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How-To Guides provide practical, task-focused instructions for implementing specific features in your AI applications. Each guide walks you through a complete implementation with code examples and best practices.

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How These Guides Fit Together

  • Core Concepts: Understand what Freeplay features do and why they matter
  • How-To Guides (this section): Learn how to implement specific patterns step-by-step
  • Developer Resources: Reference documentation for SDKs, APIs, and integrations
  • Code Recipes: Complete, runnable code examples you can copy and adapt

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Available Guides

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Integration Patterns

Common Integration Patterns

Quick reference for multi-turn chat, tool calling, metadata, and feedback

Building Agents

Structure agent workflows with traces and multi-step reasoning

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Chat & Conversations

Multi-Turn Chat

Maintain conversation context across multiple exchanges

Tool Calls

Implement function calling with OpenAI, Anthropic, and other providers

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Advanced Topics

Multimodal Data

Work with images, audio, and other non-text content

Aligning LLM Judges

Create and calibrate model-graded evaluations

Streaming Responses

Handle streaming LLM responses in your application

Managing LLM Provider Fallbacks

Configure backup providers for resilience

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Voice & Specialized

Building Voice Agents with Pipecat

Create voice-enabled AI applications using Pipecat and Twilio

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Next Steps

Once you’ve implemented a pattern, explore Code Recipes for complete examples you can run and adapt, or dive into the SDK documentation for detailed API reference.