remove unnecessary codes for simplicity

Author: ks6088ts

docs/index.md

@@ -28,7 +28,6 @@ uv run python -m template_langgraph.tasks.run_kabuto_helpdesk_agent "KABUTOの
 # BasicWorkflowAgent
 uv run python -m template_langgraph.tasks.draw_basic_workflow_agent_mermaid_png "data/basic_workflow_agent.png"
 uv run python -m template_langgraph.tasks.run_basic_workflow_agent
-# 私の名前はフグ田 サザエ。東京都世田谷区桜新町あさひが丘3丁目に住んでいる 24 歳の主婦です。夫のノリスケと子供のタラちゃんがいます
 # KABUTOの起動時に、画面全体が紫色に点滅し、システムがフリーズします。KABUTO のマニュアルから、関連する情報を取得したり過去のシステムのトラブルシュート事例が蓄積されたデータベースから、関連する情報を取得して質問に答えてください
 # 天狗のいたずら という現象について KABUTO のマニュアルから、関連する情報を取得したり過去のシステムのトラブルシュート事例が蓄積されたデータベースから、関連する情報を取得して質問に答えてください
 ```

template_langgraph/agents/basic_workflow_agent/agent.py

@@ -1,9 +1,9 @@
 import json
 
-from langchain_core.messages import AIMessage, ToolMessage
-from langgraph.graph import END, START, StateGraph
+from langchain_core.messages import ToolMessage
+from langgraph.graph import END, StateGraph
 
-from template_langgraph.agents.basic_workflow_agent.models import AgentInput, AgentOutput, AgentState, Profile
+from template_langgraph.agents.basic_workflow_agent.models import AgentState
 from template_langgraph.llms.azure_openais import AzureOpenAiWrapper
 from template_langgraph.loggers import get_logger
 from template_langgraph.tools.elasticsearch_tool import search_elasticsearch
@@ -47,8 +47,6 @@ def create_graph(self):
 
         # Create nodes
         workflow.add_node("initialize", self.initialize)
-        workflow.add_node("do_something", self.do_something)
-        workflow.add_node("extract_profile", self.extract_profile)
         workflow.add_node("chat_with_tools", self.chat_with_tools)
         workflow.add_node(
             "tools",
@@ -62,11 +60,8 @@ def create_graph(self):
         workflow.add_node("finalize", self.finalize)
 
         # Create edges
-        # workflow.add_edge(START, "initialize")
-        workflow.add_edge(START, "chat_with_tools")
-        workflow.add_edge("initialize", "do_something")
-        workflow.add_edge("do_something", "extract_profile")
-        workflow.add_edge("extract_profile", "chat_with_tools")
+        workflow.set_entry_point("initialize")
+        workflow.add_edge("initialize", "chat_with_tools")
         workflow.add_conditional_edges(
             "chat_with_tools",
             self.route_tools,
@@ -89,33 +84,6 @@ def initialize(self, state: AgentState) -> AgentState:
         # Here you can add any initialization logic if needed
         return state
 
-    def do_something(self, state: AgentState) -> AgentState:
-        """Perform some action with the given state."""
-        logger.info(f"Doing something with state: {state}")
-
-        # Here you can add the logic for the action
-        response: AIMessage = self.llm.invoke(
-            input=state["messages"],
-        )
-        logger.info(f"Response after doing something: {response}")
-        state["messages"].append(
-            {
-                "role": "assistant",
-                "content": response.content,
-            }
-        )
-
-        return state
-
-    def extract_profile(self, state: AgentState) -> AgentState:
-        """Extract profile information from the state."""
-        logger.info(f"Extracting profile from state: {state}")
-        profile = self.llm.with_structured_output(Profile).invoke(
-            input=state["messages"],
-        )
-        state["profile"] = profile
-        return state
-
     def chat_with_tools(self, state: AgentState) -> AgentState:
         """Chat with tools using the state."""
         logger.info(f"Chatting with tools using state: {state}")
@@ -155,25 +123,6 @@ def finalize(self, state: AgentState) -> AgentState:
         # Here you can add any finalization logic if needed
         return state
 
-    def run_agent(self, input: AgentInput) -> AgentOutput:
-        """Run the agent with the given input."""
-        logger.info(f"Running BasicWorkflowAgent with question: {input.model_dump_json(indent=2)}")
-        app = self.create_graph()
-        initial_state: AgentState = {
-            "messages": [
-                {
-                    "role": "user",
-                    "content": input.request,
-                }
-            ],
-        }
-        final_state = app.invoke(initial_state)
-        logger.info(f"Final state after running agent: {final_state}")
-        return AgentOutput(
-            response=final_state["messages"][-1].content,
-            profile=final_state["profile"],
-        )
-
     def draw_mermaid_png(self) -> bytes:
         """Draw the graph in Mermaid format."""
         return self.create_graph().get_graph().draw_mermaid_png()

template_langgraph/agents/basic_workflow_agent/models.py

@@ -11,22 +11,13 @@
 from pydantic import BaseModel, Field
 
 
-class Profile(BaseModel):
-    first_name: str = Field(..., description="名")
-    last_name: str = Field(..., description="姓")
-    age: int | None = Field(None, description="年齢")
-    address: str | None = Field(None, description="住所")
-
-
 class AgentInput(BaseModel):
     request: str = Field(..., description="ユーザーからのリクエスト")
 
 
 class AgentOutput(BaseModel):
     response: str = Field(..., description="エージェントの応答")
-    profile: Profile | None = Field(None, description="抽出されたプロファイル情報")
 
 
 class AgentState(TypedDict):
     messages: Annotated[Sequence[BaseMessage], add_messages]
-    profile: Profile | None = Field(None, description="抽出されたプロファイル情報")