From b8d2756ff7cc41e7424027f4e3a142be7f413d82 Mon Sep 17 00:00:00 2001 From: Salman Paracha Date: Wed, 9 Oct 2024 17:46:55 -0700 Subject: [PATCH] updated README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 2309cbdb..fa6ea02c 100644 --- a/README.md +++ b/README.md @@ -12,8 +12,8 @@ Arch is an intelligent [Layer 7](https://www.cloudflare.com/learning/ddos/what-i **Core Features**: - Built on [Envoy](https://envoyproxy.io): Arch runs alongside application servers, and builds on top of Envoy's proven HTTP management and scalability features to handle ingress and egreess traffic realted to prompts and LLMs - - Enables fast Agentic and RAG apps. Engineered with purpose-built [(fast) LLMs](https://huggingface.co/collections/katanemo/arch-function-66f209a693ea8df14317ad68) to handle fast, cost-effective, and accurate prompt-based tasks like function/API calling, and parameter extraction from prompts. - - Prompt [Guardrails](https://huggingface.co/collections/katanemo/arch-guard-6702bdc08b889e4bce8f446d): Arch centralizes prompt guardrails to prevent jailbreak attempts and ensure safe user interactions without writing a single line of code. + - Function Calling for fast Agentic and RAG apps. Engineered with purpose-built [LLMs](https://huggingface.co/collections/katanemo/arch-function-66f209a693ea8df14317ad68) to handle fast, cost-effective, and accurate prompt-based tasks like function/API calling, and parameter extraction from prompts. + - Prompt [Guard](https://huggingface.co/collections/katanemo/arch-guard-6702bdc08b889e4bce8f446d): Arch centralizes prompt guardrails to prevent jailbreak attempts and ensure safe user interactions without writing a single line of code. - Traffic Management: Arch manages LLM calls, offering smart retries, automatic cutover, and resilient upstream connections for continuous availability. - Standards-based Observability: Arch 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.