Handling rate limits and errors in LangChain - Mini Project: Build & Apply

Handling rate limits and errors

📖 Scenario: You are building a simple chatbot using LangChain that talks to an AI model. Sometimes, the AI service limits how many requests you can send quickly, or errors happen. You want to handle these limits and errors smoothly so your chatbot keeps working well.

🎯 Goal: Build a LangChain chatbot that tries to send a message to the AI model. If the service says you hit a rate limit, the chatbot waits and tries again. If other errors happen, it shows a friendly message. This way, the chatbot handles limits and errors nicely.

📋 What You'll Learn

Create a LangChain ChatOpenAI object with a simple prompt.

Add a variable max_retries to control retry attempts.

Write a try-except block to catch RateLimitError and retry.

Handle other exceptions with a friendly error message.

💡 Why This Matters

🌍 Real World

Many AI services limit how often you can send requests. Handling these limits smoothly keeps your app working well without crashing or confusing users.

💼 Career

Knowing how to handle rate limits and errors is important for developers building apps that use APIs, especially AI and cloud services.

1

DATA SETUP: Create LangChain ChatOpenAI object

Import ChatOpenAI from langchain_openai and create a variable called chat that is a ChatOpenAI object with model='gpt-4o-mini'.

LangChain

# Import ChatOpenAI and create chat object
# Your code here

Need a hint?

Use from langchain_openai import ChatOpenAI and then chat = ChatOpenAI(model='gpt-4o-mini').

2

CONFIGURATION: Add max_retries variable

Create a variable called max_retries and set it to 3. This will control how many times the chatbot tries again if rate limited.

LangChain

from langchain_openai import ChatOpenAI

chat = ChatOpenAI(model='gpt-4o-mini')

# Set max_retries to 3
# Your code here

Need a hint?

Just write max_retries = 3 below the chat object.

3

CORE LOGIC: Handle RateLimitError with retries

Import RateLimitError from openai.error. Write a for loop that tries up to max_retries times to call chat with a message 'Hello!'. Use a try-except block to catch RateLimitError. If caught, wait 2 seconds and retry. If successful, break the loop.

LangChain

from langchain_openai import ChatOpenAI
from openai.error import RateLimitError
import time

chat = ChatOpenAI(model='gpt-4o-mini')

max_retries = 3

# Try sending message with retry on RateLimitError
# Your code here

Need a hint?

Use for attempt in range(max_retries): and inside try call chat.invoke. Catch RateLimitError and time.sleep(2).

4

COMPLETION: Handle other errors with friendly message

Add an except Exception as e block after except RateLimitError to catch all other errors. Inside it, set response to a string 'Sorry, an error occurred: ' plus the error message str(e).

LangChain

from langchain_openai import ChatOpenAI
from openai.error import RateLimitError
import time

chat = ChatOpenAI(model='gpt-4o-mini')

max_retries = 3

for attempt in range(max_retries):
    try:
        response = chat.invoke('Hello!')
        break
    except RateLimitError:
        time.sleep(2)
    # Add except block for other exceptions
    # Your code here

Need a hint?

Add except Exception as e: after except RateLimitError: and set response to the error message.