feat: M1 — 立项→写章草稿(SSE)→自动保存；连一家 provider

- 薄自建 LLM 网关：OpenAI 兼容适配器(DeepSeek) + instructor 结构化输出 + usage_ledger 记账 + 档位路由
- 记忆服务 assemble：确定性选择(显式+主角+近况) + 渲染卡 + 缓存断点(中性文本)
- LangGraph 写章节点 + Postgres checkpointer + SSE 归一(token/done/error)
- API：立项 + 写章 draft(SSE) + PUT 自动保存 + 提供商凭据(Fernet 加密/测试连接)
- 前端：AppShell + 作品库 + 5 步立项向导 + 写作工作台(流式打字机+自动保存) + 设置页
- M1 E2E：真实 DB + mock 网关零 token 走通闭环

packages/llm_gateway/tests/test_openai_adapter.py

@@ -0,0 +1,102 @@
+"""OpenAI 兼容适配器单测：用替身 client 验证消息翻译 + usage 映射（不联网）。"""
+
+from __future__ import annotations
+
+import uuid
+from collections.abc import AsyncIterator
+from types import SimpleNamespace
+from typing import Any, cast
+
+from openai import AsyncOpenAI
+from ww_llm_gateway.adapters.openai_compat import OpenAICompatAdapter, _messages
+from ww_llm_gateway.types import Block, LlmRequest, Scope
+
+
+def _req(**kw: Any) -> LlmRequest:
+    kw.setdefault("tier", "writer")
+    return LlmRequest(scope=Scope(user_id=uuid.UUID(int=1)), **kw)
+
+
+class _FakeStream:
+    def __init__(self, chunks: list[Any]) -> None:
+        self._chunks = chunks
+
+    async def __aiter__(self) -> AsyncIterator[Any]:
+        for c in self._chunks:
+            yield c
+
+
+class _FakeCompletions:
+    def __init__(self, response: Any, stream_chunks: list[Any]) -> None:
+        self._response = response
+        self._stream_chunks = stream_chunks
+        self.last_messages: Any = None
+
+    async def create(self, **kw: Any) -> Any:
+        self.last_messages = kw.get("messages")
+        if kw.get("stream"):
+            return _FakeStream(self._stream_chunks)
+        return self._response
+
+
+class _FakeClient:
+    def __init__(self, completions: _FakeCompletions) -> None:
+        self.chat = SimpleNamespace(completions=completions)
+
+
+def test_messages_put_system_first_then_user() -> None:
+    req = _req(input="正文", system=[Block(text="世界观硬规则", cache=True)])
+    msgs = _messages(req)
+    assert msgs[0]["role"] == "system"
+    assert msgs[0]["content"] == "世界观硬规则"
+    assert msgs[1]["role"] == "user"
+    assert msgs[1]["content"] == "正文"
+
+
+async def test_complete_maps_text_and_usage() -> None:
+    response = SimpleNamespace(
+        choices=[SimpleNamespace(message=SimpleNamespace(content="草稿"))],
+        usage=SimpleNamespace(
+            prompt_tokens=120,
+            completion_tokens=80,
+            prompt_tokens_details=SimpleNamespace(cached_tokens=30),
+        ),
+    )
+    completions = _FakeCompletions(response, [])
+    adapter = OpenAICompatAdapter("deepseek", cast(AsyncOpenAI, _FakeClient(completions)))
+
+    result = await adapter.complete(_req(input="x"), "deepseek-chat")
+
+    assert result.text == "草稿"
+    assert result.usage.input_tokens == 120
+    assert result.usage.output_tokens == 80
+    assert result.usage.cache_read_tokens == 30
+
+
+async def test_stream_yields_text_then_final_usage() -> None:
+    chunks = [
+        SimpleNamespace(choices=[SimpleNamespace(delta=SimpleNamespace(content="他"))], usage=None),
+        SimpleNamespace(choices=[SimpleNamespace(delta=SimpleNamespace(content="说"))], usage=None),
+        SimpleNamespace(
+            choices=[],
+            usage=SimpleNamespace(
+                prompt_tokens=10,
+                completion_tokens=2,
+                prompt_tokens_details=None,
+            ),
+        ),
+    ]
+    completions = _FakeCompletions(None, chunks)
+    adapter = OpenAICompatAdapter("deepseek", cast(AsyncOpenAI, _FakeClient(completions)))
+
+    texts: list[str] = []
+    usage_seen = None
+    async for ch in adapter.stream(_req(input="x"), "deepseek-chat"):
+        if ch.text:
+            texts.append(ch.text)
+        if ch.usage is not None:
+            usage_seen = ch.usage
+
+    assert "".join(texts) == "他说"
+    assert usage_seen is not None
+    assert usage_seen.output_tokens == 2