AI & LLM integration patterns
Call LLM APIs, structure prompts, parse responses, and ship AI features safely.
How to Parse JSON from LLM Model Output Fence in Python
Extract and parse a JSON object from a language model's output that may be wrapped in triple-backtick fences with an optional language tag.
import json
import re
def parse_json_from_fence(text):
"""
Extract JSON object from a model output that may be wrapped in
triple-backtick fences with optional language tag.
"""
# Match content insideHow to Parse an LLM Response in Python
This code parses a JSON string from an LLM response, stripping code fences and handling common issues like whitespace, returning a Python dictionary.
import json
from typing import Any, Dict, List
def parse_llm_response(response: str) -> Dict[str, Any]:
"""Parse a JSON string from an LLM response, handling common edge cases."""
# Remove code fences if present
cleaned = response.strip()
if cleaned.startswith("Browse by section
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AI & LLM integration patterns — Python code examples
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This page collects ai & llm integration patterns snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
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