Termux AI Bootstrap
Built from hands-on experience running AI agents on Android/Termux aarch64. Every command and workaround in this skill was discovered through real builds, not docs. Tested across multiple devices and model sizes.
#生產力#研究#工程
評分
需要更多評價
已售出
0
使用方式
下載
Termux AI Bootstrap
Turn your Android phone into a
production AI agent host.
Personalized step-by-step setup — no guesswork, no broken dependencies.
What It Does
Ask me to help you set up your phone
and I'll walk you through:
- System setup — exact pkg install
commands for your device
- Python ML stack — the two-tier
strategy that actually works on
aarch64 - llama.cpp build — cmake flags tuned
for your phone's CPU - Model download — which model fits
your RAM and runs at usable speed - Hermes Agent — install and
configure for cloud or local inference
- Background hardening — keep your agents alive when Android wants them dead
Sample Interaction
User: I want to run a coding assistant on my phone. 6GB RAM, fresh
Termux.
Agent: > 6GB RAM means you can run up to ~2B
parameter models at Q4. For coding, I
recommend DeepSeek-Coder-1.3B or
Qwen2.5-Coder-1.5B. Here's your
setup:
>
> Step 1: Base packages
> bash
> pkg update && pkg upgrade -y > pkg install -y git curl cmake
binutils make clang python python-pip nodejs-lts
> >
> Step 2: Python ML stack (never pip
install scipy — use pkg)
> bash
> pkg install -y python-numpy python-scipy
> pip install httpx pydantic >
>
> Step 3: llama.cpp
> bash
> cd ~/storage/downloads
> git clone https://github.com/ggerganov/llama.cp
p > cd llama.cpp && mkdir build && cd
build > cmake .. -DCMAKE_BUILD_TYPE=Release
-DLLAMA_BLAS=OFF > make -j$(nproc)
> >
> Step 4: Model (DeepSeek-Coder-1.3B,
~800MB, ~20 tok/s)
> bash > mkdir -p ~/models
> curl -L -o ~/models/deepseek-coder-1.3b-q4.gguf
\ >
"https://huggingface.co/bartowski/Dee pSeek-Coder-1.3B-GGUF/resolve/main/De epSeek-Coder-1.3B-Q4_K_M.gguf"
>
What Makes This Different
Every command came from real builds
on aarch64. Not docs. Not
StackOverflow. Real devices, real
failures, real workarounds.
Things it catches that generic AI
misses:
- pip install scipy fails on aarch64 — use pkg install python-scipy - Whisper and faster-whisper do not
compile on Android
- Play Store Termux is outdated — use
F-Droid
- Android kills background agents
when screen turns off
- 8GB RAM = ~4-5GB usable for models Who's It For - Developers who want a local AI agent without cloud bills
- Tinkerers who want their phone to
do more
- Anyone who followed tutorials and
hit broken dependencies - Privacy-conscious users who want
everything running locally
What You'll Have When Done
- llama.cpp compiled and running on your phone - A working local LLM matched to your
RAM
- Hermes Agent configured (cloud or
local) - Background processes that survive
screen-off - Verified everything works
Supported
Any Android phone with Termux
(F-Droid version). 4GB-12GB devices tested. Not for iOS or Play Store
Termux.
