# Galileo

## Docs

- [Get Token](https://docs.galileo.ai/api-reference/auth/get-token.md)
- [Login Api Key](https://docs.galileo.ai/api-reference/auth/login-api-key.md)
- [Login Email](https://docs.galileo.ai/api-reference/auth/login-email.md)
- [Login Social](https://docs.galileo.ai/api-reference/auth/login-social.md)
- [Refresh Token](https://docs.galileo.ai/api-reference/auth/refresh-token.md)
- [Verify Email](https://docs.galileo.ai/api-reference/auth/verify-email.md)
- [List Evaluate Alerts](https://docs.galileo.ai/api-reference/evaluate-alerts/list-evaluate-alerts.md)
- [Cancel Jobs For Project Run](https://docs.galileo.ai/api-reference/evaluate/cancel-jobs-for-project-run.md): Get all jobs for a project and run.
- [Create a new Evaluate Run](https://docs.galileo.ai/api-reference/evaluate/create-workflows-run.md): Create a new Evaluate run with workflows.
- [Get Evaluate Run Results](https://docs.galileo.ai/api-reference/evaluate/get-evaluate-run-results.md): Fetch evaluation results for a specific run including rows and aggregate information.
- [API Reference | Getting Started with Galileo](https://docs.galileo.ai/api-reference/getting-started.md): Get started with Galileo's REST API: learn about base URLs, authentication methods, and how to verify your API setup for seamless integration.
- [Healthcheck](https://docs.galileo.ai/api-reference/health/healthcheck.md)
- [Get Workflows](https://docs.galileo.ai/api-reference/observe/get-workflows.md): Get workflows for a specific run in an Observe project.
- [Log Workflows to an Observe Project](https://docs.galileo.ai/api-reference/observe/log-workflows.md): Log workflows to an Observe project.
- [Protect notification](https://docs.galileo.ai/api-reference/protect-notification.md): When a Protect execution completes with the status specified in the configuration, the webhook specified is triggered with this payload.
- [Invoke Protect](https://docs.galileo.ai/api-reference/protect/invoke.md): Learn how to use the 'Invoke Protect' API endpoint in Galileo's Protect module to process payloads with specified rulesets effectively.
- [Workflowstep](https://docs.galileo.ai/api-reference/schemas/workflowstep.md)
- [Python Client Reference | Galileo Evaluate](https://docs.galileo.ai/client-reference/evaluate/python.md): Integrate Galileo's Evaluate module into your Python applications with this guide, featuring installation steps and examples for prompt quality assessment.
- [TypeScript Client Reference | Galileo Evaluate](https://docs.galileo.ai/client-reference/evaluate/typescript.md): Incorporate Galileo's Evaluate module into your TypeScript projects with this guide, providing setup instructions and workflow logging examples.
- [Data Quality | Fine-Tune NLP Studio Client Reference](https://docs.galileo.ai/client-reference/finetune-nlp-studio/data-quality.md): Enhance your data quality in Galileo's NLP and CV Studio using the 'dataquality' Python package; find installation and usage details here.
- [Python Client Reference | Galileo Observe](https://docs.galileo.ai/client-reference/observe/python.md): Integrate Galileo's Observe module into your Python applications; access installation instructions and comprehensive documentation for workflow monitoring.
- [TypeScript Client Reference | Galileo Observescript](https://docs.galileo.ai/client-reference/observe/typescript.md): Integrate Galileo's Observe module into TypeScript applications with setup guides, sample code, and monitoring instructions for seamless workflow tracking.
- [Client References](https://docs.galileo.ai/client-reference/overview.md): Explore Galileo's client references, including Python and TypeScript integrations, to streamline Evaluate, Observe, and Protect module implementations.
- [Python Client Reference | Galileo Protect](https://docs.galileo.ai/client-reference/protect/python.md): Integrate Galileo's Protect module into Python workflows with this guide, including code examples, setup instructions, and ruleset invocation details.
- [Data Privacy And Compliance](https://docs.galileo.ai/deployments/data-privacy-and-compliance.md): This page covers concerns regarding residency of data and compliances provided by Galileo.
- [Dependencies](https://docs.galileo.ai/deployments/dependencies.md): Understand Galileo deployment prerequisites and dependencies to ensure a smooth installation and integration across supported platforms.
- [Azure AKS](https://docs.galileo.ai/deployments/deploying-galileo-aks.md): This page details the steps to deploy a Galileo Kubernetes cluster in Microsoft Azure's AKS service environment.
- [Deploying Galileo on Amazon EKS](https://docs.galileo.ai/deployments/deploying-galileo-eks.md): Deploy Galileo on Amazon EKS with a step-by-step guide for configuring, managing, and scaling Galileo's infrastructure using Kubernetes clusters.
- [Zero Access Deployment | Galileo on EKS](https://docs.galileo.ai/deployments/deploying-galileo-eks-zero-access.md): Create a private Kubernetes Cluster with EKS in your AWS Account, upload containers to your container registry, and deploy Galileo.
- [EKS Cluster Config Example | Zero Access Deployment](https://docs.galileo.ai/deployments/deploying-galileo-eks-zero-access/eks-cluster-config-example-zero-access.md): Access a zero-access EKS cluster configuration example for secure Galileo deployments on Amazon EKS, following best practices for Kubernetes security.
- [EKS Cluster Config Example | Galileo Deployment](https://docs.galileo.ai/deployments/deploying-galileo-eks/eks-cluster-config-example.md): Review a detailed EKS cluster configuration example for deploying Galileo on Amazon EKS, ensuring efficient Kubernetes setup and management.
- [Updating Cluster](https://docs.galileo.ai/deployments/deploying-galileo-eks/updating-galileo-eks-cluster.md): Galileo EKS cluster update from 1.21 -> 1.23
- [Exoscale](https://docs.galileo.ai/deployments/deploying-galileo-exoscale.md): The Galileo applications run on managed Kubernetes-like environments, but this document will specifically cover the configuration and deployment of an Exoscale Cloud SKS environment.
- [Deploying Galileo on Google GKE](https://docs.galileo.ai/deployments/deploying-galileo-gke.md): Deploy Galileo on Google Kubernetes Engine (GKE) with this guide, covering configuration steps, cluster setup, and infrastructure scaling strategies.
- [Cluster Setup Script](https://docs.galileo.ai/deployments/deploying-galileo-gke/galileo-gcp-setup-script.md): Utilize the Galileo GCP setup script for automating Google Cloud Platform (GCP) configuration to deploy Galileo seamlessly on GKE clusters.
- [Enterprise Deployment](https://docs.galileo.ai/deployments/overview.md): Gain an overview of Galileo deployment options, covering supported platforms like Amazon EKS and Google GKE, setup requirements, and best practices.
- [Post Deployment Checklist](https://docs.galileo.ai/deployments/post-deployment-checklist.md): The following guide will walk you through steps you can take to make sure your Galileo cluster is properly deployed and running well.
- [Pre Requisites](https://docs.galileo.ai/deployments/pre-requisites.md): Before deploying Galileo, ensure the following prerequisites are met.
- [Scheduling Automatic Backups For Your Cluster](https://docs.galileo.ai/deployments/scheduling-automatic-backups-for-your-cluster.md): Schedule automatic backups for Galileo clusters with this guide, ensuring data security, disaster recovery, and operational resilience for deployments.
- [Aws Velero Account Setup Script](https://docs.galileo.ai/deployments/scheduling-automatic-backups-for-your-cluster/aws-velero-account-setup-script.md): Automate AWS Velero setup for Galileo cluster backups with this script, ensuring seamless backup scheduling and data resilience for AWS deployments.
- [Gcp Velero Account Setup Script](https://docs.galileo.ai/deployments/scheduling-automatic-backups-for-your-cluster/gcp-velero-account-setup-script.md): Set up Velero for Google Cloud backups with this GCP account script, enabling automated backup scheduling and robust data protection for Galileo clusters.
- [  Security &  Access Control](https://docs.galileo.ai/deployments/security-and-access-control.md): This page covers networking, security and access control provisions that Galileo deployments enable
- [Setting Up New Users](https://docs.galileo.ai/deployments/setting-up-new-users.md): Learn how to onboard new users in Galileo deployments with detailed instructions on user roles, access control, and permissions management.
- [SSO Integration](https://docs.galileo.ai/deployments/sso-integration.md): This page covers our SSO Integration support with information we need to setup SSO for your Galileo cluster.
- [Examples](https://docs.galileo.ai/examples/overview.md): Explore Galileo's practical examples covering real-world use cases and workflows for Evaluate, Observe, and Protect modules across AI projects.
- [What is Galileo?](https://docs.galileo.ai/galileo.md): Evaluate, Observe, and Protect your GenAI applications
- [Chainpoll](https://docs.galileo.ai/galileo-ai-research/chainpoll.md): ChainPoll is a powerful, flexible technique for LLM-based evaluation that is unique to Galileo. It is used to power multiple metrics across the Galileo platform.
- [Class Boundary Detection](https://docs.galileo.ai/galileo-ai-research/class-boundary-detection.md): Detecting samples on the decision boundary
- [Data Drift Detection](https://docs.galileo.ai/galileo-ai-research/data-drift-detection.md): Discover Galileo's data drift detection methods to monitor AI model performance, identify data changes, and maintain model reliability in production.
- [Errors In Object Detection](https://docs.galileo.ai/galileo-ai-research/errors-in-object-detection.md): This page describes the rich error types offered by Galileo for Object Detection
- [Galileo Data Error Potential  (Dep) ](https://docs.galileo.ai/galileo-ai-research/galileo-data-error-potential-dep.md): Learn about Galileo's Data Error Potential (DEP) score, a metric to identify and categorize machine learning data errors, enhancing data quality and model performance.
- [Likely Mislabeled](https://docs.galileo.ai/galileo-ai-research/likely-mislabeled.md): Garbage in, Garbage out
- [Galileo AI Research](https://docs.galileo.ai/galileo-ai-research/overview.md): Research produced by Galileo AI Labs
- [Rag Quality Metrics Using Chainpoll](https://docs.galileo.ai/galileo-ai-research/rag-quality-metrics-using-chainpoll.md): Learn how ChainPoll metrics assess retrieval-augmented generation (RAG) system quality, improving accuracy and performance of generative AI models.
- [Rag Quality Metrics Using Luna](https://docs.galileo.ai/galileo-ai-research/rag-quality-metrics-using-luna.md): This page provides a brief overview of the research behind Galileo's RAG Quality Metrics.
- [FAQs](https://docs.galileo.ai/galileo/galileo-nlp-studio/faqs.md): You have questions, we have (some) answers!
- [Third Party  3p  Integrations](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/3p-integrations.md): Galileo has integrates seamlessly with your tools.
- [Access Control Features | Galileo NLP Studio](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/access-control.md): Discover Galileo NLP Studio's access control features, including user roles and group management, to securely share and manage projects within your organization.
- [Actions](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/actions.md): Actions help close the inspection loop and error discovery process. We support a number of actions.
- [Clustering](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/clusters.md): To help you make sense of your data and your embeddings view, Galileo provides out-of-the-box Clustering and Explainability.
- [Compare Across Runs](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/compare-across-runs.md): Track your experiments, data and models in one place
- [Dataset Slices](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/dataset-slices.md): Slices is a powerful Galileo feature that allows you to monitor, across training runs, a sub-population of the dataset based on metadata filters.
- [Dataset View](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/dataset-view.md): The Dataset View provides an interactive data table for inspecting your datasets.
- [Embeddings View](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/embeddings-view.md): The Embeddings View provides a visual playground for you to interact with your datasets.
- [Error Types Breakdown](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/error-types-breakdown.md): For use cases with complex data and error types (e.g. Named Entity Recognition, Object Detection or Semantic Segmentation), the **Error Types Chart** gives you an insight into exactly how the Ground Truth differed from your model's predictions
- [Galileo + Delta Lake  Databricks](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/galileo-+-delta-lake-databricks.md): Integrate Galileo with Delta Lake on Databricks to manage large-scale data, ensuring seamless collaboration and enhanced NLP workflows.
- [Insights Panel](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/insights-panel.md): Utilize Galileo's Insights Panel to analyze data trends, detect issues, and gain actionable insights for improving NLP model performance.
- [Product Features](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/overview.md): Explore Galileo NLP Studio's features, including data insights, error detection, and monitoring tools for improving NLP workflows and AI quality.
- [Similarity Search](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/similarity-search.md): Similarity search provides out of the box ability to discover **similar samples** within your datasets.
- [Alerts](https://docs.galileo.ai/galileo/galileo-nlp-studio/galileo-product-features/xray-insights.md): Explore Galileo NLP Studio's Alerts feature, designed to detect and summarize dataset issues like mislabeling and class imbalance, enhancing data inspection.
- [Multi Label Text Classification](https://docs.galileo.ai/galileo/galileo-nlp-studio/multi-label-text-classification.md): Implement multi-label text classification in Galileo NLP Studio to accurately label datasets, streamline workflows, and enhance model training.
- [Multi-Label Text Classification | Galileo NLP Studio Guide](https://docs.galileo.ai/galileo/galileo-nlp-studio/multi-label-text-classification/getting-started.md): Get started with multi-label text classification in Galileo NLP Studio, featuring setup instructions, workflow integration, and data preparation tips.
- [Named Entity Recognition](https://docs.galileo.ai/galileo/galileo-nlp-studio/named-entity-recognition.md): NER is a sequence tagging problem, where given an input document, the task is to correctly identify the span boundaries for various entities and also classify the spans into correct entity types.
- [Named Entity Recognition | Galileo NLP Studio Guide](https://docs.galileo.ai/galileo/galileo-nlp-studio/named-entity-recognition/getting-started.md): Start building named entity recognition (NER) models in Galileo NLP Studio with this guide on setup, labeling, and model training workflows.
- [Model Monitoring & Data Drift | Named Entity Recognition](https://docs.galileo.ai/galileo/galileo-nlp-studio/named-entity-recognition/model-monitoring-and-data-drift.md): Learn how to monitor Named Entity Recognition models in production with Galileo NLP Studio, detecting data drift and maintaining model health effectively.
- [Natural Language Inference](https://docs.galileo.ai/galileo/galileo-nlp-studio/natural-language-inference.md): Leverage Galileo NLP Studio for natural language inference (NLI), enabling accurate predictions and model performance monitoring.
- [Natural Language Inference | Galileo NLP Studio Guide](https://docs.galileo.ai/galileo/galileo-nlp-studio/natural-language-inference/getting-started.md): Begin implementing natural language inference (NLI) workflows in Galileo NLP Studio with clear instructions for setup and model evaluation.
- [Logging Data | Natural Language Inference in Galileo](https://docs.galileo.ai/galileo/galileo-nlp-studio/natural-language-inference/logging-data-to-galileo.md): The fastest way to find data errors in Galileo.
- [Model Monitoring & Data Drift | Natural Language Inference](https://docs.galileo.ai/galileo/galileo-nlp-studio/natural-language-inference/model-monitoring-and-data-drift.md): Ensure optimal performance of Natural Language Inference models in production by monitoring data drift and model health with Galileo NLP Studio.
- [Text Classification](https://docs.galileo.ai/galileo/galileo-nlp-studio/text-classification.md): Using Galileo for Text Classification you can improve your classification models by improving the quality of your training data.
- [Automated Production Monitoring](https://docs.galileo.ai/galileo/galileo-nlp-studio/text-classification/automated-production-monitoring.md): Monitor text classification models in production with automated tools from Galileo NLP Studio to detect data drift and maintain performance.
- [Build your own conditions](https://docs.galileo.ai/galileo/galileo-nlp-studio/text-classification/build-your-own-conditions.md): A class to build custom conditions for DataFrame assertions and alerting.
- [Text Classification | Galileo NLP Studio Guide](https://docs.galileo.ai/galileo/galileo-nlp-studio/text-classification/getting-started.md): Start training and deploying text classification models in Galileo NLP Studio with this guide on setup, data preparation, and workflow integration.
- [Logging Data | Text Classification in Galileo](https://docs.galileo.ai/galileo/galileo-nlp-studio/text-classification/logging-data-to-galileo.md): The fastest way to find data errors in Galileo
- [Model Monitoring & Data Drift | Text Classification](https://docs.galileo.ai/galileo/galileo-nlp-studio/text-classification/model-monitoring-and-data-drift.md): Monitor text classification models in production with Galileo NLP Studio, detecting data drift and ensuring consistent model performance over time.
- [Training High-Quality Supervised NLP Models | Galileo](https://docs.galileo.ai/galileo/galileo-nlp-studio/train-high-quality-supervised-nlp-models.md): Galileo NLP Studio supports Natural Language Processing Tasks across the life-cycle of your model development.
- [Overview of Galileo Evaluate](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate.md): Stop experimenting in spreadsheets and notebooks. Use Evaluate’s powerful insights to build GenAI systems that just work.
- [Human Ratings](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/concepts/human-ratings.md): Learn how human ratings in Galileo Evaluate enable accurate model evaluations and improve performance through qualitative feedback.
- [Metrics](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/concepts/metrics.md): Metrics are quantitative or qualitative ways to express insights about the [run](/galileo/gen-ai-studio-products/galileo-evaluate/concepts/run).
- [Project Concepts | Galileo Evaluate](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/concepts/project.md): Understand project concepts in Galileo Evaluate, including organization of datasets, metrics, and workflows for AI evaluation.
- [Run](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/concepts/run.md): Runs in Galileo are experiments or iterations done within a [project](/galileo/gen-ai-studio-products/galileo-evaluate/concepts/project).
- [Template](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/concepts/template.md): Leverage templates in Galileo Evaluate to standardize metrics, model assessments, and workflows for efficient generative AI evaluation.
- [Context vs. Instruction Adherence | Galileo Evaluate FAQ](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/faq/context-adherence-vs-instruction-adherence.md): Understand the distinctions between Context Adherence and Instruction Adherence metrics in Galileo Evaluate to assess generative AI outputs accurately.
- [Error Computing Metrics | Galileo Evaluate FAQ](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/faq/errors-computing-metrics.md): Find solutions to common errors in computing metrics within Galileo Evaluate, including missing integrations and rate limit issues, to streamline your AI evaluations.
- [How-To Guide | Galileo Evaluate](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to.md): Follow step-by-step instructions in Galileo Evaluate to assess generative AI models, configure metrics, and analyze performance effectively.
- [A/B Compare Prompts](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/a-b-compare-prompts.md): Easily compare multiple LLM runs in a single screen for better decision making
- [Access Control Guide | Galileo Evaluate](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/access-control.md): Manage user permissions and securely share projects in Galileo Evaluate using detailed access control features, including system roles and group management.
- [Add Tags and Metadata to Prompt Runs](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/add-tags-and-metadata-to-prompt-runs.md): While you are experimenting with your prompts you will probably be tuning many parameters.
- [Auto-generating an LLM-as-a-judge](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/autogen-metrics.md): Learn how to use Galileo's Autogen feature to generate LLM-as-a-judge metrics.
- [Choose your Guardrail Metrics](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/choose-your-guardrail-metrics.md): Select and understand guardrail metrics in Galileo Evaluate to effectively assess your prompts and models, utilizing both industry-standard and proprietary metrics.
- [Collaborate with other personas](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/collaborate-with-other-personas.md): Galileo Evaluate is geared for cross-functional collaboration. Most of the teams using Galileo consist of a mix of the following personas
- [Customizing your LLM-powered metrics via CLHF](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/continuous-learning-via-human-feedback.md): Learn how to customize your LLM-powered metrics with Continuous Learning via Human Feedback.
- [Create an Evaluation Set](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/create-an-evaluation-set.md): Before starting your experiments, we recommend creating an evaluation set.
- [Customize Chainpoll-powered Metrics](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/customize-chainpoll-powered-metrics.md): Improve metric accuracy by customizing your Chainpoll-powered metrics
- [Enabling Scorers in Runs](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/enabling-scorers-in-runs.md): Learn how to turn on metrics when creating runs in your Python environment.
- [Evaluate and Optimize Agents](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/evaluate-and-optimize-agents--chains-or-multi-step-workflows.md): How to use Galileo Evaluate with Agents
- [Evaluate and Optimize Prompts](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/evaluate-and-optimize-prompts.md): How to use Galileo Evaluate for prompt engineering
- [Evaluate and Optimize RAG Applications](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/evaluate-and-optimize-rag-applications.md): How to use Galileo Evaluate with RAG applications
- [Evaluate with Human Feedback](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/evaluate-with-human-feedback.md): Galileo allows you to do qualitative human evaluations of your prompts and responses.
- [Experiment with Multiple Workflows](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/experiment-with-multiple-chain-workflows.md): If you're building a multi-step workflow or chain (e.g. a RAG system, an Agent, or a chain) and want to experiment with multiple combinations of parameters or your versions at once, Chain Sweeps are your friend.
- [Experiment with Multiple Prompts](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/experiment-with-multiple-prompts.md): Experiment with multiple prompts in Galileo Evaluate to optimize generative AI performance using iterative testing and comprehensive analysis tools.
- [Export your Evaluation Runs](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/export-your-evaluation-runs.md): To download the results of your evaluation you can use the Export function. To export your runs, simply click on _Export Prompt Data._
- [Identify Hallucinations](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/identify-hallucinations.md): How to use Galileo Evaluate to find Hallucinations
- [Log Pre-generated Responses in Python](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/log-pre-generated-responses-in-python.md): If you already have a dataset of requests and application responses, and you want to log and evaluate these on Galileo without re-generating the responses, you can do so via our worflows.
- [Logging and Comparing against your Expected Answers](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/logging-and-comparing-against-your-expected-answers.md): Expected outputs are a key element for evaluating LLM applications. They provide benchmarks to measure model accuracy, identify errors, and ensure consistent assessments.
- [Programmatically fetch logged data](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/programmatically-fetch-logged-data.md): If you want to fetch your logged data and metrics programmatically, you can do so via our Python clients.
- [Prompt Management-Storage](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/prompt-management-storage.md): Manage and store your AI prompts efficiently in Galileo Evaluate, with tools for organizing, versioning, and analyzing prompt performance at scale.
- [Finding the best run](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/rank-your-runs.md): Learn how to use Automatic Run Ranking to find the best run
- [Register Custom Metrics](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/register-custom-metrics.md): Galileo GenAI Studio supports Custom Metrics (programmatic or GPT-based) for all your Evaluate and Observe projects. Depending on where, when, and how you want these metrics to be executed, you have the option to choose between **Custom Scorers** and **Registered Scorers**.
- [Share a project](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/share-a-project.md): All projects on Galileo can be shared with others to enable collaboration.
- [Understanding Metric Values | Galileo Evaluate How-To](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/understand-your-metrics-values.md): Gain insights into your metric values in Galileo Evaluate with explainability features, including token-level highlighting and generated explanations for better analysis.
- [Using Datasets](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/how-to/using-datasets.md): How to use datasets in Galileo
- [Integrations | Galileo Evaluate](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/integrations.md): Discover Galileo Evaluate's integrations with AI tools and platforms, enabling seamless connectivity and enhanced generative AI evaluation workflows.
- [Logging Workflows](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/integrations/custom-chain.md): No matter how you're orchestrating your workflows, we have an interface to help you upload them to Galileo.
- [Databricks](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/integrations/data-storage/databricks.md): Integrating into Databricks to seamlessly export your data to Delta Lake
- [LangChain Integration | Galileo Evaluate](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/integrations/langchain.md): Galileo allows you to integrate with your Langchain application natively through callbacks
- [LLMs](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/integrations/llms.md): Integrate large language models (LLMs) into Galileo Evaluate to assess performance, refine outputs, and enhance generative AI model capabilities.
- [Adding Custom LLM APIs / Fine Tuned LLMs](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/integrations/llms/adding-custom-llms.md): Showcases how to use Galileo with any LLM API or custom fine-tuned LLMs, not supported out-of-the-box by Galileo.
- [Supported LLMs](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/integrations/llms/supported-llms.md): Galileo comes with support for the following LLMs out of the box. In the Playground, you will see models for which you've added an integration.
- [Quickstart Guide | Galileo Evaluate](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/quickstart.md): Start using Galileo Evaluate with this quickstart guide, covering prompt engineering, AI evaluation, and integrating tools into existing workflows.
- [Integrate Evaluate Into My Existing Application With Python](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/quickstart/integrate-evaluate-into-my-existing-application-with-python.md): Learn how to integrate Galileo Evaluate into your Python applications, featuring step-by-step guidance and code samples for streamlined integration.
- [Prompt Engineering From A UI](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-evaluate/quickstart/prompt-engineering-from-a-ui.md): Explore UI-driven prompt engineering in Galileo Evaluate to create, test, and refine prompts with intuitive interfaces and robust evaluation tools.
- [Overview of Galileo Guardrail Metrics](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics.md): Utilize Galileo's Guardrail Metrics to monitor generative AI models, ensuring adherence to quality, correctness, and alignment with project goals.
- [Action Advancement](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/action-advancement.md): Understand Galileo's Action Advancement Metric
- [Action Completion](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/action-completion.md): Understand Galileo's Action Completion Metric
- [BLEU and ROUGE](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/bleu-and-rouge-1.md): Understand BLEU & ROUGE-1 scores
- [Chunk Attribution](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/chunk-attribution.md): Understand Galileo's Chunk Attribution Metric
- [Chunk Attribution Luna](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/chunk-attribution/chunk-attribution-luna.md): Understand Galileo's Chunk Attribution Luna Metric
- [Chunk Attribution Plus](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/chunk-attribution/chunk-attribution-plus.md): Understand Galileo's Chunk Attribution Plus Metric
- [Chunk Relevance](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/chunk-relevance.md): Understand Galileo's Chunk Relevance Luna Metric
- [Chunk Utilization](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/chunk-utilization.md): Understand Galileo's Chunk Utilization Metric
- [Chunk Utilization Luna](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/chunk-utilization/chunk-utilization-luna.md): Understand Galileo's Chunk Utilization Luna Metric
- [Chunk Utilization Plus](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/chunk-utilization/chunk-utilization-plus.md): Leverage Chunk Utilization+ in Galileo Guardrail Metrics to optimize generative AI output segmentation and maximize model efficiency.
- [Completeness](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/completeness.md): Understand Galileo's Completeness Metric
- [Completeness Luna](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/completeness/completeness-luna.md): Understand Galileo's Completeness Luna Metric
- [Completeness Plus](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/completeness/completeness-plus.md): Understand Galileo's Completeness Plus Metric
- [Context Adherence](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/context-adherence.md): Understand Galileo's Context Adherence Metric
- [Context Adherence Luna](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/context-adherence/context-adherence-luna.md): Understand Galileo's Context Adherence Luna Metric
- [Context Adherence Plus](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/context-adherence/context-adherence-plus.md): Understand Galileo's Context Adherence Plus Metric
- [Correctness](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/correctness.md): Understand Galileo's Correctness Metric
- [Context vs. Instruction Adherence | Guardrail Metrics FAQ](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/faq/context-adherence-vs-instruction-adherence.md): Understand the differences between Context Adherence and Instruction Adherence metrics in Galileo's Guardrail Metrics to accurately evaluate model outputs.
- [Error Computing Metrics | Guardrail Metrics FAQ](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/faq/errors-computing-metrics.md): Find solutions to common errors in computing metrics within Galileo's Guardrail Metrics, including missing integrations and rate limit issues, to streamline your evaluations.
- [Ground Truth Adherence](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/ground-truth-adherence.md): Measure ground truth adherence in generative AI models with Galileo's Guardrail Metrics, ensuring accurate and aligned outputs with dataset benchmarks.
- [Instruction Adherence](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/instruction-adherence.md): Assess instruction adherence in AI outputs using Galileo Guardrail Metrics to ensure prompt-driven models generate precise and actionable results.
- [Private Identifiable Information](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/private-identifiable-information.md): Understand Galileo's PII Metric
- [Prompt Injection](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/prompt-injection.md): Understand Galileo's Prompt Injection metric
- [Prompt Perplexity](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/prompt-perplexity.md): Understanding Galileo's Prompt Perplexity Metrics
- [Sexism](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/sexism.md): Understand Galileo's Sexism Metric
- [Tone](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/tone.md): Understand Galileo's Tone Metric
- [Tool Error](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/tool-error.md): Understand Galileo's Tool Error Metric
- [Tool Selection Quality](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/tool-selection-quality.md): Understand Galileo's Tool Selection Quality Metric
- [Toxicity](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/toxicity.md): Understand Galileo's Toxicity Metric
- [Uncertainty](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-guardrail-metrics/uncertainty.md): Understand Galileo's Uncertainty Metric
- [Overview of Galileo LLM Fine-Tune](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-llm-fine-tune.md): Fine-tune large language models with Galileo's LLM Fine-Tune tools, enabling precise adjustments for optimized AI performance and output quality.
- [Console Walkthrough](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-llm-fine-tune/console-walkthrough.md): Upon completing a run, you'll be taken to the Galileo Console.
- [Finding Similar Samples](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-llm-fine-tune/finding-similar-samples.md): Similarity search allows you to discover **similar samples** within your datasets
- [Quickstart Guide | Galileo LLM Fine-Tune](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-llm-fine-tune/quickstart.md): Get started with Galileo's LLM Fine-Tune in this quickstart guide, featuring step-by-step instructions for tuning AI models effectively.
- [Configuring Dq Auto](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-llm-fine-tune/quickstart/dq.auto.md): Automatic Data Insights on your Seq2Seq dataset
- [Taking Action](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-llm-fine-tune/taking-action.md): Take actionable steps in Galileo LLM Fine-Tune to address model performance issues, refine outputs, and achieve targeted AI improvements.
- [Using Alerts](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-llm-fine-tune/using-alerts.md): Utilize Galileo LLM Fine-Tune's Alerts feature to detect and address dataset issues like high Data Error Potential scores and uncertainty outputs, enhancing data quality.
- [Using Data Error Potential](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-llm-fine-tune/using-data-error-potential.md): Learn about Galileo LLM Fine-Tune's Data Error Potential (DEP) score to identify and address errors in your training data, improving overall data quality.
- [Using Uncertainty](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-llm-fine-tune/using-uncertainty.md): On dataset splits where generations are enabled (e.g. the _Test split_), you'll be seeing Uncertainty Scores and Token-level Uncertainty highlighting
- [Visualizing And Understanding Your Data](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-llm-fine-tune/visualizing-and-understanding-your-data.md): Finetuning an LLM often requires large datasets.
- [Overview of Galileo Observe](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe.md): Monitor and analyze generative AI models with Galileo Observe, using real-time data insights to maintain performance and ensure quality outputs.
- [Context vs. Instruction Adherence | Galileo Observe FAQ](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/faq/context-adherence-vs-instruction-adherence.md): Differentiate between Context Adherence and Instruction Adherence metrics in Galileo Observe to effectively evaluate and enhance your model's responses.
- [Error Computing Metrics | Galileo Observe FAQ](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/faq/errors-computing-metrics.md): Troubleshoot common errors in Galileo Observe's metric computations, including integration issues, rate limits, JSON parsing errors, and missing embeddings, to ensure accurate evaluations.
- [Getting Started | Galileo Observe](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/getting-started.md): How to monitor your apps with Galileo Observe
- [How-To Guide | Galileo Observe](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/how-to.md): Learn how to use Galileo Observe to monitor and analyze generative AI models, including setup instructions, data logging, and workflow integrations.
- [How to Set Up Access Control](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/how-to/access-control.md): Manage user permissions and securely share projects in Galileo Observe using detailed access control features, including system roles and group management.
- [Choosing Your Guardrail Metrics](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/how-to/choosing-your-guardrail-metrics.md): Select and understand guardrail metrics in Galileo Observe to effectively evaluate your LLM applications, utilizing both industry-standard and proprietary metrics.
- [Exporting Your Data](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/how-to/exporting-your-data.md): To download your Observe Data you can use the Export function.
- [Identifying And Debugging Issues](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/how-to/identifying-and-debugging-issues.md): Once your monitored LLM app is up and running and you've selected your Guardrail Metrics, you can start monitoring your LLM app using Galileo.
- [Logging Data Via Python](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/how-to/logging-data-via-python.md): Learn how to manually log your data via our Python Logger
- [Monitoring Your Rag Application](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/how-to/monitoring-your-rag-application.md): Galileo Observe allows you to monitor your Retrieval-Augmented Generation (RAG) application with out-of-the-box Tracing and Analytics.
- [Programmatically Fetching Logged Data](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/how-to/programmatically-fetching-logged-data.md): Fetch logged data programmatically in Galileo Observe with step-by-step instructions for seamless integration into automated workflows and analysis tools.
- [Registering And Using Custom Metrics](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/how-to/registering-and-using-custom-metrics.md): Registered Metrics enable the ability for your team to define the custom metrics (programmatic or GPT-based) for your Observe projects.
- [Setting Up Alerts](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/how-to/setting-up-alerts.md): How to set up Alerts and automatically be alerted when things go wrong
- [Understanding Metric Values | Galileo Observe How-To](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/how-to/understand-your-metric-s-values.md): Gain insights into your metric values in Galileo Observe with explainability features, including token-level highlighting and generated explanations for better analysis.
- [Logging Data Via Langchain Callback](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-observe/integrations/langchain.md): Learn how to manually log your data from your Langchain Chains
- [Overview of Galileo Protect](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect.md): Explore Galileo Protect to safeguard AI applications with customizable rulesets, error detection, and robust metrics for enhanced AI governance.
- [Action](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/concepts/action.md): Galileo will provide a set of action types (override, passthrough), that the user can use, along with a configuration for each action type.
- [Project Concepts | Galileo Protect](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/concepts/project.md): Understand project management in Galileo Protect, focusing on ruleset organization, AI model protection, and error monitoring within structured workflows.
- [Rule](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/concepts/rule.md): A condition or rule you never want your application to break. It's composed of three ingredients
- [Ruleset](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/concepts/ruleset.md): All of the Rules within a Ruleset are executed in parallel, and the final resolution depends on all of the rules being completed.
- [Stage](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/concepts/stage.md): A set of rulesets that are applied during _one_ invocation.
- [How-To Guide | Galileo Protect](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/how-to.md): Follow detailed instructions on using Galileo Protect, including setting up rulesets, monitoring workflows, and ensuring secure AI application operations.
- [Creating And Using Stages](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/how-to/creating-and-using-stages.md): Learn to create and manage stages in Galileo Protect, enabling structured AI monitoring and progressive error resolution throughout the deployment lifecycle.
- [Editing Centralized Stages](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/how-to/editing-centralized-stages.md): Edit centralized stages in Galileo Protect with this guide, ensuring accurate ruleset updates and maintaining effective AI monitoring across applications.
- [Invoking Rulesets](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/how-to/invoking-rulesets.md): Invoke rulesets in Galileo Protect to apply AI safeguards effectively, with comprehensive guidance on ruleset usage, configuration, and execution.
- [Pausing Or Resuming A Stage](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/how-to/pausing-or-resuming-a-stage.md): When you're using the Galileo Protect product, once you've created a project and a stage, you can pause and resume the stage.
- [Setting A Timeout On Your Protect Requests](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/how-to/setting-a-timeout-on-your-protect-requests.md): Your Protect Rules rely on [Guardrail Metrics](/galileo/gen-ai-studio-products/galileo-protect/how-to/supported-metrics-and-operators). Metrics are calculated using ML models, which can have varying latencies.
- [Defining Rules](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/how-to/supported-metrics-and-operators.md): Explore supported metrics and operators in Galileo Protect to configure precise rulesets and enhance AI application monitoring and decision-making.
- [LangChain Integration | Galileo Protect](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/integrations/langchain.md): Galileo Protect can also be used within your Langchain workflows. You can use Protect to validate inputs and outputs at different stages of your workflow. We provide a `tool` that allows you to easily integrate Protect into your Langchain workflows.
- [Quickstart Guide | Galileo Protect](https://docs.galileo.ai/galileo/gen-ai-studio-products/galileo-protect/quickstart.md): Get started with Galileo Protect using this quickstart guide, covering setup, ruleset creation, and integration into AI workflows for secure operations.

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- [.pre-commit-config](https://docs.galileo.ai/.pre-commit-config.yaml)


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