Build Your First AI Agent

Step-by-step tutorial to create a working AI agent from scratch

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Building the Agent

Now for the fun part - let's build your first AI agent! We'll create a simple but powerful agent that can check weather and do calculations.

Follow along step-by-step, or copy the code to try it yourself. By the end of this section, you'll have a working agent!

Click tabs to see each step of building your agent

📝 What's happening:

First, install LangChain and OpenAI SDK. Store your API key securely in a .env file.

# Install required packages
pip install langchain openai python-dotenv

# Create .env file
OPENAI_API_KEY=your_api_key_here

Install Dependencies

LangChain provides the agent framework, OpenAI provides the LLM

Define Tools

Each tool is a Python function with a docstring describing what it does

Initialize LLM

Choose your model - GPT-4 for best reasoning, GPT-3.5 for speed

Create Agent

ReAct agent combines reasoning (think) and action (tool use)

Run & Test

Start with simple queries, then try complex multi-step tasks

✅ Simple Tool

@tool
def search(query: str):
    """Search the web"""
    return api_call(query)

✅ Tool with Validation

@tool
def calculator(expr: str):
    """Calculate math"""
    if not safe(expr):
        return "Invalid"
    return eval(expr)

•Start with 2-3 simple tools before adding complexity
•Write clear tool descriptions - the LLM uses these to decide when to call tools
•Test each tool individually before combining them in an agent
•Use temperature=0 for consistent, predictable agent behavior
•Add logging to see the agent's reasoning process