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31 points adilhafeez | 4 comments | | HN request time: 0s | source

Hi HN! My name is Adil Hafeez, and I am the Co-Founder at Katanemo and the lead developer behind Arch - an open source project for developers to build faster, generative AI apps. Previously I worked on Envoy at Lyft.

Engineered with purpose-built LLMs, Arch handles the critical but undifferentiated tasks related to the handling and processing of prompts, including detecting and rejecting jailbreak attempts, intelligently calling “backend” APIs to fulfill the user’s request represented in a prompt, routing to and offering disaster recovery between upstream LLMs, and managing the observability of prompts and LLM interactions in a centralized way - all outside business logic.

Here are some additional key details of the project,

* Built on top of Envoy and is written in rust. It runs alongside application servers, and uses Envoy's proven HTTP management and scalability features to handle traffic related to prompts and LLMs.

* Function calling for fast agentic and RAG apps. Engineered with purpose-built fast LLMs to handle fast, cost-effective, and accurate prompt-based tasks like function/API calling, and parameter extraction from prompts.

* Prompt guardrails to prevent jailbreak attempts and ensure safe user interactions without writing a single line of code.

* Manages LLM calls, offering smart retries, automatic cutover, and resilient upstream connections for continuous availability.

* Uses the W3C Trace Context standard to enable complete request tracing across applications, ensuring compatibility with observability tools, and provides metrics to monitor latency, token usage, and error rates, helping optimize AI application performance.

This is our first release, and would love to build alongside the community. We are just getting started on reinventing what we could do at the networking layer for prompts.

Do check it out on GitHub at https://github.com/katanemo/arch/.

Please leave a comment or feedback here and I will be happy to answer!

1. lionkor ◴[] No.41851210[source]
Hi, I'm curious how preventing jailbreaks protects the user?

> Prompt guardrails to prevent jailbreak attempts and ensure safe user interactions [...]

replies(3): >>41851500 #>>41851564 #>>41854302 #
2. adilhafeez ◴[] No.41851500[source]
Jailbreak ensures a smooth developer experience by controlling what traffic from user make its way to the model. With jailbreak (and other guardrails soon to be added) developers can short-circuit response and with observability developers can get insights on how users are interacting with their APIs.
3. sparacha ◴[] No.41851564[source]
That's a fair point - technically it protects the application from malicious attempts to subvert the desired LLM experience. The more specific language (and I think we could do better here) would be that Arch ensures users remain within the bounds of an intended LLM experience. That at least was the intention behind "ensure safe user interactions"...
4. harlanlewis ◴[] No.41854302[source]
Untrusted inputs to systems with agency or access to privileged data. Here’s a data exfiltration example in Google AI Studio:

https://x.com/wunderwuzzi23/status/1821210923157098919