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zclaw: personal AI assistant in under 888 KB, running on an ESP32

zclaw is a remarkably compact, C-based AI personal assistant specifically engineered for ESP32 microcontrollers. It boasts an impressive sub-888KB firmware footprint, supporting essential features like GPIO control, scheduled operations, and persistent memory. This project is popular on Hacker News for its technical ingenuity in bringing advanced AI capabilities to resource-limited embedded systems, showcasing efficient software engineering at its best.

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#7
Highest Rank
3h
on Front Page
First Seen
Feb 21, 8:00 PM
Last Seen
Feb 21, 10:00 PM
Rank Over Time
14127

The Lowdown

zclaw is an open-source project that delivers a functional AI personal assistant on ESP32 boards with a remarkably small firmware size. Developed in C, it aims for a strict budget of under 888 KB, demonstrating significant efficiency in embedded AI applications. This project empowers users to integrate AI capabilities into their IoT projects with minimal overhead.

  • Compact Design: The entire AI assistant runs on ESP32 microcontrollers with a firmware size target of less than 888 KB.
  • Core Functionality: Features include chat interaction via Telegram or a hosted web relay, timezone-aware scheduled tasks (daily, periodic, one-shot), and persistent memory across reboots.
  • Hardware Interaction: Provides GPIO read/write control with guardrails, enabling the AI to interact with physical hardware.
  • Tooling & Providers: Supports both built-in and user-defined tools, with compatibility for popular AI providers like Anthropic, OpenAI, and OpenRouter.
  • Ease of Use: Offers quick start scripts for installation, flashing, provisioning credentials, and even latency benchmarking.
  • Supported Hardware: Tested on ESP32-C3, ESP32-S3, and ESP32-C6, with other ESP32 variants expected to be compatible. The Seeed XIAO ESP32-C3 is recommended.
  • Open Source: Released under an MIT License, encouraging contributions and modifications.

zclaw stands out as an impressive example of efficient embedded software development, bringing sophisticated AI assistance to low-resource microcontrollers. Its small footprint, versatile features, and open-source nature make it a compelling solution for developers looking to explore edge AI applications.