feat(backends): wire LangGraph backend behind AGENT_BACKEND switch (assignment 2)

- src/backends/langgraph.py: LangGraphBackend implements ChatBackend;
  complete() runs one graph turn per session (thread_id=sessionId) and
  returns state-prefixed content; stream() emits the full state prefix
  before body fragments (full-answer slicing, not yet real incremental
  output - assignment 8)
- src/core/config.py: AGENT_BACKEND=fastgpt|langgraph, langgraph mode
  no longer requires FastGPT credentials at startup
- src/core/fastgpt_client.py: lifespan builds the backend by switch
- test/backends/test_langgraph_backend.py: adapter acceptance tests

Verified:
- pytest: 48 passed
- AGENT_BACKEND=langgraph uvicorn: POST /chat -> 1002;
  browser_addon -> browser_addon.1002; SSE = stage_code, text_delta,
  single done

Known limit: stream slices a complete answer; no formUpdate deltas yet
(assignment 6).

src/backends/langgraph.py

@@ -0,0 +1,65 @@
+"""LangGraph implementation of the backend-neutral chat contract（作业 2）。
+
+实现 ``ChatBackend`` Protocol，把图执行结果翻译为公共契约：
+- ``complete()`` 返回 ``ChatResult``，``content`` 保留
+  ``<state>XXXX</state>`` 前缀（API 层负责解析）；
+- ``stream()`` 产生 ``TextDelta`` / ``FormUpdate``；初期允许把固定完整答案
+  切成若干片段，真实增量输出在作业 8 接入。
+
+通过 ``build_graph()`` 编译的图构造；会话用
+``configurable.thread_id = chat_input.session_id`` 绑定。
+
+对应测试：test/backends/test_langgraph_backend.py
+"""
+
+from collections.abc import AsyncIterator
+
+from ..agent.graph import build_graph
+from .chat import ChatInput, ChatResult, ChatStreamEvent, ChatBackend, TextDelta
+
+
+class LangGraphBackend(ChatBackend):
+    """Adapt a compiled LangGraph to the neutral chat contract."""
+
+    def __init__(self, graph=None):
+        """参数:
+        graph: 编译后的图；缺省调用 ``build_graph()``（内存 checkpoint）。
+        """
+        self._graph = graph if graph is not None else build_graph()
+
+    async def complete(self, chat_input: ChatInput) -> ChatResult:
+        """非流式：执行一轮图并翻译结果。
+
+        TODO(作业 2): 实现该方法。要求：
+        - 用 ``ainvoke`` 执行图，``thread_id`` 取
+          ``chat_input.session_id``；
+        - 初始 state 至少包含 ``session_id``、``input_text``；
+        - 返回 ``ChatResult(content=<响应文本（含 state 前缀）>,
+          status_code=None, form_update={})``；
+        - 本阶段不处理 ``need_form_update`` 的真实表单差量
+          （作业 6 起实现）。
+        """
+        result = await self._graph.ainvoke(
+            {"session_id": chat_input.session_id, "input_text": chat_input.text},
+            config={"configurable": {"thread_id": chat_input.session_id}},
+        )
+        return ChatResult(
+          content = result["response_text"],
+          status_code = None,
+          form_update = {}
+        )
+
+    async def stream(self, chat_input: ChatInput) -> AsyncIterator[ChatStreamEvent]:
+        """流式：产生中立流事件。
+
+        TODO(作业 2): 实现该方法。最低要求：
+        - 先产出含完整 ``<state>...</state>`` 前缀的 ``TextDelta``，
+          再产出正文片段（保证 API 层的 stage 先于正文约束）；
+        - 本阶段允许“完整答案切片段”，提交说明须标注
+          “尚未接入模型增量输出”（作业 8 改为真实增量）。
+        """
+        result = await self.complete(chat_input)
+        prefix, _, body = result.content.partition("</state>")
+        yield TextDelta(prefix + "</state>")
+        if body:
+            yield TextDelta(body)

src/core/config.py

@@ -15,9 +15,21 @@ class Config:
     FASTGPT_BASE_URL = os.getenv("ANALYSIS_SERVICE_URL")
     FASTGPT_APP_ID = os.getenv("APP_ID")
     
+    # Chat backend switch（作业 2）
+    # "fastgpt" 保持现有行为；"langgraph" 使用内存图 fake 回复。
+    AGENT_BACKEND = os.getenv("AGENT_BACKEND", "fastgpt")
+    
     @classmethod
     def validate(cls):
         """Validate required configuration."""
+        # TODO(作业 2): 语音管线仍依赖 FastGPT。当前仅按文本后端开关校验；
+        # 接入语音开关后，需要单独校验语音路径所需配置。
+        if cls.AGENT_BACKEND not in ("fastgpt", "langgraph"):
+            raise ValueError(
+                f"AGENT_BACKEND must be 'fastgpt' or 'langgraph', got {cls.AGENT_BACKEND!r}"
+            )
+        if cls.AGENT_BACKEND != "fastgpt":
+            return
         required = [
             ("FASTGPT_BASE_URL (ANALYSIS_SERVICE_URL)", cls.FASTGPT_BASE_URL),
             ("FASTGPT_API_KEY (ANALYSIS_AUTH_TOKEN)", cls.FASTGPT_API_KEY),

src/core/fastgpt_client.py

@@ -2,8 +2,10 @@
 from contextlib import asynccontextmanager
 from fastapi import FastAPI
 from fastgpt_client import AsyncChatClient
+from ..agent.graph import build_graph
 from ..backends.chat import ChatBackend
 from ..backends.fastgpt import FastGPTBackend
+from ..backends.langgraph import LangGraphBackend
 from .config import Config
 
 
@@ -13,20 +15,25 @@ _chat_backend: ChatBackend | None = None
 
 @asynccontextmanager
 async def lifespan(app: FastAPI):
-    """Manage FastGPT client lifecycle."""
+    """Manage chat backend resource lifecycle."""
     global _chat_backend, _fastgpt_client
     Config.validate()
 
-    _fastgpt_client = AsyncChatClient(
-        api_key=Config.FASTGPT_API_KEY,
-        base_url=Config.FASTGPT_BASE_URL,
-        timeout=60.0,
-        max_retries=3,
-        retry_delay=1.0,
-        enable_logging=Config.DEBUG,
-    )
-    await _fastgpt_client.__aenter__()
-    _chat_backend = FastGPTBackend(_fastgpt_client)
+    if Config.AGENT_BACKEND == "langgraph":
+        # 作业 2：LangGraph fake 模式不要求 FastGPT 密钥。
+        # TODO(作业 2): 若语音仍启用，需在此单独初始化并校验 FastGPT 配置。
+        _chat_backend = LangGraphBackend(build_graph())
+    else:
+        _fastgpt_client = AsyncChatClient(
+            api_key=Config.FASTGPT_API_KEY,
+            base_url=Config.FASTGPT_BASE_URL,
+            timeout=60.0,
+            max_retries=3,
+            retry_delay=1.0,
+            enable_logging=Config.DEBUG,
+        )
+        await _fastgpt_client.__aenter__()
+        _chat_backend = FastGPTBackend(_fastgpt_client)
 
     try:
         yield