> ## Documentation Index
> Fetch the complete documentation index at: https://docs.freeplay.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview

> Complete, runnable code examples for common Freeplay integration patterns.

Code Recipes are self-contained examples that demonstrate how to accomplish specific tasks with Freeplay. Each recipe includes complete, working code that you can copy and adapt for your own projects.

## How Recipes Relate to Other Documentation

| Resource                                    | Purpose                            | When to Use                                            |
| ------------------------------------------- | ---------------------------------- | ------------------------------------------------------ |
| **Code Recipes**                            | Complete, runnable examples        | Starting a new integration or looking for working code |
| [SDK Documentation](/freeplay-sdk/setup)    | Detailed API reference             | Understanding all available methods and options        |
| [API Reference](/api-reference)             | HTTP endpoint documentation        | Building custom integrations or debugging              |
| [How-To Guides](/practical-guides/overview) | Step-by-step implementation guides | Learning patterns and best practices                   |

## Recipe Categories

### Basic Patterns

Get started with fundamental Freeplay integration patterns.

* [Single Prompt](/developer-resources/recipes/single-prompt) - Fetch and call a single prompt template
* [Multi-Prompt Chain](/developer-resources/recipes/multi-prompt-chain) - Chain multiple prompts together
* [Record Agent Traces](/developer-resources/recipes/record-traces) - Group related completions into traces
* [Multi-Chain Prompt with Traces](/developer-resources/recipes/multi-chain-prompt-with-traces) - Complex multi-step workflows

### Chat & Conversations

Build conversational AI applications.

* [Managing Multi-Turn Chat History](/developer-resources/recipes/continuous-chat) - Maintain conversation context across turns

### Tool Calling

Implement function calling with different providers.

* [OpenAI Function Calls](/developer-resources/recipes/using-tools-with-openai) - Use tools with OpenAI models
* [Anthropic Tools](/developer-resources/recipes/using-tools-with-anthropic) - Use tools with Claude models
* [Google GenAI Chat with Tools](/developer-resources/recipes/using-tools-with-google-genai) - Multi-turn chat with tools using Google Gemini models

### Providers & Model Hosting

Connect to models hosted on different platforms.

* [OpenAI on Azure](/developer-resources/recipes/call-openai-on-azure) - Use Azure-hosted OpenAI models
* [Anthropic on Bedrock](/developer-resources/recipes/call-anthropic-on-bedrock) - Use Claude via AWS Bedrock
* [Llama on SageMaker](/developer-resources/recipes/call-llama-3-on-aws-sagemaker) - Deploy Llama models on SageMaker
* [Provider Switching](/developer-resources/recipes/provider-switching) - Switch between providers dynamically
* [LiteLLM Proxy](/developer-resources/recipes/provider-switching-with-litellm) - Use LiteLLM for unified provider access

### Testing

Run tests and evaluations programmatically.

* [Test Runs](/developer-resources/recipes/test-run) - Execute test runs against datasets
* [Tests with Tools](/developer-resources/recipes/run-a-test-with-tools-programmatically) - Run tests that include tool calls

### Specialized

Advanced patterns and integrations.

* [OpenAI Responses API](/developer-resources/recipes/openai-responses-api) - Use OpenAI's Responses API with text, images, tools, and structured outputs
* [Structured Outputs](/developer-resources/recipes/structured-outputs) - Get typed, structured responses from models
* [OpenAI Batch API](/developer-resources/recipes/openai-batch-api) - Process large batches efficiently
* [Pipecat Observer](/developer-resources/recipes/freeplay-pipecat-observer) - Monitor Pipecat voice pipelines
* [Pipecat Processor](/developer-resources/recipes/pipecat-processor-integration) - Process audio with Pipecat
* [LangGraph](/developer-resources/integrations/langgraph) - Comprehensive LangGraph integration guide

## Using Recipes

Each recipe follows a consistent structure:

1. **Prerequisites** - What you need before starting
2. **Setup** - Environment and client configuration
3. **Implementation** - Step-by-step code with explanations
4. **Complete Example** - Full working code you can run

Most recipes include examples in Python, with some also providing TypeScript and/or Java variants. Copy the code, update the configuration values for your project, and run.