[ arisa.sh ] v4.3.0thinking...
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personal assistant through Telegram·powered by Pi Agent

// the agent builds itself around the user, not the other way around

$npm i -g arisa && arisa
1.1about
readme ▸ overview

Arisa keeps exactly two things and nothing more: Telegram as the human interface and Pi Agent as the reasoning engine.

No pre-loaded opinions about what the agent should do or which tools it should have. It starts minimal and grows from real use.

  • Telegram is the human interface
  • Pi Agent is the reasoning engine
  • everything is an artifact
  • capabilities live in isolated CLI tools
  • tools can be chained through pipes
1.2load
minimal experience
arisa37 kB
openclaw85 MB
3 deps vs 55 deps · openclaw is ≈ 2,300× heavier and carries 18× more dependencies
version 4.3.0footprint 37 kBdeps 3iface Telegram
2install
npm i -g arisa

Install globally, then run arisa. First launch guides you through Telegram setup, Pi provider/model selection, authentication, and validation.

ChatGPT subscription is enough: Arisa can authenticate through Pi's Codex OAuth flow, so you do not need a standard OpenAI API key when using supported providers.

commandaction
arisarun in foreground, blocking
arisa startstart in background
arisa stopstop background service
arisa statusshow background service status
arisa flushremove ~/.arisa
arisa --silentrun without verbose logs
arisa --pi.model ...override the model for the current process only
3arch
two pipes ▸ one engine

Arisa separates pre-reasoning normalization from reasoned action. Voice can become text before reasoning; TTS, downloads, and other chains happen after the agent decides.

telegram
text · voice · media
pi agent
one session per chat · queued batches
tools + artifacts
isolated CLI · chained pipes
4zero tools
assembled on demand

A fresh install ships with zero tools. The core is Telegram transport, the Pi Agent reasoning loop, the artifact store, and the tool registry.

  1. a request arrives that current tools cannot satisfy
  2. Arisa checks the official catalog for a matching tool
  3. low-footprint tools install immediately; heavier tools ask for confirmation
  4. if no catalog tool fits, Arisa builds the missing capability
  5. installed tools live in ~/.arisa/tools/ and are reused later
5cookbook
tools in the wild

Arisa is not a feature list. It adapts to the work: it connects tools, keeps context, and lets each chat decide how much control to retain.

use caseflow
multiplayer
WebRTC without a game server
signaling-server coordinates peers and turn-server provides TURN relays when a direct connection is not enough. Useful for rooms, calls, data channels, and multiplayer games.
a live site
idea → design → HTTPS
Ask for a landing page or internal tool: site-builder shapes the page and roster-sites publishes it with a domain and HTTPS.
live WhatsApp
group, lookup, or reply
whatsapp-web keeps one session per chat. It can reply in a group, search the web to compare prices, or receive audio that passes through transcribe before Arisa replies.
press campaign
research → draft → Gmail
web-browser finds a real reference. pr-campaign tracks the contact, creates the personalized outreach, and calls gmail-workspace to save it in Gmail Drafts. In review mode, it waits for approval; in automatic mode, it sends only within the campaign rules. stop-slop checks the tone.
web security
authorized audit
web-pentest-auditor checks headers, CORS, public routes, bundles, and token storage without attacking or modifying the site. It is technical review a normal chat cannot run on its own.
understand media
audio and video enter context
Audio is transcribed; video goes through real-video-analyzer, which extracts scenes and visual evidence. The result returns as an artifact Arisa can interpret.
pipes
one tool prepares the next
Tools do not live in isolation: URL → video → audio → transcript; research → reference → draft; message → WhatsApp reply. Arisa assembles the pipe it needs and reuses it.
6philosophy
manifesto

The agent should not come preloaded with vices or assumptions. It starts minimal and grows through real use, shaped by the user instead of the framework.

The codebase was built with Pi Agent itself, running on Codex: a recursive loop where the agent can reason about and improve its own system.

6.1missing capability
  1. check whether an installed tool can solve the task
  2. if not, check the official catalog and install or propose the match
  3. if nothing fits, build the missing tool
  4. keep the solution inside the tool architecture
note no "I can't do that" when the thing is realistically buildable.