Support langgraph checkpointer (#1005)

* Add checkpointer configuration to config.example.yaml

- Introduced a new section for checkpointer configuration to enable state persistence for the embedded DeerFlowClient.
- Documented supported types: memory, sqlite, and postgres, along with examples for each.
- Clarified that the LangGraph Server manages its own state persistence separately.

* refactor(checkpointer): streamline checkpointer initialization and logging

* fix(uv.lock): update revision and add new wheel URLs for brotlicffi package

* feat: add langchain-anthropic dependency and update related configurations

* Fix checkpointer lifecycle, docstring, and path resolution bugs from PR #1005 review (#4)

* Initial plan

* Address all review suggestions from PR #1005

Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>

* Fix resolve_path to always return real Path; move SQLite special-string handling to callers

Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>

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Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>
Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>

backend/src/config/app_config.py

@@ -6,6 +6,7 @@ import yaml
 from dotenv import load_dotenv
 from pydantic import BaseModel, ConfigDict, Field
 
+from src.config.checkpointer_config import CheckpointerConfig, load_checkpointer_config_from_dict
 from src.config.extensions_config import ExtensionsConfig
 from src.config.memory_config import load_memory_config_from_dict
 from src.config.model_config import ModelConfig
@@ -29,6 +30,7 @@ class AppConfig(BaseModel):
     skills: SkillsConfig = Field(default_factory=SkillsConfig, description="Skills configuration")
     extensions: ExtensionsConfig = Field(default_factory=ExtensionsConfig, description="Extensions configuration (MCP servers and skills state)")
     model_config = ConfigDict(extra="allow", frozen=False)
+    checkpointer: CheckpointerConfig | None = Field(default=None, description="Checkpointer configuration")
 
     @classmethod
     def resolve_config_path(cls, config_path: str | None = None) -> Path:
@@ -92,6 +94,10 @@ class AppConfig(BaseModel):
         if "subagents" in config_data:
             load_subagents_config_from_dict(config_data["subagents"])
 
+        # Load checkpointer config if present
+        if "checkpointer" in config_data:
+            load_checkpointer_config_from_dict(config_data["checkpointer"])
+
         # Load extensions config separately (it's in a different file)
         extensions_config = ExtensionsConfig.from_file()
         config_data["extensions"] = extensions_config.model_dump()