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chore: import upstream snapshot with attribution
2026-07-13 13:00:43 +08:00

209 lines
7.0 KiB
Python

"""Verify every embedding adapter posts to ``base_url`` VERBATIM.
This guards the v1.3.0 contract: what the user types in the Settings UI is
what hits the wire. No automatic ``/embeddings`` / ``/api/embed`` /
``/{api_version}/embed`` appending. Adapters get the URL once and use it.
"""
from __future__ import annotations
from typing import Any
import httpx
import pytest
from deeptutor.services.embedding.adapters.base import EmbeddingRequest
from deeptutor.services.embedding.adapters.cohere import CohereEmbeddingAdapter
from deeptutor.services.embedding.adapters.jina import JinaEmbeddingAdapter
from deeptutor.services.embedding.adapters.ollama import OllamaEmbeddingAdapter
from deeptutor.services.embedding.adapters.openai_compatible import (
OpenAICompatibleEmbeddingAdapter,
)
CUSTOM_URL = "https://internal-gateway.test/v999/foo/embeddings-bar"
def _capture_url(monkeypatch: pytest.MonkeyPatch) -> dict[str, Any]:
"""Patch ``httpx.AsyncClient.post`` to record the URL it was called with."""
captured: dict[str, Any] = {}
real_init = httpx.AsyncClient.__init__
def fake_init(self: httpx.AsyncClient, **kwargs: Any) -> None: # noqa: ANN001
real_init(self, **kwargs)
async def fake_post(self: httpx.AsyncClient, url: str, **kwargs: Any) -> httpx.Response:
captured["url"] = url
captured["json"] = kwargs.get("json")
captured["headers"] = kwargs.get("headers")
request = httpx.Request("POST", url)
# Different adapters expect different response shapes.
return httpx.Response(
status_code=200,
json={
"data": [{"embedding": [0.1, 0.2, 0.3]}],
"embeddings": [[0.1, 0.2, 0.3]],
"model": "test-model",
},
request=request,
)
monkeypatch.setattr(httpx.AsyncClient, "__init__", fake_init)
monkeypatch.setattr(httpx.AsyncClient, "post", fake_post)
return captured
def test_public_embedding_providers_do_not_use_openai_sdk_autopath() -> None:
from deeptutor.services.config.provider_runtime import EMBEDDING_PROVIDERS
for name, spec in EMBEDDING_PROVIDERS.items():
if name == "custom_openai_sdk":
continue
assert spec.adapter != "openai_sdk", name
@pytest.mark.asyncio
async def test_openai_compat_url_verbatim(monkeypatch: pytest.MonkeyPatch) -> None:
captured = _capture_url(monkeypatch)
adapter = OpenAICompatibleEmbeddingAdapter(
{
"api_key": "sk-test",
"base_url": CUSTOM_URL,
"model": "test-model",
"dimensions": 0,
"send_dimensions": False,
"request_timeout": 5,
}
)
await adapter.embed(EmbeddingRequest(texts=["hello"], model="test-model"))
assert captured["url"] == CUSTOM_URL
@pytest.mark.asyncio
async def test_openai_compat_forwards_real_authorization_header(
monkeypatch: pytest.MonkeyPatch,
) -> None:
captured = _capture_url(monkeypatch)
adapter = OpenAICompatibleEmbeddingAdapter(
{
"api_key": "sk-real",
"base_url": CUSTOM_URL,
"model": "test-model",
"dimensions": 0,
"send_dimensions": False,
"request_timeout": 5,
}
)
await adapter.embed(EmbeddingRequest(texts=["hello"], model="test-model"))
assert captured["headers"]["Authorization"] == "Bearer sk-real"
@pytest.mark.asyncio
async def test_openai_compat_suppresses_no_key_placeholder_header(
monkeypatch: pytest.MonkeyPatch,
) -> None:
captured = _capture_url(monkeypatch)
adapter = OpenAICompatibleEmbeddingAdapter(
{
"api_key": "sk-no-key-required",
"base_url": CUSTOM_URL,
"model": "test-model",
"dimensions": 0,
"send_dimensions": False,
"request_timeout": 5,
}
)
await adapter.embed(EmbeddingRequest(texts=["hello"], model="test-model"))
assert "Authorization" not in captured["headers"]
assert "api-key" not in captured["headers"]
@pytest.mark.asyncio
async def test_jina_url_verbatim(monkeypatch: pytest.MonkeyPatch) -> None:
captured = _capture_url(monkeypatch)
# Jina parses `data["data"]` items; our fake response above includes that
# shape so the adapter doesn't crash on parsing.
adapter = JinaEmbeddingAdapter(
{
"api_key": "sk-test",
"base_url": CUSTOM_URL,
"model": "jina-embeddings-v3",
"dimensions": 0,
"send_dimensions": False,
"request_timeout": 5,
}
)
await adapter.embed(EmbeddingRequest(texts=["hello"], model="jina-embeddings-v3"))
assert captured["url"] == CUSTOM_URL
@pytest.mark.asyncio
async def test_ollama_url_verbatim(monkeypatch: pytest.MonkeyPatch) -> None:
captured = _capture_url(monkeypatch)
adapter = OllamaEmbeddingAdapter(
{
"api_key": "",
"base_url": CUSTOM_URL,
"model": "nomic-embed-text",
"dimensions": 0,
"request_timeout": 5,
}
)
await adapter.embed(EmbeddingRequest(texts=["hello"], model="nomic-embed-text"))
assert captured["url"] == CUSTOM_URL
@pytest.mark.asyncio
async def test_cohere_url_verbatim(monkeypatch: pytest.MonkeyPatch) -> None:
captured = _capture_url(monkeypatch)
# Cohere v2 response: `embeddings.float` is the actual array of vectors.
async def fake_post(self: httpx.AsyncClient, url: str, **kwargs: Any) -> httpx.Response:
captured["url"] = url
request = httpx.Request("POST", url)
return httpx.Response(
status_code=200,
json={
"embeddings": {"float": [[0.1, 0.2, 0.3]]},
"model": "embed-v4.0",
},
request=request,
)
monkeypatch.setattr(httpx.AsyncClient, "post", fake_post)
adapter = CohereEmbeddingAdapter(
{
"api_key": "co-test",
"base_url": CUSTOM_URL,
"model": "embed-v4.0",
"api_version": "v2",
"dimensions": 1024,
"request_timeout": 5,
}
)
await adapter.embed(EmbeddingRequest(texts=["hello"], model="embed-v4.0"))
assert captured["url"] == CUSTOM_URL
@pytest.mark.asyncio
async def test_openai_compat_appends_only_azure_query_string(
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""`?api-version=...` is a query param, not a path component, so it
is still appended even under the URL-transparency rule."""
captured = _capture_url(monkeypatch)
adapter = OpenAICompatibleEmbeddingAdapter(
{
"api_key": "az-test",
"base_url": CUSTOM_URL,
"model": "text-embedding-3-large",
"api_version": "2024-02-01",
"dimensions": 0,
"send_dimensions": False,
"request_timeout": 5,
}
)
await adapter.embed(EmbeddingRequest(texts=["hi"], model="text-embedding-3-large"))
assert captured["url"] == f"{CUSTOM_URL}?api-version=2024-02-01"