litellm/tests/integration/compatibility/test_embedding_path_aliases.py
devin-ai-integration[bot] 1c0f722aae
test(integration): cover embeddings endpoint contracts (#44660)
* test(integration): cover embeddings endpoint contracts

* test(integration): cover azure, vllm, nebius token arrays and flag bedrock token-array bugs

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

* test(integration): pin path-over-body model routing for azure embeddings

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

* test(integration): pin embeddings base64 relay, flat token arrays and api-key-only auth

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

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo <mateo@berri.ai>
2026-10-14 03:38:12 +00:00

216 lines
8.3 KiB
Python

import base64
import json
import struct
from typing import Final, Literal
import httpx
import openai
import pytest
from integration._support.client import Gateway
from integration._support.wire import Reply, Request, wire_server
from pydantic import BaseModel, ConfigDict, JsonValue, TypeAdapter
_TEXT: Final = "path alias embedding marker"
_VECTOR: Final = (0.25, 0.5, 0.75)
_JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue])
class _Embedding(BaseModel):
model_config = ConfigDict(extra="forbid")
object: Literal["embedding"]
index: int
embedding: list[float]
class _Usage(BaseModel):
prompt_tokens: int
total_tokens: int
class _EmbeddingResponse(BaseModel):
data: tuple[_Embedding, ...]
usage: _Usage
def _assert_raw_embedding_response(response: httpx.Response) -> None:
assert response.status_code == 200, response.text
payload: Final = _EmbeddingResponse.model_validate_json(response.content)
assert [item.model_dump() for item in payload.data] == [
{"object": "embedding", "index": 0, "embedding": list(_VECTOR)}
], response.text
assert (payload.usage.prompt_tokens, payload.usage.total_tokens) == (1, 1), response.text
def _reply(encoding_format: str | None) -> Reply:
embedding: Final = (
base64.b64encode(struct.pack("<3f", *_VECTOR)).decode("ascii") if encoding_format == "base64" else list(_VECTOR)
)
return Reply(
body=json.dumps(
{
"object": "list",
"data": [{"object": "embedding", "index": 0, "embedding": embedding}],
"model": "text-embedding-3-small",
"usage": {"prompt_tokens": 1, "total_tokens": 1},
}
).encode()
)
_AZURE_SDK_BODY: Final = {
"model": "text-embedding-3-small",
"input": _TEXT,
"encoding_format": "base64",
}
def _drop_bearer_auth(request: httpx.Request) -> None:
request.headers.pop("authorization", None)
assert "api-key" in request.headers, dict(request.headers)
def _azure_sdk_embedding(
gateway: Gateway,
deployment: str | None,
api_key: str,
model: str,
) -> openai.types.CreateEmbeddingResponse:
with (
httpx.Client(trust_env=False, event_hooks={"request": [_drop_bearer_auth]}) as http_client,
openai.AzureOpenAI(
azure_endpoint=str(gateway.client.base_url).rstrip("/"),
azure_deployment=deployment,
api_key=api_key,
api_version="2024-10-21",
max_retries=0,
http_client=http_client,
) as client,
):
return client.embeddings.create(model=model, input=_TEXT)
@pytest.mark.parametrize(
"surface",
("azure_sdk", "azure_sdk_path_over_body", "deployments_raw", "engines_raw", "bare"),
ids=("azure-sdk", "azure-sdk-path-over-body", "deployments-path", "engines-path", "bare-model"),
)
def test_embedding_model_is_resolved_from_each_endpoint_surface(
gateway: Gateway,
surface: Literal["azure_sdk", "azure_sdk_path_over_body", "deployments_raw", "engines_raw", "bare"],
) -> None:
expected_key: Final = (
"synthetic-key-a"
if surface in ("azure_sdk", "azure_sdk_path_over_body", "deployments_raw")
else "synthetic-key-b"
)
# openai-python 2.33.0 defaults omitted encoding_format to base64: https://github.com/openai/openai-python/blob/v2.33.0/src/openai/resources/embeddings.py
expected_body: Final = (
_AZURE_SDK_BODY
if surface in ("azure_sdk", "azure_sdk_path_over_body")
else {"model": "text-embedding-3-small", "input": _TEXT}
)
def respond(request: Request) -> Reply:
assert request.method == "POST"
assert request.target == "/v1/embeddings"
assert request.headers["authorization"] == f"Bearer {expected_key}"
body: Final = _JSON_OBJECT.validate_json(request.body)
assert body == expected_body, body
return _reply("base64" if surface in ("azure_sdk", "azure_sdk_path_over_body") else None)
with wire_server(respond) as wire, gateway.scenario() as scenario:
group_a: Final = scenario.model(
model="openai/text-embedding-3-small",
api_base=f"{wire.url}/v1",
api_key="synthetic-key-a",
)
group_b: Final = scenario.model(
model="openai/text-embedding-3-small",
api_base=f"{wire.url}/v1",
api_key="synthetic-key-b",
)
virtual_key: Final = scenario.key()
if surface in ("azure_sdk", "azure_sdk_path_over_body"):
deployment: Final = group_a if surface == "azure_sdk_path_over_body" else None
request_model: Final = group_b if surface == "azure_sdk_path_over_body" else group_a
response: Final = _azure_sdk_embedding(gateway, deployment, virtual_key, request_model)
if surface == "azure_sdk":
assert response.model == group_a, response.model_dump_json()
assert [item.embedding for item in response.data] == [list(_VECTOR)], response.model_dump_json()
assert [item.index for item in response.data] == [0], response.model_dump_json()
assert (response.usage.prompt_tokens, response.usage.total_tokens) == (1, 1), response.model_dump_json()
elif surface == "deployments_raw":
raw_response: Final = gateway.client.post(
f"/openai/deployments/{group_a}/embeddings?api-version=2024-10-21",
json={"input": _TEXT},
headers={"api-key": virtual_key},
)
_assert_raw_embedding_response(raw_response)
elif surface == "engines_raw":
raw_response = gateway.request(
"POST",
f"/engines/{group_b}/embeddings",
{"input": _TEXT},
key=virtual_key,
)
_assert_raw_embedding_response(raw_response)
else:
raw_response = gateway.request(
"POST",
"/embeddings",
{"model": group_b, "input": _TEXT},
key=virtual_key,
)
_assert_raw_embedding_response(raw_response)
assert [(request.method, request.target) for request in wire.drain()] == [("POST", "/v1/embeddings")]
def test_azure_sdk_response_reports_the_path_group_that_served_it(gateway: Gateway) -> None:
pytest.skip(
"BUG: AzureOpenAI with azure_deployment=<group_a> and model=<group_b> is served by group_a but the response model reports group_b"
)
def respond(request: Request) -> Reply:
assert request.method == "POST"
assert request.target == "/v1/embeddings"
assert request.headers["authorization"] == "Bearer synthetic-key-a"
body: Final = _JSON_OBJECT.validate_json(request.body)
assert body == _AZURE_SDK_BODY, body
return _reply("base64")
with wire_server(respond) as wire, gateway.scenario() as scenario:
group_a: Final = scenario.model(
model="openai/text-embedding-3-small",
api_base=f"{wire.url}/v1",
api_key="synthetic-key-a",
)
group_b: Final = scenario.model(
model="openai/text-embedding-3-small",
api_base=f"{wire.url}/v1",
api_key="synthetic-key-b",
)
virtual_key: Final = scenario.key()
response: Final = _azure_sdk_embedding(gateway, group_a, virtual_key, group_b)
assert response.model == group_a, response.model_dump_json()
assert [(request.method, request.target) for request in wire.drain()] == [("POST", "/v1/embeddings")]
def test_deployments_embedding_rejects_invalid_key_without_upstream_request(gateway: Gateway) -> None:
def respond(request: Request) -> Reply:
raise AssertionError(f"Invalid key reached the peer: {request.method} {request.target}")
with wire_server(respond) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(
model="openai/text-embedding-3-small",
api_base=f"{wire.url}/v1",
api_key="synthetic-key-a",
)
response: Final = gateway.client.post(
f"/openai/deployments/{model}/embeddings?api-version=2024-10-21",
json={"input": _TEXT},
headers={"api-key": "sk-not-a-real-key"},
)
assert response.status_code == 401, response.text
assert wire.drain() == ()