Sre

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SRE (SmythOS Runtime Environment) is an open-source, cloud-native runtime for agentic AI that allows developers to build, run, and manage intelligent agents. It provides OS-level abstractions for AI resources with a unified API.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is sre?

The SmythOS Runtime Environment (SRE) is an open-source, cloud-native runtime and SDK specifically designed for production AI agents. It offers OS-level abstractions for various AI resources such as LLMs, vector databases, storage, and caching, all accessible through a unified API. This allows developers to write agent logic once and scale it across local, cloud, and edge environments without changing their business logic. SRE emphasizes built-in security, observability, and includes over 40 production-ready components. It provides a robust and scalable foundation for agent orchestration and lifecycle management, making it easier to ship production-ready AI agents.

Best used for

Ideal for developers who need to build, run, and manage intelligent agents across local, cloud, and edge environments, and integrate various AI resources. Especially valuable for creating production-ready AI agents with built-in security, modularity, and a unified API for consistent resource management.

Common actions

build AI agents

manage AI agents

orchestrate AI agents

scale AI agents

integrate AI resources

open-sourceworkflowscollaborationautomated workflowlow-code/no-code"AI Agents"github copilotdeepfakeface swapping

Capabilities

Key features

Unified API for AI resources
Modular architecture
Built-in security
Agent orchestration
40+ production-ready components
SDK and CLI included

Target Audience

developer

Integrations

openaianthropicgoogle-cloudawspineconemilvusredishashicorp-vault

Pricing & Plans

Open Source

Free

FAQs

What types of AI resources does SRE abstract?

SRE provides OS-level abstractions for various AI resources including Large Language Models (LLMs) like OpenAI and Anthropic, vector databases such as Pinecone and Milvus, storage solutions like S3 and Google Cloud, and caching mechanisms like Redis. This ensures a unified API across different providers.

How does SRE ensure security for AI agents?

Security is a core tenant of SRE, featuring a built-in Candidate/ACL system. This system ensures that every operation requires proper authorization, allowing AI agents to access only the resources they are explicitly permitted to use, enhancing overall system security.

Can I use SRE for both development and production environments?

Yes, SRE is designed to scale from development to production. Your business logic remains identical, and you can seamlessly swap between different connectors (e.g., RAM cache for dev, Redis for prod) without changing your agent's core code, making it highly flexible and production-ready.

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Coding & Development › DevOps & Infrastructure Coding & Development › Open Source & Models

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