placet-io

placet-io / facio

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A proactive AI agent for secure, traceable, human-in-the-loop task execution over long-running workflows.

agent agentic-ai agentic-workflow ai-agent approval-workflow
38
1
100% credibility
Found May 14, 2026 at 43 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Facio is an open-source runtime for building reliable, human-in-the-loop AI agents that persist state, handle approvals, and support multimodal workflows across various channels.

How It Works

1
🔍 Discover Facio

You hear about Facio, a helpful AI assistant that works alongside you for reliable, long-term tasks without taking over.

2
🚀 Set up in seconds

Run a simple command that checks your computer, downloads everything needed, and starts your personal AI workspace.

3
🔐 Create your login

Pick an email and password to securely access your AI through a friendly web page.

4
💬 Start chatting

Open the web app, say hello to your agent, and watch it respond while keeping full control.

5
✅ Guide and approve

The AI suggests actions, you review and approve safely, and it handles repetitive work reliably.

🎉 Your AI partner is ready

Enjoy a persistent assistant that remembers everything, improves over time, and collaborates perfectly on your tasks.

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Star Growth

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AI-Generated Review

What is facio?

Facio runs persistent AI agents that tackle long-running workflows with built-in human oversight, like approvals, structured forms, and resumable sessions. You get a Docker-one-liner quickstart spinning up agents integrated with Placet for file-heavy chats, plus channels like Slack, Discord, Telegram, and Teams. Python-based, it handles tools for browser automation, shell execs, MCP servers, cron jobs, image/video gen, and secure credential storage—keeping everything auditable and multimodal.

Why is it gaining traction?

In a sea of github proactive agent demos that flake after one failure, facio shines for real ops: it persists state across weeks, self-inspects logs for recovery, and gates risky actions behind HITL prompts. No token airdrops or crypto—just pragmatic features like runtime model switching, dynamic skills, and policy controls that proactive agent openclaw github forks envy. Devs dig the audit trails and how it scales agents via simple CLI commands like `./facio scale 3`.

Who should use this?

Ops engineers automating release pipelines or incident response with approval gates. Devs building personal research assistants that remember bugs and chain browser + code tools over days. Teams needing secure, traceable agents for customer support escalations or tool-rich knowledge work, beyond basic proactive agent ai chatbots.

Verdict

Alpha-stage with 38 stars and 1.0% credibility—docs are README-focused, tests basic—but grab it if you need production HITL agents now. Skip for quick prototypes; it's overkill there. Promising for clawd bot proactive-agent workflows if you Docker it up.

(187 words)

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