.. toctree:: :maxdepth: 1 :hidden: :caption: Overview welcome roadmap release_notes/flare_272 industry_use_cases
.. toctree:: :maxdepth: 1 :hidden: :caption: Get Started installation quickstart migration_guide
.. toctree:: :maxdepth: 1 :hidden: :caption: User Guide user_guide/data_scientist_guide/client_api_usage user_guide/data_scientist_guide/job_recipe user_guide/data_scientist_guide/available_recipes user_guide/data_scientist_guide/flare_api API Evolution & Recommendations <programming_guide/flare_api_evolution> user_guide/data_scientist_guide/flower_integration/flower_integration programming_guide/experiment_tracking Federated XGBoost <user_guide/data_scientist_guide/federated_xgboost/federated_xgboost> user_guide/data_scientist_guide/data_preparation CLI Tools <user_guide/nvflare_cli/nvflare_cli>
.. toctree:: :maxdepth: 1 :hidden: :caption: Examples & Tutorials example_applications_algorithms tutorials self-paced-training/index Research Papers <user_guide/researcher_guide/index>
.. toctree:: :maxdepth: 1 :hidden: :caption: Large Models & LLM Federated LLM Fine-Tuning <programming_guide/llm_fine_tuning> programming_guide/message_quantization programming_guide/memory_management programming_guide/tensor_downloader programming_guide/file_streaming programming_guide/decomposer_for_large_object
.. toctree:: :maxdepth: 1 :hidden: :caption: Edge & Mobile Mobile Training (iOS / Android) <user_guide/edge_development/mobile_training> Mobile SDK Reference <user_guide/edge_development/flare_mobile> Hierarchical FL <programming_guide/hierarchical_architecture> programming_guide/hierarchical_communication
.. toctree:: :maxdepth: 1 :hidden: :caption: Deployment & Operations user_guide/admin_guide/deployment/overview programming_guide/provisioning_system Distributed Provisioning <user_guide/nvflare_cli/distributed_provisioning> user_guide/admin_guide/deployment/dashboard_ui user_guide/admin_guide/deployment/cloud_deployment user_guide/admin_guide/deployment/aws_eks Running FLARE in Docker <user_guide/admin_guide/deployment/containerized_deployment> Running FLARE in Kubernetes <user_guide/admin_guide/deployment/helm_chart> Preflight Check <user_guide/nvflare_cli/preflight_check> user_guide/admin_guide/deployment/operation user_guide/admin_guide/monitoring user_guide/admin_guide/configurations/logging_configuration System Configuration <user_guide/admin_guide/configurations/system_configuration>
.. toctree:: :maxdepth: 1 :hidden: :caption: Security & Compliance system_architecture/security_overview user_guide/admin_guide/security/terminologies_and_roles Identity & Access Control <user_guide/admin_guide/security/identity_security> user_guide/admin_guide/security/site_policy_management Network & Communication <user_guide/admin_guide/security/communication_security> Data Privacy & Filters <user_guide/admin_guide/security/data_privacy_protection> Differential Privacy <user_guide/admin_guide/security/differential_privacy> user_guide/admin_guide/security/auditing Confidential Computing <user_guide/confidential_computing/index> security_faq
.. toctree:: :maxdepth: 1 :hidden: :caption: Developer Guide developer_guide
.. toctree:: :maxdepth: 1 :hidden: :caption: Reference API Reference <apidocs/modules> glossary publications_and_talks release_notes/previous contributing
NVIDIA FLARE (Federated Learning Application Runtime Environment) is an open-source SDK for federated learning. It helps ML practitioners adapt existing training workflows (PyTorch, TensorFlow, XGBoost, scikit-learn, NeMo) to a federated setting with minimal code changes, and enables platform teams to deploy secure, privacy-preserving multi-party collaboration.
Start here if you want to federate an existing training script.
- :doc:`Welcome <welcome>` -- What FLARE is and what it supports
- :doc:`Installation <installation>` -- Install FLARE and set up your environment
- :doc:`Quick Start <quickstart>` -- Run a Hello World example and convert your ML code
- :ref:`Client API <client_api>` -- Recommended high-level API for federated training
- :ref:`Job Recipe API <job_recipe>` -- Pre-built recipes for common FL workflows
- :doc:`Migration Guide <migration_guide>` -- Upgrade between FLARE versions
- :ref:`Examples & Tutorials <example_applications>` -- End-to-end examples and tutorials
Start here if you are deploying FLARE in an organization or consortium.
- :doc:`Deployment Overview <user_guide/admin_guide/deployment/overview>` -- Provisioning, Docker/Kubernetes, cloud deployment, dashboard
- :doc:`Admin Commands <user_guide/admin_guide/deployment/operation>` -- Operating and managing a running FL system
- :doc:`System Configuration <user_guide/admin_guide/configurations/system_configuration>` -- Configuration files and settings
- :doc:`Preflight Check <user_guide/nvflare_cli/preflight_check>` -- Pre-launch validation
- :doc:`Security Overview <system_architecture/security_overview>` -- Authentication, authorization, privacy, auditing
- :doc:`Confidential Computing <user_guide/confidential_computing/index>` -- Hardware-backed TEEs for end-to-end IP protection
Start here if you want to extend FLARE or build custom workflows.
- :ref:`Developer Guide <developer_guide>` -- Architecture deep-dives, controllers, filters, and extension points
- :doc:`API Reference <apidocs/modules>` -- Full Python API documentation
- :doc:`Contributing <contributing>` -- How to contribute to NVIDIA FLARE
- :doc:`Industry Use Cases <industry_use_cases>` -- Real-world deployments across healthcare, finance, government, and more
- :ref:`Large Models & LLM <llm_fine_tuning>` -- Federated fine-tuning, memory management, and optimization for large models
- :ref:`Edge & Mobile <mobile_training>` -- Mobile training (iOS/Android) and hierarchical FL for large-scale deployments