自动压缩

A3S Code 可以替你将长对话保持在模型的上下文预算内。启用 autoCompact 后， runtime 会持续监测上下文用量；一旦超过 autoCompactThreshold，较早的轮次就会被压缩成一份持续更新的摘要，让 agent 在大量步骤中始终保持连贯，而无需你手动管理 token。续写则处理另一个方向：当单条回复因长度被截断时，runtime 会自动继续生成，拼出完整回复。

Node.js

Python

TypeScript

import { Agent } from '@a3s-lab/code';

const agent = await Agent.create('agent.acl');

const session = agent.session('/repo', {
  // Compact older turns once context fills past the threshold.
  autoCompact: true,
  autoCompactThreshold: 0.75,
  // Auto-continue a single response that the model truncates by length.
  continuationEnabled: true,
  maxContinuationTurns: 3,
});

// Run a long, multi-step task. The runtime compacts older turns as needed;
// you never touch the token math.
for (let i = 0; i < 50; i++) {
  await session.send(`Step ${i}: continue refactoring the parser`);
}

// Inspect what the session is currently carrying.
console.log('history turns:', session.history().length);
console.log('recent memory:', await session.memoryRecent(5));

session.close();

Python

from a3s_code import Agent, SessionOptions

agent = Agent.create("agent.acl")

opts = SessionOptions()
# Compact older turns once context fills past the threshold.
opts.auto_compact = True
opts.auto_compact_threshold = 0.75
# Auto-continue a single response that the model truncates by length.
opts.continuation_enabled = True
opts.max_continuation_turns = 3
session = agent.session("/repo", opts)

# Run a long, multi-step task. The runtime compacts older turns as needed;
# you never touch the token math.
for i in range(50):
    session.send(f"Step {i}: continue refactoring the parser")

# Inspect what the session is currently carrying.
print("history turns:", len(session.history()))
print("recent memory:", session.memory_recent(5))

session.close()

长 session 若希望由 runtime 替你管理 context pressure，就使用自动压缩。 autoCompactThreshold / auto_compact_threshold 是触发压缩的上下文窗口占比（0.0–1.0，默认 0.8）；调低它可以更早触发压缩。用 history()（同步）和 memoryRecent / memory_recent 查看实时 session。

#自动压缩

自动压缩