fix(docker): 在 Dockerfile 中添加 libpq5 并更新 LangGraph 的部分特性以支持 PostgreSQL

同时更新默认模型为 Pro 分类

docker/api.Dockerfile

@@ -29,6 +29,7 @@ RUN set -ex \
     && apt-get install -y --no-install-recommends --fix-missing \
         curl \
         ffmpeg \
+        libpq5 \
         libsm6 \
         libxext6 \
     # (D) 清理垃圾，减小体积

docs/latest/advanced/configuration.md

@@ -37,7 +37,7 @@ class Config(BaseModel):
     enable_content_guard: bool = Field(default=False, description="是否启用内容审查")
 
     # 模型配置
-    default_model: str = Field(default="siliconflow/deepseek-ai/DeepSeek-V3.2")
+    default_model: str = Field(default="default="siliconflow/Pro/deepseek-ai/DeepSeek-V3.2")
     embed_model: str = Field(default="siliconflow/BAAI/bge-m3")
 
     # 运行时状态 (不持久化)

docs/latest/intro/model-config.md

@@ -32,7 +32,7 @@
 系统的默认对话模型可以在设置页面配置，也可以通过配置项 `default_model` 指定，格式统一为 `模型提供商/模型名称`，例如：
 
 ```yaml
-default_model: siliconflow/deepseek-ai/DeepSeek-V3.2
+default_model: default="siliconflow/Pro/deepseek-ai/DeepSeek-V3.2
 ```
 
 ## 自定义模型供应商

src/agents/common/base.py

@@ -1,9 +1,11 @@
 from __future__ import annotations
 
+import asyncio
 import importlib.util
 import os
 import tomllib as tomli
 from abc import abstractmethod
+from inspect import isawaitable
 from pathlib import Path
 
 from langgraph.checkpoint.memory import InMemorySaver
@@ -28,6 +30,7 @@ class BaseAgent:
     def __init__(self, **kwargs):
         self.graph = None  # will be covered by get_graph
         self.checkpointer = None
+        self._checkpointer_cm = None
         self._async_conn = None
         self.workdir = Path(sys_config.save_dir) / "agents" / self.module_name
         self.workdir.mkdir(parents=True, exist_ok=True)
@@ -156,6 +159,15 @@ class BaseAgent:
     def reload_graph(self):
         """重置 graph 缓存，强制下次调用 get_graph 时重新构建"""
         self.graph = None
+        self.checkpointer = None
+        if self._checkpointer_cm is not None:
+            try:
+                loop = asyncio.get_running_loop()
+            except RuntimeError:
+                loop = None
+
+            if loop is not None:
+                loop.create_task(self._close_checkpointer_context())
         logger.info(f"{self.name} graph 缓存已清空，将在下次调用时重新构建")
 
     @abstractmethod
@@ -207,10 +219,14 @@ class BaseAgent:
             else:
                 saver = AsyncPostgresSaver(conn_str)  # type: ignore[call-arg]
 
+            if hasattr(saver, "__aenter__") and hasattr(saver, "__aexit__"):
+                self._checkpointer_cm = saver
+                saver = await saver.__aenter__()
+
             setup_fn = getattr(saver, "setup", None)
             if callable(setup_fn):
                 result = setup_fn()
-                if hasattr(result, "__await__"):
+                if isawaitable(result):
                     await result
             logger.info(f"{self.name} 使用 postgres checkpointer")
             return saver
@@ -218,6 +234,17 @@ class BaseAgent:
             logger.warning(f"初始化 postgres checkpointer 失败，回退 sqlite: {e}")
             return None
 
+    async def _close_checkpointer_context(self):
+        if self._checkpointer_cm is None:
+            return
+
+        cm = self._checkpointer_cm
+        self._checkpointer_cm = None
+        try:
+            await cm.__aexit__(None, None, None)
+        except Exception as e:
+            logger.warning(f"关闭 postgres checkpointer 失败: {e}")
+
     async def get_async_conn(self) -> aiosqlite.Connection:
         """获取异步数据库连接"""
         if self._async_conn is not None:

src/agents/deep_agent/context.py

@@ -101,7 +101,7 @@ class DeepContext(BaseContext):
     )
 
     subagents_model: Annotated[str, {"__template_metadata__": {"kind": "llm"}}] = field(
-        default="siliconflow/deepseek-ai/DeepSeek-V3.2",
+        default="siliconflow/Pro/deepseek-ai/DeepSeek-V3.2",
         metadata={
             "name": "Sub-agent Model",
             "description": "The model used by sub-agents (e.g., critique-agent, research-agent).",

src/config/app.py

@@ -47,23 +47,23 @@ class Config(BaseModel):
     # 模型配置
     # ============================================================
     default_model: str = Field(
-        default="siliconflow/deepseek-ai/DeepSeek-V3.2",
+        default="siliconflow/Pro/deepseek-ai/DeepSeek-V3.2",
         description="默认对话模型",
     )
     fast_model: str = Field(
-        default="siliconflow/THUDM/GLM-4-9B-0414",
+        default="siliconflow/Qwen/Qwen3.5-9B",
         description="快速响应模型",
     )
     embed_model: str = Field(
-        default="siliconflow/BAAI/bge-m3",
+        default="siliconflow/Pro/BAAI/bge-m3",
         description="默认 Embedding 模型",
     )
     reranker: str = Field(
-        default="siliconflow/BAAI/bge-reranker-v2-m3",
+        default="siliconflow/Pro/BAAI/bge-reranker-v2-m3",
         description="默认 Re-Ranker 模型",
     )
     content_guard_llm_model: str = Field(
-        default="siliconflow/Qwen/Qwen3-235B-A22B-Instruct-2507",
+        default="siliconflow/Qwen/Qwen3.5-9B",
         description="内容审查LLM模型",
     )