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!
