待翻译：Awareness Local: local-first memory for AI coding agents (96% R5 on LongMemEval)

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Notifications You must be signed in to change notification settings Fork 1 Star 8 BranchesTags Open more actions menu Latest commit History 79 Commits 79 Commits Folders and files NameName Last commit message Last commit date .awareness .awareness .stryker-tmp/sandbox-PEBKNR .stryker-tmp/sandbox-PEBKNR assets/branding assets/branding benchmarks/longmemeval benchmarks/longmemeval bin bin reports/mutation reports/mutation scripts scripts src src test-results test-results test test .mcp.json .mcp.json CHANGELOG.md CHANGELOG.md CONTRIBUTING.md CONTRIBUTING.md LICENSE LICENSE README.md README.md README.zh-CN.md README.zh-CN.md awareness-spec.json awareness-spec.json install-transformers.mjs install-transformers.mjs package-lock.json package-lock.json package.json package.json playwright.config.mjs playwright.config.mjs stryker.project-dir.conf.mjs stryker.project-dir.conf.mjs Repository files navigation Languages: English | 简体中文 Give your AI agent persistent memory. One command. No account. Works offline. Awareness Local is a local-first MCP memory server for AI coding agents. It gives Cursor, Claude Code, Copilot, Cline, and other MCP IDEs persistent memory, hybrid semantic + keyword retrieval, and reusable knowledge cards for long-running software projects. It runs a lightweight daemon on your machine, stores memory as Markdown, indexes recall with SQLite FTS5 + embeddings, and keeps your AI workflow fast, explainable, and offline-ready. npx @awareness.market/setup That's it. Your AI agent now remembers everything across sessions. Why Awareness Local AI coding agents lose context between sessions. Awareness Local provides cross-session memory recall so agents can continue work without re-explaining architecture, past decisions, pending tasks, and implementation constraints. Persistent memory for AI coding agents Local-first MCP server with offline support Hybrid retrieval (keyword + semantic) Knowledge card extraction for decisions, solutions, and risks Quick Start npx @awareness.market/setup Then open your IDE and start coding. Awareness tools become available for recall, record, and session initialization. Popular Use Cases Long-running codebase migrations across many sessions Team handoffs where AI should remember prior implementation context Personal coding workflows that need durable preferences and conventions Multi-agent setups that share decision history and task memory FAQ Does Awareness Local work offline? Yes. Local mode works fully offline with memory stored on your machine. Where is data stored? Memory is stored as Markdown in .awareness/, with a local SQLite index for retrieval. Do I need a cloud account? No. Cloud sync is optional and can be enabled later. Which IDEs are supported? Any MCP-compatible IDE, including Cursor, Claude Code, Copilot, Cline, Windsurf, and others. Navigation Benchmark: LongMemEval Supported IDEs How It Works MCP Tools Cloud Sync SDK & Plugin Ecosystem Benchmark: LongMemEval (ICLR 2025) Evaluated on LongMemEval — the industry standard benchmark for long-term conversational memory. 500 human-curated questions across 5 core capabilities. ╔══════════════════════════════════════════════════════════════╗ ║ ║ ║ Awareness Memory — LongMemEval Benchmark Results ║ ║ ───────────────────────────────────────────────── ║ ║ ║ ║ Benchmark: LongMemEval (ICLR 2025) ║ ║ Dataset: 500 human-curated questions ║ ║ Variant: LongMemEval_S (~115k tokens per question) ║ ║ ║ ║ ┌─────────────────────────────────────────────────┐ ║ ║ │ │ ║ ║ │ Recall@1 80.2% (401 / 500) │ ║ ║ │ Recall@3 92.8% (464 / 500) │ ║ ║ │ Recall@5 96.0% (480 / 500) ◀ PRIMARY │ ║ ║ │ Recall@10 98.6% (493 / 500) │ ║ ║ │ │ ║ ║ └─────────────────────────────────────────────────┘ ║ ║ ║ ║ Method: Hybrid RRF (BM25 + vector, daemon pipeline) ║ ║ Embedding: multilingual-e5-small (production model) ║ ║ LLM Calls: 0 (pure retrieval, no generation cost) ║ ║ Hardware: Apple M1, 8GB RAM — 35 min total ║ ║ ║ ╚══════════════════════════════════════════════════════════════╝ ┌─────────────────────────────────────────────────────────────┐ │ Long-Term Memory Retrieval — R@5 Leaderboard │ │ LongMemEval (ICLR 2025, 500 questions) │ ├─────────────────────────────────┬───────────┬───────────────┤ │ System │ R@5 │ Note │ ├─────────────────────────────────┼───────────┼───────────────┤ │ MemPalace (ChromaDB raw) │ 96.6% │ R@5 only * │ │ ★ Awareness Memory (Hybrid) │ 96.0% │ Hybrid RRF │ │ OMEGA │ 95.4% │ QA Accuracy │ │ Mastra (GPT-5-mini) │ 94.9% │ QA Accuracy │ │ Mastra (GPT-4o) │ 84.2% │ QA Accuracy │ │ Supermemory │ 81.6% │ QA Accuracy │ │ Zep / Graphiti │ 71.2% │ QA Accuracy │ │ GPT-4o (full context) │ 60.6% │ QA Accuracy │ ├─────────────────────────────────┴───────────┴───────────────┤ │ * MemPalace 96.6% is Recall@5 only, not QA Accuracy. │ │ Palace hierarchy was NOT used in the evaluation. │ └─────────────────────────────────────────────────────────────┘ ┌─────────────────────────────────────────────────────────────┐ │ Awareness Memory — R@5 by Question Type │ │ │ │ knowledge-update ███████████████████████████ 98.7% │ │ multi-session ███████████████████████████▊ 99.2%│ │ single-session-asst ███████████████████████████▌ 98.2%│ │ temporal-reasoning ██████████████████████████▏ 93.2%│ │ single-session-user ██████████████████████████ 92.9%│ │ single-session-pref █████████████████████████▎ 90.0%│ │ │ │ Overall ██████████████████████████▉ 96.0%│ │ │ │ ┌───────────────────────────────────────────────┐ │ │ │ Ablation Study │ │ │ │ ───────────────────────────────────────── │ │ │ │ Vector-only: 92.6% ▓▓▓▓▓▓▓▓▓▓▓▓▓░░░ │ │ │ │ BM25-only: 91.4% ▓▓▓▓▓▓▓▓▓▓▓▓▓░░░ │ │ │ │ Hybrid RRF: 95.6% ▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓░ ★ │ │ │ │ (2026-04 harness run) │ │ │ │ Hybrid = +3% over any single method │ │ │ └───────────────────────────────────────────────┘ │ │ │ │ arxiv.org/abs/2410.10813 awareness.market │ └─────────────────────────────────────────────────────────────┘ Zero LLM calls on retrieval (daemon path). Reproducible benchmark scripts → What It Does Before: Every session starts from scratch. You re-explain the codebase, re-justify decisions, watch the agent redo work. After: Your agent says "I remember you were migrating from MySQL to PostgreSQL. Last session you completed the schema changes and had 2 TODOs remaining..." Session 1 Session 2 ┌─────────────────────────┐ ┌─────────────────────────┐ │ Agent: "What database?" │ │ Agent: "I remember we │ │ You: "PostgreSQL..." │ │ chose PostgreSQL for │ │ Agent: "What framework?"│ → │ JSON support. You had │ │ You: "FastAPI..." │ │ 2 TODOs left. Let me │ │ (repeat every session) │ │ continue from there." │ └─────────────────────────┘ └─────────────────────────┘ Supported IDEs (13+) IDE Auto-detected Plugin Claude Code ✅ awareness-memory Cursor ✅ via MCP Windsurf ✅ via MCP OpenClaw ✅ @awareness.market/openclaw-memory Cline ✅ via MCP GitHub Copilot ✅ via MCP Codex CLI ✅ via MCP Kiro ✅ via MCP Trae ✅ via MCP Zed ✅ via MCP JetBrains (Junie) ✅ via MCP Augment ✅ via MCP AntiGravity (Jules) ✅ via MCP How It Works Your IDE / AI Agent │ │ MCP Protocol (localhost:37800) ▼ ┌────────────────────────────────────┐ │ Awareness Local Daemon │ │ │ │ Markdown files → Human-readable, git-friendly │ SQLite FTS5 → Fast keyword search │ Local embedding → Semantic search (optional: npm i @huggingface/transformers) │ Knowledge cards → Auto-extracted decisions, solutions, risks │ Web Dashboard → http://localhost:37800/ │ │ │ Cloud sync (optional) │ │ → One-click device-auth │ │ → Bidirectional sync │ │ → Semantic vector search │ │ → Team collaboration │ └────────────────────────────────────┘ Your Data All memories stored as Markdown files in .awareness/ — human-readable, editable, git-friendly: .awareness/ ├── memories/ │ ├── 2026-03-22_decided-to-use-postgresql.md │ ├── 2026-03-22_fixed-auth-bug.md │ └── ... ├── knowledge/ │ ├── decisions/postgresql-over-mysql.md │ └── solutions/auth-token-refresh.md ├── tasks/ │ └── open/implement-rate-limiting.md └── index.db (search index, auto-rebuilt) Features MCP Tools (available in your IDE) Tool What it does awareness_init Load session context — recent knowledge, tasks, rules awareness_recall Search memories — progressive disclosure (summary → full) awareness_record Save decisions, code changes, insights — with knowledge extraction awareness_lookup Fast lookup — tasks, knowledge cards, session history, risks awareness_get_agent_prompt Get agent-specific prompts for multi-agent setups Progressive Disclosure (Smart Token Usage) Instead of dumping everything into context, Awareness uses a two-phase recall: Phase 1: awareness_recall(query, detail="summary") → Lightweight index (~80 tokens each): title + summary + score → Agent reviews and picks what's relevant Phase 2: awareness_recall(detail="full", ids=[...]) → Complete content for selected items only → No truncation, no wasted tokens Web Dashboard Visit http://localhost:37800/ to browse memories, knowledge cards, tasks, and manage cloud sync. Cloud Sync (Optional) Connect to Awareness Cloud for: Semantic vector search (100+ languages) Cross-device real-time sync Team collaboration Memory marketplace npx @awareness.market/setup --cloud # Or click "Connect to Cloud" in the dashboard SDK & Plugin Ecosystem Awareness Local is part of the Awareness ecosystem: Package For Install Awareness Local Local daemon + MCP server npx @awareness.market/setup Python SDK wrap_openai() / wrap_anthropic() interceptors pip install awareness-memory-cloud TypeScript SDK wrapOpenAI() / wrapAnthropic() interceptors npm i @awareness-sdk/memory-cloud OpenClaw Plugin Auto-recall + auto-capture openclaw plugins install @awareness.market/openclaw-memory Claude Code Plugin Skills + hooks /plugin marketplace add everest-an/Awareness-SDK → /plugin install awareness-memory@awareness Setup CLI One-command setup for 13+ IDEs npx @awareness.market/setup Full SDK docs: awareness.market/docs Requirements Node.js 18+ Any MCP-compatible IDE No Python, no Docker, no cloud account needed. ⭐ Support the project If Awareness Local saves you from re-explaining your codebase to your AI agent, give it a ⭐ — it helps more developers discover the project and pushes it toward GitHub Trending. License MIT Tags & Integration IDE Support: Cursor, Windsurf, Trae, Zed, VS Code, JetBrains. Compatible with: OpenClaw, AutoGPT, LangChain, MetaGPT. Key Technology: OMP (Open Memory Protocol), LatentMAS, Shared Thought Space, One-click Deployment. Focus: Solving AI "Lobster Memory" (Long-term memory loss), Automating complex workflows, Simplifying Agent setup. Topics Resources Readme MIT license Contributing Contributing Activity Stars 8 stars Watchers 0 watching Forks 1 fork Report repository