Skip to main content

​
Integration Models Overview

PraisonAI recipes can be integrated into your applications using six distinct models. Each model has specific use cases, trade-offs, and implementation patterns.

​
Quick Comparison

ModelLatencyBest For
Embedded SDKLowestPython apps, notebooks
CLI InvocationLowScripts, CI/CD
Plugin ModeLowIDE/CMS extensions
Local HTTP SidecarMediumMicroservices, polyglot
Remote Managed RunnerMediumMulti-tenant, cloud
Event-DrivenVariableAsync workflows

​
Decision Guide

​
Choose Your Integration Model

Model 1: Embedded SDK

Lowest latency - Direct Python integration with zero network overhead. Best for Python applications and notebooks.

Model 2: CLI Invocation

Language-agnostic - Invoke recipes from any language via subprocess. Perfect for scripts and CI/CD pipelines.

Model 3: Local HTTP Sidecar

Polyglot friendly - HTTP API running locally. Ideal for microservices and non-Python applications.

Model 4: Remote Managed Runner

Production-ready - Centralized, authenticated recipe execution. Built for multi-tenant cloud deployments.

Model 5: Event-Driven

Async at scale - Queue-based invocation for high-volume batch processing and decoupled architectures.

Model 6: Plugin Mode

Native UX - Embed recipes into IDEs, CMS platforms, and chat applications.

​
Feature Matrix

FeatureSDKCLISidecarRemoteEventPlugin
Streaming✅✅✅✅❌✅
Multi-tenant❌❌❌✅✅❌
Auth built-in❌❌✅✅✅❌
Async native✅❌✅✅✅✅
Process isolation❌✅✅✅✅✅
Hot reload❌✅✅✅❌❌

​
Quick Start

from praisonai import recipe

result = recipe.run("my-recipe", input={"query": "Hello"})
print(result.output)

​
Next Steps

  1. Choose your integration model based on the decision guide above
  2. Follow the dedicated page for step-by-step setup
  3. Review Personas for role-specific guidance
  4. Explore Use Cases for implementation patterns