69 plugins across 9 categories
69 results
Anthropic Claude
flyteplugins-anthropic
This plugin provides integration between Flyte and Anthropic's Claude API, enabling you to use Flyte tasks as tools for Claude agents.
Apache Airflow
flytekitplugins-airflow
Airflow plugin allows you to seamlessly run Airflow tasks in the Flyte workflow without changing any code.
Async FSSpec
flytekitplugins-async-fsspec
The Flyte async fsspec plugin is a powerful addition to the Flyte ecosystem designed to optimize the performance of object transmission. This plugin focuses on overriding key methods of the file systems in fsspec to introduce efficiency improvements, resulting in accelerated data transfers between Flyte workflows and object storage.
AWS Athena
flytekitplugins-athena
Flyte backend can be connected with Athena. Once enabled, it allows you to query AWS Athena service (Presto + ANSI SQL Support) and retrieve typed schema (optionally).
AWS Batch
flytekitplugins-awsbatch
Flyte backend can be connected with AWS batch. Once enabled, it allows you to run flyte task on AWS batch service
AWS SageMaker
flytekitplugins-awssagemaker
The plugin currently features a SageMaker deployment connector.
Bigquery
flytekitplugins-bigquery
BigQuery enables us to build data-intensive applications without operational burden. Flyte backend can be connected with the BigQuery service. Once enabled, it can allow you to query a BigQuery table.
BigQuery
flyteplugins-bigquery
This plugin provides BigQuery integration for Flyte, enabling you to run BigQuery queries as Flyte tasks.
Comet ML
flytekitplugins-comet-ml
Comet’s machine learning platform integrates with your existing infrastructure and tools so you can manage, visualize, and optimize models—from training runs to production monitoring. This plugin integrates Flyte with Comet.ml by configuring links between the two platforms.
Dask
flytekitplugins-dask
Flyte can execute dask jobs natively on a Kubernetes Cluster, which manages the virtual dask cluster's lifecycle
flyteplugins-dask
Databricks
flyteplugins-databricks
This plugin provides Databricks integration for Flyte, enabling you to run Spark jobs on Databricks as Flyte tasks.
DBT
flytekitplugins-dbt
Flytekit plugin for performing DBT tasks. Currently it supports dbt run , dbt test, dbt source freshness tasks.
Deck
flytekitplugins-deck-standard
This plugin provides additional renderers to improve task visibility within Flytekit.
Dgxc-lepton
flytekitplugins-dgxc-lepton
A professional Flytekit plugin that enables seamless deployment and management of AI inference endpoints using Lepton AI infrastructure within Flyte workflows.
Dolt
flytekitplugins-dolt
The DoltTable plugin is a wrapper that uses Dolt to move data between pandas.DataFrame’s at execution time and database tables at rest.
DuckDB
flytekitplugins-duckdb
Run analytical workloads with ease using DuckDB.
Envd
flytekitplugins-envd
envd is a command-line tool that helps you create the container-based development environment for AI/ML.
Flyte Interactive
flytekitplugins-flyteinteractive
FlyteInteractive plugin provides users' favorite interface to develop and debug a flyte task interactively. We support vscode, jupyter (WIP), and neovim (WIP).
FSSpec
flytekitplugins-data-fsspec
This plugin provides an implementation of the data persistence layer in Flytekit that uses fsspec. Once this plugin
Geopandas
flytekitplugins-geopandas
GeoPandas GeoPandas is an open source project to make working with geospatial data in python easier.
Google Gemini
flyteplugins-gemini
This plugin provides integration between Flyte and Google's Gemini API, enabling you to use Flyte tasks as tools for Gemini agents.
Google IAP
flytekitplugins-identity_aware_proxy
GCP Identity Aware Proxy (IAP) is a managed Google Cloud Platform (GCP) service that makes it easy to protect applications deployed on GCP by verifying user identity and using context to determine whether a user should be granted access. Because requests to applications protected with IAP first have to pass IAP before they can reach the protected backends, IAP provides a convenient way to implement a zero-trust access model.
Great Expectations
flytekitplugins-great_expectations
Great Expectations helps enforce data quality. The plugin supports the usage of Great Expectations as task and type.
Hive
flytekitplugins-hive
Flyte backend can be connected with various Hive services. Once enabled, it allows you to query a Hive service (e.g., Qubole) and retrieve typed schema (optionally).
Hugging Face
flytekitplugins-huggingface
Hugging Face is a community and data science platform that provides: Tools that enable users to build, train and deploy ML models based on open source (OS) code and technologies
Human-in-the-Loop (HITL)
flyteplugins-hitl
Human-in-the-Loop (HITL) plugin for Flyte. This plugin provides an event-based API for pausing workflows and waiting for human input.
Inference
flytekitplugins-inference
Serve models natively in Flyte tasks using inference providers like NIM, Ollama, and others.
JSONL (JSON Lines) Type Plugin
flyteplugins-jsonl
JSONL (JSON Lines) file and directory types for Flyte, backed by orjson for
Kubeflow MPI
flytekitplugins-kfmpi
This plugin uses the Kubeflow MPI Operator and provides an extremely simplified interface for executing distributed training.
Kubeflow PyTorch
flytekitplugins-kfpytorch
This plugin uses the Kubeflow PyTorch Operator and provides an extremely simplified interface for executing distributed training using various PyTorch backends.
Kubeflow TensorFlow
flytekitplugins-kftensorflow
This plugin uses the Kubeflow TensorFlow Operator and provides an extremely simplified interface for executing distributed training using various TensorFlow backends.
Kubernetes Pod
flytekitplugins-pod
By default, Flyte tasks decorated with @task are essentially single functions that are loaded in one container. But often, there is a need to run a job with more than one container.
Kubernetes Stateful
flytekitplugins-k8sdataservice
This plugin provides support for Kubernetes StatefulSet and Service integration, enabling seamless provisioning and coordination with any Kubernetes services or Flyte tasks. It is especially suited for deep learning use cases at scale, where distributed and parallelized data loading and caching across nodes are required.
LLM-powered code generation and evaluation
flyteplugins-codegen
Generate code from natural language prompts and validate it by running tests in an isolated sandbox. Works with any model that supports structured outputs (GPT-4, Claude, Gemini, etc. via LiteLLM) or directly with the Agent SDK (Claude-only).
Memory Machine Cloud
flytekitplugins-mmcloud
Flyte Connector plugin to allow executing Flyte tasks using MemVerge Memory Machine Cloud.
Memray Profiling
flytekitplugins-memray
Memray tracks and reports memory allocations, both in python code and in compiled extension modules.
MLflow
flytekitplugins-mlflow
MLflow enables us to log parameters, code, and results in machine learning experiments and compare them using an interactive UI.
MLflow tracking
flyteplugins-mlflow
MLflow tracking plugin for Flyte
Modin
flytekitplugins-modin
Modin is a pandas-accelerator that helps handle large datasets. It is a light-weight extension that is similar to the pandas API. It uses the concept of parallelism to reduce overhead, and improve the performance of pandas operations by leveraging the compute resources available.
Neptune
flytekitplugins-neptune
Neptune is the MLOps stack component for experiment tracking. It offers a single place to log, compare, store, and collaborate on experiments and models. This plugin integrates Flyte with Neptune by configuring links between the two platforms.
OmegaConf
flytekitplugins-omegaconf
Flytekit python natively supports serialization of many data types for exchanging information between tasks.
ONNX PyTorch
flytekitplugins-onnxpytorch
This plugin allows you to generate ONNX models from your PyTorch models.
ONNX ScikitLearn
flytekitplugins-onnxscikitlearn
This plugin allows you to generate ONNX models from your ScikitLearn models.
ONNX TensorFlow
flytekitplugins-onnxtensorflow
This plugin allows you to generate ONNX models from your TensorFlow Keras models.
OpenAI
flytekitplugins-openai
The plugin currently features ChatGPT and Batch API connectors.
flyteplugins-openai
This plugin provides a drop-in replacement for OpenAI packages. It provides
Optuna (wrapper)
flytekitplugins-optuna
This documentation provides a guide to a fully parallelized Flyte plugin for Optuna. This wrapper leverages Flyte's scalable and distributed workflow orchestration capabilities to parallelize Optuna's hyperparameter optimization across multiple trials efficiently.
pandera
flyteplugins-pandera
flyteplugins-pandera adds support for pandera.typing.pandas.DataFrame, pandera.typing.polars.DataFrame / LazyFrame, and pandera.typing.pyspark_sql.DataFrame in Flyte v2.
Pandera
flytekitplugins-pandera
Flytekit python natively supports many data types, including a FlyteSchema type for type-annotating pandas DataFrames. The Flytekit Pandera plugin provides an alternative for defining DataFrame schemas by integrating with Pandera, a runtime data validation tool for pandas DataFrames.
Papermill
flytekitplugins-papermill
It is possible to run a Jupyter notebook as a Flyte task using Papermill. Papermill executes the notebook as a whole, so before using this plugin, it is essential to construct your notebook as recommended by Papermill.
Perian Job Platform
flytekitplugins-perian_job
Flyte Connector plugin for executing Flyte tasks on Perian Job Platform (perian.io).
polars
flyteplugins-polars
This plugin provides native support for Polars DataFrames and LazyFrames in Flyte, enabling efficient data processing with Polars' high-performance DataFrame library.
Polars
flytekitplugins-polars
Polars is a blazingly fast DataFrames library implemented in Rust using Apache Arrow Columnar Format as memory model.
pytorch
flyteplugins-pytorch
Union can execute PyTorch distributed training jobs natively on a Kubernetes Cluster, which manages the lifecycle of worker pods, rendezvous coordination, spin-up, and tear down. It leverages the open-sourced TorchElastic (torch.distributed.elastic) launcher and the Kubeflow PyTorch Operator, enabling fault-tolerant and elastic training across multiple nodes.
Ray
flytekitplugins-ray
Flyte backend can be connected with Ray. Once enabled, it allows you to run flyte task on Ray cluster
flyteplugins-ray
Union can execute Ray jobs natively on a Kubernetes Cluster,
SGLang
flyteplugins-sglang
Serve large language models using SGLang with Flyte Apps.
Slurm
flytekitplugins-slurm
The Slurm connector is designed to integrate Flyte workflows with Slurm-managed high-performance computing (HPC) clusters, enabling users to leverage Slurm's capability of compute resource allocation, scheduling, and monitoring.
Snowflake
flytekitplugins-snowflake
Snowflake enables us to build data-intensive applications without operational burden. Flyte backend can be connected with the Snowflake service. Once enabled, it can allow you to query a Snowflake service.
flyteplugins-snowflake
Run Snowflake SQL queries as Flyte tasks with parameterized inputs, key-pair authentication, batch inserts, and DataFrame support.
Spark
flytekitplugins-spark
Flyte can execute Spark jobs natively on a Kubernetes Cluster, which manages a virtual cluster’s lifecycle, spin-up, and tear down. It leverages the open-sourced Spark On K8s Operator and can be enabled without signing up for any service. This is like running a transient spark cluster — a type of cluster spun up for a specific Spark job and torn down after completion.
flyteplugins-spark
Union can execute Spark jobs natively on a Kubernetes Cluster, which manages a virtual cluster’s lifecycle, spin-up, and tear down. It leverages the open-sourced Spark On K8s Operator and can be enabled without signing up for any service. This is like running a transient spark cluster — a type of cluster spun up for a specific Spark job and torn down after completion.
SQLAlchemy
flytekitplugins-sqlalchemy
SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL. Flyte provides an easy-to-use interface to utilize SQLAlchemy to connect to various SQL Databases.
Vaex
flytekitplugins-vaex
Vaex is a high-performance Python library for lazy out-of-core DataFrames
vLLM
flyteplugins-vllm
Serve large language models using vLLM with Flyte Apps.
Weights & Biases
flytekitplugins-wandb
The Weights and Biases MLOps platform helps AI developers streamline their ML workflow from end-to-end. This plugin
flyteplugins-wandb
This plugin provides integration between Flyte and Weights & Biases (W&B) for experiment tracking, including support for distributed training with PyTorch Elastic.
whylogs
flytekitplugins-whylogs
whylogs is an open source library for logging any kind of data. With whylogs,
