From 40cf96e7806962df26944a15f173fefc324f9ce4 Mon Sep 17 00:00:00 2001
From: vanika02 <vanikadangi02@gmail.com>
Date: Fri, 14 Aug 2026 15:15:58 +0000
Subject: [PATCH] fix(responses): validate invalid input types

---
 litellm/responses/main.py                     | 12 +++++++
 .../test_responses_prompt_management.py       | 36 +++++++++++++++++++
 2 files changed, 48 insertions(+)

diff --git a/litellm/responses/main.py b/litellm/responses/main.py
index e0af363b1a5..5b9dc228e7c 100644
--- a/litellm/responses/main.py
+++ b/litellm/responses/main.py
@@ -465,6 +465,12 @@ async def aresponses(
         ) 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}]
+            elif not isinstance(input, list):
+                raise litellm.BadRequestError(
+                    message=f"'input' must be a string or list of input items, got {type(input).__name__}",
+                    model=model,
+                    llm_provider=custom_llm_provider or "unknown",
+                )
             else:
                 client_input = [item for item in input if isinstance(item, dict) and "role" in item]
             (
@@ -579,6 +585,12 @@ def _apply_prompt_management_to_responses_call(
 
     if isinstance(input, str):
         client_input: list[AllMessageValues] = [{"role": "user", "content": input}]
+    elif not isinstance(input, list):
+        raise litellm.BadRequestError(
+            message=f"'input' must be a string or list of input items, got {type(input).__name__}",
+            model=model,
+            llm_provider=custom_llm_provider or "unknown",
+        )
     else:
         client_input = [item for item in input if isinstance(item, dict) and "role" in item]
 
diff --git a/tests/test_litellm/responses/test_responses_prompt_management.py b/tests/test_litellm/responses/test_responses_prompt_management.py
index 7044d8384f8..d76b0f93571 100644
--- a/tests/test_litellm/responses/test_responses_prompt_management.py
+++ b/tests/test_litellm/responses/test_responses_prompt_management.py
@@ -19,6 +19,7 @@ from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
+import litellm
 from litellm.integrations.anthropic_cache_control_hook import (
     AnthropicCacheControlHook,
 )
@@ -410,6 +411,23 @@ class TestResponsesAPIPromptManagement:
         assert handler_call_kwargs.get("custom_llm_provider") == "anthropic"
 
 
+    def test_invalid_input_type_raises_bad_request_error(self):
+        """Non-string, non-list input should raise BadRequestError."""
+        logging_obj = _make_logging_obj(
+            merged_model="openai/gpt-4o",
+            merged_messages=[],
+        )
+
+        patches = _patch_responses_dispatch()
+        with patches[0], patches[1], patches[2], patches[3]:
+            with pytest.raises(litellm.BadRequestError, match="input"):
+                litellm.responses(
+                    input=12345,
+                    model="gpt-4o",
+                    prompt_id="test-prompt",
+                    litellm_logging_obj=logging_obj,
+                )
+
 class TestAsyncResponsesAPIPromptManagement:
     """Tests for the async aresponses() prompt management path.
 
@@ -539,3 +557,21 @@ class TestAsyncResponsesAPIPromptManagement:
         assert sent_input[0]["cache_control"] == {"type": "ephemeral"}
         assert sent_input[1] == reasoning_item
         assert sent_input[2]["id"] == "msg_1"
+
+    @pytest.mark.asyncio
+    async def test_async_invalid_input_type_raises_bad_request_error(self):
+        """Non-string, non-list input should raise BadRequestError."""
+        logging_obj = _make_logging_obj(
+            merged_model="openai/gpt-4o",
+            merged_messages=[],
+        )
+        logging_obj.async_failure_handler = AsyncMock()
+        patches = _patch_responses_dispatch()
+        with patches[0], patches[1], patches[2], patches[3]:
+            with pytest.raises(litellm.BadRequestError, match="input"):
+                await litellm.aresponses(
+                    input=12345,
+                    model="gpt-4o",
+                    prompt_id="test-prompt",
+                    litellm_logging_obj=logging_obj,
+                )
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