Build a Multi-Tool AI Agent Using LangChain and IBM Granite
Agentic AI is very popular. Learn to build a responsive AI agent using LangChain’s tool calling with IBM's Granite model in 30 minutes. This beginner-friendly hands-on project guides you through combining key tools like live weather data fetchers, YouTube content handlers, and search utilities. Learn to design a multi-tool workflow that delivers dynamic, real-time outputs using LangChain and watsonx.ai. Ideal for developers seeking applied experience in orchestrating intelligent agents with LLMs and external APIs.

Language
- English
Topic
- Artificial Intelligence
Skills You Will Learn
- LangChain, LLM, Granite, Generative AI, Tool Calling
Offered By
- IBMSkillsNetwork
Estimated Effort
- 30 minutes
Platform
- SkillsNetwork
Last Update
- July 3, 2025
You’ll start by diving into the world of LangChain, a framework designed to empower large language models with tool calling abilities. Paired with the enterprise-grade intelligence of IBM’s Granite models through watsonx.ai, you won’t just be working with static LLMs—you’ll be training your agent to interact with the world.
- Check the weather for any city in real-time,
- Search YouTube for relevant videos based on user prompts,
- And even perform an iconic search, pulling context-rich information about public figures, places, and events.
A Look at the Project Ahead
- Understand the concept of tool calling (function calling).
- Explain the purpose of the LangChain framework
- Implement a LangChain agent using Granite-3B-Instruct model.
- Integrate and configure prebuilt tools in LangChain
What You'll Need

Language
- English
Topic
- Artificial Intelligence
Skills You Will Learn
- LangChain, LLM, Granite, Generative AI, Tool Calling
Offered By
- IBMSkillsNetwork
Estimated Effort
- 30 minutes
Platform
- SkillsNetwork
Last Update
- July 3, 2025
Instructors
Jigisha Barbhaya
Data Scientist
I am a Data scientist at IBM and Lead instructor at Skills network. I love to learn and educate. I have completed my MSc(Computer Application) specialisation in Data science from Symbiosis University.
Read moreContributors
Joseph Santarcangelo
Senior Data Scientist at IBM
Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.
Read moreAnna Gutowska
AI Engineer & Developer Advocate, IBM
Anna is an AI engineer and technical content writer with a passion for AI, data science, and education. With a background in Computer Science and Cognitive Science, she is particularly interested in the intriguing parallels between AI agents and human cognition and decision-making. Anna’s work is dedicated to empowering developers to effectively leverage advanced AI technologies in a user-friendly way for developers of all experience levels. Driven by her curiosity and commitment to innovation, she has concentrated much of her efforts on developing AI agents. Anna believes that these agentic systems can be utilized to free human resources for more complex and impactful tasks, rather than routine activities. Passionate about both sharing her expertise and learning from others, she holds the conviction that the best educators are those who continually seek knowledge.
Read moreKaran Goswami
Data Scientist
I am a dedicated Data Scientist and an AI enthusiast, currently working at IBM's Skills Builder Network. Learning how some simple mathematical operations could be used to make predictions and discover patterns sparked my curiosity, leading me to explore the exciting world of AI. Over the years, I’ve gained hands-on experience in building scalable AI solutions, fine-tuning models, and extracting meaningful insights from complex datasets. I'm driven by a desire to apply these skills to solve real-world problems and make a meaningful impact through AI.
Read more