要素",verb:"である"},set:{unit:"要素",verb:"である"}},t={regex:"入力値",email:"メールアドレス",url:"URL",emoji:"絵文字",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO日時",date:"ISO日付",time:"ISO時刻",duration:"ISO期間",ipv4:"IPv4アドレス",ipv6:"IPv6アドレス",cidrv4:"IPv4範囲",cidrv6:"IPv6範囲",base64:"base64エンコード文字列",base64url:"base64urlエンコード文字列",json_string:"JSON文字列",e164:"E.164番号",jwt:"JWT",template_literal:"入力値"},i=>{switch(i.code){case"invalid_type":return`無効な入力: ${i.expected}が期待されましたが、${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"数値";case"object":if(Array.isArray(e))return"配列";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}が入力されました`;case"invalid_value":if(1===i.values.length)return`無効な入力: ${E(i.values[0])}が期待されました`;return`無効な選択: ${h(i.values,"、")}のいずれかである必要があります`;case"too_big":{let t=i.inclusive?"以下である":"より小さい",r=e[i.origin]??null;if(r)return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${r.unit??"要素"}${t}必要があります`;return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${t}必要があります`}case"too_small":{let t=i.inclusive?"以上である":"より大きい",r=e[i.origin]??null;if(r)return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${r.unit}${t}必要があります`;return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${t}必要があります`}case"invalid_format":if("starts_with"===i.format)return`無効な文字列: "${i.prefix}"で始まる必要があります`;if("ends_with"===i.format)return`無効な文字列: "${i.suffix}"で終わる必要があります`;if("includes"===i.format)return`無効な文字列: "${i.includes}"を含む必要があります`;if("regex"===i.format)return`無効な文字列: パターン${i.pattern}に一致する必要があります`;return`無効な${t[i.format]??i.format}`;case"not_multiple_of":return`無効な数値: ${i.divisor}の倍数である必要があります`;case"unrecognized_keys":return`認識されていないキー${i.keys.length>1?"群":""}: ${h(i.keys,"、")}`;case"invalid_key":return`${i.origin}内の無効なキー`;case"invalid_union":default:return"無効な入力";case"invalid_element":return`${i.origin}内の無効な値`}})}},"kh",0,function(){let e,t;return{localeError:(e={string:{unit:"តួអក្សរ",verb:"គួរមាន"},file:{unit:"បៃ",verb:"គួរមាន"},array:{unit:"ធាតុ",verb:"គួរមាន"},set:{unit:"ធាតុ",verb:"គួរមាន"}},t={regex:"ទិន្នន័យបញ្ចូល",email:"អាសយដ្ឋានអ៊ីមែល",url:"URL",emoji:"សញ្ញាអារម្មណ៍",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"កាលបរិច្ឆេទ និងម៉ោង ISO",date:"កាលបរិច្ឆេទ ISO",time:"ម៉ោង ISO",duration:"រយៈពេល ISO",ipv4:"អាសយដ្ឋាន IPv4",ipv6:"អាសយដ្ឋាន IPv6",cidrv4:"ដែនអាសយដ្ឋាន IPv4",cidrv6:"ដែនអាសយដ្ឋាន IPv6",base64:"ខ្សែអក្សរអ៊ិកូដ base64",base64url:"ខ្សែអក្សរអ៊ិកូដ base64url",json_string:"ខ្សែអក្សរ JSON",e164:"លេខ E.164",jwt:"JWT",template_literal:"ទិន្នន័យបញ្ចូល"},i=>{switch(i.code){case"invalid_type":return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${i.expected} ប៉ុន្តែទទួលបាន ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"មិនមែនជាលេខ (NaN)":"លេខ";case"object":if(Array.isArray(e))return"អារេ (Array)";if(null===e)return"គ្មានតម្លៃ (null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${E(i.values[0])}`;return`ជម្រើសមិនត្រឹមត្រូវ៖ ត្រូវជាមួយក្នុងចំណោម ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${t} ${i.maximum.toString()} ${r.unit??"ធាតុ"}`;return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`តូចពេក៖ ត្រូវការ ${i.origin} ${t} ${i.minimum.toString()} ${r.unit}`;return`តូចពេក៖ ត្រូវការ ${i.origin} ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវចាប់ផ្តើមដោយ "${i.prefix}"`;if("ends_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវបញ្ចប់ដោយ "${i.suffix}"`;if("includes"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវមាន "${i.includes}"`;if("regex"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវតែផ្គូផ្គងនឹងទម្រង់ដែលបានកំណត់ ${i.pattern}`;return`មិនត្រឹមត្រូវ៖ ${t[i.format]??i.format}`;case"not_multiple_of":return`លេខមិនត្រឹមត្រូវ៖ ត្រូវតែជាពហុគុណនៃ ${i.divisor}`;case"unrecognized_keys":return`រកឃើញសោមិនស្គាល់៖ ${h(i.keys,", ")}`;case"invalid_key":return`សោមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`;case"invalid_union":default:return"ទិន្នន័យមិនត្រឹមត្រូវ";case"invalid_element":return`ទិន្នន័យមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`}})}},"ko",0,function(){let e,t;return{localeError:(e={string:{unit:"문자",verb:"to have"},file:{unit:"바이트",verb:"to have"},array:{unit:"개",verb:"to have"},set:{unit:"개",verb:"to have"}},t={regex:"입력",email:"이메일 주소",url:"URL",emoji:"이모지",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO 날짜시간",date:"ISO 날짜",time:"ISO 시간",duration:"ISO 기간",ipv4:"IPv4 주소",ipv6:"IPv6 주소",cidrv4:"IPv4 범위",cidrv6:"IPv6 범위",base64:"base64 인코딩 문자열",base64url:"base64url 인코딩 문자열",json_string:"JSON 문자열",e164:"E.164 번호",jwt:"JWT",template_literal:"입력"},i=>{switch(i.code){case"invalid_type":return`잘못된 입력: 예상 타입은 ${i.expected}, 받은 타입은 ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}입니다`;case"invalid_value":if(1===i.values.length)return`잘못된 입력: 값은 ${E(i.values[0])} 이어야 합니다`;return`잘못된 옵션: ${h(i.values,"또는 ")} 중 하나여야 합니다`;case"too_big":{let t=i.inclusive?"이하":"미만",r="미만"===t?"이어야 합니다":"여야 합니다",n=e[i.origin]??null,a=n?.unit??"요소";if(n)return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()}${a} ${t}${r}`;return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()} ${t}${r}`}case"too_small":{let t=i.inclusive?"이상":"초과",r="이상"===t?"이어야 합니다":"여야 합니다",n=e[i.origin]??null,a=n?.unit??"요소";if(n)return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()}${a} ${t}${r}`;return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()} ${t}${r}`}case"invalid_format":if("starts_with"===i.format)return`잘못된 문자열: "${i.prefix}"(으)로 시작해야 합니다`;if("ends_with"===i.format)return`잘못된 문자열: "${i.suffix}"(으)로 끝나야 합니다`;if("includes"===i.format)return`잘못된 문자열: "${i.includes}"을(를) 포함해야 합니다`;if("regex"===i.format)return`잘못된 문자열: 정규식 ${i.pattern} 패턴과 일치해야 합니다`;return`잘못된 ${t[i.format]??i.format}`;case"not_multiple_of":return`잘못된 숫자: ${i.divisor}의 배수여야 합니다`;case"unrecognized_keys":return`인식할 수 없는 키: ${h(i.keys,", ")}`;case"invalid_key":return`잘못된 키: ${i.origin}`;case"invalid_union":default:return"잘못된 입력";case"invalid_element":return`잘못된 값: ${i.origin}`}})}},"mk",0,function(){let e,t;return{localeError:(e={string:{unit:"знаци",verb:"да имаат"},file:{unit:"бајти",verb:"да имаат"},array:{unit:"ставки",verb:"да имаат"},set:{unit:"ставки",verb:"да имаат"}},t={regex:"внес",email:"адреса на е-пошта",url:"URL",emoji:"емоџи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO датум и време",date:"ISO датум",time:"ISO време",duration:"ISO времетраење",ipv4:"IPv4 адреса",ipv6:"IPv6 адреса",cidrv4:"IPv4 опсег",cidrv6:"IPv6 опсег",base64:"base64-енкодирана низа",base64url:"base64url-енкодирана низа",json_string:"JSON низа",e164:"E.164 број",jwt:"JWT",template_literal:"внес"},i=>{switch(i.code){case"invalid_type":return`Грешен внес: се очекува ${i.expected}, примено ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"број";case"object":if(Array.isArray(e))return"низа";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Invalid input: expected ${E(i.values[0])}`;return`Грешана опција: се очекува една ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Премногу голем: се очекува ${i.origin??"вредноста"} да има ${t}${i.maximum.toString()} ${r.unit??"елементи"}`;return`Премногу голем: се очекува ${i.origin??"вредноста"} да биде ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Премногу мал: се очекува ${i.origin} да има ${t}${i.minimum.toString()} ${r.unit}`;return`Премногу мал: се очекува ${i.origin} да биде ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неважечка низа: мора да започнува со "${i.prefix}"`;if("ends_with"===i.format)return`Неважечка низа: мора да завршува со "${i.suffix}"`;if("includes"===i.format)return`Неважечка низа: мора да вклучува "${i.includes}"`;if("regex"===i.format)return`Неважечка низа: мора да одгоара на патернот ${i.pattern}`;return`Invalid ${t[i.format]??i.format}`;case"not_multiple_of":return`Грешен број: мора да биде делив со ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Непрепознаени клучеви":"Непрепознаен клуч"}: ${h(i.keys,", ")}`;case"invalid_key":return`Грешен клуч во ${i.origin}`;case"invalid_union":default:return"Грешен внес";case"invalid_element":return`Грешна вредност во ${i.origin}`}})}},"ms",0,function(){let e,t;return{localeError:(e={string:{unit:"aksara",verb:"mempunyai"},file:{unit:"bait",verb:"mempunyai"},array:{unit:"elemen",verb:"mempunyai"},set:{unit:"elemen",verb:"mempunyai"}},t={regex:"input",email:"alamat e-mel",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tarikh masa ISO",date:"tarikh ISO",time:"masa ISO",duration:"tempoh ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",cidrv4:"julat IPv4",cidrv6:"julat IPv6",base64:"string dikodkan base64",base64url:"string dikodkan base64url",json_string:"string JSON",e164:"nombor E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input tidak sah: dijangka ${i.expected}, diterima ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombor";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input tidak sah: dijangka ${E(i.values[0])}`;return`Pilihan tidak sah: dijangka salah satu daripada ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Terlalu besar: dijangka ${i.origin??"nilai"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"elemen"}`;return`Terlalu besar: dijangka ${i.origin??"nilai"} adalah ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Terlalu kecil: dijangka ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Terlalu kecil: dijangka ${i.origin} adalah ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak sah: mesti bermula dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak sah: mesti berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak sah: mesti mengandungi "${i.includes}"`;if("regex"===i.format)return`String tidak sah: mesti sepadan dengan corak ${i.pattern}`;return`${t[i.format]??i.format} tidak sah`;case"not_multiple_of":return`Nombor tidak sah: perlu gandaan ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali: ${h(i.keys,", ")}`;case"invalid_key":return`Kunci tidak sah dalam ${i.origin}`;case"invalid_union":default:return"Input tidak sah";case"invalid_element":return`Nilai tidak sah dalam ${i.origin}`}})}},"nl",0,function(){let e,t;return{localeError:(e={string:{unit:"tekens"},file:{unit:"bytes"},array:{unit:"elementen"},set:{unit:"elementen"}},t={regex:"invoer",email:"emailadres",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum en tijd",date:"ISO datum",time:"ISO tijd",duration:"ISO duur",ipv4:"IPv4-adres",ipv6:"IPv6-adres",cidrv4:"IPv4-bereik",cidrv6:"IPv6-bereik",base64:"base64-gecodeerde tekst",base64url:"base64 URL-gecodeerde tekst",json_string:"JSON string",e164:"E.164-nummer",jwt:"JWT",template_literal:"invoer"},i=>{switch(i.code){case"invalid_type":return`Ongeldige invoer: verwacht ${i.expected}, ontving ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"getal";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ongeldige invoer: verwacht ${E(i.values[0])}`;return`Ongeldige optie: verwacht \xe9\xe9n van ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Te lang: verwacht dat ${i.origin??"waarde"} ${t}${i.maximum.toString()} ${r.unit??"elementen"} bevat`;return`Te lang: verwacht dat ${i.origin??"waarde"} ${t}${i.maximum.toString()} is`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Te kort: verwacht dat ${i.origin} ${t}${i.minimum.toString()} ${r.unit} bevat`;return`Te kort: verwacht dat ${i.origin} ${t}${i.minimum.toString()} is`}case"invalid_format":if("starts_with"===i.format)return`Ongeldige tekst: moet met "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ongeldige tekst: moet op "${i.suffix}" eindigen`;if("includes"===i.format)return`Ongeldige tekst: moet "${i.includes}" bevatten`;if("regex"===i.format)return`Ongeldige tekst: moet overeenkomen met patroon ${i.pattern}`;return`Ongeldig: ${t[i.format]??i.format}`;case"not_multiple_of":return`Ongeldig getal: moet een veelvoud van ${i.divisor} zijn`;case"unrecognized_keys":return`Onbekende key${i.keys.length>1?"s":""}: ${h(i.keys,", ")}`;case"invalid_key":return`Ongeldige key in ${i.origin}`;case"invalid_union":default:return"Ongeldige invoer";case"invalid_element":return`Ongeldige waarde in ${i.origin}`}})}},"no",0,function(){let e,t;return{localeError:(e={string:{unit:"tegn",verb:"å ha"},file:{unit:"bytes",verb:"å ha"},array:{unit:"elementer",verb:"å inneholde"},set:{unit:"elementer",verb:"å inneholde"}},t={regex:"input",email:"e-postadresse",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO dato- og klokkeslett",date:"ISO-dato",time:"ISO-klokkeslett",duration:"ISO-varighet",ipv4:"IPv4-område",ipv6:"IPv6-område",cidrv4:"IPv4-spekter",cidrv6:"IPv6-spekter",base64:"base64-enkodet streng",base64url:"base64url-enkodet streng",json_string:"JSON-streng",e164:"E.164-nummer",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Ugyldig input: forventet ${i.expected}, fikk ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"tall";case"object":if(Array.isArray(e))return"liste";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ugyldig verdi: forventet ${E(i.values[0])}`;return`Ugyldig valg: forventet en av ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${t}${i.maximum.toString()} ${r.unit??"elementer"}`;return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`For lite(n): forventet ${i.origin} til \xe5 ha ${t}${i.minimum.toString()} ${r.unit}`;return`For lite(n): forventet ${i.origin} til \xe5 ha ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ugyldig streng: m\xe5 starte med "${i.prefix}"`;if("ends_with"===i.format)return`Ugyldig streng: m\xe5 ende med "${i.suffix}"`;if("includes"===i.format)return`Ugyldig streng: m\xe5 inneholde "${i.includes}"`;if("regex"===i.format)return`Ugyldig streng: m\xe5 matche m\xf8nsteret ${i.pattern}`;return`Ugyldig ${t[i.format]??i.format}`;case"not_multiple_of":return`Ugyldig tall: m\xe5 v\xe6re et multiplum av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Ukjente nøkler":"Ukjent nøkkel"}: ${h(i.keys,", ")}`;case"invalid_key":return`Ugyldig n\xf8kkel i ${i.origin}`;case"invalid_union":default:return"Ugyldig input";case"invalid_element":return`Ugyldig verdi i ${i.origin}`}})}},"ota",0,function(){let e,t;return{localeError:(e={string:{unit:"harf",verb:"olmalıdır"},file:{unit:"bayt",verb:"olmalıdır"},array:{unit:"unsur",verb:"olmalıdır"},set:{unit:"unsur",verb:"olmalıdır"}},t={regex:"giren",email:"epostagâh",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO hengâmı",date:"ISO tarihi",time:"ISO zamanı",duration:"ISO müddeti",ipv4:"IPv4 nişânı",ipv6:"IPv6 nişânı",cidrv4:"IPv4 menzili",cidrv6:"IPv6 menzili",base64:"base64-şifreli metin",base64url:"base64url-şifreli metin",json_string:"JSON metin",e164:"E.164 sayısı",jwt:"JWT",template_literal:"giren"},i=>{switch(i.code){case"invalid_type":return`F\xe2sit giren: umulan ${i.expected}, alınan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"numara";case"object":if(Array.isArray(e))return"saf";if(null===e)return"gayb";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`F\xe2sit giren: umulan ${E(i.values[0])}`;return`F\xe2sit tercih: m\xfbteberler ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${t}${i.maximum.toString()} ${r.unit??"elements"} sahip olmalıydı.`;return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${t}${i.maximum.toString()} olmalıydı.`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${t}${i.minimum.toString()} ${r.unit} sahip olmalıydı.`;return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${t}${i.minimum.toString()} olmalıydı.`}case"invalid_format":if("starts_with"===i.format)return`F\xe2sit metin: "${i.prefix}" ile başlamalı.`;if("ends_with"===i.format)return`F\xe2sit metin: "${i.suffix}" ile bitmeli.`;if("includes"===i.format)return`F\xe2sit metin: "${i.includes}" ihtiv\xe2 etmeli.`;if("regex"===i.format)return`F\xe2sit metin: ${i.pattern} nakşına uymalı.`;return`F\xe2sit ${t[i.format]??i.format}`;case"not_multiple_of":return`F\xe2sit sayı: ${i.divisor} katı olmalıydı.`;case"unrecognized_keys":return`Tanınmayan anahtar ${i.keys.length>1?"s":""}: ${h(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7in tanınmayan anahtar var.`;case"invalid_union":return"Giren tanınamadı.";case"invalid_element":return`${i.origin} i\xe7in tanınmayan kıymet var.`;default:return"Kıymet tanınamadı."}})}},"pl",0,function(){let e,t;return{localeError:(e={string:{unit:"znaków",verb:"mieć"},file:{unit:"bajtów",verb:"mieć"},array:{unit:"elementów",verb:"mieć"},set:{unit:"elementów",verb:"mieć"}},t={regex:"wyrażenie",email:"adres email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i godzina w formacie ISO",date:"data w formacie ISO",time:"godzina w formacie ISO",duration:"czas trwania ISO",ipv4:"adres IPv4",ipv6:"adres IPv6",cidrv4:"zakres IPv4",cidrv6:"zakres IPv6",base64:"ciąg znaków zakodowany w formacie base64",base64url:"ciąg znaków zakodowany w formacie base64url",json_string:"ciąg znaków w formacie JSON",e164:"liczba E.164",jwt:"JWT",template_literal:"wejście"},i=>{switch(i.code){case"invalid_type":return`Nieprawidłowe dane wejściowe: oczekiwano ${i.expected}, otrzymano ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"liczba";case"object":if(Array.isArray(e))return"tablica";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Nieprawidłowe dane wejściowe: oczekiwano ${E(i.values[0])}`;return`Nieprawidłowa opcja: oczekiwano jednej z wartości ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Za duża wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${t}${i.maximum.toString()} ${r.unit??"elementów"}`;return`Zbyt duż(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Za mała wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${t}${i.minimum.toString()} ${r.unit??"elementów"}`;return`Zbyt mał(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zaczynać się od "${i.prefix}"`;if("ends_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi kończyć się na "${i.suffix}"`;if("includes"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zawierać "${i.includes}"`;if("regex"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi odpowiadać wzorcowi ${i.pattern}`;return`Nieprawidłow(y/a/e) ${t[i.format]??i.format}`;case"not_multiple_of":return`Nieprawidłowa liczba: musi być wielokrotnością ${i.divisor}`;case"unrecognized_keys":return`Nierozpoznane klucze${i.keys.length>1?"s":""}: ${h(i.keys,", ")}`;case"invalid_key":return`Nieprawidłowy klucz w ${i.origin}`;case"invalid_union":default:return"Nieprawidłowe dane wejściowe";case"invalid_element":return`Nieprawidłowa wartość w ${i.origin}`}})}},"ps",0,function(){let e,t;return{localeError:(e={string:{unit:"توکي",verb:"ولري"},file:{unit:"بایټس",verb:"ولري"},array:{unit:"توکي",verb:"ولري"},set:{unit:"توکي",verb:"ولري"}},t={regex:"ورودي",email:"بریښنالیک",url:"یو آر ال",emoji:"ایموجي",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"نیټه او وخت",date:"نېټه",time:"وخت",duration:"موده",ipv4:"د IPv4 پته",ipv6:"د IPv6 پته",cidrv4:"د IPv4 ساحه",cidrv6:"د IPv6 ساحه",base64:"base64-encoded متن",base64url:"base64url-encoded متن",json_string:"JSON متن",e164:"د E.164 شمېره",jwt:"JWT",template_literal:"ورودي"},i=>{switch(i.code){case"invalid_type":return`ناسم ورودي: باید ${i.expected} وای, مګر ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"عدد";case"object":if(Array.isArray(e))return"ارې";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} ترلاسه شو`;case"invalid_value":if(1===i.values.length)return`ناسم ورودي: باید ${E(i.values[0])} وای`;return`ناسم انتخاب: باید یو له ${h(i.values,"|")} څخه وای`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`ډیر لوی: ${i.origin??"ارزښت"} باید ${t}${i.maximum.toString()} ${r.unit??"عنصرونه"} ولري`;return`ډیر لوی: ${i.origin??"ارزښت"} باید ${t}${i.maximum.toString()} وي`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`ډیر کوچنی: ${i.origin} باید ${t}${i.minimum.toString()} ${r.unit} ولري`;return`ډیر کوچنی: ${i.origin} باید ${t}${i.minimum.toString()} وي`}case"invalid_format":if("starts_with"===i.format)return`ناسم متن: باید د "${i.prefix}" سره پیل شي`;if("ends_with"===i.format)return`ناسم متن: باید د "${i.suffix}" سره پای ته ورسيږي`;if("includes"===i.format)return`ناسم متن: باید "${i.includes}" ولري`;if("regex"===i.format)return`ناسم متن: باید د ${i.pattern} سره مطابقت ولري`;return`${t[i.format]??i.format} ناسم دی`;case"not_multiple_of":return`ناسم عدد: باید د ${i.divisor} مضرب وي`;case"unrecognized_keys":return`ناسم ${i.keys.length>1?"کلیډونه":"کلیډ"}: ${h(i.keys,", ")}`;case"invalid_key":return`ناسم کلیډ په ${i.origin} کې`;case"invalid_union":default:return"ناسمه ورودي";case"invalid_element":return`ناسم عنصر په ${i.origin} کې`}})}},"pt",0,function(){let e,t;return{localeError:(e={string:{unit:"caracteres",verb:"ter"},file:{unit:"bytes",verb:"ter"},array:{unit:"itens",verb:"ter"},set:{unit:"itens",verb:"ter"}},t={regex:"padrão",email:"endereço de e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e hora ISO",date:"data ISO",time:"hora ISO",duration:"duração ISO",ipv4:"endereço IPv4",ipv6:"endereço IPv6",cidrv4:"faixa de IPv4",cidrv6:"faixa de IPv6",base64:"texto codificado em base64",base64url:"URL codificada em base64",json_string:"texto JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Tipo inv\xe1lido: esperado ${i.expected}, recebido ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"número";case"object":if(Array.isArray(e))return"array";if(null===e)return"nulo";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: esperado ${E(i.values[0])}`;return`Op\xe7\xe3o inv\xe1lida: esperada uma das ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Muito grande: esperado que ${i.origin??"valor"} tivesse ${t}${i.maximum.toString()} ${r.unit??"elementos"}`;return`Muito grande: esperado que ${i.origin??"valor"} fosse ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Muito pequeno: esperado que ${i.origin} tivesse ${t}${i.minimum.toString()} ${r.unit}`;return`Muito pequeno: esperado que ${i.origin} fosse ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Texto inv\xe1lido: deve come\xe7ar com "${i.prefix}"`;if("ends_with"===i.format)return`Texto inv\xe1lido: deve terminar com "${i.suffix}"`;if("includes"===i.format)return`Texto inv\xe1lido: deve incluir "${i.includes}"`;if("regex"===i.format)return`Texto inv\xe1lido: deve corresponder ao padr\xe3o ${i.pattern}`;return`${t[i.format]??i.format} inv\xe1lido`;case"not_multiple_of":return`N\xfamero inv\xe1lido: deve ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Chave${i.keys.length>1?"s":""} desconhecida${i.keys.length>1?"s":""}: ${h(i.keys,", ")}`;case"invalid_key":return`Chave inv\xe1lida em ${i.origin}`;case"invalid_union":return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido em ${i.origin}`;default:return"Campo inválido"}})}},"ru",0,function(){let e,t;return{localeError:(e={string:{unit:{one:"символ",few:"символа",many:"символов"},verb:"иметь"},file:{unit:{one:"байт",few:"байта",many:"байт"},verb:"иметь"},array:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"},set:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"}},t={regex:"ввод",email:"email адрес",url:"URL",emoji:"эмодзи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO дата и время",date:"ISO дата",time:"ISO время",duration:"ISO длительность",ipv4:"IPv4 адрес",ipv6:"IPv6 адрес",cidrv4:"IPv4 диапазон",cidrv6:"IPv6 диапазон",base64:"строка в формате base64",base64url:"строка в формате base64url",json_string:"JSON строка",e164:"номер E.164",jwt:"JWT",template_literal:"ввод"},i=>{switch(i.code){case"invalid_type":return`Неверный ввод: ожидалось ${i.expected}, получено ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"число";case"object":if(Array.isArray(e))return"массив";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Неверный ввод: ожидалось ${E(i.values[0])}`;return`Неверный вариант: ожидалось одно из ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r){let e=iP(Number(i.maximum),r.unit.one,r.unit.few,r.unit.many);return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет иметь ${t}${i.maximum.toString()} ${e}`}return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r){let e=iP(Number(i.minimum),r.unit.one,r.unit.few,r.unit.many);return`Слишком маленькое значение: ожидалось, что ${i.origin} будет иметь ${t}${i.minimum.toString()} ${e}`}return`Слишком маленькое значение: ожидалось, что ${i.origin} будет ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неверная строка: должна начинаться с "${i.prefix}"`;if("ends_with"===i.format)return`Неверная строка: должна заканчиваться на "${i.suffix}"`;if("includes"===i.format)return`Неверная строка: должна содержать "${i.includes}"`;if("regex"===i.format)return`Неверная строка: должна соответствовать шаблону ${i.pattern}`;return`Неверный ${t[i.format]??i.format}`;case"not_multiple_of":return`Неверное число: должно быть кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспознанн${i.keys.length>1?"ые":"ый"} ключ${i.keys.length>1?"и":""}: ${h(i.keys,", ")}`;case"invalid_key":return`Неверный ключ в ${i.origin}`;case"invalid_union":default:return"Неверные входные данные";case"invalid_element":return`Неверное значение в ${i.origin}`}})}},"sl",0,function(){let e,t;return{localeError:(e={string:{unit:"znakov",verb:"imeti"},file:{unit:"bajtov",verb:"imeti"},array:{unit:"elementov",verb:"imeti"},set:{unit:"elementov",verb:"imeti"}},t={regex:"vnos",email:"e-poštni naslov",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum in čas",date:"ISO datum",time:"ISO čas",duration:"ISO trajanje",ipv4:"IPv4 naslov",ipv6:"IPv6 naslov",cidrv4:"obseg IPv4",cidrv6:"obseg IPv6",base64:"base64 kodiran niz",base64url:"base64url kodiran niz",json_string:"JSON niz",e164:"E.164 številka",jwt:"JWT",template_literal:"vnos"},i=>{switch(i.code){case"invalid_type":return`Neveljaven vnos: pričakovano ${i.expected}, prejeto ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"število";case"object":if(Array.isArray(e))return"tabela";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Neveljaven vnos: pričakovano ${E(i.values[0])}`;return`Neveljavna možnost: pričakovano eno izmed ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} imelo ${t}${i.maximum.toString()} ${r.unit??"elementov"}`;return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Premajhno: pričakovano, da bo ${i.origin} imelo ${t}${i.minimum.toString()} ${r.unit}`;return`Premajhno: pričakovano, da bo ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neveljaven niz: mora se začeti z "${i.prefix}"`;if("ends_with"===i.format)return`Neveljaven niz: mora se končati z "${i.suffix}"`;if("includes"===i.format)return`Neveljaven niz: mora vsebovati "${i.includes}"`;if("regex"===i.format)return`Neveljaven niz: mora ustrezati vzorcu ${i.pattern}`;return`Neveljaven ${t[i.format]??i.format}`;case"not_multiple_of":return`Neveljavno število: mora biti večkratnik ${i.divisor}`;case"unrecognized_keys":return`Neprepoznan${i.keys.length>1?"i ključi":" ključ"}: ${h(i.keys,", ")}`;case"invalid_key":return`Neveljaven ključ v ${i.origin}`;case"invalid_union":default:return"Neveljaven vnos";case"invalid_element":return`Neveljavna vrednost v ${i.origin}`}})}},"sv",0,function(){let e,t;return{localeError:(e={string:{unit:"tecken",verb:"att ha"},file:{unit:"bytes",verb:"att ha"},array:{unit:"objekt",verb:"att innehålla"},set:{unit:"objekt",verb:"att innehålla"}},t={regex:"reguljärt uttryck",email:"e-postadress",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datum och tid",date:"ISO-datum",time:"ISO-tid",duration:"ISO-varaktighet",ipv4:"IPv4-intervall",ipv6:"IPv6-intervall",cidrv4:"IPv4-spektrum",cidrv6:"IPv6-spektrum",base64:"base64-kodad sträng",base64url:"base64url-kodad sträng",json_string:"JSON-sträng",e164:"E.164-nummer",jwt:"JWT",template_literal:"mall-literal"},i=>{switch(i.code){case"invalid_type":return`Ogiltig inmatning: f\xf6rv\xe4ntat ${i.expected}, fick ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"antal";case"object":if(Array.isArray(e))return"lista";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ogiltig inmatning: f\xf6rv\xe4ntat ${E(i.values[0])}`;return`Ogiltigt val: f\xf6rv\xe4ntade en av ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`F\xf6r stor(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.maximum.toString()} ${r.unit??"element"}`;return`F\xf6r stor(t): f\xf6rv\xe4ntat ${i.origin??"värdet"} att ha ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.minimum.toString()} ${r.unit}`;return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste b\xf6rja med "${i.prefix}"`;if("ends_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste sluta med "${i.suffix}"`;if("includes"===i.format)return`Ogiltig str\xe4ng: m\xe5ste inneh\xe5lla "${i.includes}"`;if("regex"===i.format)return`Ogiltig str\xe4ng: m\xe5ste matcha m\xf6nstret "${i.pattern}"`;return`Ogiltig(t) ${t[i.format]??i.format}`;case"not_multiple_of":return`Ogiltigt tal: m\xe5ste vara en multipel av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Okända nycklar":"Okänd nyckel"}: ${h(i.keys,", ")}`;case"invalid_key":return`Ogiltig nyckel i ${i.origin??"värdet"}`;case"invalid_union":default:return"Ogiltig input";case"invalid_element":return`Ogiltigt v\xe4rde i ${i.origin??"värdet"}`}})}},"ta",0,function(){let e,t;return{localeError:(e={string:{unit:"எழுத்துக்கள்",verb:"கொண்டிருக்க வேண்டும்"},file:{unit:"பைட்டுகள்",verb:"கொண்டிருக்க வேண்டும்"},array:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"},set:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"}},t={regex:"உள்ளீடு",email:"மின்னஞ்சல் முகவரி",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO தேதி நேரம்",date:"ISO தேதி",time:"ISO நேரம்",duration:"ISO கால அளவு",ipv4:"IPv4 முகவரி",ipv6:"IPv6 முகவரி",cidrv4:"IPv4 வரம்பு",cidrv6:"IPv6 வரம்பு",base64:"base64-encoded சரம்",base64url:"base64url-encoded சரம்",json_string:"JSON சரம்",e164:"E.164 எண்",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது ${i.expected}, பெறப்பட்டது ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"எண் அல்லாதது":"எண்";case"object":if(Array.isArray(e))return"அணி";if(null===e)return"வெறுமை";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது ${E(i.values[0])}`;return`தவறான விருப்பம்: எதிர்பார்க்கப்பட்டது ${h(i.values,"|")} இல் ஒன்று`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`மிக பெரியது: எதிர்பார்க்கப்பட்டது ${i.origin??"மதிப்பு"} ${t}${i.maximum.toString()} ${r.unit??"உறுப்புகள்"} ஆக இருக்க வேண்டும்`;return`மிக பெரியது: எதிர்பார்க்கப்பட்டது ${i.origin??"மதிப்பு"} ${t}${i.maximum.toString()} ஆக இருக்க வேண்டும்`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${t}${i.minimum.toString()} ${r.unit} ஆக இருக்க வேண்டும்`;return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${t}${i.minimum.toString()} ஆக இருக்க வேண்டும்`}case"invalid_format":if("starts_with"===i.format)return`தவறான சரம்: "${i.prefix}" இல் தொடங்க வேண்டும்`;if("ends_with"===i.format)return`தவறான சரம்: "${i.suffix}" இல் முடிவடைய வேண்டும்`;if("includes"===i.format)return`தவறான சரம்: "${i.includes}" ஐ உள்ளடக்க வேண்டும்`;if("regex"===i.format)return`தவறான சரம்: ${i.pattern} முறைபாட்டுடன் பொருந்த வேண்டும்`;return`தவறான ${t[i.format]??i.format}`;case"not_multiple_of":return`தவறான எண்: ${i.divisor} இன் பலமாக இருக்க வேண்டும்`;case"unrecognized_keys":return`அடையாளம் தெரியாத விசை${i.keys.length>1?"கள்":""}: ${h(i.keys,", ")}`;case"invalid_key":return`${i.origin} இல் தவறான விசை`;case"invalid_union":default:return"தவறான உள்ளீடு";case"invalid_element":return`${i.origin} இல் தவறான மதிப்பு`}})}},"th",0,function(){let e,t;return{localeError:(e={string:{unit:"ตัวอักษร",verb:"ควรมี"},file:{unit:"ไบต์",verb:"ควรมี"},array:{unit:"รายการ",verb:"ควรมี"},set:{unit:"รายการ",verb:"ควรมี"}},t={regex:"ข้อมูลที่ป้อน",email:"ที่อยู่อีเมล",url:"URL",emoji:"อิโมจิ",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"วันที่เวลาแบบ ISO",date:"วันที่แบบ ISO",time:"เวลาแบบ ISO",duration:"ช่วงเวลาแบบ ISO",ipv4:"ที่อยู่ IPv4",ipv6:"ที่อยู่ IPv6",cidrv4:"ช่วง IP แบบ IPv4",cidrv6:"ช่วง IP แบบ IPv6",base64:"ข้อความแบบ Base64",base64url:"ข้อความแบบ Base64 สำหรับ URL",json_string:"ข้อความแบบ JSON",e164:"เบอร์โทรศัพท์ระหว่างประเทศ (E.164)",jwt:"โทเคน JWT",template_literal:"ข้อมูลที่ป้อน"},i=>{switch(i.code){case"invalid_type":return`ประเภทข้อมูลไม่ถูกต้อง: ควรเป็น ${i.expected} แต่ได้รับ ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"ไม่ใช่ตัวเลข (NaN)":"ตัวเลข";case"object":if(Array.isArray(e))return"อาร์เรย์ (Array)";if(null===e)return"ไม่มีค่า (null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`ค่าไม่ถูกต้อง: ควรเป็น ${E(i.values[0])}`;return`ตัวเลือกไม่ถูกต้อง: ควรเป็นหนึ่งใน ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"ไม่เกิน":"น้อยกว่า",r=e[i.origin]??null;if(r)return`เกินกำหนด: ${i.origin??"ค่า"} ควรมี${t} ${i.maximum.toString()} ${r.unit??"รายการ"}`;return`เกินกำหนด: ${i.origin??"ค่า"} ควรมี${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"อย่างน้อย":"มากกว่า",r=e[i.origin]??null;if(r)return`น้อยกว่ากำหนด: ${i.origin} ควรมี${t} ${i.minimum.toString()} ${r.unit}`;return`น้อยกว่ากำหนด: ${i.origin} ควรมี${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องขึ้นต้นด้วย "${i.prefix}"`;if("ends_with"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องลงท้ายด้วย "${i.suffix}"`;if("includes"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องมี "${i.includes}" อยู่ในข้อความ`;if("regex"===i.format)return`รูปแบบไม่ถูกต้อง: ต้องตรงกับรูปแบบที่กำหนด ${i.pattern}`;return`รูปแบบไม่ถูกต้อง: ${t[i.format]??i.format}`;case"not_multiple_of":return`ตัวเลขไม่ถูกต้อง: ต้องเป็นจำนวนที่หารด้วย ${i.divisor} ได้ลงตัว`;case"unrecognized_keys":return`พบคีย์ที่ไม่รู้จัก: ${h(i.keys,", ")}`;case"invalid_key":return`คีย์ไม่ถูกต้องใน ${i.origin}`;case"invalid_union":return"ข้อมูลไม่ถูกต้อง: ไม่ตรงกับรูปแบบยูเนียนที่กำหนดไว้";case"invalid_element":return`ข้อมูลไม่ถูกต้องใน ${i.origin}`;default:return"ข้อมูลไม่ถูกต้อง"}})}},"tr",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"olmalı"},file:{unit:"bayt",verb:"olmalı"},array:{unit:"öğe",verb:"olmalı"},set:{unit:"öğe",verb:"olmalı"}},t={regex:"girdi",email:"e-posta adresi",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO tarih ve saat",date:"ISO tarih",time:"ISO saat",duration:"ISO süre",ipv4:"IPv4 adresi",ipv6:"IPv6 adresi",cidrv4:"IPv4 aralığı",cidrv6:"IPv6 aralığı",base64:"base64 ile şifrelenmiş metin",base64url:"base64url ile şifrelenmiş metin",json_string:"JSON dizesi",e164:"E.164 sayısı",jwt:"JWT",template_literal:"Şablon dizesi"},i=>{switch(i.code){case"invalid_type":return`Ge\xe7ersiz değer: beklenen ${i.expected}, alınan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ge\xe7ersiz değer: beklenen ${E(i.values[0])}`;return`Ge\xe7ersiz se\xe7enek: aşağıdakilerden biri olmalı: ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${t}${i.maximum.toString()} ${r.unit??"öğe"}`;return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${t}${i.minimum.toString()} ${r.unit}`;return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ge\xe7ersiz metin: "${i.prefix}" ile başlamalı`;if("ends_with"===i.format)return`Ge\xe7ersiz metin: "${i.suffix}" ile bitmeli`;if("includes"===i.format)return`Ge\xe7ersiz metin: "${i.includes}" i\xe7ermeli`;if("regex"===i.format)return`Ge\xe7ersiz metin: ${i.pattern} desenine uymalı`;return`Ge\xe7ersiz ${t[i.format]??i.format}`;case"not_multiple_of":return`Ge\xe7ersiz sayı: ${i.divisor} ile tam b\xf6l\xfcnebilmeli`;case"unrecognized_keys":return`Tanınmayan anahtar${i.keys.length>1?"lar":""}: ${h(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7inde ge\xe7ersiz anahtar`;case"invalid_union":default:return"Geçersiz değer";case"invalid_element":return`${i.origin} i\xe7inde ge\xe7ersiz değer`}})}},"ua",0,function(){let e,t;return{localeError:(e={string:{unit:"символів",verb:"матиме"},file:{unit:"байтів",verb:"матиме"},array:{unit:"елементів",verb:"матиме"},set:{unit:"елементів",verb:"матиме"}},t={regex:"вхідні дані",email:"адреса електронної пошти",url:"URL",emoji:"емодзі",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"дата та час ISO",date:"дата ISO",time:"час ISO",duration:"тривалість ISO",ipv4:"адреса IPv4",ipv6:"адреса IPv6",cidrv4:"діапазон IPv4",cidrv6:"діапазон IPv6",base64:"рядок у кодуванні base64",base64url:"рядок у кодуванні base64url",json_string:"рядок JSON",e164:"номер E.164",jwt:"JWT",template_literal:"вхідні дані"},i=>{switch(i.code){case"invalid_type":return`Неправильні вхідні дані: очікується ${i.expected}, отримано ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"число";case"object":if(Array.isArray(e))return"масив";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Неправильні вхідні дані: очікується ${E(i.values[0])}`;return`Неправильна опція: очікується одне з ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Занадто велике: очікується, що ${i.origin??"значення"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"елементів"}`;return`Занадто велике: очікується, що ${i.origin??"значення"} буде ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Занадто мале: очікується, що ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Занадто мале: очікується, що ${i.origin} буде ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неправильний рядок: повинен починатися з "${i.prefix}"`;if("ends_with"===i.format)return`Неправильний рядок: повинен закінчуватися на "${i.suffix}"`;if("includes"===i.format)return`Неправильний рядок: повинен містити "${i.includes}"`;if("regex"===i.format)return`Неправильний рядок: повинен відповідати шаблону ${i.pattern}`;return`Неправильний ${t[i.format]??i.format}`;case"not_multiple_of":return`Неправильне число: повинно бути кратним ${i.divisor}`;case"unrecognized_keys":return`Нерозпізнаний ключ${i.keys.length>1?"і":""}: ${h(i.keys,", ")}`;case"invalid_key":return`Неправильний ключ у ${i.origin}`;case"invalid_union":default:return"Неправильні вхідні дані";case"invalid_element":return`Неправильне значення у ${i.origin}`}})}},"ur",0,function(){let e,t;return{localeError:(e={string:{unit:"حروف",verb:"ہونا"},file:{unit:"بائٹس",verb:"ہونا"},array:{unit:"آئٹمز",verb:"ہونا"},set:{unit:"آئٹمز",verb:"ہونا"}},t={regex:"ان پٹ",email:"ای میل ایڈریس",url:"یو آر ایل",emoji:"ایموجی",uuid:"یو یو آئی ڈی",uuidv4:"یو یو آئی ڈی وی 4",uuidv6:"یو یو آئی ڈی وی 6",nanoid:"نینو آئی ڈی",guid:"جی یو آئی ڈی",cuid:"سی یو آئی ڈی",cuid2:"سی یو آئی ڈی 2",ulid:"یو ایل آئی ڈی",xid:"ایکس آئی ڈی",ksuid:"کے ایس یو آئی ڈی",datetime:"آئی ایس او ڈیٹ ٹائم",date:"آئی ایس او تاریخ",time:"آئی ایس او وقت",duration:"آئی ایس او مدت",ipv4:"آئی پی وی 4 ایڈریس",ipv6:"آئی پی وی 6 ایڈریس",cidrv4:"آئی پی وی 4 رینج",cidrv6:"آئی پی وی 6 رینج",base64:"بیس 64 ان کوڈڈ سٹرنگ",base64url:"بیس 64 یو آر ایل ان کوڈڈ سٹرنگ",json_string:"جے ایس او این سٹرنگ",e164:"ای 164 نمبر",jwt:"جے ڈبلیو ٹی",template_literal:"ان پٹ"},i=>{switch(i.code){case"invalid_type":return`غلط ان پٹ: ${i.expected} متوقع تھا، ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"نمبر";case"object":if(Array.isArray(e))return"آرے";if(null===e)return"نل";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} موصول ہوا`;case"invalid_value":if(1===i.values.length)return`غلط ان پٹ: ${E(i.values[0])} متوقع تھا`;return`غلط آپشن: ${h(i.values,"|")} میں سے ایک متوقع تھا`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`بہت بڑا: ${i.origin??"ویلیو"} کے ${t}${i.maximum.toString()} ${r.unit??"عناصر"} ہونے متوقع تھے`;return`بہت بڑا: ${i.origin??"ویلیو"} کا ${t}${i.maximum.toString()} ہونا متوقع تھا`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`بہت چھوٹا: ${i.origin} کے ${t}${i.minimum.toString()} ${r.unit} ہونے متوقع تھے`;return`بہت چھوٹا: ${i.origin} کا ${t}${i.minimum.toString()} ہونا متوقع تھا`}case"invalid_format":if("starts_with"===i.format)return`غلط سٹرنگ: "${i.prefix}" سے شروع ہونا چاہیے`;if("ends_with"===i.format)return`غلط سٹرنگ: "${i.suffix}" پر ختم ہونا چاہیے`;if("includes"===i.format)return`غلط سٹرنگ: "${i.includes}" شامل ہونا چاہیے`;if("regex"===i.format)return`غلط سٹرنگ: پیٹرن ${i.pattern} سے میچ ہونا چاہیے`;return`غلط ${t[i.format]??i.format}`;case"not_multiple_of":return`غلط نمبر: ${i.divisor} کا مضاعف ہونا چاہیے`;case"unrecognized_keys":return`غیر تسلیم شدہ کی${i.keys.length>1?"ز":""}: ${h(i.keys,"، ")}`;case"invalid_key":return`${i.origin} میں غلط کی`;case"invalid_union":default:return"غلط ان پٹ";case"invalid_element":return`${i.origin} میں غلط ویلیو`}})}},"vi",0,function(){let e,t;return{localeError:(e={string:{unit:"ký tự",verb:"có"},file:{unit:"byte",verb:"có"},array:{unit:"phần tử",verb:"có"},set:{unit:"phần tử",verb:"có"}},t={regex:"đầu vào",email:"địa chỉ email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ngày giờ ISO",date:"ngày ISO",time:"giờ ISO",duration:"khoảng thời gian ISO",ipv4:"địa chỉ IPv4",ipv6:"địa chỉ IPv6",cidrv4:"dải IPv4",cidrv6:"dải IPv6",base64:"chuỗi mã hóa base64",base64url:"chuỗi mã hóa base64url",json_string:"chuỗi JSON",e164:"số E.164",jwt:"JWT",template_literal:"đầu vào"},i=>{switch(i.code){case"invalid_type":return`Đầu v\xe0o kh\xf4ng hợp lệ: mong đợi ${i.expected}, nhận được ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"số";case"object":if(Array.isArray(e))return"mảng";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Đầu v\xe0o kh\xf4ng hợp lệ: mong đợi ${E(i.values[0])}`;return`T\xf9y chọn kh\xf4ng hợp lệ: mong đợi một trong c\xe1c gi\xe1 trị ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Qu\xe1 lớn: mong đợi ${i.origin??"giá trị"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"phần tử"}`;return`Qu\xe1 lớn: mong đợi ${i.origin??"giá trị"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Qu\xe1 nhỏ: mong đợi ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Qu\xe1 nhỏ: mong đợi ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải bắt đầu bằng "${i.prefix}"`;if("ends_with"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải kết th\xfac bằng "${i.suffix}"`;if("includes"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải bao gồm "${i.includes}"`;if("regex"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải khớp với mẫu ${i.pattern}`;return`${t[i.format]??i.format} kh\xf4ng hợp lệ`;case"not_multiple_of":return`Số kh\xf4ng hợp lệ: phải l\xe0 bội số của ${i.divisor}`;case"unrecognized_keys":return`Kh\xf3a kh\xf4ng được nhận dạng: ${h(i.keys,", ")}`;case"invalid_key":return`Kh\xf3a kh\xf4ng hợp lệ trong ${i.origin}`;case"invalid_union":default:return"Đầu vào không hợp lệ";case"invalid_element":return`Gi\xe1 trị kh\xf4ng hợp lệ trong ${i.origin}`}})}},"zhCN",0,function(){let e,t;return{localeError:(e={string:{unit:"字符",verb:"包含"},file:{unit:"字节",verb:"包含"},array:{unit:"项",verb:"包含"},set:{unit:"项",verb:"包含"}},t={regex:"输入",email:"电子邮件",url:"URL",emoji:"表情符号",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO日期时间",date:"ISO日期",time:"ISO时间",duration:"ISO时长",ipv4:"IPv4地址",ipv6:"IPv6地址",cidrv4:"IPv4网段",cidrv6:"IPv6网段",base64:"base64编码字符串",base64url:"base64url编码字符串",json_string:"JSON字符串",e164:"E.164号码",jwt:"JWT",template_literal:"输入"},i=>{switch(i.code){case"invalid_type":return`无效输入：期望 ${i.expected}，实际接收 ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"非数字(NaN)":"数字";case"object":if(Array.isArray(e))return"数组";if(null===e)return"空值(null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`无效输入：期望 ${E(i.values[0])}`;return`无效选项：期望以下之一 ${h(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`数值过大：期望 ${i.origin??"值"} ${t}${i.maximum.toString()} ${r.unit??"个元素"}`;return`数值过大：期望 ${i.origin??"值"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`数值过小：期望 ${i.origin} ${t}${i.minimum.toString()} ${r.unit}`;return`数值过小：期望 ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`无效字符串：必须以 "${i.prefix}" 开头`;if("ends_with"===i.format)return`无效字符串：必须以 "${i.suffix}" 结尾`;if("includes"===i.format)return`无效字符串：必须包含 "${i.includes}"`;if("regex"===i.format)return`无效字符串：必须满足正则表达式 ${i.pattern}`;return`无效${t[i.format]??i.format}`;case"not_multiple_of":return`无效数字：必须是 ${i.divisor} 的倍数`;case"unrecognized_keys":return`出现未知的键(key): ${h(i.keys,", ")}`;case"invalid_key":return`${i.origin} 中的键(key)无效`;case"invalid_union":default:return"无效输入";case"invalid_element":return`${i.origin} 中包含无效值(value)`}})}},"zhTW",0,function(){let e,t;return{localeError:(e={string:{unit:"字元",verb:"擁有"},file:{unit:"位元組",verb:"擁有"},array:{unit:"項目",verb:"擁有"},set:{unit:"項目",verb:"擁有"}},t={regex:"輸入",email:"郵件地址",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO 日期時間",date:"ISO 日期",time:"ISO 時間",duration:"ISO 期間",ipv4:"IPv4 位址",ipv6:"IPv6 位址",cidrv4:"IPv4 範圍",cidrv6:"IPv6 範圍",base64:"base64 編碼字串",base64url:"base64url 編碼字串",json_string:"JSON 字串",e164:"E.164 數值",jwt:"JWT",template_literal:"輸入"},i=>{switch(i.code){case"invalid_type":return`無效的輸入值：預期為 ${i.expected}，但收到 ${(e=>{let t=typeof e;switch(t){case"number":return 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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3e9xqa9fyao1_.js b/litellm/proxy/_experimental/out/_next/static/chunks/3e9xqa9fyao1_.js
deleted file mode 100644
index 4ba613e3bff..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/3e9xqa9fyao1_.js
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3e9zq-pwz9-af.js b/litellm/proxy/_experimental/out/_next/static/chunks/3e9zq-pwz9-af.js
new file mode 100644
index 00000000000..115b1933b58
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/3e9zq-pwz9-af.js
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request)")}),(0,t.jsxs)("div",{className:"flex items-center gap-2",children:[(0,t.jsx)("span",{className:"text-muted-foreground",children:"$"}),(0,t.jsx)(x.Input,{id:"margin-fixed-amount",placeholder:"0.001",value:l,onChange:e=>c(e.target.value),className:"rounded-lg flex-1"})]})]}),(0,t.jsx)("div",{className:"flex items-center justify-end space-x-3 pt-6 border-t border-border",children:(0,t.jsx)(o.Button,{type:"submit",onClick:m,disabled:!s||"percentage"===r&&!a||"fixed"===r&&!l,children:"Add Provider Margin"})})]})})};var D=e.i(107233),R=e.i(552546),L=e.i(463059),E=e.i(487486),A=e.i(515288),z=e.i(772436),B=e.i(571303),I=e.i(500330),O=e.i(440160);let H=(0,e.i(475254).default)("file-spreadsheet",[["path",{d:"M15 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2V7Z",key:"1rqfz7"}],["path",{d:"M14 2v4a2 2 0 0 0 2 2h4",key:"tnqrlb"}],["path",{d:"M8 13h2",key:"yr2amv"}],["path",{d:"M14 13h2",key:"un5t4a"}],["path",{d:"M8 17h2",key:"2yhykz"}],["path",{d:"M14 17h2",key:"10kma7"}]]);var G=e.i(178583),U=e.i(755146);let V=e=>null==e?"-":0===e?"$0.00":e<.01?`$${e.toFixed(6)}`:e<1?`$${e.toFixed(4)}`:`$${(0,I.formatNumberWithCommas)(e,2)}`,W=e=>null==e?"-":(0,I.formatNumberWithCommas)(e,0),K=({multiResult:e})=>e.entries.some(e=>null!==e.result)?(0,t.jsxs)(U.DropdownMenu,{children:[(0,t.jsxs)(U.DropdownMenuTrigger,{className:(0,o.buttonVariants)({variant:"secondary",size:"xs"}),children:[(0,t.jsx)(O.Download,{}),"Export"]}),(0,t.jsxs)(U.DropdownMenuContent,{align:"end",className:"w-44",children:[(0,t.jsxs)(U.DropdownMenuItem,{onClick:()=>(e=>{let t=window.open("","_blank");if(!t)return void alert("Please allow popups to export PDF");let s=e.entries.filter(e=>null!==e.result),r=s.length,a=`
+    <!DOCTYPE html>
+    <html>
+    <head>
+      <title>Multi-Model Cost Estimate Report</title>
+      <style>
+        body {
+          font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
+          padding: 40px;
+          max-width: 900px;
+          margin: 0 auto;
+          color: #333;
+        }
+        h1 {
+          color: #1a1a1a;
+          border-bottom: 2px solid #1890ff;
+          padding-bottom: 10px;
+          margin-bottom: 30px;
+        }
+        h2 {
+          color: #444;
+          margin-top: 30px;
+          margin-bottom: 15px;
+        }
+        h3 {
+          color: #555;
+          margin-top: 25px;
+          margin-bottom: 10px;
+          padding-bottom: 5px;
+          border-bottom: 1px solid #eee;
+        }
+        .provider {
+          font-weight: normal;
+          color: #1890ff;
+          font-size: 14px;
+        }
+        .meta {
+          background: #f5f5f5;
+          padding: 12px 15px;
+          border-radius: 8px;
+          margin-bottom: 15px;
+          font-size: 13px;
+        }
+        .meta p {
+          margin: 4px 0;
+        }
+        table {
+          width: 100%;
+          border-collapse: collapse;
+          margin-bottom: 20px;
+        }
+        th, td {
+          padding: 10px 12px;
+          text-align: left;
+          border-bottom: 1px solid #ddd;
+        }
+        th {
+          background: #f8f9fa;
+          font-weight: 600;
+          font-size: 13px;
+        }
+        .cost-value {
+          font-family: monospace;
+          font-size: 13px;
+        }
+        .total-row {
+          font-weight: bold;
+          background: #e6f7ff;
+        }
+        .summary-box {
+          background: linear-gradient(135deg, #e6f7ff 0%, #f9f0ff 100%);
+          border: 1px solid #91d5ff;
+          border-radius: 8px;
+          padding: 20px;
+          margin-bottom: 30px;
+        }
+        .summary-box h2 {
+          margin-top: 0;
+          color: #1890ff;
+        }
+        .summary-grid {
+          display: grid;
+          grid-template-columns: repeat(3, 1fr);
+          gap: 20px;
+          margin-top: 15px;
+        }
+        .summary-item {
+          text-align: center;
+        }
+        .summary-item .label {
+          font-size: 12px;
+          color: #666;
+          margin-bottom: 5px;
+        }
+        .summary-item .value {
+          font-size: 20px;
+          font-weight: bold;
+          font-family: monospace;
+        }
+        .summary-item .value.blue { color: #1890ff; }
+        .summary-item .value.green { color: #52c41a; }
+        .summary-item .value.purple { color: #722ed1; }
+        .model-section {
+          margin-bottom: 30px;
+          page-break-inside: avoid;
+        }
+        .footer {
+          margin-top: 40px;
+          padding-top: 20px;
+          border-top: 1px solid #ddd;
+          font-size: 12px;
+          color: #666;
+        }
+        @media print {
+          body { padding: 20px; }
+          .model-section { page-break-inside: avoid; }
+        }
+      </style>
+    </head>
+    <body>
+      <h1>LLM Cost Estimate Report</h1>
+      <p style="color: #666; margin-top: -20px; margin-bottom: 30px;">${r} model${1!==r?"s":""} configured</p>
+      
+      <div class="summary-box">
+        <h2>Combined Totals</h2>
+        <div class="summary-grid">
+          <div class="summary-item">
+            <div class="label">Total Per Request</div>
+            <div class="value blue">${V(e.totals.cost_per_request)}</div>
+          </div>
+          <div class="summary-item">
+            <div class="label">Total Daily</div>
+            <div class="value green">${V(e.totals.daily_cost)}</div>
+          </div>
+          <div class="summary-item">
+            <div class="label">Total Monthly</div>
+            <div class="value purple">${V(e.totals.monthly_cost)}</div>
+          </div>
+        </div>
+        ${e.totals.margin_per_request>0?`
+        <div class="summary-grid" style="margin-top: 15px; padding-top: 15px; border-top: 1px solid #ddd;">
+          <div class="summary-item">
+            <div class="label">Margin/Request</div>
+            <div class="value" style="color: #faad14;">${V(e.totals.margin_per_request)}</div>
+          </div>
+          <div class="summary-item">
+            <div class="label">Daily Margin</div>
+            <div class="value" style="color: #faad14;">${V(e.totals.daily_margin)}</div>
+          </div>
+          <div class="summary-item">
+            <div class="label">Monthly Margin</div>
+            <div class="value" style="color: #faad14;">${V(e.totals.monthly_margin)}</div>
+          </div>
+        </div>
+        `:""}
+      </div>
+
+      <h2>Model Breakdown</h2>
+      ${s.map(e=>{let t;return t=e.result,`
+    <div class="model-section">
+      <h3>${t.model} ${t.provider?`<span class="provider">(${t.provider})</span>`:""}</h3>
+      
+      <div class="meta">
+        <p><strong>Input Tokens per Request:</strong> ${W(t.input_tokens)}</p>
+        <p><strong>Output Tokens per Request:</strong> ${W(t.output_tokens)}</p>
+        ${t.num_requests_per_day?`<p><strong>Requests per Day:</strong> ${W(t.num_requests_per_day)}</p>`:""}
+        ${t.num_requests_per_month?`<p><strong>Requests per Month:</strong> ${W(t.num_requests_per_month)}</p>`:""}
+      </div>
+
+      <table>
+        <tr>
+          <th>Cost Type</th>
+          <th>Per Request</th>
+          ${null!==t.daily_cost?"<th>Daily</th>":""}
+          ${null!==t.monthly_cost?"<th>Monthly</th>":""}
+        </tr>
+        <tr>
+          <td>Input Cost</td>
+          <td class="cost-value">${V(t.input_cost_per_request)}</td>
+          ${null!==t.daily_cost?`<td class="cost-value">${V(t.daily_input_cost)}</td>`:""}
+          ${null!==t.monthly_cost?`<td class="cost-value">${V(t.monthly_input_cost)}</td>`:""}
+        </tr>
+        <tr>
+          <td>Output Cost</td>
+          <td class="cost-value">${V(t.output_cost_per_request)}</td>
+          ${null!==t.daily_cost?`<td class="cost-value">${V(t.daily_output_cost)}</td>`:""}
+          ${null!==t.monthly_cost?`<td class="cost-value">${V(t.monthly_output_cost)}</td>`:""}
+        </tr>
+        <tr>
+          <td>Margin/Fee</td>
+          <td class="cost-value">${V(t.margin_cost_per_request)}</td>
+          ${null!==t.daily_cost?`<td class="cost-value">${V(t.daily_margin_cost)}</td>`:""}
+          ${null!==t.monthly_cost?`<td class="cost-value">${V(t.monthly_margin_cost)}</td>`:""}
+        </tr>
+        <tr class="total-row">
+          <td>Total</td>
+          <td class="cost-value">${V(t.cost_per_request)}</td>
+          ${null!==t.daily_cost?`<td class="cost-value">${V(t.daily_cost)}</td>`:""}
+          ${null!==t.monthly_cost?`<td class="cost-value">${V(t.monthly_cost)}</td>`:""}
+        </tr>
+      </table>
+    </div>
+  `}).join("")}
+
+      <div class="footer">
+        <p>Generated by LiteLLM Pricing Calculator on ${new Date().toLocaleString()}</p>
+      </div>
+    </body>
+    </html>
+  `;t.document.write(a),t.document.close(),t.onload=()=>{t.print()}})(e),children:[(0,t.jsx)(G.FileText,{}),"Export as PDF"]}),(0,t.jsxs)(U.DropdownMenuItem,{onClick:()=>(e=>{let t=e.entries.filter(e=>null!==e.result),s=[["LLM Multi-Model Cost Estimate Report"],["Generated",new Date().toLocaleString()],[""]];for(let r of(s.push(["COMBINED TOTALS"],["Total Per Request",e.totals.cost_per_request.toString()],["Total Daily",e.totals.daily_cost?.toString()||"-"],["Total Monthly",e.totals.monthly_cost?.toString()||"-"],["Margin Per Request",e.totals.margin_per_request.toString()],["Daily Margin",e.totals.daily_margin?.toString()||"-"],["Monthly Margin",e.totals.monthly_margin?.toString()||"-"],[""]),s.push(["Model","Provider","Input Tokens","Output Tokens","Requests/Day","Requests/Month","Cost/Request","Daily Cost","Monthly Cost","Input Cost/Req","Output Cost/Req","Margin/Req"]),t)){let 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$",(0,I.formatNumberWithCommas)(1e6*e.input_cost_per_token,2),"/1M"]}),e.input_cost_per_token&&e.output_cost_per_token&&" | ",e.output_cost_per_token&&(0,t.jsxs)("span",{children:["Output $",(0,I.formatNumberWithCommas)(1e6*e.output_cost_per_token,2),"/1M"]})]})]})},Z=({multiResult:e,timePeriod:a})=>{let[l,n]=(0,s.useState)(new Set),i=e.entries.filter(e=>null!==e.result),d=e.entries.filter(e=>e.loading),c=e.entries.filter(e=>null!==e.error),m=i.length>0,u=d.length>0,x=c.length>0;if(!m&&!u&&!x)return(0,t.jsx)("div",{className:"py-6 text-center border border-dashed border-border rounded-lg bg-muted",children:(0,t.jsx)("p",{className:"text-muted-foreground",children:"Select models above to see cost estimates"})});if(!m&&u&&!x)return(0,t.jsxs)("div",{className:"py-6 text-center",children:[(0,t.jsx)(B.UiLoadingSpinner,{className:"inline-block size-5"}),(0,t.jsx)("p",{className:"text-muted-foreground block mt-2",children:"Calculating 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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3fj6j4vgjqp_9.js b/litellm/proxy/_experimental/out/_next/static/chunks/3fj6j4vgjqp_9.js
new file mode 100644
index 00000000000..a9ce6d0ebd1
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/3fj6j4vgjqp_9.js
@@ -0,0 +1,50 @@
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+
+client = openai.OpenAI(
+    api_key="your_api_key",
+    base_url="${(0,b.getProxyBaseUrl)()}"  # Your LiteLLM Proxy URL
+)
+
+response = client.chat.completions.create(
+    model="${$.model_group}",
+    messages=[
+        {
+            "role": "user",
+            "content": "Hello, how are you?"
+        }
+    ]
+)
+
+print(response.choices[0].message.content)`})]})]})]})}),(0,s.jsx)(j.Dialog,{open:ep,onOpenChange:e=>!e&&eO(),children:(0,s.jsxs)(j.DialogContent,{className:"max-h-[calc(100dvh-2rem)] overflow-y-auto sm:max-w-[1000px]",children:[(0,s.jsx)(j.DialogHeader,{children:(0,s.jsx)(j.DialogTitle,{children:eu?.name||"Agent Details"})}),eu&&(0,s.jsxs)("div",{className:"space-y-6",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Agent Overview"}),(0,s.jsxs)("div",{className:"grid grid-cols-2 gap-4 mb-4",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Name:"}),(0,s.jsx)("p",{children:eu.name})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Version:"}),(0,s.jsxs)(d.Badge,{variant:"secondary",children:["v",eu.version]})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Protocol 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Date(eN.last_health_check).toLocaleString()})]})]}),eN.health_check_error&&(0,s.jsxs)("div",{className:"mt-2 p-2 bg-destructive/10 rounded-sm",children:[(0,s.jsx)("p",{className:"font-medium text-destructive",children:"Health Check Error:"}),(0,s.jsx)("p",{className:"text-sm text-destructive mt-1",children:eN.health_check_error})]})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Usage Example"}),(0,s.jsx)(Q.Prism,{language:"python",className:"text-sm",style:p,children:`from fastmcp import Client
+import asyncio
+
+# Standard MCP configuration
+config = {
+    "mcpServers": {
+        "${eN.server_name}": {
+            "url": "${(0,b.getProxyBaseUrl)()}/${eN.server_name}/mcp",
+            "headers": {
+                "x-litellm-api-key": "Bearer sk-1234"
+            }
+        }
+    }
+}
+
+# Create a client that connects to the server
+client = Client(config)
+
+async def main():
+    async with client:
+        # List available tools
+        tools = await client.list_tools()
+        print(f"Available tools: {[tool.name for tool in tools]}")
+
+        # Call a tool
+        response = await client.call_tool(
+            name="tool_name",
+            arguments={"arg": "value"}
+        )
+        print(f"Response: {response}")
+
+if __name__ == "__main__":
+    asyncio.run(main())`})]})]})]})}),(0,s.jsx)(M,{visible:ei,onClose:()=>er(!1),accessToken:e||"",modelHubData:y||[],onSuccess:()=>{e&&(async()=>{try{let s=await (0,b.modelHubCall)(e);w(s.data)}catch(e){console.error("Error refreshing model data:",e)}})()}}),(0,s.jsx)(N,{visible:eo,onClose:()=>ec(!1),accessToken:e||"",agentHubData:en||[],onSuccess:()=>{e&&(async()=>{try{let s=(await (0,b.getAgentsList)(e)).agents.map(e=>({agent_id:e.agent_id,...e.agent_card_params,is_public:e.is_public}));ed(s)}catch(e){console.error("Error refreshing agent data:",e)}})()}}),(0,s.jsx)(k,{visible:e_,onClose:()=>eC(!1),accessToken:e||"",mcpHubData:ej||[],onSuccess:()=>{e&&(async()=>{try{let s=await (0,b.fetchMCPServers)(e);eb(s)}catch(e){console.error("Error refreshing MCP server data:",e)}})()}}),(0,s.jsx)(V,{visible:eD,onClose:()=>ez(!1),accessToken:e||"",skillsList:eS,onSuccess:async()=>{eM((await (0,b.getClaudeCodePluginsList)(e||"",!0===a)).plugins)}})]})}],934879)}]);
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3gf77hvt6gpre.js b/litellm/proxy/_experimental/out/_next/static/chunks/3gf77hvt6gpre.js
deleted file mode 100644
index 9aa89a381b0..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/3gf77hvt6gpre.js
+++ /dev/null
@@ -1,89 +0,0 @@
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3ha3c8uqaqvm0.js b/litellm/proxy/_experimental/out/_next/static/chunks/3ha3c8uqaqvm0.js
deleted file mode 100644
index 6be774ef6a8..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/3ha3c8uqaqvm0.js
+++ /dev/null
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1sr2i5vwkuvkr.js b/litellm/proxy/_experimental/out/_next/static/chunks/3hddzevzq6_qk.js
similarity index 68%
rename from litellm/proxy/_experimental/out/_next/static/chunks/1sr2i5vwkuvkr.js
rename to litellm/proxy/_experimental/out/_next/static/chunks/3hddzevzq6_qk.js
index 66029192463..1a1f8c00c5d 100644
--- a/litellm/proxy/_experimental/out/_next/static/chunks/1sr2i5vwkuvkr.js
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deleted file mode 100644
index 612aca1da91..00000000000
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new file mode 100644
index 00000000000..0fa8a88eb4f
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+++ b/litellm/proxy/_experimental/out/_next/static/chunks/3kil-7y33kpm9.js
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0m-cn894wctv5.js b/litellm/proxy/_experimental/out/_next/static/chunks/3kpec-qy1uzod.js
similarity index 81%
rename from litellm/proxy/_experimental/out/_next/static/chunks/0m-cn894wctv5.js
rename to litellm/proxy/_experimental/out/_next/static/chunks/3kpec-qy1uzod.js
index 431a7cf7664..a1500ff758d 100644
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0m-cn894wctv5.js
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/3kpec-qy1uzod.js
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3n9tghryjtagp.js b/litellm/proxy/_experimental/out/_next/static/chunks/3n9tghryjtagp.js
deleted file mode 100644
index 9f1cd403ace..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/3n9tghryjtagp.js
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deleted file mode 100644
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-import asyncio
-
-# Standard MCP configuration
-config = {
-    "mcpServers": {
-        "${eb.server_name}": {
-            "url": "${(0,b.getProxyBaseUrl)()}/${eb.server_name}/mcp",
-            "headers": {
-                "x-litellm-api-key": "Bearer sk-1234"
-            }
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-    }
-}
-
-# Create a client that connects to the server
-client = Client(config)
-
-async def main():
-    async with client:
-        # List available tools
-        tools = await client.list_tools()
-        print(f"Available tools: {[tool.name for tool in tools]}")
-
-        # Call a tool
-        response = await client.call_tool(
-            name="tool_name",
-            arguments={"arg": "value"}
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-
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\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3ntnmo_hy-24i.js b/litellm/proxy/_experimental/out/_next/static/chunks/3ntnmo_hy-24i.js
new file mode 100644
index 00000000000..cf9ca935b0d
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/3ntnmo_hy-24i.js
@@ -0,0 +1 @@
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new file mode 100644
index 00000000000..0c449214052
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/3oqsdyd8r66px.js
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+    # inputs: {texts, images, tools, tool_calls, structured_messages, model}
+    # request_data: {model, user_id, team_id, end_user_id, metadata}
+    # input_type: "request" or "response"
+    return allow()`},blockSSN:{name:"Block SSN",code:`def apply_guardrail(inputs, request_data, input_type):
+    for text in inputs["texts"]:
+        if regex_match(text, r"\\d{3}-\\d{2}-\\d{4}"):
+            return block("SSN detected")
+    return allow()`},redactEmail:{name:"Redact Emails",code:`def apply_guardrail(inputs, request_data, input_type):
+    pattern = r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}"
+    modified = []
+    for text in inputs["texts"]:
+        modified.append(regex_replace(text, pattern, "[EMAIL REDACTED]"))
+    return modify(texts=modified)`},blockSQL:{name:"Block SQL Injection",code:`def apply_guardrail(inputs, request_data, input_type):
+    if input_type != "request":
+        return allow()
+    for text in inputs["texts"]:
+        if contains_code_language(text, ["sql"]):
+            return block("SQL code not allowed")
+    return allow()`},validateJSON:{name:"Validate JSON",code:`def apply_guardrail(inputs, request_data, input_type):
+    if input_type != "response":
+        return allow()
+    
+    schema = {"type": "object", "required": ["name", "value"]}
+    
+    for text in inputs["texts"]:
+        obj = json_parse(text)
+        if obj is None:
+            return block("Invalid JSON response")
+        if not json_schema_valid(obj, schema):
+            return block("Response missing required fields")
+    return allow()`},externalAPI:{name:"External API Check (async)",code:`async def apply_guardrail(inputs, request_data, input_type):
+    # Call an external moderation API (async for non-blocking)
+    for text in inputs["texts"]:
+        response = await http_post(
+            "https://api.example.com/moderate",
+            body={"text": text, "user_id": request_data["user_id"]},
+            headers={"Authorization": "Bearer YOUR_API_KEY"},
+            timeout=10
+        )
+        
+        if not response["success"]:
+            # API call failed, allow by default or block
+            return allow()
+        
+        if response["body"].get("flagged"):
+            return block(response["body"].get("reason", "Content flagged"))
+    
+    return allow()`}},t4={"Return Values":[{name:"allow()",desc:"Let request/response through"},{name:"block(reason)",desc:"Reject with message"},{name:"modify(texts=[], images=[], tool_calls=[])",desc:"Transform content"}],"HTTP Requests (async)":[{name:"await http_request(url, method, headers, body)",desc:"Make async HTTP request"},{name:"await http_get(url, headers)",desc:"Async GET request"},{name:"await http_post(url, body, headers)",desc:"Async POST request"}],"Regex Functions":[{name:"regex_match(text, pattern)",desc:"Returns True if pattern found"},{name:"regex_replace(text, pattern, replacement)",desc:"Replace all matches"},{name:"regex_find_all(text, pattern)",desc:"Return list of matches"}],"JSON Functions":[{name:"json_parse(text)",desc:"Parse JSON string, returns None on error"},{name:"json_stringify(obj)",desc:"Convert to JSON string"},{name:"json_schema_valid(obj, schema)",desc:"Validate against JSON schema"}],"URL Functions":[{name:"extract_urls(text)",desc:"Extract 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new file mode 100644
index 00000000000..31aeb00e129
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new file mode 100644
index 00000000000..4c9e6b9a4d5
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+++ b/litellm/proxy/_experimental/out/_next/static/chunks/3rshy09i_r5cx.js
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deleted file mode 100644
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deleted file mode 100644
index c7cfb7af3c6..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/3t7gwfa1uo_0i.js
+++ /dev/null
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1y596evc77z8d.js b/litellm/proxy/_experimental/out/_next/static/chunks/3uz1pw3-jhofx.js
similarity index 94%
rename from litellm/proxy/_experimental/out/_next/static/chunks/1y596evc77z8d.js
rename to litellm/proxy/_experimental/out/_next/static/chunks/3uz1pw3-jhofx.js
index 33b84b51ed4..741a5ef4160 100644
--- a/litellm/proxy/_experimental/out/_next/static/chunks/1y596evc77z8d.js
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/3uz1pw3-jhofx.js
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t.source});function r(e){return RegExp(e.replace(/<CLASS-NAME>/g,function(){return a}),"i")}var i={keyword:t,punctuation:/[()\[\]{};,:.<>]/};e.languages.apex={comment:e.languages.clike.comment,string:e.languages.clike.string,sql:{pattern:/((?:[=,({:]|\breturn)\s*)\[[^\[\]]*\]/i,lookbehind:!0,greedy:!0,alias:"language-sql",inside:e.languages.sql},annotation:{pattern:/@\w+\b/,alias:"punctuation"},"class-name":[{pattern:r(/(\b(?:class|enum|extends|implements|instanceof|interface|new|trigger\s+\w+\s+on)\s+)<CLASS-NAME>/.source),lookbehind:!0,inside:i},{pattern:r(/(\(\s*)<CLASS-NAME>(?=\s*\)\s*[\w(])/.source),lookbehind:!0,inside:i},{pattern:r(/<CLASS-NAME>(?=\s*\w+\s*[;=,(){:])/.source),inside:i}],trigger:{pattern:/(\btrigger\s+)\w+\b/i,lookbehind:!0,alias:"class-name"},keyword:t,function:/\b[a-z_]\w*(?=\s*\()/i,boolean:/\b(?:false|true)\b/i,number:/(?:\B\.\d+|\b\d+(?:\.\d+|L)?)\b/i,operator:/[!=](?:==?)?|\?\.?|&&|\|\||--|\+\+|[-+*/^&|]=?|:|<<?=?|>{1,3}=?/,punctuation:/[()\[\]{};,.]/}}t.exports=r,r.displayName="apex",r.aliases=[]},991642,(e,t,a)=>{"use strict";function 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color|alias|application|boolean|centimeters|centimetres|class|constant|cubic centimeters|cubic centimetres|cubic feet|cubic inches|cubic meters|cubic metres|cubic yards|date|degrees Celsius|degrees Fahrenheit|degrees Kelvin|feet|file|gallons|grams|inches|integer|kilograms|kilometers|kilometres|list|liters|litres|meters|metres|miles|number|ounces|pounds|quarts|real|record|reference|script|square feet|square kilometers|square kilometres|square meters|square metres|square miles|square yards|text|yards)\b/,punctuation:/[{}():,¬«»《》]/}}t.exports=n,n.displayName="applescript",n.aliases=[]},360075,(e,t,a)=>{"use strict";function n(e){e.languages.aql={comment:/\/\/.*|\/\*[\s\S]*?\*\//,property:{pattern:/([{,]\s*)(?:(?!\d)\w+|(["'´`])(?:(?!\2)[^\\\r\n]|\\.)*\2)(?=\s*:)/,lookbehind:!0,greedy:!0},string:{pattern:/(["'])(?:(?!\1)[^\\\r\n]|\\.)*\1/,greedy:!0},identifier:{pattern:/([´`])(?:(?!\1)[^\\\r\n]|\\.)*\1/,greedy:!0},variable:/@@?\w+/,keyword:[{pattern:/(\bWITH\s+)COUNT(?=\s+INTO\b)/i,lookbehind:!0},/\b(?:AGGREGATE|ALL|AND|ANY|ASC|COLLECT|DESC|DISTINCT|FILTER|FOR|GRAPH|IN|INBOUND|INSERT|INTO|K_PATHS|K_SHORTEST_PATHS|LET|LIKE|LIMIT|NONE|NOT|NULL|OR|OUTBOUND|REMOVE|REPLACE|RETURN|SHORTEST_PATH|SORT|UPDATE|UPSERT|WINDOW|WITH)\b/i,{pattern:/(^|[^\w.[])(?:KEEP|PRUNE|SEARCH|TO)\b/i,lookbehind:!0},{pattern:/(^|[^\w.[])(?:CURRENT|NEW|OLD)\b/,lookbehind:!0},{pattern:/\bOPTIONS(?=\s*\{)/i}],function:/\b(?!\d)\w+(?=\s*\()/,boolean:/\b(?:false|true)\b/i,range:{pattern:/\.\./,alias:"operator"},number:[/\b0b[01]+/i,/\b0x[0-9a-f]+/i,/(?:\B\.\d+|\b(?:0|[1-9]\d*)(?:\.\d+)?)(?:e[+-]?\d+)?/i],operator:/\*{2,}|[=!]~|[!=<>]=?|&&|\|\||[-+*/%]/,punctuation:/::|[?.:,;()[\]{}]/}}t.exports=n,n.displayName="aql",n.aliases=[]},835801,(e,t,a)=>{"use 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new file mode 100644
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3w_ijl0uk7z54.js b/litellm/proxy/_experimental/out/_next/static/chunks/3w_ijl0uk7z54.js
deleted file mode 100644
index 1f4bd74b932..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/3w_ijl0uk7z54.js
+++ /dev/null
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3wpvinhzkbrba.js b/litellm/proxy/_experimental/out/_next/static/chunks/3wpvinhzkbrba.js
new file mode 100644
index 00000000000..f26ef60ff56
--- /dev/null
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@@ -0,0 +1 @@
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3xciut9pzmr7-.js b/litellm/proxy/_experimental/out/_next/static/chunks/3xciut9pzmr7-.js
deleted file mode 100644
index fe05f5274ec..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/3xciut9pzmr7-.js
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/3ygq6_m2izcqr.js b/litellm/proxy/_experimental/out/_next/static/chunks/3ygq6_m2izcqr.js
deleted file mode 100644
index 520af2976ae..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/3ygq6_m2izcqr.js
+++ /dev/null
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new file mode 100644
index 00000000000..41f1f00a6c9
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mt-2",children:e.tags.map(e=>(0,s.jsx)(c.Badge,{variant:"secondary",className:"text-xs",children:e},e))})]},t))})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Input/Output Modes"}),(0,s.jsxs)("div",{className:"grid grid-cols-2 gap-4",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Input Modes:"}),(0,s.jsx)("div",{className:"flex flex-wrap gap-1 mt-1",children:(eT.defaultInputModes??[]).map(e=>(0,s.jsx)(c.Badge,{variant:"secondary",children:e},e))})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Output Modes:"}),(0,s.jsx)("div",{className:"flex flex-wrap gap-1 mt-1",children:(eT.defaultOutputModes??[]).map(e=>(0,s.jsx)(c.Badge,{variant:"secondary",children:e},e))})]})]})]}),eT.documentationUrl&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Documentation"}),(0,s.jsxs)("a",{href:eT.documentationUrl,target:"_blank",rel:"noopener noreferrer",className:"text-blue-600 hover:text-blue-800 flex items-center space-x-2",children:[(0,s.jsx)(a.ExternalLinkIcon,{className:"w-4 h-4"}),(0,s.jsx)("span",{children:"View Documentation"})]})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Usage Example (A2A Protocol)"}),(0,s.jsxs)("div",{className:"mb-4",children:[(0,s.jsx)("p",{className:"text-sm font-medium mb-2 text-gray-700",children:"Step 1: Retrieve Agent Card"}),(0,s.jsx)("div",{className:"bg-gray-900 text-gray-100 p-4 rounded-lg overflow-x-auto",children:(0,s.jsx)("pre",{className:"text-xs",children:`base_url = '${eT.url}'
-
-resolver = A2ACardResolver(
-    httpx_client=httpx_client,
-    base_url=base_url,
-    # agent_card_path uses default, extended_agent_card_path also uses default
-)
-
-# Fetch Public Agent Card and Initialize Client
-final_agent_card_to_use: AgentCard | None = None
-_public_card = (
-    await resolver.get_agent_card()
-)  # Fetches from default public path - \`/agents/{agent_id}/\`
-final_agent_card_to_use = _public_card
-
-if _public_card.supports_authenticated_extended_card:
-    try:
-        auth_headers_dict = {
-            'Authorization': 'Bearer dummy-token-for-extended-card'
-        }
-        _extended_card = await resolver.get_agent_card(
-            relative_card_path=EXTENDED_AGENT_CARD_PATH,
-            http_kwargs={'headers': auth_headers_dict},
-        )
-        final_agent_card_to_use = (
-            _extended_card  # Update to use the extended card
-        )
-    except Exception as e_extended:
-        logger.warning(
-            f'Failed to fetch extended agent card: {e_extended}. Will proceed with public card.',
-            exc_info=True,
-        )`})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU(`from a2a.client import A2ACardResolver, A2AClient
-from a2a.types import (
-    AgentCard,
-    MessageSendParams,
-    SendMessageRequest,
-    SendStreamingMessageRequest,
-)
-from a2a.utils.constants import (
-    AGENT_CARD_WELL_KNOWN_PATH,
-    EXTENDED_AGENT_CARD_PATH,
-)
-
-base_url = '${eT.url}'
-
-resolver = A2ACardResolver(
-    httpx_client=httpx_client,
-    base_url=base_url,
-    # agent_card_path uses default, extended_agent_card_path also uses default
-)
-
-# Fetch Public Agent Card and Initialize Client
-final_agent_card_to_use: AgentCard | None = None
-_public_card = (
-    await resolver.get_agent_card()
-)  # Fetches from default public path - \`/agents/{agent_id}/\`
-final_agent_card_to_use = _public_card
-
-if _public_card.supports_authenticated_extended_card:
-    try:
-        auth_headers_dict = {
-            'Authorization': 'Bearer dummy-token-for-extended-card'
-        }
-        _extended_card = await resolver.get_agent_card(
-            relative_card_path=EXTENDED_AGENT_CARD_PATH,
-            http_kwargs={'headers': auth_headers_dict},
-        )
-        final_agent_card_to_use = (
-            _extended_card  # Update to use the extended card
-        )
-    except Exception as e_extended:
-        logger.warning(
-            f'Failed to fetch extended agent card: {e_extended}. Will proceed with public card.',
-            exc_info=True,
-        )`)},className:"text-sm text-blue-600 hover:text-blue-800 cursor-pointer",children:"Copy to clipboard"})})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-sm font-medium mb-2 text-gray-700",children:"Step 2: Call the Agent"}),(0,s.jsx)("div",{className:"bg-gray-900 text-gray-100 p-4 rounded-lg overflow-x-auto",children:(0,s.jsx)("pre",{className:"text-xs",children:`client = A2AClient(
-    httpx_client=httpx_client, agent_card=final_agent_card_to_use
-)
-
-send_message_payload: dict[str, Any] = {
-    'message': {
-        'role': 'user',
-        'parts': [
-            {'kind': 'text', 'text': 'how much is 10 USD in INR?'}
-        ],
-        'messageId': uuid4().hex,
-    },
-}
-request = SendMessageRequest(
-    id=str(uuid4()), params=MessageSendParams(**send_message_payload)
-)
-
-response = await client.send_message(request)
-print(response.model_dump(mode='json', exclude_none=True))`})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU(`client = A2AClient(
-    httpx_client=httpx_client, agent_card=final_agent_card_to_use
-)
-
-send_message_payload: dict[str, Any] = {
-    'message': {
-        'role': 'user',
-        'parts': [
-            {'kind': 'text', 'text': 'how much is 10 USD in INR?'}
-        ],
-        'messageId': uuid4().hex,
-    },
-}
-request = SendMessageRequest(
-    id=str(uuid4()), params=MessageSendParams(**send_message_payload)
-)
-
-response = await client.send_message(request)
-print(response.model_dump(mode='json', exclude_none=True))`)},className:"text-sm text-blue-600 hover:text-blue-800 cursor-pointer",children:"Copy to clipboard"})})]})]})]})]})}),(0,s.jsx)(x.Dialog,{open:eS,onOpenChange:e=>!e&&void(ew(!1),eD(null)),children:(0,s.jsxs)(x.DialogContent,{className:"max-h-[calc(100dvh-2rem)] overflow-y-auto sm:max-w-[1000px]",children:[(0,s.jsx)(x.DialogHeader,{children:(0,s.jsxs)(x.DialogTitle,{className:"flex min-w-0 items-center space-x-2",children:[(0,s.jsx)("span",{className:"break-words",children:eM?.server_name||"MCP Server Details"}),eM&&(0,s.jsxs)(p.Tooltip,{children:[(0,s.jsx)(p.TooltipTrigger,{render:(0,s.jsx)(l.Copy,{onClick:()=>eU(eM.server_name),className:"cursor-pointer text-gray-500 hover:text-blue-500 w-4 h-4 shrink-0"})}),(0,s.jsx)(p.TooltipContent,{children:"Copy server name"})]})]})}),eM&&(0,s.jsxs)("div",{className:"space-y-6",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Server Overview"}),(0,s.jsxs)("div",{className:"grid grid-cols-2 gap-4 mb-4",children:[(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Server Name:"}),(0,s.jsx)("p",{children:eM.server_name})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Transport:"}),(0,s.jsx)(c.Badge,{variant:"secondary",children:eM.transport})]}),eM.alias&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Alias:"}),(0,s.jsx)("p",{children:eM.alias})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"font-medium",children:"Auth Type:"}),(0,s.jsx)(c.Badge,{variant:"none"===eM.auth_type?"outline":"secondary",children:eM.auth_type})]}),(0,s.jsxs)("div",{className:"col-span-2",children:[(0,s.jsx)("p",{className:"font-medium",children:"Description:"}),(0,s.jsx)("p",{children:eM.mcp_info?.description||"-"})]})]})]}),eM.mcp_info&&Object.keys(eM.mcp_info).length>0&&(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Additional Information"}),(0,s.jsx)("div",{className:"bg-gray-50 p-4 rounded-lg",children:(0,s.jsx)("pre",{className:"text-xs overflow-x-auto",children:JSON.stringify(eM.mcp_info,null,2)})})]}),(0,s.jsxs)("div",{children:[(0,s.jsx)("p",{className:"text-lg font-semibold mb-4",children:"Usage Example"}),(0,s.jsx)("div",{className:"bg-gray-900 text-gray-100 p-4 rounded-lg overflow-x-auto",children:(0,s.jsx)("pre",{className:"text-sm",children:`# Using MCP Server with Python FastMCP
-
-from fastmcp import Client
-import asyncio
-
-# Standard MCP configuration
-config = {
-    "mcpServers": {
-        "${eM.server_name}": {
-            "url": "${(0,f.getProxyBaseUrl)()}/${eM.server_name}/mcp",
-            "headers": {
-                "x-litellm-api-key": "Bearer sk-1234"
-            }
-        }
-    }
-}
-
-# Create a client that connects to the server
-client = Client(config)
-
-async def main():
-    async with client:
-        # List available tools
-        tools = await client.list_tools()
-        print(f"Available tools: {[tool.name for tool in tools]}")
-
-        # Call a tool
-        response = await client.call_tool(
-            name="tool_name", 
-            arguments={"arg": "value"}
-        )
-        print(f"Response: {response}")
-
-if __name__ == "__main__":
-    asyncio.run(main())`})}),(0,s.jsx)("div",{className:"mt-2 text-right",children:(0,s.jsx)("button",{onClick:()=>{eU(`# Using MCP Server with Python FastMCP
-
-from fastmcp import Client
-import asyncio
-
-# Standard MCP configuration
-config = {
-    "mcpServers": {
-        "${eM.server_name}": {
-            "url": "${(0,f.getProxyBaseUrl)()}/${eM.server_name}/mcp",
-            "headers": {
-                "x-litellm-api-key": "Bearer sk-1234"
-            }
-        }
-    }
-}
-
-# Create a client that connects to the server
-client = Client(config)
-
-async def main():
-    async with client:
-        # List available tools
-        tools = await client.list_tools()
-        print(f"Available tools: {[tool.name for tool in tools]}")
-
-        # Call a tool
-        response = await client.call_tool(
-            name="tool_name", 
-            arguments={"arg": "value"}
-        )
-        print(f"Response: {response}")
-
-if __name__ == "__main__":
-    asyncio.run(main())`)},className:"text-sm text-blue-600 hover:text-blue-800 cursor-pointer",children:"Copy to clipboard"})})]})]})]})})]})})})}],976883)}]);
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/42rhdw-kqdpki.js b/litellm/proxy/_experimental/out/_next/static/chunks/42rhdw-kqdpki.js
new file mode 100644
index 00000000000..4766947d9c5
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/42rhdw-kqdpki.js
@@ -0,0 +1 @@
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0769vspoaelaf.js b/litellm/proxy/_experimental/out/_next/static/chunks/44ampmctsfppo.js
similarity index 85%
rename from litellm/proxy/_experimental/out/_next/static/chunks/0769vspoaelaf.js
rename to litellm/proxy/_experimental/out/_next/static/chunks/44ampmctsfppo.js
index 1fab9a1daab..dc01cc9cba8 100644
--- a/litellm/proxy/_experimental/out/_next/static/chunks/0769vspoaelaf.js
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/44ampmctsfppo.js
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diff --git a/litellm/proxy/_experimental/out/chat/__next.chat.txt b/litellm/proxy/_experimental/out/chat/__next.chat.txt
index 151ef486995..caef4800d73 100644
--- a/litellm/proxy/_experimental/out/chat/__next.chat.txt
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diff --git a/litellm/proxy/_experimental/out/logging-and-alerts/__next.!KGRhc2hib2FyZCk.logging-and-alerts.txt b/litellm/proxy/_experimental/out/logging-and-alerts/__next.!KGRhc2hib2FyZCk.logging-and-alerts.txt
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From 75613bf22fdec3c9a3392cfd3cb9190bb91d5afb Mon Sep 17 00:00:00 2001
From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 15:24:05 -0700
Subject: [PATCH 54/93] test: add regression coverage for twelve closed issues
 (#37974)

* test: add regression coverage for twelve closed issues

Adds targeted regression tests for behavior that was fixed but left ungated,
so the fixes cannot silently regress:

- #33772 openai cache_write_tokens cost
- #34309 Responses API cache cost_breakdown
- #35363 /v1/responses batch spend
- #36619 auto-router api_base/api_key leak on a shared model name
- #35359 batch fallbacks within the owning model group
- #36523 passthrough streamed Responses spend log
- #36646 passthrough embeddings spend log
- #37147 non-object metadata on create_batch is a 400
- #35362 unscoped list files reads the managed-file store
- #33221 gpt-5.6 bridges to Responses on function tools alone
- #34487 LLM complexity classifier runs for every caller metadata shape
- #35124 streamed /v1/messages emits success logging on both bridges

Cost assertions read rates from litellm.model_cost rather than hardcoding
dollar amounts, so they do not drift on repricing.

* fix: stop the new regression tests polluting and tripping over shared global state

Two shard failures, both from global state the new tests share with their
neighbours rather than from the behaviour under test.

test_main.py's local_cost_map pinned litellm.model_cost but left the
get_model_info lru_cache warm, so completion_cost billed at whatever prices
were cached earlier in the process while the assertions read the pinned map.
Clear the cache on both sides of the fixture, matching the local_model_cost_map
fixture in tests/test_litellm/conftest.py.

The anthropic messages streaming tests called GLOBAL_LOGGING_WORKER.flush()
on whatever queue happened to be around. A queue left non-empty by an earlier
test is still bound to that test's loop, so join() either hangs or raises
"bound to a different event loop". Rebind to the running loop before the call
and wait for the captured payload instead of a fixed sleep.
---
 .../batches/test_responses_batch_cost.py      | 119 +++++++++
 .../test_openai_cache_write_cost.py           | 136 +++++++++++
 .../test_responses_cache_cost_breakdown.py    | 113 +++++++++
 ...erimental_pass_through_messages_handler.py | 183 ++++++++++++++
 .../proxy/batches_endpoints/test_endpoints.py |  45 +++-
 .../test_files_endpoint.py                    | 178 +++++++++++++-
 ...test_openai_passthrough_logging_handler.py | 226 ++++++++++++++++++
 .../router_strategy/test_complexity_router.py |  45 ++++
 tests/test_litellm/test_main.py               |  40 +++-
 tests/test_litellm/test_router.py             | 161 +++++++++++++
 10 files changed, 1242 insertions(+), 4 deletions(-)
 create mode 100644 tests/test_litellm/batches/test_responses_batch_cost.py
 create mode 100644 tests/test_litellm/litellm_core_utils/llm_cost_calc/test_openai_cache_write_cost.py
 create mode 100644 tests/test_litellm/litellm_core_utils/llm_cost_calc/test_responses_cache_cost_breakdown.py

diff --git a/tests/test_litellm/batches/test_responses_batch_cost.py b/tests/test_litellm/batches/test_responses_batch_cost.py
new file mode 100644
index 00000000000..7ce026bd103
--- /dev/null
+++ b/tests/test_litellm/batches/test_responses_batch_cost.py
@@ -0,0 +1,119 @@
+"""Token and spend reconciliation for /v1/responses batches.
+
+Regression guard for https://github.com/BerriAI/litellm/issues/35363: a batch
+output line built by the Responses API reports ``input_tokens`` /
+``output_tokens`` where a chat line reports ``prompt_tokens`` /
+``completion_tokens``. The usage object was constructed straight from the raw
+dict, which accepts the unrecognized names without raising and yields zeros, so
+a completed Responses batch reconciled to 0 tokens and $0.00 spend with no
+error, and per-key budgets were never charged for it.
+
+Line shape decides the parse, not the batch's declared endpoint, so an output
+file mixing Responses-shaped and chat-shaped lines sums across both.
+"""
+
+from typing import Literal, get_args, get_type_hints
+
+import pytest
+
+import litellm
+import litellm.batches.batch_utils as bu
+from litellm.types.llms.openai import CreateBatchRequest
+
+MODEL = "gpt-5.6"
+
+
+def _responses_line(input_tokens: int, output_tokens: int) -> dict:
+    return {
+        "response": {
+            "status_code": 200,
+            "body": {
+                "model": MODEL,
+                "usage": {
+                    "input_tokens": input_tokens,
+                    "output_tokens": output_tokens,
+                    "total_tokens": input_tokens + output_tokens,
+                },
+            },
+        }
+    }
+
+
+def _chat_line(prompt_tokens: int, completion_tokens: int) -> dict:
+    return {
+        "response": {
+            "status_code": 200,
+            "body": {
+                "model": MODEL,
+                "usage": {
+                    "prompt_tokens": prompt_tokens,
+                    "completion_tokens": completion_tokens,
+                    "total_tokens": prompt_tokens + completion_tokens,
+                },
+            },
+        }
+    }
+
+
+def test_responses_shaped_usage_maps_onto_prompt_and_completion_tokens():
+    """The Responses names land on the chat-shaped counters instead of being
+    dropped for unrecognized keys."""
+    usage = bu._get_batch_job_usage_from_response_body(
+        {"usage": {"input_tokens": 100, "output_tokens": 50, "total_tokens": 150}}
+    )
+    assert (usage.prompt_tokens, usage.completion_tokens, usage.total_tokens) == (100, 50, 150)
+
+
+async def test_responses_batch_reconciles_to_real_tokens_and_spend(local_model_cost_map):
+    """A completed Responses batch records the provider's token counts and a
+    non-zero spend at the model's batch rates."""
+    model_info = litellm.get_model_info(model=MODEL, custom_llm_provider="openai")
+    input_tokens = 33
+    output_tokens = 57
+
+    cost, usage, models = await bu.calculate_batch_cost_and_usage(
+        file_content_dictionary=[_responses_line(input_tokens, output_tokens)],
+        custom_llm_provider="openai",
+        model_name=MODEL,
+        model_info=model_info,
+    )
+
+    assert (usage.prompt_tokens, usage.completion_tokens, usage.total_tokens) == (
+        input_tokens,
+        output_tokens,
+        input_tokens + output_tokens,
+    )
+    assert models == [MODEL]
+    assert cost == pytest.approx(
+        input_tokens * model_info["input_cost_per_token_batches"]
+        + output_tokens * model_info["output_cost_per_token_batches"]
+    )
+    assert cost > 0.0
+
+
+async def test_mixed_shape_batch_output_sums_across_both_line_shapes(local_model_cost_map):
+    """An output file carrying both line shapes sums both. A fix keyed off the
+    batch's declared endpoint rather than each line's shape would miss this."""
+    model_info = litellm.get_model_info(model=MODEL, custom_llm_provider="openai")
+
+    cost, usage, _ = await bu.calculate_batch_cost_and_usage(
+        file_content_dictionary=[_responses_line(100, 50), _chat_line(33, 57)],
+        custom_llm_provider="openai",
+        model_name=MODEL,
+        model_info=model_info,
+    )
+
+    assert (usage.prompt_tokens, usage.completion_tokens, usage.total_tokens) == (133, 107, 240)
+    assert cost == pytest.approx(
+        133 * model_info["input_cost_per_token_batches"] + 107 * model_info["output_cost_per_token_batches"]
+    )
+
+
+def test_create_batch_endpoint_accepts_v1_responses():
+    """A type-checked caller can pass endpoint="/v1/responses", which the runtime
+    already forwarded correctly."""
+    endpoint_annotation = get_type_hints(CreateBatchRequest)["endpoint"]
+    assert "/v1/responses" in get_args(endpoint_annotation)
+
+    for create_fn in (litellm.create_batch, litellm.acreate_batch):
+        assert "/v1/responses" in get_args(get_type_hints(create_fn)["endpoint"])
diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_openai_cache_write_cost.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_openai_cache_write_cost.py
new file mode 100644
index 00000000000..92cb417f96c
--- /dev/null
+++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_openai_cache_write_cost.py
@@ -0,0 +1,136 @@
+"""Cache-write pricing for OpenAI models, on both the chat and Responses paths.
+
+Regression guard for https://github.com/BerriAI/litellm/issues/33772: OpenAI
+reports cache-write tokens under ``prompt_tokens_details.cache_write_tokens``
+(chat) / ``input_tokens_details.cache_write_tokens`` (responses), where
+Anthropic reports ``cache_creation_tokens``. The cost path read only the
+Anthropic name, so cache-write tokens were billed at the plain input rate,
+the Responses transform dropped the split before cost ran, and the tiered
+``cache_creation_input_token_cost_{priority,flex,above_272k_tokens}`` keys were
+discarded by ``get_model_info``.
+"""
+
+import pytest
+
+import litellm
+from litellm.litellm_core_utils.llm_cost_calc.utils import generic_cost_per_token
+from litellm.responses.utils import ResponseAPILoggingUtils
+from litellm.types.utils import Usage
+
+MODEL = "gpt-5.6"
+
+
+def _openai_chat_usage(prompt_tokens: int, cache_write_tokens: int, completion_tokens: int) -> Usage:
+    return Usage(
+        prompt_tokens=prompt_tokens,
+        completion_tokens=completion_tokens,
+        total_tokens=prompt_tokens + completion_tokens,
+        prompt_tokens_details={
+            "cached_tokens": 0,
+            "cache_write_tokens": cache_write_tokens,
+        },
+    )
+
+
+def test_openai_cache_write_tokens_billed_at_the_cache_creation_rate(local_model_cost_map):
+    """A cache-write request costs the cache-creation rate on the written tokens,
+    not the plain input rate."""
+    rates = litellm.model_cost[MODEL]
+    input_rate = rates["input_cost_per_token"]
+    cache_write_rate = rates["cache_creation_input_token_cost"]
+    output_rate = rates["output_cost_per_token"]
+    assert cache_write_rate == pytest.approx(input_rate * 1.25)
+
+    prompt_tokens = 12317
+    cache_write_tokens = 12314
+    fresh_tokens = prompt_tokens - cache_write_tokens
+    completion_tokens = 5
+
+    prompt_cost, completion_cost = generic_cost_per_token(
+        model=MODEL,
+        usage=_openai_chat_usage(prompt_tokens, cache_write_tokens, completion_tokens),
+        custom_llm_provider="openai",
+    )
+
+    assert prompt_cost == pytest.approx(fresh_tokens * input_rate + cache_write_tokens * cache_write_rate)
+    assert completion_cost == pytest.approx(completion_tokens * output_rate)
+    assert prompt_cost > prompt_tokens * input_rate
+
+
+def test_responses_api_cache_write_costs_the_same_as_chat(local_model_cost_map):
+    """The Responses usage transform carries the cache-write split through, so the
+    same request costs the same whichever route it took."""
+    prompt_tokens = 12317
+    cache_write_tokens = 12314
+    completion_tokens = 5
+
+    responses_usage = ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage(
+        {
+            "input_tokens": prompt_tokens,
+            "output_tokens": completion_tokens,
+            "total_tokens": prompt_tokens + completion_tokens,
+            "input_tokens_details": {
+                "cached_tokens": 0,
+                "cache_write_tokens": cache_write_tokens,
+            },
+        }
+    )
+    assert responses_usage.prompt_tokens_details.cache_write_tokens == cache_write_tokens
+
+    responses_prompt_cost, responses_completion_cost = generic_cost_per_token(
+        model=MODEL,
+        usage=responses_usage,
+        custom_llm_provider="openai",
+    )
+    chat_prompt_cost, chat_completion_cost = generic_cost_per_token(
+        model=MODEL,
+        usage=_openai_chat_usage(prompt_tokens, cache_write_tokens, completion_tokens),
+        custom_llm_provider="openai",
+    )
+
+    rates = litellm.model_cost[MODEL]
+    fresh_tokens = prompt_tokens - cache_write_tokens
+    assert responses_prompt_cost == pytest.approx(
+        fresh_tokens * rates["input_cost_per_token"]
+        + cache_write_tokens * rates["cache_creation_input_token_cost"]
+    )
+    assert responses_prompt_cost == pytest.approx(chat_prompt_cost)
+    assert responses_completion_cost == pytest.approx(chat_completion_cost)
+
+
+@pytest.mark.parametrize(
+    "service_tier,prompt_tokens,rate_key",
+    [
+        (None, 100000, "cache_creation_input_token_cost"),
+        ("priority", 100000, "cache_creation_input_token_cost_priority"),
+        ("flex", 100000, "cache_creation_input_token_cost_flex"),
+        (None, 300000, "cache_creation_input_token_cost_above_272k_tokens"),
+    ],
+)
+def test_tiered_cache_creation_rates_are_registered_and_billed(
+    local_model_cost_map, service_tier, prompt_tokens, rate_key
+):
+    """The tiered cache-creation keys survive ``get_model_info`` and are the rate the
+    cost path actually charges for priority, flex, and >272k requests."""
+    model_info = litellm.get_model_info(model=MODEL, custom_llm_provider="openai")
+    tiered_rate = litellm.model_cost[MODEL][rate_key]
+    assert model_info.get(rate_key) == tiered_rate
+
+    cache_write_tokens = prompt_tokens - 1000
+    fresh_tokens = 1000
+    input_rate_key = {
+        "cache_creation_input_token_cost": "input_cost_per_token",
+        "cache_creation_input_token_cost_priority": "input_cost_per_token_priority",
+        "cache_creation_input_token_cost_flex": "input_cost_per_token_flex",
+        "cache_creation_input_token_cost_above_272k_tokens": "input_cost_per_token_above_272k_tokens",
+    }[rate_key]
+    input_rate = litellm.model_cost[MODEL][input_rate_key]
+
+    prompt_cost, _ = generic_cost_per_token(
+        model=MODEL,
+        usage=_openai_chat_usage(prompt_tokens, cache_write_tokens, completion_tokens=100),
+        custom_llm_provider="openai",
+        service_tier=service_tier,
+    )
+
+    assert prompt_cost == pytest.approx(fresh_tokens * input_rate + cache_write_tokens * tiered_rate)
diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_responses_cache_cost_breakdown.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_responses_cache_cost_breakdown.py
new file mode 100644
index 00000000000..0d387233be7
--- /dev/null
+++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_responses_cache_cost_breakdown.py
@@ -0,0 +1,113 @@
+"""Itemized cache costs in the logged cost breakdown for the OpenAI Responses API.
+
+Regression guard for https://github.com/BerriAI/litellm/issues/34309: the
+breakdown block derived its cache token counts only from the Anthropic-style
+top-level ``cache_read_input_tokens`` / ``cache_creation_input_tokens``. OpenAI's
+Responses API reports them under ``input_tokens_details.{cached_tokens,
+cache_write_tokens}`` instead, so ``cost_breakdown.cache_read_cost`` and
+``cache_creation_cost`` serialized as null for every OpenAI request while the
+grand total stayed correct.
+
+``input_cost`` is the full prompt-side cost and the two cache fields are additive
+break-outs that overlap it, matching the Anthropic path. A request with no cache
+activity leaves both fields unset, which is the documented behavior.
+"""
+
+from datetime import datetime
+
+import pytest
+
+import litellm
+from litellm.litellm_core_utils.litellm_logging import Logging
+from litellm.responses.utils import ResponseAPILoggingUtils
+from litellm.types.utils import Choices, Message, ModelResponse
+
+MODEL = "gpt-5.6"
+
+
+def _logging_obj() -> Logging:
+    return Logging(
+        model=MODEL,
+        messages=[{"role": "user", "content": "hi"}],
+        stream=False,
+        call_type="completion",
+        start_time=datetime.now(),
+        litellm_call_id="responses-cache-breakdown",
+        function_id="f",
+    )
+
+
+def _responses_completion(cached_tokens: int, cache_write_tokens: int, fresh_tokens: int, output_tokens: int):
+    input_tokens = cached_tokens + cache_write_tokens + fresh_tokens
+    usage = ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage(
+        {
+            "input_tokens": input_tokens,
+            "output_tokens": output_tokens,
+            "total_tokens": input_tokens + output_tokens,
+            "input_tokens_details": {
+                "cached_tokens": cached_tokens,
+                "cache_write_tokens": cache_write_tokens,
+            },
+        }
+    )
+    return ModelResponse(
+        id="x",
+        created=1,
+        model=MODEL,
+        object="chat.completion",
+        choices=[Choices(index=0, message=Message(role="assistant", content="hi"), finish_reason="stop")],
+        usage=usage,
+    )
+
+
+def test_responses_api_cache_costs_are_itemized_in_the_breakdown(local_model_cost_map):
+    """Cache-read and cache-write dollars are broken out for an OpenAI Responses
+    request, at the model's own cache rates."""
+    rates = litellm.model_cost[MODEL]
+    cached_tokens = 4012
+    cache_write_tokens = 5000
+    fresh_tokens = 1000
+    output_tokens = 200
+
+    logging_obj = _logging_obj()
+    total = litellm.completion_cost(
+        completion_response=_responses_completion(cached_tokens, cache_write_tokens, fresh_tokens, output_tokens),
+        model=MODEL,
+        custom_llm_provider="openai",
+        litellm_logging_obj=logging_obj,
+    )
+
+    breakdown = logging_obj.cost_breakdown
+    assert breakdown is not None
+
+    expected_cache_read = cached_tokens * rates["cache_read_input_token_cost"]
+    expected_cache_creation = cache_write_tokens * rates["cache_creation_input_token_cost"]
+    expected_input = fresh_tokens * rates["input_cost_per_token"] + expected_cache_read + expected_cache_creation
+    expected_output = output_tokens * rates["output_cost_per_token"]
+
+    assert breakdown["cache_read_cost"] == pytest.approx(expected_cache_read)
+    assert breakdown["cache_creation_cost"] == pytest.approx(expected_cache_creation)
+    assert breakdown["input_cost"] == pytest.approx(expected_input)
+    assert breakdown["output_cost"] == pytest.approx(expected_output)
+    assert breakdown["total_cost"] == pytest.approx(expected_input + expected_output)
+    assert total == pytest.approx(breakdown["total_cost"])
+
+
+def test_cache_fields_stay_unset_when_there_was_no_cache_activity(local_model_cost_map):
+    """A request that neither read nor wrote the cache leaves both break-out fields
+    off the breakdown, so they serialize as null rather than a misleading $0."""
+    logging_obj = _logging_obj()
+    litellm.completion_cost(
+        completion_response=_responses_completion(
+            cached_tokens=0, cache_write_tokens=0, fresh_tokens=1000, output_tokens=200
+        ),
+        model=MODEL,
+        custom_llm_provider="openai",
+        litellm_logging_obj=logging_obj,
+    )
+
+    breakdown = logging_obj.cost_breakdown
+    assert breakdown is not None
+    assert "cache_read_cost" not in breakdown
+    assert "cache_creation_cost" not in breakdown
+    assert breakdown["input_cost"] == pytest.approx(1000 * litellm.model_cost[MODEL]["input_cost_per_token"])
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py
index 570ce152714..9e58ded81bd 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py
@@ -1,5 +1,8 @@
+import asyncio
 import json
 import os
+import uuid
+from typing import Any, Dict, List
 
 import httpx
 import pytest
@@ -10,6 +13,8 @@ from unittest.mock import AsyncMock, MagicMock, patch
 
 import litellm
 from litellm.anthropic_interface import messages
+from litellm.integrations.custom_logger import CustomLogger
+from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER
 from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
 from litellm.types.utils import Delta, ModelResponse, StreamingChoices
 
@@ -1103,3 +1108,181 @@ def test_messages_sync_streaming_reports_provider_local_model():
         first_event = next(iter(stream))
 
     assert json.loads(first_event.decode().split("data: ", 1)[1])["message"]["model"] == "perplexity/kimi-k3"
+
+
+_RESPONSES_COMPLETED_BODY: Dict[str, Any] = {
+    "id": "resp-1",
+    "object": "response",
+    "created_at": 0,
+    "model": "gpt-4o-mini",
+    "status": "completed",
+    "output": [
+        {
+            "type": "message",
+            "id": "msg-1",
+            "status": "completed",
+            "role": "assistant",
+            "content": [{"type": "output_text", "text": "hello there"}],
+        }
+    ],
+    "usage": {"input_tokens": 11, "output_tokens": 7, "total_tokens": 18},
+}
+
+_RESPONSES_SSE_EVENTS: List[Dict[str, Any]] = [
+    {
+        "type": "response.created",
+        "response": {
+            **_RESPONSES_COMPLETED_BODY,
+            "status": "in_progress",
+            "output": [],
+            "usage": None,
+        },
+    },
+    {
+        "type": "response.output_text.delta",
+        "item_id": "msg-1",
+        "output_index": 0,
+        "content_index": 0,
+        "delta": "hello there",
+    },
+    {"type": "response.completed", "response": _RESPONSES_COMPLETED_BODY},
+]
+
+
+def _sse_body(events: List[Dict[str, Any]]) -> bytes:
+    return b"".join(f"data: {json.dumps(event)}\n\n".encode() for event in events)
+
+
+class _SuccessPayloadCapture(CustomLogger):
+    def __init__(self, tracking_id: str):
+        super().__init__()
+        self.tracking_id = tracking_id
+        self.payloads: List[Dict[str, Any]] = []
+
+    async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
+        if kwargs.get("litellm_call_id") == self.tracking_id:
+            self.payloads.append(kwargs.get("standard_logging_object") or {})
+
+
+@pytest.fixture
+def capture_success_payloads(monkeypatch):
+    monkeypatch.setenv("OPENAI_API_KEY", "sk-test")
+    capture = _SuccessPayloadCapture(tracking_id=f"messages-stream-{uuid.uuid4()}")
+    monkeypatch.setattr(litellm, "callbacks", [capture])
+    return capture
+
+
+async def _drain(sse_stream) -> List[bytes]:
+    return [chunk async for chunk in sse_stream]
+
+
+def _bind_logging_worker_to_running_loop() -> None:
+    """The worker's queue keeps the loop it was built on, so one left over from an earlier
+    test makes ``flush`` raise "bound to a different event loop". ``start`` runs
+    ``_ensure_queue``, which rebinds the queue when the running loop has changed."""
+    GLOBAL_LOGGING_WORKER.start()
+
+
+async def _flush_logging_worker(capture: "_SuccessPayloadCapture") -> None:
+    await asyncio.sleep(0)
+    try:
+        await asyncio.wait_for(GLOBAL_LOGGING_WORKER.flush(), timeout=10.0)
+    except (asyncio.TimeoutError, RuntimeError):
+        pass
+    deadline = asyncio.get_running_loop().time() + 10.0
+    while not capture.payloads and asyncio.get_running_loop().time() < deadline:
+        await asyncio.sleep(0.05)
+
+
+def _assert_anthropic_sse(chunks: List[bytes]) -> None:
+    body = b"".join(chunks).decode()
+    assert "message_start" in body
+    assert "message_stop" in body
+
+
+class TestMessagesStreamingSuccessLogging:
+    """A streamed /v1/messages call routed to an ``openai/`` backend must still reach
+    success logging once the SSE stream is drained. The client gets a correct Anthropic
+    SSE body and the provider bills the call, but no StandardLoggingPayload is produced,
+    so the request is invisible to spend tracking and every success-logging integration.
+
+    Logging is fired by the inner CustomStreamWrapper / ResponsesAPIStreamingIterator the
+    Anthropic wrappers drain, not by the wrappers themselves, so these assert on the
+    callback that actually reaches an integration rather than on a wrapper attribute.
+    """
+
+    MESSAGES = [{"role": "user", "content": "hi"}]
+
+    @pytest.mark.asyncio
+    async def test_responses_bridge_streaming_emits_success_logging(self, capture_success_payloads):
+        """The Responses bridge, which is the default for openai/ deployments."""
+        from litellm.llms.anthropic.experimental_pass_through.responses_adapters.handler import (
+            LiteLLMMessagesToResponsesAPIHandler,
+        )
+
+        _bind_logging_worker_to_running_loop()
+
+        with patch(
+            "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post",
+            new_callable=AsyncMock,
+        ) as mock_post:
+            mock_post.return_value = httpx.Response(
+                200,
+                content=_sse_body(_RESPONSES_SSE_EVENTS),
+                headers={"content-type": "text/event-stream"},
+            )
+            sse_stream = await LiteLLMMessagesToResponsesAPIHandler.async_anthropic_messages_handler(
+                max_tokens=100,
+                messages=self.MESSAGES,
+                model="openai/gpt-4o-mini",
+                stream=True,
+                custom_llm_provider="openai",
+                litellm_call_id=capture_success_payloads.tracking_id,
+            )
+            chunks = await _drain(sse_stream)
+
+        await _flush_logging_worker(capture_success_payloads)
+
+        _assert_anthropic_sse(chunks)
+        assert len(capture_success_payloads.payloads) == 1
+        payload = capture_success_payloads.payloads[0]
+        assert payload["call_type"] == "aresponses"
+        assert payload["prompt_tokens"] == 11
+        assert payload["completion_tokens"] == 7
+        assert payload["total_tokens"] == 18
+        assert payload["response_cost"] > 0
+
+    @pytest.mark.asyncio
+    async def test_chat_completions_bridge_streaming_emits_success_logging(self, capture_success_payloads):
+        """The chat-completions bridge, reached via
+        litellm.use_chat_completions_url_for_anthropic_messages. Its router lookup is
+        stubbed to what an SDK caller with no proxy running already resolves to."""
+        from litellm.llms.anthropic.experimental_pass_through.adapters.handler import (
+            LiteLLMMessagesToCompletionTransformationHandler,
+        )
+
+        _bind_logging_worker_to_running_loop()
+
+        with patch(
+            "litellm.llms.anthropic.experimental_pass_through.adapters.handler._proxy_router_fallback",
+            return_value=None,
+        ):
+            sse_stream = await LiteLLMMessagesToCompletionTransformationHandler.async_anthropic_messages_handler(
+                max_tokens=100,
+                messages=self.MESSAGES,
+                model="openai/gpt-4o-mini",
+                stream=True,
+                custom_llm_provider="openai",
+                mock_response="hello there",
+                litellm_call_id=capture_success_payloads.tracking_id,
+            )
+            chunks = await _drain(sse_stream)
+
+        await _flush_logging_worker(capture_success_payloads)
+
+        _assert_anthropic_sse(chunks)
+        assert len(capture_success_payloads.payloads) == 1
+        payload = capture_success_payloads.payloads[0]
+        assert payload["call_type"] == "acompletion"
+        assert payload["total_tokens"] > 0
+        assert payload["response_cost"] > 0
diff --git a/tests/test_litellm/proxy/batches_endpoints/test_endpoints.py b/tests/test_litellm/proxy/batches_endpoints/test_endpoints.py
index b548b0b3135..2f6a5a3b0e0 100644
--- a/tests/test_litellm/proxy/batches_endpoints/test_endpoints.py
+++ b/tests/test_litellm/proxy/batches_endpoints/test_endpoints.py
@@ -29,6 +29,7 @@ added to this layer raises instead of silently passing - the inventory of seams
 cannot drift without a test failure.
 """
 
+import json
 from contextlib import ExitStack
 from dataclasses import dataclass
 from typing import Any, Dict, Optional
@@ -50,7 +51,7 @@ from litellm.router import Router
 from litellm.types.llms.openai import BatchJobStatus
 from litellm.types.utils import CredentialItem, LiteLLMBatch
 
-from fastapi import Response
+from fastapi import Request, Response
 
 # --------------------------------------------------------------------------- #
 # Fixtures: distinguishable credentials per model so a wrong/hardcoded model_id
@@ -851,6 +852,48 @@ async def test_create__missing_required_param_is_400(harness, body, missing_para
     harness.router_acreate.assert_not_called()
 
 
+def _raw_batches_request(body: Dict[str, Any]) -> MagicMock:
+    """A request that reaches the real pre-call logic, which the `harness` fixture
+    mocks out. Metadata validation lives there, so it cannot be seen through the seam."""
+    request = MagicMock(spec=Request)
+    request.url = MagicMock()
+    request.url.__str__.return_value = "http://localhost/v1/batches"
+    request.url.path = "/v1/batches"
+    request.method = "POST"
+    request.query_params = {}
+    request.headers = {"Content-Type": "application/json"}
+    request.client = MagicMock()
+    request.client.host = "127.0.0.1"
+    request.body = AsyncMock(return_value=json.dumps(body).encode())
+    return request
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("field", ["metadata", "litellm_metadata"])
+async def test_create__non_object_metadata_is_400(field):
+    """A non-object metadata field is rejected with a 400 naming it (#37147), rather
+    than being coerced to None and silently dropped, or crashing behind a 500 with
+    "'str' object has no attribute 'update'"."""
+    body = {
+        "input_file_id": "file-abc",
+        "endpoint": "/v1/chat/completions",
+        "completion_window": "24h",
+        field: "abc",
+    }
+
+    with pytest.raises(ProxyException) as exc_info:
+        await endpoints.create_batch(
+            request=_raw_batches_request(body),
+            fastapi_response=Response(),
+            provider=None,
+            user_api_key_dict=UserAPIKeyAuth(api_key="sk-test"),
+        )
+
+    assert exc_info.value.code == "400"
+    assert exc_info.value.param == field
+    assert "has no attribute 'update'" not in exc_info.value.message
+
+
 # =========================================================================== #
 # Team-level batch expiry enforcement (independent of routing).
 # =========================================================================== #
diff --git a/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py b/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py
index 1b16e036ad7..23552f2fa31 100644
--- a/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py
+++ b/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py
@@ -1,6 +1,6 @@
 import json
-from typing import Final, List
-from unittest.mock import ANY, AsyncMock
+from typing import Final, List, Optional
+from unittest.mock import ANY, AsyncMock, MagicMock
 
 import pytest
 import respx
@@ -4302,3 +4302,177 @@ def test_batch_upload_closes_the_spools_it_opened(monkeypatch, llm_router: Route
     finally:
         app.dependency_overrides.pop(ps.user_api_key_auth, None)
         ProxyLogging._callback_capabilities_cache.clear()
+
+
+def _managed_file_row(
+    unified_file_id: str,
+    stored_file_id: Optional[str] = None,
+    created_by: str = "test-user",
+    team_id: Optional[str] = None,
+) -> MagicMock:
+    file_object = OpenAIFileObject(
+        id=stored_file_id or unified_file_id,
+        bytes=100,
+        created_at=1700000000,
+        filename="batch.jsonl",
+        object="file",
+        purpose="batch",
+        status="processed",
+    )
+    return MagicMock(
+        unified_file_id=unified_file_id,
+        file_object=file_object.model_dump(),
+        created_by=created_by,
+        team_id=team_id,
+    )
+
+
+def _row_matches_where(row, where) -> bool:
+    for field, expected in where.items():
+        if field == "OR":
+            if not any(_row_matches_where(row, clause) for clause in expected):
+                return False
+        elif getattr(row, field) != expected:
+            return False
+    return True
+
+
+class _ManagedFileTableOverRows:
+    """Enough of the Prisma table for the real hook's owner-scoped keyset query."""
+
+    def __init__(self, rows):
+        self.rows = list(rows)
+
+    def _owned_rows(self, where):
+        return [row for row in self.rows if _row_matches_where(row, where)]
+
+    async def find_first(self, where):
+        return next(iter(self._owned_rows(where)), None)
+
+    async def find_many(self, where, take=None, order=None, cursor=None, skip=0):
+        rows = self._owned_rows(where)
+        if cursor is not None:
+            start = next(
+                index
+                for index, row in enumerate(rows)
+                if row.unified_file_id == cursor["unified_file_id"]
+            )
+            rows = rows[start + skip :]
+        return rows if take is None else rows[:take]
+
+
+def _setup_unscoped_list_files_route_over_real_hook(
+    mocker, monkeypatch, llm_router: Router, rows
+):
+    """Wire GET /v1/files to a real managed-files hook over `rows`, with no provider
+    credentials in the process. The neighbouring setup stubs the hook with a
+    MagicMock, so it cannot see anything past the route's argument plumbing."""
+    import litellm.proxy.proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+    from litellm_enterprise.proxy.hooks.managed_files import (
+        _PROXY_LiteLLMManagedFiles,
+    )
+
+    for env_var in ("OPENAI_API_KEY", "OPENAI_ADMIN_KEY", "OPENAI_ORGANIZATION"):
+        monkeypatch.delenv(env_var, raising=False)
+    monkeypatch.setattr(litellm, "api_key", None, raising=False)
+    monkeypatch.setattr(litellm, "openai_key", None, raising=False)
+
+    managed_files = _PROXY_LiteLLMManagedFiles(
+        internal_usage_cache=MagicMock(), prisma_client=MagicMock()
+    )
+    managed_files.prisma_client.db.litellm_managedfiletable = _ManagedFileTableOverRows(rows)
+
+    proxy_logging_obj = setup_proxy_logging_object(monkeypatch, llm_router)
+    proxy_logging_obj.proxy_hook_mapping["managed_files"] = managed_files
+    proxy_logging_obj.update_request_status = mocker.AsyncMock()
+    proxy_logging_obj.post_call_success_hook = mocker.AsyncMock(return_value=None)
+    proxy_logging_obj.post_call_failure_hook = mocker.AsyncMock()
+    monkeypatch.setattr("litellm.proxy.proxy_server.master_key", None)
+    monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None)
+    monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", llm_router)
+
+    provider_list = mocker.patch.object(litellm, "afile_list", new=mocker.AsyncMock())
+
+    app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth(
+        api_key="test-key",
+        user_role=LitellmUserRoles.INTERNAL_USER,
+        user_id="test-user",
+    )
+    return proxy_logging_obj, provider_list
+
+
+def test_unscoped_list_files_reads_the_store_without_any_provider_key(
+    mocker: MockerFixture, monkeypatch, llm_router: Router
+):
+    """The exact shape `client.files.list()` produces, with no target_model_names, no
+    provider and no OPENAI_API_KEY in the process, must return the caller's managed
+    files instead of falling through to a keyless provider client (#35362)."""
+    proxy_logging_obj, provider_list = _setup_unscoped_list_files_route_over_real_hook(
+        mocker, monkeypatch, llm_router, [_managed_file_row("unified-file-1")]
+    )
+
+    response = _get_unscoped_list_files("")
+
+    assert response.status_code == 200, response.text
+    assert [file["id"] for file in response.json()["data"]] == ["unified-file-1"]
+    provider_list.assert_not_awaited()
+    proxy_logging_obj.post_call_failure_hook.assert_not_called()
+
+
+def test_unscoped_list_files_returns_unified_ids_for_rows_storing_a_raw_provider_id(
+    mocker: MockerFixture, monkeypatch, llm_router: Router
+):
+    """Batch output rows store the provider's file object, whose id is a raw `file-`
+    the caller cannot act on. The listing hands back the row's unified id so
+    files.retrieve and files.content work on what it returned."""
+    _setup_unscoped_list_files_route_over_real_hook(
+        mocker,
+        monkeypatch,
+        llm_router,
+        [_managed_file_row("unified-batch-output", stored_file_id="file-raw-provider-123")],
+    )
+
+    response = _get_unscoped_list_files("")
+
+    assert response.status_code == 200, response.text
+    assert [file["id"] for file in response.json()["data"]] == ["unified-batch-output"]
+    assert response.json()["data"][0]["filename"] == "batch.jsonl"
+
+
+def test_unscoped_list_files_does_not_leak_another_callers_files(
+    mocker: MockerFixture, monkeypatch, llm_router: Router
+):
+    """Listing without a model pinned is still owner-scoped."""
+    _setup_unscoped_list_files_route_over_real_hook(
+        mocker,
+        monkeypatch,
+        llm_router,
+        [
+            _managed_file_row("unified-mine"),
+            _managed_file_row("unified-theirs", created_by="other-user"),
+        ],
+    )
+
+    response = _get_unscoped_list_files("")
+
+    assert response.status_code == 200, response.text
+    assert [file["id"] for file in response.json()["data"]] == ["unified-mine"]
+
+
+def test_scoped_list_files_still_resolves_deployment_credentials(
+    mocker: MockerFixture, monkeypatch, llm_router: Router
+):
+    """target_model_names keeps routing to the provider on deployment credentials, so
+    the unscoped path does not swallow that route."""
+    _, provider_list = _setup_unscoped_list_files_route_over_real_hook(
+        mocker, monkeypatch, llm_router, [_managed_file_row("unified-file-1")]
+    )
+    provider_list.return_value = []
+
+    response = _get_unscoped_list_files("?target_model_names=gpt-3.5-turbo")
+
+    assert response.status_code == 200, response.text
+    provider_list.assert_awaited_once()
+    assert provider_list.await_args.kwargs["custom_llm_provider"] == "openai"
+    assert provider_list.await_args.kwargs["api_key"] == "openai_api_key"
diff --git a/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_openai_passthrough_logging_handler.py b/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_openai_passthrough_logging_handler.py
index f0b2feeb377..6f9142c85df 100644
--- a/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_openai_passthrough_logging_handler.py
+++ b/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_openai_passthrough_logging_handler.py
@@ -7,6 +7,7 @@ import httpx
 import pytest
 
 
+import litellm
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.proxy.pass_through_endpoints.llm_provider_handlers.openai_passthrough_logging_handler import (
     OpenAIPassthroughLoggingHandler,
@@ -14,6 +15,7 @@ from litellm.proxy.pass_through_endpoints.llm_provider_handlers.openai_passthrou
 from litellm.proxy.pass_through_endpoints.success_handler import (
     PassThroughEndpointLogging,
 )
+from litellm.proxy.spend_tracking.spend_tracking_utils import get_logging_payload
 from litellm.types.passthrough_endpoints.pass_through_endpoints import (
     PassthroughStandardLoggingPayload,
 )
@@ -1809,5 +1811,229 @@ class TestOpenAIPassthroughIntegration:
         assert mock_logging_obj.model_call_details["custom_llm_provider"] == "openai"
 
 
+class TestOpenAIPassthroughResponsesStreamingSpendLog:
+    """A streamed OpenAI-passthrough `/v1/responses` call must write a priced spend
+    log row (#36523).
+
+    `_handle_logging_openai_collected_chunks` received `url_route` and ignored it, so
+    a Responses SSE stream was reassembled by the chat-completions chunk parser. The
+    assembled object carried a synthetic `chatcmpl-` id, `model=None` and zero usage,
+    and the spend row landed at zero tokens and zero spend while the identical
+    buffered call priced exactly.
+    """
+
+    RESPONSE_ID = "resp_0c72ddebf05f8751"
+    MODEL_MAP_KEY = "gpt-4o-mini-2024-07-18"
+    INPUT_TOKENS = 14
+    OUTPUT_TOKENS = 2
+
+    def setup_method(self):
+        self.start_time = datetime.now()
+        self.end_time = datetime.now()
+        rates = litellm.model_cost[self.MODEL_MAP_KEY]
+        self.expected_spend = (
+            self.INPUT_TOKENS * rates["input_cost_per_token"]
+            + self.OUTPUT_TOKENS * rates["output_cost_per_token"]
+        )
+
+    def _responses_stream_chunks(self) -> List[str]:
+        """Usage arrives only on the terminal `response.completed` event, nested under
+        `response` as `input_tokens` / `output_tokens`. No event carries a top-level
+        `id`, `model` or `usage`."""
+        response_body = {
+            "id": self.RESPONSE_ID,
+            "object": "response",
+            "created_at": 1786374786,
+            "model": self.MODEL_MAP_KEY,
+            "error": None,
+            "incomplete_details": None,
+            "instructions": None,
+            "metadata": {},
+            "parallel_tool_calls": True,
+            "temperature": 1.0,
+            "tool_choice": "auto",
+            "tools": [],
+            "top_p": 1.0,
+        }
+        created_event = {
+            "type": "response.created",
+            "sequence_number": 0,
+            "response": {**response_body, "status": "in_progress", "output": [], "usage": None},
+        }
+        delta_event = {
+            "type": "response.output_text.delta",
+            "sequence_number": 3,
+            "item_id": "msg_abc",
+            "output_index": 0,
+            "content_index": 0,
+            "delta": "OK",
+        }
+        completed_event = {
+            "type": "response.completed",
+            "sequence_number": 8,
+            "response": {
+                **response_body,
+                "status": "completed",
+                "output": [
+                    {
+                        "id": "msg_abc",
+                        "type": "message",
+                        "status": "completed",
+                        "role": "assistant",
+                        "content": [{"type": "output_text", "text": "OK", "annotations": []}],
+                    }
+                ],
+                "usage": {
+                    "input_tokens": self.INPUT_TOKENS,
+                    "input_tokens_details": {"cached_tokens": 0},
+                    "output_tokens": self.OUTPUT_TOKENS,
+                    "output_tokens_details": {"reasoning_tokens": 0},
+                    "total_tokens": self.INPUT_TOKENS + self.OUTPUT_TOKENS,
+                },
+            },
+        }
+        return [
+            f"data: {json.dumps(created_event)}",
+            f"data: {json.dumps(delta_event)}",
+            f"data: {json.dumps(completed_event)}",
+            "data: [DONE]",
+        ]
+
+    def _logging_obj(self) -> LiteLLMLoggingObj:
+        logging_obj = LiteLLMLoggingObj(
+            model="gpt-4o-mini",
+            messages=[],
+            stream=True,
+            call_type="pass_through_endpoint",
+            start_time=self.start_time,
+            litellm_call_id="323dfe4f-2741-4473-b6e2-000000000000",
+            function_id="1234",
+        )
+        logging_obj.model_call_details["custom_llm_provider"] = "openai"
+        return logging_obj
+
+    def test_streamed_responses_passthrough_spend_log_is_priced(self):
+        """The spend row books the same tokens, spend and `resp_` id as the buffered call."""
+        result = OpenAIPassthroughLoggingHandler._handle_logging_openai_collected_chunks(
+            litellm_logging_obj=self._logging_obj(),
+            passthrough_success_handler_obj=None,
+            url_route="https://api.openai.com/v1/responses",
+            request_body={
+                "model": "gpt-4o-mini",
+                "input": "Say hi in one word.",
+                "max_output_tokens": 16,
+                "stream": True,
+            },
+            endpoint_type=None,
+            start_time=self.start_time,
+            all_chunks=self._responses_stream_chunks(),
+            end_time=self.end_time,
+        )
+
+        spend_log_row = get_logging_payload(
+            kwargs=result["kwargs"],
+            response_obj=result["result"],
+            start_time=self.start_time,
+            end_time=self.end_time,
+        )
+
+        assert spend_log_row["prompt_tokens"] == self.INPUT_TOKENS
+        assert spend_log_row["completion_tokens"] == self.OUTPUT_TOKENS
+        assert spend_log_row["total_tokens"] == self.INPUT_TOKENS + self.OUTPUT_TOKENS
+        assert spend_log_row["spend"] == self.expected_spend
+        assert spend_log_row["request_id"] == self.RESPONSE_ID
+        assert spend_log_row["model"] == "gpt-4o-mini"
+
+        row_metadata = json.loads(spend_log_row["metadata"])
+        assert row_metadata["model_map_information"]["model_map_key"] == self.MODEL_MAP_KEY
+
+
+class TestOpenAIPassthroughEmbeddingsSpendLog:
+    """An OpenAI-passthrough `/v1/embeddings` call must write a priced spend log row
+    (#36646).
+
+    `_is_supported_openai_endpoint` ORed four route predicates, none of which matched
+    `/v1/embeddings`, so the dispatcher never entered the OpenAI handler and billable
+    embedding tokens produced no spend row at all, under-enforcing key budgets.
+    """
+
+    EMBEDDINGS_URL = "https://api.openai.com/v1/embeddings"
+    MODEL = "text-embedding-3-small"
+    PROMPT_TOKENS = 14
+    CALL_ID = "11024cc3-b143-4a63-954a-ec06081df768"
+
+    def setup_method(self):
+        self.start_time = datetime.now()
+        self.end_time = datetime.now()
+        self.expected_spend = self.PROMPT_TOKENS * litellm.model_cost[self.MODEL]["input_cost_per_token"]
+        self.response_body = {
+            "object": "list",
+            "data": [{"object": "embedding", "index": 0, "embedding": [0.0, 1.0]}],
+            "model": self.MODEL,
+            "usage": {"prompt_tokens": self.PROMPT_TOKENS, "total_tokens": self.PROMPT_TOKENS},
+        }
+        self.request_body = {"model": self.MODEL, "input": "hello"}
+
+    def _create_mock_httpx_response(self) -> httpx.Response:
+        mock_response = MagicMock(spec=httpx.Response)
+        mock_response.status_code = 200
+        mock_response.text = json.dumps(self.response_body)
+        mock_response.json.return_value = self.response_body
+        mock_response.headers = {"content-type": "application/json"}
+        return mock_response
+
+    def _logging_obj(self) -> LiteLLMLoggingObj:
+        logging_obj = LiteLLMLoggingObj(
+            model=self.MODEL,
+            messages=[],
+            stream=False,
+            call_type="pass_through_endpoint",
+            start_time=self.start_time,
+            litellm_call_id=self.CALL_ID,
+            function_id="1234",
+        )
+        logging_obj.model_call_details["passthrough_logging_payload"] = PassthroughStandardLoggingPayload(
+            url=self.EMBEDDINGS_URL,
+            request_body=self.request_body,
+            request_method="POST",
+        )
+        return logging_obj
+
+    def test_embeddings_passthrough_spend_log_is_priced(self):
+        """The dispatched call books prompt tokens and cost onto the spend row."""
+        dispatched = PassThroughEndpointLogging().normalize_llm_passthrough_logging_payload(
+            httpx_response=self._create_mock_httpx_response(),
+            response_body=self.response_body,
+            request_body=self.request_body,
+            logging_obj=self._logging_obj(),
+            url_route=self.EMBEDDINGS_URL,
+            result="",
+            start_time=self.start_time,
+            end_time=self.end_time,
+            cache_hit=False,
+            custom_llm_provider="openai",
+            litellm_call_id=self.CALL_ID,
+            litellm_params={},
+            call_type="pass_through_endpoint",
+        )
+
+        assert dispatched["standard_logging_response_object"] is not None
+        assert dispatched["kwargs"]["response_cost"] == self.expected_spend
+
+        spend_log_row = get_logging_payload(
+            kwargs=dispatched["kwargs"],
+            response_obj=dispatched["standard_logging_response_object"],
+            start_time=self.start_time,
+            end_time=self.end_time,
+        )
+
+        assert spend_log_row["prompt_tokens"] == self.PROMPT_TOKENS
+        assert spend_log_row["total_tokens"] == self.PROMPT_TOKENS
+        assert spend_log_row["spend"] == self.expected_spend
+        assert spend_log_row["model"] == self.MODEL
+        assert spend_log_row["custom_llm_provider"] == "openai"
+        assert spend_log_row["request_id"] == self.CALL_ID
+
+
 if __name__ == "__main__":
     pytest.main([__file__])
diff --git a/tests/test_litellm/router_strategy/test_complexity_router.py b/tests/test_litellm/router_strategy/test_complexity_router.py
index e65d79a83f4..cbaac4d89a7 100644
--- a/tests/test_litellm/router_strategy/test_complexity_router.py
+++ b/tests/test_litellm/router_strategy/test_complexity_router.py
@@ -1805,6 +1805,51 @@ class TestLLMClassifier:
         call_kwargs = mock_router_instance.acompletion.call_args.kwargs
         assert call_kwargs["metadata"] == {**request_metadata, "internal_call_origin": "autorouter_classifier"}
 
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "request_kwargs",
+        [
+            pytest.param({"metadata": {"user_api_key": "sk-abc"}}, id="metadata-bucket"),
+            pytest.param(
+                {"litellm_metadata": {"user_api_key": "sk-abc"}}, id="litellm-metadata-bucket"
+            ),
+            pytest.param({}, id="no-caller-context"),
+            pytest.param(None, id="no-request-kwargs"),
+        ],
+    )
+    async def test_aclassify_reaches_the_llm_for_every_caller_metadata_shape(
+        self, llm_classifier_config, request_kwargs
+    ):
+        """Whatever the caller's metadata bucket looks like, the configured classifier must
+        actually run. The forwarded metadata reaches litellm's own metadata handling, which
+        raises "'NoneType' object has no attribute 'update'" on a shape it does not expect;
+        aclassify catches that and silently degrades to heuristic scoring, so the tier is
+        decided by word counting while the config says otherwise. A real Router is used here
+        because a mocked acompletion accepts any shape and never reaches that handling.
+        """
+        real_router = Router(
+            model_list=[
+                {
+                    "model_name": "haiku-classifier",
+                    "litellm_params": {
+                        "model": "openai/haiku-classifier",
+                        "api_key": "sk-classifier",
+                        "mock_response": '{"tier": "COMPLEX"}',
+                    },
+                }
+            ]
+        )
+        router = ComplexityRouter(
+            model_name="test-complexity-router",
+            litellm_router_instance=real_router,
+            complexity_router_config=llm_classifier_config,
+        )
+
+        outcome = await router.aclassify("hi", request_kwargs=request_kwargs)
+
+        assert outcome.cause == "llm_classifier"
+        assert outcome.tier == ComplexityTier.COMPLEX
+
     @pytest.mark.asyncio
     async def test_aclassify_captures_request_body_in_proxy_server_request(
         self, llm_complexity_router, mock_router_instance
diff --git a/tests/test_litellm/test_main.py b/tests/test_litellm/test_main.py
index c05f25430c2..99b1cc826aa 100644
--- a/tests/test_litellm/test_main.py
+++ b/tests/test_litellm/test_main.py
@@ -850,6 +850,36 @@ def test_responses_api_bridge_check_gpt_5_4_tools_with_default_reasoning_routes_
     assert model_info.get("mode") == "responses"
 
 
+@pytest.mark.parametrize("model_name", ["gpt-5.6-sol", "gpt-5.6-luna", "gpt-5.6-terra"])
+def test_responses_api_bridge_check_gpt_5_6_tools_with_default_reasoning_routes_to_responses(
+    monkeypatch, model_name
+):
+    """
+    The whole gpt-5.6 family must bridge on function tools alone. The bridge used to
+    require an explicit reasoning_effort, so a gpt-5.6 call carrying tools and no effort
+    was rejected with "Function tools with reasoning_effort are not supported for
+    gpt-5.6-sol in /v1/chat/completions".
+    """
+    import litellm
+    from litellm.main import responses_api_bridge_check
+
+    monkeypatch.delenv("OPENAI_BASE_URL", raising=False)
+    monkeypatch.delenv("OPENAI_API_BASE", raising=False)
+    monkeypatch.setattr(litellm, "api_base", None)
+
+    with patch("litellm.main._get_model_info_helper") as mock_get_model_info:
+        mock_get_model_info.return_value = {"max_tokens": 128000}
+        model_info, model = responses_api_bridge_check(
+            model=model_name,
+            custom_llm_provider="openai",
+            tools=[{"type": "function", "function": {"name": "get_capital"}}],
+            reasoning_effort=None,
+        )
+
+    assert model == model_name
+    assert model_info.get("mode") == "responses"
+
+
 def test_responses_api_bridge_check_gpt_5_4_tools_with_reasoning_none_stays_chat():
     """
     Explicit reasoning_effort "none" is OpenAI's documented escape hatch that keeps
@@ -2833,9 +2863,17 @@ def _priced_at(prompt_tokens, completion_tokens):
 @pytest.fixture
 def local_cost_map(monkeypatch):
     """The prices these tests assert are the checked-in ones. Setting the environment
-    variable alone does not reload the map, so pin the map itself."""
+    variable alone does not reload the map, so pin the map itself.
+
+    ``get_model_info`` is lru_cached, so pinning ``model_cost`` is not enough on its
+    own: a cached entry warmed against the network-fetched map keeps its old prices
+    and ``completion_cost`` bills at those while the assertions read the pinned map.
+    Clear on the way in and out so entries never leak across tests in either direction."""
     monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
     monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    litellm.get_model_info.cache_clear()
+    yield
+    litellm.get_model_info.cache_clear()
 
 
 def test_a_streamed_response_bills_the_usage_the_provider_reported(local_cost_map):
diff --git a/tests/test_litellm/test_router.py b/tests/test_litellm/test_router.py
index 56e00ecdad6..d00fbf589e3 100644
--- a/tests/test_litellm/test_router.py
+++ b/tests/test_litellm/test_router.py
@@ -6,6 +6,7 @@ import os
 import threading
 from unittest.mock import AsyncMock, MagicMock, patch
 
+import httpx
 import pytest
 
 
@@ -7304,6 +7305,78 @@ async def test_acreate_batch_surfaces_owning_provider_error_without_disable_fall
     assert attempted_models == ["owning-model"]
 
 
+@pytest.mark.asyncio
+async def test_acreate_batch_still_falls_back_within_the_owning_model_group():
+    """Holding a batch inside the model group that owns its input file must not
+    disable fallbacks outright (#35359): the owning group's second deployment is
+    still tried in `order`, and only the cross-group target is skipped."""
+    completion_window_error = "Invalid value: '5m'. Supported values are: '24h'."
+    attempted_models = []
+
+    async def _acreate_batch(**kwargs):
+        model = kwargs["model"]
+        attempted_models.append(model)
+        if model.startswith("azure/"):
+            raise litellm.BadRequestError(
+                message="Error code: 400 - {'error': {'code': 'quotaExceeded'}}",
+                model=model,
+                llm_provider="azure",
+            )
+        raise litellm.BadRequestError(
+            message=completion_window_error,
+            model=model,
+            llm_provider="openai",
+        )
+
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "my-gpt",
+                "litellm_params": {
+                    "model": "openai/gpt-4o-mini",
+                    "api_key": "sk-owning",
+                    "order": 1,
+                },
+                "model_info": {"id": "my-gpt-1"},
+            },
+            {
+                "model_name": "my-gpt",
+                "litellm_params": {
+                    "model": "openai/gpt-4o-mini-backup",
+                    "api_key": "sk-owning",
+                    "order": 2,
+                },
+                "model_info": {"id": "my-gpt-2"},
+            },
+            {
+                "model_name": "my-azure-gpt",
+                "litellm_params": {
+                    "model": "azure/gpt-4o-mini",
+                    "api_key": "sk-fallback",
+                    "api_base": "https://fallback.openai.azure.com",
+                    "api_version": "2024-08-01-preview",
+                },
+                "model_info": {"id": "my-azure-gpt-1"},
+            },
+        ],
+        fallbacks=[{"my-gpt": ["my-azure-gpt"]}],
+        num_retries=0,
+    )
+
+    with patch.object(litellm, "acreate_batch", new=_acreate_batch):
+        with pytest.raises(litellm.BadRequestError) as raised:
+            await router.acreate_batch(
+                model="my-gpt",
+                input_file_id="file-owned-by-my-gpt",
+                endpoint="/v1/chat/completions",
+                completion_window="5m",
+            )
+
+    assert "24h" in str(raised.value)
+    assert "quotaExceeded" not in str(raised.value)
+    assert attempted_models == ["openai/gpt-4o-mini", "openai/gpt-4o-mini-backup"]
+
+
 @pytest.mark.asyncio
 async def test_acreate_batch_request_bedrock_tags_override_deployment_tags():
     import httpx
@@ -8264,6 +8337,94 @@ class TestTaggedAutoRouterOnSharedModelName:
         assert marker_only._model_name_has_plain_deployments("gpt4o") is False
 
 
+class TestAutoRouterSharedModelNameConnectionParams:
+    """A plain deployment sharing its model_name with an `auto_router/` marker must not have
+    its api_base and api_key grafted onto the routed tier's outbound call (#36619)."""
+
+    PLAIN_API_BASE = "https://plain-sibling.openai.example/v1"
+    PLAIN_API_KEY = "sk-plain-sibling-secret"
+
+    class _FixedRouteLayer:
+        def __call__(self, text: str):
+            from semantic_router.schema import RouteChoice
+
+            return RouteChoice(name="gemini-flash")
+
+    @classmethod
+    def _router(cls, plain_entry_first: bool) -> "litellm.Router":
+        pytest.importorskip("semantic_router", reason="auto-router needs the semantic-router extra")
+        plain = {
+            "model_name": "gpt4o",
+            "litellm_params": {
+                "model": "openai/gpt-4o",
+                "api_key": cls.PLAIN_API_KEY,
+                "api_base": cls.PLAIN_API_BASE,
+            },
+        }
+        marker = {
+            "model_name": "gpt4o",
+            "litellm_params": {
+                "model": "auto_router/gpt4o-router",
+                "auto_router_config": json.dumps(
+                    {"routes": [{"name": "gemini-flash", "utterances": ["capital city questions"]}]}
+                ),
+                "auto_router_default_model": "gemini-flash",
+                "auto_router_embedding_model": "text-embedding-3-small",
+                "drop_params": True,
+            },
+        }
+        tier = {
+            "model_name": "gemini-flash",
+            "litellm_params": {"model": "gemini/gemini-3.6-flash", "api_key": "sk-tier-key"},
+        }
+        shared_name_entries = [plain, marker] if plain_entry_first else [marker, plain]
+        router = litellm.Router(model_list=[*shared_name_entries, tier])
+        router.auto_routers["gpt4o"][0].strategy.routelayer = cls._FixedRouteLayer()
+        return router
+
+    @staticmethod
+    def _gemini_response() -> httpx.Response:
+        return httpx.Response(
+            status_code=200,
+            json={
+                "candidates": [
+                    {"content": {"parts": [{"text": "Paris"}], "role": "model"}, "finishReason": "STOP"}
+                ],
+                "usageMetadata": {"promptTokenCount": 5, "candidatesTokenCount": 1, "totalTokenCount": 6},
+                "modelVersion": "gemini-3.6-flash",
+            },
+            request=httpx.Request("POST", "https://generativelanguage.googleapis.com"),
+        )
+
+    @pytest.mark.parametrize(
+        "plain_entry_first", [True, False], ids=["plain_entry_first", "marker_entry_first"]
+    )
+    async def test_routed_tier_call_goes_out_on_its_own_endpoint_and_credentials(self, plain_entry_first):
+        """The outbound provider request for the routed tier hits the tier's own Gemini host
+        with the tier's own key, never the plain sibling's api_base or api_key."""
+        from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
+
+        router = self._router(plain_entry_first)
+
+        with patch.object(
+            AsyncHTTPHandler, "post", new_callable=AsyncMock, return_value=self._gemini_response()
+        ) as mock_post:
+            await router.acompletion(
+                model="gpt4o",
+                messages=[{"role": "user", "content": "What is the capital of France?"}],
+            )
+
+        call = mock_post.call_args
+        outbound_url = str(call.kwargs["url"] if "url" in call.kwargs else call.args[0])
+        outbound_headers = dict(call.kwargs.get("headers") or {})
+
+        assert "generativelanguage.googleapis.com" in outbound_url
+        assert "gemini-3.6-flash" in outbound_url
+        assert self.PLAIN_API_BASE not in outbound_url
+        assert self.PLAIN_API_KEY not in outbound_url
+        assert self.PLAIN_API_KEY not in json.dumps(outbound_headers)
+
+
 class TestGetAllowedFailsFromPolicy:
     def _make_router(self, **policy_kwargs) -> litellm.Router:
         from litellm.types.router import AllowedFailsPolicy

From 23e64c8b3d89b781642703e4543aa45e56002881 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 15:25:59 -0700
Subject: [PATCH 55/93] chore(responses): keep the session lookup inside the
 type-discipline budget

---
 .../litellm_completion_transformation/session_handler.py   | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/litellm/responses/litellm_completion_transformation/session_handler.py b/litellm/responses/litellm_completion_transformation/session_handler.py
index 2008006e6cf..1566bb1bdd7 100644
--- a/litellm/responses/litellm_completion_transformation/session_handler.py
+++ b/litellm/responses/litellm_completion_transformation/session_handler.py
@@ -108,7 +108,10 @@ class ResponsesSessionHandler:
             if isinstance(_response_input_param, (str, list)):
                 response_input_param = _response_input_param
             elif isinstance(_response_input_param, dict):
-                response_input_param = cast(ResponseInputParam, [_response_input_param])
+                response_input_param = cast(
+                    ResponseInputParam,
+                    [_response_input_param],  # mutable-ok: a lone input item still has to arrive as a list
+                )
 
         if response_input_param:
             chat_completion_messages = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages(
@@ -301,4 +304,4 @@ class ResponsesSessionHandler:
                 return spend_logs
 
         verbose_proxy_logger.debug("Found no spend logs for previous response id %s", response_id)
-        return []
+        return []  # mutable-ok: an empty result the caller only reads

From 8b566a7f0aa3e1c935c0d84e646379a505d6904d Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 15:28:12 -0700
Subject: [PATCH 56/93] fix(interactions): stop two settlement paths from
 pinning the budget reservation

Both leave a background interaction's pre-call reservation open, so the
serving process keeps refusing traffic on the key at the estimated cost
while its recorded spend stays near zero.

A raise from the completion event propagated out with the settlement gate
already claimed, and nothing retries a claim that is set, so the reservation
was never released. Billing now releases it on the way out.

`requires_action` was missing from the terminal set. It is terminal for the
interaction it names: the API has no operation that resumes one, and a caller
answers a tool request by creating a new interaction whose
`previous_interaction_id` points at it. A function-calling background create
that stopped there was polled until the 3600s timeout, losing the tokens it
had already spent producing the tool request and holding its reservation open
for that whole window.
---
 .../interactions/background_cost_polling.py   | 28 ++++++-
 .../test_background_cost_polling.py           | 78 +++++++++++++++++++
 2 files changed, 103 insertions(+), 3 deletions(-)

diff --git a/litellm/interactions/background_cost_polling.py b/litellm/interactions/background_cost_polling.py
index f2957d08840..5d7dca80b73 100644
--- a/litellm/interactions/background_cost_polling.py
+++ b/litellm/interactions/background_cost_polling.py
@@ -10,6 +10,14 @@ billing: it schedules a poll task that fetches the interaction until it
 reaches a terminal status and logs the final usage as a single success event
 attributed to the original request.
 
+``requires_action`` is terminal for the interaction it names. The API has no
+operation that resumes one: a caller answers a tool request by creating a new
+interaction whose ``previous_interaction_id`` points at it, and that new
+interaction bills itself. The paused interaction keeps the tokens it already
+spent producing the tool request, so it is billed and settled where it stops
+rather than polled until the timeout, which would both lose that usage and
+hold its budget reservation open for the whole timeout window.
+
 Deleting an interaction makes every subsequent poll fail, which would let a
 caller retrieve the completed output themselves and then delete it before the
 poll task settles, leaving the work unbilled and the budget reservation
@@ -39,7 +47,7 @@ from litellm.types.interactions import InteractionsAPIResponse
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 
-_TERMINAL_STATUSES = frozenset({"completed", "failed", "cancelled", "incomplete", "budget_exceeded"})
+_TERMINAL_STATUSES = frozenset({"completed", "failed", "cancelled", "incomplete", "budget_exceeded", "requires_action"})
 
 
 @dataclass(frozen=True, slots=True)
@@ -125,7 +133,7 @@ async def poll_and_log_background_interaction_cost(
         if not _claim_settlement(context.logging_obj):
             return
         if response.usage is not None:
-            await context.logging_obj.async_log_background_interaction_completion(result=response)
+            await _bill_settled_interaction(logging_obj=context.logging_obj, response=response)
         else:
             await _release_open_budget_reservation(logging_obj=context.logging_obj)
         return
@@ -162,6 +170,20 @@ async def _release_open_budget_reservation(logging_obj: "LiteLLMLoggingObj") ->
         verbose_logger.exception("Failed to release budget reservation for an unbilled background interaction")
 
 
+async def _bill_settled_interaction(logging_obj: "LiteLLMLoggingObj", response: InteractionsAPIResponse) -> None:
+    """
+    Claiming the settlement makes the claimer solely responsible for the
+    reservation, and no one retries a claim that is already set. A billing
+    failure here must therefore release the reservation on its way out, or it
+    stays pinned at the estimated cost until the whole poll times out.
+    """
+    try:
+        await logging_obj.async_log_background_interaction_completion(result=response)
+    except Exception:
+        await _release_open_budget_reservation(logging_obj=logging_obj)
+        raise
+
+
 def is_pollable_background_interaction(response: InteractionsAPIResponse) -> bool:
     """
     The single gate deciding whether a create's response gets a poll task.
@@ -247,6 +269,6 @@ async def maybe_settle_background_interaction_before_delete(
     if not _claim_settlement(context.logging_obj):
         return
     if response.status in _TERMINAL_STATUSES and response.usage is not None:
-        await context.logging_obj.async_log_background_interaction_completion(result=response)
+        await _bill_settled_interaction(logging_obj=context.logging_obj, response=response)
         return
     await _release_open_budget_reservation(logging_obj=context.logging_obj)
diff --git a/tests/test_litellm/interactions/test_background_cost_polling.py b/tests/test_litellm/interactions/test_background_cost_polling.py
index 7908e0e8f17..759bdc71dfc 100644
--- a/tests/test_litellm/interactions/test_background_cost_polling.py
+++ b/tests/test_litellm/interactions/test_background_cost_polling.py
@@ -59,6 +59,10 @@ def _logging_obj_with_reservation(reservation: dict) -> LitellmLogging:
     return _logging_obj(litellm_params={"metadata": {"user_api_key_budget_reservation": reservation}})
 
 
+async def _raise_on_billing(result: InteractionsAPIResponse) -> None:
+    raise RuntimeError("cost calculation failed for a settled background interaction")
+
+
 def _context(logging_obj: LitellmLogging, timeout_seconds: float = 1.0) -> BackgroundInteractionPollContext:
     return BackgroundInteractionPollContext(
         interaction_id="interactions/bg-abc",
@@ -120,6 +124,33 @@ async def test_poller_bills_once_when_interaction_completes():
     assert logging_obj.model_call_details["standard_logging_object"]["total_tokens"] == 175
 
 
+@pytest.mark.asyncio
+async def test_poller_bills_an_interaction_paused_for_a_tool_result():
+    logging_obj = _logging_obj()
+    fetch, calls = _fetch_sequence(
+        _response("in_progress", with_usage=False),
+        _response("requires_action", with_usage=True),
+    )
+
+    await poll_and_log_background_interaction_cost(_context(logging_obj), fetch_interaction=fetch)
+
+    assert len(calls) == 2
+    assert logging_obj.model_call_details["response_cost"] > 0
+    assert logging_obj.model_call_details["standard_logging_object"]["total_tokens"] == 175
+
+
+@pytest.mark.asyncio
+async def test_poller_does_not_pin_the_budget_for_an_interaction_paused_for_a_tool_result():
+    reservation = _reservation()
+    logging_obj = _logging_obj_with_reservation(reservation)
+    fetch, _ = _fetch_sequence(_response("requires_action", with_usage=True))
+
+    await poll_and_log_background_interaction_cost(_context(logging_obj), fetch_interaction=fetch)
+
+    assert logging_obj.model_call_details["response_cost"] > 0
+    assert reservation["finalized"] is False
+
+
 @pytest.mark.asyncio
 async def test_poller_stops_without_billing_on_terminal_status_without_usage():
     logging_obj = _logging_obj()
@@ -170,6 +201,19 @@ async def test_poller_releases_budget_reservation_on_timeout_give_up():
     assert reservation["finalized"] is True
 
 
+@pytest.mark.asyncio
+async def test_poller_releases_budget_reservation_when_billing_raises():
+    reservation = _reservation()
+    logging_obj = _logging_obj_with_reservation(reservation)
+    fetch, _ = _fetch_sequence(_response("completed", with_usage=True))
+    logging_obj.async_log_background_interaction_completion = _raise_on_billing
+
+    with pytest.raises(RuntimeError):
+        await poll_and_log_background_interaction_cost(_context(logging_obj), fetch_interaction=fetch)
+
+    assert reservation["finalized"] is True
+
+
 @pytest.mark.asyncio
 async def test_poller_leaves_reservation_reconciliation_to_the_completion_event():
     reservation = _reservation()
@@ -248,6 +292,22 @@ def _register_poll(logging_obj: LitellmLogging, poll_fetch=None) -> asyncio.Task
     return task
 
 
+@pytest.mark.asyncio
+async def test_delete_settlement_bills_an_interaction_paused_for_a_tool_result():
+    logging_obj = _logging_obj()
+    task = _register_poll(logging_obj)
+    fetch, calls = _fetch_sequence(_response("requires_action", with_usage=True))
+
+    await maybe_settle_background_interaction_before_delete(
+        interaction_id="interactions/bg-abc",
+        fetch_interaction=fetch,
+    )
+
+    assert len(calls) == 1
+    assert logging_obj.model_call_details["response_cost"] > 0
+    await asyncio.wait_for(task, timeout=5)
+
+
 @pytest.mark.asyncio
 async def test_delete_settlement_bills_pending_background_interaction():
     logging_obj = _logging_obj()
@@ -299,6 +359,24 @@ async def test_delete_settlement_releases_reservation_when_prefetch_fails():
     await asyncio.wait_for(task, timeout=5)
 
 
+@pytest.mark.asyncio
+async def test_delete_settlement_releases_reservation_when_billing_raises():
+    reservation = _reservation()
+    logging_obj = _logging_obj_with_reservation(reservation)
+    task = _register_poll(logging_obj)
+    fetch, _ = _fetch_sequence(_response("completed", with_usage=True))
+    logging_obj.async_log_background_interaction_completion = _raise_on_billing
+
+    with pytest.raises(RuntimeError):
+        await maybe_settle_background_interaction_before_delete(
+            interaction_id="interactions/bg-abc",
+            fetch_interaction=fetch,
+        )
+
+    assert reservation["finalized"] is True
+    await asyncio.wait_for(task, timeout=5)
+
+
 @pytest.mark.asyncio
 async def test_delete_settlement_ignores_interactions_without_pending_poll():
     fetch, calls = _fetch_sequence(_response("completed", with_usage=True))

From da3dcb139d207c9cdff006cd2fcd022007782f43 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 15:37:37 -0700
Subject: [PATCH 57/93] fix(databricks): charge the input rate for cache tokens
 on models with no cache pricing

The shared cost calculator treats a missing cache rate as free, so routing
Databricks through it billed cached tokens at zero on the 14 entries that
publish no cache pricing. On a 10,000 token prompt with 8,000 cache reads
that is $0.0010000 against the correct $0.0050001, a fivefold undercharge.

Those entries now declare cache rates equal to their input rate, which is
what a model with no caching discount should charge, and a test pins every
priced Databricks entry to declaring cache rates so no future entry can
regress into it.

Also repoints the provider-neutral generalization test off an id the new
Opus 5 entry now shadows, adds backup-to-main parity tests for the five new
entries, pins that Databricks Claude is never auto-injected with cache
control despite reporting caching support, and trims the Sonnet 5 pricing
note, which is served on an unauthenticated route.
---
 ...odel_prices_and_context_window_backup.json | 30 ++++++++++-
 model_prices_and_context_window.json          | 30 ++++++++++-
 .../test_anthropic_cache_control_hook.py      |  8 +++
 .../test_fallback_generalizations.py          |  4 +-
 .../test_databricks_cost_calculator.py        | 50 +++++++++++++++++++
 5 files changed, 119 insertions(+), 3 deletions(-)

diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index e296e828b92..f1e330cb4ff 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -14551,6 +14551,8 @@
         ]
     },
     "databricks/databricks-bge-large-en": {
+        "cache_creation_input_token_cost": 1.0003e-07,
+        "cache_read_input_token_cost": 1.0003e-07,
         "input_cost_per_token": 1.0003e-07,
         "input_dbu_cost_per_token": 1.429e-06,
         "litellm_provider": "databricks",
@@ -14904,7 +14906,7 @@
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Anthropic's introductory launch rates (28.571 input / 142.857 output DBU) run through 2026-08-31. The standard rates listed here, equal to Sonnet 4.5 / 4.6, are used instead because pricing carries no expiry date, and undercharging past the window would let spend outrun enforced budgets."
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Introductory launch rates of 28.571 input / 142.857 output DBU run through 2026-08-31; the standard rates are listed here because entries carry no expiry date."
         },
         "mode": "chat",
         "output_cost_per_token": 1.5000020000000002e-05,
@@ -15042,6 +15044,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-gemma-3-12b": {
+        "cache_creation_input_token_cost": 1.5000999999999998e-07,
+        "cache_read_input_token_cost": 1.5000999999999998e-07,
         "input_cost_per_token": 1.5000999999999998e-07,
         "input_dbu_cost_per_token": 2.1429999999999996e-06,
         "litellm_provider": "databricks",
@@ -15273,6 +15277,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-oss-120b": {
+        "cache_creation_input_token_cost": 1.5000999999999998e-07,
+        "cache_read_input_token_cost": 1.5000999999999998e-07,
         "input_cost_per_token": 1.5000999999999998e-07,
         "input_dbu_cost_per_token": 2.1429999999999996e-06,
         "litellm_provider": "databricks",
@@ -15288,6 +15294,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-gpt-oss-20b": {
+        "cache_creation_input_token_cost": 7e-08,
+        "cache_read_input_token_cost": 7e-08,
         "input_cost_per_token": 7e-08,
         "input_dbu_cost_per_token": 1e-06,
         "litellm_provider": "databricks",
@@ -15303,6 +15311,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-gte-large-en": {
+        "cache_creation_input_token_cost": 1.2999000000000001e-07,
+        "cache_read_input_token_cost": 1.2999000000000001e-07,
         "input_cost_per_token": 1.2999000000000001e-07,
         "input_dbu_cost_per_token": 1.857e-06,
         "litellm_provider": "databricks",
@@ -15318,6 +15328,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-llama-2-70b-chat": {
+        "cache_creation_input_token_cost": 5.0001e-07,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.0001e-07,
         "input_dbu_cost_per_token": 7.143e-06,
         "litellm_provider": "databricks",
@@ -15334,6 +15346,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-llama-4-maverick": {
+        "cache_creation_input_token_cost": 5.0001e-07,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.0001e-07,
         "input_dbu_cost_per_token": 7.143e-06,
         "litellm_provider": "databricks",
@@ -15350,6 +15364,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-meta-llama-3-1-405b-instruct": {
+        "cache_creation_input_token_cost": 5.00003e-06,
+        "cache_read_input_token_cost": 5.00003e-06,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -15366,6 +15382,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-meta-llama-3-1-8b-instruct": {
+        "cache_creation_input_token_cost": 1.5000999999999998e-07,
+        "cache_read_input_token_cost": 1.5000999999999998e-07,
         "input_cost_per_token": 1.5000999999999998e-07,
         "input_dbu_cost_per_token": 2.1429999999999996e-06,
         "litellm_provider": "databricks",
@@ -15381,6 +15399,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-meta-llama-3-3-70b-instruct": {
+        "cache_creation_input_token_cost": 5.0001e-07,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.0001e-07,
         "input_dbu_cost_per_token": 7.143e-06,
         "litellm_provider": "databricks",
@@ -15397,6 +15417,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-meta-llama-3-70b-instruct": {
+        "cache_creation_input_token_cost": 1.00002e-06,
+        "cache_read_input_token_cost": 1.00002e-06,
         "input_cost_per_token": 1.00002e-06,
         "input_dbu_cost_per_token": 1.4286e-05,
         "litellm_provider": "databricks",
@@ -15413,6 +15435,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-mixtral-8x7b-instruct": {
+        "cache_creation_input_token_cost": 5.0001e-07,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.0001e-07,
         "input_dbu_cost_per_token": 7.143e-06,
         "litellm_provider": "databricks",
@@ -15429,6 +15453,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-mpt-30b-instruct": {
+        "cache_creation_input_token_cost": 1.00002e-06,
+        "cache_read_input_token_cost": 1.00002e-06,
         "input_cost_per_token": 1.00002e-06,
         "input_dbu_cost_per_token": 1.4286e-05,
         "litellm_provider": "databricks",
@@ -15445,6 +15471,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-mpt-7b-instruct": {
+        "cache_creation_input_token_cost": 5.0001e-07,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.0001e-07,
         "input_dbu_cost_per_token": 7.143e-06,
         "litellm_provider": "databricks",
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index e296e828b92..f1e330cb4ff 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -14551,6 +14551,8 @@
         ]
     },
     "databricks/databricks-bge-large-en": {
+        "cache_creation_input_token_cost": 1.0003e-07,
+        "cache_read_input_token_cost": 1.0003e-07,
         "input_cost_per_token": 1.0003e-07,
         "input_dbu_cost_per_token": 1.429e-06,
         "litellm_provider": "databricks",
@@ -14904,7 +14906,7 @@
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Anthropic's introductory launch rates (28.571 input / 142.857 output DBU) run through 2026-08-31. The standard rates listed here, equal to Sonnet 4.5 / 4.6, are used instead because pricing carries no expiry date, and undercharging past the window would let spend outrun enforced budgets."
+            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Introductory launch rates of 28.571 input / 142.857 output DBU run through 2026-08-31; the standard rates are listed here because entries carry no expiry date."
         },
         "mode": "chat",
         "output_cost_per_token": 1.5000020000000002e-05,
@@ -15042,6 +15044,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-gemma-3-12b": {
+        "cache_creation_input_token_cost": 1.5000999999999998e-07,
+        "cache_read_input_token_cost": 1.5000999999999998e-07,
         "input_cost_per_token": 1.5000999999999998e-07,
         "input_dbu_cost_per_token": 2.1429999999999996e-06,
         "litellm_provider": "databricks",
@@ -15273,6 +15277,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-oss-120b": {
+        "cache_creation_input_token_cost": 1.5000999999999998e-07,
+        "cache_read_input_token_cost": 1.5000999999999998e-07,
         "input_cost_per_token": 1.5000999999999998e-07,
         "input_dbu_cost_per_token": 2.1429999999999996e-06,
         "litellm_provider": "databricks",
@@ -15288,6 +15294,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-gpt-oss-20b": {
+        "cache_creation_input_token_cost": 7e-08,
+        "cache_read_input_token_cost": 7e-08,
         "input_cost_per_token": 7e-08,
         "input_dbu_cost_per_token": 1e-06,
         "litellm_provider": "databricks",
@@ -15303,6 +15311,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-gte-large-en": {
+        "cache_creation_input_token_cost": 1.2999000000000001e-07,
+        "cache_read_input_token_cost": 1.2999000000000001e-07,
         "input_cost_per_token": 1.2999000000000001e-07,
         "input_dbu_cost_per_token": 1.857e-06,
         "litellm_provider": "databricks",
@@ -15318,6 +15328,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-llama-2-70b-chat": {
+        "cache_creation_input_token_cost": 5.0001e-07,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.0001e-07,
         "input_dbu_cost_per_token": 7.143e-06,
         "litellm_provider": "databricks",
@@ -15334,6 +15346,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-llama-4-maverick": {
+        "cache_creation_input_token_cost": 5.0001e-07,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.0001e-07,
         "input_dbu_cost_per_token": 7.143e-06,
         "litellm_provider": "databricks",
@@ -15350,6 +15364,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-meta-llama-3-1-405b-instruct": {
+        "cache_creation_input_token_cost": 5.00003e-06,
+        "cache_read_input_token_cost": 5.00003e-06,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -15366,6 +15382,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-meta-llama-3-1-8b-instruct": {
+        "cache_creation_input_token_cost": 1.5000999999999998e-07,
+        "cache_read_input_token_cost": 1.5000999999999998e-07,
         "input_cost_per_token": 1.5000999999999998e-07,
         "input_dbu_cost_per_token": 2.1429999999999996e-06,
         "litellm_provider": "databricks",
@@ -15381,6 +15399,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-meta-llama-3-3-70b-instruct": {
+        "cache_creation_input_token_cost": 5.0001e-07,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.0001e-07,
         "input_dbu_cost_per_token": 7.143e-06,
         "litellm_provider": "databricks",
@@ -15397,6 +15417,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-meta-llama-3-70b-instruct": {
+        "cache_creation_input_token_cost": 1.00002e-06,
+        "cache_read_input_token_cost": 1.00002e-06,
         "input_cost_per_token": 1.00002e-06,
         "input_dbu_cost_per_token": 1.4286e-05,
         "litellm_provider": "databricks",
@@ -15413,6 +15435,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-mixtral-8x7b-instruct": {
+        "cache_creation_input_token_cost": 5.0001e-07,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.0001e-07,
         "input_dbu_cost_per_token": 7.143e-06,
         "litellm_provider": "databricks",
@@ -15429,6 +15453,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-mpt-30b-instruct": {
+        "cache_creation_input_token_cost": 1.00002e-06,
+        "cache_read_input_token_cost": 1.00002e-06,
         "input_cost_per_token": 1.00002e-06,
         "input_dbu_cost_per_token": 1.4286e-05,
         "litellm_provider": "databricks",
@@ -15445,6 +15471,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-mpt-7b-instruct": {
+        "cache_creation_input_token_cost": 5.0001e-07,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.0001e-07,
         "input_dbu_cost_per_token": 7.143e-06,
         "litellm_provider": "databricks",
diff --git a/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py b/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py
index b6e063a6d94..9281a80dfa5 100644
--- a/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py
+++ b/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py
@@ -1599,6 +1599,14 @@ class TestEnableAnthropicPromptCaching:
         assert supports_prompt_caching(model=model, custom_llm_provider=provider) is True
         assert self._points(model=model, provider=provider) == []
 
+    def test_databricks_claude_not_injected_despite_caching_support(self, monkeypatch):
+        from litellm.utils import supports_prompt_caching
+
+        monkeypatch.setattr(litellm, "enable_anthropic_prompt_caching", True)
+        model = "databricks/databricks-claude-sonnet-4-5"
+        assert supports_prompt_caching(model=model, custom_llm_provider="databricks") is True
+        assert self._points(model=model, provider="databricks") == []
+
     def test_model_without_caching_support_not_injected(self, monkeypatch):
         monkeypatch.setattr(litellm, "enable_anthropic_prompt_caching", True)
         assert self._points(model="anthropic.claude-3-5-sonnet-20240620-v1:0", provider="bedrock") == []
diff --git a/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py b/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py
index 882429fd7cd..0587628e2fe 100644
--- a/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py
+++ b/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py
@@ -378,7 +378,7 @@ def test_shipped_rules_flag_unmapped_fable_as_always_on_thinking(shipped_cost_ma
     "model,provider",
     [
         ("claude-opus-4-9@20260101", "vertex_ai"),
-        ("databricks-claude-opus-5-1", "databricks"),
+        ("databricks-claude-haiku-5-1", "databricks"),
     ],
 )
 def test_shipped_rules_are_provider_neutral_for_unmapped_ids(shipped_cost_map, model, provider):
@@ -388,6 +388,8 @@ def test_shipped_rules_are_provider_neutral_for_unmapped_ids(shipped_cost_map, m
     assert info["supports_adaptive_thinking"] is True
     assert info["supports_mid_conversation_system"] is True
     assert info["supports_function_calling"] is True
+    assert not info.get("input_cost_per_token")
+    assert not info.get("output_cost_per_token")
 
 
 @pytest.mark.parametrize(
diff --git a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
index 9353292c668..102a861fe1a 100644
--- a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
+++ b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
@@ -1,4 +1,6 @@
+import json
 from collections.abc import Iterator
+from pathlib import Path
 from typing import Final
 
 import pytest
@@ -7,6 +9,17 @@ import litellm
 from litellm.llms.databricks.cost_calculator import cost_per_token
 from litellm.types.utils import ModelInfo, Usage
 
+REPO_ROOT: Final = Path(__file__).parents[4]
+MAIN_PRICES: Final = REPO_ROOT / "model_prices_and_context_window.json"
+BACKUP_PRICES: Final = REPO_ROOT / "litellm" / "model_prices_and_context_window_backup.json"
+NEW_MODELS: Final = (
+    "databricks/databricks-claude-opus-4-7",
+    "databricks/databricks-claude-opus-4-8",
+    "databricks/databricks-claude-opus-5",
+    "databricks/databricks-claude-sonnet-5",
+    "databricks/databricks-claude-fable-5",
+)
+
 
 @pytest.fixture
 def local_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> Iterator[None]:
@@ -91,6 +104,43 @@ def test_new_models_carry_cache_pricing(local_model_cost_map: None, model: str)
     assert info["supports_prompt_caching"] is True
 
 
+def test_every_priced_databricks_model_declares_cache_rates(local_model_cost_map: None) -> None:
+    undeclared: Final = [
+        model
+        for model, info in litellm.model_cost.items()
+        if model.startswith("databricks/")
+        and info.get("input_cost_per_token") is not None
+        and info.get("cache_read_input_token_cost") is None
+    ]
+
+    assert undeclared == []
+
+
+def test_models_without_a_cache_discount_bill_cache_tokens_at_the_input_rate(
+    local_model_cost_map: None,
+) -> None:
+    model: Final = "databricks/databricks-meta-llama-3-3-70b-instruct"
+    info: Final = _model_info(model)
+    usage: Final = Usage(
+        prompt_tokens=10000,
+        completion_tokens=100,
+        total_tokens=10100,
+        cache_read_input_tokens=8000,
+    )
+
+    prompt_cost, _ = cost_per_token(model=model, usage=usage)
+
+    assert prompt_cost == pytest.approx(10000 * info["input_cost_per_token"])
+
+
+@pytest.mark.parametrize("model", NEW_MODELS)
+def test_backup_price_map_matches_main(model: str) -> None:
+    main_cost: Final = json.loads(MAIN_PRICES.read_text())
+    backup_cost: Final = json.loads(BACKUP_PRICES.read_text())
+
+    assert backup_cost.get(model) == main_cost.get(model)
+
+
 def test_sonnet_5_ships_standard_rates_not_introductory(local_model_cost_map: None) -> None:
     sonnet_5: Final = _model_info("databricks/databricks-claude-sonnet-5")
     sonnet_4_6: Final = _model_info("databricks/databricks-claude-sonnet-4-6")

From e487e470c732c447050a2a40d1ff2f270b1f6397 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 15:51:17 -0700
Subject: [PATCH 58/93] test(databricks): pin the cache-control test to the
 in-repo cost map

The new supports_prompt_caching assertion reads a capability this branch
adds to the registry, so it only holds against the bundled map. CI leaves
LITELLM_LOCAL_MODEL_COST_MAP unset and fetches main's copy, which lags the
branch until merge, so the test failed there while passing locally.

Use the local_model_cost_map fixture the repo already provides, matching
what the other two test files in this change do.
---
 .../integrations/test_anthropic_cache_control_hook.py           | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py b/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py
index 9281a80dfa5..cf3318b32fe 100644
--- a/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py
+++ b/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py
@@ -1599,7 +1599,7 @@ class TestEnableAnthropicPromptCaching:
         assert supports_prompt_caching(model=model, custom_llm_provider=provider) is True
         assert self._points(model=model, provider=provider) == []
 
-    def test_databricks_claude_not_injected_despite_caching_support(self, monkeypatch):
+    def test_databricks_claude_not_injected_despite_caching_support(self, monkeypatch, local_model_cost_map):
         from litellm.utils import supports_prompt_caching
 
         monkeypatch.setattr(litellm, "enable_anthropic_prompt_caching", True)

From 68bda9499533545065299c4995f74214d0c92e05 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 15:53:12 -0700
Subject: [PATCH 59/93] chore: mark the new API payload literals for the
 type-discipline budget

---
 .../litellm_responses_transformation/transformation.py     | 7 ++++---
 .../responses_adapters/streaming_iterator.py               | 5 ++++-
 .../responses_adapters/transformation.py                   | 4 ++--
 3 files changed, 10 insertions(+), 6 deletions(-)

diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py
index 3e55c3c637e..cf227cfa7d1 100644
--- a/litellm/completion_extras/litellm_responses_transformation/transformation.py
+++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py
@@ -94,13 +94,14 @@ def _reasoning_input_items(msg: "AllMessageValues") -> list[dict[str, object]]:
     Stored reasoning items win because they carry an id the Responses API minted; thinking
     blocks are the fallback for turns that arrived over another API surface.
     """
-    stored: Final = [_reasoning_item_to_response_input(r_item) for r_item in _get_reasoning_items(msg)]
+    items: Final = _get_reasoning_items(msg)
+    stored: Final = [_reasoning_item_to_response_input(item) for item in items]  # mutable-ok: API message payload
     if stored:
         return stored
     raw_blocks: Final = msg.get("thinking_blocks") or ()
     blocks: Final = cast("Iterable[ChatCompletionThinkingBlock]", raw_blocks)  # cast-ok: untyped client json
     from_thinking: Final = responses_reasoning_item_from_thinking_blocks(blocks)
-    return [] if from_thinking is None else [dict(from_thinking)]
+    return [] if from_thinking is None else [dict(from_thinking)]  # mutable-ok: API message payload
 
 
 def _build_reasoning_item(
@@ -393,7 +394,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
                 input_items.extend(_reasoning_input_items(msg))
                 if content:
                     input_items.append(
-                        {
+                        {  # mutable-ok: API message payload
                             "type": "message",
                             "role": "assistant",
                             "content": self._convert_content_to_responses_format(content, "assistant"),
diff --git a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py
index 5577d4a9c2d..292d2622c7f 100644
--- a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py
+++ b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py
@@ -152,7 +152,10 @@ class AnthropicResponsesStreamWrapper:
             if block_idx < 0:
                 if not delta:
                     return
-                block_idx = self._open_block(item_id, {"type": "thinking", "thinking": "", "signature": ""})
+                block_idx = self._open_block(
+                    item_id,
+                    {"type": "thinking", "thinking": "", "signature": ""},  # mutable-ok: API message payload
+                )
             self._chunk_queue.append(
                 {
                     "type": "content_block_delta",
diff --git a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
index 1a6b0498a52..23a9a60d810 100644
--- a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
@@ -148,13 +148,13 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
         if btype == "thinking":
             blocks: Final = cast(tuple[ChatCompletionThinkingBlock, ...], group)  # cast-ok: untrusted client payload
             reasoning_item: Final = responses_reasoning_item_from_thinking_blocks(blocks)
-            return None if reasoning_item is None else dict(reasoning_item)
+            return None if reasoning_item is None else dict(reasoning_item)  # mutable-ok: API message payload
         if btype == "tool_use":
             return {  # mutable-ok: API message payload
                 "type": "function_call",
                 "call_id": first.get("id", ""),
                 "name": first.get("name", ""),
-                "arguments": json.dumps(first.get("input", {})),
+                "arguments": json.dumps(first.get("input", {})),  # mutable-ok: API message payload
             }
         return None
 

From 0ab8ef60bf86f4fbc61359488c0d967f75b01a9b Mon Sep 17 00:00:00 2001
From: Cursor Agent <cursoragent@cursor.com>
Date: Sat, 22 Aug 2026 22:54:08 +0000
Subject: [PATCH 60/93] fix(interactions): stop the unpollable-create path from
 firing a false cost-tracking alert

The tightened gate correctly stopped deferring the reservation release for
InteractionsAPIResponses the scheduler will not poll (terminal status, or
in_progress without an id), but the response then fell through into the
generic 'Cost tracking failed' raise and the failed_tracking_alert path.
A create returning failed, cancelled, requires_action, incomplete,
budget_exceeded, or an id-less in_progress without usage therefore released
its reservation as intended and, in the same breath, alerted operators for a
legitimate no-usage response, both creating noise and masking real
cost-tracking failures.

The two gates are now nested under a single 'unbilled interaction response'
outer check, so any InteractionsAPIResponse with no usage takes either the
defer path (pollable, polling on) or the release-and-return path, and none
of them fall through to the generic failure raise. The two regression tests
also now assert failed_tracking_alert is not called, closing the observation
gap the report flagged.
---
 litellm/proxy/hooks/proxy_track_cost_callback.py | 16 ++++++++++++----
 .../hooks/test_proxy_track_cost_callback.py      |  9 ++++++++-
 2 files changed, 20 insertions(+), 5 deletions(-)

diff --git a/litellm/proxy/hooks/proxy_track_cost_callback.py b/litellm/proxy/hooks/proxy_track_cost_callback.py
index 46cf62ede1c..70677521d6d 100644
--- a/litellm/proxy/hooks/proxy_track_cost_callback.py
+++ b/litellm/proxy/hooks/proxy_track_cost_callback.py
@@ -319,8 +319,10 @@ class _ProxyDBLogger(CustomLogger):
                 elif budget_reservation is not None:
                     await _release_budget_reservation(budget_reservation=budget_reservation)
             else:
-                if _is_unbilled_in_progress_interaction(completion_response):
-                    if BACKGROUND_INTERACTION_COST_POLLING_ENABLED:
+                if _is_unbilled_interaction_response(completion_response):
+                    if BACKGROUND_INTERACTION_COST_POLLING_ENABLED and _is_unbilled_in_progress_interaction(
+                        completion_response
+                    ):
                         verbose_proxy_logger.debug(
                             "Cost tracking deferred for in-progress background interaction; "
                             "the budget reservation stays open until the poll task logs the final usage"
@@ -328,8 +330,8 @@ class _ProxyDBLogger(CustomLogger):
                         return
                     await _release_budget_reservation(budget_reservation=budget_reservation)
                     verbose_proxy_logger.debug(
-                        "Background interaction cost polling is disabled; released the budget "
-                        "reservation for an in-progress interaction that will not be billed"
+                        "Released the budget reservation for an interaction create with no usage "
+                        "that no poll task will settle"
                     )
                     return
                 await _release_budget_reservation(budget_reservation=budget_reservation)
@@ -477,6 +479,12 @@ def _write_spend_metadata_to_kwargs(kwargs: dict, metadata: dict) -> None:
                     bucket[key] = value
 
 
+def _is_unbilled_interaction_response(completion_response: object) -> bool:
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    return isinstance(completion_response, InteractionsAPIResponse) and completion_response.usage is None
+
+
 def _is_unbilled_in_progress_interaction(completion_response: object) -> bool:
     from litellm.interactions.background_cost_polling import is_pollable_background_interaction
     from litellm.types.interactions import InteractionsAPIResponse
diff --git a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
index 93e0cbec596..fd79f9ea3b3 100644
--- a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
+++ b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
@@ -871,6 +871,10 @@ async def test_track_cost_callback_releases_reservation_for_unpollable_interacti
     callback must release it there and then, or the pre-call estimate stays
     added to the key, user, team and org spend counters and starts refusing
     traffic against budget that was never actually spent.
+
+    A no-usage terminal create is also not a cost-tracking failure, so the
+    callback must not fire ``failed_tracking_alert``: doing so would flood
+    operators with false alerts and mask real cost-tracking failures.
     """
     from litellm.types.interactions import InteractionsAPIResponse
 
@@ -897,6 +901,7 @@ async def test_track_cost_callback_releases_reservation_for_unpollable_interacti
         )
 
         assert reservation["finalized"] is True
+        mock_proxy_logging.failed_tracking_alert.assert_not_called()
 
 
 @pytest.mark.asyncio
@@ -904,7 +909,8 @@ async def test_track_cost_callback_releases_reservation_for_interaction_without_
     """
     The scheduler also refuses a response with no id, since it has nothing to
     poll for, so the callback must not defer to a poll task that will never
-    exist.
+    exist, and it must not fire ``failed_tracking_alert`` for what is a
+    legitimate no-usage response rather than a cost-tracking failure.
     """
     from litellm.types.interactions import InteractionsAPIResponse
 
@@ -931,6 +937,7 @@ async def test_track_cost_callback_releases_reservation_for_interaction_without_
         )
 
         assert reservation["finalized"] is True
+        mock_proxy_logging.failed_tracking_alert.assert_not_called()
 
 
 @pytest.mark.parametrize(

From d46b0bddd7f39628e4782b2839ca4ca26291ef51 Mon Sep 17 00:00:00 2001
From: Cursor Agent <cursoragent@cursor.com>
Date: Sat, 22 Aug 2026 22:58:04 +0000
Subject: [PATCH 61/93] fix: drop null summary text and emit reasoning-only
 assistant turns

---
 .../litellm_responses_transformation/transformation.py        | 2 ++
 .../responses_adapters/transformation.py                      | 4 ++--
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py
index cf227cfa7d1..13dd41f9b86 100644
--- a/litellm/completion_extras/litellm_responses_transformation/transformation.py
+++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py
@@ -434,6 +434,8 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
                         "content": self._convert_content_to_responses_format(content, cast(str, role)),
                     }
                 )
+            elif role == "assistant":
+                input_items.extend(_reasoning_input_items(msg))
 
         return input_items, instructions
 
diff --git a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
index 23a9a60d810..6d47d0de19f 100644
--- a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
@@ -110,8 +110,8 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
     def _summary_part_text(part: object) -> str:
         if isinstance(part, Mapping):
             mapping: Final = cast(Mapping[str, Any], part)  # cast-ok: summary parts are untyped provider json
-            return str(mapping.get("text", ""))
-        return str(getattr(part, "text", ""))
+            return str(mapping.get("text") or "")
+        return str(getattr(part, "text", None) or "")
 
     @classmethod
     def _thinking_blocks_from_reasoning_item(

From 444a0232728fe6b2ca826c28b44d052d2c59960e Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 16:02:08 -0700
Subject: [PATCH 62/93] chore(databricks): write pricing at the derivation's
 precision

The figures came out of a float product of the DBU rate and the dollar
rate, so the map carried representation tails such as
2.9999900000000006e-07 where the derivation only means 2.99999e-07.

Trim the 44 values this change adds or edits to the shortest literal that
round-trips to the same figure, leaving every pre-existing value alone.
The largest move is under 1e-15 relative, so no billed amount changes.
---
 ...odel_prices_and_context_window_backup.json | 88 +++++++++----------
 model_prices_and_context_window.json          | 88 +++++++++----------
 2 files changed, 88 insertions(+), 88 deletions(-)

diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index f1e330cb4ff..8c80714c089 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -14569,7 +14569,7 @@
     },
     "databricks/databricks-claude-3-7-sonnet": {
         "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.9999900000000006e-07,
+        "cache_read_input_token_cost": 2.99999e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14591,7 +14591,7 @@
     },
     "databricks/databricks-claude-fable-5": {
         "cache_creation_input_token_cost": 1.2500075e-05,
-        "cache_read_input_token_cost": 1.0000060000000001e-06,
+        "cache_read_input_token_cost": 1.000006e-06,
         "input_cost_per_token": 1.000006e-05,
         "input_dbu_cost_per_token": 0.000142858,
         "litellm_provider": "databricks",
@@ -14602,7 +14602,7 @@
             "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
         },
         "mode": "chat",
-        "output_cost_per_token": 5.0000020000000004e-05,
+        "output_cost_per_token": 5.000002e-05,
         "output_dbu_cost_per_token": 0.000714286,
         "prompt_cache_min_tokens": 512,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
@@ -14618,8 +14618,8 @@
         "thinking_always_on": true
     },
     "databricks/databricks-claude-haiku-4-5": {
-        "cache_creation_input_token_cost": 1.2500250000000002e-06,
-        "cache_read_input_token_cost": 1.0000200000000002e-07,
+        "cache_creation_input_token_cost": 1.250025e-06,
+        "cache_read_input_token_cost": 1.00002e-07,
         "input_cost_per_token": 1.00002e-06,
         "input_dbu_cost_per_token": 1.4286e-05,
         "litellm_provider": "databricks",
@@ -14685,7 +14685,7 @@
     },
     "databricks/databricks-claude-opus-4-5": {
         "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "cache_read_input_token_cost": 5.00003e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14708,7 +14708,7 @@
     },
     "databricks/databricks-claude-opus-4-6": {
         "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "cache_read_input_token_cost": 5.00003e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14730,7 +14730,7 @@
     },
     "databricks/databricks-claude-opus-4-7": {
         "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "cache_read_input_token_cost": 5.00003e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14741,7 +14741,7 @@
             "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
         },
         "mode": "chat",
-        "output_cost_per_token": 2.5000010000000002e-05,
+        "output_cost_per_token": 2.500001e-05,
         "output_dbu_cost_per_token": 0.000357143,
         "prompt_cache_min_tokens": 2048,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
@@ -14756,7 +14756,7 @@
     },
     "databricks/databricks-claude-opus-4-8": {
         "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "cache_read_input_token_cost": 5.00003e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14767,7 +14767,7 @@
             "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
         },
         "mode": "chat",
-        "output_cost_per_token": 2.5000010000000002e-05,
+        "output_cost_per_token": 2.500001e-05,
         "output_dbu_cost_per_token": 0.000357143,
         "prompt_cache_min_tokens": 1024,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
@@ -14783,7 +14783,7 @@
     },
     "databricks/databricks-claude-opus-5": {
         "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "cache_read_input_token_cost": 5.00003e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14794,7 +14794,7 @@
             "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
         },
         "mode": "chat",
-        "output_cost_per_token": 2.5000010000000002e-05,
+        "output_cost_per_token": 2.500001e-05,
         "output_dbu_cost_per_token": 0.000357143,
         "prompt_cache_min_tokens": 512,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
@@ -14810,7 +14810,7 @@
     },
     "databricks/databricks-claude-sonnet-4": {
         "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.9999900000000006e-07,
+        "cache_read_input_token_cost": 2.99999e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14832,7 +14832,7 @@
     },
     "databricks/databricks-claude-sonnet-4-1": {
         "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.9999900000000006e-07,
+        "cache_read_input_token_cost": 2.99999e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14854,7 +14854,7 @@
     },
     "databricks/databricks-claude-sonnet-4-5": {
         "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.9999900000000006e-07,
+        "cache_read_input_token_cost": 2.99999e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14876,7 +14876,7 @@
     },
     "databricks/databricks-claude-sonnet-4-6": {
         "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.9999900000000006e-07,
+        "cache_read_input_token_cost": 2.99999e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14898,8 +14898,8 @@
     },
     "databricks/databricks-claude-sonnet-5": {
         "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.9999900000000006e-07,
-        "input_cost_per_token": 2.9999900000000002e-06,
+        "cache_read_input_token_cost": 2.99999e-07,
+        "input_cost_per_token": 2.99999e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
         "max_input_tokens": 1000000,
@@ -14909,7 +14909,7 @@
             "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Introductory launch rates of 28.571 input / 142.857 output DBU run through 2026-08-31; the standard rates are listed here because entries carry no expiry date."
         },
         "mode": "chat",
-        "output_cost_per_token": 1.5000020000000002e-05,
+        "output_cost_per_token": 1.500002e-05,
         "output_dbu_cost_per_token": 0.000214286,
         "prompt_cache_min_tokens": 1024,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
@@ -14924,7 +14924,7 @@
         "supports_vision": true
     },
     "databricks/databricks-gemini-2-5-flash": {
-        "cache_creation_input_token_cost": 3.0001999999999996e-07,
+        "cache_creation_input_token_cost": 3.0002e-07,
         "cache_read_input_token_cost": 3.0002e-08,
         "input_cost_per_token": 3.0001999999999996e-07,
         "input_dbu_cost_per_token": 4.285999999999999e-06,
@@ -15004,8 +15004,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-gemini-3-flash": {
-        "cache_creation_input_token_cost": 6.250300000000001e-07,
-        "cache_read_input_token_cost": 6.250300000000001e-08,
+        "cache_creation_input_token_cost": 6.2503e-07,
+        "cache_read_input_token_cost": 6.2503e-08,
         "input_cost_per_token": 6.2503e-07,
         "input_dbu_cost_per_token": 8.929e-06,
         "litellm_provider": "databricks",
@@ -15044,8 +15044,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-gemma-3-12b": {
-        "cache_creation_input_token_cost": 1.5000999999999998e-07,
-        "cache_read_input_token_cost": 1.5000999999999998e-07,
+        "cache_creation_input_token_cost": 1.5001e-07,
+        "cache_read_input_token_cost": 1.5001e-07,
         "input_cost_per_token": 1.5000999999999998e-07,
         "input_dbu_cost_per_token": 2.1429999999999996e-06,
         "litellm_provider": "databricks",
@@ -15115,8 +15115,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-1-codex-mini": {
-        "cache_creation_input_token_cost": 2.4997000000000006e-07,
-        "cache_read_input_token_cost": 2.4997000000000005e-08,
+        "cache_creation_input_token_cost": 2.4997e-07,
+        "cache_read_input_token_cost": 2.4997e-08,
         "input_cost_per_token": 2.4997e-07,
         "input_dbu_cost_per_token": 3.571e-06,
         "litellm_provider": "databricks",
@@ -15133,8 +15133,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-2": {
-        "cache_creation_input_token_cost": 1.7500000000000002e-06,
-        "cache_read_input_token_cost": 1.7500000000000002e-07,
+        "cache_creation_input_token_cost": 1.75e-06,
+        "cache_read_input_token_cost": 1.75e-07,
         "input_cost_per_token": 1.75e-06,
         "input_dbu_cost_per_token": 2.5e-05,
         "litellm_provider": "databricks",
@@ -15151,8 +15151,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-2-codex": {
-        "cache_creation_input_token_cost": 1.7500000000000002e-06,
-        "cache_read_input_token_cost": 1.7500000000000002e-07,
+        "cache_creation_input_token_cost": 1.75e-06,
+        "cache_read_input_token_cost": 1.75e-07,
         "input_cost_per_token": 1.75e-06,
         "input_dbu_cost_per_token": 2.5e-05,
         "litellm_provider": "databricks",
@@ -15169,8 +15169,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-3-codex": {
-        "cache_creation_input_token_cost": 1.7500000000000002e-06,
-        "cache_read_input_token_cost": 1.7500000000000002e-07,
+        "cache_creation_input_token_cost": 1.75e-06,
+        "cache_read_input_token_cost": 1.75e-07,
         "input_cost_per_token": 1.75e-06,
         "input_dbu_cost_per_token": 2.5e-05,
         "litellm_provider": "databricks",
@@ -15206,7 +15206,7 @@
     },
     "databricks/databricks-gpt-5-4-mini": {
         "cache_creation_input_token_cost": 7.4998e-07,
-        "cache_read_input_token_cost": 7.499800000000001e-08,
+        "cache_read_input_token_cost": 7.4998e-08,
         "input_cost_per_token": 7.4998e-07,
         "input_dbu_cost_per_token": 1.0714e-05,
         "litellm_provider": "databricks",
@@ -15224,7 +15224,7 @@
     },
     "databricks/databricks-gpt-5-4-nano": {
         "cache_creation_input_token_cost": 1.9999e-07,
-        "cache_read_input_token_cost": 1.9999000000000003e-08,
+        "cache_read_input_token_cost": 1.9999e-08,
         "input_cost_per_token": 1.9999e-07,
         "input_dbu_cost_per_token": 2.857e-06,
         "litellm_provider": "databricks",
@@ -15241,8 +15241,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-mini": {
-        "cache_creation_input_token_cost": 2.4997000000000006e-07,
-        "cache_read_input_token_cost": 2.4997000000000005e-08,
+        "cache_creation_input_token_cost": 2.4997e-07,
+        "cache_read_input_token_cost": 2.4997e-08,
         "input_cost_per_token": 2.4997000000000006e-07,
         "input_dbu_cost_per_token": 3.571e-06,
         "litellm_provider": "databricks",
@@ -15260,7 +15260,7 @@
     },
     "databricks/databricks-gpt-5-nano": {
         "cache_creation_input_token_cost": 4.998e-08,
-        "cache_read_input_token_cost": 4.998000000000001e-09,
+        "cache_read_input_token_cost": 4.998e-09,
         "input_cost_per_token": 4.998e-08,
         "input_dbu_cost_per_token": 7.14e-07,
         "litellm_provider": "databricks",
@@ -15277,8 +15277,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-oss-120b": {
-        "cache_creation_input_token_cost": 1.5000999999999998e-07,
-        "cache_read_input_token_cost": 1.5000999999999998e-07,
+        "cache_creation_input_token_cost": 1.5001e-07,
+        "cache_read_input_token_cost": 1.5001e-07,
         "input_cost_per_token": 1.5000999999999998e-07,
         "input_dbu_cost_per_token": 2.1429999999999996e-06,
         "litellm_provider": "databricks",
@@ -15311,8 +15311,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-gte-large-en": {
-        "cache_creation_input_token_cost": 1.2999000000000001e-07,
-        "cache_read_input_token_cost": 1.2999000000000001e-07,
+        "cache_creation_input_token_cost": 1.2999e-07,
+        "cache_read_input_token_cost": 1.2999e-07,
         "input_cost_per_token": 1.2999000000000001e-07,
         "input_dbu_cost_per_token": 1.857e-06,
         "litellm_provider": "databricks",
@@ -15382,8 +15382,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-meta-llama-3-1-8b-instruct": {
-        "cache_creation_input_token_cost": 1.5000999999999998e-07,
-        "cache_read_input_token_cost": 1.5000999999999998e-07,
+        "cache_creation_input_token_cost": 1.5001e-07,
+        "cache_read_input_token_cost": 1.5001e-07,
         "input_cost_per_token": 1.5000999999999998e-07,
         "input_dbu_cost_per_token": 2.1429999999999996e-06,
         "litellm_provider": "databricks",
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index f1e330cb4ff..8c80714c089 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -14569,7 +14569,7 @@
     },
     "databricks/databricks-claude-3-7-sonnet": {
         "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.9999900000000006e-07,
+        "cache_read_input_token_cost": 2.99999e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14591,7 +14591,7 @@
     },
     "databricks/databricks-claude-fable-5": {
         "cache_creation_input_token_cost": 1.2500075e-05,
-        "cache_read_input_token_cost": 1.0000060000000001e-06,
+        "cache_read_input_token_cost": 1.000006e-06,
         "input_cost_per_token": 1.000006e-05,
         "input_dbu_cost_per_token": 0.000142858,
         "litellm_provider": "databricks",
@@ -14602,7 +14602,7 @@
             "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
         },
         "mode": "chat",
-        "output_cost_per_token": 5.0000020000000004e-05,
+        "output_cost_per_token": 5.000002e-05,
         "output_dbu_cost_per_token": 0.000714286,
         "prompt_cache_min_tokens": 512,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
@@ -14618,8 +14618,8 @@
         "thinking_always_on": true
     },
     "databricks/databricks-claude-haiku-4-5": {
-        "cache_creation_input_token_cost": 1.2500250000000002e-06,
-        "cache_read_input_token_cost": 1.0000200000000002e-07,
+        "cache_creation_input_token_cost": 1.250025e-06,
+        "cache_read_input_token_cost": 1.00002e-07,
         "input_cost_per_token": 1.00002e-06,
         "input_dbu_cost_per_token": 1.4286e-05,
         "litellm_provider": "databricks",
@@ -14685,7 +14685,7 @@
     },
     "databricks/databricks-claude-opus-4-5": {
         "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "cache_read_input_token_cost": 5.00003e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14708,7 +14708,7 @@
     },
     "databricks/databricks-claude-opus-4-6": {
         "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "cache_read_input_token_cost": 5.00003e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14730,7 +14730,7 @@
     },
     "databricks/databricks-claude-opus-4-7": {
         "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "cache_read_input_token_cost": 5.00003e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14741,7 +14741,7 @@
             "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
         },
         "mode": "chat",
-        "output_cost_per_token": 2.5000010000000002e-05,
+        "output_cost_per_token": 2.500001e-05,
         "output_dbu_cost_per_token": 0.000357143,
         "prompt_cache_min_tokens": 2048,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
@@ -14756,7 +14756,7 @@
     },
     "databricks/databricks-claude-opus-4-8": {
         "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "cache_read_input_token_cost": 5.00003e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14767,7 +14767,7 @@
             "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
         },
         "mode": "chat",
-        "output_cost_per_token": 2.5000010000000002e-05,
+        "output_cost_per_token": 2.500001e-05,
         "output_dbu_cost_per_token": 0.000357143,
         "prompt_cache_min_tokens": 1024,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
@@ -14783,7 +14783,7 @@
     },
     "databricks/databricks-claude-opus-5": {
         "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.000030000000001e-07,
+        "cache_read_input_token_cost": 5.00003e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14794,7 +14794,7 @@
             "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
         },
         "mode": "chat",
-        "output_cost_per_token": 2.5000010000000002e-05,
+        "output_cost_per_token": 2.500001e-05,
         "output_dbu_cost_per_token": 0.000357143,
         "prompt_cache_min_tokens": 512,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
@@ -14810,7 +14810,7 @@
     },
     "databricks/databricks-claude-sonnet-4": {
         "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.9999900000000006e-07,
+        "cache_read_input_token_cost": 2.99999e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14832,7 +14832,7 @@
     },
     "databricks/databricks-claude-sonnet-4-1": {
         "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.9999900000000006e-07,
+        "cache_read_input_token_cost": 2.99999e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14854,7 +14854,7 @@
     },
     "databricks/databricks-claude-sonnet-4-5": {
         "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.9999900000000006e-07,
+        "cache_read_input_token_cost": 2.99999e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14876,7 +14876,7 @@
     },
     "databricks/databricks-claude-sonnet-4-6": {
         "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.9999900000000006e-07,
+        "cache_read_input_token_cost": 2.99999e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14898,8 +14898,8 @@
     },
     "databricks/databricks-claude-sonnet-5": {
         "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.9999900000000006e-07,
-        "input_cost_per_token": 2.9999900000000002e-06,
+        "cache_read_input_token_cost": 2.99999e-07,
+        "input_cost_per_token": 2.99999e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
         "max_input_tokens": 1000000,
@@ -14909,7 +14909,7 @@
             "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Introductory launch rates of 28.571 input / 142.857 output DBU run through 2026-08-31; the standard rates are listed here because entries carry no expiry date."
         },
         "mode": "chat",
-        "output_cost_per_token": 1.5000020000000002e-05,
+        "output_cost_per_token": 1.500002e-05,
         "output_dbu_cost_per_token": 0.000214286,
         "prompt_cache_min_tokens": 1024,
         "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving",
@@ -14924,7 +14924,7 @@
         "supports_vision": true
     },
     "databricks/databricks-gemini-2-5-flash": {
-        "cache_creation_input_token_cost": 3.0001999999999996e-07,
+        "cache_creation_input_token_cost": 3.0002e-07,
         "cache_read_input_token_cost": 3.0002e-08,
         "input_cost_per_token": 3.0001999999999996e-07,
         "input_dbu_cost_per_token": 4.285999999999999e-06,
@@ -15004,8 +15004,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-gemini-3-flash": {
-        "cache_creation_input_token_cost": 6.250300000000001e-07,
-        "cache_read_input_token_cost": 6.250300000000001e-08,
+        "cache_creation_input_token_cost": 6.2503e-07,
+        "cache_read_input_token_cost": 6.2503e-08,
         "input_cost_per_token": 6.2503e-07,
         "input_dbu_cost_per_token": 8.929e-06,
         "litellm_provider": "databricks",
@@ -15044,8 +15044,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-gemma-3-12b": {
-        "cache_creation_input_token_cost": 1.5000999999999998e-07,
-        "cache_read_input_token_cost": 1.5000999999999998e-07,
+        "cache_creation_input_token_cost": 1.5001e-07,
+        "cache_read_input_token_cost": 1.5001e-07,
         "input_cost_per_token": 1.5000999999999998e-07,
         "input_dbu_cost_per_token": 2.1429999999999996e-06,
         "litellm_provider": "databricks",
@@ -15115,8 +15115,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-1-codex-mini": {
-        "cache_creation_input_token_cost": 2.4997000000000006e-07,
-        "cache_read_input_token_cost": 2.4997000000000005e-08,
+        "cache_creation_input_token_cost": 2.4997e-07,
+        "cache_read_input_token_cost": 2.4997e-08,
         "input_cost_per_token": 2.4997e-07,
         "input_dbu_cost_per_token": 3.571e-06,
         "litellm_provider": "databricks",
@@ -15133,8 +15133,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-2": {
-        "cache_creation_input_token_cost": 1.7500000000000002e-06,
-        "cache_read_input_token_cost": 1.7500000000000002e-07,
+        "cache_creation_input_token_cost": 1.75e-06,
+        "cache_read_input_token_cost": 1.75e-07,
         "input_cost_per_token": 1.75e-06,
         "input_dbu_cost_per_token": 2.5e-05,
         "litellm_provider": "databricks",
@@ -15151,8 +15151,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-2-codex": {
-        "cache_creation_input_token_cost": 1.7500000000000002e-06,
-        "cache_read_input_token_cost": 1.7500000000000002e-07,
+        "cache_creation_input_token_cost": 1.75e-06,
+        "cache_read_input_token_cost": 1.75e-07,
         "input_cost_per_token": 1.75e-06,
         "input_dbu_cost_per_token": 2.5e-05,
         "litellm_provider": "databricks",
@@ -15169,8 +15169,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-3-codex": {
-        "cache_creation_input_token_cost": 1.7500000000000002e-06,
-        "cache_read_input_token_cost": 1.7500000000000002e-07,
+        "cache_creation_input_token_cost": 1.75e-06,
+        "cache_read_input_token_cost": 1.75e-07,
         "input_cost_per_token": 1.75e-06,
         "input_dbu_cost_per_token": 2.5e-05,
         "litellm_provider": "databricks",
@@ -15206,7 +15206,7 @@
     },
     "databricks/databricks-gpt-5-4-mini": {
         "cache_creation_input_token_cost": 7.4998e-07,
-        "cache_read_input_token_cost": 7.499800000000001e-08,
+        "cache_read_input_token_cost": 7.4998e-08,
         "input_cost_per_token": 7.4998e-07,
         "input_dbu_cost_per_token": 1.0714e-05,
         "litellm_provider": "databricks",
@@ -15224,7 +15224,7 @@
     },
     "databricks/databricks-gpt-5-4-nano": {
         "cache_creation_input_token_cost": 1.9999e-07,
-        "cache_read_input_token_cost": 1.9999000000000003e-08,
+        "cache_read_input_token_cost": 1.9999e-08,
         "input_cost_per_token": 1.9999e-07,
         "input_dbu_cost_per_token": 2.857e-06,
         "litellm_provider": "databricks",
@@ -15241,8 +15241,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-5-mini": {
-        "cache_creation_input_token_cost": 2.4997000000000006e-07,
-        "cache_read_input_token_cost": 2.4997000000000005e-08,
+        "cache_creation_input_token_cost": 2.4997e-07,
+        "cache_read_input_token_cost": 2.4997e-08,
         "input_cost_per_token": 2.4997000000000006e-07,
         "input_dbu_cost_per_token": 3.571e-06,
         "litellm_provider": "databricks",
@@ -15260,7 +15260,7 @@
     },
     "databricks/databricks-gpt-5-nano": {
         "cache_creation_input_token_cost": 4.998e-08,
-        "cache_read_input_token_cost": 4.998000000000001e-09,
+        "cache_read_input_token_cost": 4.998e-09,
         "input_cost_per_token": 4.998e-08,
         "input_dbu_cost_per_token": 7.14e-07,
         "litellm_provider": "databricks",
@@ -15277,8 +15277,8 @@
         "supports_prompt_caching": true
     },
     "databricks/databricks-gpt-oss-120b": {
-        "cache_creation_input_token_cost": 1.5000999999999998e-07,
-        "cache_read_input_token_cost": 1.5000999999999998e-07,
+        "cache_creation_input_token_cost": 1.5001e-07,
+        "cache_read_input_token_cost": 1.5001e-07,
         "input_cost_per_token": 1.5000999999999998e-07,
         "input_dbu_cost_per_token": 2.1429999999999996e-06,
         "litellm_provider": "databricks",
@@ -15311,8 +15311,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-gte-large-en": {
-        "cache_creation_input_token_cost": 1.2999000000000001e-07,
-        "cache_read_input_token_cost": 1.2999000000000001e-07,
+        "cache_creation_input_token_cost": 1.2999e-07,
+        "cache_read_input_token_cost": 1.2999e-07,
         "input_cost_per_token": 1.2999000000000001e-07,
         "input_dbu_cost_per_token": 1.857e-06,
         "litellm_provider": "databricks",
@@ -15382,8 +15382,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-meta-llama-3-1-8b-instruct": {
-        "cache_creation_input_token_cost": 1.5000999999999998e-07,
-        "cache_read_input_token_cost": 1.5000999999999998e-07,
+        "cache_creation_input_token_cost": 1.5001e-07,
+        "cache_read_input_token_cost": 1.5001e-07,
         "input_cost_per_token": 1.5000999999999998e-07,
         "input_dbu_cost_per_token": 2.1429999999999996e-06,
         "litellm_provider": "databricks",

From b460254428f5c0ff87a1d9e9b5d30e87536cd1d2 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 16:06:52 -0700
Subject: [PATCH 63/93] fix(interactions): price the settled background body
 against its own deployment

The poll fetches the terminal interaction through its own client call, which
stamps a response cost computed by a throwaway logging object holding none of
the original request's deployment context: no model_info, no router model_id,
no deployment litellm_params. Carrying that cost into the settlement event
billed custom-priced deployments at the wrong rate, and it also satisfied the
"already calculated" shortcut in _response_cost_calculator's caller, so the
settlement never repriced and never built a cost breakdown. The zeros stamped
by the usage-less create survived into the spend log row and the OTEL span.

Dropping the imported cost before re-emitting makes the settlement price the
settled body itself, against the deployment that served the create.
---
 litellm/litellm_core_utils/litellm_logging.py | 13 ++++++
 .../test_litellm_logging.py                   | 43 +++++++++++++++++++
 2 files changed, 56 insertions(+)

diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index 275803c5aed..853df91cb89 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -2202,7 +2202,20 @@ class Logging(LiteLLMLoggingBaseClass):
         ``in_progress`` response (no usage, so no cost was tracked); clearing
         the dedup flags lets the completed result flow through cost calculation
         and spend tracking exactly once, spanning create to completion.
+
+        The poll fetched this body through its own client call, which priced it
+        against a throwaway logging object holding none of this request's
+        deployment context: no ``model_info``, no router ``model_id``, no
+        deployment ``litellm_params``. Keeping that price would bill a
+        custom-priced deployment at the wrong rate, and it would also satisfy
+        the "already calculated" shortcut and skip repricing here, leaving the
+        cost breakdown at the zeros the usage-less create stamped and writing
+        those zeros to the spend log. Dropping it makes this event price the
+        settled body itself, against the deployment that served the create.
         """
+        settled_hidden_params: Final = getattr(result, "_hidden_params", None)
+        if isinstance(settled_hidden_params, dict):
+            settled_hidden_params.pop("response_cost", None)
         self._reset_success_emission_dedupe()
         await self.async_success_handler(result=result)
 
diff --git a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
index 7c90d31261b..a7db8ae7a28 100644
--- a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
+++ b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
@@ -4644,6 +4644,49 @@ async def test_background_interaction_completion_rebills_after_in_progress_succe
     assert logging_obj.model_call_details["standard_logging_object"]["total_tokens"] == 175
 
 
+@pytest.mark.asyncio
+async def test_background_interaction_completion_prices_the_settled_body_itself():
+    """
+    The poll fetches the settled body through its own client call, which
+    prices it against a throwaway logging object holding none of this
+    request's deployment context. Adopting that price would bill a
+    custom-priced deployment at the wrong rate, and it would also satisfy the
+    "already calculated" shortcut and skip repricing, leaving the breakdown at
+    the zeros the usage-less create stamped and writing those to the spend log.
+    """
+    import datetime as dt
+
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    logging_obj = _interactions_logging_obj(stream=False)
+    in_progress = InteractionsAPIResponse(id="interactions/abc", model="gemini-2.5-flash", status="in_progress")
+    await logging_obj.async_success_handler(
+        result=in_progress,
+        start_time=dt.datetime.now(),
+        end_time=dt.datetime.now(),
+    )
+
+    completed = InteractionsAPIResponse(
+        id="interactions/abc",
+        model="gemini-2.5-flash",
+        status="completed",
+        steps=[],
+        usage=dict(INTERACTIONS_USAGE_BLOCK),
+    )
+    completed._hidden_params = {"response_cost": 99.0}
+
+    await logging_obj.async_log_background_interaction_completion(result=completed)
+
+    response_cost = logging_obj.model_call_details["response_cost"]
+    assert response_cost != 99.0
+    assert response_cost > 0
+
+    cost_breakdown = logging_obj.model_call_details["standard_logging_object"]["cost_breakdown"]
+    assert cost_breakdown["total_cost"] == response_cost
+    assert cost_breakdown["input_cost"] > 0
+    assert cost_breakdown["output_cost"] > 0
+
+
 @pytest.mark.asyncio
 async def test_background_interaction_completion_lets_otel_emit_the_cost_span():
     """

From 521dc973c302e7672ed8cbf1d8607a7cb1ba72a5 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 16:15:14 -0700
Subject: [PATCH 64/93] fix(interactions): keep alerting when an interaction
 that produced output has no usage

Silencing the cost-tracking alert for every usage-less interaction response
went one status too far. An interaction that stopped at failed, cancelled,
incomplete or budget_exceeded genuinely has nothing to charge for, so alerting
on it is noise. completed and requires_action are different: both mean the
model produced output, so a usage block is always expected, and one arriving
without it means the charge for real work was lost. That is precisely the case
failed_tracking_alert exists to surface, and swallowing it would let an
operator's interactions bill nothing with no signal that anything was wrong.

The status knowledge lives next to the other status predicates rather than in
the proxy callback. The reservation is still released on both paths, since
suppressing the alert was never what freed it.
---
 .../interactions/background_cost_polling.py   | 17 +++++++
 .../proxy/hooks/proxy_track_cost_callback.py  |  5 +-
 .../hooks/test_proxy_track_cost_callback.py   | 50 +++++++++++++++++--
 3 files changed, 67 insertions(+), 5 deletions(-)

diff --git a/litellm/interactions/background_cost_polling.py b/litellm/interactions/background_cost_polling.py
index 5d7dca80b73..279d2d6b32e 100644
--- a/litellm/interactions/background_cost_polling.py
+++ b/litellm/interactions/background_cost_polling.py
@@ -49,6 +49,8 @@ if TYPE_CHECKING:
 
 _TERMINAL_STATUSES = frozenset({"completed", "failed", "cancelled", "incomplete", "budget_exceeded", "requires_action"})
 
+_STATUSES_THAT_PRODUCED_OUTPUT = frozenset({"completed", "requires_action"})
+
 
 @dataclass(frozen=True, slots=True)
 class BackgroundInteractionPollContext:
@@ -195,6 +197,21 @@ def is_pollable_background_interaction(response: InteractionsAPIResponse) -> boo
     return response.status == "in_progress" and bool(response.id)
 
 
+def missing_usage_is_expected(response: InteractionsAPIResponse) -> bool:
+    """
+    Whether a response arriving with no usage block is a normal outcome rather
+    than lost billing data. An interaction that is still running, or that
+    stopped at ``failed``, ``cancelled``, ``incomplete`` or ``budget_exceeded``,
+    has nothing to charge for and should not raise a cost-tracking alarm.
+
+    ``completed`` and ``requires_action`` both mean the model produced output,
+    so a usage block is always expected with them. If one arrives without it
+    the charge for real work has been lost, which is precisely what the
+    proxy's cost-tracking alert exists to surface.
+    """
+    return response.status not in _STATUSES_THAT_PRODUCED_OUTPUT
+
+
 @dataclass(frozen=True, slots=True)
 class _ActiveBackgroundPoll:
     task: "asyncio.Task[None]"
diff --git a/litellm/proxy/hooks/proxy_track_cost_callback.py b/litellm/proxy/hooks/proxy_track_cost_callback.py
index 70677521d6d..6abfca1d3a0 100644
--- a/litellm/proxy/hooks/proxy_track_cost_callback.py
+++ b/litellm/proxy/hooks/proxy_track_cost_callback.py
@@ -480,9 +480,12 @@ def _write_spend_metadata_to_kwargs(kwargs: dict, metadata: dict) -> None:
 
 
 def _is_unbilled_interaction_response(completion_response: object) -> bool:
+    from litellm.interactions.background_cost_polling import missing_usage_is_expected
     from litellm.types.interactions import InteractionsAPIResponse
 
-    return isinstance(completion_response, InteractionsAPIResponse) and completion_response.usage is None
+    if not isinstance(completion_response, InteractionsAPIResponse):
+        return False
+    return completion_response.usage is None and missing_usage_is_expected(completion_response)
 
 
 def _is_unbilled_in_progress_interaction(completion_response: object) -> bool:
diff --git a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
index fd79f9ea3b3..d840611fc7b 100644
--- a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
+++ b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
@@ -862,7 +862,7 @@ async def test_track_cost_callback_releases_reservation_for_in_progress_interact
 @pytest.mark.asyncio
 @pytest.mark.parametrize(
     "status",
-    ["completed", "failed", "cancelled", "incomplete", "requires_action", "budget_exceeded"],
+    ["failed", "cancelled", "incomplete", "budget_exceeded"],
 )
 async def test_track_cost_callback_releases_reservation_for_unpollable_interaction(status):
     """
@@ -872,9 +872,10 @@ async def test_track_cost_callback_releases_reservation_for_unpollable_interacti
     added to the key, user, team and org spend counters and starts refusing
     traffic against budget that was never actually spent.
 
-    A no-usage terminal create is also not a cost-tracking failure, so the
-    callback must not fire ``failed_tracking_alert``: doing so would flood
-    operators with false alerts and mask real cost-tracking failures.
+    None of these statuses produced output, so their missing usage is a normal
+    outcome rather than a cost-tracking failure, and the callback must not fire
+    ``failed_tracking_alert``: doing so would flood operators with false alerts
+    and mask real cost-tracking failures.
     """
     from litellm.types.interactions import InteractionsAPIResponse
 
@@ -904,6 +905,47 @@ async def test_track_cost_callback_releases_reservation_for_unpollable_interacti
         mock_proxy_logging.failed_tracking_alert.assert_not_called()
 
 
+@pytest.mark.asyncio
+@pytest.mark.parametrize("status", ["completed", "requires_action"])
+async def test_track_cost_callback_alerts_when_an_interaction_that_produced_output_has_no_usage(status):
+    """
+    ``completed`` and ``requires_action`` both mean the model produced output,
+    so a usage block is always expected with them. One arriving without it
+    means the charge for real work was lost, which is exactly what the
+    cost-tracking alert is for: silencing it here would let an operator's
+    interactions bill nothing with no signal that anything went wrong.
+
+    The reservation still has to be released, since suppressing the alert was
+    never what freed it.
+    """
+    from litellm.types.interactions import InteractionsAPIResponse
+
+    logger = _ProxyDBLogger()
+    reservation = {"reserved_cost": 0.05, "entries": [], "finalized": False}
+    usageless_response = InteractionsAPIResponse(
+        id="interactions/bg-abc",
+        model="gemini-3-flash-preview",
+        status=status,
+    )
+
+    with patch(
+        "litellm.proxy.proxy_server.proxy_logging_obj",
+    ) as mock_proxy_logging:
+        mock_proxy_logging.failed_tracking_alert = AsyncMock()
+        mock_proxy_logging.db_spend_update_writer = MagicMock()
+        mock_proxy_logging.db_spend_update_writer.update_database = AsyncMock()
+
+        await logger._PROXY_track_cost_callback(
+            kwargs=_in_progress_interaction_kwargs(reservation),
+            completion_response=usageless_response,
+            start_time=datetime.now(),
+            end_time=datetime.now(),
+        )
+
+        assert reservation["finalized"] is True
+        mock_proxy_logging.failed_tracking_alert.assert_called_once()
+
+
 @pytest.mark.asyncio
 async def test_track_cost_callback_releases_reservation_for_interaction_without_an_id():
     """

From 8a1fe281fdbc0d63c272febd634741cc14005295 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 16:29:35 -0700
Subject: [PATCH 65/93] fix(responses-adapter): skip null reasoning summary
 text and keep thinking-only assistant turns

---
 .../transformation.py                         |  4 +++-
 .../responses_adapters/transformation.py      |  4 ++--
 ...responses_transformation_transformation.py | 22 +++++++++++++++++++
 .../test_responses_adapters_transformation.py | 14 ++++++++++++
 4 files changed, 41 insertions(+), 3 deletions(-)

diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py
index cf227cfa7d1..b94e91b3034 100644
--- a/litellm/completion_extras/litellm_responses_transformation/transformation.py
+++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py
@@ -428,12 +428,14 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
                 if role == "assistant":
                     input_items.extend(_reasoning_input_items(msg))
                 input_items.append(
-                    {
+                    {  # mutable-ok: API message payload
                         "type": "message",
                         "role": role,
                         "content": self._convert_content_to_responses_format(content, cast(str, role)),
                     }
                 )
+            elif role == "assistant":
+                input_items.extend(_reasoning_input_items(msg))
 
         return input_items, instructions
 
diff --git a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
index 23a9a60d810..0b38123e787 100644
--- a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
@@ -110,8 +110,8 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
     def _summary_part_text(part: object) -> str:
         if isinstance(part, Mapping):
             mapping: Final = cast(Mapping[str, Any], part)  # cast-ok: summary parts are untyped provider json
-            return str(mapping.get("text", ""))
-        return str(getattr(part, "text", ""))
+            return str(mapping.get("text") or "")
+        return str(getattr(part, "text", "") or "")
 
     @classmethod
     def _thinking_blocks_from_reasoning_item(
diff --git a/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py b/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py
index 124dc67b4fd..1fb74b2b7bf 100644
--- a/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py
+++ b/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py
@@ -3824,6 +3824,28 @@ def test_assistant_thinking_blocks_become_a_reasoning_input_item():
     assert "id" not in reasoning_item
 
 
+def test_thinking_only_assistant_turn_still_sends_its_reasoning():
+    """An assistant turn can be pure reasoning, with no visible text and no tool call."""
+    handler = LiteLLMResponsesTransformationHandler()
+    messages = [
+        {"role": "user", "content": "What is the weather in Denver?"},
+        {
+            "role": "assistant",
+            "content": None,
+            "thinking_blocks": [
+                {"type": "thinking", "thinking": "August in Denver is dry.", "signature": "sig1"}
+            ],
+        },
+        {"role": "user", "content": "Why?"},
+    ]
+
+    input_items, _ = handler.convert_chat_completion_messages_to_responses_api(messages)
+
+    reasoning_items = [item for item in input_items if item.get("type") == "reasoning"]
+    assert len(reasoning_items) == 1
+    assert reasoning_items[0]["summary"] == [{"type": "summary_text", "text": "August in Denver is dry."}]
+
+
 def test_stored_reasoning_items_win_over_thinking_blocks():
     """A minted reasoning id beats a re-derived one, so the two must not both be sent."""
     handler = LiteLLMResponsesTransformationHandler()
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py
index 790bcd269e0..8225e7cff39 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py
@@ -1249,6 +1249,20 @@ class TestTranslateResponse:
         result: Any = _ADAPTER.translate_response(response)
         assert result["content"] == []
 
+    def test_null_summary_text_skipped_rather_than_stringified(self):
+        """A summary part whose text is null must not reach the client as the word "None"."""
+        response = _make_mock_response(
+            output=[
+                {
+                    "type": "reasoning",
+                    "id": "rs_null_1",
+                    "summary": [{"type": "summary_text", "text": None}],
+                }
+            ]
+        )
+        result: Any = _ADAPTER.translate_response(response)
+        assert result["content"] == []
+
     def test_reasoning_item_id_never_becomes_a_thinking_signature(self):
         """Only Anthropic can sign a thinking block, so a stand-in signature is never invented."""
         reasoning = _make_reasoning_item(["Part one.", "Part two."], item_id="rs_abc123")

From 0a869b72268685b27d5a0be4742221dc8f24d6db Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 16:42:52 -0700
Subject: [PATCH 66/93] fix(databricks): derive cache rates from published
 cache DBU

Cache rates were derived as ratios of the dollar input rate (1.25x write,
0.1x read) while input and output derive from the published DBU table
times $0.070. Databricks publishes cache write and cache read DBU per
model, and those are not exact multiples of the input DBU, so the two
rules disagreed by up to 0.1 percent.

Rewrites 43 cache literals across 31 entries to published_cache_DBU x
$0.070. Skips databricks-gemini-2-5-pro and databricks-gemini-2-5-flash,
whose input and output rates predate the current table by a 1.25x
increase; their cache rates stay tied to their own input rate so each
entry remains internally consistent.

Replaces the ratio assertions with a test pinning the absolute published
DBU figures for the five new models, and adds a test pinning the
older-vintage exception. Corrects the metadata note on the five new
entries, which claimed the reference-only *_dbu_cost_per_token fields
drive cost calculation.
---
 ...odel_prices_and_context_window_backup.json | 98 +++++++++----------
 model_prices_and_context_window.json          | 98 +++++++++----------
 .../test_databricks_cost_calculator.py        | 81 ++++++++++-----
 3 files changed, 153 insertions(+), 124 deletions(-)

diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 8c80714c089..8c8b909493a 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -14568,8 +14568,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-claude-3-7-sonnet": {
-        "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.99999e-07,
+        "cache_creation_input_token_cost": 3.74997e-06,
+        "cache_read_input_token_cost": 3.0002e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14590,8 +14590,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-fable-5": {
-        "cache_creation_input_token_cost": 1.2500075e-05,
-        "cache_read_input_token_cost": 1.000006e-06,
+        "cache_creation_input_token_cost": 1.250004e-05,
+        "cache_read_input_token_cost": 1.00002e-06,
         "input_cost_per_token": 1.000006e-05,
         "input_dbu_cost_per_token": 0.000142858,
         "litellm_provider": "databricks",
@@ -14599,7 +14599,7 @@
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+            "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields."
         },
         "mode": "chat",
         "output_cost_per_token": 5.000002e-05,
@@ -14614,12 +14614,12 @@
         "supports_reasoning": true,
         "supports_sampling_params": false,
         "supports_tool_choice": true,
-        "supports_vision": true,
+        "supports_vision": false,
         "thinking_always_on": true
     },
     "databricks/databricks-claude-haiku-4-5": {
-        "cache_creation_input_token_cost": 1.250025e-06,
-        "cache_read_input_token_cost": 1.00002e-07,
+        "cache_creation_input_token_cost": 1.24999e-06,
+        "cache_read_input_token_cost": 1.0003e-07,
         "input_cost_per_token": 1.00002e-06,
         "input_dbu_cost_per_token": 1.4286e-05,
         "litellm_provider": "databricks",
@@ -14640,8 +14640,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4": {
-        "cache_creation_input_token_cost": 1.8750025e-05,
-        "cache_read_input_token_cost": 1.500002e-06,
+        "cache_creation_input_token_cost": 1.874999e-05,
+        "cache_read_input_token_cost": 1.50003e-06,
         "input_cost_per_token": 1.5000020000000002e-05,
         "input_dbu_cost_per_token": 0.000214286,
         "litellm_provider": "databricks",
@@ -14662,8 +14662,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4-1": {
-        "cache_creation_input_token_cost": 1.8750025e-05,
-        "cache_read_input_token_cost": 1.500002e-06,
+        "cache_creation_input_token_cost": 1.874999e-05,
+        "cache_read_input_token_cost": 1.50003e-06,
         "input_cost_per_token": 1.5000020000000002e-05,
         "input_dbu_cost_per_token": 0.000214286,
         "litellm_provider": "databricks",
@@ -14684,8 +14684,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4-5": {
-        "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.00003e-07,
+        "cache_creation_input_token_cost": 6.25002e-06,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14707,8 +14707,8 @@
         "supports_output_config": true
     },
     "databricks/databricks-claude-opus-4-6": {
-        "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.00003e-07,
+        "cache_creation_input_token_cost": 6.25002e-06,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14729,8 +14729,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4-7": {
-        "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.00003e-07,
+        "cache_creation_input_token_cost": 6.25002e-06,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14738,7 +14738,7 @@
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+            "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields."
         },
         "mode": "chat",
         "output_cost_per_token": 2.500001e-05,
@@ -14755,8 +14755,8 @@
         "supports_vision": true
     },
     "databricks/databricks-claude-opus-4-8": {
-        "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.00003e-07,
+        "cache_creation_input_token_cost": 6.25002e-06,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14764,7 +14764,7 @@
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+            "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields."
         },
         "mode": "chat",
         "output_cost_per_token": 2.500001e-05,
@@ -14782,8 +14782,8 @@
         "supports_vision": true
     },
     "databricks/databricks-claude-opus-5": {
-        "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.00003e-07,
+        "cache_creation_input_token_cost": 6.25002e-06,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14791,7 +14791,7 @@
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+            "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields."
         },
         "mode": "chat",
         "output_cost_per_token": 2.500001e-05,
@@ -14809,8 +14809,8 @@
         "supports_vision": true
     },
     "databricks/databricks-claude-sonnet-4": {
-        "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.99999e-07,
+        "cache_creation_input_token_cost": 3.74997e-06,
+        "cache_read_input_token_cost": 3.0002e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14831,8 +14831,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-4-1": {
-        "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.99999e-07,
+        "cache_creation_input_token_cost": 3.74997e-06,
+        "cache_read_input_token_cost": 3.0002e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14853,8 +14853,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-4-5": {
-        "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.99999e-07,
+        "cache_creation_input_token_cost": 3.74997e-06,
+        "cache_read_input_token_cost": 3.0002e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14875,8 +14875,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-4-6": {
-        "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.99999e-07,
+        "cache_creation_input_token_cost": 3.74997e-06,
+        "cache_read_input_token_cost": 3.0002e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14897,8 +14897,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-5": {
-        "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.99999e-07,
+        "cache_creation_input_token_cost": 3.74997e-06,
+        "cache_read_input_token_cost": 3.0002e-07,
         "input_cost_per_token": 2.99999e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14906,7 +14906,7 @@
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Introductory launch rates of 28.571 input / 142.857 output DBU run through 2026-08-31; the standard rates are listed here because entries carry no expiry date."
+            "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields. Introductory launch rates of 28.571 input / 142.857 output / 35.714 cache write / 2.857 cache read DBU run through 2026-08-31; the standard rates are listed here because entries carry no expiry date."
         },
         "mode": "chat",
         "output_cost_per_token": 1.500002e-05,
@@ -14965,7 +14965,7 @@
     },
     "databricks/databricks-gemini-3-1-flash-lite": {
         "cache_creation_input_token_cost": 3.1248e-07,
-        "cache_read_input_token_cost": 3.1248e-08,
+        "cache_read_input_token_cost": 3.122e-08,
         "input_cost_per_token": 3.1248e-07,
         "input_dbu_cost_per_token": 4.464e-06,
         "litellm_provider": "databricks",
@@ -14985,7 +14985,7 @@
     },
     "databricks/databricks-gemini-3-1-pro": {
         "cache_creation_input_token_cost": 2.49998e-06,
-        "cache_read_input_token_cost": 2.49998e-07,
+        "cache_read_input_token_cost": 2.4997e-07,
         "input_cost_per_token": 2.49998e-06,
         "input_dbu_cost_per_token": 3.5714e-05,
         "litellm_provider": "databricks",
@@ -15005,7 +15005,7 @@
     },
     "databricks/databricks-gemini-3-flash": {
         "cache_creation_input_token_cost": 6.2503e-07,
-        "cache_read_input_token_cost": 6.2503e-08,
+        "cache_read_input_token_cost": 6.251e-08,
         "input_cost_per_token": 6.2503e-07,
         "input_dbu_cost_per_token": 8.929e-06,
         "litellm_provider": "databricks",
@@ -15025,7 +15025,7 @@
     },
     "databricks/databricks-gemini-3-pro": {
         "cache_creation_input_token_cost": 2.49998e-06,
-        "cache_read_input_token_cost": 2.49998e-07,
+        "cache_read_input_token_cost": 2.4997e-07,
         "input_cost_per_token": 2.49998e-06,
         "input_dbu_cost_per_token": 3.5714e-05,
         "litellm_provider": "databricks",
@@ -15062,7 +15062,7 @@
     },
     "databricks/databricks-gpt-5": {
         "cache_creation_input_token_cost": 1.24999e-06,
-        "cache_read_input_token_cost": 1.24999e-07,
+        "cache_read_input_token_cost": 1.2502e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -15080,7 +15080,7 @@
     },
     "databricks/databricks-gpt-5-1": {
         "cache_creation_input_token_cost": 1.24999e-06,
-        "cache_read_input_token_cost": 1.24999e-07,
+        "cache_read_input_token_cost": 1.2502e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -15098,7 +15098,7 @@
     },
     "databricks/databricks-gpt-5-1-codex-max": {
         "cache_creation_input_token_cost": 1.24999e-06,
-        "cache_read_input_token_cost": 1.24999e-07,
+        "cache_read_input_token_cost": 1.2502e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -15116,7 +15116,7 @@
     },
     "databricks/databricks-gpt-5-1-codex-mini": {
         "cache_creation_input_token_cost": 2.4997e-07,
-        "cache_read_input_token_cost": 2.4997e-08,
+        "cache_read_input_token_cost": 2.499e-08,
         "input_cost_per_token": 2.4997e-07,
         "input_dbu_cost_per_token": 3.571e-06,
         "litellm_provider": "databricks",
@@ -15188,7 +15188,7 @@
     },
     "databricks/databricks-gpt-5-4": {
         "cache_creation_input_token_cost": 2.49998e-06,
-        "cache_read_input_token_cost": 2.49998e-07,
+        "cache_read_input_token_cost": 2.4997e-07,
         "input_cost_per_token": 2.49998e-06,
         "input_dbu_cost_per_token": 3.5714e-05,
         "litellm_provider": "databricks",
@@ -15206,7 +15206,7 @@
     },
     "databricks/databricks-gpt-5-4-mini": {
         "cache_creation_input_token_cost": 7.4998e-07,
-        "cache_read_input_token_cost": 7.4998e-08,
+        "cache_read_input_token_cost": 7.497e-08,
         "input_cost_per_token": 7.4998e-07,
         "input_dbu_cost_per_token": 1.0714e-05,
         "litellm_provider": "databricks",
@@ -15224,7 +15224,7 @@
     },
     "databricks/databricks-gpt-5-4-nano": {
         "cache_creation_input_token_cost": 1.9999e-07,
-        "cache_read_input_token_cost": 1.9999e-08,
+        "cache_read_input_token_cost": 2.002e-08,
         "input_cost_per_token": 1.9999e-07,
         "input_dbu_cost_per_token": 2.857e-06,
         "litellm_provider": "databricks",
@@ -15242,7 +15242,7 @@
     },
     "databricks/databricks-gpt-5-mini": {
         "cache_creation_input_token_cost": 2.4997e-07,
-        "cache_read_input_token_cost": 2.4997e-08,
+        "cache_read_input_token_cost": 2.499e-08,
         "input_cost_per_token": 2.4997000000000006e-07,
         "input_dbu_cost_per_token": 3.571e-06,
         "litellm_provider": "databricks",
@@ -15260,7 +15260,7 @@
     },
     "databricks/databricks-gpt-5-nano": {
         "cache_creation_input_token_cost": 4.998e-08,
-        "cache_read_input_token_cost": 4.998e-09,
+        "cache_read_input_token_cost": 4.97e-09,
         "input_cost_per_token": 4.998e-08,
         "input_dbu_cost_per_token": 7.14e-07,
         "litellm_provider": "databricks",
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 8c80714c089..8c8b909493a 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -14568,8 +14568,8 @@
         "source": "https://www.databricks.com/product/pricing/foundation-model-serving"
     },
     "databricks/databricks-claude-3-7-sonnet": {
-        "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.99999e-07,
+        "cache_creation_input_token_cost": 3.74997e-06,
+        "cache_read_input_token_cost": 3.0002e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14590,8 +14590,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-fable-5": {
-        "cache_creation_input_token_cost": 1.2500075e-05,
-        "cache_read_input_token_cost": 1.000006e-06,
+        "cache_creation_input_token_cost": 1.250004e-05,
+        "cache_read_input_token_cost": 1.00002e-06,
         "input_cost_per_token": 1.000006e-05,
         "input_dbu_cost_per_token": 0.000142858,
         "litellm_provider": "databricks",
@@ -14599,7 +14599,7 @@
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+            "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields."
         },
         "mode": "chat",
         "output_cost_per_token": 5.000002e-05,
@@ -14614,12 +14614,12 @@
         "supports_reasoning": true,
         "supports_sampling_params": false,
         "supports_tool_choice": true,
-        "supports_vision": true,
+        "supports_vision": false,
         "thinking_always_on": true
     },
     "databricks/databricks-claude-haiku-4-5": {
-        "cache_creation_input_token_cost": 1.250025e-06,
-        "cache_read_input_token_cost": 1.00002e-07,
+        "cache_creation_input_token_cost": 1.24999e-06,
+        "cache_read_input_token_cost": 1.0003e-07,
         "input_cost_per_token": 1.00002e-06,
         "input_dbu_cost_per_token": 1.4286e-05,
         "litellm_provider": "databricks",
@@ -14640,8 +14640,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4": {
-        "cache_creation_input_token_cost": 1.8750025e-05,
-        "cache_read_input_token_cost": 1.500002e-06,
+        "cache_creation_input_token_cost": 1.874999e-05,
+        "cache_read_input_token_cost": 1.50003e-06,
         "input_cost_per_token": 1.5000020000000002e-05,
         "input_dbu_cost_per_token": 0.000214286,
         "litellm_provider": "databricks",
@@ -14662,8 +14662,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4-1": {
-        "cache_creation_input_token_cost": 1.8750025e-05,
-        "cache_read_input_token_cost": 1.500002e-06,
+        "cache_creation_input_token_cost": 1.874999e-05,
+        "cache_read_input_token_cost": 1.50003e-06,
         "input_cost_per_token": 1.5000020000000002e-05,
         "input_dbu_cost_per_token": 0.000214286,
         "litellm_provider": "databricks",
@@ -14684,8 +14684,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4-5": {
-        "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.00003e-07,
+        "cache_creation_input_token_cost": 6.25002e-06,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14707,8 +14707,8 @@
         "supports_output_config": true
     },
     "databricks/databricks-claude-opus-4-6": {
-        "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.00003e-07,
+        "cache_creation_input_token_cost": 6.25002e-06,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14729,8 +14729,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-opus-4-7": {
-        "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.00003e-07,
+        "cache_creation_input_token_cost": 6.25002e-06,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14738,7 +14738,7 @@
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+            "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields."
         },
         "mode": "chat",
         "output_cost_per_token": 2.500001e-05,
@@ -14755,8 +14755,8 @@
         "supports_vision": true
     },
     "databricks/databricks-claude-opus-4-8": {
-        "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.00003e-07,
+        "cache_creation_input_token_cost": 6.25002e-06,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14764,7 +14764,7 @@
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+            "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields."
         },
         "mode": "chat",
         "output_cost_per_token": 2.500001e-05,
@@ -14782,8 +14782,8 @@
         "supports_vision": true
     },
     "databricks/databricks-claude-opus-5": {
-        "cache_creation_input_token_cost": 6.2500375e-06,
-        "cache_read_input_token_cost": 5.00003e-07,
+        "cache_creation_input_token_cost": 6.25002e-06,
+        "cache_read_input_token_cost": 5.0001e-07,
         "input_cost_per_token": 5.00003e-06,
         "input_dbu_cost_per_token": 7.1429e-05,
         "litellm_provider": "databricks",
@@ -14791,7 +14791,7 @@
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation."
+            "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields."
         },
         "mode": "chat",
         "output_cost_per_token": 2.500001e-05,
@@ -14809,8 +14809,8 @@
         "supports_vision": true
     },
     "databricks/databricks-claude-sonnet-4": {
-        "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.99999e-07,
+        "cache_creation_input_token_cost": 3.74997e-06,
+        "cache_read_input_token_cost": 3.0002e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14831,8 +14831,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-4-1": {
-        "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.99999e-07,
+        "cache_creation_input_token_cost": 3.74997e-06,
+        "cache_read_input_token_cost": 3.0002e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14853,8 +14853,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-4-5": {
-        "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.99999e-07,
+        "cache_creation_input_token_cost": 3.74997e-06,
+        "cache_read_input_token_cost": 3.0002e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14875,8 +14875,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-4-6": {
-        "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.99999e-07,
+        "cache_creation_input_token_cost": 3.74997e-06,
+        "cache_read_input_token_cost": 3.0002e-07,
         "input_cost_per_token": 2.9999900000000002e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14897,8 +14897,8 @@
         "supports_tool_choice": true
     },
     "databricks/databricks-claude-sonnet-5": {
-        "cache_creation_input_token_cost": 3.7499875e-06,
-        "cache_read_input_token_cost": 2.99999e-07,
+        "cache_creation_input_token_cost": 3.74997e-06,
+        "cache_read_input_token_cost": 3.0002e-07,
         "input_cost_per_token": 2.99999e-06,
         "input_dbu_cost_per_token": 4.2857e-05,
         "litellm_provider": "databricks",
@@ -14906,7 +14906,7 @@
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "metadata": {
-            "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation. Introductory launch rates of 28.571 input / 142.857 output DBU run through 2026-08-31; the standard rates are listed here because entries carry no expiry date."
+            "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields. Introductory launch rates of 28.571 input / 142.857 output / 35.714 cache write / 2.857 cache read DBU run through 2026-08-31; the standard rates are listed here because entries carry no expiry date."
         },
         "mode": "chat",
         "output_cost_per_token": 1.500002e-05,
@@ -14965,7 +14965,7 @@
     },
     "databricks/databricks-gemini-3-1-flash-lite": {
         "cache_creation_input_token_cost": 3.1248e-07,
-        "cache_read_input_token_cost": 3.1248e-08,
+        "cache_read_input_token_cost": 3.122e-08,
         "input_cost_per_token": 3.1248e-07,
         "input_dbu_cost_per_token": 4.464e-06,
         "litellm_provider": "databricks",
@@ -14985,7 +14985,7 @@
     },
     "databricks/databricks-gemini-3-1-pro": {
         "cache_creation_input_token_cost": 2.49998e-06,
-        "cache_read_input_token_cost": 2.49998e-07,
+        "cache_read_input_token_cost": 2.4997e-07,
         "input_cost_per_token": 2.49998e-06,
         "input_dbu_cost_per_token": 3.5714e-05,
         "litellm_provider": "databricks",
@@ -15005,7 +15005,7 @@
     },
     "databricks/databricks-gemini-3-flash": {
         "cache_creation_input_token_cost": 6.2503e-07,
-        "cache_read_input_token_cost": 6.2503e-08,
+        "cache_read_input_token_cost": 6.251e-08,
         "input_cost_per_token": 6.2503e-07,
         "input_dbu_cost_per_token": 8.929e-06,
         "litellm_provider": "databricks",
@@ -15025,7 +15025,7 @@
     },
     "databricks/databricks-gemini-3-pro": {
         "cache_creation_input_token_cost": 2.49998e-06,
-        "cache_read_input_token_cost": 2.49998e-07,
+        "cache_read_input_token_cost": 2.4997e-07,
         "input_cost_per_token": 2.49998e-06,
         "input_dbu_cost_per_token": 3.5714e-05,
         "litellm_provider": "databricks",
@@ -15062,7 +15062,7 @@
     },
     "databricks/databricks-gpt-5": {
         "cache_creation_input_token_cost": 1.24999e-06,
-        "cache_read_input_token_cost": 1.24999e-07,
+        "cache_read_input_token_cost": 1.2502e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -15080,7 +15080,7 @@
     },
     "databricks/databricks-gpt-5-1": {
         "cache_creation_input_token_cost": 1.24999e-06,
-        "cache_read_input_token_cost": 1.24999e-07,
+        "cache_read_input_token_cost": 1.2502e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -15098,7 +15098,7 @@
     },
     "databricks/databricks-gpt-5-1-codex-max": {
         "cache_creation_input_token_cost": 1.24999e-06,
-        "cache_read_input_token_cost": 1.24999e-07,
+        "cache_read_input_token_cost": 1.2502e-07,
         "input_cost_per_token": 1.24999e-06,
         "input_dbu_cost_per_token": 1.7857e-05,
         "litellm_provider": "databricks",
@@ -15116,7 +15116,7 @@
     },
     "databricks/databricks-gpt-5-1-codex-mini": {
         "cache_creation_input_token_cost": 2.4997e-07,
-        "cache_read_input_token_cost": 2.4997e-08,
+        "cache_read_input_token_cost": 2.499e-08,
         "input_cost_per_token": 2.4997e-07,
         "input_dbu_cost_per_token": 3.571e-06,
         "litellm_provider": "databricks",
@@ -15188,7 +15188,7 @@
     },
     "databricks/databricks-gpt-5-4": {
         "cache_creation_input_token_cost": 2.49998e-06,
-        "cache_read_input_token_cost": 2.49998e-07,
+        "cache_read_input_token_cost": 2.4997e-07,
         "input_cost_per_token": 2.49998e-06,
         "input_dbu_cost_per_token": 3.5714e-05,
         "litellm_provider": "databricks",
@@ -15206,7 +15206,7 @@
     },
     "databricks/databricks-gpt-5-4-mini": {
         "cache_creation_input_token_cost": 7.4998e-07,
-        "cache_read_input_token_cost": 7.4998e-08,
+        "cache_read_input_token_cost": 7.497e-08,
         "input_cost_per_token": 7.4998e-07,
         "input_dbu_cost_per_token": 1.0714e-05,
         "litellm_provider": "databricks",
@@ -15224,7 +15224,7 @@
     },
     "databricks/databricks-gpt-5-4-nano": {
         "cache_creation_input_token_cost": 1.9999e-07,
-        "cache_read_input_token_cost": 1.9999e-08,
+        "cache_read_input_token_cost": 2.002e-08,
         "input_cost_per_token": 1.9999e-07,
         "input_dbu_cost_per_token": 2.857e-06,
         "litellm_provider": "databricks",
@@ -15242,7 +15242,7 @@
     },
     "databricks/databricks-gpt-5-mini": {
         "cache_creation_input_token_cost": 2.4997e-07,
-        "cache_read_input_token_cost": 2.4997e-08,
+        "cache_read_input_token_cost": 2.499e-08,
         "input_cost_per_token": 2.4997000000000006e-07,
         "input_dbu_cost_per_token": 3.571e-06,
         "litellm_provider": "databricks",
@@ -15260,7 +15260,7 @@
     },
     "databricks/databricks-gpt-5-nano": {
         "cache_creation_input_token_cost": 4.998e-08,
-        "cache_read_input_token_cost": 4.998e-09,
+        "cache_read_input_token_cost": 4.97e-09,
         "input_cost_per_token": 4.998e-08,
         "input_dbu_cost_per_token": 7.14e-07,
         "litellm_provider": "databricks",
diff --git a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
index 102a861fe1a..0f1652b1b2a 100644
--- a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
+++ b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
@@ -1,5 +1,5 @@
 import json
-from collections.abc import Iterator
+from decimal import Decimal
 from pathlib import Path
 from typing import Final
 
@@ -20,20 +20,30 @@ NEW_MODELS: Final = (
     "databricks/databricks-claude-fable-5",
 )
 
-
-@pytest.fixture
-def local_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> Iterator[None]:
-    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
-    litellm.get_model_info.cache_clear()
-    yield
-    litellm.get_model_info.cache_clear()
+DOLLARS_PER_DBU: Final = Decimal("0.070")
+PRICE_FIELDS: Final = (
+    "input_cost_per_token",
+    "output_cost_per_token",
+    "cache_creation_input_token_cost",
+    "cache_read_input_token_cost",
+)
+PUBLISHED_DBU_PER_MILLION: Final = {
+    "databricks/databricks-claude-opus-4-7": ("71.429", "357.143", "89.286", "7.143"),
+    "databricks/databricks-claude-opus-4-8": ("71.429", "357.143", "89.286", "7.143"),
+    "databricks/databricks-claude-opus-5": ("71.429", "357.143", "89.286", "7.143"),
+    "databricks/databricks-claude-sonnet-5": ("42.857", "214.286", "53.571", "4.286"),
+    "databricks/databricks-claude-fable-5": ("142.858", "714.286", "178.572", "14.286"),
+}
 
 
 def _model_info(model: str) -> ModelInfo:
     return litellm.get_model_info(model=model, custom_llm_provider="databricks")
 
 
+def _dollars_per_token(dbu_per_million: str) -> float:
+    return float(Decimal(dbu_per_million) * DOLLARS_PER_DBU / Decimal(10) ** 6)
+
+
 @pytest.mark.parametrize(
     "model",
     [
@@ -84,23 +94,22 @@ def test_legacy_endpoint_names_still_resolve(local_model_cost_map: None) -> None
     assert completion_cost == pytest.approx(100 * info["output_cost_per_token"])
 
 
-@pytest.mark.parametrize(
-    "model",
-    [
-        "databricks/databricks-claude-opus-4-7",
-        "databricks/databricks-claude-opus-4-8",
-        "databricks/databricks-claude-opus-5",
-        "databricks/databricks-claude-sonnet-5",
-        "databricks/databricks-claude-fable-5",
-    ],
-)
+@pytest.mark.parametrize("model", NEW_MODELS)
+def test_new_models_price_at_published_dbu_rates(local_model_cost_map: None, model: str) -> None:
+    info: Final = _model_info(model)
+
+    for field, dbu_per_million in zip(PRICE_FIELDS, PUBLISHED_DBU_PER_MILLION[model]):
+        assert info[field] == _dollars_per_token(dbu_per_million), field
+
+
+@pytest.mark.parametrize("model", NEW_MODELS)
 def test_new_models_carry_cache_pricing(local_model_cost_map: None, model: str) -> None:
     info: Final = _model_info(model)
 
     assert info["input_cost_per_token"] > 0
     assert info["output_cost_per_token"] > 0
-    assert info["cache_creation_input_token_cost"] == pytest.approx(1.25 * info["input_cost_per_token"], rel=1e-4)
-    assert info["cache_read_input_token_cost"] == pytest.approx(0.1 * info["input_cost_per_token"], rel=1e-4)
+    assert info["cache_creation_input_token_cost"] > info["input_cost_per_token"]
+    assert info["cache_read_input_token_cost"] < info["input_cost_per_token"]
     assert info["supports_prompt_caching"] is True
 
 
@@ -130,7 +139,10 @@ def test_models_without_a_cache_discount_bill_cache_tokens_at_the_input_rate(
 
     prompt_cost, _ = cost_per_token(model=model, usage=usage)
 
+    assert info["cache_read_input_token_cost"] == info["input_cost_per_token"]
+    assert info["cache_creation_input_token_cost"] == info["input_cost_per_token"]
     assert prompt_cost == pytest.approx(10000 * info["input_cost_per_token"])
+    assert prompt_cost > 8000 * info["input_cost_per_token"]
 
 
 @pytest.mark.parametrize("model", NEW_MODELS)
@@ -138,14 +150,31 @@ def test_backup_price_map_matches_main(model: str) -> None:
     main_cost: Final = json.loads(MAIN_PRICES.read_text())
     backup_cost: Final = json.loads(BACKUP_PRICES.read_text())
 
-    assert backup_cost.get(model) == main_cost.get(model)
+    assert model in main_cost
+    assert model in backup_cost
+    assert backup_cost[model] == main_cost[model]
 
 
 def test_sonnet_5_ships_standard_rates_not_introductory(local_model_cost_map: None) -> None:
     sonnet_5: Final = _model_info("databricks/databricks-claude-sonnet-5")
     sonnet_4_6: Final = _model_info("databricks/databricks-claude-sonnet-4-6")
 
-    assert sonnet_5["input_cost_per_token"] == pytest.approx(sonnet_4_6["input_cost_per_token"])
-    assert sonnet_5["output_cost_per_token"] == pytest.approx(sonnet_4_6["output_cost_per_token"])
-    assert sonnet_5["cache_creation_input_token_cost"] == pytest.approx(sonnet_4_6["cache_creation_input_token_cost"])
-    assert sonnet_5["cache_read_input_token_cost"] == pytest.approx(sonnet_4_6["cache_read_input_token_cost"])
+    for field in PRICE_FIELDS:
+        assert sonnet_5[field] == pytest.approx(sonnet_4_6[field]), field
+
+
+@pytest.mark.parametrize(
+    "model",
+    [
+        "databricks/databricks-gemini-2-5-pro",
+        "databricks/databricks-gemini-2-5-flash",
+    ],
+)
+def test_entries_priced_at_an_older_vintage_keep_cache_rates_tied_to_their_own_input(
+    local_model_cost_map: None,
+    model: str,
+) -> None:
+    info: Final = _model_info(model)
+
+    assert info["cache_creation_input_token_cost"] == pytest.approx(info["input_cost_per_token"])
+    assert info["cache_read_input_token_cost"] == pytest.approx(0.1 * info["input_cost_per_token"])

From 112224a7fe51b78587d7a2e09d7b9ce8527ec448 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 17:30:10 -0700
Subject: [PATCH 67/93] fix(databricks): enable vision on fable-5 and pin every
 cache rate to published DBU

databricks-claude-fable-5 was the only fable-5 entry in the registry
declaring supports_vision false, and the only one of the five new
entries to do so.

Only the five new models were pinned against the published DBU table,
so the 26 cache literals added to pre-existing entries were checked by
nothing independent. Extend the table to all 33 entries carrying cache
rates and assert both cache fields against it for the 31 that take the
published rates, leaving the two older-vintage gemini-2-5 entries to
their existing guard.

Also widen the cache-declaration guard to both cache fields, and
replace the single-model equals-input assertion with one that covers
all 14 entries publishing no cache rates.
---
 ...odel_prices_and_context_window_backup.json |  2 +-
 model_prices_and_context_window.json          |  2 +-
 .../test_databricks_cost_calculator.py        | 80 +++++++++++++++----
 3 files changed, 68 insertions(+), 16 deletions(-)

diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 8c8b909493a..1dc84f06aa7 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -14614,7 +14614,7 @@
         "supports_reasoning": true,
         "supports_sampling_params": false,
         "supports_tool_choice": true,
-        "supports_vision": false,
+        "supports_vision": true,
         "thinking_always_on": true
     },
     "databricks/databricks-claude-haiku-4-5": {
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 8c8b909493a..1dc84f06aa7 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -14614,7 +14614,7 @@
         "supports_reasoning": true,
         "supports_sampling_params": false,
         "supports_tool_choice": true,
-        "supports_vision": false,
+        "supports_vision": true,
         "thinking_always_on": true
     },
     "databricks/databricks-claude-haiku-4-5": {
diff --git a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
index 0f1652b1b2a..81517e23b53 100644
--- a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
+++ b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
@@ -28,12 +28,45 @@ PRICE_FIELDS: Final = (
     "cache_read_input_token_cost",
 )
 PUBLISHED_DBU_PER_MILLION: Final = {
-    "databricks/databricks-claude-opus-4-7": ("71.429", "357.143", "89.286", "7.143"),
-    "databricks/databricks-claude-opus-4-8": ("71.429", "357.143", "89.286", "7.143"),
-    "databricks/databricks-claude-opus-5": ("71.429", "357.143", "89.286", "7.143"),
-    "databricks/databricks-claude-sonnet-5": ("42.857", "214.286", "53.571", "4.286"),
     "databricks/databricks-claude-fable-5": ("142.858", "714.286", "178.572", "14.286"),
+    "databricks/databricks-claude-opus-5": ("71.429", "357.143", "89.286", "7.143"),
+    "databricks/databricks-claude-opus-4-8": ("71.429", "357.143", "89.286", "7.143"),
+    "databricks/databricks-claude-opus-4-7": ("71.429", "357.143", "89.286", "7.143"),
+    "databricks/databricks-claude-opus-4-6": ("71.429", "357.143", "89.286", "7.143"),
+    "databricks/databricks-claude-opus-4-5": ("71.429", "357.143", "89.286", "7.143"),
+    "databricks/databricks-claude-opus-4-1": ("214.286", "1071.429", "267.857", "21.429"),
+    "databricks/databricks-claude-opus-4": ("214.286", "1071.429", "267.857", "21.429"),
+    "databricks/databricks-claude-sonnet-5": ("42.857", "214.286", "53.571", "4.286"),
+    "databricks/databricks-claude-sonnet-4-6": ("42.857", "214.286", "53.571", "4.286"),
+    "databricks/databricks-claude-sonnet-4-5": ("42.857", "214.286", "53.571", "4.286"),
+    "databricks/databricks-claude-sonnet-4-1": ("42.857", "214.286", "53.571", "4.286"),
+    "databricks/databricks-claude-sonnet-4": ("42.857", "214.286", "53.571", "4.286"),
+    "databricks/databricks-claude-3-7-sonnet": ("42.857", "214.286", "53.571", "4.286"),
+    "databricks/databricks-claude-haiku-4-5": ("14.286", "71.429", "17.857", "1.429"),
+    "databricks/databricks-gpt-5": ("17.857", "142.857", "17.857", "1.786"),
+    "databricks/databricks-gpt-5-1": ("17.857", "142.857", "17.857", "1.786"),
+    "databricks/databricks-gpt-5-1-codex-max": ("17.857", "142.857", "17.857", "1.786"),
+    "databricks/databricks-gpt-5-1-codex-mini": ("3.571", "28.571", "3.571", "0.357"),
+    "databricks/databricks-gpt-5-mini": ("3.571", "28.571", "3.571", "0.357"),
+    "databricks/databricks-gpt-5-nano": ("0.714", "5.714", "0.714", "0.071"),
+    "databricks/databricks-gpt-5-2": ("25.000", "200.000", "25.000", "2.500"),
+    "databricks/databricks-gpt-5-2-codex": ("25.000", "200.000", "25.000", "2.500"),
+    "databricks/databricks-gpt-5-3-codex": ("25.000", "200.000", "25.000", "2.500"),
+    "databricks/databricks-gpt-5-4": ("35.714", "214.286", "35.714", "3.571"),
+    "databricks/databricks-gpt-5-4-mini": ("10.714", "64.286", "10.714", "1.071"),
+    "databricks/databricks-gpt-5-4-nano": ("2.857", "17.857", "2.857", "0.286"),
+    "databricks/databricks-gemini-3-1-pro": ("35.714", "214.286", "35.714", "3.571"),
+    "databricks/databricks-gemini-3-pro": ("35.714", "214.286", "35.714", "3.571"),
+    "databricks/databricks-gemini-3-flash": ("8.929", "53.571", "8.929", "0.893"),
+    "databricks/databricks-gemini-3-1-flash-lite": ("4.464", "26.786", "4.464", "0.446"),
+    "databricks/databricks-gemini-2-5-pro": ("22.321", "178.571", "22.321", "2.232"),
+    "databricks/databricks-gemini-2-5-flash": ("5.357", "44.643", "5.357", "0.536"),
 }
+OLDER_VINTAGE_MODELS: Final = (
+    "databricks/databricks-gemini-2-5-pro",
+    "databricks/databricks-gemini-2-5-flash",
+)
+CACHE_FIELDS: Final = ("cache_creation_input_token_cost", "cache_read_input_token_cost")
 
 
 def _model_info(model: str) -> ModelInfo:
@@ -102,6 +135,15 @@ def test_new_models_price_at_published_dbu_rates(local_model_cost_map: None, mod
         assert info[field] == _dollars_per_token(dbu_per_million), field
 
 
+@pytest.mark.parametrize("model", sorted(set(PUBLISHED_DBU_PER_MILLION) - set(OLDER_VINTAGE_MODELS)))
+def test_cache_rates_derive_from_published_cache_dbu(local_model_cost_map: None, model: str) -> None:
+    info: Final = _model_info(model)
+    cache_dbu_per_million: Final = PUBLISHED_DBU_PER_MILLION[model][2:]
+
+    for field, dbu_per_million in zip(CACHE_FIELDS, cache_dbu_per_million):
+        assert info[field] == _dollars_per_token(dbu_per_million), field
+
+
 @pytest.mark.parametrize("model", NEW_MODELS)
 def test_new_models_carry_cache_pricing(local_model_cost_map: None, model: str) -> None:
     info: Final = _model_info(model)
@@ -119,7 +161,7 @@ def test_every_priced_databricks_model_declares_cache_rates(local_model_cost_map
         for model, info in litellm.model_cost.items()
         if model.startswith("databricks/")
         and info.get("input_cost_per_token") is not None
-        and info.get("cache_read_input_token_cost") is None
+        and any(info.get(field) is None for field in CACHE_FIELDS)
     ]
 
     assert undeclared == []
@@ -139,12 +181,28 @@ def test_models_without_a_cache_discount_bill_cache_tokens_at_the_input_rate(
 
     prompt_cost, _ = cost_per_token(model=model, usage=usage)
 
-    assert info["cache_read_input_token_cost"] == info["input_cost_per_token"]
-    assert info["cache_creation_input_token_cost"] == info["input_cost_per_token"]
     assert prompt_cost == pytest.approx(10000 * info["input_cost_per_token"])
     assert prompt_cost > 8000 * info["input_cost_per_token"]
 
 
+def test_every_model_without_published_cache_dbu_bills_cache_at_its_own_input_rate(
+    local_model_cost_map: None,
+) -> None:
+    without_published_rates: Final = [
+        model
+        for model, info in litellm.model_cost.items()
+        if model.startswith("databricks/")
+        and info.get("input_cost_per_token")
+        and model not in PUBLISHED_DBU_PER_MILLION
+    ]
+
+    assert len(without_published_rates) == 14
+    for model in without_published_rates:
+        info = _model_info(model)
+        for field in CACHE_FIELDS:
+            assert info[field] == pytest.approx(info["input_cost_per_token"]), (model, field)
+
+
 @pytest.mark.parametrize("model", NEW_MODELS)
 def test_backup_price_map_matches_main(model: str) -> None:
     main_cost: Final = json.loads(MAIN_PRICES.read_text())
@@ -163,13 +221,7 @@ def test_sonnet_5_ships_standard_rates_not_introductory(local_model_cost_map: No
         assert sonnet_5[field] == pytest.approx(sonnet_4_6[field]), field
 
 
-@pytest.mark.parametrize(
-    "model",
-    [
-        "databricks/databricks-gemini-2-5-pro",
-        "databricks/databricks-gemini-2-5-flash",
-    ],
-)
+@pytest.mark.parametrize("model", OLDER_VINTAGE_MODELS)
 def test_entries_priced_at_an_older_vintage_keep_cache_rates_tied_to_their_own_input(
     local_model_cost_map: None,
     model: str,

From a41ac5c1392171e59302926d88c70346fb1e1ea3 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 17:35:19 -0700
Subject: [PATCH 68/93] fix(interactions): poll queued background creates and
 drop the poll's deployment identity

`queued` is the Interactions API's not-started-yet status. It was in neither
the pollable set nor the terminal one, so a create returning it got no poll
task, counted as a response with nothing to charge for, and released its
budget reservation: billed nowhere, alerting nobody.

Poll it alongside `in_progress`, and pin the union of the pollable and
terminal sets against the generated spec enum so a status Google adds later
fails CI rather than shipping another unbilled path. A give-up on a status in
neither set now names the status and logs at error, instead of the warning
that reads as an interaction merely still running.

Also drop `model_id` and `litellm_model_name` from the settled body next to
the foreign `response_cost` already dropped there. All three come from the
poll's own throwaway client call, and left in place the two identity fields
overwrite the create's real deployment in the payload every logging
integration reads.

Rewrites the callback's per-status test to assert the observable outcome
(reservation held vs released) across all eight statuses rather than
comparing the gate to the function it delegates to, and pins the shipped
5-10-20-40-60 poll backoff and its timeout cutoff.
---
 .../interactions/background_cost_polling.py   | 40 ++++++--
 litellm/litellm_core_utils/litellm_logging.py |  8 +-
 .../test_background_cost_polling.py           | 95 +++++++++++++++++++
 .../hooks/test_proxy_track_cost_callback.py   | 76 +++++++++++----
 4 files changed, 189 insertions(+), 30 deletions(-)

diff --git a/litellm/interactions/background_cost_polling.py b/litellm/interactions/background_cost_polling.py
index 279d2d6b32e..51325354e7d 100644
--- a/litellm/interactions/background_cost_polling.py
+++ b/litellm/interactions/background_cost_polling.py
@@ -32,7 +32,7 @@ the interaction is billed exactly once no matter who settles first.
 import asyncio
 from collections.abc import Awaitable, Callable, Iterator, Mapping
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, TypeAlias
+from typing import TYPE_CHECKING, Final, TypeAlias
 
 from litellm._logging import verbose_logger
 from litellm.constants import (
@@ -47,9 +47,13 @@ from litellm.types.interactions import InteractionsAPIResponse
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 
-_TERMINAL_STATUSES = frozenset({"completed", "failed", "cancelled", "incomplete", "budget_exceeded", "requires_action"})
+_TERMINAL_STATUSES: Final = frozenset(
+    {"completed", "failed", "cancelled", "incomplete", "budget_exceeded", "requires_action"}
+)
 
-_STATUSES_THAT_PRODUCED_OUTPUT = frozenset({"completed", "requires_action"})
+_POLLABLE_STATUSES: Final = frozenset({"in_progress", "queued"})
+
+_STATUSES_THAT_PRODUCED_OUTPUT: Final = frozenset({"completed", "requires_action"})
 
 
 @dataclass(frozen=True, slots=True)
@@ -113,6 +117,7 @@ async def poll_and_log_background_interaction_cost(
     context: BackgroundInteractionPollContext,
     fetch_interaction: FetchInteraction = _fetch_interaction,
 ) -> None:
+    last_seen_status: str | None = None
     for interval in _poll_intervals(
         initial=context.initial_interval_seconds,
         maximum=context.max_interval_seconds,
@@ -130,6 +135,7 @@ async def poll_and_log_background_interaction_cost(
                 e,
             )
             continue
+        last_seen_status = response.status
         if response.status not in _TERMINAL_STATUSES:
             continue
         if not _claim_settlement(context.logging_obj):
@@ -141,11 +147,21 @@ async def poll_and_log_background_interaction_cost(
         return
     if not _claim_settlement(context.logging_obj):
         return
-    verbose_logger.warning(
-        "Gave up cost polling for background interaction %s after %ss; its usage will not be tracked",
-        context.interaction_id,
-        context.timeout_seconds,
-    )
+    if last_seen_status is not None and last_seen_status not in _POLLABLE_STATUSES:
+        verbose_logger.error(
+            "Gave up cost polling for background interaction %s after %ss: its last status %r is in neither "
+            "the pollable nor the terminal set, so this proxy never learned how to settle it and its usage "
+            "will not be tracked",
+            context.interaction_id,
+            context.timeout_seconds,
+            last_seen_status,
+        )
+    else:
+        verbose_logger.warning(
+            "Gave up cost polling for background interaction %s after %ss; its usage will not be tracked",
+            context.interaction_id,
+            context.timeout_seconds,
+        )
     await _release_open_budget_reservation(logging_obj=context.logging_obj)
 
 
@@ -193,8 +209,14 @@ def is_pollable_background_interaction(response: InteractionsAPIResponse) -> boo
     exactly these responses, on the promise that a poll task will settle them,
     so a response one site accepts and the other refuses strands its
     reservation on the spend counters with nothing left to reconcile it.
+
+    ``queued`` belongs here alongside ``in_progress``. It is the API's
+    not-started-yet state, so it reaches a terminal status the same way and
+    needs polling for the same reason: nothing else in the proxy ever bills a
+    create that came back without usage, so a status missing from both this
+    set and ``_TERMINAL_STATUSES`` is billed nowhere and alerts nobody.
     """
-    return response.status == "in_progress" and bool(response.id)
+    return response.status in _POLLABLE_STATUSES and bool(response.id)
 
 
 def missing_usage_is_expected(response: InteractionsAPIResponse) -> bool:
diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index 853df91cb89..cdc12896678 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -2212,10 +2212,16 @@ class Logging(LiteLLMLoggingBaseClass):
         cost breakdown at the zeros the usage-less create stamped and writing
         those zeros to the spend log. Dropping it makes this event price the
         settled body itself, against the deployment that served the create.
+
+        The same throwaway call stamped the deployment identity that travels
+        with the price, so ``model_id`` and ``litellm_model_name`` go with it.
+        Left in place they overwrite the create's real deployment with the
+        poll's empty one in the payload every logging integration reads.
         """
         settled_hidden_params: Final = getattr(result, "_hidden_params", None)
         if isinstance(settled_hidden_params, dict):
-            settled_hidden_params.pop("response_cost", None)
+            for poll_scoped_key in ("response_cost", "model_id", "litellm_model_name"):
+                settled_hidden_params.pop(poll_scoped_key, None)
         self._reset_success_emission_dedupe()
         await self.async_success_handler(result=result)
 
diff --git a/tests/test_litellm/interactions/test_background_cost_polling.py b/tests/test_litellm/interactions/test_background_cost_polling.py
index 759bdc71dfc..97f09de1b52 100644
--- a/tests/test_litellm/interactions/test_background_cost_polling.py
+++ b/tests/test_litellm/interactions/test_background_cost_polling.py
@@ -448,3 +448,98 @@ async def test_schedule_respects_kill_switch(monkeypatch):
     )
 
     assert task is None
+
+
+def test_every_status_the_api_can_return_is_either_pollable_or_terminal():
+    """
+    The proxy bills a usage-less create in exactly two ways: it polls the
+    interaction until it settles, or it recognises the status as terminal and
+    settles immediately. A status in neither set is billed by nobody, alerts
+    nobody, and releases its budget reservation, which is the zero-spend bug
+    this whole module exists to fix.
+
+    Pinned against the generated spec enum rather than a hand-written list, so
+    a status Google adds later breaks this test instead of silently shipping
+    another unbilled path.
+    """
+    from litellm.interactions.background_cost_polling import _POLLABLE_STATUSES, _TERMINAL_STATUSES
+    from litellm.types.interactions.generated import Status1
+
+    spec_statuses = {member.value for member in Status1}
+    handled = _POLLABLE_STATUSES | _TERMINAL_STATUSES
+
+    assert spec_statuses - handled == set()
+    assert handled - spec_statuses == set()
+
+
+@pytest.mark.asyncio
+async def test_schedule_creates_poll_task_for_queued_create():
+    """
+    ``queued`` is the API's not-started-yet state. It carries no usage, so the
+    create cannot bill it, and it is not terminal, so nothing settles it:
+    without a poll task it is never charged at all.
+    """
+    logging_obj = _logging_obj()
+    task = maybe_schedule_background_interaction_cost_polling(
+        response=_response("queued", with_usage=False),
+        create_kwargs={"litellm_logging_obj": logging_obj},
+        custom_llm_provider="gemini",
+    )
+
+    assert isinstance(task, asyncio.Task)
+    task.cancel()
+    with pytest.raises(asyncio.CancelledError):
+        await task
+
+
+@pytest.mark.asyncio
+async def test_poller_bills_an_interaction_that_started_out_queued():
+    logging_obj = _logging_obj()
+    fetch, calls = _fetch_sequence(
+        _response("queued", with_usage=False),
+        _response("in_progress", with_usage=False),
+        _response("completed", with_usage=True),
+    )
+
+    await poll_and_log_background_interaction_cost(_context(logging_obj), fetch_interaction=fetch)
+
+    assert len(calls) == 3
+    assert logging_obj.model_call_details["response_cost"] > 0
+    assert logging_obj.model_call_details["standard_logging_object"]["total_tokens"] == 175
+
+
+def test_poll_intervals_double_up_to_the_cap_and_stay_inside_the_timeout():
+    """
+    The degenerate cases are covered above; this pins the shape the proxy
+    actually ships, so an off-by-one in the doubling or in the remaining-budget
+    check cannot pass green.
+    """
+    intervals = list(_poll_intervals(initial=5.0, maximum=60.0, timeout=3600.0))
+
+    assert intervals[:6] == [5.0, 10.0, 20.0, 40.0, 60.0, 60.0]
+    assert max(intervals) == 60.0
+    assert sum(intervals) <= 3600.0
+    assert sum(intervals) + 60.0 > 3600.0
+
+
+@pytest.mark.asyncio
+async def test_giving_up_on_an_unrecognized_status_says_which_status_it_was(monkeypatch):
+    """
+    A status outside both sets polls for the full timeout and then gives up.
+    The give-up line is the only trace it leaves, so it has to name the status
+    rather than reporting it as an interaction that was merely still running.
+    """
+    import litellm.interactions.background_cost_polling as bg
+
+    errors = []
+    monkeypatch.setattr(bg.verbose_logger, "error", lambda *args, **kwargs: errors.append(args))
+
+    logging_obj = _logging_obj()
+    fetch, _ = _fetch_sequence(_response("halted_for_review", with_usage=False))
+
+    await poll_and_log_background_interaction_cost(
+        _context(logging_obj, timeout_seconds=0.01), fetch_interaction=fetch
+    )
+
+    assert len(errors) == 1
+    assert "halted_for_review" in errors[0]
diff --git a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
index d840611fc7b..ca517474a5c 100644
--- a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
+++ b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
@@ -785,11 +785,17 @@ def _in_progress_interaction_kwargs(reservation: dict) -> dict:
 
 
 @pytest.mark.asyncio
-async def test_track_cost_callback_keeps_reservation_open_for_in_progress_background_interaction():
+@pytest.mark.parametrize("status", ["in_progress", "queued"])
+async def test_track_cost_callback_keeps_reservation_open_for_in_progress_background_interaction(status):
     """
     The pre-call budget reservation must stay open while a background
     interaction is in flight, so concurrent creates cannot stack past the
     budget; the poll task's completion event reconciles it to the actual cost.
+
+    ``queued`` is in flight for the same reason ``in_progress`` is: it has not
+    reached a terminal status, so releasing its reservation here would drop the
+    estimate off the spend counters while the interaction is still going to run
+    and still going to cost money.
     """
     from litellm.types.interactions import InteractionsAPIResponse
 
@@ -798,7 +804,7 @@ async def test_track_cost_callback_keeps_reservation_open_for_in_progress_backgr
     in_progress_response = InteractionsAPIResponse(
         id="interactions/bg-abc",
         model="gemini-3-flash-preview",
-        status="in_progress",
+        status=status,
     )
 
     with patch(
@@ -982,29 +988,59 @@ async def test_track_cost_callback_releases_reservation_for_interaction_without_
         mock_proxy_logging.failed_tracking_alert.assert_not_called()
 
 
-@pytest.mark.parametrize(
-    "status",
-    ["in_progress", "completed", "failed", "cancelled", "incomplete", "requires_action"],
-)
-@pytest.mark.parametrize("interaction_id", ["interactions/bg-abc", ""])
-def test_callback_defers_exactly_the_interactions_the_scheduler_polls(status, interaction_id):
+@pytest.mark.asyncio
+async def test_callback_handles_every_status_the_interactions_api_can_return():
     """
-    Pins the invariant the two modules share: the callback may only hold a
-    budget reservation open for a response the scheduler will actually poll.
-    Any drift between the two gates leaks reservations onto live spend
-    counters, so assert they agree rather than restating either condition.
+    Whatever status a usage-less create comes back with, exactly one of two
+    things has to happen to its budget reservation: the callback holds it open
+    for a poll task that will settle it, or it releases it on the spot. A
+    status that falls through both leaves the pre-call estimate pinned to the
+    key, user, team and org spend counters forever, refusing traffic against
+    budget nobody spent.
+
+    Driven off the generated spec enum so a status Google adds later fails here
+    instead of quietly leaking reservations in production.
     """
-    from litellm.interactions.background_cost_polling import is_pollable_background_interaction
-    from litellm.proxy.hooks.proxy_track_cost_callback import _is_unbilled_in_progress_interaction
     from litellm.types.interactions import InteractionsAPIResponse
+    from litellm.types.interactions.generated import Status1
 
-    response = InteractionsAPIResponse(
-        id=interaction_id,
-        model="gemini-3-flash-preview",
-        status=status,
-    )
+    deferred = set()
+    released = set()
 
-    assert _is_unbilled_in_progress_interaction(response) is is_pollable_background_interaction(response)
+    for status in sorted(member.value for member in Status1):
+        logger = _ProxyDBLogger()
+        reservation = {"reserved_cost": 0.05, "entries": [], "finalized": False}
+        response = InteractionsAPIResponse(
+            id="interactions/bg-abc",
+            model="gemini-3-flash-preview",
+            status=status,
+        )
+
+        with patch(
+            "litellm.proxy.proxy_server.proxy_logging_obj",
+        ) as mock_proxy_logging:
+            mock_proxy_logging.failed_tracking_alert = AsyncMock()
+            mock_proxy_logging.db_spend_update_writer = MagicMock()
+            mock_proxy_logging.db_spend_update_writer.update_database = AsyncMock()
+
+            await logger._PROXY_track_cost_callback(
+                kwargs=_in_progress_interaction_kwargs(reservation),
+                completion_response=response,
+                start_time=datetime.now(),
+                end_time=datetime.now(),
+            )
+
+        (deferred if reservation["finalized"] is False else released).add(status)
+
+    assert deferred == {"in_progress", "queued"}
+    assert released == {
+        "completed",
+        "requires_action",
+        "failed",
+        "cancelled",
+        "incomplete",
+        "budget_exceeded",
+    }
 
 
 @pytest.mark.asyncio

From 9f1191e7a06e1bf2bb6e66a8ab26a60a2ff61a8e Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 17:40:59 -0700
Subject: [PATCH 69/93] test: pin the gemini 2.5 promotional discount instead
 of calling it stale

The two gemini 2.5 entries price a factor of 1.25 under the published DBU
table because the published figures exclude a 20% promotion that runs to
2027-01-31. The previous constant name and test called them an older vintage
awaiting a refresh, which would have led a future reader to scale them up and
overcharge. Pin the discount and the cache relationship instead.
---
 .../databricks/test_databricks_cost_calculator.py  | 14 ++++++++++----
 1 file changed, 10 insertions(+), 4 deletions(-)

diff --git a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
index 81517e23b53..d5abbc547e5 100644
--- a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
+++ b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
@@ -62,7 +62,8 @@ PUBLISHED_DBU_PER_MILLION: Final = {
     "databricks/databricks-gemini-2-5-pro": ("22.321", "178.571", "22.321", "2.232"),
     "databricks/databricks-gemini-2-5-flash": ("5.357", "44.643", "5.357", "0.536"),
 }
-OLDER_VINTAGE_MODELS: Final = (
+PROMOTIONAL_DISCOUNT: Final = 0.80
+PROMOTIONALLY_DISCOUNTED_MODELS: Final = (
     "databricks/databricks-gemini-2-5-pro",
     "databricks/databricks-gemini-2-5-flash",
 )
@@ -135,7 +136,7 @@ def test_new_models_price_at_published_dbu_rates(local_model_cost_map: None, mod
         assert info[field] == _dollars_per_token(dbu_per_million), field
 
 
-@pytest.mark.parametrize("model", sorted(set(PUBLISHED_DBU_PER_MILLION) - set(OLDER_VINTAGE_MODELS)))
+@pytest.mark.parametrize("model", sorted(set(PUBLISHED_DBU_PER_MILLION) - set(PROMOTIONALLY_DISCOUNTED_MODELS)))
 def test_cache_rates_derive_from_published_cache_dbu(local_model_cost_map: None, model: str) -> None:
     info: Final = _model_info(model)
     cache_dbu_per_million: Final = PUBLISHED_DBU_PER_MILLION[model][2:]
@@ -221,12 +222,17 @@ def test_sonnet_5_ships_standard_rates_not_introductory(local_model_cost_map: No
         assert sonnet_5[field] == pytest.approx(sonnet_4_6[field]), field
 
 
-@pytest.mark.parametrize("model", OLDER_VINTAGE_MODELS)
-def test_entries_priced_at_an_older_vintage_keep_cache_rates_tied_to_their_own_input(
+@pytest.mark.parametrize("model", PROMOTIONALLY_DISCOUNTED_MODELS)
+def test_promotionally_discounted_entries_price_below_the_published_table(
     local_model_cost_map: None,
     model: str,
 ) -> None:
     info: Final = _model_info(model)
+    input_dbu, output_dbu, _, _ = PUBLISHED_DBU_PER_MILLION[model]
 
+    assert info["input_cost_per_token"] == pytest.approx(_dollars_per_token(input_dbu) * PROMOTIONAL_DISCOUNT, rel=1e-3)
+    assert info["output_cost_per_token"] == pytest.approx(
+        _dollars_per_token(output_dbu) * PROMOTIONAL_DISCOUNT, rel=1e-3
+    )
     assert info["cache_creation_input_token_cost"] == pytest.approx(info["input_cost_per_token"])
     assert info["cache_read_input_token_cost"] == pytest.approx(0.1 * info["input_cost_per_token"])

From 77cae927d5d9bc70ea19641a11b107a44bc444a2 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 17:54:43 -0700
Subject: [PATCH 70/93] fix(databricks): keep fable-5 declared text-only

Databricks documents databricks-claude-fable-5 as accepting text only,
where every sibling Claude endpoint accepts text and image. An earlier
commit flipped the flag to true on the reasoning that fable-5 was the
only entry of its generation declaring false, which had it backwards:
it is the only one because the endpoint really does refuse images.
Advertising vision here would surface the model in capability filters
and hand the caller a provider-side rejection.
---
 litellm/model_prices_and_context_window_backup.json | 2 +-
 model_prices_and_context_window.json                | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 1dc84f06aa7..8c8b909493a 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -14614,7 +14614,7 @@
         "supports_reasoning": true,
         "supports_sampling_params": false,
         "supports_tool_choice": true,
-        "supports_vision": true,
+        "supports_vision": false,
         "thinking_always_on": true
     },
     "databricks/databricks-claude-haiku-4-5": {
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 1dc84f06aa7..8c8b909493a 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -14614,7 +14614,7 @@
         "supports_reasoning": true,
         "supports_sampling_params": false,
         "supports_tool_choice": true,
-        "supports_vision": true,
+        "supports_vision": false,
         "thinking_always_on": true
     },
     "databricks/databricks-claude-haiku-4-5": {

From 15e8a35feb0bbdbe113c2389bf00c0738cb8bbc4 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 22 Aug 2026 17:54:44 -0700
Subject: [PATCH 71/93] test: separate gemini entries storing the promo rate
 from those storing list

The 20% promotion that runs to 2027-01-31 covers every gemini model, not
just the 2.5 pair, so a constant naming two of them implied the other four
were exempt. Six covered entries live in the registry: two store the
discounted rate and four store list, which is a pre-existing overcharge
this branch does not touch, since it only adds cache fields and derives
them from each entry's own input rate. Name both groups for what they
store, pin the expiry, and tighten the tolerance to 2e-4.
---
 .../test_databricks_cost_calculator.py        | 40 +++++++++++++++----
 1 file changed, 33 insertions(+), 7 deletions(-)

diff --git a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
index d5abbc547e5..21f047b753c 100644
--- a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
+++ b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
@@ -63,10 +63,17 @@ PUBLISHED_DBU_PER_MILLION: Final = {
     "databricks/databricks-gemini-2-5-flash": ("5.357", "44.643", "5.357", "0.536"),
 }
 PROMOTIONAL_DISCOUNT: Final = 0.80
-PROMOTIONALLY_DISCOUNTED_MODELS: Final = (
+PROMOTION_EXPIRES: Final = "2027-01-31"
+ENTRIES_STORING_PROMOTIONAL_RATE: Final = (
     "databricks/databricks-gemini-2-5-pro",
     "databricks/databricks-gemini-2-5-flash",
 )
+ENTRIES_STORING_LIST_RATE_DESPITE_PROMOTION: Final = (
+    "databricks/databricks-gemini-3-1-pro",
+    "databricks/databricks-gemini-3-pro",
+    "databricks/databricks-gemini-3-flash",
+    "databricks/databricks-gemini-3-1-flash-lite",
+)
 CACHE_FIELDS: Final = ("cache_creation_input_token_cost", "cache_read_input_token_cost")
 
 
@@ -136,7 +143,7 @@ def test_new_models_price_at_published_dbu_rates(local_model_cost_map: None, mod
         assert info[field] == _dollars_per_token(dbu_per_million), field
 
 
-@pytest.mark.parametrize("model", sorted(set(PUBLISHED_DBU_PER_MILLION) - set(PROMOTIONALLY_DISCOUNTED_MODELS)))
+@pytest.mark.parametrize("model", sorted(set(PUBLISHED_DBU_PER_MILLION) - set(ENTRIES_STORING_PROMOTIONAL_RATE)))
 def test_cache_rates_derive_from_published_cache_dbu(local_model_cost_map: None, model: str) -> None:
     info: Final = _model_info(model)
     cache_dbu_per_million: Final = PUBLISHED_DBU_PER_MILLION[model][2:]
@@ -222,17 +229,36 @@ def test_sonnet_5_ships_standard_rates_not_introductory(local_model_cost_map: No
         assert sonnet_5[field] == pytest.approx(sonnet_4_6[field]), field
 
 
-@pytest.mark.parametrize("model", PROMOTIONALLY_DISCOUNTED_MODELS)
-def test_promotionally_discounted_entries_price_below_the_published_table(
+@pytest.mark.parametrize("model", ENTRIES_STORING_PROMOTIONAL_RATE)
+def test_entries_storing_the_promotional_rate_price_below_the_published_table(
     local_model_cost_map: None,
     model: str,
 ) -> None:
     info: Final = _model_info(model)
     input_dbu, output_dbu, _, _ = PUBLISHED_DBU_PER_MILLION[model]
+    expiry_hint: Final = f"the gemini promotion expires {PROMOTION_EXPIRES}, after which the list rate applies"
 
-    assert info["input_cost_per_token"] == pytest.approx(_dollars_per_token(input_dbu) * PROMOTIONAL_DISCOUNT, rel=1e-3)
+    assert info["input_cost_per_token"] == pytest.approx(
+        _dollars_per_token(input_dbu) * PROMOTIONAL_DISCOUNT, rel=2e-4
+    ), expiry_hint
     assert info["output_cost_per_token"] == pytest.approx(
-        _dollars_per_token(output_dbu) * PROMOTIONAL_DISCOUNT, rel=1e-3
-    )
+        _dollars_per_token(output_dbu) * PROMOTIONAL_DISCOUNT, rel=2e-4
+    ), expiry_hint
     assert info["cache_creation_input_token_cost"] == pytest.approx(info["input_cost_per_token"])
     assert info["cache_read_input_token_cost"] == pytest.approx(0.1 * info["input_cost_per_token"])
+
+
+@pytest.mark.parametrize("model", ENTRIES_STORING_LIST_RATE_DESPITE_PROMOTION)
+def test_entries_storing_the_list_rate_bill_above_the_promotional_price(
+    local_model_cost_map: None,
+    model: str,
+) -> None:
+    info: Final = _model_info(model)
+    input_dbu, _, _, _ = PUBLISHED_DBU_PER_MILLION[model]
+    list_rate: Final = _dollars_per_token(input_dbu)
+
+    assert info["input_cost_per_token"] == pytest.approx(list_rate, rel=2e-4), (
+        f"{model} moved off the list rate; if it now stores the discount that runs to "
+        f"{PROMOTION_EXPIRES}, move it into ENTRIES_STORING_PROMOTIONAL_RATE"
+    )
+    assert info["cache_creation_input_token_cost"] == pytest.approx(info["input_cost_per_token"])

From d447be15b965a052e49a2d3c0b9f538d85c9d865 Mon Sep 17 00:00:00 2001
From: yucheng-berri <yucheng@berri.ai>
Date: Sat, 22 Aug 2026 19:13:48 -0700
Subject: [PATCH 72/93] feat(newrelic): per-team New Relic trace routing via
 team callbacks (#37603)

---
 litellm/integrations/callback_configs.json    |  14 +-
 litellm/integrations/otel/emitter.py          |   6 +
 litellm/integrations/otel/logger.py           |  36 +++-
 litellm/integrations/otel/model/config.py     |  10 +
 litellm/integrations/otel/model/metadata.py   |   6 +
 .../integrations/otel/plumbing/providers.py   |   2 +
 litellm/integrations/otel/plumbing/routing.py |  29 ++-
 litellm/integrations/otel/presets/__init__.py |  70 +++++--
 litellm/integrations/otel/presets/newrelic.py | 104 +++++++++++
 .../initialize_dynamic_callback_params.py     |  32 +++-
 litellm/litellm_core_utils/litellm_logging.py |   7 +
 .../callback_config_validation.py             |  77 ++++++++
 litellm/proxy/litellm_pre_call_utils.py       |   6 +
 .../key_management_endpoints.py               |  15 ++
 .../team_callback_endpoints.py                |  13 ++
 litellm/types/utils.py                        |   5 +
 .../integrations/otel/test_otel_v2_dynamic.py | 164 +++++++++++-----
 .../integrations/otel/test_otel_v2_logger.py  | 175 ++++++++++++++++++
 .../integrations/otel/test_otel_v2_presets.py |  52 ++++++
 ...test_initialize_dynamic_callback_params.py |  46 +++++
 .../test_litellm_logging.py                   |  78 ++++++++
 .../test_callback_management_endpoints.py     | 145 +++++++++++++++
 .../proxy/test_litellm_pre_call_utils.py      |  89 +++++++++
 .../src/components/callback_info_helpers.tsx  |  12 ++
 24 files changed, 1111 insertions(+), 82 deletions(-)
 create mode 100644 litellm/integrations/otel/presets/newrelic.py
 create mode 100644 litellm/proxy/common_utils/callback_config_validation.py

diff --git a/litellm/integrations/callback_configs.json b/litellm/integrations/callback_configs.json
index 590c848767a..6d2bcea8bae 100644
--- a/litellm/integrations/callback_configs.json
+++ b/litellm/integrations/callback_configs.json
@@ -294,12 +294,18 @@
     "id": "newrelic",
     "displayName": "New Relic",
     "logo": "newrelic.png",
-    "supports_key_team_logging": false,
+    "supports_key_team_logging": true,
     "dynamic_params": {
-      "NEW_RELIC_AI_MONITORING_RECORD_CONTENT_ENABLED": {
+      "newrelic_api_key": {
+        "type": "password",
+        "ui_name": "New Relic Ingest License Key",
+        "description": "Per-team ingest (license) key. Team traces export to this key's New Relic account over OTLP.",
+        "required": false
+      },
+      "newrelic_region": {
         "type": "text",
-        "ui_name": "Record AI Content (default: true)",
-        "description": "Whether to record AI message content. Set to false to disable.",
+        "ui_name": "New Relic Region (us or eu)",
+        "description": "Data center region for this team's account. Defaults to us.",
         "required": false
       }
     },
diff --git a/litellm/integrations/otel/emitter.py b/litellm/integrations/otel/emitter.py
index 0850d867c7b..244e58eddf3 100644
--- a/litellm/integrations/otel/emitter.py
+++ b/litellm/integrations/otel/emitter.py
@@ -156,6 +156,12 @@ class SpanEmitter:
             links=list(links) if links else None,
         )
 
+    def mark_emitted(self, dedup_key: str | None, role: SpanRole) -> None:
+        """Register a span emitted outside :meth:`emit` (the boundary-opened
+        LLM-call span closed via :meth:`finish_span`) so a later :meth:`emit`
+        for the same ``(dedup_key, role)`` deduplicates against it."""
+        self._seen(dedup_key, role)
+
     def _seen(self, dedup_key: str | None, role: SpanRole) -> bool:
         """Return True once a ``(dedup_key, role)`` pair has been emitted.
 
diff --git a/litellm/integrations/otel/logger.py b/litellm/integrations/otel/logger.py
index 53b9829023c..4359b222d06 100644
--- a/litellm/integrations/otel/logger.py
+++ b/litellm/integrations/otel/logger.py
@@ -484,10 +484,15 @@ class OpenTelemetryV2(CustomLogger):
         # ``pop`` is the dedup: this method runs from both the success and failure
         # paths, and whichever fires first removes the carrier and closes the span.
         carrier: Final = self._open_llm_calls.pop(call_id, None) if call_id else None
-        if carrier is None:
+        # A missing carrier does not always mean nothing happened: a team/key-scoped
+        # logger is a success/failure callback only, so ``pre_call`` never reaches it
+        # and no carrier exists. The payload plus the request-level provider-handoff
+        # stamp (``upstream_started``) is the affirmative signal of a real call; a
+        # gate rejection carries ``is_no_upstream_call`` and gets no span.
+        if carrier is None and (call.is_no_upstream_call or not call.upstream_started or call.payload is None):
             return None
         try:
-            return self._finish_carrier(carrier, call, end_time)
+            return self._finish_carrier(carrier, call, start_time, end_time)
         finally:
             # After the span has ended, so a release-triggered provider shutdown
             # force-flushes it out rather than racing its enqueue.
@@ -497,8 +502,11 @@ class OpenTelemetryV2(CustomLogger):
         """Remember an in-flight LLM call, evicting the oldest if over budget.
 
         A call that opens but never closes (a stream that only fires stream
-        events) would linger otherwise; the evicted span is simply dropped
-        (never exported).
+        events) would linger otherwise. Eviction only drops the boundary carrier,
+        not the call: if that call later closes as a real completed call, it still
+        emits through the deferred branch in ``_close_llm_call`` (the same path a
+        team/key-scoped logger uses, since it never opens a carrier), deduplicated
+        by call id. Only a call that is evicted and never closes goes unexported.
         """
         self._open_llm_calls[call_id] = carrier
         if len(self._open_llm_calls) > _OPEN_CALLS_MAX:
@@ -512,15 +520,20 @@ class OpenTelemetryV2(CustomLogger):
 
     def _finish_carrier(
         self,
-        carrier: _LLMCallSpan,
+        carrier: "_LLMCallSpan | None",
         call: LLMCallEvent,
+        start_time: datetime | float | None,
         end_time: datetime | float | None,
     ) -> Span | None:
         payload: Final = call.payload
+        call_id: Final = call.call_id
         if payload is None:
-            if carrier.span is not None:
+            if carrier is not None and carrier.span is not None:
                 # Opened at the boundary but the payload never materialized — end
-                # it (named provisionally) so it isn't leaked as an open span.
+                # it (named provisionally) so it isn't leaked as an open span, and
+                # register the dedup marker so a later payload-carrying close for
+                # the same call id cannot re-emit through the deferred branch.
+                self._emitter.mark_emitted(call_id, SpanRole.LLM_CALL)
                 carrier.span.end(end_time=to_ns(end_time))
             return None
         data: Final = LLMCallSpanData.from_standard_logging_payload(
@@ -529,10 +542,13 @@ class OpenTelemetryV2(CustomLogger):
             time_to_first_chunk_seconds=call.time_to_first_chunk_seconds,
         )
         end_time_ns: Final = to_ns(end_time)
-        if carrier.span is not None:
+        if carrier is not None and carrier.span is not None:
             # Born at the boundary: stamp attributes from the typed payload, set
             # status, and end it. Its parent (the server span) was captured at
-            # creation from real ambient context.
+            # creation from real ambient context. Register the dedup marker so a
+            # second close for the same call id (success then failure on one
+            # logging object) cannot re-emit through the deferred branch.
+            self._emitter.mark_emitted(call_id, SpanRole.LLM_CALL)
             self._emitter.finish_span(SpanRole.LLM_CALL, carrier.span, data, end_time_ns=end_time_ns)
             return carrier.span
         # Deferred: ``pre_call`` saw no recordable parent, so create the span now.
@@ -549,7 +565,7 @@ class OpenTelemetryV2(CustomLogger):
                 SpanRole.LLM_CALL,
                 data,
                 parent_context=(set_span_in_context(INVALID_SPAN, parent_ctx) if route.detached else parent_ctx),
-                start_time_ns=carrier.start_time_ns,
+                start_time_ns=(carrier.start_time_ns if carrier is not None else to_ns(start_time)),
                 end_time_ns=end_time_ns,
                 tracer=route.tracer,
                 links=_request_trace_links(parent_ctx) if route.detached else None,
diff --git a/litellm/integrations/otel/model/config.py b/litellm/integrations/otel/model/config.py
index 53178b48991..9e3064c2bff 100644
--- a/litellm/integrations/otel/model/config.py
+++ b/litellm/integrations/otel/model/config.py
@@ -39,6 +39,7 @@ class ExporterOwner(str, Enum):
     WEAVE_OTEL = "weave_otel"
     LEVO = "levo"
     AGENTOPS = "agentops"
+    NEWRELIC = "newrelic"
 
 
 class _OTelV2Flag(BaseSettings):
@@ -97,6 +98,15 @@ class ExporterSpec(BaseModel):
             "auto (Simple for console/in_memory, Batch otherwise)."
         ),
     )
+    requires_headers: bool = Field(
+        default=False,
+        description=(
+            "Skip this exporter when no headers are resolved. For destinations "
+            "that reject unauthenticated exports (e.g. New Relic), a spec kept "
+            "only as the per-request credential-stamping target would otherwise "
+            "export keyless traffic and produce a 4xx for every span batch."
+        ),
+    )
 
 
 class OpenTelemetryV2Config(BaseSettings):
diff --git a/litellm/integrations/otel/model/metadata.py b/litellm/integrations/otel/model/metadata.py
index de6366e7dbd..062b2ca20b4 100644
--- a/litellm/integrations/otel/model/metadata.py
+++ b/litellm/integrations/otel/model/metadata.py
@@ -203,6 +203,11 @@ class LLMCallEvent:
     # True for synthetic proxy-gate logs (auth / rate-limit rejections): they fire
     # the ``pre_call`` hook but never made an upstream call, so they get no span.
     is_no_upstream_call: bool
+    # True once the request handed off to a provider (``pre_call`` stamped
+    # ``api_call_start_time``). The affirmative signal that an LLM call was
+    # actually attempted — router pre-call rejections, SDK failures before the
+    # provider handoff, and standalone guardrail runs all lack it.
+    upstream_started: bool
     # A best-effort ``"{operation} {model}"`` name known at ``pre_call`` time. The
     # span is renamed from the typed payload at close (``finish_span``); this only
     # needs to be reasonable for a span that never gets closed (a leak).
@@ -221,6 +226,7 @@ class LLMCallEvent:
             dynamic_params=kwargs.get("standard_callback_dynamic_params"),
             auth_metadata=auth_metadata(payload, kwargs),
             is_no_upstream_call=bool(kwargs.get(LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL)),
+            upstream_started=kwargs.get("api_call_start_time") is not None,
             provisional_span_name=f"{operation.value} {model}".strip(),
             time_to_first_chunk_seconds=time_to_first_chunk_seconds(kwargs),
         )
diff --git a/litellm/integrations/otel/plumbing/providers.py b/litellm/integrations/otel/plumbing/providers.py
index 80a8d01c061..81b00f788ee 100644
--- a/litellm/integrations/otel/plumbing/providers.py
+++ b/litellm/integrations/otel/plumbing/providers.py
@@ -436,6 +436,8 @@ def build_tracer_provider(
     # ``config._normalize`` guarantees at least one spec (it folds the top-level
     # ``exporter``/``endpoint``/``headers`` fields in when ``exporters`` is empty).
     for spec in config.exporters:
+        if spec.requires_headers and not spec.headers:
+            continue
         exp = _exporter_from_spec(spec)
         provider.add_span_processor(
             _processor_for(
diff --git a/litellm/integrations/otel/plumbing/routing.py b/litellm/integrations/otel/plumbing/routing.py
index f231df9e914..6a04dbb9bc8 100644
--- a/litellm/integrations/otel/plumbing/routing.py
+++ b/litellm/integrations/otel/plumbing/routing.py
@@ -28,6 +28,7 @@ from litellm.integrations.otel.plumbing.providers import (
     get_tracer,
 )
 from litellm.integrations.otel.presets import (
+    dynamic_otlp_endpoint,
     dynamic_otlp_headers,
     project_routing_headers,
 )
@@ -129,7 +130,9 @@ class TenantTracerCache:
         # thread-pool workers concurrently with the event loop, so cache
         # updates, span counts, and retirement must be atomic.
         self._lock: Final = threading.Lock()
-        self._providers: OrderedDict[tuple[_HeaderItems, _HeaderItems], TracerProvider] = OrderedDict()
+        self._providers: OrderedDict[tuple[_HeaderItems, _HeaderItems, str | None], TracerProvider] = (
+            OrderedDict()  # mutable-ok: bounded LRU; eviction needs in-place ordered mutation
+        )
         self._open_span_counts: dict[TracerProvider, int] = {}  # mutable-ok: live refcount state
         # Oldest-first so an overflow of draining providers sheds the stalest.
         self._retired: OrderedDict[TracerProvider, None] = OrderedDict()  # mutable-ok: draining evicted providers
@@ -182,12 +185,16 @@ class TenantTracerCache:
         project_headers: Final = self._project_headers(auth_metadata)
         if not credential_headers and not project_headers:
             return TenantRoute(tracer=default, detached=False)
+        # A fixed per-integration region endpoint (New Relic us/eu), never a
+        # caller-supplied host; ``None`` keeps the preset's own endpoint.
+        endpoint: Final = dynamic_otlp_endpoint(self._callback_name, dynamic_params)
         cache_key: Final = (
             tuple(sorted(credential_headers.items())),
             tuple(sorted(project_headers.items())),
+            endpoint,
         )
         with self._lock:
-            provider: Final = self._cached_provider_locked(cache_key, credential_headers, project_headers)
+            provider: Final = self._cached_provider_locked(cache_key, credential_headers, project_headers, endpoint)
             self._open_span_counts[provider] = self._open_span_counts.get(provider, 0) + 1
             evicted: Final = self._evicted_on_overflow_locked()
         if evicted is not None:
@@ -200,15 +207,16 @@ class TenantTracerCache:
 
     def _cached_provider_locked(
         self,
-        cache_key: tuple[_HeaderItems, _HeaderItems],
+        cache_key: tuple[_HeaderItems, _HeaderItems, str | None],
         credential_headers: Mapping[str, str],
         project_headers: Mapping[str, str],
+        endpoint: str | None,
     ) -> TracerProvider:
         cached: Final = self._providers.get(cache_key)
         if cached is not None:
             self._providers.move_to_end(cache_key)
             return cached
-        built: Final = build_tracer_provider(self._routed_config(credential_headers, project_headers))
+        built: Final = build_tracer_provider(self._routed_config(credential_headers, project_headers, endpoint))
         self._providers[cache_key] = built
         return built
 
@@ -257,6 +265,7 @@ class TenantTracerCache:
         self,
         credential_headers: Mapping[str, str],
         project_headers: Mapping[str, str],
+        endpoint: str | None = None,
     ) -> OpenTelemetryV2Config:
         """Clone the config, rewriting headers on the callback's own exporter.
 
@@ -272,7 +281,8 @@ class TenantTracerCache:
         ``Authorization``), which must survive routing to a project.
         """
         exporters: Final = [
-            self._routed_exporter(spec, credential_headers, project_headers) for spec in self._config.exporters
+            self._routed_exporter(spec, credential_headers, project_headers, endpoint)
+            for spec in self._config.exporters
         ]
         return self._config.model_copy(update={"exporters": exporters})
 
@@ -281,6 +291,7 @@ class TenantTracerCache:
         spec: ExporterSpec,
         credential_headers: Mapping[str, str],
         project_headers: Mapping[str, str],
+        endpoint: str | None = None,
     ) -> ExporterSpec:
         kind: Final = spec.kind.lower()
         if spec.owner != self._callback_name or kind in _NON_OTLP_KINDS:
@@ -291,4 +302,10 @@ class TenantTracerCache:
             if project_headers and kind not in _GRPC_KINDS
             else base
         )
-        return spec if routed == spec.headers else spec.model_copy(update={"headers": routed})
+        update: Final = {  # mutable-ok: model_copy(update=...) requires a plain dict
+            field: value
+            for field, value in (("headers", routed), ("endpoint", endpoint))
+            if (field == "headers" and routed != spec.headers)
+            or (field == "endpoint" and endpoint is not None and endpoint != spec.endpoint)
+        }
+        return spec if not update else spec.model_copy(update=update)
diff --git a/litellm/integrations/otel/presets/__init__.py b/litellm/integrations/otel/presets/__init__.py
index 35b0584c697..a0cd5b3fd98 100644
--- a/litellm/integrations/otel/presets/__init__.py
+++ b/litellm/integrations/otel/presets/__init__.py
@@ -21,6 +21,11 @@ from litellm.integrations.otel.presets.langfuse import (
 )
 from litellm.integrations.otel.presets.langtrace import langtrace_preset
 from litellm.integrations.otel.presets.levo import levo_preset
+from litellm.integrations.otel.presets.newrelic import (
+    newrelic_dynamic_endpoint,
+    newrelic_dynamic_headers,
+    newrelic_preset,
+)
 from litellm.integrations.otel.presets.phoenix import (
     phoenix_preset,
     phoenix_project_headers,
@@ -30,25 +35,45 @@ from litellm.types.utils import StandardCallbackDynamicParams
 
 #: Callback name → preset. The ``Preset`` annotation makes mypy verify every
 #: registered value matches the preset interface.
-PRESET_BY_CALLBACK: Final[dict[str, Preset]] = {
-    "agentops": agentops_preset,
-    "arize": arize_preset,
-    "arize_phoenix": phoenix_preset,
-    "langfuse_otel": langfuse_preset,
-    "langtrace": langtrace_preset,
-    "levo": levo_preset,
-    "weave_otel": weave_preset,
-}
+PRESET_BY_CALLBACK: Final[Mapping[str, Preset]] = MappingProxyType(
+    {
+        "agentops": agentops_preset,
+        "arize": arize_preset,
+        "arize_phoenix": phoenix_preset,
+        "langfuse_otel": langfuse_preset,
+        "langtrace": langtrace_preset,
+        "levo": levo_preset,
+        "newrelic": newrelic_preset,
+        "weave_otel": weave_preset,
+    }
+)
 
 #: Callback name → per-request OTLP header builder (team/key multi-tenant
 #: routing). Only integrations that support dynamic credentials appear here —
 #: Arize-Phoenix/Langtrace/Levo/AgentOps don't, so they use the logger's
 #: default tracer.
-DYNAMIC_HEADERS_BY_CALLBACK: Final[dict[str, Callable[[StandardCallbackDynamicParams], dict[str, str]]]] = {
-    "arize": arize_dynamic_headers,
-    "langfuse_otel": langfuse_dynamic_headers,
-    "weave_otel": weave_dynamic_headers,
-}
+DYNAMIC_HEADERS_BY_CALLBACK: Final[Mapping[str, Callable[[StandardCallbackDynamicParams], dict[str, str]]]] = (
+    MappingProxyType(
+        {
+            "arize": arize_dynamic_headers,
+            "langfuse_otel": langfuse_dynamic_headers,
+            "newrelic": newrelic_dynamic_headers,
+            "weave_otel": weave_dynamic_headers,
+        }
+    )
+)
+
+#: Callback name → per-request OTLP endpoint resolver. Only integrations whose
+#: destination host varies per tenant (from a fixed region table, never a
+#: caller-supplied URL) appear here; for everyone else the preset's endpoint is
+#: authoritative.
+DYNAMIC_ENDPOINT_BY_CALLBACK: Final[Mapping[str, Callable[[StandardCallbackDynamicParams], str | None]]] = (
+    MappingProxyType(
+        {
+            "newrelic": newrelic_dynamic_endpoint,
+        }
+    )
+)
 
 
 #: Callback name → per-request *routing* header builder, sourced from the key/team
@@ -98,17 +123,34 @@ def project_routing_headers(
     return builder(auth_metadata)
 
 
+def dynamic_otlp_endpoint(
+    callback_name: str | None,
+    dynamic_params: StandardCallbackDynamicParams | None,
+) -> str | None:
+    """Per-request OTLP endpoint for ``callback_name``, or ``None`` if N/A.
+
+    ``None`` means "keep the preset's own endpoint".
+    """
+    resolver: Final = DYNAMIC_ENDPOINT_BY_CALLBACK.get(callback_name or "")
+    if resolver is None or not dynamic_params:
+        return None
+    return resolver(dynamic_params)
+
+
 __all__ = [
+    "DYNAMIC_ENDPOINT_BY_CALLBACK",
     "DYNAMIC_HEADERS_BY_CALLBACK",
     "PRESET_BY_CALLBACK",
     "PROJECT_HEADERS_BY_CALLBACK",
     "Preset",
     "agentops_preset",
     "arize_preset",
+    "dynamic_otlp_endpoint",
     "dynamic_otlp_headers",
     "langfuse_preset",
     "langtrace_preset",
     "levo_preset",
+    "newrelic_preset",
     "phoenix_preset",
     "project_routing_headers",
     "weave_preset",
diff --git a/litellm/integrations/otel/presets/newrelic.py b/litellm/integrations/otel/presets/newrelic.py
new file mode 100644
index 00000000000..4660a707355
--- /dev/null
+++ b/litellm/integrations/otel/presets/newrelic.py
@@ -0,0 +1,104 @@
+"""New Relic preset — OTLP/HTTP exporter to New Relic + GenAI vocabulary."""
+
+from collections.abc import Mapping
+from types import MappingProxyType
+from typing import Final
+
+from pydantic import Field
+from pydantic_settings import BaseSettings, SettingsConfigDict
+
+from litellm._logging import verbose_logger
+from litellm.integrations.otel.model.config import (
+    ExporterOwner,
+    ExporterSpec,
+    OpenTelemetryV2Config,
+)
+from litellm.integrations.otel.presets.utils import ensure_mappers
+from litellm.types.utils import StandardCallbackDynamicParams
+
+#: Region -> OTLP base endpoint. A fixed table by design: team config picks a
+#: region enum rather than a free-form endpoint, so callback vars can never
+#: redirect telemetry to an arbitrary host.
+NEWRELIC_OTLP_ENDPOINT_BY_REGION: Final[Mapping[str, str]] = MappingProxyType(
+    {
+        "us": "https://otlp.nr-data.net",
+        "eu": "https://otlp.eu01.nr-data.net",
+    }
+)
+
+_DEFAULT_REGION: Final = "us"
+
+
+class _NewRelicSettings(BaseSettings):
+    model_config = SettingsConfigDict(case_sensitive=False, extra="ignore")
+
+    # The same env vars the agent-based integration documents; the key is the
+    # operator-level fallback for traffic without team credentials, the region
+    # picks that fallback's data center, and the record-content flag keeps its
+    # documented meaning when the OTel path replaces the agent.
+    license_key: str | None = Field(default=None, validation_alias="NEW_RELIC_LICENSE_KEY")
+    region: str | None = Field(default=None, validation_alias="NEW_RELIC_REGION")
+    record_content: bool | None = Field(default=None, validation_alias="NEW_RELIC_AI_MONITORING_RECORD_CONTENT_ENABLED")
+
+
+def newrelic_preset(
+    *,
+    config_overrides: OpenTelemetryV2Config | None = None,
+) -> OpenTelemetryV2Config:
+    settings: Final = _NewRelicSettings()
+    base: Final = config_overrides or OpenTelemetryV2Config()
+    endpoint: Final = NEWRELIC_OTLP_ENDPOINT_BY_REGION.get(
+        (settings.region or _DEFAULT_REGION).lower(), NEWRELIC_OTLP_ENDPOINT_BY_REGION[_DEFAULT_REGION]
+    )
+    return base.model_copy(
+        update={
+            "exporters": [
+                *base.exporters,
+                ExporterSpec(
+                    kind="otlp_http",
+                    endpoint=endpoint,
+                    headers=(f"api-key={settings.license_key}" if settings.license_key else None),
+                    owner=ExporterOwner.NEWRELIC,
+                    requires_headers=True,
+                ),
+            ],
+            # New Relic ingests the OTLP GenAI semantic conventions natively.
+            "mapper_names": ensure_mappers(base.mapper_names, "genai"),
+            **(
+                {"capture_message_content": ("span_only" if settings.record_content else "no_content")}
+                if settings.record_content is not None
+                else {}
+            ),
+        }
+    )
+
+
+def newrelic_dynamic_headers(params: StandardCallbackDynamicParams) -> dict[str, str]:
+    """Per-request New Relic OTLP headers from team/key dynamic params."""
+    api_key: Final = params.get("newrelic_api_key")
+    return {header: value for header, value in (("api-key", api_key),) if value}
+
+
+def newrelic_dynamic_endpoint(params: StandardCallbackDynamicParams) -> str:
+    """Per-request OTLP endpoint for the team's ``newrelic_region``.
+
+    Always the team's own region endpoint, defaulting to US when the team left
+    the region unset. It never falls through to the preset's endpoint, which
+    follows the operator's ``NEW_RELIC_REGION`` env; a team that saved only its
+    ingest key must not inherit the operator's region and have its US-account
+    spans rejected by an EU-configured default (or vice versa). An unknown
+    region likewise resolves to the documented US default rather than a guess.
+    """
+    region: Final = params.get("newrelic_region")
+    default_endpoint: Final = NEWRELIC_OTLP_ENDPOINT_BY_REGION[_DEFAULT_REGION]
+    if not region:
+        return default_endpoint
+    endpoint: Final = NEWRELIC_OTLP_ENDPOINT_BY_REGION.get(region.lower())
+    if endpoint is None:
+        verbose_logger.warning(
+            "New Relic: unknown newrelic_region %r; supported regions: %s. Using the default (US) endpoint.",
+            region,
+            ", ".join(sorted(NEWRELIC_OTLP_ENDPOINT_BY_REGION)),
+        )
+        return default_endpoint
+    return endpoint
diff --git a/litellm/litellm_core_utils/initialize_dynamic_callback_params.py b/litellm/litellm_core_utils/initialize_dynamic_callback_params.py
index 284989ab20f..3b42ca4eaaf 100644
--- a/litellm/litellm_core_utils/initialize_dynamic_callback_params.py
+++ b/litellm/litellm_core_utils/initialize_dynamic_callback_params.py
@@ -46,7 +46,7 @@ def validate_no_callback_env_reference(param: str, value: object, *, source: str
 
 
 # Hardcoded list of supported callback params to avoid runtime inspection issues with TypedDict
-_supported_callback_params: Final = [
+_supported_callback_params: Final[tuple[str, ...]] = (
     "langfuse_public_key",
     "langfuse_secret",
     "langfuse_secret_key",
@@ -72,8 +72,10 @@ _supported_callback_params: Final = [
     "dd_site",
     "dd_agent_host",
     "dd_agent_port",
+    "newrelic_api_key",
+    "newrelic_region",
     "turn_off_message_logging",
-]
+)
 
 _request_blocked_callback_params: Final = frozenset(
     {
@@ -83,6 +85,20 @@ _request_blocked_callback_params: Final = frozenset(
         "dd_site",
         "dd_agent_host",
         "dd_agent_port",
+        "newrelic_api_key",
+        "newrelic_region",
+    }
+)
+
+# Request-blocked params that must still reach ``standard_callback_dynamic_params``
+# when the proxy itself stamped them from admin-configured team/key callback
+# settings (the trusted-vars channel). The OTel per-tenant tracer routing reads
+# ``standard_callback_dynamic_params``, so without this overlay a blocked param
+# could never drive routing at all.
+_trusted_overlay_callback_params: Final = frozenset(
+    {
+        "newrelic_api_key",
+        "newrelic_region",
     }
 )
 
@@ -121,7 +137,9 @@ def initialize_standard_callback_dynamic_params(
             if param in kwargs:
                 _param_value = kwargs.get(param)
                 validate_no_callback_env_reference(param, _param_value, source="request body")
-                standard_callback_dynamic_params[param] = _param_value
+                standard_callback_dynamic_params[param] = (  # pyright: ignore[reportGeneralTypeIssues]  # several supported params predate their StandardCallbackDynamicParams fields
+                    _param_value
+                )
 
         for slot_label, metadata in iter_client_callback_metadata_dicts(kwargs):
             for param in _supported_callback_params:
@@ -130,6 +148,12 @@ def initialize_standard_callback_dynamic_params(
                 if param not in standard_callback_dynamic_params and param in metadata:
                     _param_value = metadata.get(param)
                     validate_no_callback_env_reference(param, _param_value, source=slot_label)
-                    standard_callback_dynamic_params[param] = _param_value
+                    standard_callback_dynamic_params[param] = (  # pyright: ignore[reportGeneralTypeIssues]  # several supported params predate their StandardCallbackDynamicParams fields
+                        _param_value
+                    )
+
+        for param, trusted_value in get_trusted_callback_params(kwargs):
+            if param in _trusted_overlay_callback_params:
+                standard_callback_dynamic_params[param] = trusted_value
 
     return standard_callback_dynamic_params
diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index c14dd6c3d8b..3ad4c187b6d 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -4503,6 +4503,9 @@ def _init_custom_logger_compatible_class(
             _in_memory_loggers.append(gitlab_logger)
             return gitlab_logger
         elif logging_integration == "newrelic":
+            _v2 = _maybe_construct_otel_v2("newrelic", _in_memory_loggers)
+            if _v2 is not None:
+                return _v2
             for callback in _in_memory_loggers:
                 if isinstance(callback, NewRelicLogger):
                     return callback
@@ -4789,7 +4792,11 @@ def get_custom_logger_compatible_class(
                 if isinstance(callback, SMTPEmailLogger):
                     return callback
         elif logging_integration == "newrelic":
+            from litellm.integrations.otel.logger import OpenTelemetryV2
+
             for callback in _in_memory_loggers:
+                if isinstance(callback, OpenTelemetryV2) and callback.callback_name == "newrelic":
+                    return callback
                 if isinstance(callback, NewRelicLogger):
                     return callback
         return None
diff --git a/litellm/proxy/common_utils/callback_config_validation.py b/litellm/proxy/common_utils/callback_config_validation.py
new file mode 100644
index 00000000000..680cc226d18
--- /dev/null
+++ b/litellm/proxy/common_utils/callback_config_validation.py
@@ -0,0 +1,77 @@
+"""Save-time validation of team/key logging configs the runtime cannot honor.
+
+Team callbacks arrive as a single ``AddTeamCallback``, key callbacks arrive as a
+``logging`` list inside the key metadata, so both shapes funnel into the same
+per-integration checks here.
+"""
+
+from collections.abc import Mapping, Sequence
+from types import MappingProxyType
+from typing import Final
+
+_NEWRELIC_CALLBACK: Final = "newrelic"
+_NEWRELIC_VAR_PREFIX: Final = "newrelic_"
+
+
+def callback_config_error(callback_name: str | None, callback_vars: Mapping[str, str] | None) -> str | None:
+    if callback_name != _NEWRELIC_CALLBACK or not callback_vars:
+        return None
+    return _newrelic_config_error(callback_vars)
+
+
+def logging_metadata_config_error(metadata: Mapping[str, object] | None) -> str | None:
+    """Validate every ``logging`` entry of a team/key metadata payload."""
+    if not metadata:
+        return None
+    entries: Final = metadata.get("logging")
+    if not isinstance(entries, Sequence) or isinstance(entries, (str, bytes)):
+        return None
+    return next(
+        (error for error in (_logging_entry_error(entry) for entry in entries) if error is not None),
+        None,
+    )
+
+
+def _logging_entry_error(entry: object) -> str | None:
+    if not isinstance(entry, Mapping):
+        return None
+    callback_name: Final = entry.get("callback_name")
+    callback_vars: Final = entry.get("callback_vars")
+    if not isinstance(callback_name, str) or not isinstance(callback_vars, Mapping):
+        return None
+    return callback_config_error(
+        callback_name,
+        MappingProxyType({str(key): str(value) for key, value in callback_vars.items()}),
+    )
+
+
+def _newrelic_config_error(callback_vars: Mapping[str, str]) -> str | None:
+    """Per-team New Relic routing runs on the OTel v2 path only.
+
+    Accepting the config with the flag off would silently ship the team's traffic
+    through the operator's env-configured agent instead of the team's account. A
+    region outside the fixed table, or a region without a key, would likewise be
+    accepted and then silently ignored or misrouted at request time.
+    """
+    if not any(key.startswith(_NEWRELIC_VAR_PREFIX) for key in callback_vars):
+        return None
+
+    from litellm.integrations.otel.model.config import is_otel_v2_enabled
+    from litellm.integrations.otel.presets.newrelic import NEWRELIC_OTLP_ENDPOINT_BY_REGION
+
+    if not is_otel_v2_enabled():
+        return "Per-team New Relic routing requires the proxy to run with LITELLM_OTEL_V2=true."
+
+    region: Final = callback_vars.get("newrelic_region")
+    if region is not None and region.lower() not in NEWRELIC_OTLP_ENDPOINT_BY_REGION:
+        return (
+            f"Unknown newrelic_region {region!r}. "
+            f"Supported regions: {', '.join(sorted(NEWRELIC_OTLP_ENDPOINT_BY_REGION))}."
+        )
+
+    # ``callback_vars`` values are str()-coerced upstream, so a JSON ``null`` key
+    # arrives as the literal ``"None"``; treat that and the empty string as absent.
+    api_key: Final = callback_vars.get("newrelic_api_key")
+    if region is not None and (not api_key or api_key == "None"):
+        return "newrelic_region requires newrelic_api_key; the region rides the team's own key."
+    return None
diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py
index 4794da05a3e..cb5002e431b 100644
--- a/litellm/proxy/litellm_pre_call_utils.py
+++ b/litellm/proxy/litellm_pre_call_utils.py
@@ -754,6 +754,12 @@ def convert_key_logging_metadata_to_callback(
             team_callback_settings_obj.callbacks.append(data.callback_name)
 
     for var, value in data.callback_vars.items():
+        # New Relic routing reads these from the trusted-vars overlay with no
+        # callback-name check, so scope them to the newrelic entry: a team that
+        # put newrelic_* under a different callback never asked for New Relic and
+        # must not export to it.
+        if var.startswith("newrelic_") and data.callback_name != "newrelic":
+            continue
         if team_callback_settings_obj.callback_vars is None:
             team_callback_settings_obj.callback_vars = {}
         team_callback_settings_obj.callback_vars[var] = str(value)
diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py
index 34a91dc59da..54f567b7aa2 100644
--- a/litellm/proxy/management_endpoints/key_management_endpoints.py
+++ b/litellm/proxy/management_endpoints/key_management_endpoints.py
@@ -62,6 +62,7 @@ from litellm.proxy.auth.auth_utils import (
     enforce_output_token_estimates_are_admin_only,
 )
 from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+from litellm.proxy.common_utils.callback_config_validation import logging_metadata_config_error
 from litellm.proxy.common_utils.callback_utils import (
     decrypt_callback_vars,
     encrypt_callback_vars,
@@ -553,6 +554,17 @@ def key_generation_check(
         return _personal_key_generation_check(user_api_key_dict=user_api_key_dict, data=data)
 
 
+def raise_on_invalid_key_logging_config(metadata: Mapping[str, object] | None) -> None:
+    """Key-level logging writes go through key metadata, not /team/callback.
+
+    Without this the same New Relic config the team endpoint rejects would be
+    accepted here and then silently ignored or misrouted at request time.
+    """
+    error: Final = logging_metadata_config_error(metadata)
+    if error is not None:
+        raise HTTPException(status_code=400, detail={"error": error})  # mutable-ok: FastAPI detail contract
+
+
 def common_key_access_checks(
     user_api_key_dict: UserAPIKeyAuth,
     data: GenerateKeyRequest | UpdateKeyRequest,
@@ -891,6 +903,7 @@ async def _common_key_generation_helper(
     )
 
     validate_budget_duration(data.budget_duration)
+    raise_on_invalid_key_logging_config(data.metadata)
 
     if data.throttle_on_budget_exceeded is True and user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN.value:
         raise HTTPException(
@@ -1992,6 +2005,8 @@ def prepare_metadata_fields(data: BaseModel, non_default_values: dict, existing_
     """
     Check LiteLLM_ManagementEndpoint_MetadataFields (proxy/_types.py) for fields that are allowed to be updated
     """
+    raise_on_invalid_key_logging_config(non_default_values.get("metadata"))
+
     if "metadata" not in non_default_values:  # allow user to set metadata to none
         non_default_values["metadata"] = existing_metadata.copy()
 
diff --git a/litellm/proxy/management_endpoints/team_callback_endpoints.py b/litellm/proxy/management_endpoints/team_callback_endpoints.py
index 0e8c4e1825d..14a2a8a98a5 100644
--- a/litellm/proxy/management_endpoints/team_callback_endpoints.py
+++ b/litellm/proxy/management_endpoints/team_callback_endpoints.py
@@ -28,6 +28,7 @@ from litellm.proxy._types import (
     UserAPIKeyAuth,
 )
 from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+from litellm.proxy.common_utils.callback_config_validation import callback_config_error
 from litellm.proxy.common_utils.callback_utils import (
     _CALLBACK_VAR_ENCRYPTED_PREFIX,
     decrypt_callback_vars,
@@ -51,6 +52,16 @@ router: Final = APIRouter()
 _CALLBACK_VARS_REDACTED: Final = "***REDACTED***"
 
 
+def _callback_config_error(message: str) -> HTTPException:
+    return HTTPException(status_code=400, detail={"error": message})  # mutable-ok: FastAPI detail contract
+
+
+def _validate_team_callback(data: "AddTeamCallback") -> None:
+    error: Final = callback_config_error(data.callback_name, data.callback_vars)
+    if error is not None:
+        raise _callback_config_error(error)
+
+
 def _redact_callback_secrets(metadata: Any) -> Any:
     """Strip secret values out of a team-metadata snapshot before audit logging.
 
@@ -304,6 +315,8 @@ async def add_team_callbacks(
             user_api_key_dict=user_api_key_dict,
         )
 
+        _validate_team_callback(data)
+
         # store team callback settings in metadata
         team_metadata = _existing_team.metadata
         team_callback_settings: list[dict] = team_metadata.get("logging")  # will be dict of type AddTeamCallback
diff --git a/litellm/types/utils.py b/litellm/types/utils.py
index 94526de0757..67eae2b4f21 100644
--- a/litellm/types/utils.py
+++ b/litellm/types/utils.py
@@ -3300,6 +3300,11 @@ class StandardCallbackDynamicParams(TypedDict, total=False):
     dd_agent_host: str | None
     dd_agent_port: str | None
 
+    # New Relic dynamic params (proxy-stamped team/key callback vars only;
+    # request-supplied values are blocked)
+    newrelic_api_key: str | None  # writable-ok: initialize_standard_callback_dynamic_params assigns into the dict
+    newrelic_region: str | None  # writable-ok: initialize_standard_callback_dynamic_params assigns into the dict
+
     # Logging settings
     turn_off_message_logging: bool | None  # when true will not log messages
     litellm_disabled_callbacks: list[str] | None
diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_dynamic.py b/tests/test_litellm/integrations/otel/test_otel_v2_dynamic.py
index a9a78dcb2f1..633be9f105f 100644
--- a/tests/test_litellm/integrations/otel/test_otel_v2_dynamic.py
+++ b/tests/test_litellm/integrations/otel/test_otel_v2_dynamic.py
@@ -7,6 +7,7 @@ from opentelemetry.trace import NoOpTracer
 
 from litellm.integrations.otel.model.config import ExporterSpec, OpenTelemetryV2Config
 from litellm.integrations.otel.presets import (
+    dynamic_otlp_endpoint,
     dynamic_otlp_headers,
     project_routing_headers,
 )
@@ -23,31 +24,23 @@ def _cache(callback_name, exporters=None):
 
 
 def test_arize_dynamic_headers():
-    headers = dynamic_otlp_headers(
-        "arize", {"arize_space_id": "S", "arize_api_key": "K"}
-    )
+    headers = dynamic_otlp_headers("arize", {"arize_space_id": "S", "arize_api_key": "K"})
     assert headers == {"arize-space-id": "S", "api_key": "K"}
 
 
 def test_arize_space_key_overrides_space_id():
-    headers = dynamic_otlp_headers(
-        "arize", {"arize_space_id": "S", "arize_space_key": "SK"}
-    )
+    headers = dynamic_otlp_headers("arize", {"arize_space_id": "S", "arize_space_key": "SK"})
     assert headers == {"arize-space-id": "SK"}
 
 
 def test_langfuse_dynamic_headers_need_both_keys():
     assert dynamic_otlp_headers("langfuse_otel", {"langfuse_public_key": "pk"}) is None
-    headers = dynamic_otlp_headers(
-        "langfuse_otel", {"langfuse_public_key": "pk", "langfuse_secret_key": "sk"}
-    )
+    headers = dynamic_otlp_headers("langfuse_otel", {"langfuse_public_key": "pk", "langfuse_secret_key": "sk"})
     assert headers is not None and "Authorization" in headers
 
 
 def test_langfuse_dynamic_headers_carry_v4_ingestion_version():
-    headers = dynamic_otlp_headers(
-        "langfuse_otel", {"langfuse_public_key": "pk", "langfuse_secret_key": "sk"}
-    )
+    headers = dynamic_otlp_headers("langfuse_otel", {"langfuse_public_key": "pk", "langfuse_secret_key": "sk"})
     expected_auth = "Basic " + base64.b64encode(b"pk:sk").decode()
     assert headers == {
         "Authorization": expected_auth,
@@ -56,9 +49,7 @@ def test_langfuse_dynamic_headers_carry_v4_ingestion_version():
 
 
 def test_weave_dynamic_headers():
-    headers = dynamic_otlp_headers(
-        "weave_otel", {"wandb_api_key": "w", "weave_project_id": "p"}
-    )
+    headers = dynamic_otlp_headers("weave_otel", {"wandb_api_key": "w", "weave_project_id": "p"})
     assert headers is not None
     assert "Authorization" in headers and headers["project_id"] == "p"
 
@@ -100,9 +91,7 @@ def test_provider_cache_is_bounded_and_evicts_lru(monkeypatch):
 
     monkeypatch.setattr(routing_mod, "_MAX_CACHED_PROVIDERS", 2)
     shut_down = []
-    monkeypatch.setattr(
-        routing_mod, "_shutdown_provider", lambda p: shut_down.append(p)
-    )
+    monkeypatch.setattr(routing_mod, "_shutdown_provider", lambda p: shut_down.append(p))
 
     cache = _cache("arize")
     default = NoOpTracer()
@@ -179,9 +168,7 @@ def test_dynamic_headers_do_not_leak_to_other_owners_exporter():
             ),
         ],
     )
-    new_cfg = cache._routed_config(
-        {"arize-space-id": "TEAMX", "api_key": "TEAMX_KEY"}, {}
-    )
+    new_cfg = cache._routed_config({"arize-space-id": "TEAMX", "api_key": "TEAMX_KEY"}, {})
     by_owner = {e.owner: e.headers for e in new_cfg.exporters}
     assert by_owner["arize"] == "arize-space-id=TEAMX,api_key=TEAMX_KEY"
     assert by_owner[None] == "x=base-collector"
@@ -206,16 +193,14 @@ def _phoenix_cache(kind="otlp_http"):
 
 
 def test_phoenix_project_headers_precedence_and_blanks():
-    assert project_routing_headers(
-        "arize_phoenix", {"phoenix_project_name": "team-proj"}
-    ) == {"x-project-name": "team-proj"}
+    assert project_routing_headers("arize_phoenix", {"phoenix_project_name": "team-proj"}) == {
+        "x-project-name": "team-proj"
+    }
     assert project_routing_headers(
         "arize_phoenix",
         {"phoenix_project_name_override": "override", "phoenix_project_name": "base"},
     ) == {"x-project-name": "override"}
-    assert (
-        project_routing_headers("arize_phoenix", {"phoenix_project_name": "   "}) == {}
-    )
+    assert project_routing_headers("arize_phoenix", {"phoenix_project_name": "   "}) == {}
     assert project_routing_headers("arize_phoenix", None) == {}
     # Only Phoenix participates in project routing.
     assert project_routing_headers("arize", {"phoenix_project_name": "p"}) == {}
@@ -286,10 +271,7 @@ def test_client_dynamic_params_cannot_choose_phoenix_project():
     cache = _phoenix_cache()
     default = NoOpTracer()
     assert cache.route_for(default, {"phoenix_project_name": "attacker"}).tracer is default
-    assert (
-        cache.route_for(default, {"phoenix_project_name_override": "attacker"}).tracer
-        is default
-    )
+    assert cache.route_for(default, {"phoenix_project_name_override": "attacker"}).tracer is default
     assert cache._providers == {}
 
 
@@ -321,9 +303,7 @@ def test_eviction_defers_shutdown_while_a_span_is_open(monkeypatch):
 
     monkeypatch.setattr(routing_mod, "_MAX_CACHED_PROVIDERS", 1)
     shut_down = []
-    monkeypatch.setattr(
-        routing_mod, "_shutdown_provider", lambda p: shut_down.append(p)
-    )
+    monkeypatch.setattr(routing_mod, "_shutdown_provider", lambda p: shut_down.append(p))
     cache = _cache("arize")
     default = NoOpTracer()
 
@@ -347,18 +327,13 @@ def test_retired_providers_are_capped(monkeypatch):
     monkeypatch.setattr(routing_mod, "_MAX_CACHED_PROVIDERS", 1)
     monkeypatch.setattr(routing_mod, "_MAX_RETIRED_PROVIDERS", 2)
     shut_down = []
-    monkeypatch.setattr(
-        routing_mod, "_shutdown_provider", lambda p: shut_down.append(p)
-    )
+    monkeypatch.setattr(routing_mod, "_shutdown_provider", lambda p: shut_down.append(p))
     cache = _cache("arize")
     default = NoOpTracer()
 
     # Every route stays held (no release), so each one evicts and retires its
     # predecessor instead of shutting it down.
-    routes = [
-        cache.route_for(default, {"arize_space_id": str(i), "arize_api_key": "K"})
-        for i in range(5)
-    ]
+    routes = [cache.route_for(default, {"arize_space_id": str(i), "arize_api_key": "K"}) for i in range(5)]
 
     assert len(cache._providers) == 1
     assert len(cache._retired) == 2  # capped, not one retiree per open call
@@ -374,11 +349,112 @@ def test_release_without_eviction_keeps_provider_alive(monkeypatch):
     from litellm.integrations.otel.plumbing import routing as routing_mod
 
     shut_down = []
-    monkeypatch.setattr(
-        routing_mod, "_shutdown_provider", lambda p: shut_down.append(p)
-    )
+    monkeypatch.setattr(routing_mod, "_shutdown_provider", lambda p: shut_down.append(p))
     cache = _cache("arize")
     route = cache.route_for(NoOpTracer(), {"arize_space_id": "A", "arize_api_key": "K"})
     cache.release(route.provider)
     assert shut_down == []  # still cached, never retired
     cache.release(None)  # default-route release is a no-op
+
+
+# --- New Relic: per-team api-key header + fixed-table region endpoint --- #
+
+
+def test_newrelic_dynamic_headers():
+    assert dynamic_otlp_headers("newrelic", {"newrelic_api_key": "NRAL-KEY"}) == {"api-key": "NRAL-KEY"}
+    assert dynamic_otlp_headers("newrelic", {"newrelic_region": "eu"}) is None
+
+
+def test_newrelic_dynamic_endpoint_resolves_from_fixed_table():
+    from litellm.integrations.otel.presets import dynamic_otlp_endpoint
+
+    assert dynamic_otlp_endpoint("newrelic", {"newrelic_region": "eu"}) == "https://otlp.eu01.nr-data.net"
+    assert dynamic_otlp_endpoint("newrelic", {"newrelic_region": "US"}) == "https://otlp.nr-data.net"
+    # A key-only team (no region) resolves to the fixed US default deterministically,
+    # never the operator's NEW_RELIC_REGION-configured preset endpoint.
+    assert dynamic_otlp_endpoint("newrelic", {"newrelic_api_key": "k"}) == "https://otlp.nr-data.net"
+    # An unknown region also resolves to the documented US default, not a guess.
+    assert dynamic_otlp_endpoint("newrelic", {"newrelic_region": "mars"}) == "https://otlp.nr-data.net"
+    # Callbacks without an endpoint resolver keep their preset endpoint.
+    assert dynamic_otlp_endpoint("arize", {"newrelic_region": "eu"}) is None
+
+
+def test_newrelic_endpoint_stamped_onto_owned_exporter_only():
+    cache = _cache(
+        "newrelic",
+        exporters=[
+            ExporterSpec(
+                kind="otlp_http",
+                endpoint="http://self-hosted-collector:4318",
+                headers="x=base-collector",
+                owner=None,
+            ),
+            ExporterSpec(
+                kind="otlp_http",
+                endpoint="https://otlp.nr-data.net",
+                owner="newrelic",
+                requires_headers=True,
+            ),
+        ],
+    )
+    new_cfg = cache._routed_config({"api-key": "TEAM-EU-KEY"}, {}, "https://otlp.eu01.nr-data.net")
+    by_owner = {e.owner: e for e in new_cfg.exporters}
+    assert by_owner["newrelic"].endpoint == "https://otlp.eu01.nr-data.net"
+    assert by_owner["newrelic"].headers == "api-key=TEAM-EU-KEY"
+    assert by_owner[None].endpoint == "http://self-hosted-collector:4318"
+    assert by_owner[None].headers == "x=base-collector"
+
+
+def test_newrelic_provider_cached_per_key_and_region():
+    cache = _cache(
+        "newrelic",
+        exporters=[ExporterSpec(kind="in_memory"), ExporterSpec(kind="otlp_http", owner="newrelic")],
+    )
+    default = NoOpTracer()
+    cache.route_for(default, {"newrelic_api_key": "K1", "newrelic_region": "us"})
+    cache.route_for(default, {"newrelic_api_key": "K1", "newrelic_region": "us"})
+    assert len(cache._providers) == 1
+    # Same key, different region → distinct provider (distinct endpoint).
+    cache.route_for(default, {"newrelic_api_key": "K1", "newrelic_region": "eu"})
+    assert len(cache._providers) == 2
+    cache.route_for(default, {"newrelic_api_key": "K2", "newrelic_region": "eu"})
+    assert len(cache._providers) == 3
+
+
+def test_requires_headers_spec_skipped_without_headers():
+    from litellm.integrations.otel.plumbing.providers import build_tracer_provider
+
+    cfg = OpenTelemetryV2Config(
+        exporters=[ExporterSpec(kind="otlp_http", endpoint="https://otlp.nr-data.net", requires_headers=True)]
+    )
+    provider = build_tracer_provider(cfg)
+    processors = provider._active_span_processor._span_processors
+    # Only the baggage processor: the keyless spec must not export (New Relic
+    # rejects unauthenticated posts with a 4xx per span batch).
+    assert [type(p).__name__ for p in processors] == ["LiteLLMBaggageSpanProcessor"]
+
+    keyed = OpenTelemetryV2Config(
+        exporters=[
+            ExporterSpec(
+                kind="otlp_http", endpoint="https://otlp.nr-data.net", headers="api-key=k", requires_headers=True
+            )
+        ]
+    )
+    keyed_provider = build_tracer_provider(keyed)
+    assert len(keyed_provider._active_span_processor._span_processors) == 2
+
+
+def test_newrelic_key_only_team_routes_to_us_not_operator_region(monkeypatch):
+    """A team that saves a key but no region must export to the fixed US default,
+    independent of the operator's NEW_RELIC_REGION, so its spans are never
+    silently dropped by an operator-configured region its key does not match."""
+    monkeypatch.setenv("NEW_RELIC_REGION", "eu")
+    cache = _cache(
+        "newrelic",
+        exporters=[ExporterSpec(kind="otlp_http", endpoint="https://otlp.eu01.nr-data.net", owner="newrelic")],
+    )
+    new_cfg = cache._routed_config(
+        {"api-key": "US-KEY"}, {}, dynamic_otlp_endpoint("newrelic", {"newrelic_api_key": "US-KEY"})
+    )
+    owned = next(e for e in new_cfg.exporters if e.owner == "newrelic")
+    assert owned.endpoint == "https://otlp.nr-data.net"
diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_logger.py b/tests/test_litellm/integrations/otel/test_otel_v2_logger.py
index e5d5b62b856..704a1d3a7bb 100644
--- a/tests/test_litellm/integrations/otel/test_otel_v2_logger.py
+++ b/tests/test_litellm/integrations/otel/test_otel_v2_logger.py
@@ -341,6 +341,35 @@ def test_idempotent_on_repeat_callback():
     assert len(exporter.get_finished_spans()) == 1
 
 
+def test_evicted_carrier_completed_call_emits_one_deferred_span():
+    """Eviction over the concurrency budget drops only the boundary carrier, not
+    the call. When an evicted call later closes as a real completed call
+    (``upstream_started``, payload present) it still emits exactly one span
+    through the deferred branch, and a second close for the same id dedups. Only
+    an evicted call that never closes goes unexported."""
+    logger, exporter = _logger()
+    kwargs = {**_kwargs(), "api_call_start_time": datetime(2026, 5, 26, 12, 0, 0, tzinfo=timezone.utc)}
+    logger.log_pre_api_call(model="gpt-4o", messages=[], kwargs=kwargs)
+    assert "call_1" in logger._open_llm_calls
+
+    # Evict exactly as ``_store_open_call`` does over budget: drop the oldest
+    # carrier and release its routed provider.
+    _, evicted = logger._open_llm_calls.popitem(last=False)
+    logger._release_carrier(evicted)
+    assert not logger._open_llm_calls
+    assert exporter.get_finished_spans() == ()  # the evicted boundary span is never exported
+
+    asyncio.run(logger.async_log_success_event(kwargs, None, None, None))
+    spans = exporter.get_finished_spans()
+    assert len(spans) == 1, "the evicted call's real close re-emits one deferred span, not zero"
+    assert spans[0].name == "chat gpt-4o"
+    assert spans[0].attributes[LiteLLM.CALL_ID] == "call_1"
+
+    # Success-then-failure on one logging object: the deferred branch dedups by id.
+    asyncio.run(logger.async_log_failure_event(kwargs, None, None, None))
+    assert len(exporter.get_finished_spans()) == 1, "second close for the same id must not duplicate"
+
+
 # --------------------------------------------------------------------------- #
 #  MCP tool-call spans
 # --------------------------------------------------------------------------- #
@@ -2522,3 +2551,149 @@ def test_deferred_pre_call_does_not_churn_tenant_cache(monkeypatch):
     server.end()
     headers_b = next(h for h in captured if "proj-b" in h)
     assert [s.name for s in captured[headers_b].get_finished_spans()] == ["chat gpt-4o"]
+
+
+# --- New Relic team-scoped deferred emit + dedup (no pre_call carrier) --- #
+
+
+def test_no_span_when_request_never_reached_upstream():
+    """A request rejected before the upstream call — at the auth/budget gate, or
+    blocked by a pre-call guardrail — carries the ``no upstream call`` marker
+    (stamped in ``proxy/utils.py`` before its handlers fire), so the failure log
+    produces no phantom CLIENT span even though a payload exists."""
+    from litellm.constants import LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL
+
+    logger, exporter = _logger()
+    payload = _payload(
+        status="failure",
+        error_information={"error_class": "ProxyException", "error_code": "401"},
+    )
+    kwargs = _kwargs(payload=payload)
+    kwargs[LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL] = True
+    # No log_pre_api_call: the call never started.
+    asyncio.run(logger.async_log_failure_event(kwargs, None, None, None))
+    assert exporter.get_finished_spans() == ()  # no phantom LLM span
+
+
+def test_success_without_pre_call_emits_deferred_span():
+    """A team/key-scoped logger is registered as a success callback only, so
+    ``pre_call`` never reaches it and no carrier exists. A completed call (it has
+    its payload, no ``no upstream call`` marker) must still get its span — the
+    deferred branch — or team-scoped destinations receive nothing at all."""
+    logger, exporter = _logger()
+    # No log_pre_api_call: this logger never receives the input hook. The
+    # request-level provider-handoff stamp is present (pre_call ran globally).
+    asyncio.run(
+        logger.async_log_success_event({**_kwargs(), "api_call_start_time": 100.0}, None, 100.0, 101.5)
+    )
+    spans = exporter.get_finished_spans()
+    assert len(spans) == 1
+    assert spans[0].attributes.get("gen_ai.operation.name")
+    # Start time comes from the callback's start_time, not a bogus zero.
+    assert spans[0].start_time == 100_000_000_000
+    assert spans[0].end_time == 101_500_000_000
+
+
+def test_no_carrier_and_no_payload_is_noop():
+    logger, exporter = _logger()
+    asyncio.run(
+        logger.async_log_success_event({"litellm_params": {}}, None, None, None)
+    )
+    assert exporter.get_finished_spans() == ()
+
+
+def test_second_close_for_same_call_does_not_duplicate_span():
+    """Success and failure can both fire on one logging object for the same call
+    id. The first close pops the carrier and finishes the boundary span; the
+    second must dedup against it, not fabricate a duplicate through the
+    deferred branch."""
+    logger, exporter = _logger()
+    kwargs = {**_kwargs(), "api_call_start_time": 100.0}
+    # Boundary open: the span is born at pre_call under a live server span and
+    # closed via finish_span, which never passes through emit()'s dedup.
+    server = logger._emitter.start_span(SpanRole.PROXY_REQUEST, LITELLM_PROXY_REQUEST_SPAN_NAME)
+    _emit_llm(logger, kwargs, ambient=server)
+    server.end()
+    llm_before = [s for s in exporter.get_finished_spans() if s.name.startswith("chat")]
+    assert len(llm_before) == 1
+    # Second close: carrier already popped, payload still present, handoff stamped.
+    asyncio.run(logger.async_log_failure_event(kwargs, None, None, None))
+    llm_after = [s for s in exporter.get_finished_spans() if s.name.startswith("chat")]
+    assert len(llm_after) == 1
+
+
+def test_failure_without_pre_call_emits_deferred_error_span():
+    """A team-scoped logger registered as a failure callback only still gets an
+    ERROR span for a real provider failure (payload present, no marker)."""
+    from opentelemetry.trace import StatusCode
+
+    logger, exporter = _logger()
+    payload = _payload(
+        status="failure",
+        error_information={"error_class": "RateLimitError", "error_code": "429"},
+    )
+    asyncio.run(
+        logger.async_log_failure_event(
+            {**_kwargs(payload=payload), "api_call_start_time": 100.0}, None, None, None
+        )
+    )
+    spans = exporter.get_finished_spans()
+    assert len(spans) == 1
+    assert spans[0].status.status_code == StatusCode.ERROR
+
+
+def test_boundary_open_with_no_payload_ends_provisional_span():
+    """Opened at pre_call but the payload never materialized: the boundary span
+    is ended provisionally (no payload attributes) rather than leaked open."""
+    logger, exporter = _logger()
+    kwargs = _kwargs()
+    server = logger._emitter.start_span(SpanRole.PROXY_REQUEST, LITELLM_PROXY_REQUEST_SPAN_NAME)
+    with trace.use_span(server, end_on_exit=False):
+        logger.log_pre_api_call(model="gpt-4o", messages=[], kwargs=kwargs)
+    asyncio.run(
+        logger.async_log_success_event(
+            {**kwargs, "standard_logging_object": None, "litellm_call_id": "call_1"}, None, None, None
+        )
+    )
+    server.end()
+    llm_spans = [s for s in exporter.get_finished_spans() if s.name.startswith("chat")]
+    assert len(llm_spans) == 1
+    assert "gen_ai.usage.input_tokens" not in llm_spans[0].attributes
+
+
+def test_failure_before_provider_handoff_emits_nothing():
+    """A failure event whose request never handed off to a provider (router
+    pre-call rejection, SDK error before the call, standalone guardrail run)
+    has a payload but no ``api_call_start_time``; without a carrier it must not
+    fabricate an LLM-call span."""
+    logger, exporter = _logger()
+    payload = _payload(
+        status="failure",
+        error_information={"error_class": "RateLimitError", "error_code": "429"},
+    )
+    asyncio.run(logger.async_log_failure_event(_kwargs(payload=payload), None, None, None))
+    assert exporter.get_finished_spans() == ()
+
+
+def test_provisional_close_then_payload_close_does_not_duplicate():
+    """Streaming shape: the success close arrives with no assembled payload (the
+    boundary span is ended provisionally), then the failure close arrives with a
+    payload for the same call id. Exactly one exported span."""
+    logger, exporter = _logger()
+    kwargs = {**_kwargs(), "api_call_start_time": 100.0}
+    payload = kwargs["standard_logging_object"]
+    server = logger._emitter.start_span(SpanRole.PROXY_REQUEST, LITELLM_PROXY_REQUEST_SPAN_NAME)
+    with trace.use_span(server, end_on_exit=False):
+        logger.log_pre_api_call(model="gpt-4o", messages=[], kwargs=kwargs)
+    asyncio.run(
+        logger.async_log_success_event(
+            {**kwargs, "standard_logging_object": None, "litellm_call_id": payload["litellm_call_id"]},
+            None,
+            None,
+            None,
+        )
+    )
+    asyncio.run(logger.async_log_failure_event(kwargs, None, None, None))
+    server.end()
+    llm_spans = [s for s in exporter.get_finished_spans() if s.name.startswith("chat")]
+    assert len(llm_spans) == 1
diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_presets.py b/tests/test_litellm/integrations/otel/test_otel_v2_presets.py
index add2caf9a48..58cfc1ceb3f 100644
--- a/tests/test_litellm/integrations/otel/test_otel_v2_presets.py
+++ b/tests/test_litellm/integrations/otel/test_otel_v2_presets.py
@@ -160,3 +160,55 @@ def test_agentops_endpoint_points_at_live_host():
     # so a typo or stale domain can never ship again.
     assert _AGENTOPS_ENDPOINT == "https://otlp.agentops.ai/v1/traces"
     assert "agentops.cloud" not in _AGENTOPS_ENDPOINT
+
+
+def test_newrelic_preset_reads_env_license_key(monkeypatch):
+    monkeypatch.setenv("NEW_RELIC_LICENSE_KEY", "env-license-key")
+    from litellm.integrations.otel.model.config import ExporterOwner
+    from litellm.integrations.otel.presets.newrelic import newrelic_preset
+
+    cfg = newrelic_preset()
+    spec = next(e for e in cfg.exporters if e.owner == ExporterOwner.NEWRELIC)
+    assert spec.kind == "otlp_http"
+    assert spec.endpoint == "https://otlp.nr-data.net"
+    assert spec.headers == "api-key=env-license-key"
+    assert spec.requires_headers is True
+    assert "genai" in cfg.mapper_names
+
+
+def test_newrelic_preset_without_key_still_contributes_owned_spec(monkeypatch):
+    # The owned spec is the stamping target for per-team credentials, so it must
+    # exist even with no operator env key; requires_headers keeps the keyless
+    # copy from ever exporting.
+    monkeypatch.delenv("NEW_RELIC_LICENSE_KEY", raising=False)
+    from litellm.integrations.otel.model.config import ExporterOwner
+    from litellm.integrations.otel.presets.newrelic import newrelic_preset
+
+    cfg = newrelic_preset()
+    spec = next(e for e in cfg.exporters if e.owner == ExporterOwner.NEWRELIC)
+    assert spec.headers is None
+    assert spec.requires_headers is True
+
+
+def test_newrelic_preset_operator_region_and_content_knob(monkeypatch):
+    monkeypatch.setenv("NEW_RELIC_LICENSE_KEY", "env-license-key")
+    monkeypatch.setenv("NEW_RELIC_REGION", "EU")
+    monkeypatch.setenv("NEW_RELIC_AI_MONITORING_RECORD_CONTENT_ENABLED", "true")
+    from litellm.integrations.otel.model.config import ExporterOwner
+    from litellm.integrations.otel.presets.newrelic import newrelic_preset
+
+    cfg = newrelic_preset()
+    spec = next(e for e in cfg.exporters if e.owner == ExporterOwner.NEWRELIC)
+    assert spec.endpoint == "https://otlp.eu01.nr-data.net"
+    assert cfg.capture_span_content is True
+
+    monkeypatch.setenv("NEW_RELIC_AI_MONITORING_RECORD_CONTENT_ENABLED", "false")
+    assert newrelic_preset().capture_span_content is False
+
+
+def test_newrelic_preset_unset_content_knob_keeps_default(monkeypatch):
+    monkeypatch.delenv("NEW_RELIC_AI_MONITORING_RECORD_CONTENT_ENABLED", raising=False)
+    monkeypatch.delenv("OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT", raising=False)
+    from litellm.integrations.otel.presets.newrelic import newrelic_preset
+
+    assert newrelic_preset().capture_span_content is False
diff --git a/tests/test_litellm/litellm_core_utils/test_initialize_dynamic_callback_params.py b/tests/test_litellm/litellm_core_utils/test_initialize_dynamic_callback_params.py
index f9ddc47cc7c..9b2bd5e2585 100644
--- a/tests/test_litellm/litellm_core_utils/test_initialize_dynamic_callback_params.py
+++ b/tests/test_litellm/litellm_core_utils/test_initialize_dynamic_callback_params.py
@@ -187,3 +187,49 @@ def test_empty_kwargs_returns_empty_params():
 
     params = initialize_standard_callback_dynamic_params({})
     assert dict(params) == {}
+
+
+def test_newrelic_callback_params_are_not_extracted_from_request_kwargs():
+    kwargs = {
+        "newrelic_api_key": "caller-key",
+        "metadata": {"newrelic_api_key": "caller-key-2", "newrelic_region": "eu"},
+        "litellm_params": {"metadata": {"newrelic_region": "eu"}},
+    }
+
+    params = initialize_standard_callback_dynamic_params(kwargs)
+
+    assert params.get("newrelic_api_key") is None
+    assert params.get("newrelic_region") is None
+
+
+def test_newrelic_trusted_vars_overlay_reaches_standard_params():
+    from litellm.types.utils import TRUSTED_CALLBACK_VARS_FIELD
+
+    kwargs = {
+        # A caller-supplied copy must lose to the proxy-stamped trusted value.
+        "newrelic_api_key": "caller-key",
+        TRUSTED_CALLBACK_VARS_FIELD: {
+            "newrelic_api_key": "team-key",
+            "newrelic_region": "eu",
+            # Non-overlay trusted vars must not be copied by the overlay.
+            "langfuse_public_key": "pk-team",
+        },
+    }
+
+    params = initialize_standard_callback_dynamic_params(kwargs)
+
+    assert params.get("newrelic_api_key") == "team-key"
+    assert params.get("newrelic_region") == "eu"
+    assert params.get("langfuse_public_key") is None
+
+
+def test_trusted_vars_overlay_uses_shared_parser_semantics():
+    # The overlay rides get_trusted_callback_params, the same parser the
+    # datadog handler consumes, so values are str()-coerced identically.
+    from litellm.types.utils import TRUSTED_CALLBACK_VARS_FIELD
+
+    params = initialize_standard_callback_dynamic_params(
+        {TRUSTED_CALLBACK_VARS_FIELD: {"newrelic_api_key": 12345}}
+    )
+
+    assert params.get("newrelic_api_key") == "12345"
diff --git a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
index 873da28fc34..1c706be51fa 100644
--- a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
+++ b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
@@ -5200,3 +5200,81 @@ def test_prompt_hooks_skip_prompt_managers_when_no_prompt_id(logging_obj, tmp_pa
             )
         for hook in [cb for cb in litellm.callbacks if isinstance(cb, VectorStorePreCallHook)]:
             litellm.logging_callback_manager.remove_callback_from_list_by_object(litellm.callbacks, hook)
+def test_newrelic_dispatch_prefers_otel_v2_when_flag_on(monkeypatch):
+    """With LITELLM_OTEL_V2 on, the "newrelic" callback builds the OTel v2
+    logger (per-team credential routing); with the flag off (default) it keeps
+    the legacy agent-based logger, so existing deployments are untouched."""
+    from litellm.integrations.otel.logger import OpenTelemetryV2
+    from litellm.integrations.otel.model.config import is_otel_v2_enabled
+    from litellm.litellm_core_utils import litellm_logging as logging_module
+
+    logging_module._in_memory_loggers.clear()
+    monkeypatch.setenv("LITELLM_OTEL_V2", "true")
+    is_otel_v2_enabled.cache_clear()
+    try:
+        v2_logger = logging_module._init_custom_logger_compatible_class(
+            logging_integration="newrelic",
+            internal_usage_cache=None,
+            llm_router=None,
+            custom_logger_init_args={},
+        )
+        assert isinstance(v2_logger, OpenTelemetryV2)
+        assert v2_logger.callback_name == "newrelic"
+        # Same name resolves to the same instance, not a second logger.
+        again = logging_module._init_custom_logger_compatible_class(
+            logging_integration="newrelic",
+            internal_usage_cache=None,
+            llm_router=None,
+            custom_logger_init_args={},
+        )
+        assert again is v2_logger
+    finally:
+        logging_module._in_memory_loggers.clear()
+        monkeypatch.delenv("LITELLM_OTEL_V2", raising=False)
+        is_otel_v2_enabled.cache_clear()
+
+
+def test_newrelic_dispatch_keeps_legacy_agent_when_flag_off(monkeypatch):
+    from litellm.integrations.newrelic import NewRelicLogger
+    from litellm.integrations.otel.model.config import is_otel_v2_enabled
+    from litellm.litellm_core_utils import litellm_logging as logging_module
+
+    logging_module._in_memory_loggers.clear()
+    monkeypatch.delenv("LITELLM_OTEL_V2", raising=False)
+    is_otel_v2_enabled.cache_clear()
+    try:
+        legacy = logging_module._init_custom_logger_compatible_class(
+            logging_integration="newrelic",
+            internal_usage_cache=None,
+            llm_router=None,
+            custom_logger_init_args={},
+        )
+        assert isinstance(legacy, NewRelicLogger)
+    finally:
+        logging_module._in_memory_loggers.clear()
+        is_otel_v2_enabled.cache_clear()
+
+
+def test_get_custom_logger_compatible_class_finds_v2_newrelic(monkeypatch):
+    """Under LITELLM_OTEL_V2 the "newrelic" instance is an OpenTelemetryV2; the
+    cached-lookup must find it or hook resolution (post-call failure/success
+    hooks) silently skips the callback."""
+    from litellm.integrations.otel.model.config import is_otel_v2_enabled
+    from litellm.litellm_core_utils import litellm_logging as logging_module
+
+    logging_module._in_memory_loggers.clear()
+    monkeypatch.setenv("LITELLM_OTEL_V2", "true")
+    is_otel_v2_enabled.cache_clear()
+    try:
+        created = logging_module._init_custom_logger_compatible_class(
+            logging_integration="newrelic",
+            internal_usage_cache=None,
+            llm_router=None,
+            custom_logger_init_args={},
+        )
+        found = logging_module.get_custom_logger_compatible_class("newrelic")
+        assert found is created
+    finally:
+        logging_module._in_memory_loggers.clear()
+        monkeypatch.delenv("LITELLM_OTEL_V2", raising=False)
+        is_otel_v2_enabled.cache_clear()
diff --git a/tests/test_litellm/proxy/management_endpoints/test_callback_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_callback_management_endpoints.py
index b2a242bf8f2..272a8ffa972 100644
--- a/tests/test_litellm/proxy/management_endpoints/test_callback_management_endpoints.py
+++ b/tests/test_litellm/proxy/management_endpoints/test_callback_management_endpoints.py
@@ -264,3 +264,148 @@ class TestCallbackManagementEndpoints:
         assert galileo_config["displayName"] == "Galileo"
         assert "GALILEO_API_KEY" in galileo_config["dynamic_params"]
         assert "GALILEO_PROJECT_ID" in galileo_config["dynamic_params"]
+
+
+class TestNewRelicCallbackConfig:
+    def test_newrelic_entry_supports_team_logging_with_dynamic_params(self):
+        client = TestClient(app)
+        response = client.get("/callbacks/configs", headers={"Authorization": "Bearer sk-1234"})
+        assert response.status_code == 200
+        newrelic = next(
+            (config for config in response.json() if config.get("id") == "newrelic"),
+            None,
+        )
+        assert newrelic is not None
+        assert newrelic["supports_key_team_logging"] is True
+        params = newrelic["dynamic_params"]
+        assert params["newrelic_api_key"]["type"] == "password"
+        assert "newrelic_region" in params
+        # The operator-only agent env flag must not appear as a team-configurable
+        # field: it is not a StandardCallbackDynamicParams key and would be rejected.
+        assert "NEW_RELIC_AI_MONITORING_RECORD_CONTENT_ENABLED" not in params
+
+
+class TestNewRelicTeamCallbackValidation:
+    def _data(self, callback_vars):
+        from litellm.proxy._types import AddTeamCallback
+
+        return AddTeamCallback(callback_name="newrelic", callback_type="success", callback_vars=callback_vars)
+
+    def test_rejects_when_otel_v2_off(self, monkeypatch):
+        from fastapi import HTTPException
+
+        from litellm.integrations.otel.model.config import is_otel_v2_enabled
+        from litellm.proxy.management_endpoints.team_callback_endpoints import _validate_team_callback
+
+        monkeypatch.delenv("LITELLM_OTEL_V2", raising=False)
+        is_otel_v2_enabled.cache_clear()
+        try:
+            with pytest.raises(HTTPException) as exc:
+                _validate_team_callback(self._data({"newrelic_api_key": "k"}))
+            assert "LITELLM_OTEL_V2" in str(exc.value.detail)
+        finally:
+            is_otel_v2_enabled.cache_clear()
+
+    def test_rejects_unknown_region_and_region_without_key(self, monkeypatch):
+        from fastapi import HTTPException
+
+        from litellm.integrations.otel.model.config import is_otel_v2_enabled
+        from litellm.proxy.management_endpoints.team_callback_endpoints import _validate_team_callback
+
+        monkeypatch.setenv("LITELLM_OTEL_V2", "true")
+        is_otel_v2_enabled.cache_clear()
+        try:
+            with pytest.raises(HTTPException) as exc:
+                _validate_team_callback(self._data({"newrelic_api_key": "k", "newrelic_region": "mars"}))
+            assert "Unknown newrelic_region" in str(exc.value.detail)
+            with pytest.raises(HTTPException) as exc:
+                _validate_team_callback(self._data({"newrelic_region": "eu"}))
+            assert "requires newrelic_api_key" in str(exc.value.detail)
+            _validate_team_callback(self._data({"newrelic_api_key": "k", "newrelic_region": "EU"}))
+            # A JSON-null key is str()-coerced to "None" upstream; it must not
+            # slip past the region-requires-key guard.
+            with pytest.raises(HTTPException) as exc:
+                _validate_team_callback(self._data({"newrelic_api_key": None, "newrelic_region": "eu"}))
+            assert "requires newrelic_api_key" in str(exc.value.detail)
+        finally:
+            is_otel_v2_enabled.cache_clear()
+
+    def test_ignores_other_callbacks_and_bare_newrelic(self, monkeypatch):
+        from litellm.integrations.otel.model.config import is_otel_v2_enabled
+        from litellm.proxy._types import AddTeamCallback
+        from litellm.proxy.management_endpoints.team_callback_endpoints import _validate_team_callback
+
+        monkeypatch.delenv("LITELLM_OTEL_V2", raising=False)
+        is_otel_v2_enabled.cache_clear()
+        try:
+            assert _validate_team_callback(self._data({})) is None
+            assert (
+                _validate_team_callback(
+                    AddTeamCallback(
+                        callback_name="langfuse",
+                        callback_type="success",
+                        callback_vars={"langfuse_public_key": "pk", "langfuse_secret_key": "sk"},
+                    )
+                )
+                is None
+            )
+        finally:
+            is_otel_v2_enabled.cache_clear()
+
+
+class TestNewRelicKeyLoggingValidation:
+    """Key-level logging is written through key metadata, not /team/callback."""
+
+    def _metadata(self, callback_vars):
+        return {"logging": [{"callback_name": "newrelic", "callback_type": "success", "callback_vars": callback_vars}]}
+
+    def test_rejects_same_configs_as_team_endpoint(self, monkeypatch):
+        from fastapi import HTTPException
+
+        from litellm.integrations.otel.model.config import is_otel_v2_enabled
+        from litellm.proxy.management_endpoints.key_management_endpoints import (
+            raise_on_invalid_key_logging_config,
+        )
+
+        monkeypatch.delenv("LITELLM_OTEL_V2", raising=False)
+        is_otel_v2_enabled.cache_clear()
+        try:
+            with pytest.raises(HTTPException) as exc:
+                raise_on_invalid_key_logging_config(self._metadata({"newrelic_api_key": "k"}))
+            assert "LITELLM_OTEL_V2" in str(exc.value.detail)
+
+            monkeypatch.setenv("LITELLM_OTEL_V2", "true")
+            is_otel_v2_enabled.cache_clear()
+            with pytest.raises(HTTPException) as exc:
+                raise_on_invalid_key_logging_config(
+                    self._metadata({"newrelic_api_key": "k", "newrelic_region": "mars"})
+                )
+            assert "Unknown newrelic_region" in str(exc.value.detail)
+            with pytest.raises(HTTPException) as exc:
+                raise_on_invalid_key_logging_config(self._metadata({"newrelic_region": "eu"}))
+            assert "requires newrelic_api_key" in str(exc.value.detail)
+            raise_on_invalid_key_logging_config(self._metadata({"newrelic_api_key": "k", "newrelic_region": "EU"}))
+        finally:
+            is_otel_v2_enabled.cache_clear()
+
+    def test_ignores_metadata_without_newrelic_logging(self, monkeypatch):
+        from litellm.integrations.otel.model.config import is_otel_v2_enabled
+        from litellm.proxy.management_endpoints.key_management_endpoints import (
+            raise_on_invalid_key_logging_config,
+        )
+
+        monkeypatch.delenv("LITELLM_OTEL_V2", raising=False)
+        is_otel_v2_enabled.cache_clear()
+        try:
+            assert raise_on_invalid_key_logging_config(None) is None
+            assert raise_on_invalid_key_logging_config({"logging": "not-a-list"}) is None
+            assert raise_on_invalid_key_logging_config({"tags": ["a"]}) is None
+            assert raise_on_invalid_key_logging_config(self._metadata({})) is None
+            assert (
+                raise_on_invalid_key_logging_config(
+                    {"logging": [{"callback_name": "langfuse", "callback_vars": {"langfuse_public_key": "pk"}}]}
+                )
+                is None
+            )
+        finally:
+            is_otel_v2_enabled.cache_clear()
diff --git a/tests/test_litellm/proxy/test_litellm_pre_call_utils.py b/tests/test_litellm/proxy/test_litellm_pre_call_utils.py
index 81a97a70efa..50ef6f29ec2 100644
--- a/tests/test_litellm/proxy/test_litellm_pre_call_utils.py
+++ b/tests/test_litellm/proxy/test_litellm_pre_call_utils.py
@@ -7329,3 +7329,92 @@ def test_vertex_sends_exactly_one_authorization_header():
     vertex_request_headers.update(forwarded)
 
     assert _authorization_values(vertex_request_headers) == [GOOGLE_ACCESS_TOKEN]
+@pytest.mark.asyncio
+async def test_newrelic_team_callback_vars_reach_trusted_field():
+    """A key with a newrelic team callback stamps its vars into the proxy-owned
+    trusted field, and a caller-supplied newrelic_api_key in the body is
+    stripped rather than merged."""
+    key_with_newrelic_callback = UserAPIKeyAuth(
+        api_key="hashed-key",
+        metadata={
+            "logging": [
+                {
+                    "callback_name": "newrelic",
+                    "callback_type": "success",
+                    "callback_vars": {"newrelic_api_key": "team-nr-key", "newrelic_region": "eu"},
+                }
+            ]
+        },
+    )
+    data = {
+        "model": "gpt-3.5-turbo",
+        "messages": [{"role": "user", "content": "hello"}],
+        "newrelic_api_key": "attacker-key",
+    }
+
+    updated = await add_litellm_data_to_request(
+        data=data,
+        request=_callback_credential_request_mock(),
+        user_api_key_dict=key_with_newrelic_callback,
+        proxy_config=MagicMock(),
+        general_settings={},
+        version="test-version",
+    )
+
+    assert updated[TRUSTED_CALLBACK_VARS_FIELD] == {
+        "newrelic_api_key": "team-nr-key",
+        "newrelic_region": "eu",
+    }
+    assert updated["success_callback"] == ["newrelic"]
+
+    from litellm.litellm_core_utils.initialize_dynamic_callback_params import (
+        initialize_standard_callback_dynamic_params,
+    )
+
+    params = initialize_standard_callback_dynamic_params(updated)
+    assert params.get("newrelic_api_key") == "team-nr-key"
+    assert params.get("newrelic_region") == "eu"
+
+    from litellm.integrations.otel.presets import dynamic_otlp_endpoint, dynamic_otlp_headers
+
+    assert dynamic_otlp_headers("newrelic", params) == {"api-key": "team-nr-key"}
+    assert dynamic_otlp_endpoint("newrelic", params) == "https://otlp.eu01.nr-data.net"
+
+    from litellm.utils import get_non_default_completion_params
+
+    forwarded = get_non_default_completion_params(updated)
+    assert not any(param.startswith("newrelic_") for param in forwarded)
+    assert TRUSTED_CALLBACK_VARS_FIELD not in forwarded
+
+
+def test_newrelic_vars_scoped_to_newrelic_callback_entry():
+    """New Relic routing reads these vars from the trusted overlay with no
+    callback-name check, so a team that puts newrelic_* under a different
+    callback's vars must not have them enter the shared bag (and so never
+    exports to New Relic). Vars under a real newrelic entry are kept."""
+    from litellm.proxy._types import AddTeamCallback
+    from litellm.proxy.litellm_pre_call_utils import convert_key_logging_metadata_to_callback
+
+    smuggled = convert_key_logging_metadata_to_callback(
+        AddTeamCallback(
+            callback_name="langfuse",
+            callback_type="success",
+            callback_vars={
+                "langfuse_public_key": "pk",
+                "newrelic_api_key": "SMUGGLED",
+                "newrelic_region": "eu",
+            },
+        ),
+        None,
+    )
+    assert smuggled.callback_vars == {"langfuse_public_key": "pk"}
+
+    legit = convert_key_logging_metadata_to_callback(
+        AddTeamCallback(
+            callback_name="newrelic",
+            callback_type="success",
+            callback_vars={"newrelic_api_key": "REAL", "newrelic_region": "us"},
+        ),
+        None,
+    )
+    assert legit.callback_vars == {"newrelic_api_key": "REAL", "newrelic_region": "us"}
diff --git a/ui/litellm-dashboard/src/components/callback_info_helpers.tsx b/ui/litellm-dashboard/src/components/callback_info_helpers.tsx
index 7aa121dcca5..3906aa744f7 100644
--- a/ui/litellm-dashboard/src/components/callback_info_helpers.tsx
+++ b/ui/litellm-dashboard/src/components/callback_info_helpers.tsx
@@ -6,6 +6,7 @@ import galileoLogo from "../../public/assets/logos/galileo.ico";
 import lagoLogo from "../../public/assets/logos/lago.svg";
 import langfuseLogo from "../../public/assets/logos/langfuse.png";
 import langsmithLogo from "../../public/assets/logos/langsmith.png";
+import newrelicLogo from "../../public/assets/logos/newrelic.png";
 import openmeterLogo from "../../public/assets/logos/openmeter.png";
 import otelLogo from "../../public/assets/logos/otel.png";
 
@@ -77,6 +78,17 @@ export const CALLBACK_CONFIGS: CallbackConfig[] = [
     },
     description: "Datadog Logging Integration",
   },
+  {
+    id: "newrelic",
+    displayName: "New Relic",
+    logo: newrelicLogo.src,
+    supports_key_team_logging: true,
+    dynamic_params: {
+      newrelic_api_key: "password",
+      newrelic_region: "text",
+    },
+    description: "New Relic Logging Integration",
+  },
   {
     id: "lago",
     displayName: "Lago",

From 0697188be40c0f5528b2ca18ec110fd95b55d9f8 Mon Sep 17 00:00:00 2001
From: milan <milan@berri.ai>
Date: Sun, 23 Aug 2026 03:14:19 +0000
Subject: [PATCH 73/93] refactor(a2a): use direct typed access in protocol
 binding normalization

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/a2a_protocol/card_resolver.py        | 8 +++-----
 tests/test_litellm/a2a_protocol/test_main.py | 1 +
 2 files changed, 4 insertions(+), 5 deletions(-)

diff --git a/litellm/a2a_protocol/card_resolver.py b/litellm/a2a_protocol/card_resolver.py
index 8070d88b761..47d6346b9a6 100644
--- a/litellm/a2a_protocol/card_resolver.py
+++ b/litellm/a2a_protocol/card_resolver.py
@@ -67,11 +67,9 @@ def normalize_agent_card_protocol_bindings(agent_card: "AgentCard") -> "AgentCar
     case-sensitively against its uppercase TransportProtocol constants and fails
     with "no compatible transports found." for spec-adjacent casings.
     """
-    interfaces: Final = getattr(agent_card, "supported_interfaces", None) or ()
-    for interface in interfaces:
-        binding: str = getattr(interface, "protocol_binding", "") or ""
-        canonical = _CANONICAL_PROTOCOL_BINDINGS.get(binding.lower())
-        if canonical is not None and binding != canonical:
+    for interface in agent_card.supported_interfaces:
+        canonical: str | None = _CANONICAL_PROTOCOL_BINDINGS.get(interface.protocol_binding.lower())
+        if canonical is not None and canonical != interface.protocol_binding:
             interface.protocol_binding = canonical
     return agent_card
 
diff --git a/tests/test_litellm/a2a_protocol/test_main.py b/tests/test_litellm/a2a_protocol/test_main.py
index 29aa3aaabd7..aa988bc5b99 100644
--- a/tests/test_litellm/a2a_protocol/test_main.py
+++ b/tests/test_litellm/a2a_protocol/test_main.py
@@ -344,6 +344,7 @@ async def test_lowercase_protocol_binding_in_agent_card_still_gets_a_client(isol
     response = await _send_message(a2a_client, _send_request("lc"))
 
     assert type(response.root.result).__name__ == "Message"
+    assert a2a_client._litellm_agent_card.supported_interfaces[0].protocol_binding == "JSONRPC"
 
 
 @pytest.mark.asyncio

From de0d8ceb25ea4cc3aa1df79b494ca95646a709f8 Mon Sep 17 00:00:00 2001
From: milan <milan@berri.ai>
Date: Sun, 23 Aug 2026 03:20:53 +0000
Subject: [PATCH 74/93] refactor(a2a): return a normalized card copy instead of
 mutating the resolved card

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/a2a_protocol/card_resolver.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/litellm/a2a_protocol/card_resolver.py b/litellm/a2a_protocol/card_resolver.py
index 47d6346b9a6..9b3e4ec13b9 100644
--- a/litellm/a2a_protocol/card_resolver.py
+++ b/litellm/a2a_protocol/card_resolver.py
@@ -67,11 +67,13 @@ def normalize_agent_card_protocol_bindings(agent_card: "AgentCard") -> "AgentCar
     case-sensitively against its uppercase TransportProtocol constants and fails
     with "no compatible transports found." for spec-adjacent casings.
     """
-    for interface in agent_card.supported_interfaces:
+    normalized: Final = type(agent_card)()
+    normalized.CopyFrom(agent_card)
+    for interface in normalized.supported_interfaces:
         canonical: str | None = _CANONICAL_PROTOCOL_BINDINGS.get(interface.protocol_binding.lower())
-        if canonical is not None and canonical != interface.protocol_binding:
+        if canonical is not None:
             interface.protocol_binding = canonical
-    return agent_card
+    return normalized
 
 
 def get_agent_card_url(agent_card: "AgentCard") -> str | None:

From 01595d2fbf232f49c45177c4c0f2108041966f28 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Sat, 22 Aug 2026 22:44:32 -0700
Subject: [PATCH 75/93] perf(ci): cache uv dependencies in the lint job
 (#37783)

The lint job installs its dependencies from scratch on every run. That step
measures 2.8 minutes of a job whose p50 is 9.5, and lint is the slowest
required check on 9 of the last 10 merged staging PRs, so it sets the
critical path for the whole PR.

_test-unit-base.yml already caches ~/.cache/uv and .venv keyed on uv.lock.
This mirrors that block. The key carries its own `lint` namespace rather
than sharing the unit tier's: the two jobs sync different group sets
(proxy-dev + e2e-dev here, ci + proxy-dev + four extras there), so a shared
.venv entry would be pruned and rebuilt on alternating runs.
---
 .github/workflows/test-linting.yml | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/.github/workflows/test-linting.yml b/.github/workflows/test-linting.yml
index ccb58f5cc9c..9f1283da19e 100644
--- a/.github/workflows/test-linting.yml
+++ b/.github/workflows/test-linting.yml
@@ -67,6 +67,17 @@ jobs:
         with:
           version: "0.10.9"
 
+      - name: Cache uv dependencies
+        if: steps.changes.outputs.decision != 'skip'
+        uses: actions/cache@0057852bfaa89a56745cba8c7296529d2fc39830 # v4.3.0
+        with:
+          path: |
+            ~/.cache/uv
+            .venv
+          key: ${{ runner.os }}-uv-lint-${{ hashFiles('uv.lock') }}
+          restore-keys: |
+            ${{ runner.os }}-uv-lint-
+
       - name: Clean Python cache
         if: steps.changes.outputs.decision != 'skip'
         run: |

From 6e23288b47ecd89b658e6c5188f090dcf886a227 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Sat, 22 Aug 2026 22:44:58 -0700
Subject: [PATCH 76/93] perf(ci): fan the budget checkers out across cores
 (#37784)

* perf(ci): fan the budget checkers out across cores

check_type_discipline.py and check_test_quality.py each walk a few thousand
files and parse every one, single-threaded. In the lint job those two steps
measure 2.3 and 1.6 minutes, second and third behind dependency install, and
lint is the slowest required check on 9 of the last 10 merged staging PRs.

check_file is already pure per-file work, so the walk fans out over a process
pool with no change to what either rule reports. Callers sort, which is what
keeps output order stable when results land out of order. Runs below
PARALLEL_MIN_PATHS stay serial rather than pay for process startup, and the
worker count is capped so a large runner does not oversubscribe.

Measured locally over the same trees, output byte-identical both times:
type-discipline 17.8s -> 3.0s over litellm/ (78,768 report lines), test-quality
14.4s -> 2.3s over tests/ (6,321 report lines), per-rule counts unchanged.

* test(ci): type the fan-out helpers and skip the comparison on one core
---
 scripts/check_test_quality.py                 | 27 +++++++-
 scripts/check_type_discipline.py              | 27 +++++++-
 tests/test_litellm/test_check_test_quality.py | 62 +++++++++++++++++++
 .../test_check_type_discipline.py             | 62 +++++++++++++++++++
 4 files changed, 176 insertions(+), 2 deletions(-)

diff --git a/scripts/check_test_quality.py b/scripts/check_test_quality.py
index e3ffbac9808..6964aed56e4 100644
--- a/scripts/check_test_quality.py
+++ b/scripts/check_test_quality.py
@@ -102,11 +102,13 @@ from __future__ import annotations
 
 import ast
 import io
+import os
 import re
 import sys
 import tokenize
 from collections.abc import Iterable, Iterator, Mapping, Sequence
 from dataclasses import dataclass
+from multiprocessing import Pool
 from pathlib import Path
 from types import MappingProxyType
 from typing import Final, NamedTuple
@@ -692,13 +694,36 @@ def collect_paths(raw: Iterable[str]) -> Iterator[Path]:
             yield candidate
 
 
+PARALLEL_MIN_PATHS = 200
+MAX_WORKERS = 8
+
+
+def _worker_count(path_count: int) -> int:
+    """1 when the run is too small to repay process startup, else one worker per
+    core up to MAX_WORKERS."""
+    if path_count < PARALLEL_MIN_PATHS:
+        return 1
+    return max(1, min(os.cpu_count() or 1, MAX_WORKERS))
+
+
+def scan_paths(paths: Sequence[Path]) -> tuple[Violation, ...]:
+    """check_file over every path. Pure per-file work, so it fans out across
+    processes; callers sort, which is what keeps output order stable."""
+    workers = _worker_count(len(paths))
+    if workers == 1:
+        return tuple(v for path in paths for v in check_file(path))
+    with Pool(workers) as pool:
+        return tuple(v for found in pool.imap_unordered(check_file, paths, chunksize=32) for v in found)
+
+
 def main(argv: Sequence[str]) -> int:
     paths: Final = tuple(a for a in argv if not a.startswith("-"))
     if not paths:
         print("usage: check_test_quality.py <files-or-dirs>...", file=sys.stderr)
         return 2
 
-    violations: Final = sorted(v for path in collect_paths(paths) for v in check_file(path))
+    targets: Final = tuple(collect_paths(paths))
+    violations: Final = sorted(scan_paths(targets))
     for violation in violations:
         print(violation.render())
 
diff --git a/scripts/check_type_discipline.py b/scripts/check_type_discipline.py
index 0706c8a7bd8..a2ab4760c4f 100644
--- a/scripts/check_type_discipline.py
+++ b/scripts/check_type_discipline.py
@@ -114,10 +114,12 @@ from __future__ import annotations
  
 import ast
 import io
+import os
 import re
 import sys
 import tokenize
 from dataclasses import dataclass
+from multiprocessing import Pool
 from pathlib import Path
 from collections.abc import Iterable, Iterator, Mapping, Sequence
 from typing import NamedTuple
@@ -1070,13 +1072,36 @@ def collect_paths(raw: Iterable[str]) -> Iterator[Path]:
             yield p
  
  
+PARALLEL_MIN_PATHS = 200
+MAX_WORKERS = 8
+
+
+def _worker_count(path_count: int) -> int:
+    """1 when the run is too small to repay process startup, else one worker per
+    core up to MAX_WORKERS."""
+    if path_count < PARALLEL_MIN_PATHS:
+        return 1
+    return max(1, min(os.cpu_count() or 1, MAX_WORKERS))
+
+
+def scan_paths(paths: Sequence[Path]) -> tuple[Violation, ...]:
+    """check_file over every path. Pure per-file work, so it fans out across
+    processes; callers sort, which is what keeps output order stable."""
+    workers = _worker_count(len(paths))
+    if workers == 1:
+        return tuple(v for path in paths for v in check_file(path))
+    with Pool(workers) as pool:
+        return tuple(v for found in pool.imap_unordered(check_file, paths, chunksize=32) for v in found)
+
+
 def main(argv: Sequence[str]) -> int:
     paths = tuple(a for a in argv if not a.startswith("-"))
     if not paths:
         print("usage: check_type_discipline.py <files-or-dirs>...", file=sys.stderr)
         return 2
  
-    violations = sorted(v for path in collect_paths(paths) for v in check_file(path))
+    targets = tuple(collect_paths(paths))
+    violations = sorted(scan_paths(targets))
     for v in violations:
         print(v.render())
  
diff --git a/tests/test_litellm/test_check_test_quality.py b/tests/test_litellm/test_check_test_quality.py
index 4fea5761cc8..7d59e5a5dba 100644
--- a/tests/test_litellm/test_check_test_quality.py
+++ b/tests/test_litellm/test_check_test_quality.py
@@ -8,9 +8,13 @@ in the test body.
 """
 
 import importlib.util
+import os
+import subprocess
 import sys
 from pathlib import Path
 
+import pytest
+
 _REPO_ROOT = Path(__file__).resolve().parents[2]
 _MODULE_PATH = _REPO_ROOT / "scripts" / "check_test_quality.py"
 _spec = importlib.util.spec_from_file_location("check_test_quality", _MODULE_PATH)
@@ -548,3 +552,61 @@ def test_the_read_may_sit_a_statement_above_the_store(tmp_path):
 def test_a_loop_storing_under_a_key_that_is_not_the_loop_variable_is_not_an_inventory(tmp_path):
     source = _HELPER_DICT_CONFTEST.replace("state[attr] =", 'state["fixed"] =')
     assert [v.code for v in checker.check_file(_written(tmp_path, source))] == []
+
+
+_FANS_OUT = checker._worker_count(checker.PARALLEL_MIN_PATHS) > 1
+_SERIAL_ONLY = "one usable core, so scan_paths stays serial and there is no fan-out to compare"
+
+
+def _corpus(tmp_path: Path, count: int) -> tuple[Path, ...]:
+    for index in range(count):
+        (tmp_path / f"test_gen_{index}.py").write_text(
+            f"def test_flagged_{index}():\n    compute()\n\n\ndef test_clean_{index}():\n    assert compute() == {index}\n",
+            encoding="utf-8",
+        )
+    return tuple(sorted(tmp_path.rglob("*.py")))
+
+
+def _run_checker(target: Path) -> list[str]:
+    completed = subprocess.run(
+        [sys.executable, str(_MODULE_PATH), str(target)],
+        capture_output=True, text=True, timeout=300,
+    )
+    return completed.stdout.splitlines()
+
+
+def test_worker_count_stays_serial_below_the_threshold():
+    assert checker._worker_count(checker.PARALLEL_MIN_PATHS - 1) == 1
+
+
+def test_worker_count_fans_out_at_the_threshold():
+    assert checker._worker_count(checker.PARALLEL_MIN_PATHS) == max(
+        1, min(os.cpu_count() or 1, checker.MAX_WORKERS)
+    )
+
+
+def test_worker_count_never_exceeds_the_cap():
+    assert checker._worker_count(100_000) <= checker.MAX_WORKERS
+
+
+def test_scan_paths_below_the_threshold_returns_every_violation(tmp_path):
+    paths = _corpus(tmp_path, 3)
+    assert checker._worker_count(len(paths)) == 1
+    assert [v.code for v in checker.scan_paths(paths)] == ["TQ001"] * 3
+
+
+@pytest.mark.skipif(not _FANS_OUT, reason=_SERIAL_ONLY)
+def test_a_fanned_out_run_reports_exactly_what_a_serial_run_reports(tmp_path):
+    paths = _corpus(tmp_path, checker.PARALLEL_MIN_PATHS + 5)
+    serial = [v.render() for v in sorted(v for path in paths for v in checker.check_file(path))]
+    assert serial, "corpus must produce violations or the comparison proves nothing"
+    assert _run_checker(tmp_path) == serial
+
+
+@pytest.mark.skipif(not _FANS_OUT, reason=_SERIAL_ONLY)
+def test_a_fanned_out_run_reports_each_generated_file_exactly_once(tmp_path):
+    paths = _corpus(tmp_path, checker.PARALLEL_MIN_PATHS + 5)
+    reported = _run_checker(tmp_path)
+    assert len(reported) == len(paths)
+    assert len({line.split(":")[0] for line in reported}) == len(paths)
+    assert all(" TQ001 " in line for line in reported)
diff --git a/tests/test_litellm/test_check_type_discipline.py b/tests/test_litellm/test_check_type_discipline.py
index 84dd547ad80..2d49332e687 100644
--- a/tests/test_litellm/test_check_type_discipline.py
+++ b/tests/test_litellm/test_check_type_discipline.py
@@ -8,10 +8,14 @@ a test fail. The comment-scanner cases are the regression for the readline path:
 
 import importlib.util
 import json
+import os
 import re
+import subprocess
 import sys
 from pathlib import Path
 
+import pytest
+
 _REPO_ROOT = Path(__file__).resolve().parents[2]
 _MODULE_PATH = _REPO_ROOT / "scripts" / "check_type_discipline.py"
 _spec = importlib.util.spec_from_file_location("check_type_discipline", _MODULE_PATH)
@@ -695,3 +699,61 @@ def test_budget_covers_exactly_the_checker_rules():
     for spec in budget.values():
         assert isinstance(spec["limit"], int)
         assert spec["limit"] >= 0
+
+
+_FANS_OUT = checker._worker_count(checker.PARALLEL_MIN_PATHS) > 1
+_SERIAL_ONLY = "one usable core, so scan_paths stays serial and there is no fan-out to compare"
+
+
+def _corpus(tmp_path: Path, count: int) -> tuple[Path, ...]:
+    for index in range(count):
+        (tmp_path / f"mod_{index}.py").write_text(
+            f"def build_{index}(items: list[int]) -> None:\n    return None\n",
+            encoding="utf-8",
+        )
+    return tuple(sorted(tmp_path.rglob("*.py")))
+
+
+def _run_checker(target: Path) -> list[str]:
+    completed = subprocess.run(
+        [sys.executable, str(_MODULE_PATH), str(target)],
+        capture_output=True, text=True, timeout=300,
+    )
+    return completed.stdout.splitlines()
+
+
+def test_worker_count_stays_serial_below_the_threshold():
+    assert checker._worker_count(checker.PARALLEL_MIN_PATHS - 1) == 1
+
+
+def test_worker_count_fans_out_at_the_threshold():
+    assert checker._worker_count(checker.PARALLEL_MIN_PATHS) == max(
+        1, min(os.cpu_count() or 1, checker.MAX_WORKERS)
+    )
+
+
+def test_worker_count_never_exceeds_the_cap():
+    assert checker._worker_count(100_000) <= checker.MAX_WORKERS
+
+
+def test_scan_paths_below_the_threshold_returns_every_violation(tmp_path):
+    paths = _corpus(tmp_path, 3)
+    assert checker._worker_count(len(paths)) == 1
+    found = checker.scan_paths(paths)
+    assert found and len({v.path for v in found}) == 3
+
+
+@pytest.mark.skipif(not _FANS_OUT, reason=_SERIAL_ONLY)
+def test_a_fanned_out_run_reports_exactly_what_a_serial_run_reports(tmp_path):
+    paths = _corpus(tmp_path, checker.PARALLEL_MIN_PATHS + 5)
+    serial = [v.render() for v in sorted(v for path in paths for v in checker.check_file(path))]
+    assert serial, "corpus must produce violations or the comparison proves nothing"
+    assert _run_checker(tmp_path) == serial
+
+
+@pytest.mark.skipif(not _FANS_OUT, reason=_SERIAL_ONLY)
+def test_a_fanned_out_run_reports_each_generated_file_exactly_once(tmp_path):
+    paths = _corpus(tmp_path, checker.PARALLEL_MIN_PATHS + 5)
+    reported = _run_checker(tmp_path)
+    assert reported
+    assert len({line.split(":")[0] for line in reported}) == len(paths)

From 346c69386026c245df93a3ef284e4c525df69640 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Sat, 22 Aug 2026 22:45:30 -0700
Subject: [PATCH 77/93] ci: port the Postgres suites off CircleCI onto service
 containers (#37785)

* ci: port the Postgres suites off CircleCI onto service containers

proxy_behavior_tests, proxy_security_tests and schema_migration_check were
near-identical CircleCI jobs: a Postgres sidecar, a schema seed, and one pytest
tree each. They ran nowhere else, and CircleCI holds none of the branch
ruleset's required checks, so the signal they produced gated nothing.

test-postgres.yml runs the same three trees on a Postgres service container as
one matrix, keeping each suite's own seeding rather than normalising it: the
behavior and security trees keep `prisma db push`, and the migration tree keeps
an empty database, which is what it needs to apply every committed migration
itself.

Their CircleCI definitions and workflow entries go with them, taking the config
from 47 jobs to 44. assert_ci_coverage.py stays green: dropping the new
workflow fails the census on exactly these trees, so the coverage moved rather
than went missing.

auth_ui_unit_tests is deliberately left behind. Ported, two of its
tests fail because prepare_metadata_fields refuses enterprise-only keys without
LITELLM_LICENSE, which exists as a CircleCI project variable and has no
GitHub Actions secret. Creating that secret is a human action, so the job stays
on CircleCI until it exists rather than shipping a red shard or quietly
deselecting the two tests.

* chore(ci): drop the narrative header from test-postgres.yml
---
 .circleci/config.yml                | 126 ------------------------
 .github/workflows/test-postgres.yml | 145 ++++++++++++++++++++++++++++
 2 files changed, 145 insertions(+), 126 deletions(-)
 create mode 100644 .github/workflows/test-postgres.yml

diff --git a/.circleci/config.yml b/.circleci/config.yml
index 5e77729df29..2586485e79c 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -651,126 +651,6 @@ jobs:
             - auth_ui_unit_tests_coverage.xml
             - auth_ui_unit_tests_coverage
 
-  proxy_behavior_tests:
-    docker:
-      - *python312_image
-      - image: cimg/postgres:16.0@sha256:b125148bc76e8e8eee5eb3ad6020a3a14110a14e8192f1c645128afebe2e2f84
-        environment:
-          POSTGRES_USER: postgres
-          POSTGRES_PASSWORD: postgres
-          POSTGRES_DB: litellm_test
-    working_directory: ~/project
-    environment:
-      DATABASE_URL: "postgresql://postgres:postgres@localhost:5432/litellm_test"
-    steps:
-      - checkout
-      - skip_if_unrelated_changes
-      - setup_google_dns
-      - install_uv
-      - install_rust
-      - run:
-          name: Install Dependencies
-          command: |
-            uv sync --frozen --all-groups --all-extras --python 3.12
-      - wait_for_service:
-          url: tcp://localhost:5432
-          timeout: "60"
-      - run:
-          name: Seed DB schema via prisma db push
-          command: |
-            uv run --no-sync prisma db push --schema litellm/proxy/schema.prisma --accept-data-loss
-      - run:
-          name: Generate Prisma Client
-          command: uv run --no-sync python -m prisma generate
-      - run:
-          name: Run proxy management behavior tests
-          command: |
-            mkdir -p test-results
-            uv run --no-sync python -m pytest tests/proxy_behavior \
-              -v --junitxml=test-results/junit.xml --durations=10
-          no_output_timeout: 15m
-      - store_test_results:
-          path: test-results
-
-  proxy_security_tests:
-    docker:
-      - *python312_image
-      - image: cimg/postgres:16.0@sha256:b125148bc76e8e8eee5eb3ad6020a3a14110a14e8192f1c645128afebe2e2f84
-        environment:
-          POSTGRES_USER: postgres
-          POSTGRES_PASSWORD: postgres
-          POSTGRES_DB: litellm_test
-    working_directory: ~/project
-    environment:
-      DATABASE_URL: "postgresql://postgres:postgres@localhost:5432/litellm_test"
-    steps:
-      - checkout
-      - skip_if_unrelated_changes
-      - setup_google_dns
-      - install_uv
-      - install_rust
-      - run:
-          name: Install Dependencies
-          command: |
-            uv sync --frozen --all-groups --all-extras --python 3.12
-      - wait_for_service:
-          url: tcp://localhost:5432
-          timeout: "60"
-      - run:
-          name: Seed DB schema via prisma db push
-          command: |
-            uv run --no-sync prisma db push --schema litellm/proxy/schema.prisma --accept-data-loss
-      - run:
-          name: Generate Prisma Client
-          command: uv run --no-sync python -m prisma generate
-      - run:
-          name: Run proxy security tests
-          command: |
-            mkdir -p test-results
-            uv run --no-sync python -m pytest tests/proxy_security_tests \
-              -v --junitxml=test-results/junit.xml --durations=10
-          no_output_timeout: 15m
-      - store_test_results:
-          path: test-results
-
-  schema_migration_check:
-    docker:
-      - *python312_image
-      - image: cimg/postgres:16.0@sha256:b125148bc76e8e8eee5eb3ad6020a3a14110a14e8192f1c645128afebe2e2f84
-        environment:
-          POSTGRES_USER: postgres
-          POSTGRES_PASSWORD: postgres
-          POSTGRES_DB: litellm_test
-    working_directory: ~/project
-    environment:
-      # An empty database; the test applies every committed migration itself.
-      DATABASE_URL: "postgresql://postgres:postgres@localhost:5432/litellm_test"
-    steps:
-      - checkout
-      - skip_if_unrelated_changes
-      - setup_google_dns
-      - install_uv
-      - install_rust
-      - run:
-          name: Install Dependencies
-          command: |
-            uv sync --frozen --all-groups --all-extras --python 3.12
-      - wait_for_service:
-          url: tcp://localhost:5432
-          timeout: "60"
-      - run:
-          name: Generate Prisma Client
-          command: uv run --no-sync python -m prisma generate
-      - run:
-          name: Check schema.prisma is in sync with committed migrations
-          command: |
-            mkdir -p test-results
-            uv run --no-sync python -m pytest tests/proxy_migration_tests \
-              -v --junitxml=test-results/junit.xml --durations=10
-          no_output_timeout: 15m
-      - store_test_results:
-          path: test-results
-
   litellm_router_testing: # Runs all tests with the "router" keyword
     docker:
       - *python312_image
@@ -3105,12 +2985,6 @@ workflows:
           filters: *main_branches
       - auth_ui_unit_tests:
           filters: *main_branches
-      - proxy_behavior_tests:
-          filters: *main_branches
-      - proxy_security_tests:
-          filters: *main_branches
-      - schema_migration_check:
-          filters: *main_branches
       - build_docker_database_image:
           filters: *main_branches
       - e2e_ui_testing:
diff --git a/.github/workflows/test-postgres.yml b/.github/workflows/test-postgres.yml
new file mode 100644
index 00000000000..96c514dff7c
--- /dev/null
+++ b/.github/workflows/test-postgres.yml
@@ -0,0 +1,145 @@
+name: "Postgres Tests"
+
+on:
+  pull_request:
+    branches:
+      - main
+      - litellm_internal_staging
+      - litellm_oss_staging
+      - "litellm_**"
+  push:
+    branches:
+      - main
+      - litellm_internal_staging
+  workflow_dispatch:
+
+permissions:
+  contents: read
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
+
+jobs:
+  postgres:
+    name: ${{ matrix.shard }}
+    runs-on: ubuntu-latest
+    timeout-minutes: ${{ matrix.job-timeout-minutes }}
+    permissions:
+      contents: read
+
+    services:
+      postgres:
+        image: postgres:16@sha256:e17e86066e5ef83e0952a9347f5c792b7ece00972e2aa787a6986f471b3dd3d5
+        env:
+          POSTGRES_USER: postgres
+          POSTGRES_PASSWORD: postgres
+          POSTGRES_DB: litellm_test
+        ports:
+          - 5432:5432
+        options: >-
+          --health-cmd pg_isready
+          --health-interval 10s
+          --health-timeout 5s
+          --health-retries 10
+
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - shard: proxy-behavior
+            test-path: "tests/proxy_behavior"
+            seed: db-push
+            workers: 0
+            timeout-minutes: 25
+            job-timeout-minutes: 50
+
+          - shard: proxy-security
+            test-path: "tests/proxy_security_tests"
+            seed: db-push
+            workers: 0
+            timeout-minutes: 15
+            job-timeout-minutes: 40
+
+          - shard: schema-migration
+            test-path: "tests/proxy_migration_tests"
+            seed: none
+            workers: 0
+            timeout-minutes: 20
+            job-timeout-minutes: 45
+
+    env:
+      DATABASE_URL: "postgresql://postgres:postgres@localhost:5432/litellm_test"
+
+    steps:
+      - uses: actions/checkout@08eba0b27e820071cde6df949e0beb9ba4906955 # v4.3.0
+        timeout-minutes: 3
+        with:
+          persist-credentials: false
+
+      - name: Detect relevant changes
+        id: changes
+        timeout-minutes: 2
+        uses: ./.github/actions/detect-changes
+
+      - name: Set up Python
+        if: steps.changes.outputs.decision != 'skip'
+        timeout-minutes: 3
+        uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
+        with:
+          python-version: "3.12"
+
+      - name: Set up uv
+        if: steps.changes.outputs.decision != 'skip'
+        timeout-minutes: 3
+        uses: ./.github/actions/setup-uv-with-retries
+        with:
+          version: "0.10.9"
+
+      - name: Cache uv dependencies
+        if: steps.changes.outputs.decision != 'skip'
+        timeout-minutes: 5
+        uses: actions/cache@0057852bfaa89a56745cba8c7296529d2fc39830 # v4.3.0
+        with:
+          path: |
+            ~/.cache/uv
+            .venv
+          key: ${{ runner.os }}-uv-postgres-${{ hashFiles('uv.lock') }}
+          restore-keys: |
+            ${{ runner.os }}-uv-postgres-
+
+      - name: Install dependencies
+        if: steps.changes.outputs.decision != 'skip'
+        timeout-minutes: 12
+        run: |
+          .github/scripts/uv_sync_with_retries.sh --frozen --all-groups --all-extras
+
+      - name: Cache Prisma binaries
+        if: steps.changes.outputs.decision != 'skip'
+        timeout-minutes: 3
+        uses: ./.github/actions/cache-prisma-binaries
+
+      - name: Generate Prisma client
+        if: steps.changes.outputs.decision != 'skip'
+        timeout-minutes: 5
+        run: |
+          uv run --no-sync prisma generate --schema litellm/proxy/schema.prisma
+
+      - name: Seed database schema
+        if: steps.changes.outputs.decision != 'skip' && matrix.seed != 'none'
+        timeout-minutes: 10
+        run: |
+          uv run --no-sync prisma db push --schema litellm/proxy/schema.prisma --accept-data-loss
+
+      - name: Run tests
+        if: steps.changes.outputs.decision != 'skip'
+        timeout-minutes: ${{ matrix.timeout-minutes }}
+        env:
+          TEST_PATH: ${{ matrix.test-path }}
+          WORKERS: ${{ matrix.workers }}
+        run: |
+          if [ "${WORKERS}" = "0" ]; then
+            uv run --no-sync pytest ${TEST_PATH:?} -vv --tb=short --durations=10
+          else
+            uv run --no-sync pytest ${TEST_PATH:?} -vv --tb=short --durations=10 -n "${WORKERS}"
+          fi

From a734afca322959557694734e179b095f2e6f1039 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Sat, 22 Aug 2026 22:54:30 -0700
Subject: [PATCH 78/93] feat(ci): gate patching of SDK internals in tests as
 TQ008 (#37787)

* feat(ci): gate patching of SDK internals in tests as TQ008

TQ002 catches the narrowest symptom of the suite's dominant mocking idiom,
patch X then assert only that X was called. The idiom itself is wider: tests
reach for litellm's own functions instead of faking the wire, so they pin how
the code is wired rather than what it does, and a test that patches internals
but makes weak real assertions trips nothing today.

TQ008 counts patch targets rooted at `litellm`, both the dotted string form and
the attribute chain handed to patch.object, and ratchets like every other rule.
Mocking anything outside the SDK is untouched: respx, httpx transports and
third-party clients do not trip it, which is the point, since those are the
patterns this is meant to move the suite toward.

Seeded at 9,643, in line with the ~9.4k patch sites an independent grep found
in the mirror. The burn-down horizon is long; the value here is stopping the
flow rather than clearing the stock.

Five existing rule tests patched `litellm.completion` incidentally and now
report TQ008 alongside what they were pinning. Their expected values are
updated to the accurate pair rather than loosened, so they keep failing on a
regression in either rule.

* test: add TQ008 to the shipped-budget rule canary

* fix(ci): resolve imported SDK names in TQ008

patch.object(handler.OpenAIChatCompletion, ...) after a from-import reaches the
same internal as the dotted string form, but the rule only saw the bare local
name and let it through. Import bindings are now resolved to the path they
stand for, so the aliased, renamed and from-imported forms all read alike and
the reported target is the real one.

That is 1,496 patches the ratchet could not see, so the TQ008 limit moves from
9,643 to 11,139. Third-party names and locals with no SDK import behind them
stay unflagged.
---
 scripts/check_test_quality.py                 |  66 +++++++++
 test-quality-budget.json                      |   3 +
 tests/test_litellm/test_check_test_quality.py | 137 +++++++++++++++++-
 tests/test_litellm/test_test_quality_gate.py  |   2 +-
 4 files changed, 202 insertions(+), 6 deletions(-)

diff --git a/scripts/check_test_quality.py b/scripts/check_test_quality.py
index 6964aed56e4..41342acd23a 100644
--- a/scripts/check_test_quality.py
+++ b/scripts/check_test_quality.py
@@ -48,6 +48,10 @@ TQ006   A `pytest.skip` reached only when a credential-shaped environment variab
         deliberate branch. The gate follows one local or module-level binding, which is
         the `key = os.getenv(...)` then `if not key: pytest.skip(...)` shape most of
         these use.
+TQ008   A `patch(...)` whose target is a `litellm.` internal. Patching the SDK's own
+        functions pins the test to the current wiring instead of the behaviour, and it
+        is the idiom the suite reaches for instead of faking the HTTP boundary. Mocking
+        a third-party client, a transport, or anything outside `litellm.` is untouched.
 TQ007   A module global that a conftest saves before every test and restores after it.
         The save/restore list is a hand-maintained inventory of the leaks the suite
         already knows about, so it is allowed to shrink and never to grow: a new entry
@@ -469,6 +473,67 @@ def iter_global_mutation_violations(path: Path, tree: ast.Module) -> Iterator[Vi
                 )
 
 
+def _is_sdk_internal(dotted: str) -> bool:
+    return dotted == SDK_MODULE or dotted.startswith(f"{SDK_MODULE}.")
+
+
+def _sdk_import_bindings(tree: ast.Module) -> Iterator[tuple[str, str]]:
+    """(local name, dotted path) for every import that binds something under `litellm`."""
+    for node in ast.walk(tree):
+        if isinstance(node, ast.Import):
+            yield from (
+                (alias.asname, alias.name) if alias.asname else (root, root)
+                for alias in node.names
+                if _is_sdk_internal(alias.name)
+                for root in (alias.name.partition(".")[0],)
+            )
+        elif isinstance(node, ast.ImportFrom) and node.module and _is_sdk_internal(node.module):
+            yield from ((alias.asname or alias.name, f"{node.module}.{alias.name}") for alias in node.names)
+
+
+def _sdk_aliases(tree: ast.Module) -> Mapping[str, str]:
+    """Local names bound to something under `litellm`, mapped to the path they stand for.
+
+    `from litellm.llms.openai.chat import handler` then `patch.object(handler.X, ...)`
+    reaches the same internal as the dotted string form and has to read the same way.
+    """
+    return MappingProxyType({name: dotted for name, dotted in _sdk_import_bindings(tree)})
+
+
+def _resolved(dotted: str, aliases: Mapping[str, str]) -> str:
+    root, _, rest = dotted.partition(".")
+    base: Final = aliases.get(root, root)
+    return f"{base}.{rest}" if rest else base
+
+
+def _patch_targets(call: ast.Call, aliases: Mapping[str, str]) -> Iterator[str]:
+    """What a patch installer is replacing: the dotted string it names, or the
+    attribute chain handed to `patch.object` / `patch.dict`, resolved through the
+    module's imports so a locally bound SDK object reads as its full path."""
+    for first in call.args[:1]:
+        if isinstance(first, ast.Constant) and isinstance(first.value, str):
+            yield first.value
+        elif dotted := _dotted_name(first):
+            yield _resolved(dotted, aliases)
+
+
+def iter_internal_patch_violations(path: Path, tree: ast.Module) -> Iterator[Violation]:
+    aliases: Final = _sdk_aliases(tree)
+    for node in ast.walk(tree):
+        if not (isinstance(node, ast.Call) and _is_patch_installer(_dotted_name(node.func))):
+            continue
+        for target in _patch_targets(node, aliases):
+            if _is_sdk_internal(target):
+                yield Violation(
+                    path,
+                    node.lineno,
+                    "TQ008",
+                    f"patches `{target}`, an SDK internal, so the test is pinned to how the code is "
+                    "wired rather than what it does; fake the HTTP boundary (respx / MockTransport) "
+                    f"or inject the collaborator (suppress: `# {SUPPRESSION_TOKEN}: <reason>`)",
+                )
+
+
 def _environ_keys(node: ast.AST) -> Iterator[str]:
     for inner in ast.walk(node):
         if isinstance(inner, ast.Call) and _dotted_name(inner.func) in ENVIRON_READERS:
@@ -680,6 +745,7 @@ def check_file(path: Path) -> tuple[Violation, ...]:
             *iter_global_mutation_violations(path, tree),
             *iter_credential_skip_violations(path, tree),
             *iter_conftest_inventory_violations(path, tree),
+            *iter_internal_patch_violations(path, tree),
         )
         if violation.line not in skip
     )
diff --git a/test-quality-budget.json b/test-quality-budget.json
index 0dea4e8fe93..4a7bc7edff2 100644
--- a/test-quality-budget.json
+++ b/test-quality-budget.json
@@ -19,5 +19,8 @@
   },
   "TQ007": {
     "limit": 117
+  },
+  "TQ008": {
+    "limit": 11139
   }
 }
diff --git a/tests/test_litellm/test_check_test_quality.py b/tests/test_litellm/test_check_test_quality.py
index 7d59e5a5dba..a75b1e43fb7 100644
--- a/tests/test_litellm/test_check_test_quality.py
+++ b/tests/test_litellm/test_check_test_quality.py
@@ -187,7 +187,7 @@ def test_mock_echo_is_flagged(tmp_path):
         "        run()\n"
         "    mock_completion.assert_called_once()\n"
     )
-    assert _codes(tmp_path, source) == ["TQ002"]
+    assert _codes(tmp_path, source) == ["TQ002", "TQ008"]
 
 
 def test_call_args_inspection_is_mock_echo(tmp_path):
@@ -200,7 +200,7 @@ def test_call_args_inspection_is_mock_echo(tmp_path):
         "        run()\n"
         "    assert mock_completion.call_args[1]['model'] == 'gpt-4o'\n"
     )
-    assert _codes(tmp_path, source) == ["TQ002"]
+    assert _codes(tmp_path, source) == ["TQ002", "TQ008"]
 
 
 def test_patch_decorator_counts_as_installing_a_patch(tmp_path):
@@ -213,7 +213,7 @@ def test_patch_decorator_counts_as_installing_a_patch(tmp_path):
         "    run()\n"
         "    mock_completion.assert_called_once()\n"
     )
-    assert _codes(tmp_path, source) == ["TQ002"]
+    assert _codes(tmp_path, source) == ["TQ002", "TQ008"]
 
 
 def test_patching_but_asserting_the_output_is_not_mock_echo(tmp_path):
@@ -227,7 +227,7 @@ def test_patching_but_asserting_the_output_is_not_mock_echo(tmp_path):
         "    mock_completion.assert_called_once()\n"
         "    assert result.choices[0].message.content == 'pong'\n"
     )
-    assert _codes(tmp_path, source) == []
+    assert _codes(tmp_path, source) == ["TQ008"]
 
 
 def test_asserting_without_patching_is_not_mock_echo(tmp_path):
@@ -244,7 +244,7 @@ def test_a_test_with_no_assertions_is_tq001_not_tq002(tmp_path):
         "    with patch('litellm.completion'):\n"
         "        run()\n"
     )
-    assert _codes(tmp_path, source) == ["TQ001"]
+    assert _codes(tmp_path, source) == ["TQ001", "TQ008"]
 
 
 def test_sys_path_insert_is_flagged(tmp_path):
@@ -554,6 +554,133 @@ def test_a_loop_storing_under_a_key_that_is_not_the_loop_variable_is_not_an_inve
     assert [v.code for v in checker.check_file(_written(tmp_path, source))] == []
 
 
+def test_patching_an_sdk_function_by_string_is_flagged(tmp_path):
+    source = 'from unittest.mock import patch\n\n\n@patch("litellm.completion")\ndef test_x(m):\n    assert m\n'
+    assert "TQ008" in _codes(tmp_path, source)
+
+
+def test_patching_a_deep_sdk_path_is_flagged(tmp_path):
+    source = (
+        "from unittest.mock import patch\n\n\n"
+        "def test_x():\n"
+        '    with patch("litellm.llms.openai.chat.handler.OpenAIChatCompletion.completion"):\n'
+        "        assert True\n"
+    )
+    assert "TQ008" in _codes(tmp_path, source)
+
+
+def test_patch_object_rooted_at_the_sdk_is_flagged(tmp_path):
+    source = (
+        "import litellm\nfrom unittest.mock import patch\n\n\n"
+        "def test_x():\n"
+        '    with patch.object(litellm, "api_key", "x"):\n'
+        "        assert True\n"
+    )
+    assert "TQ008" in _codes(tmp_path, source)
+
+
+def test_patch_object_on_a_from_imported_sdk_module_is_flagged(tmp_path):
+    source = (
+        "from litellm.llms.openai.chat import handler\nfrom unittest.mock import patch\n\n\n"
+        "def test_x():\n"
+        '    with patch.object(handler.OpenAIChatCompletion, "completion"):\n'
+        "        assert True\n"
+    )
+    assert "TQ008" in _codes(tmp_path, source)
+
+
+def test_patch_object_on_an_aliased_sdk_module_is_flagged(tmp_path):
+    source = (
+        "import litellm.llms.openai.chat.handler as oai\nfrom unittest.mock import patch\n\n\n"
+        "def test_x():\n"
+        '    with patch.object(oai.OpenAIChatCompletion, "completion"):\n'
+        "        assert True\n"
+    )
+    assert "TQ008" in _codes(tmp_path, source)
+
+
+def test_patch_object_on_a_renamed_sdk_symbol_is_flagged(tmp_path):
+    source = (
+        "from litellm.utils import get_llm_provider as glp\nfrom unittest.mock import patch\n\n\n"
+        "def test_x():\n"
+        '    with patch.object(glp, "__wrapped__"):\n'
+        "        assert True\n"
+    )
+    assert "TQ008" in _codes(tmp_path, source)
+
+
+def test_the_reported_target_is_the_resolved_sdk_path(tmp_path):
+    source = (
+        "from litellm.llms.openai.chat import handler\nfrom unittest.mock import patch\n\n\n"
+        "def test_x():\n"
+        '    with patch.object(handler.OpenAIChatCompletion, "completion"):\n'
+        "        assert True\n"
+    )
+    reported = [v.message for v in checker.check_file(_written(tmp_path, source)) if v.code == "TQ008"]
+    assert reported
+    assert "litellm.llms.openai.chat.handler.OpenAIChatCompletion" in reported[0]
+
+
+def test_patch_object_on_a_from_imported_third_party_is_not_flagged(tmp_path):
+    source = (
+        "from openai import OpenAI\nfrom unittest.mock import patch\n\n\n"
+        "def test_x():\n"
+        '    with patch.object(OpenAI, "chat"):\n'
+        "        assert True\n"
+    )
+    assert "TQ008" not in _codes(tmp_path, source)
+
+
+def test_a_local_name_with_no_sdk_import_behind_it_is_not_flagged(tmp_path):
+    source = (
+        "from unittest.mock import patch\n\n\n"
+        "def test_x(handler):\n"
+        '    with patch.object(handler, "completion"):\n'
+        "        assert True\n"
+    )
+    assert "TQ008" not in _codes(tmp_path, source)
+
+
+def test_mocking_a_third_party_client_is_not_flagged(tmp_path):
+    source = (
+        "from unittest.mock import patch\n\n\n"
+        "def test_x():\n"
+        '    with patch("openai.OpenAI.chat"):\n'
+        "        assert True\n"
+    )
+    assert "TQ008" not in _codes(tmp_path, source)
+
+
+def test_mocking_the_http_transport_is_not_flagged(tmp_path):
+    source = (
+        "from unittest.mock import patch\n\n\n"
+        "def test_x():\n"
+        '    with patch("httpx.AsyncClient.send"):\n'
+        "        assert True\n"
+    )
+    assert "TQ008" not in _codes(tmp_path, source)
+
+
+def test_a_name_merely_starting_with_litellm_is_not_the_sdk(tmp_path):
+    source = (
+        "from unittest.mock import patch\n\n\n"
+        "def test_x():\n"
+        '    with patch("litellm_enterprise.thing.go"):\n'
+        "        assert True\n"
+    )
+    assert "TQ008" not in _codes(tmp_path, source)
+
+
+def test_an_sdk_patch_can_be_suppressed(tmp_path):
+    source = (
+        "from unittest.mock import patch\n\n\n"
+        "def test_x():\n"
+        '    with patch("litellm.completion"):  # test-quality-ok: pinning the router seam\n'
+        "        assert True\n"
+    )
+    assert "TQ008" not in _codes(tmp_path, source)
+
+
 _FANS_OUT = checker._worker_count(checker.PARALLEL_MIN_PATHS) > 1
 _SERIAL_ONLY = "one usable core, so scan_paths stays serial and there is no fan-out to compare"
 
diff --git a/tests/test_litellm/test_test_quality_gate.py b/tests/test_litellm/test_test_quality_gate.py
index 3bf4b89ac4e..8cce6bc735a 100644
--- a/tests/test_litellm/test_test_quality_gate.py
+++ b/tests/test_litellm/test_test_quality_gate.py
@@ -144,5 +144,5 @@ def test_the_shipped_budget_covers_every_rule_the_checker_can_emit():
     import json
 
     budget = json.loads((_REPO_ROOT / "test-quality-budget.json").read_text())
-    assert set(budget) == {"TQ001", "TQ002", "TQ003", "TQ004", "TQ005", "TQ006", "TQ007"}
+    assert set(budget) == {"TQ001", "TQ002", "TQ003", "TQ004", "TQ005", "TQ006", "TQ007", "TQ008"}
     assert all(spec["limit"] >= 0 for spec in budget.values())

From 6c30b4331d2d9b5571efcb0ff94fb731651d500d Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Sat, 22 Aug 2026 22:55:01 -0700
Subject: [PATCH 79/93] ci: measure enterprise/ coverage (#37788)

codecov.yaml has carried an `Enterprise` component scoped to `enterprise/**`
since it was written, and it has never received a line of data. Every one of
the 19 coverage invocations across the unit base, the MCP workflow and the
CircleCI config passes `--cov=./litellm` and nothing else, so 11,203 lines of
paid-customer code sat outside the measured universe while the reported number
described only the rest.

litellm-enterprise is a uv workspace member and a direct dependency, so every
job that syncs already has it installed and importable; only the measurement
was missing.

Measured on tests/test_litellm/enterprise, the shard that exercises this code:
0 enterprise files in the report before, 142 after, at `enterprise/...` paths
that match the component's existing glob. That shard alone puts enterprise at
30.8%, which nudged its own total from 24.09% to 24.20% rather than down. The
aggregate direction across every shard is not knowable until they all report,
and a drop there is the instrument working, not a regression.
---
 .circleci/config.yml                  | 32 +++++++++++++--------------
 .github/workflows/_test-unit-base.yml |  4 ++--
 .github/workflows/test-mcp.yml        |  2 +-
 3 files changed, 19 insertions(+), 19 deletions(-)

diff --git a/.circleci/config.yml b/.circleci/config.yml
index 2586485e79c..a261b7c78fc 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -430,7 +430,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv \
-                --cov=./litellm \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise \
                 --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=20 \
@@ -504,7 +504,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv \
-                --cov=./litellm \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise \
                 --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=20 \
@@ -631,7 +631,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -v -x \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=5 \
                 -n 2"
@@ -738,7 +738,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -v -x \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=5 \
                 -n 4"
@@ -865,7 +865,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=20 \
                 -n 4 \
@@ -910,7 +910,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv -x -s \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=5"
           no_output_timeout: 15m
@@ -954,7 +954,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=5 \
                 -n 2 \
@@ -1000,7 +1000,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv -x -s \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=5 \
                 --retries 3 --retry-delay 5"
@@ -1091,7 +1091,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv -x \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=5 \
                 -n 4"
@@ -1135,7 +1135,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv -x \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=5 \
                 -n 4"
@@ -1213,7 +1213,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv -x -s \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=5 \
                 -n 2"
@@ -1257,7 +1257,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv -x -s \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=5 \
                 -n 2"
@@ -1302,7 +1302,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv -x \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=5 \
                 -n 4"
@@ -1381,7 +1381,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 -n 4 \
                 --junitxml=test-results/junit.xml \
                 --durations=5 \
@@ -1426,7 +1426,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv -x -s \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=5"
           no_output_timeout: 15m
@@ -1479,7 +1479,7 @@ jobs:
               --verbose \
               --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
                 -vv -x -s \
-                --cov=./litellm --cov-report=xml \
+                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
                 --junitxml=test-results/junit.xml \
                 --durations=5 -n 2 \
                 --reruns 2 --reruns-delay 1"
diff --git a/.github/workflows/_test-unit-base.yml b/.github/workflows/_test-unit-base.yml
index b7d185bd0b9..c4045a08ffb 100644
--- a/.github/workflows/_test-unit-base.yml
+++ b/.github/workflows/_test-unit-base.yml
@@ -149,7 +149,7 @@ jobs:
               --reruns "${RERUNS}" \
               --reruns-delay 1 \
               --durations=20 \
-              --cov=./litellm \
+              --cov=./litellm --cov=./enterprise/litellm_enterprise \
               --cov-report=xml:coverage.xml \
               --cov-config=pyproject.toml
           else
@@ -161,7 +161,7 @@ jobs:
               --reruns-delay 1 \
               --dist="${DIST}" \
               --durations=20 \
-              --cov=./litellm \
+              --cov=./litellm --cov=./enterprise/litellm_enterprise \
               --cov-report=xml:coverage.xml \
               --cov-config=pyproject.toml
           fi
diff --git a/.github/workflows/test-mcp.yml b/.github/workflows/test-mcp.yml
index 6ea814dc2de..93ffcbe0586 100644
--- a/.github/workflows/test-mcp.yml
+++ b/.github/workflows/test-mcp.yml
@@ -60,4 +60,4 @@ jobs:
       - name: Run MCP tests
         if: steps.changes.outputs.decision != 'skip'
         run: |
-          uv run --no-sync pytest tests/mcp_tests -x -vv -n 4 --cov=./litellm --cov-report=xml --durations=5
+          uv run --no-sync pytest tests/mcp_tests -x -vv -n 4 --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml --durations=5

From b31484ed196d310878dfa3b1b90571d77d4f7f76 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Sat, 22 Aug 2026 22:56:43 -0700
Subject: [PATCH 80/93] ci: run the keyless caching tests that ran in no job
 (#37790)

The allowlist recorded eight files in tests/local_testing, 118 tests, that
every job globbing that directory then deselects: local_testing_part1 and
part2 carry `-k "... and not caching and not cache"`, and the other three keep
one unrelated keyword each. They counted as covered while running nowhere.

Five of the eight need nothing. Measured with no provider credentials and no
Redis: test_cache_preset_key, test_caching_handler, test_prompt_caching,
test_responses_stream_cache_keys and test_unit_test_caching pass, 45 tests
together, and they now run as a caching-local shard. The other three stay
allowlisted with what they actually need recorded rather than a question:
test_caching wants Redis and a provider key for 37 of its 65, disk-cache wants
OPENAI_API_KEY for 2 of 4, gcs-cache wants GCS credentials for all 4.

Taking them off the allowlist exposed a gap in the slice guard itself: it
reasoned only about CircleCI `-k` expressions, so a file every slice drops read
as unrun even when a workflow names it outright. It now credits workflow
test-paths the way the census already does, and only workflows, so a tree only
CircleCI globs is still reported.
---
 .github/ci-coverage-allowlist.yml             | 25 ++++++++-----------
 .github/scripts/assert_ci_coverage.py         | 16 ++++++++++++
 .github/workflows/test-unit.yml               | 13 ++++++++++
 tests/test_litellm/test_assert_ci_coverage.py | 24 ++++++++++++++++++
 4 files changed, 64 insertions(+), 14 deletions(-)

diff --git a/.github/ci-coverage-allowlist.yml b/.github/ci-coverage-allowlist.yml
index 918589f84d1..b6ec08bd295 100644
--- a/.github/ci-coverage-allowlist.yml
+++ b/.github/ci-coverage-allowlist.yml
@@ -5,24 +5,21 @@ description: >-
 
 test_paths:
   - reason: >-
-      The caching suite in tests/local_testing, which runs nowhere. Every job that globs that
-      directory either deselects it (local_testing_part1 and part2 carry `-k "... and not caching
-      and not cache"`) or keeps only another keyword (langfuse, router, assistants), and no job
-      names these files the way redis_caching_unit_tests names test_dual_cache.py. Measured
-      2026-08-20 by collecting the directory under each job's own selector: 118 tests across
-      these eight files are selected by none of them. Listed so the gap is a decision rather
-      than an accident, and so the --slices guard has a baseline to ratchet down from. Revisit
-      when tests/local_testing is ported off CircleCI, where the keyless part of this suite
-      belongs in a real job
+      What is left of the caching suite in tests/local_testing that runs nowhere. Every job that
+      globs that directory either deselects it (local_testing_part1 and part2 carry `-k "... and
+      not caching and not cache"`) or keeps only another keyword (langfuse, router, assistants),
+      and no job names these files the way redis_caching_unit_tests names test_dual_cache.py.
+      The gap was eight files and 118 tests when measured 2026-08-20; the five keyless ones now
+      run in the caching-local shard, leaving these three. Measured 2026-08-21 with no provider
+      credentials and no Redis: test_caching.py needs both (37 of 65 fail without them),
+      test_disk_cache_unit_tests.py needs OPENAI_API_KEY for 2 of its 4, and
+      test_gcs_cache_unit_tests.py needs GCS credentials for all 4. They want the keyless/live
+      split that porting tests/local_testing off CircleCI will force, not a job that is red by
+      construction
     paths:
-      - tests/local_testing/test_cache_preset_key.py
       - tests/local_testing/test_caching.py
-      - tests/local_testing/test_caching_handler.py
       - tests/local_testing/test_disk_cache_unit_tests.py
       - tests/local_testing/test_gcs_cache_unit_tests.py
-      - tests/local_testing/test_prompt_caching.py
-      - tests/local_testing/test_responses_stream_cache_keys.py
-      - tests/local_testing/test_unit_test_caching.py
   - reason: >-
       The end-to-end suite runs against a deployed proxy from its own in-cluster rig rather than
       from a pull request; it needs a live gateway and provider credentials no PR job holds
diff --git a/.github/scripts/assert_ci_coverage.py b/.github/scripts/assert_ci_coverage.py
index c8572d9f6ef..411852acb98 100644
--- a/.github/scripts/assert_ci_coverage.py
+++ b/.github/scripts/assert_ci_coverage.py
@@ -312,8 +312,23 @@ def _matchable_names(relative_path: str) -> frozenset[str]:
     )
 
 
+def _workflow_named_tokens() -> frozenset[str]:
+    """Test tokens a GitHub Actions job names directly.
+
+    A CircleCI `-k` that deselects a file no longer means the file runs nowhere once a
+    workflow names it, so the slice check has to credit those the same way the census does.
+    """
+    return _invoked_test_tokens(
+        scalar
+        for path in _config_files()
+        if path != CIRCLECI_CONFIG
+        for scalar in _scalars(yaml.safe_load(path.read_text(encoding="utf-8")), path.name)
+    )
+
+
 def _deselected_everywhere(allowlist: Allowlist) -> tuple[Finding, ...]:
     slices: Final = _slices()
+    named_by_workflow: Final = _workflow_named_tokens()
     globbed: Final = tuple(
         path
         for path in _test_files()
@@ -326,6 +341,7 @@ def _deselected_everywhere(allowlist: Allowlist) -> tuple[Finding, ...]:
         )
         for path in globbed
         if not allowlist.covers_test(path)
+        and not any(_token_covers(token, path) for token in named_by_workflow)
         and not any(slice_.claims(path, _matchable_names(path)) for slice_ in slices)
     )
 
diff --git a/.github/workflows/test-unit.yml b/.github/workflows/test-unit.yml
index 71eb0958bec..5a75b4af7db 100644
--- a/.github/workflows/test-unit.yml
+++ b/.github/workflows/test-unit.yml
@@ -200,6 +200,19 @@ jobs:
             timeout-minutes: 20
             job-timeout-minutes: 60
 
+          - shard: caching-local
+            artifact-name: caching-local
+            test-path: >-
+              tests/local_testing/test_cache_preset_key.py
+              tests/local_testing/test_caching_handler.py
+              tests/local_testing/test_prompt_caching.py
+              tests/local_testing/test_responses_stream_cache_keys.py
+              tests/local_testing/test_unit_test_caching.py
+            workers: 2
+            reruns: 2
+            timeout-minutes: 20
+            job-timeout-minutes: 55
+
           - shard: responses-caching-types
             artifact-name: responses-caching-types
             test-path: >-
diff --git a/tests/test_litellm/test_assert_ci_coverage.py b/tests/test_litellm/test_assert_ci_coverage.py
index 4c8f4cc2984..d948c1a4155 100644
--- a/tests/test_litellm/test_assert_ci_coverage.py
+++ b/tests/test_litellm/test_assert_ci_coverage.py
@@ -280,3 +280,27 @@ def test_a_dockerfile_directory_entry_is_stale_because_only_an_exact_path_exempt
         dockerfiles=("docker/Dockerfile.database",),
     )
     assert [f.subject for f in findings] == ["docker"]
+
+
+def test_a_workflow_that_names_a_file_clears_it_from_the_slice_check():
+    named = coverage._workflow_named_tokens()
+    assert named, "the workflows must name some test paths or the check proves nothing"
+    assert any(
+        coverage._token_covers(token, "tests/local_testing/test_caching_handler.py")
+        for token in named
+    )
+
+
+def test_the_slice_check_credits_only_workflows_never_the_circleci_config():
+    named = coverage._workflow_named_tokens()
+    circleci_only = "tests/proxy_admin_ui_tests"
+    assert not any(coverage._token_covers(token, f"{circleci_only}/test_key_management.py") for token in named), (
+        "a tree only CircleCI globs must not be credited to a workflow"
+    )
+
+
+def test_a_file_no_workflow_names_is_still_reported_when_every_slice_drops_it():
+    named = coverage._workflow_named_tokens()
+    assert not any(
+        coverage._token_covers(token, "tests/local_testing/test_caching.py") for token in named
+    ), "test_caching.py is allowlisted, not run; crediting it would hide a real gap"

From ae0e8a20dbf9200a5ec324d8381a1dc3c952fa46 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Sat, 22 Aug 2026 22:57:16 -0700
Subject: [PATCH 81/93] fix(ci): run the migration DDL guard, and stop it
 reading comments as SQL (#37791)

* fix(ci): make the migration DDL guard run, and stop it reading comments as SQL

TestMigrationSQLIdempotency requires guarded DDL across litellm-proxy-extras
and has never run in any job, so the convention eroded quietly. Four of its
assertions fail today, and it was allowlisted rather than wired up because
fixing the migrations is not an option: Prisma checksums an applied migration,
so editing one breaks `migrate deploy` for every existing install.

Two things were wrong with the guard itself. It scanned raw lines, so Prisma's
own `-- CREATE INDEX CONCURRENTLY ...` explanations counted as the statements
they describe, which is two of the reported migrations. And it had no way to
say "these predate the rule", so the only options were editing immutable files
or leaving the whole file unrun.

Comments are now stripped before matching, on the drop-column rule too, and the
migrations that already violate are named once in _PRE_GUARD_MIGRATIONS. The
rules bind everything after them, so a new migration with bare CREATE TABLE,
ADD COLUMN, CREATE INDEX or an unguarded ADD CONSTRAINT now fails a check
instead of landing unnoticed.

That set is 14 migrations, not the 13 previously recorded, measured after
comment-stripping. It can only shrink: a test fails if an entry names no
migration on disk, and another fails if an entry no longer violates anything.

The file now runs as a proxy-extras shard and comes off the coverage allowlist.

* fix(ci): strip block comments in the migration guard too

Prisma opens a destructive migration with a /* Warnings: You are about to
drop the column ... */ header. Nothing in the tree trips a rule on that text
today, but it is prose about a statement rather than the statement, and the
line-comment fix left the class open. Bodies are blanked rather than removed
so the reported line number still points at the real statement.
---
 .github/ci-coverage-allowlist.yml             |  11 -
 .github/workflows/test-unit.yml               |   8 +
 .../test_litellm_proxy_extras_utils.py        | 172 ++++++++++++--
 whitelisted_bedrock_models.txt                | 219 ++++++++++++++++++
 4 files changed, 379 insertions(+), 31 deletions(-)
 create mode 100644 whitelisted_bedrock_models.txt

diff --git a/.github/ci-coverage-allowlist.yml b/.github/ci-coverage-allowlist.yml
index b6ec08bd295..f7a785b3b80 100644
--- a/.github/ci-coverage-allowlist.yml
+++ b/.github/ci-coverage-allowlist.yml
@@ -89,17 +89,6 @@ test_paths:
       - tests/integration/sandbox/test_e2b_sandbox.py
       - tests/integration/test_oci_integration.py
       - tests/integration/test_oci_proxy_integration.py
-  - reason: >-
-      A unit test for the proxy-extras package that no job invokes, while the package's other
-      tests live under tests/proxy_migration_tests. Measured 2026-08-20: 24 of its 28 tests pass
-      and the 4 in TestMigrationSQLIdempotency fail, because 13 migrations from 2026-03 onward use
-      bare CREATE TABLE, ADD COLUMN, CREATE INDEX and ADD CONSTRAINT rather than the guarded forms
-      this file requires. It also matches those keywords inside SQL comments, so two further
-      migrations are reported that are in fact fine. Wiring it up means deciding what to do about
-      the 13 first, and they cannot simply be edited: Prisma checksums an applied migration, so a
-      changed one breaks migrate deploy for existing installs
-    paths:
-      - tests/litellm-proxy-extras/test_litellm_proxy_extras_utils.py
 
 dockerfiles:
   - reason: >-
diff --git a/.github/workflows/test-unit.yml b/.github/workflows/test-unit.yml
index 5a75b4af7db..368680d9ec2 100644
--- a/.github/workflows/test-unit.yml
+++ b/.github/workflows/test-unit.yml
@@ -213,6 +213,14 @@ jobs:
             timeout-minutes: 20
             job-timeout-minutes: 55
 
+          - shard: proxy-extras
+            artifact-name: proxy-extras
+            test-path: "tests/litellm-proxy-extras"
+            workers: 2
+            reruns: 2
+            timeout-minutes: 20
+            job-timeout-minutes: 55
+
           - shard: responses-caching-types
             artifact-name: responses-caching-types
             test-path: >-
diff --git a/tests/litellm-proxy-extras/test_litellm_proxy_extras_utils.py b/tests/litellm-proxy-extras/test_litellm_proxy_extras_utils.py
index 6f4979b9b84..09f3e0ba34f 100644
--- a/tests/litellm-proxy-extras/test_litellm_proxy_extras_utils.py
+++ b/tests/litellm-proxy-extras/test_litellm_proxy_extras_utils.py
@@ -161,6 +161,58 @@ def _get_all_migrations():
     return results
 
 
+_LINE_COMMENT = re.compile(r"--.*$")
+_BLOCK_COMMENT = re.compile(r"/\*.*?\*/", re.DOTALL)
+
+_PRE_GUARD_MIGRATIONS = frozenset({
+    "20260331000000_add_prompt_environment_and_created_by",
+    "20260418000000_add_adaptive_router_tables",
+    "20260429161855_workflow_runs_tables",
+    "20260605182307_add_timeout_to_mcp_server_table",
+    "20260626120000_add_mcp_tool_search_enabled",
+    "20260629000000_add_max_concurrent_requests_to_mcp_server_table",
+    "20260710000000_add_dcr_bridge_to_mcp_server_table",
+    "20260713230852_add_key_type_to_litellm_verification_token",
+    "20260811172448_add_shadow_eval",
+    "20260813180408_add_shadow_eval_direction",
+    "20260814000000_add_proxy_worker_heartbeat",
+    "20260817143646_add_daily_guardrail_usage_units",
+    "20260818224500_add_shadow_eval_stopped_by",
+    "20260819000000_shadow_eval_max_budget",
+})
+
+
+def _blanked_block_comments(sql):
+    """`sql` with every `/* ... */` body blanked out, newlines kept so lines still count.
+
+    Prisma opens a destructive migration with a `/* Warnings: You are about to drop the
+    column ... */` header, which is prose about the statement rather than the statement.
+    """
+    return _BLOCK_COMMENT.sub(lambda m: re.sub(r"[^\n]", " ", m.group(0)), sql)
+
+
+def _statements(sql):
+    """(line_number, sql) for each line, with comments removed.
+
+    Prisma writes its own explanations as `-- CREATE INDEX CONCURRENTLY ...`, which a
+    raw-line scan reads as the statement it is describing.
+    """
+    return [
+        (number, _LINE_COMMENT.sub("", line))
+        for number, line in enumerate(_blanked_block_comments(sql).splitlines(), 1)
+    ]
+
+
+def _guarded_migrations(all_migrations):
+    """Migrations the DDL rules apply to. Prisma checksums an applied migration, so the
+    ones that predate these rules cannot be edited without breaking `migrate deploy`
+    for existing installs; they are named once, and the rules bind everything after.
+    """
+    return [
+        (name, sql) for name, sql in all_migrations if name not in _PRE_GUARD_MIGRATIONS
+    ]
+
+
 class TestMigrationSQLIdempotency:
     """Ensure all migration SQL files use idempotent DDL (IF [NOT] EXISTS).
 
@@ -181,8 +233,8 @@ class TestMigrationSQLIdempotency:
     def test_create_table_uses_if_not_exists(self, all_migrations):
         """CREATE TABLE statements must use IF NOT EXISTS"""
         violations = []
-        for migration_name, sql in all_migrations:
-            for line_num, line in enumerate(sql.splitlines(), 1):
+        for migration_name, sql in _guarded_migrations(all_migrations):
+            for line_num, line in _statements(sql):
                 if re.search(
                     r"CREATE\s+TABLE\s+", line, re.IGNORECASE
                 ) and not re.search(
@@ -198,8 +250,8 @@ class TestMigrationSQLIdempotency:
     def test_add_column_uses_if_not_exists(self, all_migrations):
         """ADD COLUMN statements must use IF NOT EXISTS"""
         violations = []
-        for migration_name, sql in all_migrations:
-            for line_num, line in enumerate(sql.splitlines(), 1):
+        for migration_name, sql in _guarded_migrations(all_migrations):
+            for line_num, line in _statements(sql):
                 if re.search(r"ADD\s+COLUMN\s+", line, re.IGNORECASE) and not re.search(
                     r"ADD\s+COLUMN\s+IF\s+NOT\s+EXISTS", line, re.IGNORECASE
                 ):
@@ -212,8 +264,8 @@ class TestMigrationSQLIdempotency:
     def test_drop_column_uses_if_exists(self, all_migrations):
         """DROP COLUMN statements must use IF EXISTS"""
         violations = []
-        for migration_name, sql in all_migrations:
-            for line_num, line in enumerate(sql.splitlines(), 1):
+        for migration_name, sql in _guarded_migrations(all_migrations):
+            for line_num, line in _statements(sql):
                 if re.search(
                     r"DROP\s+COLUMN\s+", line, re.IGNORECASE
                 ) and not re.search(
@@ -239,7 +291,7 @@ class TestMigrationSQLIdempotency:
         for migration_name, sql in all_migrations:
             if migration_name in self._DROP_COLUMN_ALLOWLIST:
                 continue
-            for line_num, line in enumerate(sql.splitlines(), 1):
+            for line_num, line in _statements(sql):
                 if re.search(r"DROP\s+COLUMN", line, re.IGNORECASE):
                     violations.append(f"  {migration_name}:{line_num}: {line.strip()}")
         assert (
@@ -251,8 +303,8 @@ class TestMigrationSQLIdempotency:
     def test_drop_index_uses_if_exists(self, all_migrations):
         """DROP INDEX statements must use IF EXISTS"""
         violations = []
-        for migration_name, sql in all_migrations:
-            for line_num, line in enumerate(sql.splitlines(), 1):
+        for migration_name, sql in _guarded_migrations(all_migrations):
+            for line_num, line in _statements(sql):
                 if re.search(r"DROP\s+INDEX\s+", line, re.IGNORECASE) and not re.search(
                     r"DROP\s+INDEX\s+IF\s+EXISTS", line, re.IGNORECASE
                 ):
@@ -266,8 +318,8 @@ class TestMigrationSQLIdempotency:
     def test_create_index_uses_if_not_exists(self, all_migrations):
         """CREATE INDEX statements must use IF NOT EXISTS"""
         violations = []
-        for migration_name, sql in all_migrations:
-            for line_num, line in enumerate(sql.splitlines(), 1):
+        for migration_name, sql in _guarded_migrations(all_migrations):
+            for line_num, line in _statements(sql):
                 if re.search(
                     r"CREATE\s+(?:UNIQUE\s+)?INDEX\s+", line, re.IGNORECASE
                 ) and not re.search(
@@ -284,10 +336,9 @@ class TestMigrationSQLIdempotency:
     def test_rename_column_is_guarded(self, all_migrations):
         """RENAME COLUMN must be inside a DO $$ IF EXISTS block"""
         violations = []
-        for migration_name, sql in all_migrations:
-            lines = sql.splitlines()
+        for migration_name, sql in _guarded_migrations(all_migrations):
             in_do_block = False
-            for line_num, line in enumerate(lines, 1):
+            for line_num, line in _statements(sql):
                 if re.search(r"DO\s+\$\$", line, re.IGNORECASE):
                     in_do_block = True
                 if re.search(r"END\s+\$\$", line, re.IGNORECASE):
@@ -305,10 +356,9 @@ class TestMigrationSQLIdempotency:
     def test_add_constraint_is_guarded(self, all_migrations):
         """ADD CONSTRAINT must be inside a DO $$ IF NOT EXISTS block"""
         violations = []
-        for migration_name, sql in all_migrations:
-            lines = sql.splitlines()
+        for migration_name, sql in _guarded_migrations(all_migrations):
             in_do_block = False
-            for line_num, line in enumerate(lines, 1):
+            for line_num, line in _statements(sql):
                 if re.search(r"DO\s+\$\$", line, re.IGNORECASE):
                     in_do_block = True
                 if re.search(r"END\s+\$\$", line, re.IGNORECASE):
@@ -326,10 +376,9 @@ class TestMigrationSQLIdempotency:
     def test_drop_constraint_is_guarded(self, all_migrations):
         """DROP CONSTRAINT must be inside a DO $$ IF EXISTS block"""
         violations = []
-        for migration_name, sql in all_migrations:
-            lines = sql.splitlines()
+        for migration_name, sql in _guarded_migrations(all_migrations):
             in_do_block = False
-            for line_num, line in enumerate(lines, 1):
+            for line_num, line in _statements(sql):
                 if re.search(r"DO\s+\$\$", line, re.IGNORECASE):
                     in_do_block = True
                 if re.search(r"END\s+\$\$", line, re.IGNORECASE):
@@ -343,3 +392,86 @@ class TestMigrationSQLIdempotency:
             "DROP CONSTRAINT without DO $$ IF EXISTS guard found in migrations:\n"
             + "\n".join(violations)
         )
+
+
+class TestMigrationGuardScope:
+    """The guard must ignore SQL comments, exempt only the named pre-guard migrations,
+    and still fail on a new migration that uses bare DDL."""
+
+    _NEW = "20990101000000_a_new_migration"
+
+    def _run_rules(self, migrations):
+        suite = TestMigrationSQLIdempotency()
+        failures = []
+        for name in (
+            "test_create_table_uses_if_not_exists",
+            "test_add_column_uses_if_not_exists",
+            "test_create_index_uses_if_not_exists",
+            "test_add_constraint_is_guarded",
+        ):
+            try:
+                getattr(suite, name)(migrations)
+            except AssertionError:
+                failures.append(name)
+        return failures
+
+    def test_a_comment_describing_ddl_is_not_the_ddl(self):
+        sql = '-- CREATE TABLE "Foo" (id TEXT);\n-- ADD COLUMN "bar" TEXT;\n'
+        assert self._run_rules([(self._NEW, sql)]) == []
+
+    def test_a_prisma_warning_block_is_not_the_ddl_it_describes(self):
+        sql = (
+            "/*\n"
+            "  Warnings:\n"
+            "\n"
+            "  - You are about to CREATE TABLE \"Foo\" and ADD COLUMN \"bar\".\n"
+            "\n"
+            "*/\n"
+            'CREATE TABLE IF NOT EXISTS "Foo" (id TEXT);\n'
+        )
+        assert self._run_rules([(self._NEW, sql)]) == []
+
+    def test_a_block_comment_does_not_shift_the_reported_line(self):
+        sql = "/* filler\nfiller */\n" + 'CREATE TABLE "Foo" (id TEXT);\n'
+        suite = TestMigrationSQLIdempotency()
+        with pytest.raises(AssertionError) as failure:
+            suite.test_create_table_uses_if_not_exists([(self._NEW, sql)])
+        assert f"{self._NEW}:3:" in str(failure.value)
+
+    def test_a_new_migration_with_bare_create_table_fails(self):
+        assert "test_create_table_uses_if_not_exists" in self._run_rules(
+            [(self._NEW, 'CREATE TABLE "Foo" (id TEXT);\n')]
+        )
+
+    def test_a_new_migration_with_bare_add_column_fails(self):
+        assert "test_add_column_uses_if_not_exists" in self._run_rules(
+            [(self._NEW, 'ALTER TABLE "Foo" ADD COLUMN "bar" TEXT;\n')]
+        )
+
+    def test_the_guarded_forms_pass(self):
+        sql = (
+            'CREATE TABLE IF NOT EXISTS "Foo" (id TEXT);\n'
+            'ALTER TABLE "Foo" ADD COLUMN IF NOT EXISTS "bar" TEXT;\n'
+            'CREATE INDEX IF NOT EXISTS "Foo_bar_idx" ON "Foo"("bar");\n'
+        )
+        assert self._run_rules([(self._NEW, sql)]) == []
+
+    def test_a_pre_guard_migration_is_exempt_but_a_new_one_is_not(self):
+        bare = 'CREATE TABLE "Foo" (id TEXT);\n'
+        exempt = sorted(_PRE_GUARD_MIGRATIONS)[0]
+        assert self._run_rules([(exempt, bare)]) == []
+        assert self._run_rules([(self._NEW, bare)]) != []
+
+    def test_every_pre_guard_migration_still_exists_on_disk(self):
+        present = {name for name, _ in _get_all_migrations()}
+        missing = _PRE_GUARD_MIGRATIONS - present
+        assert not missing, f"pre-guard entries naming no migration: {sorted(missing)}"
+
+    def test_no_pre_guard_entry_is_already_clean(self):
+        by_name = dict(_get_all_migrations())
+        redundant = [
+            name
+            for name in sorted(_PRE_GUARD_MIGRATIONS)
+            if not self._run_rules([(TestMigrationGuardScope._NEW, by_name[name])])
+        ]
+        assert not redundant, f"these no longer violate and should be removed: {redundant}"
diff --git a/whitelisted_bedrock_models.txt b/whitelisted_bedrock_models.txt
new file mode 100644
index 00000000000..7e20081988d
--- /dev/null
+++ b/whitelisted_bedrock_models.txt
@@ -0,0 +1,219 @@
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+ai21.j2-ultra-v1
+ai21.jamba-1-5-large-v1:0
+ai21.jamba-1-5-mini-v1:0
+ai21.jamba-instruct-v1:0
+twelvelabs.pegasus-1-2-v1:0
+us.twelvelabs.pegasus-1-2-v1:0
+eu.twelvelabs.pegasus-1-2-v1:0
+amazon.titan-text-express-v1
+amazon.titan-text-lite-v1
+amazon.titan-text-premier-v1:0
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+anthropic.claude-3-7-sonnet-20240620-v1:0
+anthropic.claude-3-haiku-20240307-v1:0
+anthropic.claude-3-opus-20240229-v1:0
+anthropic.claude-3-sonnet-20240229-v1:0
+anthropic.claude-instant-v1
+anthropic.claude-mythos-preview
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+apac.anthropic.claude-3-sonnet-20240229-v1:0
+bedrock/*/1-month-commitment/cohere.command-light-text-v14
+bedrock/*/1-month-commitment/cohere.command-text-v14
+bedrock/*/6-month-commitment/cohere.command-light-text-v14
+bedrock/*/6-month-commitment/cohere.command-text-v14
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+bedrock/us-gov-west-1/amazon.nova-pro-v1:0
+bedrock/us-gov-west-1/amazon.titan-text-express-v1
+bedrock/us-gov-west-1/amazon.titan-text-lite-v1
+bedrock/us-gov-west-1/amazon.titan-text-premier-v1:0
+bedrock/us-gov-west-1/anthropic.claude-3-7-sonnet-20250219-v1:0
+bedrock/us-gov-west-1/anthropic.claude-3-5-sonnet-20240620-v1:0
+bedrock/us-gov-west-1/anthropic.claude-3-haiku-20240307-v1:0
+bedrock/us-gov-west-1/anthropic.claude-sonnet-4-5-20250929-v1:0
+bedrock/us-gov-west-1/claude-sonnet-4-5-20250929-v1:0
+bedrock/us-gov-west-1/meta.llama3-70b-instruct-v1:0
+bedrock/us-gov-west-1/meta.llama3-8b-instruct-v1:0
+bedrock/us-west-1/meta.llama3-70b-instruct-v1:0
+bedrock/us-west-1/meta.llama3-8b-instruct-v1:0
+bedrock/us-west-2/1-month-commitment/anthropic.claude-instant-v1
+bedrock/us-west-2/1-month-commitment/anthropic.claude-v1
+bedrock/us-west-2/1-month-commitment/anthropic.claude-v2:1
+bedrock/us-west-2/6-month-commitment/anthropic.claude-instant-v1
+bedrock/us-west-2/6-month-commitment/anthropic.claude-v1
+bedrock/us-west-2/6-month-commitment/anthropic.claude-v2:1
+bedrock/us-west-2/anthropic.claude-instant-v1
+bedrock/us-west-2/anthropic.claude-v1
+bedrock/us-west-2/anthropic.claude-v2:1
+bedrock/us-west-2/mistral.mistral-7b-instruct-v0:2
+bedrock/us-west-2/mistral.mistral-large-2402-v1:0
+bedrock/us-west-2/mistral.mixtral-8x7b-instruct-v0:1
+bedrock/us-west-2/deepseek.v3.2
+bedrock/us-west-2/minimax.minimax-m2.1
+bedrock/us-west-2/minimax.minimax-m2.5
+bedrock/us-west-2/moonshotai.kimi-k2-thinking
+bedrock/us-west-2/moonshotai.kimi-k2.5
+bedrock/us-west-2/qwen.qwen3-coder-next
+bedrock/us.anthropic.claude-3-5-haiku-20241022-v1:0
+claude-sonnet-4-5-20250929-v1:0
+cohere.command-light-text-v14
+cohere.command-r-plus-v1:0
+cohere.command-r-v1:0
+cohere.command-text-v14
+eu.anthropic.claude-3-5-haiku-20241022-v1:0
+eu.anthropic.claude-3-5-sonnet-20240620-v1:0
+eu.anthropic.claude-3-5-sonnet-20241022-v2:0
+eu.anthropic.claude-3-7-sonnet-20250219-v1:0
+eu.anthropic.claude-3-haiku-20240307-v1:0
+eu.anthropic.claude-3-opus-20240229-v1:0
+eu.anthropic.claude-3-sonnet-20240229-v1:0
+eu.meta.llama3-2-1b-instruct-v1:0
+eu.meta.llama3-2-3b-instruct-v1:0
+meta.llama2-13b-chat-v1
+meta.llama2-70b-chat-v1
+meta.llama3-1-405b-instruct-v1:0
+meta.llama3-1-70b-instruct-v1:0
+meta.llama3-1-8b-instruct-v1:0
+meta.llama3-2-11b-instruct-v1:0
+meta.llama3-2-1b-instruct-v1:0
+meta.llama3-2-3b-instruct-v1:0
+meta.llama3-2-90b-instruct-v1:0
+meta.llama3-70b-instruct-v1:0
+meta.llama3-8b-instruct-v1:0
+mistral.mistral-7b-instruct-v0:2
+mistral.mistral-large-2402-v1:0
+mistral.mistral-large-2407-v1:0
+mistral.mistral-small-2402-v1:0
+mistral.mixtral-8x7b-instruct-v0:1
+us.anthropic.claude-3-5-haiku-20241022-v1:0
+us.anthropic.claude-3-5-sonnet-20240620-v1:0
+us.anthropic.claude-3-5-sonnet-20241022-v2:0
+us.anthropic.claude-3-haiku-20240307-v1:0
+us.anthropic.claude-3-opus-20240229-v1:0
+us.anthropic.claude-3-sonnet-20240229-v1:0
+us.meta.llama3-1-405b-instruct-v1:0
+us.meta.llama3-1-70b-instruct-v1:0
+us.meta.llama3-1-8b-instruct-v1:0
+us.meta.llama3-2-11b-instruct-v1:0
+us.meta.llama3-2-1b-instruct-v1:0
+us.meta.llama3-2-3b-instruct-v1:0
+us.meta.llama3-2-90b-instruct-v1:0
+bedrock/us-east-1/zai.glm-5
+bedrock/us-west-2/zai.glm-5
+bedrock/us-gov-east-1/anthropic.claude-haiku-4-5-20251001-v1:0
+bedrock/us-gov-west-1/anthropic.claude-haiku-4-5-20251001-v1:0

From 68489f62ff5db52005bfd4084b8c4f46dafebe53 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Sat, 22 Aug 2026 22:57:50 -0700
Subject: [PATCH 82/93] ci: run the enterprise package suite in GitHub Actions
 (#37798)

tests/enterprise is 13 files and 244 tests that only CircleCI runs, and CircleCI
gates nothing: it triggers on PR labeled events, none of its jobs are required,
and red runs get merged past. So the suite that covers the enterprise package's
guardrails, auth and management endpoints has had no say in whether a change
lands.

Measured on 2026-08-21 with every credential stripped from the environment: 240
passed, 4 skipped, nothing failed. It needs no provider key, so it can be a
required shard rather than a scheduled lane, unlike the other CircleCI suites in
this group, which each carry a live-API minority.

The CircleCI job is removed in the same commit so the suite runs once, not twice.
---
 .circleci/config.yml            | 37 ---------------------------------
 .github/workflows/test-unit.yml |  8 +++++++
 2 files changed, 8 insertions(+), 37 deletions(-)

diff --git a/.circleci/config.yml b/.circleci/config.yml
index a261b7c78fc..4615a6a5a7e 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -1154,40 +1154,6 @@ jobs:
           paths:
             - search_coverage.xml
             - search_coverage
-  litellm_mapped_enterprise_tests:
-    docker:
-      - *python312_image
-    working_directory: ~/project
-    resource_class: large
-
-    steps:
-      - checkout
-      - skip_if_unrelated_changes
-      - setup_google_dns
-      - install_uv
-      - install_rust
-      - run:
-          name: Install Dependencies
-          command: |
-            uv sync --frozen --all-groups --all-extras --python 3.12
-      - setup_litellm_enterprise_pip
-      - run:
-          name: Run enterprise tests
-          command: |
-            uv run --no-sync python -m prisma generate
-            mkdir -p test-results
-            TEST_FILES=$(circleci tests glob "tests/enterprise/**/test_*.py")
-            echo "$TEST_FILES" | circleci tests run \
-              --verbose \
-              --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \
-                -v -x \
-                --junitxml=test-results/junit-enterprise.xml \
-                --durations=10 \
-                -n 4"
-          no_output_timeout: 15m
-      # Store test results
-      - store_test_results:
-          path: test-results
   batches_testing:
     docker:
       - *python312_image
@@ -3041,8 +3007,6 @@ workflows:
           filters: *main_branches
       - search_testing:
           filters: *main_branches
-      - litellm_mapped_enterprise_tests:
-          filters: *main_branches
       - batches_testing:
           filters: *main_branches
       - litellm_utils_testing:
@@ -3065,7 +3029,6 @@ workflows:
             - guardrails_testing
             - ocr_testing
             - search_testing
-            - litellm_mapped_enterprise_tests
             - batches_testing
             - litellm_utils_testing
             - pass_through_unit_testing
diff --git a/.github/workflows/test-unit.yml b/.github/workflows/test-unit.yml
index 368680d9ec2..1370a05181a 100644
--- a/.github/workflows/test-unit.yml
+++ b/.github/workflows/test-unit.yml
@@ -221,6 +221,14 @@ jobs:
             timeout-minutes: 20
             job-timeout-minutes: 55
 
+          - shard: enterprise-package
+            artifact-name: enterprise-package
+            test-path: "tests/enterprise"
+            workers: 4
+            reruns: 2
+            timeout-minutes: 20
+            job-timeout-minutes: 55
+
           - shard: responses-caching-types
             artifact-name: responses-caching-types
             test-path: >-

From d1f37788492b98b19974d981fff0498a5e090f64 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Sat, 22 Aug 2026 22:58:26 -0700
Subject: [PATCH 83/93] perf(ci): give the two longest unit shards the runner's
 spare cores (#37804)

proxy-endpoints and proxy-infra are the unit tier's critical path at 358s and
325s of pytest, measured on staging 2026-08-21, and both run two xdist workers
on a four-vCPU runner. proxy-server already runs four. This is the cheaper half
of splitting them: no second job, so no second setup to pay for.
---
 .github/workflows/test-unit.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/test-unit.yml b/.github/workflows/test-unit.yml
index 1370a05181a..a7c67f2b35d 100644
--- a/.github/workflows/test-unit.yml
+++ b/.github/workflows/test-unit.yml
@@ -168,7 +168,7 @@ jobs:
               tests/test_litellm/proxy/ui_crud_endpoints
               tests/test_litellm/proxy/config_resolvers
               tests/test_litellm/proxy/utils
-            workers: 2
+            workers: 4
             reruns: 2
             timeout-minutes: 20
             job-timeout-minutes: 60
@@ -195,7 +195,7 @@ jobs:
               tests/test_litellm/proxy/types_utils
               tests/test_litellm/proxy/logging_endpoints
               tests/test_litellm/proxy/test_*.py
-            workers: 2
+            workers: 4
             reruns: 2
             timeout-minutes: 20
             job-timeout-minutes: 60

From f005afa1460385a218be8ef1fdfa49998bf93523 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Sat, 22 Aug 2026 22:59:02 -0700
Subject: [PATCH 84/93] test(exception-mapping): pin the status and error-shape
 table every provider maps to (#37807)

`exception_type` decides the class and status a caller sees for every provider
failure, across 190 raise sites, and the tests for it were written one incident
at a time. Nothing said what a plain 401 from any given provider should be, so
mutating a raise site went unnoticed: swapping the class at each of the 190 in
turn, the mapped test file caught 15.

Adds two tables asserted end to end through `exception_type`: 25 providers by
the 9 upstream statuses, and the three error shapes the router branches on
(a full context window, a content policy block, a timeout). The same 190
mutants now fail 97 of them.

The tables record today's behavior, uneven where it is uneven. cloudflare,
ollama and vllm map no status at all, so every failure reaches the caller as a
500. A full context window is recognised by 15 of the 25, and a content policy
block by 11, which bounds where `context_window_fallbacks` and the content
policy retry policy can fire.
---
 .../test_exception_mapping_utils.py           | 285 ++++++++++++++++++
 1 file changed, 285 insertions(+)

diff --git a/tests/test_litellm/litellm_core_utils/test_exception_mapping_utils.py b/tests/test_litellm/litellm_core_utils/test_exception_mapping_utils.py
index cc0a52247a4..599ad016827 100644
--- a/tests/test_litellm/litellm_core_utils/test_exception_mapping_utils.py
+++ b/tests/test_litellm/litellm_core_utils/test_exception_mapping_utils.py
@@ -1,5 +1,6 @@
 
 import httpx
+import openai
 import pytest
 
 import litellm
@@ -759,6 +760,290 @@ def test_azure_404_with_invalid_request_error_type_maps_to_not_found():
     assert "Response with id 'resp_abc' not found." in excinfo.value.message
 
 
+class _UpstreamHTTPError(Exception):
+    def __init__(self, status_code: int) -> None:
+        super().__init__("upstream failure")
+        self.message = "upstream failure"
+        self.status_code = status_code
+        self.request = httpx.Request("POST", "https://api.example.com/v1/chat/completions")
+        self.response = httpx.Response(
+            status_code=status_code, request=self.request, text="upstream failure"
+        )
+
+
+UPSTREAM_STATUS_CODES = (400, 401, 403, 404, 408, 422, 429, 500, 503)
+
+OPENAI_SHAPED = {
+    400: (litellm.BadRequestError, 400),
+    401: (litellm.AuthenticationError, 401),
+    403: (litellm.APIError, 403),
+    404: (litellm.NotFoundError, 404),
+    408: (litellm.Timeout, 408),
+    422: (litellm.BadRequestError, 422),
+    429: (litellm.RateLimitError, 429),
+    500: (litellm.InternalServerError, 500),
+    503: (litellm.ServiceUnavailableError, 503),
+}
+
+UPSTREAM_STATUS_DISCARDED = (litellm.APIConnectionError, 500)
+
+PROVIDERS_THAT_DISCARD_THE_UPSTREAM_STATUS = ("cloudflare", "ollama", "vllm")
+
+DEVIATIONS_FROM_THE_OPENAI_SHAPE = {
+    "anthropic": {403: UPSTREAM_STATUS_DISCARDED, 422: UPSTREAM_STATUS_DISCARDED},
+    "azure": {500: (litellm.APIError, 500)},
+    "bedrock": {
+        403: UPSTREAM_STATUS_DISCARDED,
+        500: (litellm.ServiceUnavailableError, 503),
+    },
+    "cohere": {
+        401: UPSTREAM_STATUS_DISCARDED,
+        403: UPSTREAM_STATUS_DISCARDED,
+        404: UPSTREAM_STATUS_DISCARDED,
+        422: UPSTREAM_STATUS_DISCARDED,
+        429: UPSTREAM_STATUS_DISCARDED,
+        503: UPSTREAM_STATUS_DISCARDED,
+    },
+    "databricks": {
+        403: (litellm.AuthenticationError, 401),
+        422: (litellm.BadRequestError, 400),
+    },
+    "gemini": {
+        403: (litellm.PermissionDeniedError, 403),
+        422: UPSTREAM_STATUS_DISCARDED,
+    },
+    "huggingface": {
+        404: (litellm.APIError, 404),
+        422: (litellm.APIError, 422),
+        500: (litellm.APIError, 500),
+    },
+    "nlp_cloud": {
+        403: (litellm.AuthenticationError, 403),
+        404: (litellm.APIError, 404),
+        408: (litellm.APIError, 408),
+        500: (litellm.APIError, 500),
+        503: (litellm.APIError, 503),
+    },
+    "openrouter": {500: (litellm.APIError, 500)},
+    "replicate": {
+        403: (litellm.APIError, 500),
+        404: (litellm.APIError, 500),
+        422: (litellm.UnprocessableEntityError, 422),
+        500: (litellm.ServiceUnavailableError, 503),
+        503: (litellm.APIError, 500),
+    },
+    "sagemaker": {
+        403: UPSTREAM_STATUS_DISCARDED,
+        500: (litellm.ServiceUnavailableError, 503),
+    },
+    "vertex_ai": {
+        403: (litellm.PermissionDeniedError, 403),
+        422: UPSTREAM_STATUS_DISCARDED,
+    },
+    **{
+        provider: dict.fromkeys(UPSTREAM_STATUS_CODES, UPSTREAM_STATUS_DISCARDED)
+        for provider in PROVIDERS_THAT_DISCARD_THE_UPSTREAM_STATUS
+    },
+}
+
+PROVIDERS_WITH_A_HANDLER = (
+    "ai21",
+    "anthropic",
+    "azure",
+    "azure_ai",
+    "bedrock",
+    "cloudflare",
+    "cohere",
+    "databricks",
+    "deepseek",
+    "fireworks_ai",
+    "gemini",
+    "groq",
+    "huggingface",
+    "mistral",
+    "nlp_cloud",
+    "ollama",
+    "openai",
+    "openrouter",
+    "perplexity",
+    "replicate",
+    "sagemaker",
+    "together_ai",
+    "vertex_ai",
+    "vllm",
+    "xai",
+)
+
+
+def _expected_for(provider: str, status_code: int) -> tuple[type[Exception], int]:
+    return DEVIATIONS_FROM_THE_OPENAI_SHAPE.get(provider, {}).get(
+        status_code, OPENAI_SHAPED[status_code]
+    )
+
+
+@pytest.fixture
+def quiet_exception_mapping(monkeypatch):
+    monkeypatch.setattr(litellm, "suppress_debug_info", True)
+
+
+@pytest.mark.parametrize("status_code", UPSTREAM_STATUS_CODES)
+@pytest.mark.parametrize("provider", PROVIDERS_WITH_A_HANDLER)
+def test_an_upstream_status_maps_to_one_exception_per_provider(
+    provider, status_code, quiet_exception_mapping
+):
+    expected_class, expected_status = _expected_for(provider, status_code)
+
+    with pytest.raises(openai.APIError) as raised:
+        exception_type(
+            model="test-model",
+            original_exception=_UpstreamHTTPError(status_code=status_code),
+            custom_llm_provider=provider,
+        )
+
+    assert type(raised.value) is expected_class
+    assert raised.value.status_code == expected_status
+
+
+@pytest.mark.parametrize("status_code", UPSTREAM_STATUS_CODES)
+@pytest.mark.parametrize("provider", PROVIDERS_WITH_A_HANDLER)
+def test_a_mapped_exception_keeps_the_provider_and_model_it_came_from(
+    provider, status_code, quiet_exception_mapping
+):
+    with pytest.raises(openai.APIError) as raised:
+        exception_type(
+            model="test-model",
+            original_exception=_UpstreamHTTPError(status_code=status_code),
+            custom_llm_provider=provider,
+        )
+
+    assert raised.value.llm_provider == provider
+    assert raised.value.model == "test-model"
+
+
+@pytest.mark.parametrize("provider", PROVIDERS_WITH_A_HANDLER)
+def test_an_already_mapped_litellm_exception_passes_through_untouched(
+    provider, quiet_exception_mapping
+):
+    already_mapped = litellm.RateLimitError(
+        message="already mapped", llm_provider=provider, model="test-model"
+    )
+
+    returned = exception_type(
+        model="test-model",
+        original_exception=already_mapped,
+        custom_llm_provider=provider,
+    )
+
+    assert returned is already_mapped
+
+
+CONTEXT_WINDOW_MESSAGE = "This model's maximum context length is 4096 tokens."
+CONTENT_POLICY_MESSAGE = (
+    '{"error": {"type": "invalid_request_error", "code": "content_policy_violation"}}'
+)
+TIMEOUT_MESSAGE = "Request timed out."
+
+PROVIDERS_THAT_RECOGNISE_A_FULL_CONTEXT_WINDOW = (
+    "ai21",
+    "anthropic",
+    "azure",
+    "azure_ai",
+    "databricks",
+    "deepseek",
+    "fireworks_ai",
+    "gemini",
+    "groq",
+    "mistral",
+    "openai",
+    "perplexity",
+    "together_ai",
+    "vertex_ai",
+    "xai",
+)
+
+PROVIDERS_THAT_RECOGNISE_A_CONTENT_POLICY_BLOCK = (
+    "ai21",
+    "azure",
+    "azure_ai",
+    "deepseek",
+    "fireworks_ai",
+    "groq",
+    "mistral",
+    "openai",
+    "perplexity",
+    "together_ai",
+    "xai",
+)
+
+
+class _UpstreamErrorWithMessage(_UpstreamHTTPError):
+    def __init__(self, message: str, status_code: int) -> None:
+        super().__init__(status_code=status_code)
+        self.args = (message,)
+        self.message = message
+        self.response = httpx.Response(
+            status_code=status_code, request=self.request, text=message
+        )
+
+
+@pytest.mark.parametrize("provider", PROVIDERS_WITH_A_HANDLER)
+def test_a_full_context_window_reaches_the_caller_as_the_router_needs_it(
+    provider, quiet_exception_mapping
+):
+    if provider in PROVIDERS_THAT_DISCARD_THE_UPSTREAM_STATUS:
+        expected_class, expected_status = UPSTREAM_STATUS_DISCARDED
+    elif provider in PROVIDERS_THAT_RECOGNISE_A_FULL_CONTEXT_WINDOW:
+        expected_class, expected_status = litellm.ContextWindowExceededError, 400
+    else:
+        expected_class, expected_status = litellm.BadRequestError, 400
+
+    with pytest.raises(openai.APIError) as raised:
+        exception_type(
+            model="test-model",
+            original_exception=_UpstreamErrorWithMessage(CONTEXT_WINDOW_MESSAGE, 400),
+            custom_llm_provider=provider,
+        )
+
+    assert type(raised.value) is expected_class
+    assert raised.value.status_code == expected_status
+
+
+@pytest.mark.parametrize("provider", PROVIDERS_WITH_A_HANDLER)
+def test_a_content_policy_block_reaches_the_caller_as_the_router_needs_it(
+    provider, quiet_exception_mapping
+):
+    if provider in PROVIDERS_THAT_DISCARD_THE_UPSTREAM_STATUS:
+        expected_class, expected_status = UPSTREAM_STATUS_DISCARDED
+    elif provider in PROVIDERS_THAT_RECOGNISE_A_CONTENT_POLICY_BLOCK:
+        expected_class, expected_status = litellm.ContentPolicyViolationError, 400
+    else:
+        expected_class, expected_status = litellm.BadRequestError, 400
+
+    with pytest.raises(openai.APIError) as raised:
+        exception_type(
+            model="test-model",
+            original_exception=_UpstreamErrorWithMessage(CONTENT_POLICY_MESSAGE, 400),
+            custom_llm_provider=provider,
+        )
+
+    assert type(raised.value) is expected_class
+    assert raised.value.status_code == expected_status
+
+
+@pytest.mark.parametrize("provider", PROVIDERS_WITH_A_HANDLER)
+def test_a_timed_out_request_is_a_timeout_for_every_provider(
+    provider, quiet_exception_mapping
+):
+    with pytest.raises(litellm.Timeout) as raised:
+        exception_type(
+            model="test-model",
+            original_exception=_UpstreamErrorWithMessage(TIMEOUT_MESSAGE, 408),
+            custom_llm_provider=provider,
+        )
+
+    assert raised.value.status_code == 408
+
+
 def test_bedrock_mantle_400_maps_to_bad_request():
     from litellm.llms.base_llm.chat.transformation import BaseLLMException
 

From a72203eae4e98d216668b3a7216dda8a628431ca Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Mon, 24 Aug 2026 10:12:10 -0700
Subject: [PATCH 85/93] fix(terraform): add soft_budget, tags, and
 soft_budget_alerting_emails to litellm_team (#37918)

* fix(terraform): add soft_budget, tags, and soft_budget_alerting_emails to litellm_team

The team resource rejected soft_budget and tags at plan time and had no way
to express the list-valued metadata.soft_budget_alerting_emails the proxy
reads for soft-budget alerts, even though /team/new and /team/update accept
all three. Add the attributes, forward them in buildTeamData (alert emails
merged under metadata, where the proxy stores them), and send the full
metadata map whenever either half changes because /team/update replaces
metadata wholesale.

Read was decoding /team/info as if the team fields were top-level, but the
proxy nests them under team_info, so every attribute silently fell back to
prior state. Decode the envelope and split the proxy's metadata back into
tags / soft_budget_alerting_emails / string metadata, dropping the
server-managed team_member_budget_id.

Verified with OpenTofu plan/apply against a live proxy: the attributes are
accepted, land on the proxy, refresh into state, re-plan clean, propagate
on update, and clear when removed from HCL.

* fix(terraform): clear litellm_team.soft_budget in state when the proxy returns null

Read only wrote soft_budget when the proxy returned a value, so a soft
budget cleared outside Terraform stayed in state and never surfaced as
drift. Set it from the response unconditionally so a null clears it.
---
 terraform/provider/CHANGELOG.md               |   8 +
 terraform/provider/docs/resources/team.md     |  15 +-
 terraform/provider/litellm/resource_team.go   |  97 ++++++++-
 .../provider/litellm/resource_team_test.go    | 184 ++++++++++++++++++
 terraform/provider/litellm/types.go           |   6 +
 5 files changed, 300 insertions(+), 10 deletions(-)
 create mode 100644 terraform/provider/litellm/resource_team_test.go

diff --git a/terraform/provider/CHANGELOG.md b/terraform/provider/CHANGELOG.md
index ff2f3f817f9..3bd3c4d1d6c 100644
--- a/terraform/provider/CHANGELOG.md
+++ b/terraform/provider/CHANGELOG.md
@@ -14,6 +14,14 @@ longer signal it.
 
 ## [Unreleased]
 
+### Added
+
+- **team**: `soft_budget`, `tags`, and `soft_budget_alerting_emails` attributes on `litellm_team`, matching what `/team/new` and `/team/update` already accept; `soft_budget_alerting_emails` is sent under `metadata`, where the proxy reads it
+
+### Fixed
+
+- **team**: Read now decodes the `team_info` envelope `/team/info` actually returns, so team attributes refresh from the proxy instead of always falling back to the prior state
+
 ### Changed
 
 - **Versioning**: the provider is now published at the LiteLLM version, from the same commit as the proxy, on every LiteLLM release (dev, rc, stable). The `0.x` line ends at `0.4.0`; a `~> 0.4` constraint will not receive further releases, so re-pin to the LiteLLM version your proxy runs (for example `~> 1.99.0`). Existing `0.x` versions remain in the registry and keep verifying
diff --git a/terraform/provider/docs/resources/team.md b/terraform/provider/docs/resources/team.md
index 68535309f10..65ab4bf82d4 100644
--- a/terraform/provider/docs/resources/team.md
+++ b/terraform/provider/docs/resources/team.md
@@ -24,11 +24,18 @@ resource "litellm_team" "advanced_team" {
 
   # Budget and rate limiting
   max_budget      = 1000.0
+  soft_budget     = 800.0
   budget_duration = "1mo"
   tpm_limit       = 500000
   rpm_limit       = 5000
   blocked         = false
 
+  # Who gets paged when spend crosses soft_budget
+  soft_budget_alerting_emails = ["finops@example.com"]
+
+  # Tags for spend tracking and tag-based routing
+  tags = ["team:ai-research", "environment:production"]
+
   # Team member permissions
   team_member_permissions = [
     "create_key",
@@ -91,7 +98,9 @@ The following arguments are supported:
 
 * `models` - (Optional) List of model names that this team can access.
 
-* `metadata` - (Optional) A map of metadata key-value pairs associated with the team.
+* `metadata` - (Optional) A map of string metadata key-value pairs associated with the team. `tags` and `soft_budget_alerting_emails` are stored by the proxy under metadata but are managed through their own attributes below, not this map.
+
+* `tags` - (Optional) List of tags applied to the team, used for [spend tracking](https://docs.litellm.ai/docs/proxy/enterprise#tracking-spend-for-custom-tags) and [tag-based routing](https://docs.litellm.ai/docs/proxy/tag_routing).
 
 * `blocked` - (Optional) Whether the team is blocked from making requests. Default is `false`.
 
@@ -101,6 +110,10 @@ The following arguments are supported:
 
 * `max_budget` - (Optional) Maximum budget allocated to the team.
 
+* `soft_budget` - (Optional) Spend threshold at which the proxy sends a soft budget alert without blocking requests.
+
+* `soft_budget_alerting_emails` - (Optional) List of email addresses notified when the team's spend crosses `soft_budget`.
+
 * `budget_duration` - (Optional) Duration for the budget cycle. Valid values are:
   * `daily`
   * `weekly`
diff --git a/terraform/provider/litellm/resource_team.go b/terraform/provider/litellm/resource_team.go
index 88e0dcd4811..2a167a1b5c4 100644
--- a/terraform/provider/litellm/resource_team.go
+++ b/terraform/provider/litellm/resource_team.go
@@ -53,6 +53,11 @@ func ResourceLiteLLMTeam() *schema.Resource {
 				Type:     schema.TypeFloat,
 				Optional: true,
 			},
+			"soft_budget": {
+				Type:        schema.TypeFloat,
+				Optional:    true,
+				Description: "Spend threshold that triggers a soft budget alert without blocking requests",
+			},
 			"budget_duration": {
 				Type:     schema.TypeString,
 				Optional: true,
@@ -72,6 +77,18 @@ func ResourceLiteLLMTeam() *schema.Resource {
 				Elem:        &schema.Schema{Type: schema.TypeString},
 				Description: "List of permissions granted to team members",
 			},
+			"tags": {
+				Type:        schema.TypeList,
+				Optional:    true,
+				Elem:        &schema.Schema{Type: schema.TypeString},
+				Description: "Tags for spend tracking and tag-based routing",
+			},
+			"soft_budget_alerting_emails": {
+				Type:        schema.TypeList,
+				Optional:    true,
+				Elem:        &schema.Schema{Type: schema.TypeString},
+				Description: "Email addresses alerted when the team crosses soft_budget",
+			},
 		},
 	}
 }
@@ -117,21 +134,20 @@ func resourceLiteLLMTeamRead(d *schema.ResourceData, m interface{}) error {
 		return nil
 	}
 
-	var teamResp TeamResponse
-	if err := json.NewDecoder(resp.Body).Decode(&teamResp); err != nil {
+	var infoResp TeamInfoResponse
+	if err := json.NewDecoder(resp.Body).Decode(&infoResp); err != nil {
 		return fmt.Errorf("error decoding team info response: %w", err)
 	}
+	teamResp := infoResp.TeamInfo
 
 	// Update the state with values from the response or fall back to the data passed in during creation
 	d.Set("team_alias", GetStringValue(teamResp.TeamAlias, d.Get("team_alias").(string)))
 	d.Set("organization_id", GetStringValue(teamResp.OrganizationID, d.Get("organization_id").(string)))
 
-	// Handle metadata separately as it's a map
-	if teamResp.Metadata != nil {
-		d.Set("metadata", teamResp.Metadata)
-	} else {
-		d.Set("metadata", d.Get("metadata"))
-	}
+	metadata, tags, alertEmails := splitTeamMetadata(teamResp.Metadata)
+	d.Set("metadata", metadata)
+	d.Set("tags", tags)
+	d.Set("soft_budget_alerting_emails", alertEmails)
 
 	if teamResp.TPMLimit != nil {
 		d.Set("tpm_limit", *teamResp.TPMLimit)
@@ -142,6 +158,7 @@ func resourceLiteLLMTeamRead(d *schema.ResourceData, m interface{}) error {
 	if teamResp.MaxBudget != nil {
 		d.Set("max_budget", *teamResp.MaxBudget)
 	}
+	d.Set("soft_budget", teamResp.SoftBudget)
 	d.Set("budget_duration", GetStringValue(teamResp.BudgetDuration, d.Get("budget_duration").(string)))
 
 	// Handle models separately as it's a list
@@ -240,15 +257,77 @@ func buildTeamData(d *schema.ResourceData, teamID string) map[string]interface{}
 		"team_alias": d.Get("team_alias").(string),
 	}
 
-	for _, key := range []string{"organization_id", "metadata", "tpm_limit", "rpm_limit", "max_budget", "budget_duration", "models", "blocked", "team_member_permissions"} {
+	for _, key := range []string{"organization_id", "tpm_limit", "rpm_limit", "max_budget", "budget_duration", "models", "blocked", "team_member_permissions"} {
 		if v, ok := d.GetOk(key); ok {
 			teamData[key] = v
 		}
 	}
 
+	if v, ok := d.GetOk("soft_budget"); ok {
+		teamData["soft_budget"] = v
+	} else if d.HasChange("soft_budget") {
+		teamData["soft_budget"] = nil
+	}
+
+	if v, ok := d.GetOk("tags"); ok || d.HasChange("tags") {
+		teamData["tags"] = v
+	}
+
+	if metadata := buildTeamMetadata(d); metadata != nil {
+		teamData["metadata"] = metadata
+	}
+
 	return teamData
 }
 
+// /team/update replaces metadata wholesale, so the full map must go out whenever either half changed.
+func buildTeamMetadata(d *schema.ResourceData) map[string]interface{} {
+	metadata := map[string]interface{}{}
+	for k, v := range d.Get("metadata").(map[string]interface{}) {
+		metadata[k] = v
+	}
+	if v, ok := d.GetOk("soft_budget_alerting_emails"); ok {
+		metadata["soft_budget_alerting_emails"] = v
+	}
+	if len(metadata) == 0 && !d.HasChange("metadata") && !d.HasChange("soft_budget_alerting_emails") {
+		return nil
+	}
+	return metadata
+}
+
+func splitTeamMetadata(raw map[string]interface{}) (map[string]string, []string, []string) {
+	metadata := map[string]string{}
+	var tags, alertEmails []string
+	for k, v := range raw {
+		switch k {
+		case "tags":
+			tags = toStringSlice(v)
+		case "soft_budget_alerting_emails":
+			alertEmails = toStringSlice(v)
+		case "team_member_budget_id":
+		default:
+			if s, ok := v.(string); ok {
+				metadata[k] = s
+			}
+		}
+	}
+	return metadata, tags, alertEmails
+}
+
+func toStringSlice(v interface{}) []string {
+	items, ok := v.([]interface{})
+	if !ok {
+		return nil
+	}
+	out := make([]string, 0, len(items))
+	for _, item := range items {
+		if s, ok := item.(string); ok {
+			out = append(out, s)
+		}
+	}
+	return out
+}
+
 func handleResponse(resp *http.Response, action string) error {
 	if resp.StatusCode != http.StatusOK {
 		body, _ := io.ReadAll(resp.Body)
diff --git a/terraform/provider/litellm/resource_team_test.go b/terraform/provider/litellm/resource_team_test.go
new file mode 100644
index 00000000000..1f74be4819d
--- /dev/null
+++ b/terraform/provider/litellm/resource_team_test.go
@@ -0,0 +1,184 @@
+package litellm
+
+import (
+	"context"
+	"encoding/json"
+	"io"
+	"net/http"
+	"net/http/httptest"
+	"reflect"
+	"testing"
+
+	"github.com/hashicorp/terraform-plugin-sdk/v2/helper/schema"
+	"github.com/hashicorp/terraform-plugin-sdk/v2/terraform"
+)
+
+func newTeamTestServer(t *testing.T, captured *map[string]interface{}, infoBody string) *httptest.Server {
+	t.Helper()
+	return httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		w.Header().Set("Content-Type", "application/json")
+		switch r.URL.Path {
+		case endpointTeamNew, endpointTeamUpdate:
+			body, _ := io.ReadAll(r.Body)
+			json.Unmarshal(body, captured)
+			w.Write([]byte(`{}`))
+		case endpointTeamInfo:
+			w.Write([]byte(infoBody))
+		case endpointTeamPermissionsList:
+			w.Write([]byte(`{"team_id":"team-1","team_member_permissions":[],"all_available_permissions":[]}`))
+		default:
+			w.WriteHeader(http.StatusNotFound)
+		}
+	}))
+}
+
+const teamInfoWithSoftBudget = `{
+  "team_id": "team-1",
+  "team_info": {
+    "team_id": "team-1",
+    "team_alias": "insights",
+    "max_budget": 750.0,
+    "soft_budget": 600.0,
+    "models": ["claude-haiku-4-5"],
+    "metadata": {
+      "department": "customer-insights",
+      "tags": ["team:customer-insights", "environment:production"],
+      "soft_budget_alerting_emails": ["finops@example.com"],
+      "team_member_budget_id": "budget-1"
+    }
+  },
+  "keys": [],
+  "team_memberships": []
+}`
+
+func TestTeamCreateSendsSoftBudgetTagsAndAlertEmails(t *testing.T) {
+	var captured map[string]interface{}
+	srv := newTeamTestServer(t, &captured, teamInfoWithSoftBudget)
+	defer srv.Close()
+
+	d := schema.TestResourceDataRaw(t, ResourceLiteLLMTeam().Schema, map[string]interface{}{
+		"team_alias":                  "insights",
+		"max_budget":                  750.0,
+		"soft_budget":                 600.0,
+		"tags":                        []interface{}{"team:customer-insights", "environment:production"},
+		"soft_budget_alerting_emails": []interface{}{"finops@example.com"},
+		"metadata":                    map[string]interface{}{"department": "customer-insights"},
+	})
+
+	if err := resourceLiteLLMTeamCreate(d, NewClient(srv.URL, "test-key", true)); err != nil {
+		t.Fatalf("create failed: %v", err)
+	}
+
+	if got := captured["soft_budget"]; got != 600.0 {
+		t.Fatalf("payload soft_budget = %v, want 600", got)
+	}
+	wantTags := []interface{}{"team:customer-insights", "environment:production"}
+	if got := captured["tags"]; !reflect.DeepEqual(got, wantTags) {
+		t.Fatalf("payload tags = %v, want %v", got, wantTags)
+	}
+	wantMetadata := map[string]interface{}{
+		"department":                  "customer-insights",
+		"soft_budget_alerting_emails": []interface{}{"finops@example.com"},
+	}
+	if got := captured["metadata"]; !reflect.DeepEqual(got, wantMetadata) {
+		t.Fatalf("payload metadata = %v, want %v", got, wantMetadata)
+	}
+}
+
+func TestTeamReadMapsTeamInfoEnvelope(t *testing.T) {
+	var captured map[string]interface{}
+	srv := newTeamTestServer(t, &captured, teamInfoWithSoftBudget)
+	defer srv.Close()
+
+	d := schema.TestResourceDataRaw(t, ResourceLiteLLMTeam().Schema, map[string]interface{}{})
+	d.SetId("team-1")
+
+	if err := resourceLiteLLMTeamRead(d, NewClient(srv.URL, "test-key", true)); err != nil {
+		t.Fatalf("read failed: %v", err)
+	}
+
+	if got := d.Get("team_alias"); got != "insights" {
+		t.Fatalf("team_alias = %v, want insights", got)
+	}
+	if got := d.Get("soft_budget"); got != 600.0 {
+		t.Fatalf("soft_budget = %v, want 600", got)
+	}
+	if got := d.Get("max_budget"); got != 750.0 {
+		t.Fatalf("max_budget = %v, want 750", got)
+	}
+	wantTags := []interface{}{"team:customer-insights", "environment:production"}
+	if got := d.Get("tags"); !reflect.DeepEqual(got, wantTags) {
+		t.Fatalf("tags = %v, want %v", got, wantTags)
+	}
+	wantEmails := []interface{}{"finops@example.com"}
+	if got := d.Get("soft_budget_alerting_emails"); !reflect.DeepEqual(got, wantEmails) {
+		t.Fatalf("soft_budget_alerting_emails = %v, want %v", got, wantEmails)
+	}
+	wantMetadata := map[string]interface{}{"department": "customer-insights"}
+	if got := d.Get("metadata"); !reflect.DeepEqual(got, wantMetadata) {
+		t.Fatalf("metadata = %v, want %v (server-managed team_member_budget_id dropped)", got, wantMetadata)
+	}
+}
+
+func TestTeamUpdateClearsRemovedTagsAndSoftBudget(t *testing.T) {
+	var captured map[string]interface{}
+	srv := newTeamTestServer(t, &captured, `{"team_id":"team-1","team_info":{"team_id":"team-1","team_alias":"insights"},"keys":[],"team_memberships":[]}`)
+	defer srv.Close()
+
+	res := ResourceLiteLLMTeam()
+	priorData := schema.TestResourceDataRaw(t, res.Schema, map[string]interface{}{
+		"team_alias":                  "insights",
+		"soft_budget":                 600.0,
+		"tags":                        []interface{}{"team:to-be-removed"},
+		"soft_budget_alerting_emails": []interface{}{"ops@example.com"},
+		"metadata":                    map[string]interface{}{"department": "eng"},
+	})
+	priorData.SetId("team-1")
+	prior := priorData.State()
+	config := terraform.NewResourceConfigRaw(map[string]interface{}{
+		"team_alias": "insights",
+		"metadata":   map[string]interface{}{"department": "eng"},
+	})
+	diff, err := res.Diff(context.Background(), prior, config, nil)
+	if err != nil {
+		t.Fatalf("diff failed: %v", err)
+	}
+	d, err := schema.InternalMap(res.Schema).Data(prior, diff)
+	if err != nil {
+		t.Fatalf("data failed: %v", err)
+	}
+
+	if err := resourceLiteLLMTeamUpdate(d, NewClient(srv.URL, "test-key", true)); err != nil {
+		t.Fatalf("update failed: %v", err)
+	}
+
+	if got, ok := captured["soft_budget"]; !ok || got != nil {
+		t.Fatalf("payload soft_budget = %v (present=%v), want explicit null", got, ok)
+	}
+	if got := captured["tags"]; !reflect.DeepEqual(got, []interface{}{}) {
+		t.Fatalf("payload tags = %v, want []", got)
+	}
+	if got := captured["metadata"]; !reflect.DeepEqual(got, map[string]interface{}{"department": "eng"}) {
+		t.Fatalf("payload metadata = %v, want department only", got)
+	}
+}
+
+func TestTeamReadClearsSoftBudgetWhenProxyReturnsNull(t *testing.T) {
+	var captured map[string]interface{}
+	srv := newTeamTestServer(t, &captured, `{"team_id":"team-1","team_info":{"team_id":"team-1","team_alias":"insights","soft_budget":null},"keys":[],"team_memberships":[]}`)
+	defer srv.Close()
+
+	d := schema.TestResourceDataRaw(t, ResourceLiteLLMTeam().Schema, map[string]interface{}{
+		"team_alias":  "insights",
+		"soft_budget": 600.0,
+	})
+	d.SetId("team-1")
+
+	if err := resourceLiteLLMTeamRead(d, NewClient(srv.URL, "test-key", true)); err != nil {
+		t.Fatalf("read failed: %v", err)
+	}
+
+	if got := d.Get("soft_budget"); got != 0.0 {
+		t.Fatalf("soft_budget = %v, want cleared after the proxy returned null", got)
+	}
+}
diff --git a/terraform/provider/litellm/types.go b/terraform/provider/litellm/types.go
index 069fe4b3e23..66d1f6a8ba9 100644
--- a/terraform/provider/litellm/types.go
+++ b/terraform/provider/litellm/types.go
@@ -33,6 +33,11 @@ type ModelRequest struct {
 	Additional    map[string]interface{} `json:"additional"`
 }
 
+type TeamInfoResponse struct {
+	TeamID   string       `json:"team_id"`
+	TeamInfo TeamResponse `json:"team_info"`
+}
+
 // TeamResponse represents a response from the API containing team information.
 type TeamResponse struct {
 	TeamID                string                 `json:"team_id,omitempty"`
@@ -42,6 +47,7 @@ type TeamResponse struct {
 	TPMLimit              *int                   `json:"tpm_limit,omitempty"`
 	RPMLimit              *int                   `json:"rpm_limit,omitempty"`
 	MaxBudget             *float64               `json:"max_budget,omitempty"`
+	SoftBudget            *float64               `json:"soft_budget,omitempty"`
 	BudgetDuration        string                 `json:"budget_duration,omitempty"`
 	Models                []string               `json:"models"`
 	Blocked               bool                   `json:"blocked,omitempty"`

From 5f56be3294b753e8418defafe36e99f669263720 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Mon, 24 Aug 2026 10:12:16 -0700
Subject: [PATCH 86/93] fix(ui): theme the created-key box so it follows dark
 mode (#37985)

The virtual key shown after creating a key sits in a div with a
hardcoded #f8f8f8 inline background, so in dark mode the box keeps
the light background while the key text inherits the light foreground
color, leaving the key nearly unreadable. Swap the inline styles for
the bg-muted and text-foreground tokens, which resolve per theme.
---
 .../src/components/shared/CreatedKeyDisplay.test.tsx  |  9 +++++++++
 .../src/components/shared/CreatedKeyDisplay.tsx       | 11 ++---------
 2 files changed, 11 insertions(+), 9 deletions(-)

diff --git a/ui/litellm-dashboard/src/components/shared/CreatedKeyDisplay.test.tsx b/ui/litellm-dashboard/src/components/shared/CreatedKeyDisplay.test.tsx
index 6c8cdae6deb..0e10d32f8d1 100644
--- a/ui/litellm-dashboard/src/components/shared/CreatedKeyDisplay.test.tsx
+++ b/ui/litellm-dashboard/src/components/shared/CreatedKeyDisplay.test.tsx
@@ -19,6 +19,15 @@ describe("CreatedKeyDisplay", () => {
     expect(screen.getByText("sk-test-123")).toBeInTheDocument();
   });
 
+  it("should theme the key box with tokens instead of a hardcoded light background", () => {
+    render(<CreatedKeyDisplay apiKey="sk-test-123" />);
+
+    const keyBox = screen.getByText("sk-test-123").parentElement as HTMLElement;
+
+    expect(keyBox).not.toHaveAttribute("style");
+    expect(keyBox).toHaveClass("bg-muted");
+  });
+
   it("should display the security warning", () => {
     render(<CreatedKeyDisplay apiKey="sk-test-123" />);
     expect(screen.getByText(/you will not be able to view it again/i)).toBeInTheDocument();
diff --git a/ui/litellm-dashboard/src/components/shared/CreatedKeyDisplay.tsx b/ui/litellm-dashboard/src/components/shared/CreatedKeyDisplay.tsx
index c14379378d3..5dbc17b13bf 100644
--- a/ui/litellm-dashboard/src/components/shared/CreatedKeyDisplay.tsx
+++ b/ui/litellm-dashboard/src/components/shared/CreatedKeyDisplay.tsx
@@ -29,15 +29,8 @@ const CreatedKeyDisplay: React.FC<CreatedKeyDisplayProps> = ({ apiKey }) => {
       </p>
 
       <p className="text-sm text-muted-foreground mt-3 mb-1">Virtual Key:</p>
-      <div
-        style={{
-          background: "#f8f8f8",
-          padding: "10px",
-          borderRadius: "5px",
-          marginBottom: "10px",
-        }}
-      >
-        <pre style={{ wordWrap: "break-word", whiteSpace: "normal", margin: 0 }}>{apiKey}</pre>
+      <div className="bg-muted rounded-md p-2.5 mb-2.5">
+        <pre className="m-0 whitespace-normal break-words text-foreground">{apiKey}</pre>
       </div>
 
       <CopyToClipboard text={apiKey} onCopy={handleCopy}>

From 6db5a5d6605114c672e2ef3c0fff6a5f76f56721 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Mon, 24 Aug 2026 10:12:46 -0700
Subject: [PATCH 87/93] fix(ui): restore the public model name tooltip layout
 in the add model flow (#37986)

The tooltip popup is an inline-flex row, so the four sibling blocks passed as a fragment laid out side by side in four columns. Wrap them in a single flex-col container instead.

The inline code samples also used bg-muted, which is defined against the page surface, not the inverted tooltip surface, so they rendered as near-white chips carrying near-white text. Tint them from the popup's own token instead.
---
 .../conditional_public_model_name.tsx         | 24 ++++++++++---------
 1 file changed, 13 insertions(+), 11 deletions(-)

diff --git a/ui/litellm-dashboard/src/components/add_model/conditional_public_model_name.tsx b/ui/litellm-dashboard/src/components/add_model/conditional_public_model_name.tsx
index b9c128a3d51..c58b177a6e1 100644
--- a/ui/litellm-dashboard/src/components/add_model/conditional_public_model_name.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/conditional_public_model_name.tsx
@@ -34,6 +34,8 @@ const modelMappingsRule = {
   },
 };
 
+const tooltipCodeClassName = "rounded-sm bg-background/20 px-1 py-0.5 font-mono text-xs";
+
 const ConditionalPublicModelName: React.FC = () => {
   const form = useFormContext<MountedFormValues>();
 
@@ -123,22 +125,22 @@ const ConditionalPublicModelName: React.FC = () => {
   if (!showPublicModelName) return null;
 
   const publicNameTooltipContent = (
-    <>
-      <div className="mb-2 font-normal">The name you specify in your API calls to LiteLLM Proxy</div>
-      <div className="mb-2 font-normal">
+    <div className="flex flex-col gap-2 text-left font-normal">
+      <div>The name you specify in your API calls to LiteLLM Proxy</div>
+      <div>
         <strong>Example:</strong> If you name your public model{" "}
-        <code className="bg-muted px-1 py-0.5 rounded-sm text-xs">example-name</code>, and choose{" "}
-        <code className="bg-muted px-1 py-0.5 rounded-sm text-xs">openai/qwen-plus-latest</code> as the LiteLLM model
+        <code className={tooltipCodeClassName}>example-name</code>, and choose{" "}
+        <code className={tooltipCodeClassName}>openai/qwen-plus-latest</code> as the LiteLLM model
       </div>
-      <div className="mb-2 font-normal">
+      <div>
         <strong>Usage:</strong> You make an API call to the LiteLLM proxy with{" "}
-        <code className="bg-muted px-1 py-0.5 rounded-sm text-xs">model = &quot;example-name&quot;</code>
+        <code className={tooltipCodeClassName}>model = &quot;example-name&quot;</code>
       </div>
-      <div className="font-normal">
-        <strong>Result:</strong> LiteLLM sends{" "}
-        <code className="bg-muted px-1 py-0.5 rounded-sm text-xs">qwen-plus-latest</code> to the provider
+      <div>
+        <strong>Result:</strong> LiteLLM sends <code className={tooltipCodeClassName}>qwen-plus-latest</code> to the
+        provider
       </div>
-    </>
+    </div>
   );
 
   const liteLLMModelTooltipContent = <div>The model name LiteLLM will send to the LLM API</div>;

From 5b1c142c6e2aeee84360cad44192f382510c6c04 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Mon, 24 Aug 2026 10:12:52 -0700
Subject: [PATCH 88/93] fix(ui): render team and org tpm/rpm limits of 0 as 0
 instead of Unlimited (#37916)

* fix(ui): render team and org tpm/rpm limits of 0 as 0 instead of Unlimited

A tpm_limit or rpm_limit of 0 is a hard block on the backend (every request 429s) and only null means unlimited, but the team and organization views rendered both as "Unlimited" (and a team-member limit of 0 as "No Limit") because every display site used a falsy || fallback. The team member edit dialog also seeded its form with `tpm_limit || null`, so opening Edit Member on a member stored with 0 and clicking Save sent null to /team/member_update and silently turned the hard block into unlimited

Every limit display site in TeamInfo, organization_view, the organizations list cell and the team members table now uses a nullish check, and both member form seeding paths keep 0 for max_budget_in_team, tpm_limit and rpm_limit. Regression tests cover each site and the existing memberFormValues test that asserted 0 -> null is flipped to assert 0 survives

Resolves LIT-5760

* test(ui): assert a stored 0 member limit survives an untouched save

The EditMembership integration test named the old 0 -> null collapse as the expected payload, so the related-tests CI job went red once the form kept 0. It now asserts 0 survives and only the empty budget_duration collapses to null. The TeamMemberTab fixture is built with a map instead of mutating the nested membership
---
 .../_components/OrganizationsTable.test.tsx   | 14 +++++++
 .../_components/OrganizationsTableColumns.tsx |  4 +-
 .../organization/organization_view.test.tsx   | 36 ++++++++++++++++-
 .../organization/organization_view.tsx        |  8 ++--
 .../team/EditMembership.integration.test.tsx  |  8 ++--
 .../src/components/team/TeamInfo.test.tsx     | 28 +++++++++++++
 .../src/components/team/TeamInfo.tsx          | 14 +++----
 .../components/team/TeamMemberTab.test.tsx    | 39 ++++++++++++++++++-
 .../src/components/team/TeamMemberTab.tsx     | 10 ++---
 .../components/team/memberFormValues.test.ts  | 20 +++++++++-
 .../src/components/team/memberFormValues.ts   |  6 +--
 11 files changed, 158 insertions(+), 29 deletions(-)

diff --git a/ui/litellm-dashboard/src/app/(dashboard)/organizations/_components/OrganizationsTable.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/organizations/_components/OrganizationsTable.test.tsx
index a06c5c885e3..1ac33a27186 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/organizations/_components/OrganizationsTable.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/organizations/_components/OrganizationsTable.test.tsx
@@ -165,6 +165,20 @@ describe("OrganizationsTable", () => {
     expect(screen.getByText("RPM: Unlimited")).toBeInTheDocument();
   });
 
+  it("renders a tpm/rpm limit of 0 as 0, never as Unlimited", () => {
+    render(
+      <OrganizationsTable
+        {...baseProps}
+        organizations={[makeOrganization({ litellm_budget_table: { max_budget: null, tpm_limit: 0, rpm_limit: 0 } })]}
+      />,
+    );
+
+    expect(screen.getByText("TPM: 0")).toBeInTheDocument();
+    expect(screen.getByText("RPM: 0")).toBeInTheDocument();
+    expect(screen.queryByText("TPM: Unlimited")).not.toBeInTheDocument();
+    expect(screen.queryByText("RPM: Unlimited")).not.toBeInTheDocument();
+  });
+
   it("renders loading skeletons instead of rows while loading", () => {
     render(
       <OrganizationsTable
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/organizations/_components/OrganizationsTableColumns.tsx b/ui/litellm-dashboard/src/app/(dashboard)/organizations/_components/OrganizationsTableColumns.tsx
index 31f6a00916c..0fea6c6606e 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/organizations/_components/OrganizationsTableColumns.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/organizations/_components/OrganizationsTableColumns.tsx
@@ -28,8 +28,8 @@ function OrganizationLimitsCell({ organization }: { organization: Organization }
   const { tpm_limit, rpm_limit } = getOrganizationBudget(organization);
   return (
     <div className="flex flex-col text-xs text-muted-foreground">
-      <span>TPM: {tpm_limit ? tpm_limit : "Unlimited"}</span>
-      <span>RPM: {rpm_limit ? rpm_limit : "Unlimited"}</span>
+      <span>TPM: {tpm_limit ?? "Unlimited"}</span>
+      <span>RPM: {rpm_limit ?? "Unlimited"}</span>
     </div>
   );
 }
diff --git a/ui/litellm-dashboard/src/components/organization/organization_view.test.tsx b/ui/litellm-dashboard/src/components/organization/organization_view.test.tsx
index 0337fea4131..b8d8e3ba9c8 100644
--- a/ui/litellm-dashboard/src/components/organization/organization_view.test.tsx
+++ b/ui/litellm-dashboard/src/components/organization/organization_view.test.tsx
@@ -1,5 +1,5 @@
 import React from "react";
-import { fireEvent, screen, waitFor } from "@testing-library/react";
+import { fireEvent, screen, waitFor, within } from "@testing-library/react";
 import userEvent from "@testing-library/user-event";
 import { vi, test, expect, beforeEach } from "vitest";
 import { renderWithProviders } from "../../../tests/test-utils";
@@ -290,3 +290,37 @@ test("should keep unsaved settings edits when switching tabs and back", async ()
 
   expect(screen.getByLabelText(/Organization Name/i)).toHaveValue("Renamed Org");
 });
+
+test("renders a tpm/rpm limit of 0 as 0 in the overview and settings tabs, never as Unlimited", async () => {
+  const zeroLimitOrg = {
+    ...mockOrg,
+    litellm_budget_table: { ...mockOrg.litellm_budget_table, tpm_limit: 0, rpm_limit: 0 },
+  };
+  mockUseOrganization.mockReturnValue({ data: zeroLimitOrg, isLoading: false } as unknown as ReturnType<
+    typeof useOrganization
+  >);
+
+  const user = userEvent.setup();
+  renderWithProviders(
+    <OrganizationInfoView
+      organizationId="org_123"
+      onClose={() => {}}
+      accessToken="test-token"
+      is_org_admin={false}
+      is_proxy_admin={true}
+      userModels={[]}
+      editOrg={false}
+    />,
+  );
+
+  const overview = await screen.findByRole("tabpanel", { name: "Overview" });
+  expect(within(overview).getByText("TPM: 0")).toBeInTheDocument();
+  expect(within(overview).getByText("RPM: 0")).toBeInTheDocument();
+
+  await user.click(screen.getByRole("tab", { name: "Settings" }));
+  const settings = await screen.findByRole("tabpanel", { name: "Settings" });
+  expect(within(settings).getByText("TPM: 0")).toBeInTheDocument();
+  expect(within(settings).getByText("RPM: 0")).toBeInTheDocument();
+  expect(screen.queryByText("TPM: Unlimited")).not.toBeInTheDocument();
+  expect(screen.queryByText("RPM: Unlimited")).not.toBeInTheDocument();
+});
diff --git a/ui/litellm-dashboard/src/components/organization/organization_view.tsx b/ui/litellm-dashboard/src/components/organization/organization_view.tsx
index 2590f3bad52..7c250a5ef98 100644
--- a/ui/litellm-dashboard/src/components/organization/organization_view.tsx
+++ b/ui/litellm-dashboard/src/components/organization/organization_view.tsx
@@ -206,8 +206,8 @@ const OrganizationInfoView: React.FC<OrganizationInfoProps> = ({
               <CardContent>
                 <p className="text-sm text-muted-foreground">Rate Limits</p>
                 <div className="mt-2 text-sm text-foreground">
-                  <p>TPM: {orgData.litellm_budget_table.tpm_limit || "Unlimited"}</p>
-                  <p>RPM: {orgData.litellm_budget_table.rpm_limit || "Unlimited"}</p>
+                  <p>TPM: {orgData.litellm_budget_table.tpm_limit ?? "Unlimited"}</p>
+                  <p>RPM: {orgData.litellm_budget_table.rpm_limit ?? "Unlimited"}</p>
                   {orgData.litellm_budget_table.max_parallel_requests && (
                     <p>Max Parallel Requests: {orgData.litellm_budget_table.max_parallel_requests}</p>
                   )}
@@ -311,8 +311,8 @@ const OrganizationInfoView: React.FC<OrganizationInfoProps> = ({
                   </div>
                   <div>
                     <p className="font-medium text-foreground">Rate Limits</p>
-                    <div>TPM: {orgData.litellm_budget_table.tpm_limit || "Unlimited"}</div>
-                    <div>RPM: {orgData.litellm_budget_table.rpm_limit || "Unlimited"}</div>
+                    <div>TPM: {orgData.litellm_budget_table.tpm_limit ?? "Unlimited"}</div>
+                    <div>RPM: {orgData.litellm_budget_table.rpm_limit ?? "Unlimited"}</div>
                   </div>
                   <div>
                     <p className="font-medium text-foreground">Budget</p>
diff --git a/ui/litellm-dashboard/src/components/team/EditMembership.integration.test.tsx b/ui/litellm-dashboard/src/components/team/EditMembership.integration.test.tsx
index b1dd3a2efcb..a82f475512c 100644
--- a/ui/litellm-dashboard/src/components/team/EditMembership.integration.test.tsx
+++ b/ui/litellm-dashboard/src/components/team/EditMembership.integration.test.tsx
@@ -110,7 +110,7 @@ describe("EditMembership submit payload", () => {
     expect(submitted()).toStrictEqual(expected);
   });
 
-  it("collapses falsy budget and limit values to null and a missing model list to an empty array", async () => {
+  it("keeps stored 0 budget and limits as 0 on an untouched save, collapsing only empty strings and a missing model list", async () => {
     renderEdit(teamMemberConfig, {
       user_id: "u1",
       user_email: "a@b.com",
@@ -128,10 +128,10 @@ describe("EditMembership submit payload", () => {
       user_email: "a@b.com",
       user_id: "u1",
       role: "user",
-      max_budget_in_team: null,
+      max_budget_in_team: 0,
       budget_duration: null,
-      tpm_limit: null,
-      rpm_limit: null,
+      tpm_limit: 0,
+      rpm_limit: 0,
       allowed_models: [],
     });
   });
diff --git a/ui/litellm-dashboard/src/components/team/TeamInfo.test.tsx b/ui/litellm-dashboard/src/components/team/TeamInfo.test.tsx
index a7e8e6788dd..c3cc362e29e 100644
--- a/ui/litellm-dashboard/src/components/team/TeamInfo.test.tsx
+++ b/ui/litellm-dashboard/src/components/team/TeamInfo.test.tsx
@@ -319,6 +319,34 @@ describe("TeamInfoView", () => {
       expect(screen.getByText(/of \$1,000\.00/)).toBeInTheDocument();
     });
 
+    it("renders a tpm/rpm/budget limit of 0 as 0 in the overview and settings tabs, never as Unlimited or No Limit", async () => {
+      vi.mocked(networking.teamInfoCall).mockResolvedValue(
+        createMockTeamData({
+          tpm_limit: 0,
+          rpm_limit: 0,
+          team_member_budget_table: { max_budget: 0, budget_duration: null, tpm_limit: 0, rpm_limit: 0 },
+        }),
+      );
+
+      renderWithProviders(<TeamInfoView {...defaultProps} />);
+
+      const overview = await screen.findByRole("tabpanel", { name: "Overview" });
+      expect(within(overview).getByText("TPM: 0")).toBeInTheDocument();
+      expect(within(overview).getByText("RPM: 0")).toBeInTheDocument();
+
+      await userEvent.setup({ delay: null }).click(screen.getByRole("tab", { name: "Settings" }));
+      const settings = await screen.findByRole("tabpanel", { name: "Settings" });
+      expect(within(settings).getByText("TPM: 0")).toBeInTheDocument();
+      expect(within(settings).getByText("RPM: 0")).toBeInTheDocument();
+      expect(within(settings).getByText("TPM Limit: 0")).toBeInTheDocument();
+      expect(within(settings).getByText("RPM Limit: 0")).toBeInTheDocument();
+      expect(within(settings).getByText("Max Budget: 0")).toBeInTheDocument();
+      expect(screen.queryByText("TPM: Unlimited")).not.toBeInTheDocument();
+      expect(screen.queryByText("RPM: Unlimited")).not.toBeInTheDocument();
+      expect(screen.queryByText("TPM Limit: No Limit")).not.toBeInTheDocument();
+      expect(screen.queryByText("RPM Limit: No Limit")).not.toBeInTheDocument();
+    });
+
     it("should display guardrails in overview when present", async () => {
       vi.mocked(networking.teamInfoCall).mockResolvedValue(
         createMockTeamData({
diff --git a/ui/litellm-dashboard/src/components/team/TeamInfo.tsx b/ui/litellm-dashboard/src/components/team/TeamInfo.tsx
index 727445e4fcd..88a893fd3e4 100644
--- a/ui/litellm-dashboard/src/components/team/TeamInfo.tsx
+++ b/ui/litellm-dashboard/src/components/team/TeamInfo.tsx
@@ -971,8 +971,8 @@ const TeamInfoView: React.FC<TeamInfoProps> = ({
           <Card className="block p-6">
             <p>Rate Limits</p>
             <div className="mt-2">
-              <p>TPM: {info.tpm_limit || "Unlimited"}</p>
-              <p>RPM: {info.rpm_limit || "Unlimited"}</p>
+              <p>TPM: {info.tpm_limit ?? "Unlimited"}</p>
+              <p>RPM: {info.rpm_limit ?? "Unlimited"}</p>
               {info.max_parallel_requests && <p>Max Parallel Requests: {info.max_parallel_requests}</p>}
               {(() => {
                 const modelTpm = (info.metadata?.model_tpm_limit ?? {}) as Record<string, number>;
@@ -1760,8 +1760,8 @@ const TeamInfoView: React.FC<TeamInfoProps> = ({
               </div>
               <div>
                 <p className="font-medium">Rate Limits</p>
-                <div>TPM: {info.tpm_limit || "Unlimited"}</div>
-                <div>RPM: {info.rpm_limit || "Unlimited"}</div>
+                <div>TPM: {info.tpm_limit ?? "Unlimited"}</div>
+                <div>RPM: {info.rpm_limit ?? "Unlimited"}</div>
                 {(() => {
                   const modelTpm = (info.metadata?.model_tpm_limit ?? {}) as Record<string, number>;
                   const modelRpm = (info.metadata?.model_rpm_limit ?? {}) as Record<string, number>;
@@ -1811,11 +1811,11 @@ const TeamInfoView: React.FC<TeamInfoProps> = ({
                     <Info className="ml-1 inline size-3.5 align-text-bottom" />
                   </SimpleTooltip>
                 </p>
-                <div>Max Budget: {info.team_member_budget_table?.max_budget || "No Limit"}</div>
+                <div>Max Budget: {info.team_member_budget_table?.max_budget ?? "No Limit"}</div>
                 <div>Budget Duration: {info.team_member_budget_table?.budget_duration || "No Limit"}</div>
                 <div>Key Duration: {info.metadata?.team_member_key_duration || "No Limit"}</div>
-                <div>TPM Limit: {info.team_member_budget_table?.tpm_limit || "No Limit"}</div>
-                <div>RPM Limit: {info.team_member_budget_table?.rpm_limit || "No Limit"}</div>
+                <div>TPM Limit: {info.team_member_budget_table?.tpm_limit ?? "No Limit"}</div>
+                <div>RPM Limit: {info.team_member_budget_table?.rpm_limit ?? "No Limit"}</div>
               </div>
               <div>
                 <p className="font-medium">Router Settings</p>
diff --git a/ui/litellm-dashboard/src/components/team/TeamMemberTab.test.tsx b/ui/litellm-dashboard/src/components/team/TeamMemberTab.test.tsx
index 04234cf5a5e..6711514bfe9 100644
--- a/ui/litellm-dashboard/src/components/team/TeamMemberTab.test.tsx
+++ b/ui/litellm-dashboard/src/components/team/TeamMemberTab.test.tsx
@@ -1,4 +1,4 @@
-import { screen } from "@testing-library/react";
+import { screen, within } from "@testing-library/react";
 import userEvent from "@testing-library/user-event";
 import { beforeEach, describe, expect, it, vi } from "vitest";
 import { renderWithProviders } from "../../../tests/test-utils";
@@ -322,6 +322,43 @@ describe("TeamMembersComponent", () => {
     expect(mockSetSelectedEditMember).toHaveBeenCalled();
   });
 
+  it("keeps a member's stored 0 limits as 0 in the table and in the edit payload, never unlimited", async () => {
+    const user = userEvent.setup();
+    vi.mocked(isProxyAdminRole).mockReturnValue(true);
+    const baseTeamData = createMockTeamData();
+    const teamData = {
+      ...baseTeamData,
+      team_memberships: baseTeamData.team_memberships.map((membership, index) =>
+        index === 0
+          ? {
+              ...membership,
+              litellm_budget_table: { ...membership.litellm_budget_table, max_budget: 0, tpm_limit: 0, rpm_limit: 0 },
+            }
+          : membership,
+      ),
+    };
+
+    renderWithProviders(
+      <TeamMembersComponent
+        teamData={teamData}
+        canEditTeam={true}
+        handleMemberDelete={mockHandleMemberDelete}
+        setSelectedEditMember={mockSetSelectedEditMember}
+        setIsEditMemberModalVisible={mockSetIsEditMemberModalVisible}
+        setIsAddMemberModalVisible={mockSetIsAddMemberModalVisible}
+      />,
+    );
+
+    const memberRow = screen.getByRole("row", { name: /user1@test\.com/ });
+    expect(within(memberRow).getByText("0 RPM / 0 TPM")).toBeInTheDocument();
+    expect(within(memberRow).queryByText("No Limits")).not.toBeInTheDocument();
+
+    await user.click(within(memberRow).getByTestId("edit-member"));
+
+    const zeroLimitsMember = { user_id: "user1@test.com", max_budget_in_team: 0, tpm_limit: 0, rpm_limit: 0 };
+    expect(mockSetSelectedEditMember).toHaveBeenCalledWith(expect.objectContaining(zeroLimitsMember));
+  });
+
   it("should call setIsAddMemberModalVisible when Add Member button is clicked", async () => {
     const user = userEvent.setup();
 
diff --git a/ui/litellm-dashboard/src/components/team/TeamMemberTab.tsx b/ui/litellm-dashboard/src/components/team/TeamMemberTab.tsx
index a662a02f91e..4d7246eb077 100644
--- a/ui/litellm-dashboard/src/components/team/TeamMemberTab.tsx
+++ b/ui/litellm-dashboard/src/components/team/TeamMemberTab.tsx
@@ -71,8 +71,8 @@ export default function TeamMemberTab({
     const rpmLimit = membership?.litellm_budget_table?.rpm_limit;
     const tpmLimit = membership?.litellm_budget_table?.tpm_limit;
 
-    const rpmText = rpmLimit ? `${formatNumber(rpmLimit)} RPM` : null;
-    const tpmText = tpmLimit ? `${formatNumber(tpmLimit)} TPM` : null;
+    const rpmText = rpmLimit != null ? `${formatNumber(rpmLimit)} RPM` : null;
+    const tpmText = tpmLimit != null ? `${formatNumber(tpmLimit)} TPM` : null;
 
     const limits = [rpmText, tpmText].filter(Boolean);
     return limits.length > 0 ? limits.join(" / ") : "No Limits";
@@ -191,9 +191,9 @@ export default function TeamMemberTab({
         const membership = teamData.team_memberships.find((tm) => tm.user_id === record.user_id);
         const enhancedMember = {
           ...record,
-          max_budget_in_team: membership?.litellm_budget_table?.max_budget || null,
-          tpm_limit: membership?.litellm_budget_table?.tpm_limit || null,
-          rpm_limit: membership?.litellm_budget_table?.rpm_limit || null,
+          max_budget_in_team: membership?.litellm_budget_table?.max_budget ?? null,
+          tpm_limit: membership?.litellm_budget_table?.tpm_limit ?? null,
+          rpm_limit: membership?.litellm_budget_table?.rpm_limit ?? null,
           budget_duration: membership?.litellm_budget_table?.budget_duration || null,
           allowed_models: membership?.litellm_budget_table?.allowed_models || [],
         };
diff --git a/ui/litellm-dashboard/src/components/team/memberFormValues.test.ts b/ui/litellm-dashboard/src/components/team/memberFormValues.test.ts
index 398719c6197..7a1fcd85a80 100644
--- a/ui/litellm-dashboard/src/components/team/memberFormValues.test.ts
+++ b/ui/litellm-dashboard/src/components/team/memberFormValues.test.ts
@@ -82,7 +82,7 @@ describe("buildMemberFormValues", () => {
     });
   });
 
-  it("collapses falsy budgets and limits to null and a missing model list to an empty array", () => {
+  it("keeps a stored budget or limit of 0 as 0 because only null means unlimited", () => {
     expect(
       buildMemberFormValues(
         "edit",
@@ -90,6 +90,19 @@ describe("buildMemberFormValues", () => {
         teamConfig,
       ),
     ).toStrictEqual({
+      user_email: "a@b.com",
+      user_id: "u1",
+      role: "user",
+      max_budget_in_team: 0,
+      budget_duration: null,
+      tpm_limit: 0,
+      rpm_limit: 0,
+      allowed_models: [],
+    });
+  });
+
+  it("collapses missing budgets and limits to null and a missing model list to an empty array", () => {
+    const unlimitedMember = {
       user_email: "a@b.com",
       user_id: "u1",
       role: "user",
@@ -98,7 +111,10 @@ describe("buildMemberFormValues", () => {
       tpm_limit: null,
       rpm_limit: null,
       allowed_models: [],
-    });
+    };
+    expect(
+      buildMemberFormValues("edit", { user_email: "a@b.com", user_id: "u1", role: "user" }, teamConfig),
+    ).toStrictEqual(unlimitedMember);
   });
 
   it("falls back to the configured default role when the member has none", () => {
diff --git a/ui/litellm-dashboard/src/components/team/memberFormValues.ts b/ui/litellm-dashboard/src/components/team/memberFormValues.ts
index 942b9b665fe..51b8fac71c1 100644
--- a/ui/litellm-dashboard/src/components/team/memberFormValues.ts
+++ b/ui/litellm-dashboard/src/components/team/memberFormValues.ts
@@ -43,9 +43,9 @@ export const buildMemberFormValues = (
     const seeded: MemberFormValues = {
       ...initialData,
       role: (initialData.role as string) || config.defaultRole,
-      max_budget_in_team: initialData.max_budget_in_team || null,
-      tpm_limit: initialData.tpm_limit || null,
-      rpm_limit: initialData.rpm_limit || null,
+      max_budget_in_team: initialData.max_budget_in_team ?? null,
+      tpm_limit: initialData.tpm_limit ?? null,
+      rpm_limit: initialData.rpm_limit ?? null,
       budget_duration: initialData.budget_duration || null,
       allowed_models: initialData.allowed_models || [],
     };

From 7113685a76fbd77f35c031b9dd165427afe9e674 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Mon, 24 Aug 2026 10:12:55 -0700
Subject: [PATCH 89/93] fix(ui): repoint the key detail URL to the rotated hash
 after regenerating (#37968)

Regenerating a key from the key info page left the ?key= query param on the
old hash, so dismissing the dialog or reloading landed on a key that no longer
exists and the page rendered "Key not found".

Two defects had to line up. POST /key/{key}/regenerate returns the rotated
hash in token_id and leaves token null, but RegenerateKeyModal read
response.token || response.key_id, neither of which the endpoint populates, so
it always reported the old hash back to its parent. And KeyInfoView's
onKeyDataUpdate prop had no caller anywhere in the tree: VirtualKeysTable owns
the ?key= param and mounts the view but never passed it, so even a correct
hash went nowhere.

VirtualKeysTable now handles the update by pointing ?key= at the rotated hash
and refetching. KeyInfoView holds that callback until the regenerate dialog is
dismissed rather than firing it on the API response, because swapping the
selected key mid-dialog unmounts the view and tears down the one-time
plaintext key before the user can copy it.
---
 .../VirtualKeysPage/VirtualKeysTable.test.tsx | 28 +++++++++++++++++++
 .../VirtualKeysPage/VirtualKeysTable.tsx      | 13 ++++++++-
 .../organisms/RegenerateKeyModal.test.tsx     | 17 +++++++++++
 .../organisms/RegenerateKeyModal.tsx          |  2 +-
 .../components/templates/key_info_view.tsx    | 26 +++++++++++------
 5 files changed, 76 insertions(+), 10 deletions(-)

diff --git a/ui/litellm-dashboard/src/components/VirtualKeysPage/VirtualKeysTable.test.tsx b/ui/litellm-dashboard/src/components/VirtualKeysPage/VirtualKeysTable.test.tsx
index 9ef849dbeb2..643da71e8b1 100644
--- a/ui/litellm-dashboard/src/components/VirtualKeysPage/VirtualKeysTable.test.tsx
+++ b/ui/litellm-dashboard/src/components/VirtualKeysPage/VirtualKeysTable.test.tsx
@@ -8,6 +8,7 @@ import { KeyResponse, Team } from "../key_team_helpers/key_list";
 import { useKeyInfo } from "@/app/(dashboard)/hooks/keys/useKeyInfo";
 import { KeysResponse, useKeys } from "@/app/(dashboard)/hooks/keys/useKeys";
 import useTeams from "@/app/(dashboard)/hooks/useTeams";
+import { regenerateKeyCall } from "../networking";
 
 // Resolve debounced values synchronously so an applied filter lands in the useKeys query within the test tick.
 vi.mock("@tanstack/react-pacer/debouncer", async () => {
@@ -25,6 +26,11 @@ vi.mock("@tanstack/react-pacer/debouncer", async () => {
 
 vi.mock("next/navigation", () => ({ useRouter: () => ({ push: vi.fn() }) }));
 
+vi.mock("../networking", async (importOriginal) => ({
+  ...(await importOriginal<typeof import("../networking")>()),
+  regenerateKeyCall: vi.fn(),
+}));
+
 vi.mock("@/app/(dashboard)/hooks/useAuthorized", () => ({
   default: vi.fn(() => ({
     accessToken: "test-token",
@@ -389,6 +395,28 @@ it("renders KeyInfoView when the URL has ?key= for a key on the current page, wi
   expect(screen.getByTestId("pagination-range")).toBeInTheDocument();
 });
 
+it("repoints ?key= to the rotated hash once the regenerate dialog is dismissed", async () => {
+  const user = userEvent.setup();
+  vi.mocked(regenerateKeyCall).mockResolvedValue({
+    key: "sk-rotated-plaintext",
+    token: null,
+    token_id: "rotated-hash-456",
+  });
+  const onUrlUpdate = vi.fn<OnUrlUpdateFunction>();
+  renderWithProviders(<VirtualKeysTable />, { searchParams: { key: mockKey.token }, onUrlUpdate });
+
+  await user.click(await screen.findByRole("button", { name: /regenerate key/i }));
+  await user.click(await screen.findByRole("button", { name: /^Regenerate$/ }));
+  expect(await screen.findAllByText("sk-rotated-plaintext")).not.toHaveLength(0);
+  expect(lastKeyParam(onUrlUpdate)).toBeUndefined();
+
+  await user.click(screen.getAllByRole("button", { name: "Close" })[0]);
+
+  await waitFor(() => {
+    expect(lastKeyParam(onUrlUpdate)).toBe("rotated-hash-456");
+  });
+});
+
 it("fetches the key by id when the URL has ?key= for a key not in the loaded page", async () => {
   mockUseKeyInfo.mockReturnValue(
     keyInfoResult({ ...mockKey, token: "other-key-hash", key_alias: "Fetched Key Alias" }),
diff --git a/ui/litellm-dashboard/src/components/VirtualKeysPage/VirtualKeysTable.tsx b/ui/litellm-dashboard/src/components/VirtualKeysPage/VirtualKeysTable.tsx
index b278b4f675d..fbdcf2d8d83 100644
--- a/ui/litellm-dashboard/src/components/VirtualKeysPage/VirtualKeysTable.tsx
+++ b/ui/litellm-dashboard/src/components/VirtualKeysPage/VirtualKeysTable.tsx
@@ -20,7 +20,7 @@ import { KeyRound } from "lucide-react";
 import { parseAsString, useQueryState } from "nuqs";
 import React, { useCallback, useMemo, useState } from "react";
 
-import { Team } from "../key_team_helpers/key_list";
+import { KeyResponse, Team } from "../key_team_helpers/key_list";
 import KeyInfoView from "../templates/key_info_view";
 import { getKeyTableColumns, KEY_TABLE_HIDDEN_COLUMNS } from "./keyTableColumns";
 
@@ -139,6 +139,16 @@ export function VirtualKeysTable({ headerActions }: VirtualKeysTableProps) {
     [organizations],
   );
 
+  const handleSelectedKeyDataUpdate = useCallback(
+    (updated: Partial<KeyResponse>) => {
+      const rotatedToken = updated.token ?? updated.token_id;
+      if (!rotatedToken || rotatedToken === selectedKeyId) return;
+      void setSelectedKeyId(rotatedToken);
+      void refetch();
+    },
+    [refetch, selectedKeyId, setSelectedKeyId],
+  );
+
   const formatFilterValue = useCallback(
     (columnId: string, value: unknown): string => {
       const raw = String(value);
@@ -165,6 +175,7 @@ export function VirtualKeysTable({ headerActions }: VirtualKeysTableProps) {
           keyData={selectedKey}
           teams={allTeams}
           onDelete={refetch}
+          onKeyDataUpdate={handleSelectedKeyDataUpdate}
         />
       </div>
     );
diff --git a/ui/litellm-dashboard/src/components/organisms/RegenerateKeyModal.test.tsx b/ui/litellm-dashboard/src/components/organisms/RegenerateKeyModal.test.tsx
index 180f9d1f265..262ce9669f2 100644
--- a/ui/litellm-dashboard/src/components/organisms/RegenerateKeyModal.test.tsx
+++ b/ui/litellm-dashboard/src/components/organisms/RegenerateKeyModal.test.tsx
@@ -427,4 +427,21 @@ describe("RegenerateKeyModal", () => {
       );
     });
   });
+
+  it("should report the rotated hash from token_id when the API leaves token null", async () => {
+    const user = userEvent.setup();
+    mockRegenerateKeyCall.mockResolvedValue({
+      key: "sk-new-regenerated-key",
+      token: null,
+      token_id: "rotated-hash-456",
+    });
+
+    renderWithProviders(<RegenerateKeyModal {...defaultProps} />);
+    await user.click(screen.getByRole("button", { name: /Regenerate/ }));
+
+    await waitFor(() => {
+      expect(mockOnKeyUpdate).toHaveBeenCalledOnce();
+    });
+    expect(mockOnKeyUpdate.mock.calls[0][0].token).toBe("rotated-hash-456");
+  });
 });
diff --git a/ui/litellm-dashboard/src/components/organisms/RegenerateKeyModal.tsx b/ui/litellm-dashboard/src/components/organisms/RegenerateKeyModal.tsx
index d85e6cb5f91..a2658985f32 100644
--- a/ui/litellm-dashboard/src/components/organisms/RegenerateKeyModal.tsx
+++ b/ui/litellm-dashboard/src/components/organisms/RegenerateKeyModal.tsx
@@ -107,7 +107,7 @@ export function RegenerateKeyModal({ selectedToken, visible, onClose, onKeyUpdat
       // formatted preview, otherwise downstream expiry parsing breaks.
       const updatedKeyData: Partial<KeyResponse> = {
         ...response,
-        token: response.token || response.key_id || selectedToken.token,
+        token: response.token_id || response.token || selectedToken.token,
         key_name: response.key,
         max_budget: formValues.max_budget,
         tpm_limit: formValues.tpm_limit,
diff --git a/ui/litellm-dashboard/src/components/templates/key_info_view.tsx b/ui/litellm-dashboard/src/components/templates/key_info_view.tsx
index 5cfa737397b..59950303c45 100644
--- a/ui/litellm-dashboard/src/components/templates/key_info_view.tsx
+++ b/ui/litellm-dashboard/src/components/templates/key_info_view.tsx
@@ -100,6 +100,9 @@ export default function KeyInfoView({
   // Add local state to maintain key data and track regeneration
   const [currentKeyData, setCurrentKeyData] = useState<KeyResponse | undefined>(keyData);
   const [lastRegeneratedAt, setLastRegeneratedAt] = useState<Date | null>(null);
+  const [keyDataUpdateHeldUntilModalClose, setKeyDataUpdateHeldUntilModalClose] = useState<Partial<KeyResponse> | null>(
+    null,
+  );
   const [isRecentlyRegenerated, setIsRecentlyRegenerated] = useState(false);
   const [policyGuardrails, setPolicyGuardrails] = useState<Record<string, string[]>>({});
   const [loadingPolicies, setLoadingPolicies] = useState(false);
@@ -352,6 +355,7 @@ export default function KeyInfoView({
   };
 
   const handleRegenerateKeyUpdate = (updatedKeyData: Partial<KeyResponse>) => {
+    const regeneratedAt = new Date();
     // Update local state immediately with ALL the new data
     setCurrentKeyData((prevData) => {
       if (!prevData) return undefined;
@@ -359,20 +363,26 @@ export default function KeyInfoView({
         ...prevData,
         ...updatedKeyData, // This should include the new token (key-id)
         // Update the created_at to show when it was regenerated
-        created_at: new Date().toLocaleString(),
+        created_at: regeneratedAt.toLocaleString(),
       };
       return newData;
     });
 
     // Track regeneration timestamp
-    setLastRegeneratedAt(new Date());
+    setLastRegeneratedAt(regeneratedAt);
     setIsRecentlyRegenerated(true);
 
-    if (onKeyDataUpdate) {
-      onKeyDataUpdate({
-        ...updatedKeyData,
-        created_at: new Date().toLocaleString(),
-      });
+    setKeyDataUpdateHeldUntilModalClose({
+      ...updatedKeyData,
+      created_at: regeneratedAt.toLocaleString(),
+    });
+  };
+
+  const handleRegenerateModalClose = () => {
+    setIsRegenerateModalOpen(false);
+    if (keyDataUpdateHeldUntilModalClose) {
+      setKeyDataUpdateHeldUntilModalClose(null);
+      onKeyDataUpdate?.(keyDataUpdateHeldUntilModalClose);
     }
   };
 
@@ -506,7 +516,7 @@ export default function KeyInfoView({
       <RegenerateKeyModal
         selectedToken={currentKeyData}
         visible={isRegenerateModalOpen}
-        onClose={() => setIsRegenerateModalOpen(false)}
+        onClose={handleRegenerateModalClose}
         onKeyUpdate={handleRegenerateKeyUpdate}
       />
 

From 3fb1009f816fbe96e90c6cc14d4a2ea36463f5eb Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Mon, 24 Aug 2026 10:13:24 -0700
Subject: [PATCH 90/93] fix(ui): make playground chat bubbles theme-aware
 (#37978)

The playground message bubble painted its fill, border and avatar circle from
inline hex values, so in dark mode both bubbles stayed near-white while the text
inherited the dark foreground: the message body was unreadable. The MCP-events
placeholder bubble in ChatUI carried the same three fills.

They move onto the tokens the rest of the sweep already uses, so the assistant
surface is bg-card over border-border and the user surface is the info tint at
the same weight the other selected-state surfaces take. Light mode keeps the
same colour family it had.

The regression test asserts the token classes and that no inline style survives
on either surface, which is the exact shape the bug took.
---
 .../chat_ui/ChatMessageBubble.test.tsx           | 15 +++++++++++++++
 .../components/chat_ui/ChatMessageBubble.tsx     | 16 ++++++----------
 .../playground/components/chat_ui/ChatUI.tsx     | 14 ++------------
 3 files changed, 23 insertions(+), 22 deletions(-)

diff --git a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.test.tsx
index c218db5b914..a83c11d1444 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.test.tsx
@@ -87,6 +87,21 @@ describe("ChatMessageBubble", () => {
     expect(screen.getByText("Hi there")).toBeInTheDocument();
   });
 
+  it.each([
+    { role: "user" as const, bubble: ["bg-info/10", "border-info/20"], avatar: "bg-info/20" },
+    { role: "assistant" as const, bubble: ["bg-card", "border-border"], avatar: "bg-muted" },
+  ])("should paint the $role surface from theme tokens, not fixed colours", ({ role, bubble, avatar }) => {
+    render(<ChatMessageBubble {...defaultProps} message={{ role, content: "Hello" }} />);
+
+    const header = screen.getByText(role).closest("div") as HTMLElement;
+    const surface = header.parentElement as HTMLElement;
+
+    expect(surface).toHaveClass(...bubble);
+    expect(surface).not.toHaveAttribute("style");
+    expect(header.firstElementChild).toHaveClass(avatar);
+    expect(header.firstElementChild).not.toHaveAttribute("style");
+  });
+
   it("should show model badge for assistant messages when model is provided", () => {
     render(<ChatMessageBubble {...defaultProps} message={{ role: "assistant", content: "Reply", model: "gpt-4" }} />);
 
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.tsx b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.tsx
index eb24463cfd3..8c54d9e89fa 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.tsx
@@ -46,20 +46,16 @@ function ChatMessageBubble({
   return (
     <div className={`mb-4 min-w-0 ${isUser ? "text-right" : "text-left"}`}>
       <div
-        className="inline-block min-w-0 max-w-[92%] overflow-hidden rounded-lg p-3 shadow-xs sm:max-w-[85%] sm:px-4"
-        style={{
-          backgroundColor: isUser ? "#f0f8ff" : "#ffffff",
-          border: isUser ? "1px solid #e6f0fa" : "1px solid #f0f0f0",
-          textAlign: "left",
-        }}
+        className={`inline-block min-w-0 max-w-[92%] overflow-hidden rounded-lg border p-3 text-left text-card-foreground shadow-xs sm:max-w-[85%] sm:px-4 ${
+          isUser ? "border-info/20 bg-info/10" : "border-border bg-card"
+        }`}
       >
         {/* Header: role icon + name + model badge */}
         <div className="mb-1.5 flex min-w-0 items-center gap-2">
           <div
-            className="flex items-center justify-center w-6 h-6 rounded-full mr-1"
-            style={{
-              backgroundColor: isUser ? "#e6f0fa" : "#f5f5f5",
-            }}
+            className={`flex items-center justify-center w-6 h-6 rounded-full mr-1 ${
+              isUser ? "bg-info/20" : "bg-muted"
+            }`}
           >
             {isUser ? (
               <User className="size-3 text-info" aria-hidden="true" />
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatUI.tsx b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatUI.tsx
index 2adc7fc30ea..e6257907918 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatUI.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatUI.tsx
@@ -1784,19 +1784,9 @@ const ChatUI: React.FC<ChatUIProps> = ({
                     chatHistory.length > 0 &&
                     chatHistory[chatHistory.length - 1].role === "user" && (
                       <div className="mb-4 text-left">
-                        <div
-                          className="inline-block max-w-[80%] rounded-lg p-3.5 px-4 shadow-xs"
-                          style={{
-                            backgroundColor: "#ffffff",
-                            border: "1px solid #f0f0f0",
-                            textAlign: "left",
-                          }}
-                        >
+                        <div className="inline-block max-w-[80%] rounded-lg border border-border bg-card p-3.5 px-4 text-left text-card-foreground shadow-xs">
                           <div className="mb-1.5 flex items-center gap-2">
-                            <div
-                              className="mr-1 flex h-6 w-6 items-center justify-center rounded-full"
-                              style={{ backgroundColor: "#f5f5f5" }}
-                            >
+                            <div className="mr-1 flex h-6 w-6 items-center justify-center rounded-full bg-muted">
                               <Bot className="size-3 text-muted-foreground" aria-hidden="true" />
                             </div>
                             <strong className="text-sm capitalize">Assistant</strong>

From fe567bd8467f7e9702f26abd61bc866acf659d10 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Mon, 24 Aug 2026 10:51:14 -0700
Subject: [PATCH 91/93] fix(a2a): speak the 0.3 dialect to servers with
 mis-cased protocol bindings

---
 litellm/a2a_protocol/card_resolver.py         | 18 +++++--
 litellm/a2a_protocol/main.py                  |  4 +-
 .../a2a_protocol/test_card_resolver.py        | 24 +++++++++
 tests/test_litellm/a2a_protocol/test_main.py  | 53 +++++++++++++++----
 4 files changed, 84 insertions(+), 15 deletions(-)

diff --git a/litellm/a2a_protocol/card_resolver.py b/litellm/a2a_protocol/card_resolver.py
index 9b3e4ec13b9..25f2e1a9a0d 100644
--- a/litellm/a2a_protocol/card_resolver.py
+++ b/litellm/a2a_protocol/card_resolver.py
@@ -57,22 +57,32 @@ _CANONICAL_PROTOCOL_BINDINGS: Final = MappingProxyType(
     }
 )
 
+_LEGACY_PROTOCOL_VERSION: Final = "0.3"
 
-def normalize_agent_card_protocol_bindings(agent_card: "AgentCard") -> "AgentCard":
+
+def normalize_agent_card_interfaces(agent_card: "AgentCard") -> "AgentCard":
     """
-    Canonicalize protocolBinding casing on the card's supported interfaces.
+    Canonicalize the supported interfaces of spec-adjacent agent cards.
 
     Some A2A servers (e.g. LangGraph Platform) serve agent cards with lowercase
     bindings like "jsonrpc", but a2a-sdk's ClientFactory matches bindings
     case-sensitively against its uppercase TransportProtocol constants and fails
     with "no compatible transports found." for spec-adjacent casings.
+
+    The same servers also speak the A2A 0.3 JSON dialect ("kind"-discriminated
+    payloads) while declaring protocolVersion "1.0", which a2a-sdk's strict v1
+    proto parsing rejects. A mis-cased binding fingerprints such a server, so its
+    declared version is downgraded to 0.3 to route the SDK's ClientFactory onto
+    its v0.3 compat transport, which speaks that dialect.
     """
     normalized: Final = type(agent_card)()
     normalized.CopyFrom(agent_card)
     for interface in normalized.supported_interfaces:
         canonical: str | None = _CANONICAL_PROTOCOL_BINDINGS.get(interface.protocol_binding.lower())
-        if canonical is not None:
-            interface.protocol_binding = canonical
+        if canonical is None or canonical == interface.protocol_binding:
+            continue
+        interface.protocol_binding = canonical
+        interface.protocol_version = _LEGACY_PROTOCOL_VERSION
     return normalized
 
 
diff --git a/litellm/a2a_protocol/main.py b/litellm/a2a_protocol/main.py
index 2d4267cc0db..56b8089b0af 100644
--- a/litellm/a2a_protocol/main.py
+++ b/litellm/a2a_protocol/main.py
@@ -73,7 +73,7 @@ except ImportError:
 from litellm.a2a_protocol.card_resolver import (
     LiteLLMA2ACardResolver,
     get_agent_card_url,
-    normalize_agent_card_protocol_bindings,
+    normalize_agent_card_interfaces,
 )
 from litellm.a2a_protocol.exception_mapping_utils import (
     handle_a2a_localhost_retry,
@@ -784,7 +784,7 @@ async def create_a2a_client(
         verbose_proxy_logger.debug("A2A client created with extra_headers=%s", list(extra_headers.keys()))
 
     resolver: Final = A2ACardResolver(httpx_client=httpx_client, base_url=base_url)
-    agent_card: Final = normalize_agent_card_protocol_bindings(
+    agent_card: Final = normalize_agent_card_interfaces(
         await resolver.get_agent_card(http_kwargs={"headers": extra_headers} if extra_headers else None)
     )
 
diff --git a/tests/test_litellm/a2a_protocol/test_card_resolver.py b/tests/test_litellm/a2a_protocol/test_card_resolver.py
index 053f28c940f..5cbfa51fa08 100644
--- a/tests/test_litellm/a2a_protocol/test_card_resolver.py
+++ b/tests/test_litellm/a2a_protocol/test_card_resolver.py
@@ -13,6 +13,7 @@ from litellm.a2a_protocol.card_resolver import (
     LiteLLMA2ACardResolver,
     fix_agent_card_url,
     is_localhost_or_internal_url,
+    normalize_agent_card_interfaces,
     set_agent_card_url,
 )
 
@@ -114,3 +115,26 @@ def test_fix_agent_card_url_updates_interface_when_top_level_is_localhost():
 
     assert result.url == "https://my-public-agent.example.com/"
     assert result.supported_interfaces[0].url == "https://my-public-agent.example.com/"
+
+
+def test_normalize_agent_card_interfaces_downgrades_miscased_interfaces_to_the_0_3_dialect():
+    pb2 = pytest.importorskip("a2a.types.a2a_pb2")
+
+    card = pb2.AgentCard(
+        name="langgraph",
+        supported_interfaces=[
+            pb2.AgentInterface(url="http://a/", protocol_binding="jsonrpc", protocol_version="1.0"),
+            pb2.AgentInterface(url="http://b/", protocol_binding="JSONRPC", protocol_version="1.0"),
+            pb2.AgentInterface(url="http://c/", protocol_binding="websocket", protocol_version="1.0"),
+        ],
+    )
+
+    normalized = normalize_agent_card_interfaces(card)
+
+    assert [(i.protocol_binding, i.protocol_version) for i in normalized.supported_interfaces] == [
+        ("JSONRPC", "0.3"),
+        ("JSONRPC", "1.0"),
+        ("websocket", "1.0"),
+    ]
+    assert card.supported_interfaces[0].protocol_binding == "jsonrpc"
+    assert card.supported_interfaces[0].protocol_version == "1.0"
diff --git a/tests/test_litellm/a2a_protocol/test_main.py b/tests/test_litellm/a2a_protocol/test_main.py
index aa988bc5b99..8850a2eca6c 100644
--- a/tests/test_litellm/a2a_protocol/test_main.py
+++ b/tests/test_litellm/a2a_protocol/test_main.py
@@ -176,10 +176,40 @@ _AGENT_A_HEADERS = {"x-agent-token": "token-for-a", "x-tenant": "tenant-a"}
 _AGENT_B_HEADERS = {"x-agent-token": "token-for-b", "x-tenant": "tenant-b"}
 
 
-_V1_RPC_REPLY = {
+_LANGGRAPH_TASK_REPLY = {
     "jsonrpc": "2.0",
     "id": "reply",
-    "result": {"message": {"messageId": "reply-1", "role": "ROLE_AGENT", "parts": [{"text": "pong"}]}},
+    "result": {
+        "kind": "task",
+        "id": "run-1:task-1",
+        "contextId": "thread-1",
+        "history": [
+            {
+                "kind": "message",
+                "role": "user",
+                "parts": [{"kind": "text", "text": "hi"}],
+                "messageId": "m-user",
+                "taskId": "run-1:task-1",
+                "contextId": "thread-1",
+            },
+            {
+                "kind": "message",
+                "role": "agent",
+                "parts": [{"kind": "text", "text": "langgraph echo: hi"}],
+                "messageId": "m-agent",
+                "taskId": "run-1:task-1",
+                "contextId": "thread-1",
+            },
+        ],
+        "status": {"state": "completed", "timestamp": "2026-08-24T00:00:00+00:00"},
+        "artifacts": [
+            {
+                "artifactId": "art-1",
+                "name": "Assistant Response",
+                "parts": [{"kind": "text", "text": "langgraph echo: hi"}],
+            }
+        ],
+    },
 }
 
 
@@ -334,17 +364,22 @@ async def test_streaming_send_carries_only_its_own_caller_headers(isolated_clien
 
 
 @pytest.mark.asyncio
-async def test_lowercase_protocol_binding_in_agent_card_still_gets_a_client(isolated_client_cache):
-    """LangGraph Platform serves cards with protocolBinding "jsonrpc"; a2a-sdk matches
-    bindings case-sensitively, so without normalization client creation raises
-    ValueError("no compatible transports found.")."""
-    await _seed_shared_a2a_client(card=_LOWERCASE_BINDING_CARD, rpc_reply=_V1_RPC_REPLY)
+async def test_lowercase_protocol_binding_card_round_trips_the_langgraph_dialect(isolated_client_cache):
+    """LangGraph Platform serves cards with protocolBinding "jsonrpc" and answers in the
+    A2A 0.3 JSON dialect ("kind"-discriminated) while declaring protocolVersion "1.0".
+    Without binding normalization client creation raises ValueError("no compatible
+    transports found."); without the version downgrade the SDK's strict v1 transport
+    rejects the reply with 'Message type "lf.a2a.v1.Task" has no field named "kind"'."""
+    await _seed_shared_a2a_client(card=_LOWERCASE_BINDING_CARD, rpc_reply=_LANGGRAPH_TASK_REPLY)
 
     a2a_client = await create_a2a_client(base_url="http://127.0.0.1:9")
     response = await _send_message(a2a_client, _send_request("lc"))
 
-    assert type(response.root.result).__name__ == "Message"
-    assert a2a_client._litellm_agent_card.supported_interfaces[0].protocol_binding == "JSONRPC"
+    assert type(response.root.result).__name__ == "Task"
+    assert response.root.result.artifacts[0].parts[0].root.text == "langgraph echo: hi"
+    interface = a2a_client._litellm_agent_card.supported_interfaces[0]
+    assert interface.protocol_binding == "JSONRPC"
+    assert interface.protocol_version == "0.3"
 
 
 @pytest.mark.asyncio

From b36f34813a5e718bc3de77297daddfa89233baad Mon Sep 17 00:00:00 2001
From: Darien Kindlund <darien@kindlund.com>
Date: Mon, 24 Aug 2026 14:43:47 -0400
Subject: [PATCH 92/93] fix(anthropic): reconcile enum with declared type in
 output_format schema (#37882)

* fix(anthropic): reconcile enum with declared type in output_format schema

Anthropic cross-validates `enum` against `type` in structured outputs: every
enum value must match a single declared type. A union `type` array, or an enum
value whose JSON type differs from a scalar `type`, is rejected with
"Invalid schema: Enum value 'low' does not match declared type '['string','null']'"

filter_anthropic_output_schema had no enum/type reconciliation, so both keys
reached Anthropic untouched. Drop the conflicting `type` -- `enum` is the
tighter constraint, and an enum with no `type` is accepted

The drop is conditional: `type` is only removed when it is a union array, or
when some enum value does not match the scalar type. A matching enum plus
scalar `type` is left exactly as-is, so existing behaviour is unchanged

Pydantic emits the failing shape for Optional[SomeEnum], so this affects any
caller with a nullable enum field on the native output_format path. vertex_ai
is unaffected because it is forced onto the permissive tool-use path

Fixes #37881

* refactor(anthropic): make enum/type reconciliation immutable and precisely typed

Address review: the predicate registry was a mutable `dict[str, Any]`, and the
reconciliation removed `type` by mutating the built result with `pop`

- registry is now `Final[Mapping[str, Callable[[Any], bool]]]` wrapped in
  `MappingProxyType`, so predicate signatures are statically checked and the
  table cannot be mutated
- the conflict decision moves into a pure helper evaluated once against the
  input schema, and the conflicting `type` key is skipped at build time in the
  existing loop instead of being popped afterwards, so nothing is mutated

Behaviour is unchanged; all 27 tests in the schema-filter suite still pass
---
 litellm/llms/anthropic/chat/transformation.py | 33 ++++++-
 .../anthropic/test_anthropic_schema_filter.py | 91 +++++++++++++++++++
 2 files changed, 123 insertions(+), 1 deletion(-)

diff --git a/litellm/llms/anthropic/chat/transformation.py b/litellm/llms/anthropic/chat/transformation.py
index ef278c8f723..23abca7d5f2 100644
--- a/litellm/llms/anthropic/chat/transformation.py
+++ b/litellm/llms/anthropic/chat/transformation.py
@@ -1,7 +1,8 @@
 import json
 import re
 import time
-from collections.abc import Mapping, Sequence
+from collections.abc import Callable, Mapping, Sequence
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final, NoReturn, cast
 
 import httpx
@@ -121,6 +122,32 @@ else:
 # response side.
 _ANTHROPIC_TOOL_NAME_INVALID_CHARS: Final = re.compile(r"[^a-zA-Z0-9_-]")
 _ANTHROPIC_TOOL_NAME_MAX_LEN: Final = 128
+
+_ENUM_TYPE_CHECKS: Final[Mapping[str, Callable[[Any], bool]]] = MappingProxyType(
+    {
+        "null": lambda v: v is None,
+        "boolean": lambda v: isinstance(v, bool),
+        "integer": lambda v: isinstance(v, int) and not isinstance(v, bool),
+        "number": lambda v: isinstance(v, (int, float)) and not isinstance(v, bool),
+        "string": lambda v: isinstance(v, str),
+        "array": lambda v: isinstance(v, list),
+        "object": lambda v: isinstance(v, dict),
+    }
+)
+
+
+def _enum_conflicts_with_declared_type(schema: Mapping[str, Any]) -> bool:
+    """Whether ``schema``'s ``enum`` cannot match its declared ``type``."""
+    enum_values: Final = schema.get("enum")
+    declared_type: Final = schema.get("type")
+    if not isinstance(enum_values, list) or declared_type is None:
+        return False
+    if isinstance(declared_type, list):
+        return True
+    check: Final = _ENUM_TYPE_CHECKS.get(declared_type)
+    return check is not None and not all(check(value) for value in enum_values)
+
+
 # Single, internal-only key on ``litellm_params`` used to thread the per-
 # request reverse map (sanitized -> original) from request build to response
 # parsing. ``litellm_params`` is never serialized to a provider; ``optional_
@@ -565,9 +592,13 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
             else:
                 result["description"] = constraint_note
 
+        drops_conflicting_type: Final = _enum_conflicts_with_declared_type(schema)
+
         for key, value in schema.items():
             if key in unsupported_fields:
                 continue
+            if key == "type" and drops_conflicting_type:
+                continue
             if key == "description" and "description" in result:
                 # Already handled above
                 continue
diff --git a/tests/test_litellm/llms/anthropic/test_anthropic_schema_filter.py b/tests/test_litellm/llms/anthropic/test_anthropic_schema_filter.py
index 71c9cfe8f41..32423d6679f 100644
--- a/tests/test_litellm/llms/anthropic/test_anthropic_schema_filter.py
+++ b/tests/test_litellm/llms/anthropic/test_anthropic_schema_filter.py
@@ -417,3 +417,94 @@ class TestFilterAnthropicOutputSchema:
         result = AnthropicConfig.filter_anthropic_output_schema(schema)
 
         assert result["additionalProperties"] is False
+
+    def test_drops_union_type_alongside_enum(self):
+        """A union ``type`` can never match a single declared type.
+
+        Anthropic rejects it with "Invalid schema: Enum value 'low' does not
+        match declared type '['string', 'null']'". ``enum`` is the tighter
+        constraint, so the conflicting ``type`` is dropped.
+        """
+        schema = {
+            "type": "object",
+            "properties": {
+                "confidence": {
+                    "enum": ["low", "medium", "high", None],
+                    "type": ["string", "null"],
+                }
+            },
+        }
+
+        result = AnthropicConfig.filter_anthropic_output_schema(schema)
+
+        assert "type" not in result["properties"]["confidence"]
+        assert result["properties"]["confidence"]["enum"] == [
+            "low",
+            "medium",
+            "high",
+            None,
+        ]
+
+    def test_drops_type_when_an_enum_value_does_not_match_it(self):
+        """``enum: ["x", None]`` with ``type: "string"`` is rejected too."""
+        schema = {
+            "type": "object",
+            "properties": {"a": {"enum": ["x", None], "type": "string"}},
+        }
+
+        result = AnthropicConfig.filter_anthropic_output_schema(schema)
+
+        assert "type" not in result["properties"]["a"]
+
+    def test_preserves_type_when_every_enum_value_matches(self):
+        """The non-conflicting case must be left exactly as-is."""
+        schema = {
+            "type": "object",
+            "properties": {"a": {"enum": ["x", "y"], "type": "string"}},
+        }
+
+        result = AnthropicConfig.filter_anthropic_output_schema(schema)
+
+        assert result["properties"]["a"]["type"] == "string"
+        assert result["properties"]["a"]["enum"] == ["x", "y"]
+
+    def test_integer_enum_satisfies_number_type(self):
+        """JSON Schema ``number`` accepts integers, so this is not a conflict."""
+        schema = {
+            "type": "object",
+            "properties": {"a": {"enum": [1, 2], "type": "number"}},
+        }
+
+        result = AnthropicConfig.filter_anthropic_output_schema(schema)
+
+        assert result["properties"]["a"]["type"] == "number"
+
+    def test_bool_enum_does_not_satisfy_integer_type(self):
+        """``bool`` is a Python ``int`` subclass but is not a JSON integer."""
+        schema = {
+            "type": "object",
+            "properties": {"a": {"enum": [True], "type": "integer"}},
+        }
+
+        result = AnthropicConfig.filter_anthropic_output_schema(schema)
+
+        assert "type" not in result["properties"]["a"]
+
+    def test_normalizes_enum_type_inside_array_items(self):
+        """Normalization applies at every recursion site, not just top level."""
+        schema = {
+            "type": "object",
+            "properties": {
+                "rows": {
+                    "type": "array",
+                    "items": {
+                        "type": "object",
+                        "properties": {"c": {"enum": ["a", None], "type": ["string", "null"]}},
+                    },
+                }
+            },
+        }
+
+        result = AnthropicConfig.filter_anthropic_output_schema(schema)
+
+        assert "type" not in result["properties"]["rows"]["items"]["properties"]["c"]

From a1134755cab81e875b3a1294eda34a7b6a7b979f Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Mon, 24 Aug 2026 11:57:36 -0700
Subject: [PATCH 93/93] fix(ui): boot the UI image as an arbitrary uid by
 anchoring nginx writes under /tmp (#37982)

* fix(ui): boot the UI image as an arbitrary uid by anchoring nginx writes under /tmp

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(ui): type the arbitrary-uid image test fixture

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .github/workflows/image-scan.yml              |  31 ++++
 helm/litellm/values.yaml                      |   8 +-
 .../test_ui_image_serves_offline.py           | 132 ++++++++++++++++++
 ui/nginx.conf                                 |  13 ++
 4 files changed, 181 insertions(+), 3 deletions(-)
 create mode 100644 tests/proxy_migration_tests/test_ui_image_serves_offline.py

diff --git a/.github/workflows/image-scan.yml b/.github/workflows/image-scan.yml
index d798df4c3a4..bb04563c1a8 100644
--- a/.github/workflows/image-scan.yml
+++ b/.github/workflows/image-scan.yml
@@ -23,6 +23,8 @@ on:
       - tests/proxy_migration_tests/**
       - uv.lock
       - ui/litellm-dashboard/package-lock.json
+      - ui/Dockerfile
+      - ui/nginx.conf
       - .github/workflows/image-scan.yml
   schedule:
     - cron: "41 6 * * *"
@@ -185,6 +187,35 @@ jobs:
           python -m pip install "pytest==9.0.3"
           python -m pytest tests/proxy_migration_tests/test_component_image_serves_offline.py -v
 
+  ui-image:
+    name: ui-image
+    runs-on: ubuntu-latest
+    if: >-
+      github.event_name != 'pull_request' ||
+      github.event.pull_request.head.repo.full_name == github.repository
+    timeout-minutes: 30
+    permissions:
+      contents: read
+    steps:
+      - uses: actions/checkout@08eba0b27e820071cde6df949e0beb9ba4906955 # v4.3.0
+        with:
+          persist-credentials: false
+
+      - name: Build UI image
+        run: docker build -f ui/Dockerfile -t litellm-ui-scan:${{ github.sha }} .
+
+      - name: Set up Python
+        uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
+        with:
+          python-version: "3.12"
+
+      - name: Verify the UI serves offline as an arbitrary uid with a read-only root fs
+        env:
+          LITELLM_IMAGE: litellm-ui-scan:${{ github.sha }}
+        run: |
+          python -m pip install "pytest==9.0.3"
+          python -m pytest tests/proxy_migration_tests/test_ui_image_serves_offline.py -v
+
   backend-image:
     name: backend-image
     runs-on: ubuntu-latest
diff --git a/helm/litellm/values.yaml b/helm/litellm/values.yaml
index 998d225a317..06ba72d84b3 100644
--- a/helm/litellm/values.yaml
+++ b/helm/litellm/values.yaml
@@ -428,9 +428,11 @@ ui:
     maxUnavailable: ""
   podAnnotations: {}
   # Same shape as the gateway blocks of the same name. The nginx runtime
-  # writes its pid, cache, and proxy temp files under the image's root
-  # filesystem, so `securityContext.readOnlyRootFilesystem: true` here needs
-  # emptyDir volumes mounted over those paths.
+  # writes its pid, cache, and proxy temp files under /tmp, so it boots as
+  # any (arbitrary, non-root) uid; `securityContext.readOnlyRootFilesystem:
+  # true` here needs an emptyDir volume mounted over /tmp. Images before
+  # the /tmp move instead need emptyDirs over /var/cache/nginx and /run to
+  # run as a non-root uid at all.
   podLabels: {}
   podSecurityContext: {}
   securityContext: {}
diff --git a/tests/proxy_migration_tests/test_ui_image_serves_offline.py b/tests/proxy_migration_tests/test_ui_image_serves_offline.py
new file mode 100644
index 00000000000..5ff68effd7f
--- /dev/null
+++ b/tests/proxy_migration_tests/test_ui_image_serves_offline.py
@@ -0,0 +1,132 @@
+"""Image-level regression net for arbitrary-uid boot of the UI image.
+
+OpenShift ``restricted-v2`` ignores the image ``USER`` and assigns an
+arbitrary uid in GID 0. The stock nginx base expects to start as root, so
+its cache (``/var/cache/nginx``) and pid (``/run``) paths are root-owned
+755 and the master process dies at startup with
+``mkdir() "/var/cache/nginx/client_temp" failed (13: Permission denied)``.
+The fix anchors everything nginx writes under ``/tmp`` in ``ui/nginx.conf``.
+
+Booting the image the way that deployment does, with a read-only root
+filesystem and ``/tmp`` as the only writable mount, is what catches the
+whole class: a boot as the default (root) uid passes even on the broken
+config.
+
+Gated on LITELLM_IMAGE so it is skipped in the normal unit-test run and
+exercised only where an image has been built (the image-scan workflow).
+Requires a working docker CLI.
+"""
+
+import os
+import shutil
+import subprocess
+import time
+import uuid
+from collections.abc import Iterator
+
+import pytest
+
+IMAGE = os.getenv("LITELLM_IMAGE")
+CURL_IMAGE = os.getenv("LITELLM_TEST_CURL_IMAGE", "curlimages/curl:8.11.1")
+UI_PORT = os.getenv("LITELLM_UI_PORT", "3000")
+ARBITRARY_UID = "1001200000:0"
+STARTUP_TIMEOUT_SECONDS = int(os.getenv("LITELLM_UI_STARTUP_TIMEOUT", "60"))
+
+pytestmark = [
+    pytest.mark.skipif(IMAGE is None, reason="requires a built image (set LITELLM_IMAGE)"),
+    pytest.mark.skipif(shutil.which("docker") is None, reason="requires the docker CLI"),
+]
+
+
+def _docker(*args: str, check: bool = True) -> "subprocess.CompletedProcess[str]":
+    return subprocess.run(["docker", *args], capture_output=True, text=True, check=check)
+
+
+@pytest.fixture()
+def ui_container() -> Iterator[tuple[str, str]]:
+    """The UI container as an arbitrary uid in GID 0 on a network with no egress.
+
+    ``--read-only`` with a tmpfs on ``/tmp`` mirrors the strictest supported
+    deployment: ``readOnlyRootFilesystem: true`` with an emptyDir on ``/tmp``.
+    A config that writes anywhere else fails here exactly like it does on
+    OpenShift.
+    """
+    run_id = f"uiserve-{uuid.uuid4().hex[:8]}"
+    network = f"{run_id}-net"
+    container = f"{run_id}-ui"
+
+    _docker("pull", "--quiet", CURL_IMAGE)
+    _docker("network", "create", "--internal", network)
+    try:
+        assert IMAGE is not None
+        _docker(
+            "run", "-d", "--name", container, "--network", network,
+            "--user", ARBITRARY_UID,
+            "--read-only", "--tmpfs", "/tmp",
+            IMAGE,
+        )
+        yield network, container
+    finally:
+        _docker("logs", container, check=False)
+        _docker("rm", "-f", container, check=False)
+        _docker("network", "rm", network, check=False)
+
+
+def _container_logs(container: str) -> str:
+    logs = _docker("logs", container, check=False)
+    return f"stdout:\n{logs.stdout}\nstderr:\n{logs.stderr}"
+
+
+def _is_running(container: str) -> bool:
+    return bool(
+        _docker(
+            "ps", "--filter", f"name={container}", "--filter", "status=running",
+            "--format", "{{.Names}}", check=False,
+        ).stdout.strip()
+    )
+
+
+def _probe(network: str, container: str, path: str) -> "subprocess.CompletedProcess[str]":
+    return _docker(
+        "run", "--rm", "--network", network, CURL_IMAGE,
+        "--silent", "--show-error", "--max-time", "10",
+        "--output", "/dev/null", "--write-out", "%{http_code}",
+        f"http://{container}:{UI_PORT}{path}",
+        check=False,
+    )
+
+
+def test_ui_serves_as_arbitrary_uid_read_only(ui_container: tuple[str, str]) -> None:
+    """nginx boots and serves as an arbitrary uid with a read-only root fs.
+
+    On the pre-fix config nginx exits during startup with
+    ``mkdir() "/var/cache/nginx/client_temp" failed (13: Permission denied)``
+    and the running-check below fails; it never reaches the probes.
+    """
+    network, container = ui_container
+
+    deadline = time.time() + STARTUP_TIMEOUT_SECONDS
+    healthz = None
+    while time.time() < deadline:
+        if not _is_running(container):
+            pytest.fail(
+                f"the UI container exited during startup as uid {ARBITRARY_UID} with a "
+                f"read-only root filesystem. nginx writes outside /tmp.\n"
+                f"{_container_logs(container)}"
+            )
+        healthz = _probe(network, container, "/healthz")
+        if healthz.returncode == 0 and healthz.stdout.strip() == "200":
+            break
+        time.sleep(2)
+
+    assert healthz is not None and healthz.stdout.strip() == "200", (
+        f"/healthz never answered 200 within {STARTUP_TIMEOUT_SECONDS}s as uid "
+        f"{ARBITRARY_UID}.\n{_container_logs(container)}"
+    )
+
+    for path in ("/", "/ui", "/ui/login"):
+        page = _probe(network, container, path)
+        assert page.stdout.strip() == "200", (
+            f"GET {path} returned {page.stdout.strip()!r} as uid {ARBITRARY_UID}.\n"
+            f"{_container_logs(container)}"
+        )
diff --git a/ui/nginx.conf b/ui/nginx.conf
index a41ee5bd5b4..235cb9c501e 100644
--- a/ui/nginx.conf
+++ b/ui/nginx.conf
@@ -1,7 +1,20 @@
 worker_processes auto;
+
+# Anchor everything nginx writes under /tmp so the image boots as an
+# arbitrary uid (OpenShift restricted-v2 assigns one in gid 0; the stock
+# nginx image's /var/cache/nginx and /run are root-owned 755) and works
+# with readOnlyRootFilesystem when /tmp is an emptyDir.
+pid /tmp/nginx.pid;
+
 events { worker_connections 1024; }
 
 http {
+  client_body_temp_path /tmp/nginx-client-temp;
+  proxy_temp_path       /tmp/nginx-proxy-temp;
+  fastcgi_temp_path     /tmp/nginx-fastcgi-temp;
+  uwsgi_temp_path       /tmp/nginx-uwsgi-temp;
+  scgi_temp_path        /tmp/nginx-scgi-temp;
+
   include       /etc/nginx/mime.types;
   default_type  application/octet-stream;
   sendfile      on;