Files
routstr-core/tests/integration/test_embeddings.py
T
2025-12-11 13:58:57 +08:00

98 lines
3.5 KiB
Python

import json
from typing import Any
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from httpx import AsyncClient
@pytest.mark.integration
@pytest.mark.asyncio
async def test_proxy_embeddings_endpoint(authenticated_client: AsyncClient) -> None:
"""Test the embeddings endpoint proxy functionality"""
test_payload = {
"model": "text-embedding-ada-002",
"input": "The quick brown fox",
}
mock_response_data = {
"object": "list",
"data": [
{"object": "embedding", "embedding": [0.0023, -0.0012, 0.0045], "index": 0}
],
"model": "text-embedding-ada-002",
"usage": {"prompt_tokens": 5, "total_tokens": 5},
}
with patch("httpx.AsyncClient.send") as mock_send:
# Create a proper async generator for iter_bytes
async def mock_iter_bytes(*args: Any, **kwargs: Any) -> Any:
yield json.dumps(mock_response_data).encode()
mock_response = AsyncMock()
mock_response.status_code = 200
mock_response.headers = {"content-type": "application/json"}
mock_response.text = json.dumps(mock_response_data)
# Use MagicMock for synchronous .json() method
mock_response.json = MagicMock(return_value=mock_response_data)
mock_response.iter_bytes = mock_iter_bytes
mock_response.aiter_bytes = mock_iter_bytes
mock_send.return_value = mock_response
# Make POST request to embeddings endpoint
response = await authenticated_client.post("/v1/embeddings", json=test_payload)
assert response.status_code == 200
response_data = response.json()
assert response_data["object"] == "list"
assert len(response_data["data"]) == 1
assert response_data["data"][0]["object"] == "embedding"
# Verify request was forwarded
mock_send.assert_called_once()
forwarded_request = mock_send.call_args[0][0]
# Verify the path ends with embeddings
# Note: forwarded path might be full URL
assert str(forwarded_request.url).endswith("embeddings")
@pytest.mark.integration
@pytest.mark.asyncio
async def test_model_case_insensitivity(authenticated_client: AsyncClient) -> None:
"""Test that model lookups are case insensitive"""
# We'll use a mixed-case model ID that should match the lowercase one in the system
# We assume 'gpt-3.5-turbo' is available in the mock env/database
test_payload = {
"model": "GPT-3.5-TURBO",
"messages": [{"role": "user", "content": "Hello"}],
}
with patch("httpx.AsyncClient.send") as mock_send:
mock_response_data = {
"id": "chatcmpl-123",
"object": "chat.completion",
"choices": [{"message": {"content": "Hi"}}],
"usage": {"total_tokens": 10},
}
async def mock_iter_bytes(*args: Any, **kwargs: Any) -> Any:
yield json.dumps(mock_response_data).encode()
mock_response = AsyncMock()
mock_response.status_code = 200
mock_response.headers = {"content-type": "application/json"}
mock_response.text = json.dumps(mock_response_data)
mock_response.json = MagicMock(return_value=mock_response_data)
mock_response.iter_bytes = mock_iter_bytes
mock_response.aiter_bytes = mock_iter_bytes
mock_send.return_value = mock_response
response = await authenticated_client.post(
"/v1/chat/completions", json=test_payload
)
assert response.status_code == 200