初始化提交

backend/tests/ai_provider/llm/test_openai_format.py

@@ -0,0 +1,114 @@
+from __future__ import annotations
+
+import pytest
+
+from app.ai_provider.config.models import ModelConfig, ParameterMapping, ProviderConfig
+from app.ai_provider.llm.openai_format import OpenAIFormatAdapter
+from app.ai_provider.types.messages import AIMessage, HumanMessage, SystemMessage, ToolMessage
+
+
+class TestOpenAIMessageConversion:
+    @pytest.fixture
+    def adapter(self):
+        provider = ProviderConfig(
+            name="deepseek",
+            format="openai",
+            base_url_env="DEEPSEEK_BASE_URL",
+            api_key_env="DEEPSEEK_API_KEY",
+            parameter_mappings={
+                "temperature": ParameterMapping(provider_param="temperature", min=0, max=2),
+                "max_tokens": ParameterMapping(provider_param="max_tokens"),
+            },
+        )
+        return OpenAIFormatAdapter(provider_config=provider)
+
+    def test_convert_system_message(self, adapter):
+        msg = SystemMessage(content="You are a helpful assistant.")
+        result = adapter._convert_message(msg)
+        assert result["role"] == "system"
+        assert result["content"] == "You are a helpful assistant."
+
+    def test_convert_human_message(self, adapter):
+        msg = HumanMessage(content="Hello!")
+        result = adapter._convert_message(msg)
+        assert result["role"] == "user"
+
+    def test_convert_ai_message(self, adapter):
+        msg = AIMessage(
+            content="Sure!",
+            tool_calls=[{"name": "read_file", "args": {"path": "x.txt"}, "id": "call_1"}],
+        )
+        result = adapter._convert_message(msg)
+        assert result["role"] == "assistant"
+        assert "tool_calls" in result
+
+    def test_convert_tool_message(self, adapter):
+        msg = ToolMessage(content="File contents", tool_call_id="call_1")
+        result = adapter._convert_message(msg)
+        assert result["role"] == "tool"
+        assert result["tool_call_id"] == "call_1"
+
+    def test_build_request_body(self, adapter):
+        model = ModelConfig(
+            name="test", provider="deepseek", model="deepseek-v4-flash", format="openai"
+        )
+        messages = [HumanMessage(content="Hi")]
+        body = adapter.build_request(
+            model=model,
+            messages=messages,
+            params={"temperature": 0.7, "max_tokens": 4096},
+        )
+        assert body["model"] == "deepseek-v4-flash"
+        assert body["temperature"] == 0.7
+        assert body["max_tokens"] == 4096
+        assert len(body["messages"]) == 1
+
+    def test_parse_chunk(self, adapter):
+        raw = {"choices": [{"delta": {"content": "Hello"}, "index": 0}], "usage": None}
+        chunk = adapter.parse_chunk(raw)
+        assert chunk.delta_content == "Hello"
+
+    def test_parse_chunk_with_usage(self, adapter):
+        raw = {
+            "choices": [{"delta": {}, "index": 0, "finish_reason": "stop"}],
+            "usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15},
+        }
+        chunk = adapter.parse_chunk(raw)
+        assert chunk.usage is not None
+        assert chunk.usage.prompt_tokens == 10
+
+    def test_parse_tool_call_chunk(self, adapter):
+        raw = {
+            "choices": [
+                {
+                    "delta": {
+                        "tool_calls": [
+                            {
+                                "index": 0,
+                                "id": "call_1",
+                                "function": {
+                                    "name": "read_file",
+                                    "arguments": '{"path": "test.txt"}',
+                                },
+                            }
+                        ],
+                    },
+                    "index": 0,
+                }
+            ],
+        }
+        chunk = adapter.parse_chunk(raw)
+        assert len(chunk.tool_call_chunks) == 1
+        assert chunk.tool_call_chunks[0]["name"] == "read_file"
+
+    def test_bind_tools(self, adapter):
+        tools = [
+            {
+                "type": "function",
+                "function": {"name": "read_file", "parameters": {"type": "object"}},
+            }
+        ]
+        body = {}
+        adapter.bind_tools(body, tools, tool_choice="auto")
+        assert body["tools"] == tools
+        assert body["tool_choice"] == "auto"