Building Your First Agent

Let's build a production-ready agent step-by-step. Follow along with this interactive walkthrough to understand each component.

Interactive: Step-by-Step Agent Builder

Step 1 of 6

Install & Import

Install packages and import necessary components

pip install langchain langchain-openai

from langchain_openai import ChatOpenAI
from langchain.agents import Tool, initialize_agent, AgentType
from langchain.memory import ConversationBufferMemory

🔧 Common Patterns

Error Handling

agent = initialize_agent(..., handle_parsing_errors=True, max_iterations=5)

Catch errors, set iteration limits to prevent loops

Streaming Responses

agent.stream({"input": query})

Stream token-by-token for better UX

Callbacks

agent.run(query, callbacks=[logging_handler])

Track execution, log steps, debug issues

Multiple Tools

tools = [calculator, search, db_query, api_call]

Agent automatically selects the right tool

💡 Production Best Practices

•

Always set max_iterations: Prevent infinite loops (default 15, use 5-10 for safety)

•

Use OpenAI Functions in prod: Most reliable, fewer hallucinations than ReAct

•

Write clear tool descriptions: LLM uses them to decide which tool to call

•

Implement callbacks: LangSmith or custom logging for observability

•

Test with edge cases: Ambiguous queries, invalid tool inputs, missing data

LangChain Agents

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