> ## 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

Practical guides, tutorials, and reference documentation for building with Fiddler.

## ⚡ Quick Starts

Get up and running in minutes with step-by-step quick start guides:

* [**Get Started in \<10 Minutes**](/developers/quick-starts/get-started-in-less-than-10-minutes) - Fastest way to integrate Fiddler
* **Agentic Monitoring Quick Starts** - Monitor AI agents and multi-step workflows
  * [OpenTelemetry Quick Start](/developers/quick-starts/opentelemetry-quick-start) (`fiddler-otel`) or
  * [LangChain SDK Quick Start](/developers/quick-starts/langchain-sdk-quick-start) (`fiddler-langchain`) or
  * [LangGraph SDK Quick Start](/developers/quick-starts/langgraph-sdk-quick-start) (`fiddler-langgraph`) or
  * [Strands Agent SDK Quick Start](/developers/quick-starts/strands-agent-quick-start) (`fiddler-strands`)
* [**Experiments Quick Start**](/developers/quick-starts/experiments-quick-start) - Evaluate LLM outputs with custom metrics
* [**Guardrails Quick Start**](/developers/quick-starts/guardrails-quick-start) - Add safety guardrails to your AI applications

## 📚 Tutorials

In-depth, hands-on tutorials organized by product area:

### Experiments

Learn how to evaluate and test your LLM applications:

* [RAG Health Metrics Tutorial](/developers/tutorials/experiments/rag-health-metrics-tutorial)
* [Evals SDK Advanced Guide](/developers/tutorials/experiments/evals-sdk-advanced)
* [Advanced Prompt Specs](/developers/tutorials/llm-monitoring/prompt-specs-advanced)

### Agentic & LLM Monitoring

Monitor production LLM applications and AI agents:

* [LangGraph SDK Quick Start](/developers/quick-starts/langgraph-sdk-quick-start)
* [LangGraph SDK Advanced](/developers/tutorials/llm-monitoring/langgraph-sdk-advanced)
* [Simple LLM Monitoring](/developers/quick-starts/simple-llm-monitoring)

### Guardrails

Implement safety controls for your AI applications:

* [Faithfulness Guardrails](/developers/tutorials/guardrails/guardrails-faithfulness)
* [Safety Guardrails](/developers/tutorials/guardrails/guardrails-safety)
* [PII Detection Guardrails](/developers/tutorials/guardrails/guardrails-pii)

### ML Monitoring

Monitor traditional ML models in production:

* [ML Monitoring Quick Start](/developers/quick-starts/simple-ml-monitoring)
* [NLP Model Monitoring](/developers/tutorials/ml-monitoring/simple-nlp-monitoring-quick-start)
* [Class Imbalance Handling](/developers/tutorials/ml-monitoring/class-imbalance-monitoring-example)
* [Model Versions](/developers/tutorials/ml-monitoring/ml-monitoring-model-versions)
* [Ranking Models](/developers/tutorials/ml-monitoring/ranking-model)
* [Regression Models](/developers/tutorials/ml-monitoring/ml-monitoring-regression)
* [Feature Impact Analysis](/developers/tutorials/ml-monitoring/user-defined-feature-impact)
* [Computer Vision Monitoring](/developers/tutorials/ml-monitoring/cv-monitoring)

## 🍳 Cookbooks

Use-case oriented guides that demonstrate end-to-end workflows for solving real problems:

* [**RAG Evaluation Fundamentals**](/developers/cookbooks/rag-evaluation-fundamentals) — Evaluate RAG quality with built-in evaluators
* [**Running RAG Experiments at Scale**](/developers/cookbooks/rag-experiments-at-scale) — Compare pipeline configurations systematically
* [**Building Custom Judge Evaluators**](/developers/cookbooks/custom-judge-evaluators) — Create domain-specific evaluation criteria
* [**Detecting Hallucinations in RAG**](/developers/cookbooks/hallucination-detection-pipeline) — Monitor for hallucinations in production
* [**Monitoring Agentic Content Generation**](/developers/cookbooks/agentic-content-generation) — Quality and brand compliance for content agents

## 📖 Client Library Reference

Comprehensive reference documentation for Fiddler's Python client:

### Getting Started

* [Installation and Setup](/developers/python-client-guides/installation-and-setup)
* [Naming Convention Guidelines](/developers/python-client-guides/naming-convention-guidelines)
* [Alerts with Fiddler Client](/developers/python-client-guides/alerts-with-fiddler-client)

### Model Onboarding

* [Create a Project and Model](/developers/python-client-guides/model-onboarding/create-a-project-and-model)
* [Customizing Your Model Schema](/developers/python-client-guides/model-onboarding/customizing-your-model-schema)
* [Task Types](/developers/python-client-guides/model-onboarding/task-types)
* [Custom Missing Values](/developers/python-client-guides/model-onboarding/specifying-custom-missing-value-representations)

### Publishing Production Data

* [Creating a Baseline Dataset](/developers/python-client-guides/publishing-production-data/creating-a-baseline-dataset)
* [Publishing Batches of Events](/developers/python-client-guides/publishing-production-data/publishing-batches-of-events)
* [Streaming Live Events](/developers/python-client-guides/publishing-production-data/streaming-live-events)
* [Updating Events](/developers/python-client-guides/publishing-production-data/updating-events)
* [Deleting Events](/developers/python-client-guides/publishing-production-data/deleting-events)
* [Ranking Events](/developers/python-client-guides/publishing-production-data/ranking-events)

For supported task setup and schema guidance, continue with the
[*Model Onboarding guide*](/developers/client-library-reference/model-onboarding)
and
[*Updating Model Schema*](/developers/python-client-guides/model-onboarding/updating-model-schema).

***

## Related Documentation

* [**SDK & API Reference**](/sdk-api/index) - Complete API documentation
* [**Integrations**](/integrations) - Connect Fiddler with your ML stack
* [**Documentation**](/) - Product guides and platform documentation