| Crates.io | ghostai |
| lib.rs | ghostai |
| version | 0.2.2-beta |
| created_at | 2025-04-26 18:00:14.582144+00 |
| updated_at | 2025-05-20 10:47:45.03343+00 |
| description | Your second brain at the computer. |
| homepage | |
| repository | https://github.com/yazaldefilimone/ghost.ai |
| max_upload_size | |
| id | 1650457 |
| size | 245,503 |
A second brain for your computer: vision, hear, memory, smart writing — all locally by default.
Ghost is a lightweight, local-first second brain that helps you remember everything you see and do on your computer. It captures screen frames, extracts visible text using OCR, stores the information, and lets you recall, autocomplete, or chat based on your visual memory.
Ghost supports three main flows:
Ghost is modular and highly configurable — each memory stage (vision, chat, autocomplete, hearing) can be powered by different models, locally or remotely.
Ghost is blindly influenced by Guillermo Rauch's vision, but built with full offline privacy in mind.
hear) is under active development and will arrive in future versions..config/ghost/.data.db
# Install Rust if you haven't already.
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
You can install Ghost via Cargo:
cargo install ghostai
ghost init
Ghost uses Ollama by default to run local LLMs. Make sure Ollama is installed and running.
Default model:
ollama run mistral:7b-instruct
Model selection is fully customizable per stage.
Allow your terminal or IDE to:
(System Preferences → Privacy & Security → Screen Recording)
ghost run
Ghost will start capturing frames, extracting text, building memory, and listening for input.
chat >> What was the article about the best technologies humans have invented?
Ghost acts like a private GPT that only knows what you have personally seen — not generic internet data.
Ghost is deeply customizable.
Example configuration (.config/ghost/settings.toml):
name = "Your Name"
language = "en"
[embed]
provider = "ollama"
model = "nomic-embed-text"
[autocomplete]
provider = "ollama"
model = "mistral:7b-instruct"
stream = true
skip_app = ["code", "zed"]
discard_behavior = "full"
[chat]
enabled = true
provider = "ollama"
model = "mistral:7b-instruct"
[hear]
enabled = false
model = "whisper" # or elevenlabs
[vision]
skip_app = ["code", "zed"]
skip_patterns = []
security_skip = true
[shortcuts.macos]
look = "cmd+c"
autocomplete = "cmd+a"
hear = "cmd+h"
Each stage (embedding, autocomplete, chat, hearing) can use a different model from different providers.
Supported providers: anthropic, google, openai, groq, ollama, together, elevenlabs
It is strongly recommended to use an instruction-tuned model (like mistral-instruct or gpt-3.5-turbo) for better sentence completions.
Avoid using "reasoning" or "chat" oriented models for autocomplete tasks.
Skip App: skip specified apps (VSCode, Zed, etc.).
Skip Patterns: filters to avoid capturing sensitive content.
Security Skip: extra layer to automatically ignore known private windows.
Autocomplete discard behavior:
full: one backspace discards the entire suggestion.word: each backspace deletes one word at a time.Shortcuts: customizable hotkeys (macOS only for now).