Python: reject misaligned base64 embedding payloads with a descriptive error

python/packages/openai/agent_framework_openai/_embedding_client.py

@@ -296,6 +296,13 @@ async def get_embeddings(
             if encoding == "base64" and isinstance(item.embedding, str):
                 # Decode base64-encoded floats (little-endian IEEE 754)
                 raw = base64.b64decode(item.embedding)
+                if len(raw) % 4:
+                    # A misaligned buffer would otherwise fail inside struct.unpack with a
+                    # bare buffer-size error and no hint about which response item broke.
+                    raise ValueError(
+                        f"Base64 encoded embedding for input index {item.index} decoded to {len(raw)} bytes, "
+                        "which cannot be split into 4-byte little-endian floats. The response payload is malformed."
+                    )
                 vector = list(struct.unpack(f"<{len(raw) // 4}f", raw))
             else:
                 vector = item.embedding

python/packages/openai/tests/openai/test_openai_embedding_client.py

@@ -232,6 +232,35 @@ async def test_openai_base64_decoding(openai_unit_test_env: dict[str, str]) -> N
     for expected, actual in zip(raw_floats, result[0].vector):
         assert abs(expected - actual) < 1e-6
 
+async def test_openai_base64_misaligned_payload_raises_descriptive_error(openai_unit_test_env: dict[str, str]) -> None:
+    """A truncated base64 payload must fail with a clear error naming the input index,
+    not a bare struct buffer-size error."""
+    import base64
+    import struct
+
+    # One well formed float (4 bytes) plus a stray byte.
+    misaligned = base64.b64encode(struct.pack("<1f", 0.5) + b"\x00").decode()
+
+    mock_item = MagicMock()
+    mock_item.embedding = misaligned
+    mock_item.index = 0
+
+    mock_response = MagicMock()
+    mock_response.data = [mock_item]
+    mock_response.model = "text-embedding-3-small"
+    mock_response.usage = MagicMock(prompt_tokens=3, total_tokens=3)
+
+    client = OpenAIEmbeddingClient()
+    client.client = MagicMock()
+    client.client.embeddings = MagicMock()
+    client.client.embeddings.create = AsyncMock(return_value=mock_response)
+
+    options: OpenAIEmbeddingOptions = {"encoding_format": "base64"}
+
+    with pytest.raises(ValueError, match="cannot be split into 4-byte little-endian floats"):
+        await client.get_embeddings(["test"], options=options)
+
+
 
 async def test_openai_error_when_no_model() -> None:
     client = cast(Any, object.__new__(OpenAIEmbeddingClient))