shareAI-lab/claw0

Dernière activité source enregistrée: 26 février 2026 à 15:44

Catalogue SkillsMP mis à jour: 9 novembre 2026 à 14:22

skills collectés: 1

Étoiles GitHub: 3 439
Forks GitHub: 389

Installer avec un assistant IA

Copiez ce prompt dans l’assistant IA que vous utilisez.

Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/shareAI-lab/claw0.

README du dépôt

Fichier source du README : README.md

Lire le README source

Afficher le README complet

[English](README.md) | [中文](README.zh.md) | [日本語](README.ja.md) # claw0 **From Zero to One: Build an AI Agent Gateway** > 10 progressive sections -- every section is a single, runnable Python file. > 3 languages (English, Chinese, Japanese) -- code + docs co-located. --- ## What is this? Most agent tutorials stop at "call an API once." This repository starts from that while loop and takes you all the way to a production-grade gateway. Build a minimal AI agent gateway from scratch, section by section. 10 sections, 10 core concepts, ~7,000 lines of Python. Each section introduces exactly one new idea while keeping all prior code intact. After all 10, you can read OpenClaw's production codebase with confidence. ```sh s01: Agent Loop -- The foundation: while + stop_reason s02: Tool Use -- Let the model call tools: dispatch table s03: Sessions & Context -- Persist conversations, handle overflow s04: Channels -- Telegram + Feishu: real channel pipelines s05: Gateway & Routing -- 5-tier binding, session isolation s06: Intelligence -- Soul, memory, skills, prompt assembly s07: Heartbeat & Cron -- Proactive agent + scheduled tasks s08: Delivery -- Reliable message queue with backoff s09: Resilience -- 3-layer retry onion + auth profile rotation s10: Concurrency -- Named lanes serialize the chaos ``` ## Architecture ``` +------------------- claw0 layers -------------------+ | | | s10: Concurrency (named lanes, generation track) | | s09: Resilience (auth rotation, overflow compact)| | s08: Delivery (write-ahead queue, backoff) | | s07: Heartbeat (lane lock, cron scheduler) | | s06: Intelligence (8-layer prompt, hybrid memory) | | s05: Gateway (WebSocket, 5-tier routing) | | s04: Channels (Telegram pipeline, Feishu hook) | | s03: Sessions (JSONL persistence, 3-stage retry)| | s02: Tools (dispatch table, 4 tools) | | s01: Agent Loop (while True + stop_reason) | | | +-----------------------------------------------------+ ``` ## Section Dependencies ``` s01 --> s02 --> s03 --> s04 --> s05 | | v v s06 ----------> s07 --> s08 | | v v s09 ----------> s10 ``` - s01-s02: Foundation (no dependencies) - s03: Builds on s02 (adds persistence to the tool loop) - s04: Builds on s03 (channels produce InboundMessages for sessions) - s05: Builds on s04 (routes channel messages to agents) - s06: Builds on s03 (uses sessions for context, adds prompt layers) - s07: Builds on s06 (heartbeat uses soul/memory for prompt) - s08: Builds on s07 (heartbeat output flows through delivery queue) - s09: Builds on s03+s06 (reuses ContextGuard for overflow, model config) - s10: Builds on s07 (replaces single Lock with named lane system) ## Quick Start ```sh # 1. Clone and enter git clone https://github.com/shareAI-lab/claw0.git && cd claw0 # 2. Install dependencies pip install -r requirements.txt # 3. Configure cp .env.example .env # Edit .env: set ANTHROPIC_API_KEY and MODEL_ID # 4. Run any section (pick your language) python sessions/en/s01_agent_loop.py # English python sessions/zh/s01_agent_loop.py # Chinese python sessions/ja/s01_agent_loop.py # Japanese ``` ## Learning Path Each section adds exactly one new concept. All prior code stays intact: ``` Phase 1: FOUNDATION Phase 2: CONNECTIVITY Phase 3: BRAIN Phase 4: AUTONOMY Phase 5: PRODUCTION +----------------+ +-------------------+ +-----------------+ +-----------------+ +-----------------+ | s01: Loop | | s03: Sessions | | s06: Intelligence| | s07: Heartbeat | | s09: Resilience | | s02: Tools | ---> | s04: Channels | --> | soul, memory, | ->| & Cron |-->| & Concurrency | | | | s05: Gateway | | skills, prompt | | s08: Delivery | | s10: Lanes | +----------------+ +-------------------+ +-----------------+ +-----------------+ +-----------------+ while + dispatch persist + route personality + recall proactive + reliable retry + serialize ``` ## Section Details | # | Section | Core Concept | Lines | |---|---------|-------------|-------| | 01 | Agent Loop | `while True` + `stop_reason` -- that's an agent | ~175 | | 02 | Tool Use | Tools = schema dict + handler map. Model picks a name, you look it up | ~445 | | 03 | Sessions | JSONL: append on write, replay on read. Too big? Summarize old parts | ~890 | | 04 | Channels | Every platform differs, but they all produce the same `InboundMessage` | ~780 | | 05 | Gateway | Binding table maps (channel, peer) to agent. Most specific wins | ~625 | | 06 | Intelligence | System prompt = files on disk. Swap files, change personality | ~750 | | 07 | Heartbeat & Cron | Timer thread: "should I run?" + queue work alongside user messages | ~660 | | 08 | Delivery | Write to disk first, then send. Crashes can't lose messages | ~870 | | 09 | Resilience | 3-layer retry onion: auth rotation, overflow compaction, tool-use loop | ~1130 | | 10 | Concurrency | Named lanes with FIFO queues, generation tracking, Future-based results | ~900 | ## Repository Structure ``` claw0/ README.md English README README.zh.md Chinese README README.ja.md Japanese README .env.example Configuration template requirements.txt Python dependencies sessions/ All teaching sessions (code + docs) en/ English s01_agent_loop.py s01_agent_loop.md s02_tool_use.py s02_tool_use.md ... (10 .py + 10 .md) zh/ Chinese s01_agent_loop.py s01_agent_loop.md ... (10 .py + 10 .md) ja/ Japanese s01_agent_loop.py s01_agent_loop.md ... (10 .py + 10 .md) workspace/ Shared workspace samples SOUL.md IDENTITY.md TOOLS.md USER.md HEARTBEAT.md BOOTSTRAP.md AGENTS.md MEMORY.md CRON.json skills/example-skill/SKILL.md ``` Each language folder is self-contained: runnable Python code + documentation side by side. Code logic is identical across languages; comments and docs differ. ## Prerequisites - Python 3.11+ - An API key for Anthropic (or compatible provider) ## Dependencies ``` anthropic>=0.39.0 python-dotenv>=1.0.0 websockets>=12.0 croniter>=2.0.0 python-telegram-bot>=21.0 httpx>=0.27.0 ``` ## Related Projects - **[learn-claude-code](https://github.com/shareAI-lab/learn-claude-code)** -- A companion teaching repo that builds an agent **framework** (nano Claude Code) from scratch in 12 progressive sessions. Where claw0 focuses on gateway routing, channels, and proactive behavior, learn-claude-code dives deep into the agent's internal design: structured planning (TodoManager + nag), context compression (3-layer compact), file-based task persistence with dependency graphs, team coordination (JSONL mailboxes, shutdown/plan-approval FSM), autonomous self-organization, and git worktree isolation for parallel execution. If you want to understand how a production-grade unit agent works inside, start there. ## About <img width="260" src="https://github.com/user-attachments/assets/fe8b852b-97da-4061-a467-9694906b5edf" /><br> Scan with Wechat to fellow us, or fellow on X: [shareAI-Lab](https://x.com/baicai003) ## License MIT

Chargement du README du dépôt…

Skills dans ce dépôt

Autres occupations informatiques

1 catégories métier · 100% classifié

skill

métier

description

mis à jour

example-skill

Autres occupations informatiques

A sample skill for demonstration

Langue du texte source : anglais

2026-02-26

Affichage de 1 skills collectés sur 1.