Reference library

AI & LLM integration patterns

Call LLM APIs, structure prompts, parse responses, and ship AI features safely.

5 matches

Circuit Breaker Pattern in Python for LLM API Calls

Implements a circuit breaker class that wraps LLM client calls to fail fast when the service is degrading, then recover automatically after a timeout.

circuit-breaker llm resilience

Python

import time

class CircuitBreaker:
    def __init__(self, failure_threshold=3, recovery_timeout=5):
        self.failure_threshold = failure_threshold
        self.recovery_timeout = recovery_timeout
        self.failure_count = 0
        self.state = "closed"
        self.last_failure_time = None

    def call(self, …

15 0 Open

AI & LLM integration patterns medium

How to Build a Data Helper for LLM Prompts in Python

A beginner-friendly helper class that flattens nested dictionaries, formats prompt templates, and safely parses JSON for AI/LLM pipelines.

llm prompt-engineering data-prep

Python

import json
from typing import Any, Dict, List, Optional


class DataHelper:
    """Simple helper class for working with data in AI/LLM pipelines."""
    
    def __init__(self, data: Optional[Dict[str, Any]] = None) -> None:
        self.data = data or {}
    
    def flatten(self, prefix: str = "") -> Dict[str, Any]…

17 0 Open

AI & LLM integration patterns medium

How to Detect Prompt Injection in Python

Implements a regex-based heuristic in Python to flag common prompt injection attempts before sending input to an LLM.

prompt-injection regex llm-security

Python

import re

def contains_prompt_injection(user_input: str) -> bool:
    # Directives to ignore previous instructions or act as system
    ignore_patterns = [
        r"\bignore\s+(all\s+)?previous\s+instructions\b",
        r"\bdisregard\s+(all\s+)?previous\s+instructions\b",
        r"\bdon'?t\s+follow\s+(any\s+)?inst…

13 0 Open

AI & LLM integration patterns medium

How to Repair Malformed JSON Braces Heuristically in Python

Heuristically fix malformed JSON by balancing braces and quotes, using a stack-based approach to add missing closing characters.

json repair heuristic

Python

import json
import re

def repair_json(text: str) -> str:
    """Heuristically repair malformed JSON by balancing braces and quotes."""
    # Trim whitespace and handle leading/trailing garbage
    text = text.strip()
    
    # Remove common non-JSON decorations
    text = re.sub(r'^(

13 0 Open

AI & LLM integration patterns medium

How to Retry LLM Calls on Rate Limit Errors in Python

Implement a retry mechanism with exponential backoff for LLM API calls that raises a custom RateLimitError, using a mock function to demonstrate the pattern.

llm retry rate-limit

Python

import time
import random


def mock_llm_call():
    """Simulates an LLM API call that may raise a rate limit error."""
    if random.random() < 0.4:  # 40% chance of rate limit
        raise RateLimitError("Rate limit exceeded. Try again later.")
    return {"response": "Hello world from mock LLM"}


class RateLimitE…

16 0 Open

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