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README.md
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README.md
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<div align="center">
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<img src="docs/source/_static/img/arch-logo.png" alt="Arch Logo" width="75%" heigh=auto>
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<img src="docs/source/_static/img/arch-logp.png" alt="Arch Logo" width="75%" heigh=auto>
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</div>
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<div align="center">
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_The AI-native proxy server for agentic applications._<br><br>
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Arch handles the **pesky**, low-level details like routing user prompts to the right agents or specialized Model Context Protocol (MCP) tools, providing unified access and observability to large language models (LLMs), and quickly clarifying vague user inputs. With Arch, you build faster by focusing on the high-level logic of agents.
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_The AI-native proxy server and the universal data plane for AI agents._<br><br>
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Arch implements **pesky**, low-level infrastructure patterns like quickly clarifying vague user inputs, routing prompts to the right agents or specialized Model Context Protocol (MCP) tools, and providing unified access and observability to large language models (LLMs) - all without locking you into a framework.. With Arch, you build faster by focusing on the high-level logic of your agents.
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[Quickstart](#Quickstart) •
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[Demos](#Demos) •
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# Overview
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<a href="https://www.producthunt.com/posts/arch-3?embed=true&utm_source=badge-top-post-badge&utm_medium=badge&utm_souce=badge-arch-3" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/top-post-badge.svg?post_id=565761&theme=dark&period=daily&t=1742359429995" alt="Arch - Build fast, hyper-personalized agents with intelligent infra | Product Hunt" style="width: 188px; height: 41px;" width="188" height="41" /></a>
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Past the thrill of an AI demo, have you found yourself hitting these walls? You know, the all too familiar ones:
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AI demos are easy to build. But past the thrill of a quick hack, you are left building, maintaining and scaling low-level plumbing code for agents that slows down AI innovation. For example:
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- You go from one BIG prompt to specialized prompts, but get stuck building **routing and handoff** code?
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- You want use new LLMs, but struggle to **quickly and safely add LLMs** without writing integration code?
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- You're bogged down with prompt engineering just to **clarify user intent and validate inputs** effectively?
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- You're wasting cycles choosing and integrating code for **observability** instead of it happening transparently?
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- You want to build specialized agents, but get stuck building **routing and handoff** code.
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- You want use new LLMs, but struggle to **quickly and safely add LLMs** without writing integration code.
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- You're bogged down with prompt engineering work to **clarify user intent and validate inputs**.
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- You're wasting cycles choosing and integrating code for **observability** instead of it happening transparently.
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And you think to yourself, can't I move faster by focusing on higher-level objectives in a language/framework agnostic way? Well, you can! **Arch Gateway** was built by the contributors of [Envoy Proxy](https://www.envoyproxy.io/) with the belief that:
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With Arch, you can move faster by focusing on higher-level objectives in a language and framework agnostic way. **Arch** was built by the contributors of [Envoy Proxy](https://www.envoyproxy.io/) with the belief that:
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>Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests including secure handling, intelligent routing, robust observability, and integration with backend (API) systems to improve speed and accuracy for common agentic scenarios – all outside core application logic.*
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Intro to Arch
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=============
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AI demos are easy to build. But past the thrill of a quick hack, you are left building, maintaining and scaling low-level plumbing code for agents that slows down AI innovation.
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For example:
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Arch is an intelligent proxy server designed agentic applications. **Move faster** by letting Arch handle the **pesky heavy lifting** in building agents:
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fast input clarification, agent routing, seamless integration of prompts with tools for common tasks, and unified access and observability of LLMs.
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- You want to build specialized agents, but get stuck writing **routing and handoff** code.
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- You bogged down with prompt engineering work to **clarify user intent and validate inputs**.
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- You want to **quickly and safely use new LLMs** but get stuck writing integration code.
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- You waste cycles writing and maintaining **observability** code, when it can be transparent.
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- You want to **apply guardrails**, but have to write custom code for each prompt and LLM.
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Past the thrill of an AI demo, have you found yourself hitting these walls? You know, the all too familiar ones:
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- You break a prompt into specialized ones, but **get stuck writing routing** and handoff logic?
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- You want use new LLMs, but **struggle to quickly add LLMs** without writing integration logic?
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- You're **trapped in tedious prompting work** to clarify inputs and user intents?
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- You're **wasting cycles** choosing and integrating **code for observability** instead of it just happening transparently?
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And you think to yourself, can't I move faster by focusing on higher-level objectives in a language and framework agnostic way? Well, you can!
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Arch is designed to solve these problems by providing a unified, out-of-process architecture that integrates with your existing application stack, enabling you to focus on building high-level features rather than plumbing — all without locking you into a framework.
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.. figure:: /_static/img/arch_network_diagram_high_level.png
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:width: 100%
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@ -22,7 +20,7 @@ And you think to yourself, can't I move faster by focusing on higher-level objec
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High-level network flow of where Arch Gateway sits in your agentic stack. Designed for both ingress and egress prompt traffic.
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**Arch Gateway was built by the contributors of Envoy Proxy with the belief that:**
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Arch is an AI-native proxy server and the universal data plane for AI built by the contributors of Envoy Proxy with the belief that:
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*Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests
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including secure handling, intelligent routing, robust observability, and integration with backend (API)
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@ -41,8 +39,8 @@ This gives Arch several advantages:
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* Arch can be deployed and upgraded quickly across your infrastructure transparently without the horrid pain of deploying library upgrades in your applications.
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**Engineered with Fast LLMs:** Arch is engineered with specialized small LLMs that are designed for fast, cost-effective and accurate handling of prompts.
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These LLMs are designed to be best-in-class for critical prompt-related tasks like:
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**Engineered with Fast Task-Specific LLMs (TLMs):** Arch is engineered with specialized LLMs that are designed for the fast, cost-effective and accurate handling of prompts.
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These LLMs are designed to be best-in-class for critical tasks like:
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* **Function Calling:** Arch helps you easily personalize your applications by enabling calls to application-specific (API) operations via user prompts.
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This involves any predefined functions or APIs you want to expose to users to perform tasks, gather information, or manipulate data.
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Overview
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============
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Welcome to Arch, The intelligent (edge and LLM) proxy server for agentic applications.
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`Arch <https://github.com/katanemo/arch>`_ is an AI-native proxy server and the universal data plane for AI - one that is natively designed to handle and process AI prompts, not just network traffic.
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Built by contributors to the widely adopted `Envoy Proxy <https://www.envoyproxy.io/>`_, Arch helps you move faster by handling the pesky heavy lifting in AI agent development—fast input clarification, intelligent agent routing, seamless prompt-to-tool integration, and unified LLM access and observability—all without locking you into a framework.
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Move **faster** by letting Arch handle the pesky heavy lifting in building agents: **fast input clarification**, **agent routing**,
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seamless integration of prompts with **tools for common tasks**, and **unified access and observability of LLMs**.
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In this documentation, you will learn how to quickly set up Arch to trigger API calls via prompts, apply prompt guardrails without writing any application-level logic,
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simplify the interaction with upstream LLMs, and improve observability all while simplifying your application development process.
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@ -9,14 +9,14 @@ Welcome to Arch!
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<div style="text-align: center; font-size: 1.25rem;">
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<br>
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<p>Build <strong>fast</strong>, <strong>observable</strong>, and <strong>personalized</strong> GenAI apps</p>
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<p>Build <strong>fast</strong>, <strong>secure</strong>, and <strong>highly personalized</strong> AI.</p>
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</div>
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<a href="https://www.producthunt.com/posts/arch-3?embed=true&utm_source=badge-top-post-badge&utm_medium=badge&utm_souce=badge-arch-3" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/top-post-badge.svg?post_id=565761&theme=dark&period=daily&t=1742433071161" alt="Arch - Build fast, hyper-personalized agents with intelligent infra | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
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`Arch <https://github.com/katanemo/arch>`_ is an intelligent (edge and LLM) proxy, exclusively designed for prompts and agents - and built by the contributors of the widely adopted and loved `Envoy <https://www.envoyproxy.io/>`_ ).
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`Arch <https://github.com/katanemo/arch>`_ is an AI-native proxy server and the universal data plane for AI - one that is natively designed to handle and process AI prompts, not just network traffic.
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**Move faster** by letting Arch handle the **pesky heavy lifting** in building agents: fast input clarification, agent routing, seamless integration of prompts with tools for common tasks, and unified access and observability of LLMs - all outside business logic.
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Built by contributors to the widely adopted `Envoy Proxy <https://www.envoyproxy.io/>`_, Arch helps you move faster by handling the pesky heavy lifting in AI agent development—fast input clarification, intelligent agent routing, seamless prompt-to-tool integration, and unified LLM access and observability—all without locking you into a framework.
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.. tab-set::
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