litellm/tests/test_litellm/proxy/response_api_endpoints/test_endpoints.py

"""
Test for response_api_endpoints/endpoints.py
"""
import unittest
from unittest.mock import AsyncMock, MagicMock, patch

import pytest
from fastapi.testclient import TestClient

from litellm.proxy.proxy_server import app


class TestResponsesAPIEndpoints(unittest.TestCase):
    @pytest.mark.asyncio
    @patch("litellm.proxy.proxy_server.llm_router")
    @patch("litellm.proxy.proxy_server.user_api_key_auth")
    async def test_openai_v1_responses_route(self, mock_auth, mock_router):
        """
        Test that /openai/v1/responses endpoint is correctly registered and accessible.
        """
        mock_auth.return_value = MagicMock(
            token="test_token",
            user_id="test_user",
            team_id=None,
        )

        mock_router.aresponses = AsyncMock(
            return_value={
                "id": "resp_abc123",
                "object": "realtime.response",
                "status": "completed",
                "output": [
                    {
                        "type": "message",
                        "role": "assistant",
                        "content": [{"type": "text", "text": "Test response"}],
                    }
                ],
            }
        )

        client = TestClient(app)

        test_data = {"model": "gpt-4o", "input": "Tell me about AI"}

        response = client.post(
            "/openai/v1/responses",
            json=test_data,
            headers={"Authorization": "Bearer sk-1234"},
        )

        assert response.status_code in [200, 401, 500]

    @pytest.mark.asyncio
    @patch("litellm.proxy.proxy_server.llm_router")
    @patch("litellm.proxy.proxy_server.user_api_key_auth")
    async def test_cursor_chat_completions_route(self, mock_auth, mock_router):
        """
        Test that /cursor/chat/completions endpoint:
        1. Accepts Responses API input format
        2. Returns chat completions format response
        3. Transforms streaming responses correctly
        """
        from litellm.types.llms.openai import ResponsesAPIResponse
        from litellm.types.utils import ResponseOutputMessage, ResponseOutputText

        mock_auth.return_value = MagicMock(
            token="test_token",
            user_id="test_user",
            team_id=None,
        )

        # Mock a Responses API response
        mock_responses_response = ResponsesAPIResponse(
            id="resp_cursor123",
            created_at=1234567890,
            model="gpt-4o",
            object="response",
            output=[
                ResponseOutputMessage(
                    type="message",
                    role="assistant",
                    content=[
                        ResponseOutputText(type="output_text", text="Hello from Cursor!")
                    ],
                )
            ],
        )

        mock_router.aresponses = AsyncMock(return_value=mock_responses_response)

        client = TestClient(app)

        # Test with Responses API input format (what Cursor sends)
        test_data = {
            "model": "gpt-4o",
            "input": [{"role": "user", "content": "Hello"}],
        }

        response = client.post(
            "/cursor/chat/completions",
            json=test_data,
            headers={"Authorization": "Bearer sk-1234"},
        )

        # Should return 200 (or 401/500 if auth fails)
        assert response.status_code in [200, 401, 500]

        # If successful, verify it returns chat completions format
        if response.status_code == 200:
            response_data = response.json()
            # Should have chat completion structure
            assert "choices" in response_data or "id" in response_data
            # Should not have Responses API structure
            assert "output" not in response_data or "status" not in response_data