From 44a2e74123d33df774c3f9a58c2a3e73c0c7a0ce Mon Sep 17 00:00:00 2001
From: Aasif-Simpplr <aasif.multani@simpplr.com>
Date: Mon, 5 Oct 2026 15:50:47 +0530
Subject: [PATCH] fix(embedding): reject mock input counts a provider would
 reject

An empty input list or more than 2048 inputs now raises BadRequestError
instead of returning zero rows or one row per item without limit, matching
OpenAI's documented bounds
---
 litellm/litellm_core_utils/mock_functions.py  | 27 ++++++++++++-------
 .../litellm_core_utils/test_mock_functions.py |  7 +++++
 2 files changed, 25 insertions(+), 9 deletions(-)

diff --git a/litellm/litellm_core_utils/mock_functions.py b/litellm/litellm_core_utils/mock_functions.py
index 94d0ef8e423..4d33008d692 100644
--- a/litellm/litellm_core_utils/mock_functions.py
+++ b/litellm/litellm_core_utils/mock_functions.py
@@ -1,5 +1,7 @@
 from collections.abc import Sequence
+from typing import Final
 
+from ..exceptions import BadRequestError
 from ..types.utils import (
     Embedding,
     EmbeddingResponse,
@@ -8,13 +10,15 @@ from ..types.utils import (
     Usage,
 )
 
+# OpenAI caps an embedding input array at 2048 items, as of 2026-10-05:
+# https://platform.openai.com/docs/api-reference/embeddings/create
+_MAX_EMBEDDING_INPUTS: Final = 2048
+
 
 def _embedding_input_count(embedding_input: str | Sequence[str] | Sequence[int] | Sequence[Sequence[int]]) -> int:
-    match embedding_input:
-        case str() | [int(), *_]:
-            return 1
-        case _:
-            return len(embedding_input)
+    if isinstance(embedding_input, str) or (len(embedding_input) > 0 and isinstance(embedding_input[0], int)):
+        return 1
+    return len(embedding_input)
 
 
 def mock_embedding(
@@ -26,12 +30,17 @@ def mock_embedding(
         mock_response = [0.0] * 1536
     elif mock_response == "error":
         raise Exception("Mock error")
+    input_count: Final = _embedding_input_count(embedding_input)
+    if not 1 <= input_count <= _MAX_EMBEDDING_INPUTS:
+        raise BadRequestError(
+            message=f"input must contain between 1 and {_MAX_EMBEDDING_INPUTS} items, got {input_count}",
+            model=model,
+            llm_provider=None,
+            body={"param": "input"},
+        )
     return EmbeddingResponse(
         model=model,
-        data=[
-            Embedding(embedding=mock_response, index=index, object="embedding")
-            for index in range(_embedding_input_count(embedding_input))
-        ],
+        data=[Embedding(embedding=mock_response, index=index, object="embedding") for index in range(input_count)],
         usage=Usage(prompt_tokens=10, completion_tokens=0),
     )
 
diff --git a/tests/unit/litellm_core_utils/test_mock_functions.py b/tests/unit/litellm_core_utils/test_mock_functions.py
index 841336f9917..e362ae98055 100644
--- a/tests/unit/litellm_core_utils/test_mock_functions.py
+++ b/tests/unit/litellm_core_utils/test_mock_functions.py
@@ -3,6 +3,7 @@ from typing import Final
 import pytest
 
 import litellm
+from litellm.exceptions import BadRequestError
 
 
 @pytest.mark.parametrize(
@@ -21,3 +22,9 @@ def test_mock_embedding_returns_one_embedding_per_input(embedding_input: object,
 
     assert [row["index"] for row in response.data] == list(range(expected_count))
     assert [row["embedding"] for row in response.data] == [vector] * expected_count
+
+
+@pytest.mark.parametrize("embedding_input", [[], ["text"] * 2049])
+def test_mock_embedding_rejects_input_count_a_provider_would_reject(embedding_input: list[str]) -> None:
+    with pytest.raises(BadRequestError, match="between 1 and 2048 items"):
+        litellm.embedding(model="openai/test-model", input=embedding_input, mock_response=[0.1, 0.2])