mirror of https://github.com/agentscope-ai/ReMe.git synced 2026-09-19 00:01:33 +00:00

feat(proactive): separate proactive refresh from auto dream (#488 )

* refractor(proactive): upgrade proactive feature with disentangled job and steps

* refactor(proactive): apply audit fixes

- rename read-side job 'proactive' -> 'proactive_read' (less confusing vs the refresh pipeline)
- drop dedicated agent_wrapper.proactive; extraction reuses the default wrapper
- simplify schema: remove unused ProactiveExtractOutput/TopicUpdate, drop resource_paths
- extract no longer scans resource/ directly (daily notes already carry resource content)
- update tests and docs accordingly

* feat(proactive): strict extract-output gate and prompt total budget

- parse_extract_reply now requires a contract section (follow_ups/extends/updates
  as a list); non-empty replies with misspelled section names trigger the
  existing one-shot retry instead of silently checkpointing changed files
- pack_paths gains max_total_chars; extract packs newest daily material first,
  keeps the first file on overflow, and records omitted files in a trailer
  (default budget 300000 chars, configurable via max_total_chars)
- tests: schema gate unit, schema-error retry e2e, budget unit + e2e

* feat(proactive): add scenario-card plan step and generative agenda step

* feat(proactive): digest-personal profile personalization and leaner LLM contract

- extract/plan/agenda now draw a user profile block from <digest_dir>/personal/*.md
  (frontmatter description + body excerpt, per-file budget, profile.md fallback)
- all daily access honours the configured daily_dir (prompt paths parameterized,
  config-driven fallbacks) so workspaces using e.g. memory/ work unchanged
- schema trim: drop dead fields errors/material_paths, carry_forward_all -> count
- shrink LLM output contract: new topics emit title/reason/confidence/paths only;
  keywords removed end-to-end, evidence derived from paths[0] (updates keep it)

* fix(proactive): skip checkpoint when extract reply stays unusable after retry

Two consecutive unparseable replies now short-circuit the round without
checkpointing, so the same material is retried next round instead of being
silently consumed (closes the residual audit #1 gap: the structural gate
detected schema-wrong output but a double failure still checkpointed).

* fix(proactive): replace running bool with reference-counted job activity tracker for the idle gate

* refactor(proactive): remove job activity tracking and idle gate, restore job tree to upstream

* fix(proactive): address second audit round (readonly reader, mtime checkpoint, wider fallbacks, profile containment, horizon content, expiry boundary)

* refactor(dream): strip interests.yaml ownership from dream, proactive is now the sole writer

* refactor(dream): separate proactive topic generation

* ci: update renamed auto dream smoke test

* fix(proactive): complete refresh migration and docs

---------

Co-authored-by: jinli.yl <jinli.yl@alibaba-inc.com>

2026-09-07 17:23:37 +08:00

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title	description
Agent Integrations	Connect ReMe to agents through the CLI, HTTP, MCP, Skills, and host adapters.

Agent Integrations

ReMe keeps memory in an independent service and a user-owned workspace. Multiple agents can call the same memory system without binding storage to one model or host.

Choose an interface

Scenario	Recommended interface
Local script or hook	ReMe CLI
Application backend	HTTP Client
Tool-protocol host	MCP
TypeScript agent	`@agentscope-ai/reme`
Claude Code	MCP + Skill + Stop Hook
Hermes Agent	Memory provider adapter
Codex or another coding agent	`reme_memory` Skill or MCP

General memory loop

Before answering, call search for relevant memory.
Use read on high-value results and traverse when relationships matter.
Retain workspace-relative source paths in the answer.
At session end, pass source messages to auto_memory.
Let background or scheduled workflows consolidate daily notes into digest memory.

An empty search result must remain empty; do not present model inference as recalled history.

MCP

The default HTTP service exposes streamable HTTP MCP at http://127.0.0.1:2333/mcp. Common tools include search, read, traverse, list, auto_memory, and proactive_read.

Use service.jobs to expose a read-only subset or keep write tools in a separate configuration.

CLI and Skill

skills/reme_memory/SKILL.md defines a general workflow for agents that can run local commands: installation checks, service discovery, retrieval, reading, and persistence boundaries.

It deliberately avoids silently modifying Python environments, stopping unknown processes on port conflicts, writing recalled tool output back as conversation source, or persisting credentials.

TypeScript, OpenClaw, and DeepSeek Harness

The @agentscope-ai/reme TypeScript package provides the shared HTTP client and host adapters. See the dedicated guides for DeepSeek Harness and OpenClaw.

Claude Code

integrations/claude_code/ provides streamable HTTP MCP configuration, a reme-memory Skill, and a Stop hook that calls auto_memory_cc. Follow that directory's README for installation.

Hermes Agent

integrations/hermes_agent/ provides a memory provider that recalls context before model calls and asynchronously invokes auto_memory after each turn.

Production guidance

choose a stable absolute workspace_dir;
reuse a service discovered by reme find_reme;
treat reme help as the active Job contract;
apply timeouts and failure logging to writes;
do not block the host's core response path when memory is temporarily unavailable;
use authentication, TLS, and a minimal Job allowlist for remote access.

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