Error Handling - LangChain in Production

Learn robust error handling strategies for LangChain applications, including retries, circuit breakers, and graceful degradation

🚨 Error Handling Overview

Error handling ensures reliability and resilience in LangChain systems. This guide covers error patterns, retry logic, circuit breakers, and best practices for production.

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🏛️ Error Patterns

• Catch and log exceptions at all layers
• Use custom error classes for clarity
• Provide meaningful error messages to users

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🔄 Retry Logic & Circuit Breakers

• Implement retries with exponential backoff
• Use circuit breakers to prevent cascading failures
• Gracefully degrade features on persistent errors

import time
import logging

logger = logging.getLogger("langchain")

# Retry with exponential backoff
def retry_call(func, max_attempts=3):
    for attempt in range(max_attempts):
        try:
            return func()
        except Exception as e:
            logger.error(f"Attempt {attempt+1} failed: {e}")
            time.sleep(2 ** attempt)
    raise Exception("All attempts failed")

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🧩 Example: FastAPI Error Handler

from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse

app = FastAPI()

@app.exception_handler(Exception)
def generic_exception_handler(request: Request, exc: Exception):
    return JSONResponse(status_code=500, content={"error": str(exc)})

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🔗 Next Steps

• Logging Patterns
• Monitoring Patterns
• Callback Patterns

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Key Error Handling Takeaways:

• Catch and log all exceptions
• Use retries and circuit breakers
• Gracefully degrade on persistent errors
• Provide clear error messages
• Continuously improve error handling