A practical tutorial with full code examples for building and running multi-tool agents
LLMs are remarkable — they can memorize vast amounts of information, answer general knowledge questions, write code, generate stories, and even fix your grammar. However, they are not without limitations. They hallucinate, have a knowledge cut-off that may range from a few months to several years, and are confined to generating text, unable to interact with the real world. This restricts their utility for tasks requiring real-time data, source citations, or functionalities beyond text generation. This is the main issue that Agents and Tools are attempting to solve: they bridge this gap by augmenting LLMs with additional capabilities. These improvements allow LLMs to access up-to-date information, interact with APIs, Search, and even influence the physical world, like adjusting a smart home’s temperature.
In this tutorial, we are going to build a simple LLM agent that is equipped with four tools that it can use to answer a user’s question. This Agent will have the following specifications:
- Can answer general Knowledge questions with up-to-date verifiable information.
- Can use four types of tools: DuckDuckGo…
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#Building #Autonomous #MultiTool #Agents #Gemini #LangGraph #Youness #Mansar #Jan
