Handling rate limits and errors in LangChain - Step-by-Step Execution

Concept Flow - Handling rate limits and errors

Start API Call

↓

Send Request

↓

Receive Response

↓

Is Response OK?

No→Is Rate Limit Error?

↓

Process Data

↓

End

This flow shows how a request is sent, checked for errors, and if a rate limit error occurs, waits and retries before processing data.

Execution Sample

LangChain

from langchain import OpenAI
from openai.error import RateLimitError

client = OpenAI()

try:
    response = client("Hello")
except RateLimitError:
    # wait and retry
    pass

This code tries to send a request to OpenAI via Langchain, catches a rate limit error, and plans to retry.

Execution Table

Step	Action	API Response	Error Detected	Next Step
1	Send request with prompt 'Hello'	429 Too Many Requests	RateLimitError	Wait 2 seconds and retry
2	Retry request	200 OK with response text	No error	Process response data
3	Process response	Response text processed	No error	End execution

💡 Request succeeded after retrying due to rate limit error

Variable Tracker

Variable	Start	After Step 1	After Step 2	Final
response	None	Error 429	Valid response text	Valid response text
error	None	RateLimitError caught	None	None
retry_count	0	1	1	1

Key Moments - 2 Insights

Why do we catch RateLimitError separately from other errors?

Because rate limit errors mean we should wait and retry, unlike other errors which may need different handling. See execution_table step 1 where RateLimitError triggers a wait and retry.

What happens if the retry also hits a rate limit?

You would catch the RateLimitError again and typically increase wait time or stop after max retries. This example shows one retry for simplicity (execution_table step 2).

Visual Quiz - 3 Questions

Look at the execution table, what is the API response at step 1?

A 429 Too Many Requests

B 500 Internal Server Error

C 200 OK with response text

D No response

💡 Hint

Check the 'API Response' column in execution_table row for step 1

At which step does the code process the valid response data?

A Step 1

B Step 3

C Step 2

D No processing happens

💡 Hint

Look at the 'Next Step' column in execution_table for step 3

If the retry_count variable started at 0, what is its value after the first retry?

A 2

B 0

C 1

D Undefined

💡 Hint

See variable_tracker row for retry_count after Step 2

Concept Snapshot

Handling rate limits means catching specific errors from API calls.
When a rate limit error occurs, wait some time and retry the request.
Other errors need different handling.
Track retries to avoid infinite loops.
Process data only after a successful response.

Full Transcript

This lesson shows how to handle rate limits and errors when using Langchain to call APIs. The code sends a request and checks the response. If a rate limit error occurs (HTTP 429), it waits and retries the request. After a successful retry, it processes the response data. Variables like response, error, and retry_count change during execution. Key points include catching rate limit errors separately and retrying carefully. The visual quiz tests understanding of the steps and variable changes.