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Token-bounded short-term memory for Autourgos agents — TokenBufferedMemory.

Project description

autourgos-token-memory

Token-bounded short-term memory for Autourgos agents.

Keeps messages in RAM and evicts the oldest ones when the total token count exceeds a budget. Automatically uses tiktoken for accurate counts if installed, with a fast character-based heuristic as fallback.


Install

pip install autourgos-token-memory

# For accurate tiktoken counts (recommended for OpenAI models)
pip install 'autourgos-token-memory[tiktoken]'

Quick Start

from autourgos_token_memory import TokenBufferedMemory
from autourgos_react_agent import ReactAgent

memory = TokenBufferedMemory(max_tokens=4000)
agent  = ReactAgent(llm=my_llm, memory=memory)
agent.invoke("Long conversation task...")

Parameters

Parameter Type Default Description
max_tokens int 2000 Token budget. Oldest messages evicted when exceeded.
token_estimator callable None Custom (text: str) -> int. Defaults to tiktoken / heuristic.

Custom token estimator

from autourgos_token_memory import TokenBufferedMemory

def my_estimator(text: str) -> int:
    return len(text.split())  # word count

memory = TokenBufferedMemory(max_tokens=500, token_estimator=my_estimator)

Token counting

  • tiktoken installed: uses cl100k_base encoding (accurate for GPT-3.5/4/4o).
  • tiktoken not installed: Unicode-aware heuristic — ~0.25 tokens per ASCII char, ~1.5 per CJK character.

Check current usage:

print(memory.total_tokens)  # → int

Links


License

MIT — see LICENSE

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