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Memory

NucleusIQ agents support conversation memory across turns. Choose a strategy that fits your workload.

Strategies

Strategy Use case
FULL_HISTORY Short conversations, full context
SLIDING_WINDOW Limit recent messages only
SUMMARY Long conversations, compress older turns
SUMMARY_WINDOW Summary + recent messages
TOKEN_BUDGET Hard token limit

Configuration

from nucleusiq.agents import Agent
from nucleusiq.memory import MemoryFactory, MemoryStrategy

memory = MemoryFactory.create_memory(
    MemoryStrategy.SLIDING_WINDOW,
    window_size=10,
)

agent = Agent(
    ...,
    memory=memory,
)

Strategy examples

from nucleusiq.memory import MemoryFactory, MemoryStrategy

full_history = MemoryFactory.create_memory(MemoryStrategy.FULL_HISTORY)
windowed = MemoryFactory.create_memory(MemoryStrategy.SLIDING_WINDOW, window_size=12)
budgeted = MemoryFactory.create_memory(MemoryStrategy.TOKEN_BUDGET, max_tokens=4096)
summary = MemoryFactory.create_memory(MemoryStrategy.SUMMARY)
summary_window = MemoryFactory.create_memory(MemoryStrategy.SUMMARY_WINDOW, window_size=8)

Use SLIDING_WINDOW for most chat apps, TOKEN_BUDGET for hard limits, and SUMMARY_WINDOW for long-running assistants.

File-aware metadata

All strategies store attachment metadata alongside messages. User messages with attachments get a [Attached: ...] summary prefix for context continuity.

See also