https://github.com/emretheus/inclave
Local-first AI assistant for macOS — chat with your PDFs, spreadsheets, CSVs and code using a local LLM via Ollama. Model-generated Python runs in a Seatbelt sandbox with no network. No cloud, no telemetry, no API keys.
https://github.com/emretheus/inclave
ai-assistant chatbot cli llm local-first local-llm macos offline-ai ollama pdf-chat privacy python rag sandbox seatbelt
Last synced: about 1 month ago
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Local-first AI assistant for macOS — chat with your PDFs, spreadsheets, CSVs and code using a local LLM via Ollama. Model-generated Python runs in a Seatbelt sandbox with no network. No cloud, no telemetry, no API keys.
- Host: GitHub
- URL: https://github.com/emretheus/inclave
- Owner: emretheus
- License: apache-2.0
- Created: 2026-02-18T15:17:14.000Z (4 months ago)
- Default Branch: master
- Last Pushed: 2026-05-11T15:33:39.000Z (about 2 months ago)
- Last Synced: 2026-05-11T17:29:59.745Z (about 2 months ago)
- Topics: ai-assistant, chatbot, cli, llm, local-first, local-llm, macos, offline-ai, ollama, pdf-chat, privacy, python, rag, sandbox, seatbelt
- Language: Python
- Homepage: https://github.com/emretheus/inclave
- Size: 3.48 MB
- Stars: 2
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Notice: NOTICE
Awesome Lists containing this project
README
# InClave — your local AI assistant, in one CLI
> A **local-first, privacy-first AI assistant** for macOS. Talk to your PDFs,
> spreadsheets, CSVs, and code with a **local LLM via Ollama** — and let the
> model run Python code in a **Seatbelt sandbox** with no network access.
> No cloud, no telemetry, no API keys, no data leaves your machine.
[](https://github.com/emretheus/inclave/actions/workflows/ci.yml)
[](LICENSE)
[](https://www.python.org/downloads/)
[]()
---
## Install
```bash
curl -fsSL https://raw.githubusercontent.com/emretheus/inclave/master/install.sh | sh
```
Then just:
```bash
inclave
```
That's it. On first run, InClave starts the Ollama daemon for you, lets you
pick a model from a curated list (`llama3.2`, `llama3.1:8b`,
`qwen2.5-coder:7b`, or your own), pulls it, and drops you into a chat.
> **Requires:** macOS, Python 3.12+. Ollama is auto-detected; if missing the
> CLI tells you to `brew install ollama`.
## What it does
- **Local LLM via [Ollama](https://ollama.com/)** — every prompt and response
stays on `127.0.0.1`. No API keys, no rate limits, no usage caps.
- **Native macOS sandbox** ([Seatbelt](https://en.wikipedia.org/wiki/Seatbelt_(software)))
— model-generated Python runs in a jail with **no network**, locked to a
single read/write directory, with CPU/memory/wall-clock limits.
- **A workspace of your files** the model can read — PDF, Excel, CSV, Markdown,
text, and source code. Originals are never modified; only content-hashed
copies live under `~/.inclave/`.
- **Drop a file, ask a question.** Drag any file from Finder onto the chat
prompt — it's attached automatically. Add a question on the same line to
send everything in one shot.
## Quick demo
````text
$ inclave
● inclave qwen2.5-coder:7b workspace: 0 files workdir: ~/Downloads
› ~/Downloads/mrr_2026.csv print total mrr_usd growth in %
+ mrr_2026.csv (added)
```python
import pandas as pd
df = pd.read_csv("mrr_2026.csv")
total = (df["mrr_usd"].iloc[-1] - df["mrr_usd"].iloc[0]) / df["mrr_usd"].iloc[0] * 100
print(f"Total MRR_USD growth: {total:.2f}%")
```
╭──────────── stdout ────────────╮
│ Total MRR_USD growth: 96.06%
╰────────────────────────────────╯
ran · exit 0 · 1.2s
MRR_USD grew by approximately 96 % from September to April.
````
The python block ran **automatically** in a temporary sandbox: no network,
no escape to `~/.ssh`, output fed back to the model so the summary is
grounded in real stdout — not a prediction.
## Why InClave?
Cloud AI wants your files. Letting an LLM run code on your laptop is
convenient *and* dangerous. InClave keeps the model local and sandboxes
the execution — an **offline AI code interpreter** that respects your
filesystem.
## Inside the chat
- **Python blocks auto-run** in the sandbox; the model reads its own
stdout and writes the follow-up.
- **Drop a path** from Finder, with or without a question on the same line.
- `/help` `/run` `/setup` `/model` `/save` `/files` `/clear` `/reset` —
see `/help` for full descriptions.
Sessions autosave after every reply. Resume the last with
`inclave chat --resume`; `inclave sessions list` shows everything saved.
## Supported file types
| Type | Extensions | Notes |
|--------|---------------------------------------------------|--------------------------------------|
| Text | `.txt` `.md` | Read as-is |
| Tables | `.csv` | First 1,000 rows as markdown |
| Excel | `.xlsx` `.xls` | Each sheet as markdown |
| PDF | `.pdf` | Text via `pypdf` |
| Code | `.py .js .ts .go .rs .java .sh .sql .json .yaml`… | Fenced as source |
Limits: 5 files / 200 KB total / 100 KB per file. Excess is truncated.
## Privacy contract
- Talks only to `127.0.0.1:11434` (local Ollama). CI guard rejects any
non-localhost URL in production code.
- Sandbox profile blocks network, denies file I/O outside the run dir,
enforces CPU / memory / wall-clock rlimits.
- Workspace files live at `~/.inclave/workspaces/default/` as content-
hashed copies. `inclave files clear` or `rm -rf ~/.inclave` wipes them.
- No telemetry, no analytics, no auto-update. Logs are off by default;
`--debug` writes operational events only — **never** message content.
## Configuration
`~/.inclave/config.json` — edit by hand or with `inclave config set `:
| Key | Default | Purpose |
|------------------------|---------|---------------------------------------------|
| `default_model` | `null` | Model used when `--model` isn't passed |
| `sandbox_cpu_seconds` | `30` | CPU time limit per sandbox run |
| `sandbox_memory_mb` | `512` | Memory limit per sandbox run |
Global flags: `--debug` (operational logs only) and `--no-color`
(also via `NO_COLOR=1`).
## Status & platform
`v0.1`, macOS only — the sandbox depends on Seatbelt (`sandbox-exec`).
Core flow is stable; APIs may still change.
## Roadmap
- [ ] **Linux support** via [`bubblewrap`](https://github.com/containers/bubblewrap).
Same policy (no network, single read/write directory, rlimits),
different backend behind the same `inclave_sandbox.api` contract.
- [ ] **Windows support** via the WSL2 Linux backend, or — longer term —
a native sandbox using AppContainer / Job Objects. Tracking issue
welcome.
- [ ] Image attachments (drag a PNG into the prompt, send to a
vision-capable local model).
- [ ] Per-project sandbox profile overrides (allow specific paths /
domains for the rare workflow that legitimately needs them).
- [ ] Better long-context handling for big PDFs (chunking + retrieval
across pages instead of the current 100 KB truncate).
## Manual install
Don't want to pipe `curl` into `sh`?
```bash
brew install ollama && ollama serve &
git clone https://github.com/emretheus/inclave.git && cd inclave
uv tool install --from packages/cli inclave-cli
```
## Development
```bash
uv sync --all-packages --all-extras
uv run pytest # 170+ tests
uv run ruff check . && uv run ruff format --check .
uv run mypy packages shared # strict
```
A [`uv`](https://docs.astral.sh/uv/) workspace: `packages/cli` (Typer +
REPL), `packages/ollama` (inference), `packages/sandbox` (Seatbelt
executor), `shared/inclave_core` (config, sessions, logging).
## Contributing
See [CONTRIBUTING.md](CONTRIBUTING.md) — issues for non-trivial changes,
tests required, CI gates lint / format / type-check / coverage / the
no-outbound-HTTP guard.
## Authors
Built by:
- **Emre Ulgac**
- **Emre Kocyigit**
- **Ibrahim Furkan Gulcan**
See the [contributors page](https://github.com/emretheus/inclave/graphs/contributors)
for everyone who has contributed.
## License
Apache 2.0 — see [LICENSE](LICENSE) and [NOTICE](NOTICE).