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

# Overview

> Use-case oriented guides for solving real-world AI evaluation and monitoring problems with Fiddler.

Cookbooks are use-case oriented guides that demonstrate end-to-end workflows for solving real problems with Fiddler. Unlike quick starts (which introduce product features) or tutorials (which deep-dive into specific capabilities), cookbooks are organized by scenario — they show you how to combine multiple Fiddler features to achieve a practical goal.

<Info>
  **Prerequisites for all cookbooks**

  * Fiddler account with API access
  * Python 3.10+
  * Fiddler Evals SDK: `pip install fiddler-evals`
  * LLM credential configured in **Settings > LLM Gateway**
</Info>

## RAG Evaluation & Monitoring

| Cookbook                                                                                  | Use Case                                            | Key Features                                                     |
| ----------------------------------------------------------------------------------------- | --------------------------------------------------- | ---------------------------------------------------------------- |
| [RAG Evaluation Fundamentals](/developers/cookbooks/rag-evaluation-fundamentals)          | "I have a RAG app and want to evaluate its quality" | RAG Faithfulness, Answer Relevance, direct `.score()` API        |
| [Running RAG Experiments at Scale](/developers/cookbooks/rag-experiments-at-scale)        | "I want to compare RAG pipeline configurations"     | Datasets, Experiments, `evaluate()`, golden label validation     |
| [Detecting Hallucinations in RAG](/developers/cookbooks/hallucination-detection-pipeline) | "I want to monitor my RAG app for hallucinations"   | RAG Health triad, Evaluator Rules, LLM Observability enrichments |

## Custom Evaluators

| Cookbook                                                                          | Use Case                                     | Key Features                                                            |
| --------------------------------------------------------------------------------- | -------------------------------------------- | ----------------------------------------------------------------------- |
| [Building Custom Judge Evaluators](/developers/cookbooks/custom-judge-evaluators) | "I need domain-specific evaluation criteria" | `CustomJudge`, prompt templates, `output_fields`, iterative improvement |

## Agentic AI

| Cookbook                                                                                  | Use Case                                                                     | Key Features                                         |
| ----------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------- | ---------------------------------------------------- |
| [Monitoring Agentic Content Generation](/developers/cookbooks/agentic-content-generation) | "I want to ensure quality and brand compliance in content generation agents" | Built-in evaluators + custom Brand Voice Match judge |

***

## Related Resources

* [Experiments Getting Started](/getting-started/experiments) — Product overview
* [Experiments Quick Start](/developers/quick-starts/experiments-quick-start) — SDK setup and first experiment
* [RAG Health Diagnostics](/concepts/rag-health-diagnostics) — Conceptual guide to the diagnostic triad
* [Evals SDK Advanced Guide](/developers/tutorials/experiments/evals-sdk-advanced) — Advanced patterns