What breaks without openclaw ai assistant framework
Persona management requiring custom code every project. No multi-turn history abstraction in core. LLM provider switching breaking bot implementations.
→
Conversational AI assistant in hours × persona, history, and LLM abstraction pre-built ÷ 20-minute install ÷ no framework from scratch = production assistant without the boilerplate.
Security check — openclaw ai assistant framework
Privacy score: 7/10 — accesses connected platform APIs only.
Lock it: review OAuth scopes before install, confirm Linux, macOS; OpenClaw ≥1.2; compatible with Claude API, OpenAI API, and OpenAI-compatible providers compatibility.
Quick start — openclaw ai assistant framework in 20–40 minutes
Setup time: 20–40 minutes
!
You need:
- OpenClaw core
- LLM API key (Claude
- OpenAI
- or compatible)
- Node.js ≥18
Install the package:
git clone https://github.com/Work-Fisher/openclaw-ai-assistant-framework
cd openclaw-ai-assistant-framework && npm install
npm start
2
Configure your LLM API key and provider in config.js
3
Define your assistant's persona and capabilities in assistant.config.js
4
Run npm start to launch the assistant
5
Connect your preferred adapter (QQ, DingTalk, Feishu, etc.)
6
Test with a multi-turn conversation
Compatibility & status
Works with: Linux, macOS; OpenClaw ≥1.2; compatible with Claude API, OpenAI API, and OpenAI-compatible providers
intermediate
Last updated: Oct 2025
★ 260 on GitHub
MIT
Official docs →
View on GitHub →
FAQ — openclaw ai assistant framework
Does this framework lock me into a specific LLM?
No. The provider abstraction layer supports Claude, OpenAI, and OpenAI-compatible APIs.
How is this different from just using OpenClaw with a skill?
This provides opinionated structure for building assistants — conversation history, persona management, LLM abstraction.
Can I use this with multiple adapters simultaneously?
Yes. The framework works with any adapter registered in OpenClaw.