AfterImage Documentation

Introduction

• Overview
  • Use Cases
  • Key Features
  • Key Concepts
• QuickStart
  • Installation
  • Core Concepts
  • 1. Basic Usage
  • 2. Context-Aware Generation (RAG-like)
  • 3. Persona-Based Generation

Tutorials

• Conversation Generation
  • ConversationGenerator
  • Strategies & Callbacks
  • Complete Example
• Structured Generation
  • Concept
  • StructuredGenerator class
  • Example: Data Extraction from Documents
• Persona Generation
  • Concept
  • PersonaGenerator
  • Using Personas in Conversation
• Monitoring & Observability
  • GenerationMonitor
  • Visualization
  • Alerts
  • Internals & Extensibility (For Developers)
• OpenSimula (Simula-style data)
  • Imports
  • Generation monitoring
  • API reference
• Evaluation Framework
  • Overview
  • Metrics
  • Usage
• Advanced Configuration
  • Smart Key Management
  • Storage Backends
  • Custom Document Providers

Architecture

• Architecture & Design
  • System Overview
  • Extension Points
  • Design Patterns

Export & datasets

• Export & integration
  • Quick Start
  • Available Formats
  • Output Schemas
  • CLI Reference
  • Auto-Export After Generation
  • Training Tool Integration
  • Programmatic API
  • Design Notes
• JSONL source schema
  • Schema (EvaluatedConversationWithContext)
  • Field details
  • Notes
• Local models
  • Quick start
  • vLLM
  • Ollama
  • llama.cpp
  • Tips
• Preference (DPO) data
  • Quick start
  • How it works
  • Variation strategies
  • Output formats
  • Multi-turn preferences
  • Full generation log
  • Using with training tools
  • Python API
  • CLI reference
  • Tips

API Reference

• API Reference
  • Generators
  • Instruction Generators
  • Respondent Prompt Modifiers
  • Stopping Callbacks
  • Providers
  • Evaluators
  • Storage
  • Monitoring
  • Simula / OpenSimula
  • Base Classes
  • Types

Indices and tables

• Index

• Module Index

• Search Page