AI & LLM integration patterns
Call LLM APIs, structure prompts, parse responses, and ship AI features safely.
How to Keep Last K Turns in a Memory Buffer in Python
A TurnBuffer class using deque with maxlen to keep only the most recent k conversation turns in memory for LLM context.
from collections import deque
class TurnBuffer:
def __init__(self, k):
self.k = k
self.turns = deque(maxlen=k)
def add(self, turn):
self.turns.append(turn)
def last_k(self):
return list(self.turns)
if __name__ == "__main__":
buffer = TurnBuffer(3)
buffer.add("tu…How to Truncate Text to a Token Budget in Python
Truncate a string to a maximum token budget for LLM context using the tiktoken library and OpenAI's tokenizer.
import tiktoken
def truncate_to_token_budget(text, max_tokens, model="gpt-3.5-turbo"):
enc = tiktoken.encoding_for_model(model)
tokens = enc.encode(text)
if len(tokens) <= max_tokens:
return text
truncated_tokens = tokens[:max_tokens]
return enc.decode(truncated_tokens)
if __name__ == "__…Browse by section
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AI & LLM integration patterns — Python code examples
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