wenshuangl/agent-mem

Prompts

Multi-Agent Memory + Dispatch System. 4-tier memory (HOT/WARM/COLD/ARCHIVE), cross-channel sharing, dispatch loop with auto-learning.

Install

openclaw skills install agent-mem

AgentMem

Multi-Agent Memory + Dispatch System

Core Capabilities

1. Four-Tier Memory (HOT → WARM → COLD → ARCHIVE)

Memories decay naturally over time instead of being treated equally.

2. Cross-Channel Memory Sharing

Same agent shares memory across different channels (webchat/Feishu/Slack/Telegram).

3. Dispatch + Memory Loop

User request → Intent recognition → Agent dispatch → Execution → Auto-log → Optimize next dispatch

4. 17 Memory Modules

Fact extraction, BM25+vector fusion search, contradiction detection, knowledge graph, forgetting mechanism, active recall, memory feedback, self-review.

Quick Start

pip install -e .

# Write a memory
python -m agent_mem.core.hot_cache write --agent main --channel webchat --text "User prefers concise answers" --importance 7

# Cross-channel query
python -m agent_mem.core.hot_cache query --agent main --limit 5

# Dispatch stats
python -m agent_mem.core.dispatch_logger stats

# Run memory engine
python -m agent_mem.core.engine_v2 --mode daily

Requirements

Python 3.10+
chromadb (single dependency)
Zero external API dependencies, fully local