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Open Source Personal AI is the Path Forward

· 2 min read
Sam Johnston
Product Manager

I absolutely agree Open Source AI is the Path Forward, and while Meta's Mark Zuckerberg raises pertinent points on geopolitics and business opportunities, I'm more about making it personal with personal AI, which we've been calling "pAI" at non-profit Kwaai and in the open source Personal Artificial Intelligence Operating System (pAI-OS).

Like with the widespread adoption of computers starting half a century ago, Artificial Intelligence can empower individuals in their daily tasks, encourage lifelong learning, and enhance personal growth. It can also replace them, leaving many without work or a sense of purpose. Like computers, it will likely do both depending on who you are, but we can all agree we're better off for them.

Open source became popular around that time as a way to protect freedoms and prevent vendor lock-in, and today most Internet infrastructure runs on open source products like Linux (pAI-OS aims to be "The Linux of Artificial Intelligence"). The evolutionary shift from products to services that we called "Cloud Computing" meant users weren't running software locally any more, rather on millions of servers running Linux — in some ways cloud is "just someone else's computer".

With the advent of personal AI this paradigm is problematic, because the power of the AI is proportional to the amount of data it has available. Rather than use the right tool for the job, people will be forced to "pick a pocket" and store their data in proximity to their personal AI of choice, be it Apple's Siri, Microsoft's Cortana, or Google's Assistant. With Open Source AI and models like Llama 3.1 powering projects like pAI-OS, consumers will retain the choice to store and exploit their most valuable asset where they want, once again protecting important freedoms.

That's why I'm devoting so much time to its success, as I did 15 years ago with cloud, while studying for an MSc in AI at Georgia Tech. AI is the future, but I prefer a future where users are in control of their data and destiny, not one where we become digital serfs to technocratic overlords.

Code signing to prevent supply chain vulnerabilities

· 5 min read
Sam Johnston
Product Manager

In our ongoing efforts to raise the bar and improve the security and integrity of our codebase, we've implemented a robust system of GPG signature verification and code ownership all the way back to the repo root/initial commit. This post will explain the key components of our approach and its benefits and implications.

Contributors can fork the pAI-OS/paios repo (git clone https://github.com/pAI-OS/paios.git) and create pull requests (with GPG signed commits!) from there, and more active active contributors can work on feature-* branches in the paios repo itself where it is more readily accessible to others. The first time we accept a pull request we'll need to do a quick video keysigning ceremony with a maintainer (currently myself and Karsten Wade) where you show ID and confirm compliance with CONTRIBUTING.md before we sign your key and have you publish it on a GPG keyserver (i.e., keyserver.ubuntu.com with gpg --keyserver keyserver.ubuntu.com --send-keys <0xabcd1234>).

This was inspired by:

  • Debian: My work as a Debian developer (where new maintainers need to have their key signed by at least two existing developers before they can be added to the Debian keyring)
  • CAcert: My work as Organisation Assurance Officer for community certification authority CAcert
  • Apple: Apple's recent pioneering work on Private Cloud Compute (some 15 years into the transition from products to services that we call "cloud").
  • Qubes OS: Security operating system Qubes OS' own code signing policy requiring that "All contributions to the Qubes OS source code must be cryptographically signed by the author’s PGP key."

Key Components

  1. CODEOWNERS File: The CODEOWNERS file defines who is responsible for different parts of the repository. This ensures that the right people are automatically requested for review when changes are requested.
  2. GPG Signature Verification Workflow: We've set up a GitHub Actions workflow (verify-gpg-signatures.yml) that runs on pull requests, pushes to the main branch, and can be manually triggered. This workflow sets up the GPG environment and runs our custom verification script.
  3. GPG Signature Verification Script: Our custom verification script (verify-gpg-signatures.sh) is the heart of our verification process. It imports trusted GPG keys from the gpg-keys, verifies commit signatures, checks if signing keys are trusted or signed by trusted keys, and reports any issues with commit signatures.

Benefits of This Approach

  1. Integrity: By requiring GPG signatures on all commits, we ensure - and you can verify - that all code changes are coming from verified contributors.
  2. Accountability: The CODEOWNERS file clearly defines who is responsible for different parts of the codebase. It currently contains myself and Karsten Wade, a fellow long-time open source community member.
  3. Automation: The GitHub Actions workflow automatically checks signatures on new pull requests and pushes.
  4. Flexibility: The workflow can be manually triggered with a flag to check all commits in the repository.
  5. Transparency: Any issues with signatures are clearly reported in the GitHub interface.

Implications for Developers

We've recently migrated from SSH to GPG signatures for all commits in our history. As a result, anyone who cloned the pAI-OS/paios repo before July 15, 2024, will need to re-clone it. This is because the commit hashes, which are generated from the contents of the commit itself, have necessarily changed due to the rewriting of history to accommodate the new GPG signatures:

> git log --reverse --pretty=raw
commit adfcc54c511955d56576fa903eb07605e3c32c1a
tree fb3a2b360e4cb9ea6100006d56ca0bab863c520a
author Sam Johnston <[email protected]> 1712456042 -0700
committer Sam Johnston <[email protected]> 1712456042 -0700
gpgsig -----BEGIN PGP SIGNATURE-----

iHUEABYKAB0WIQQCg6PrpLqfl0rHX+kYjl3CelT6JQUCZpVWaAAKCRAYjl3CelT6
JVHUAP0QTwdTC6yWA+yYirJ2GrYqB4J+rOiJ8EvZuv7DIYmnXwEAnHHn0/pXT/Ld
mcCGKcFfpONKAoIe+wnYgMCsIRrmaAQ=
=9KWo
-----END PGP SIGNATURE-----

Initial commit

Process

The following command was used to rebase the repository to add GPG signatures to all commits, using the 'exec' option to run a script for each commit that does a git commit with the amend and no-edit flags as well as the -S flag to sign the commit with our GPG key (and --allow-empty and --empty=keep on the parent command to preserve a few empty commits in the log):

git rebase --empty=keep -X theirs --committer-date-is-author-date --exec '../sign-commit.sh' -i --root

The git command was originally inline but it wasn't picking up the commit date from the environment variables so it looked like months of work was done in seconds; the --committer-date-is-author-date would normally have done this but not when you specify your own command wtih --exec.

By using interactive (-i) mode I was able to change pick to drop for the two commits that made it in unsigned early on (and remove the following exec lines). Telling the rebase -X theirs has it automatically accept the incoming change rather than drop to merge conflict resolution.

#!/bin/sh

COMMIT_DATE=$(git show -s --format=%ci HEAD)
AUTHOR_DATE=$(git show -s --format=%ai HEAD)

GIT_COMMITTER_DATE="$COMMIT_DATE" GIT_AUTHOR_DATE="$AUTHOR_DATE" git commit --amend --no-edit --allow-empty -S

I now know more about git than I ever wanted to know, but not enough to be confident this was the best way to achieve the project's goals. Hopefully by sharing it I can save others hours of yak shaving.

Conclusion

By implementing these security measures, we're taking significant steps to ensure the integrity and trustworthiness of our codebase. Fortunately it was early enough on in the project's life to be able to do with minimal disruption, though obviously it would have been better to start from the initial commit. While the new process may require some adjustment for contributors, the long-term benefits in terms of security and accountability are well worth the effort.

We encourage all contributors to set up GPG signing (not SSH!) for their commits and to familiarize themselves with our new verification process. Together, we can maintain a secure and trustworthy open-source project while raising the bar for the industry in light of increasingly frequent supply chain attacks.

Hardening the pAI-OS API

· 4 min read
Sam Johnston
Product Manager

One of the key design decisions we made in developing pAI-OS was that the frontend/s (by default, a single page web application written in React) and backend (a Python Flask app) are separate services. This separation of concerns allows us to have a more fine-grained control over the API security, and to be able to use the tools and techniques we already know best for each layer. By being strict about not using private APIs, you can be sure that all the features and functions you see in any interface are available to all of them.

In the ever-evolving landscape of API security, ensuring that all requests and responses are compliant with predefined specifications is increasingly important in a multi-layer defense strategy. At pAI-OS, we have adopted OpenAPI and "pattern" regexps with Connexion to achieve this goal without having to rely on third-party services (though you can upload your OpenAPI spec to providers like Cloudflare who will enforce it before requests even reach your server!).

Why OpenAPI and Connexion?

OpenAPI is a powerful specification for defining APIs, allowing us to describe our API endpoints, request/response formats, and validation rules in a standardized way. Connexion is a Python framework that automates the validation of requests and responses against an OpenAPI specification. By integrating these tools, we ensure that our API adheres to strict validation rules, reducing the risk of security vulnerabilities and improving overall reliability. This can exact a small performance penalty, but given this is an administrative interface rather than one that's invovled in user requests, the trade-off is worth it.

Using "pattern" Regular Expressions for Validation

One of the key features we leverage in our OpenAPI spec is the use of "pattern" regexps. These regular expressions allow us to define precise validation rules for various parts of our API, such as path parameters, query parameters, and request bodies. By specifying patterns, we can enforce constraints on the data being sent to and from our API, ensuring it meets our security and format requirements.

Examples

Filenames

pAI-OS is designed to be cross platform, but different platforms accept different characters in filenames (and use different path formats too, which is why use pathlib.Path internally). We also use the following regexp to ensure that filenames are valid on macOS, Windows, and Linux:

fileName:
type: string
description: A filename that is valid on macOS, Windows, and Linux
example: Mistral-7B-Instruct-v0.3-Q8_0.gguf
pattern: '^[^<>:;,?"*|/]+$'

UUIDs

For scalability and security, we don't let users define the id of objects they create (via POST) or update (via PUT). Instead, we generate UUIDs for them. This way we can ensure that the id of an object is a valid UUID, that it follows the correct format, and that it's unique even if it's generated by one of several servers.

Rather than hoping users only ever send us valid UUIDs, we can be sure that they will by using the pattern regexp:

uuid4:
type: string
format: uuid
example: 7bea4732-214f-40e7-9161-4e7241a2b97e
pattern: ^[0-9a-f]{8}-[0-9a-f]{4}-4[0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$

Emails

For a more complex example one need look no further than an almost 100% RFC-compliant email regex:

email:
type: string
format: email
example: [email protected]
pattern: (?:[a-z0-9!#$%&'*+/=?^_`{|}~-]+(?:\.[a-z0-9!#$%&'*+/=?^_`{|}~-]+)_|"(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21\x23-\x5b\x5d-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])_")@(?:(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?|\[(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?|[a-z0-9-]\*[a-z0-9]:(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21-\x5a\x53-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])+)\])

Path Traversal Example

For example, here Connexion has intercepted an attempt at executing a path traversal vulnerability before reaching the rest of our code:

Path Traversal Example

Conclusion

In summary, by using OpenAPI and Connexion, we can ensure that our API is secure and compliant with the latest standards. This approach allows us to have a more fine-grained control over the API security, albeit with a small performance penalty. By being strict about not using private APIs, you can be sure that all the features and functions you see in any interface are available to all of them.

Developers! Developers! Developers!

· One min read
Sam Johnston
Product Manager

If you've been waiting to kick the tires then now's a good time to git clone https://github.com/pAI-OS/paios, run python -m paios (after running python3 paios/scripts/setup_environment.py the first time and activating the virtual environment every time with source paios/.venv/bin/activate), before visiting http://localhost:3080

One of the biggest changes is that it's now a single server (instead of one for frontend and one for backend) all served out of that same URL (with the API at /api/v1 and its docs at /api/v1/ui). I've also eliminated the Node.js dependency for early adopters and users by having the frontend built for the canary branch by GitHub Actions on every commit to main. You do still need to have Python installed, but it comes with Linux there are installers for macOS and Windows (you don't need to install Docker or anything like that).

I've also been migrating to a modern asynchronous architecture so we don't have to look back once we start building on it. I'm in the process of migrating the abilities infrastructure in backend/api.py to backend\managers\AbilitiesManager.py (and DownloadsManager.py) so you can't download and run models for the moment, but I've broken the back of it now.

pAI-OS Development Update (May 2024)

· 2 min read
Sam Johnston
Product Manager

I started working on bringing the front- and backend into the same server environment and was initially going to find a cross-platform way to deploy nginx as a reverse proxy for various pAI-OS components, but the result was likely to be brittle. I then moved on to having a single server instance that also serves the frontend/dist files as static files, meaning you can start one server and immediately access pAI-OS.

Uvicorn (https://www.uvicorn.org/) is an ASGI (asynchronous equivalent of WSGI) web server implementation for Python that happens to be the one Connexion uses. Connexion, which reads the pAI-OS OpenAPI spec and automatically binds URLs to python functions, has recently had a major release that moves from synchronous (WSGI) to asynchronous (ASGI) by default (https://connexion.readthedocs.io/en/latest/v3.html) and it's as good a time as any to jump into the future.

This probably would have been unnecessary if the OS was only involving itself in configuration/deployment/etc. but as it already has awareness of assets I figured it will likely end up in the flow of user queries before long, and many of those will likely be WebSockets which are kryptonite for synchronous servers (WSGI). As such, building a common server for front- and backend has turned into a migration from WSGI to ASGI which is now nearly complete on the feature/uvicorn branch: https://github.com/pAI-OS/paios/tree/feature/uvicorn

I'd suggest holding off a few more days on testing the code on main as I'll be merging soon.

pAI-OS Early Demo

· One min read
Sam Johnston
Product Manager

Here's a quick demo of the Personal Artificial Intelligence Operating System (PAIOS) developed for Kwaai, a California 501(c)3 nonprofit organisation.

pAI-OS, like Linux, allows users to bring together the best free and open-source software to securely use artificial intelligence agents with direct access to all of their own data.

Kwaai's mission is to empower users to retain and own their personal data and knowledge model, enhancing their digital abilities and competitiveness in the modern economy.