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AI & LLM integration patterns

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

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How to parallel map embeddings with a thread pool in Python

Run embedding computations in parallel using ThreadPoolExecutor, collect results into a dict keyed by the original item.

concurrency threadpool embeddings
Python 
import threading
from concurrent.futures import ThreadPoolExecutor
import time


def compute_embedding(item: int) -> tuple[int, int]:
    time.sleep(0.05)  # Simulate embedding work
    return item, item * 10


def parallel_map_embed(items, max_workers=3):
    results = {}
    with ThreadPoolExecutor(max_workers=max_w…
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