feat: add embedding types, port and openai-compat transport

tests/unit/test_embedding.py

@@ -0,0 +1,157 @@
+"""Embedding 类型/端口/transport 测试(M2 设计 §7;T8)。
+
+蓝本审计: GovDoc retrieval/embedding.py(分批/index 排序/维度校验)与
+VT adapters/embedding.py(归一化);库裁决见设计 §7.3 表。
+"""
+
+import dataclasses
+import json
+
+import httpx
+import pytest
+
+from polygateway.errors import (
+    RequestRejectedError,
+    ResultInvalidError,
+    SourceDeadError,
+    TransientError,
+)
+from polygateway.ports import EmbeddingTransport
+from polygateway.transports.openai_compat import OpenAICompatTransport
+from polygateway.types import EmbeddingResponse, EmbeddingTransportResult, SourceConfig
+
+
+def _src(**overrides):
+    base = {
+        "name": "e1",
+        "provider": "openai",
+        "base_url": "https://gw.example/v1",
+        "api_key": "sk",
+        "model": "embed-1",
+        "timeout_s": 10.0,
+        "est_tokens": 7,
+    }
+    base.update(overrides)
+    return SourceConfig(**base)
+
+
+class TestTypes:
+    def test_embedding_response_frozen_with_defaults(self):
+        resp = EmbeddingResponse(
+            vectors=[[0.1, 0.2]],
+            dim=2,
+            model="m",
+            provider="p",
+            prompt_tokens=3,
+            usage_source="measured",
+            latency_ms=10,
+            call_id="c",
+            source_name="e1",
+        )
+        assert resp.cost is None
+        with pytest.raises(dataclasses.FrozenInstanceError):
+            resp.dim = 3
+
+    def test_transport_result_frozen(self):
+        r = EmbeddingTransportResult(
+            vectors=[[1.0]], dim=1, prompt_tokens=1, usage_source="measured", raw={}
+        )
+        with pytest.raises(dataclasses.FrozenInstanceError):
+            r.dim = 2
+
+
+class _DummyEmbedTransport:
+    async def embed(self, *, texts, source, call_id):
+        raise NotImplementedError
+
+
+def test_embedding_transport_protocol_runtime_checkable():
+    assert isinstance(_DummyEmbedTransport(), EmbeddingTransport)
+    assert isinstance(OpenAICompatTransport(), EmbeddingTransport)
+
+
+def _transport_with(handler):
+    return OpenAICompatTransport(
+        client_factory=lambda source: httpx.AsyncClient(transport=httpx.MockTransport(handler))
+    )
+
+
+def _ok_body(vectors, *, usage=None, shuffle=False):
+    data = [{"index": i, "embedding": v} for i, v in enumerate(vectors)]
+    if shuffle:
+        data = list(reversed(data))
+    body = {"data": data}
+    if usage is not None:
+        body["usage"] = usage
+    return body
+
+
+class TestEmbedTransport:
+    async def test_sorts_by_index_and_measures_usage(self):
+        def handler(request):
+            assert request.url.path.endswith("/embeddings")
+            payload = json.loads(request.content)
+            assert payload == {"model": "embed-1", "input": ["a", "b"]}
+            return httpx.Response(
+                200,
+                json=_ok_body(
+                    [[1.0, 0.0], [0.0, 1.0]], usage={"prompt_tokens": 5}, shuffle=True
+                ),
+            )
+
+        result = await _transport_with(handler).embed(
+            texts=["a", "b"], source=_src(), call_id="c"
+        )
+        assert result.vectors == [[1.0, 0.0], [0.0, 1.0]]  # 乱序响应按 index 重排
+        assert result.dim == 2
+        assert result.prompt_tokens == 5 and result.usage_source == "measured"
+
+    async def test_missing_usage_falls_back_estimated(self):
+        def handler(request):
+            return httpx.Response(200, json=_ok_body([[1.0]]))
+
+        result = await _transport_with(handler).embed(texts=["a"], source=_src(), call_id="c")
+        assert result.prompt_tokens == 7 and result.usage_source == "estimated"  # est_tokens
+
+    @pytest.mark.parametrize(
+        ("status", "exc_type"),
+        [(401, SourceDeadError), (400, RequestRejectedError), (500, TransientError)],
+    )
+    async def test_http_errors_translate(self, status, exc_type):
+        def handler(request):
+            return httpx.Response(status, text="boom")
+
+        with pytest.raises(exc_type):
+            await _transport_with(handler).embed(texts=["a"], source=_src(), call_id="c")
+
+    async def test_network_error_is_transient(self):
+        def handler(request):
+            raise httpx.ConnectError("refused")
+
+        with pytest.raises(TransientError):
+            await _transport_with(handler).embed(texts=["a"], source=_src(), call_id="c")
+
+    @pytest.mark.parametrize(
+        "body",
+        [
+            {"data": []},  # 空 data
+            {"data": [{"index": 0, "embedding": [1.0]}]},  # 数量与输入不符(输入 2 条)
+            {
+                "data": [
+                    {"index": 0, "embedding": [1.0, 2.0]},
+                    {"index": 1, "embedding": [1.0]},  # 维度不一致
+                ]
+            },
+            {"nope": True},  # 缺 data
+        ],
+    )
+    async def test_malformed_payload_is_result_invalid(self, body):
+        def handler(request):
+            return httpx.Response(200, json=body)
+
+        with pytest.raises(ResultInvalidError):
+            await _transport_with(handler).embed(texts=["a", "b"], source=_src(), call_id="c")
+
+    async def test_empty_texts_rejected(self):
+        with pytest.raises(ValueError):
+            await _transport_with(lambda r: None).embed(texts=[], source=_src(), call_id="c")