mulit-agent/mulit_agent/tests/test_openai_compatible_provider.py

import json

from mulit_agent_app.infrastructure.openai_compatible_provider import (
    _MAX_TOOL_ROUNDS,
    OpenAICompatibleProvider,
)
from mulit_agent_app.infrastructure.provider_factory import (
    _MAX_TOOL_ROUNDS as PROVIDER_FACTORY_MAX_TOOL_ROUNDS,
)


class _Credentials:
    def load_llm_api_key(self):
        return "test-key"


class _Response:
    def __enter__(self):
        return self

    def __exit__(self, *args):
        return False

    def read(self):
        return json.dumps({"choices": [{"message": {"content": "  模型结果  "}}]}).encode("utf-8")


def test_all_provider_tool_round_limits_allow_long_desktop_workflows():
    assert _MAX_TOOL_ROUNDS == 200
    assert PROVIDER_FACTORY_MAX_TOOL_ROUNDS == 200


def test_provider_posts_a_chat_completion(monkeypatch, tmp_path):
    captured = {}

    def fake_urlopen(request, timeout):
        captured["url"] = request.full_url
        captured["body"] = json.loads(request.data.decode("utf-8"))
        captured["authorization"] = request.get_header("Authorization")
        captured["timeout"] = timeout
        return _Response()

    monkeypatch.setattr("mulit_agent_app.infrastructure.openai_compatible_provider.urlopen", fake_urlopen)

    output = OpenAICompatibleProvider("https://api.example.test/v1", "example-model", _Credentials()).generate("请总结")

    assert output == "模型结果"
    assert captured == {
        "url": "https://api.example.test/v1/chat/completions",
        "body": {"model": "example-model", "messages": [{"role": "user", "content": "请总结"}], "stream": False},
        "authorization": "Bearer test-key",
        "timeout": 90,
    }


def test_provider_sends_the_conversation_history_before_the_new_turn(monkeypatch):
    captured = {}

    def fake_urlopen(request, timeout):
        captured["body"] = json.loads(request.data.decode("utf-8"))
        return _Response()

    monkeypatch.setattr("mulit_agent_app.infrastructure.openai_compatible_provider.urlopen", fake_urlopen)

    output = OpenAICompatibleProvider("https://api.example.test/v1", "example-model", _Credentials()).generate(
        "把它复制到 D:\\target",
        history=(("user", "下载到 D:\\demo"), ("assistant", "已下载到 D:\\demo\\a.zip")),
    )

    assert output == "模型结果"
    assert captured["body"]["messages"] == [
        {"role": "user", "content": "下载到 D:\\demo"},
        {"role": "assistant", "content": "已下载到 D:\\demo\\a.zip"},
        {"role": "user", "content": "把它复制到 D:\\target"},
    ]


def test_provider_without_history_still_sends_a_single_user_message(monkeypatch):
    captured = {}

    def fake_urlopen(request, timeout):
        captured["body"] = json.loads(request.data.decode("utf-8"))
        return _Response()

    monkeypatch.setattr("mulit_agent_app.infrastructure.openai_compatible_provider.urlopen", fake_urlopen)

    OpenAICompatibleProvider("https://api.example.test/v1", "example-model", _Credentials()).generate("请总结")

    assert captured["body"]["messages"] == [{"role": "user", "content": "请总结"}]


def test_provider_removes_reasoning_tags_before_returning_result(monkeypatch):
    class ThinkingResponse(_Response):
        def read(self):
            return json.dumps({"choices": [{"message": {"content": "<think>内部推理</think>最终答案"}}]}).encode("utf-8")

    monkeypatch.setattr(
        "mulit_agent_app.infrastructure.openai_compatible_provider.urlopen", lambda request, timeout: ThinkingResponse()
    )

    output = OpenAICompatibleProvider("https://api.example.test/v1", "example-model", _Credentials()).generate("请总结")

    assert output == "最终答案"


def test_provider_executes_confirmed_local_tool_call_before_returning_answer(monkeypatch):
    responses = [
        {
            "choices": [
                {
                    "message": {
                        "content": None,
                        "tool_calls": [
                            {
                                "id": "call-1",
                                "type": "function",
                                "function": {"name": "run_powershell", "arguments": '{"command":"Get-Date"}'},
                            }
                        ],
                    }
                }
            ]
        },
        {"choices": [{"message": {"content": "已实际完成本机操作。"}}]},
    ]
    captured: list[dict[str, object]] = []

    class Response:
        def __init__(self, payload):
            self.payload = payload

        def __enter__(self):
            return self

        def __exit__(self, *args):
            return False

        def read(self):
            return json.dumps(self.payload).encode("utf-8")

    def fake_urlopen(request, timeout):
        captured.append(json.loads(request.data.decode("utf-8")))
        return Response(responses.pop(0))

    monkeypatch.setattr("mulit_agent_app.infrastructure.openai_compatible_provider.urlopen", fake_urlopen)
    commands: list[str] = []
    output = OpenAICompatibleProvider("https://api.example.test/v1", "example-model", _Credentials()).generate(
        "在桌面创建文件夹", tool_executor=lambda command: commands.append(command) or "已创建。"
    )

    assert output == "已实际完成本机操作。"
    assert commands == ["Get-Date"]
    assert captured[0]["tools"]
    assert captured[1]["messages"][-1] == {"role": "tool", "tool_call_id": "call-1", "content": "已创建。"}