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v0.5

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v0.5

Calling Model Endpoints

Introduction

What is JFrog ML?
JFrog ML Architecture

Quickstart

Installation
Getting Started
JFrog ML Examples

BUILD Models

Model Build Overview
Training Models
Testing Models
- Local Testing
- Adding Integration Tests to a Model Build
Loading Pre-built Models
Model Registry and Metadata
Advanced Build Concepts

Serve Models

Prediction Input & Output Adapters
Real-Time Deployments
Batch Deployments
Streaming Deployments
Inference Analytics
LLM Model Library

Monitor Models

Runtime Metrics
Model Monitors
Prediction Timers
Performance Monitors
Inference Distribution (Analytics)

Automate

Defining Automations
- Automating Build & Deploy
- Automating Batch Execution
Managing Automations
Tutorials
- Scheduled Training and Deployment
Github Actions
- Build & Deploy Actions
- Advanced CI/CD Patterns

Configuration

Alerts
Instance Sizes
JFrog Platform
Account Management
Secret Management
Accessing AWS Resources with IAM Role

Model EXPERIMENTation

Workspaces
- Installing Additional Software
Integrating Experiment Tracking Tools with JFrog ML

Feature Store

Feature Store Overview
Quickstart Guide
Data Sources
- Batch Data Sources
- Streaming Data Sources
Batch Feature Set
Streaming Feature Set
Feature Consumption
- Features in Inference
- Features in Training
Feature Set Alerts
Use-cases
Cross-environment Online Serving Replication

vector store

Vector Store Overview
Managing Collections
Managing Data
Vector Store API Reference

Prompt Management

Managing Prompts
AI Providers

Qwak Client

Qwak Client Examples

TROUBLESHOOTING

Performance Issues
Installation Issues
Network & Connectivity Issues

Changelog

Qwak-SDK
A Migration Guide for the new SDK - v0.5

Calling Model Endpoints

In this section, you'll learn how to effectively interact with and call real-time model endpoints using various SDKs and our REST API.

Updated 6 months ago