use prompt store

lang_agent/graphs/dual_path.py

@@ -1,5 +1,5 @@
 from dataclasses import dataclass, field
-from typing import Type, TypedDict, Literal, Dict, List
+from typing import Type, TypedDict, Literal, Dict, List, Optional
 import tyro
 from pydantic import BaseModel, Field
 from loguru import logger
@@ -9,6 +9,7 @@ from langchain.chat_models import init_chat_model
 from lang_agent.config import LLMKeyConfig
 from lang_agent.base import GraphBase
 from lang_agent.components.tool_manager import ToolManager, ToolManagerConfig
+from lang_agent.components.prompt_store import build_prompt_store
 from lang_agent.graphs.graph_states import State
 
 from langchain.agents import create_agent
@@ -50,6 +51,12 @@ TOOL_SYS_PROMPT = """根据用户的心情使用self_led_control改变灯的颜
 class DualConfig(LLMKeyConfig):
     _target: Type = field(default_factory=lambda:Dual)
 
+    pipeline_id: Optional[str] = None
+    """If set, load prompts from database (with hardcoded fallback)"""
+
+    prompt_set_id: Optional[str] = None
+    """If set, load from this specific prompt set instead of the active one"""
+
     tool_manager_config: ToolManagerConfig = field(default_factory=ToolManagerConfig)
 
 from langchain.tools import tool
@@ -96,14 +103,23 @@ class Dual(GraphBase):
         self.tool_agent = create_agent(self.tool_llm, self.tool_manager.get_langchain_tools())
         # self.tool_agent = create_agent(self.tool_llm, [turn_lights])
 
+        self.prompt_store = build_prompt_store(
+            pipeline_id=self.config.pipeline_id,
+            prompt_set_id=self.config.prompt_set_id,
+            hardcoded={
+                "sys_prompt": SYS_PROMPT,
+                "tool_sys_prompt": TOOL_SYS_PROMPT,
+            },
+        )
+
         self.streamable_tags = [["dual_chat_llm"]]
     
 
     def _chat_call(self, state:State):
-        return self._agent_call_template(SYS_PROMPT, self.chat_agent, state)
+        return self._agent_call_template(self.prompt_store.get("sys_prompt"), self.chat_agent, state)
     
     def _tool_call(self, state:State):
-        self._agent_call_template(TOOL_SYS_PROMPT, self.tool_agent, state)
+        self._agent_call_template(self.prompt_store.get("tool_sys_prompt"), self.tool_agent, state)
         return {}
 
     def _join(self, state:State):