build ReActAgent class

react_agent.py

@@ -0,0 +1,38 @@
+import os
+from dotenv import load_dotenv
+from langchain_core.messages import HumanMessage
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langgraph.prebuilt import create_react_agent
+from custom_tools import custom_tools
+
+class ReActAgent:
+    def __init__(self):
+        load_dotenv()
+        os.environ["GOOGLE_API_KEY"] = os.getenv("GOOGLE")
+        # Initialize your LLM
+        llm = ChatGoogleGenerativeAI(
+            model="gemini-2.5-flash",
+            temperature=0,
+            max_retries=5
+        )
+        # Optional: you can set a System prompt template here
+        sys_prompt = ""
+        # Build the ReAct agent
+        self.agent = create_react_agent(
+            model=llm,
+            tools=custom_tools,
+            prompt=""  # you can define a PromptTemplate if needed
+        )
+        print("ReActAgent initialized.")
+
+    def __call__(self, question: str) -> str:
+        # Wrap question in HumanMessage to match React expectations
+        input_msg = HumanMessage(content=question)
+        # Invoke the agent; returns a stream or single response
+        out = self.agent.invoke({"messages": [input_msg]})
+        # The last message contains the agent's reply
+        reply = out["messages"][-1].content
+        # Optionally, strip out “Final Answer:” headers
+        if "Final Answer:" in reply:
+            reply = reply.split("Final Answer:")[-1].strip()
+        return reply