From LLMs to Agents: Build Smart AI Systems with Tools in LangChain

In previous blogs, we learned how to: work with multiple LLM providers use PromptTemplate build a Streamlit web app Now let’s take a big step forward. 👉 Instead of just generating text, we will build AI Agents that can use tools. Tool → A function the AI can call Agent → An AI system that decides which tool to use based on the question Create a Simple Custom Tool Let’s start with a basic example. from langchain_core.tools import tool @tool def get_weather ( city : str ) -> dict : """ Return wea