chore: initial commit (sources + docs, ignore build artifacts and secrets)

mulit_agent/tests/test_openai_compatible_provider.py

@@ -0,0 +1,107 @@
+import json
+
+from mulit_agent_app.infrastructure.openai_compatible_provider import OpenAICompatibleProvider
+
+
+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_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_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。"}