fix(prompts): apply prompt templates before routing on /v1/responses and honor ignore_prompt_manager_model

On /v1/responses the prompt template ran inside litellm.aresponses, after the
router had already resolved a deployment and injected its api_key/api_base, so a
prompt whose metadata.model pointed at another provider sent the old
deployment's credentials cross-provider (401). The proxy now runs the prompt
template for aresponses in the pre-call hook, before routing, so the router
picks the deployment that matches the swapped model. As a backstop, the SDK
refuses a cross-provider swap when explicit credentials are already present
instead of forwarding them.

ignore_prompt_manager_model and ignore_prompt_manager_optional_params saved on
a prompt were only read by the generic manager, so dotprompt prompts ignored
them on every endpoint. PromptManagementBase now merges the prompt spec's flags
with the per-request ones for every manager, and the generic manager no longer
drops caller flags when no spec is present.

litellm/integrations/dotprompt/dotprompt_manager.py

@@ -209,6 +209,8 @@ class DotpromptManager(CustomPromptManagement):
             prompt_spec=prompt_spec,
             prompt_label=prompt_label,
             prompt_version=prompt_version,
+            ignore_prompt_manager_model=ignore_prompt_manager_model,
+            ignore_prompt_manager_optional_params=ignore_prompt_manager_optional_params,
         )
 
     async def async_get_chat_completion_prompt(

litellm/integrations/generic_prompt_management/generic_prompt_manager.py

@@ -416,17 +416,8 @@ class GenericPromptManager(CustomPromptManagement):
             tools=tools,
             prompt_label=prompt_label,
             prompt_version=prompt_version,
-            ignore_prompt_manager_model=(
-                ignore_prompt_manager_model or prompt_spec.litellm_params.ignore_prompt_manager_model
-                if prompt_spec
-                else False
-            ),
-            ignore_prompt_manager_optional_params=(
-                ignore_prompt_manager_optional_params
-                or prompt_spec.litellm_params.ignore_prompt_manager_optional_params
-                if prompt_spec
-                else False
-            ),
+            ignore_prompt_manager_model=ignore_prompt_manager_model,
+            ignore_prompt_manager_optional_params=ignore_prompt_manager_optional_params,
         )
 
     def get_chat_completion_prompt(
@@ -457,17 +448,8 @@ class GenericPromptManager(CustomPromptManagement):
             prompt_spec=prompt_spec,
             prompt_label=prompt_label,
             prompt_version=prompt_version,
-            ignore_prompt_manager_model=(
-                ignore_prompt_manager_model or prompt_spec.litellm_params.ignore_prompt_manager_model
-                if prompt_spec
-                else False
-            ),
-            ignore_prompt_manager_optional_params=(
-                ignore_prompt_manager_optional_params
-                or prompt_spec.litellm_params.ignore_prompt_manager_optional_params
-                if prompt_spec
-                else False
-            ),
+            ignore_prompt_manager_model=ignore_prompt_manager_model,
+            ignore_prompt_manager_optional_params=ignore_prompt_manager_optional_params,
         )
 
     def clear_cache(self) -> None:

litellm/integrations/prompt_management_base.py

@@ -19,6 +19,19 @@ class PromptManagementClient(TypedDict):
     completed_messages: list[AllMessageValues] | None
 
 
+def resolve_prompt_manager_ignore_flags(
+    prompt_spec: PromptSpec | None,
+    ignore_prompt_manager_model: bool | None,
+    ignore_prompt_manager_optional_params: bool | None,
+) -> tuple[bool, bool]:
+    spec_params: Final = prompt_spec.litellm_params if prompt_spec is not None else None
+    return (
+        bool(ignore_prompt_manager_model) or bool(spec_params is not None and spec_params.ignore_prompt_manager_model),
+        bool(ignore_prompt_manager_optional_params)
+        or bool(spec_params is not None and spec_params.ignore_prompt_manager_optional_params),
+    )
+
+
 class PromptManagementBase(ABC):
     @property
     @abstractmethod
@@ -182,13 +195,18 @@ class PromptManagementBase(ABC):
             prompt_version=prompt_version,
         )
 
+        resolved_ignore_model, resolved_ignore_optional_params = resolve_prompt_manager_ignore_flags(
+            prompt_spec=prompt_spec,
+            ignore_prompt_manager_model=ignore_prompt_manager_model,
+            ignore_prompt_manager_optional_params=ignore_prompt_manager_optional_params,
+        )
         return self.post_compile_prompt_processing(
             prompt_template=prompt_template,
             messages=messages,
             non_default_params=non_default_params,
             model=model,
-            ignore_prompt_manager_model=ignore_prompt_manager_model,
-            ignore_prompt_manager_optional_params=ignore_prompt_manager_optional_params,
+            ignore_prompt_manager_model=resolved_ignore_model,
+            ignore_prompt_manager_optional_params=resolved_ignore_optional_params,
         )
 
     async def async_get_chat_completion_prompt(
@@ -224,11 +242,16 @@ class PromptManagementBase(ABC):
             prompt_version=prompt_version,
         )
 
+        resolved_ignore_model, resolved_ignore_optional_params = resolve_prompt_manager_ignore_flags(
+            prompt_spec=prompt_spec,
+            ignore_prompt_manager_model=ignore_prompt_manager_model,
+            ignore_prompt_manager_optional_params=ignore_prompt_manager_optional_params,
+        )
         return self.post_compile_prompt_processing(
             prompt_template=prompt_template,
             messages=messages,
             non_default_params=non_default_params,
             model=model,
-            ignore_prompt_manager_model=ignore_prompt_manager_model,
-            ignore_prompt_manager_optional_params=ignore_prompt_manager_optional_params,
+            ignore_prompt_manager_model=resolved_ignore_model,
+            ignore_prompt_manager_optional_params=resolved_ignore_optional_params,
         )

litellm/proxy/utils.py

@@ -1402,6 +1402,7 @@ class ProxyLogging:
             get_latest_version_prompt_id,
         )
         from litellm.proxy.prompts.prompt_registry import IN_MEMORY_PROMPT_REGISTRY
+        from litellm.responses.utils import ResponsesAPIRequestUtils
         from litellm.utils import get_non_default_completion_params
 
         if prompt_version is None:
@@ -1420,13 +1421,20 @@ class ProxyLogging:
             data.pop("prompt_id", None)
 
         if custom_logger and prompt_spec is not None:
+            is_responses_call: Final = call_type == "aresponses"
+            original_responses_input: Final = data.get("input", "") if is_responses_call else None
+            client_messages: Final = (
+                ResponsesAPIRequestUtils.responses_input_to_chat_messages(original_responses_input)
+                if is_responses_call
+                else data.get("messages", [])
+            )
             (
                 model,
                 messages,
                 optional_params,
             ) = await litellm_logging_obj.async_get_chat_completion_prompt(
                 model=data.get("model", ""),
-                messages=data.get("messages", []),
+                messages=client_messages,
                 non_default_params=get_non_default_completion_params(kwargs=data) or {},
                 prompt_id=litellm_prompt_id,
                 prompt_spec=prompt_spec,
@@ -1438,7 +1446,14 @@ class ProxyLogging:
 
             data.update(optional_params)
             data["model"] = model
-            data["messages"] = messages
+            if is_responses_call:
+                data["input"] = ResponsesAPIRequestUtils.merge_prompt_management_input(
+                    original_input=original_responses_input,
+                    client_input=client_messages,
+                    merged_input=messages,
+                )
+            else:
+                data["messages"] = messages
             # prevent re-processing the prompt template
             data.pop("prompt_id", None)
             data.pop("prompt_variables", None)
@@ -1653,7 +1668,7 @@ class ProxyLogging:
             not guardrails_only
             and litellm_logging_obj is not None
             and prompt_id is not None
-            and (call_type == "completion" or call_type == "acompletion")
+            and (call_type == "completion" or call_type == "acompletion" or call_type == "aresponses")
         ):
             await self._process_prompt_template(
                 data=data,

litellm/responses/main.py

@@ -26,7 +26,6 @@ from litellm.responses.litellm_completion_transformation.handler import (
 )
 from litellm.responses.utils import ResponsesAPIRequestUtils
 from litellm.types.llms.openai import (
-    AllMessageValues,
     PromptObject,
     Reasoning,
     ResponseIncludable,
@@ -463,10 +462,7 @@ async def aresponses(
         if isinstance(
             litellm_logging_obj, LiteLLMLoggingObj
         ) and litellm_logging_obj.should_run_prompt_management_hooks(prompt_id=prompt_id, non_default_params=kwargs):
-            if isinstance(input, str):
-                client_input: list[AllMessageValues] = [{"role": "user", "content": input}]
-            else:
-                client_input = [item for item in input if isinstance(item, dict) and "role" in item]
+            client_input: Final = ResponsesAPIRequestUtils.responses_input_to_chat_messages(input)
             (
                 model,
                 merged_input,
@@ -489,7 +485,13 @@ async def aresponses(
                 ),
             )
             if model != original_model:
-                _, custom_llm_provider, _, _ = litellm.get_llm_provider(model=model)
+                custom_llm_provider = _resolve_prompt_swapped_provider(
+                    original_model=original_model,
+                    swapped_model=model,
+                    custom_llm_provider=custom_llm_provider,
+                    kwargs=kwargs,
+                    prompt_id=prompt_id,
+                )
             kwargs.pop("prompt_id", None)
             kwargs["_async_prompt_merged_params"] = merged_optional_params
 
@@ -559,6 +561,35 @@ async def aresponses(
         )
 
 
+def _resolve_prompt_swapped_provider(
+    original_model: str,
+    swapped_model: str,
+    custom_llm_provider: str | None,
+    kwargs: Mapping[str, object],
+    prompt_id: str | None,
+) -> str:
+    swapped_provider: Final = litellm.get_llm_provider(model=swapped_model)[1]
+    if kwargs.get("api_key") is None and kwargs.get("api_base") is None:
+        return swapped_provider
+    try:
+        original_provider: Final = custom_llm_provider or litellm.get_llm_provider(model=original_model)[1]
+    except litellm.BadRequestError:
+        return swapped_provider
+    if swapped_provider == original_provider:
+        return swapped_provider
+    raise litellm.BadRequestError(
+        message=(
+            f"prompt_id '{prompt_id}' swaps model '{original_model}' -> '{swapped_model}', which changes the "
+            f"provider from '{original_provider}' to '{swapped_provider}' after credentials for "
+            f"'{original_provider}' were already resolved. Refusing to send them to '{swapped_provider}'. "
+            "Point the request at a model whose provider matches the prompt's metadata.model, or set "
+            "ignore_prompt_manager_model on the prompt to keep the requested model."
+        ),
+        model=swapped_model,
+        llm_provider=swapped_provider,
+    )
+
+
 def _apply_prompt_management_to_responses_call(
     input: str | ResponseInputParam,
     model: str,
@@ -577,10 +608,7 @@ def _apply_prompt_management_to_responses_call(
     prompt_variables: Final = cast(dict | None, kwargs.get("prompt_variables", None))
     original_model: Final = model
 
-    if isinstance(input, str):
-        client_input: list[AllMessageValues] = [{"role": "user", "content": input}]
-    else:
-        client_input = [item for item in input if isinstance(item, dict) and "role" in item]
+    client_input: Final = ResponsesAPIRequestUtils.responses_input_to_chat_messages(input)
 
     if isinstance(litellm_logging_obj, LiteLLMLoggingObj) and litellm_logging_obj.should_run_prompt_management_hooks(
         prompt_id=prompt_id, non_default_params=kwargs
@@ -609,7 +637,13 @@ def _apply_prompt_management_to_responses_call(
         local_vars["input"] = input
         local_vars["model"] = model
         if model != original_model:
-            _, custom_llm_provider, _, _ = litellm.get_llm_provider(model=model)
+            custom_llm_provider = _resolve_prompt_swapped_provider(
+                original_model=original_model,
+                swapped_model=model,
+                custom_llm_provider=custom_llm_provider,
+                kwargs=kwargs,
+                prompt_id=prompt_id,
+            )
             local_vars["custom_llm_provider"] = custom_llm_provider
         for key, value in merged_optional_params.items():
             local_vars[key] = value

litellm/responses/utils.py

@@ -72,6 +72,16 @@ class ResponsesAPIRequestUtils:
         shaped_content: Final = [_as_input_text_part(part) for part in content]  # mutable-ok: Responses-shaped copy
         return {**message, "content": shaped_content}  # mutable-ok: copy, the hook's message stays untouched
 
+    @staticmethod
+    def responses_input_to_chat_messages(
+        input: str | ResponseInputParam | None,
+    ) -> list[AllMessageValues]:
+        if input is None:
+            return []
+        if isinstance(input, str):
+            return [{"role": "user", "content": input}]
+        return [item for item in input if isinstance(item, dict) and "role" in item]
+
     @staticmethod
     def merge_prompt_management_input(
         original_input: str | ResponseInputParam,

tests/test_litellm/integrations/dotprompt/test_prompt_manager.py

@@ -577,3 +577,93 @@ async def test_dotprompt_with_prompt_version():
     )
     assert "Version 2:" in v2_rendered
     assert "Test v2" in v2_rendered
+
+
+def _swap_prompt_manager_and_spec(ignore_prompt_manager_model: bool):
+    from litellm.integrations.dotprompt.dotprompt_manager import DotpromptManager
+    from litellm.types.prompts.init_prompts import PromptLiteLLMParams, PromptSpec
+
+    manager = DotpromptManager(
+        prompt_data={"content": "You are a pirate assistant.", "metadata": {"model": "gpt-4o-mini"}},
+        prompt_id="swap-prompt",
+    )
+    spec = PromptSpec(
+        prompt_id="swap-prompt",
+        litellm_params=PromptLiteLLMParams(
+            prompt_id="swap-prompt",
+            prompt_integration="dotprompt",
+            ignore_prompt_manager_model=ignore_prompt_manager_model,
+        ),
+    )
+    return manager, spec
+
+
+@pytest.mark.asyncio
+async def test_async_prompt_spec_ignore_prompt_manager_model_keeps_requested_model():
+    from litellm.types.utils import StandardCallbackDynamicParams
+
+    manager, spec = _swap_prompt_manager_and_spec(ignore_prompt_manager_model=True)
+    model, messages, _ = await manager.async_get_chat_completion_prompt(
+        model="anthropic/claude-haiku-4-5",
+        messages=[{"role": "user", "content": "hi"}],
+        non_default_params={},
+        prompt_id="swap-prompt",
+        prompt_variables=None,
+        dynamic_callback_params=StandardCallbackDynamicParams(),
+        litellm_logging_obj=MagicMock(),
+        prompt_spec=spec,
+    )
+    assert model == "anthropic/claude-haiku-4-5"
+    assert len(messages) == 2
+    assert "pirate" in str(messages[0]["content"])
+
+
+@pytest.mark.asyncio
+async def test_async_prompt_spec_without_ignore_flag_swaps_model():
+    from litellm.types.utils import StandardCallbackDynamicParams
+
+    manager, spec = _swap_prompt_manager_and_spec(ignore_prompt_manager_model=False)
+    model, _, _ = await manager.async_get_chat_completion_prompt(
+        model="anthropic/claude-haiku-4-5",
+        messages=[{"role": "user", "content": "hi"}],
+        non_default_params={},
+        prompt_id="swap-prompt",
+        prompt_variables=None,
+        dynamic_callback_params=StandardCallbackDynamicParams(),
+        litellm_logging_obj=MagicMock(),
+        prompt_spec=spec,
+    )
+    assert model == "gpt-4o-mini"
+
+
+def test_sync_prompt_spec_ignore_prompt_manager_model_keeps_requested_model():
+    from litellm.types.utils import StandardCallbackDynamicParams
+
+    manager, spec = _swap_prompt_manager_and_spec(ignore_prompt_manager_model=True)
+    model, _, _ = manager.get_chat_completion_prompt(
+        model="anthropic/claude-haiku-4-5",
+        messages=[{"role": "user", "content": "hi"}],
+        non_default_params={},
+        prompt_id="swap-prompt",
+        prompt_variables=None,
+        dynamic_callback_params=StandardCallbackDynamicParams(),
+        prompt_spec=spec,
+    )
+    assert model == "anthropic/claude-haiku-4-5"
+
+
+def test_sync_caller_ignore_flag_survives_missing_prompt_spec():
+    from litellm.types.utils import StandardCallbackDynamicParams
+
+    manager, _ = _swap_prompt_manager_and_spec(ignore_prompt_manager_model=False)
+    model, _, _ = manager.get_chat_completion_prompt(
+        model="anthropic/claude-haiku-4-5",
+        messages=[{"role": "user", "content": "hi"}],
+        non_default_params={},
+        prompt_id="swap-prompt",
+        prompt_variables=None,
+        dynamic_callback_params=StandardCallbackDynamicParams(),
+        prompt_spec=None,
+        ignore_prompt_manager_model=True,
+    )
+    assert model == "anthropic/claude-haiku-4-5"

tests/test_litellm/proxy/utils/proxy_logging/test_guardrail_pipeline.py

@@ -818,3 +818,50 @@ async def test_process_prompt_template_async_get_prompt_error_raises(proxy_loggi
             prompt_version=None,
             call_type="completion",
         )
+
+
+@pytest.mark.asyncio
+async def test_process_prompt_template_aresponses_swaps_model_and_merges_input(proxy_logging, monkeypatch):
+    from litellm.proxy.prompts import prompt_registry
+
+    custom_logger = MagicMock()
+    prompt_spec = MagicMock()
+    prompt_spec.litellm_params = MagicMock(prompt_id="resolved-id")
+    monkeypatch.setattr(
+        prompt_registry.IN_MEMORY_PROMPT_REGISTRY,
+        "get_prompt_callback_by_id",
+        lambda *a, **kw: custom_logger,
+    )
+    monkeypatch.setattr(
+        prompt_registry.IN_MEMORY_PROMPT_REGISTRY, "get_prompt_by_id", lambda *a, **kw: prompt_spec
+    )
+
+    logging_obj = MagicMock()
+    logging_obj.async_get_chat_completion_prompt = AsyncMock(
+        return_value=(
+            "gpt-4o-mini",
+            [
+                {"role": "user", "content": "You are a pirate."},
+                {"role": "user", "content": "Who are you?"},
+            ],
+            {},
+        )
+    )
+    data: Dict[str, Any] = {"input": "Who are you?", "model": "anthropic-haiku-4-5", "prompt_id": "x"}
+    await proxy_logging._process_prompt_template(
+        data=data,
+        litellm_logging_obj=logging_obj,
+        prompt_id="x",
+        prompt_version=None,
+        call_type="aresponses",
+    )
+    assert data["model"] == "gpt-4o-mini"
+    assert data["input"] == [
+        {"role": "user", "content": "You are a pirate."},
+        {"role": "user", "content": "Who are you?"},
+    ]
+    assert "messages" not in data
+    assert "prompt_id" not in data
+    hook_kwargs = logging_obj.async_get_chat_completion_prompt.await_args.kwargs
+    assert hook_kwargs["messages"] == [{"role": "user", "content": "Who are you?"}]
+    assert hook_kwargs["prompt_spec"] is prompt_spec

tests/test_litellm/proxy/utils/proxy_logging/test_pre_call_hook.py

@@ -298,6 +298,22 @@ async def test_default_path_still_applies_prompt_templates(proxy_logging, make_u
     process.assert_awaited_once()
 
 
+@pytest.mark.asyncio
+async def test_aresponses_call_type_applies_prompt_templates_before_routing(proxy_logging, make_user_api_key_auth, monkeypatch):
+    """The responses surface must process registry prompts pre-routing so credentials follow the swapped model."""
+    monkeypatch.setattr(litellm, "callbacks", [])
+    proxy_logging.slack_alerting_instance = MagicMock(alerting=None)
+    process = AsyncMock()
+    monkeypatch.setattr(proxy_logging, "_process_prompt_template", process)
+
+    await proxy_logging.pre_call_hook(
+        user_api_key_dict=make_user_api_key_auth(),
+        data={"input": "hi", "model": "m", "prompt_id": "p1", "litellm_logging_obj": MagicMock()},
+        call_type="aresponses",
+    )
+    process.assert_awaited_once()
+
+
 # ---------------------------------------------------------------------------
 # enforces_request_content: which CustomLoggers a guardrails-only walk reaches
 # ---------------------------------------------------------------------------

tests/test_litellm/responses/test_responses_prompt_management.py

@@ -539,3 +539,84 @@ class TestAsyncResponsesAPIPromptManagement:
         assert sent_input[0]["cache_control"] == {"type": "ephemeral"}
         assert sent_input[1] == reasoning_item
         assert sent_input[2]["id"] == "msg_1"
+
+
+# ---------------------------------------------------------------------------
+# Cross-provider model swap guard (prompt swaps model after credential resolution)
+# ---------------------------------------------------------------------------
+
+
+def test_resolve_prompt_swapped_provider_raises_cross_provider_with_credentials():
+    import litellm
+    from litellm.responses.main import _resolve_prompt_swapped_provider
+
+    with pytest.raises(litellm.BadRequestError, match="Refusing to send"):
+        _resolve_prompt_swapped_provider(
+            original_model="anthropic/claude-haiku-4-5",
+            swapped_model="gpt-4o-mini",
+            custom_llm_provider="anthropic",
+            kwargs={"api_key": "sk-ant-test"},
+            prompt_id="p1",
+        )
+
+
+def test_resolve_prompt_swapped_provider_allows_swap_without_credentials():
+    from litellm.responses.main import _resolve_prompt_swapped_provider
+
+    assert (
+        _resolve_prompt_swapped_provider(
+            original_model="anthropic/claude-haiku-4-5",
+            swapped_model="gpt-4o-mini",
+            custom_llm_provider="anthropic",
+            kwargs={},
+            prompt_id="p1",
+        )
+        == "openai"
+    )
+
+
+def test_resolve_prompt_swapped_provider_allows_same_provider_swap_with_credentials():
+    from litellm.responses.main import _resolve_prompt_swapped_provider
+
+    assert (
+        _resolve_prompt_swapped_provider(
+            original_model="openai/gpt-4o",
+            swapped_model="gpt-4o-mini",
+            custom_llm_provider="openai",
+            kwargs={"api_key": "sk-test", "api_base": "https://api.openai.com/v1"},
+            prompt_id="p1",
+        )
+        == "openai"
+    )
+
+
+def test_sync_prompt_swap_cross_provider_with_credentials_raises():
+    import litellm
+    from litellm.responses.main import _apply_prompt_management_to_responses_call
+
+    logging_obj = _make_logging_obj("gpt-4o-mini", [{"role": "user", "content": "hi"}])
+    with pytest.raises(litellm.BadRequestError, match="Refusing to send"):
+        _apply_prompt_management_to_responses_call(
+            input="hi",
+            model="anthropic/claude-haiku-4-5",
+            custom_llm_provider="anthropic",
+            litellm_logging_obj=logging_obj,
+            kwargs={"prompt_id": "p1", "api_key": "sk-ant-test"},
+            local_vars={},
+        )
+
+
+@pytest.mark.asyncio
+async def test_aresponses_prompt_swap_cross_provider_with_credentials_raises():
+    import litellm
+
+    logging_obj = _make_logging_obj("gpt-4o-mini", [{"role": "user", "content": "hi"}])
+    logging_obj.async_failure_handler = AsyncMock()
+    with pytest.raises(litellm.BadRequestError, match="Refusing to send"):
+        await litellm.aresponses(
+            input="hi",
+            model="anthropic/claude-haiku-4-5",
+            litellm_logging_obj=logging_obj,
+            prompt_id="p1",
+            api_key="sk-ant-test",
+        )

tests/test_litellm/responses/test_responses_utils.py

@@ -724,3 +724,20 @@ class TestMergePromptManagementInputReshape:
         )
 
         assert result == merged
+
+
+class TestResponsesInputToChatMessages:
+    def test_none_input_returns_empty_list(self):
+        assert ResponsesAPIRequestUtils.responses_input_to_chat_messages(None) == []
+
+    def test_str_input_becomes_user_message(self):
+        assert ResponsesAPIRequestUtils.responses_input_to_chat_messages("hi") == [
+            {"role": "user", "content": "hi"}
+        ]
+
+    def test_list_input_keeps_only_role_items(self):
+        reasoning_item = {"type": "reasoning", "id": "rs_1", "summary": []}
+        user_message = {"role": "user", "content": "hi"}
+        assert ResponsesAPIRequestUtils.responses_input_to_chat_messages(
+            [reasoning_item, user_message, "stray"]
+        ) == [user_message]