update links to autogenerated flytesnacks pages

README.md

@@ -117,25 +117,25 @@ To dig deeper into Flyte, refer to the [Documentation](https://docs.flyte.org/en
 - Supports multiple **[data types](https://docs.flyte.org/projects/cookbook/en/latest/core.html)** for machine learning and data processing pipelines, such as Blobs (images, arbitrary files), Directories, Schema (columnar structured data), collections, maps etc.
 - Memoization and Lineage tracking
 - Workflow features:
-  - Start with one task, convert to a pipeline, attach **[multiple schedules](https://docs.flyte.org/projects/cookbook/en/latest/auto_core_remote_flyte/lp_schedules.html)**, trigger using a programmatic API, or on-demand
+  - Start with one task, convert to a pipeline, attach **[multiple schedules](https://docs.flyte.org/projects/cookbook/en/latest/auto/deployment/workflow/lp_schedules.html)**, trigger using a programmatic API, or on-demand
   - Parallel step execution
-  - Extensible backend to add [customized plugin](https://docs.flyte.org/projects/cookbook/en/latest/auto_core_advanced/custom_task_plugin.html) experience (with simplified user experience)
-  - **[Branching](https://docs.flyte.org/projects/cookbook/en/latest/auto_core_intermediate/run_conditions.html)**
-  - Inline **[subworkflows](https://docs.flyte.org/projects/cookbook/en/latest/auto_core_intermediate/subworkflows.html)** (a workflow can be embeded within one node of the top level workflow)
+  - Extensible backend to add **[customized plugin](https://docs.flyte.org/projects/cookbook/en/latest/auto/core/extend_flyte/custom_task_plugin.html)** experience (with simplified user experience)
+  - **[Branching](https://docs.flyte.org/projects/cookbook/en/latest/auto/core/control_flow/run_conditions.html)**
+  - Inline **[subworkflows](https://docs.flyte.org/projects/cookbook/en/latest/auto/core/control_flow/subworkflows.html)** (a workflow can be embeded within one node of the top level workflow)
   - Distributed **remote child workflows** (a remote workflow can be triggered and statically verified at compile time)
-  - **[Array Tasks](https://docs.flyte.org/projects/cookbook/en/latest/auto_core_intermediate/map_task.html)** (map a function over a large dataset -- ensures controlled execution of thousands of containers)
-  - **[Dynamic workflow](https://docs.flyte.org/projects/cookbook/en/latest/auto_core_intermediate/dynamics.html)** creation and execution with runtime type safety
+  - **[Array Tasks](https://docs.flyte.org/projects/cookbook/en/latest/auto/core/control_flow/map_task.html)** (map a function over a large dataset -- ensures controlled execution of thousands of containers)
+  - **[Dynamic workflow](https://docs.flyte.org/projects/cookbook/en/latest/auto/core/control_flow/dynamics.html)** creation and execution with runtime type safety
   - Container side [plugins](https://docs.flyte.org/projects/cookbook/en/latest/plugins.html) with first class support in Python
-  - _PreAlpha_: Arbitrary flytekit-less containers supported ([RawContainer](https://docs.flyte.org/projects/cookbook/en/latest/auto_core_intermediate/raw_container.html))
-- Guaranteed **[reproducibility](https://docs.flyte.org/projects/cookbook/en/latest/auto_core_basic/task_cache.html)** of pipelines via:
+  - _PreAlpha_: Arbitrary flytekit-less containers supported ([RawContainer](https://docs.flyte.org/projects/cookbook/en/latest/auto/core/containerization/raw_container.html))
+- Guaranteed **[reproducibility](https://docs.flyte.org/projects/cookbook/en/latest/auto/core/flyte_basics/task_cache.html)** of pipelines via:
   - Versioned data, code and models
   - Automatically tracked executions
   - Declarative pipelines
 - **Multi cloud support** (AWS, GCP and others)
 - Extensible core, modularized, and deep observability
 - Automated notifications to Slack, Email, and Pagerduty
-- [Multi K8s cluster support](https://docs.flyte.org/projects/cookbook/en/latest/auto_plugins_pod/index.html)
-- Out of the box support to run **[Spark jobs on K8s](https://docs.flyte.org/projects/cookbook/en/latest/auto_plugins_k8s_spark/index.html)**, **[Hive queries](https://docs.flyte.org/projects/cookbook/en/latest/auto_plugins_hive/index.html)**, etc.
+- [Multi K8s cluster support](https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/kubernetes/pod/index.html)
+- Out of the box support to run **[Spark jobs on K8s](https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/kubernetes/k8s_spark/index.html)**, **[Hive queries](https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/external_services/hive/index.html)**, etc.
 - Snappy Console
 - Python CLI and Golang CLI (flytectl)
 - Written in **Golang** and optimized for large running jobs' performance
@@ -150,17 +150,17 @@ To dig deeper into Flyte, refer to the [Documentation](https://docs.flyte.org/en
 ## 🔌 Available Plugins
 
 - Containers
-- [K8s Pods](https://docs.flyte.org/projects/cookbook/en/latest/auto_plugins_pod/index.html)
+- [K8s Pods](https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/kubernetes/pod/index.html)
 - AWS Batch Arrays
 - K8s Pod Arrays
-- K8s Spark (native [Pyspark](https://docs.flyte.org/projects/cookbook/en/latest/auto_plugins_k8s_spark/index.html) and Java/Scala)
+- K8s Spark (native [Pyspark](https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/kubernetes/k8s_spark/index.html) and Java/Scala)
 - AWS Athena
-- [Qubole Hive](https://docs.flyte.org/projects/cookbook/en/latest/auto_plugins_hive/index.html)
+- [Qubole Hive](https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/external_services/hive/index.html)
 - Presto Queries
-- Distributed Pytorch (K8s Native) -- [Pytorch Operator](https://docs.flyte.org/projects/cookbook/en/latest/auto_plugins_kfpytorch/index.html)
-- Sagemaker([builtin algorithms](https://docs.flyte.org/projects/cookbook/en/latest/auto_plugins_sagemaker_training/sagemaker_builtin_algo_training.html) & [custom models](https://docs.flyte.org/projects/cookbook/en/latest/auto_plugins_sagemaker_training/sagemaker_custom_training.html))
-- Distributed Tensorflow (K8s Native) - TFOperator
-- Papermill notebook execution ([Python](https://github.com/lyft/flytekit/tree/master/plugins/papermill) and Spark)
+- Distributed Pytorch (K8s Native) -- [Pytorch Operator](https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/kubernetes/kfpytorch/index.html)
+- Sagemaker([builtin algorithms](https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/aws/sagemaker_training/sagemaker_builtin_algo_training.html) & [custom models](https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/aws/sagemaker_training/sagemaker_custom_training.html))
+- Distributed Tensorflow (K8s Native) - [TFOperator](https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/kubernetes/kftensorflow/index.html)
+- Papermill notebook execution ([Python](https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/flytekit_plugins/papermilltasks/index.html) and Spark)
 - Type safe and data checking for Pandas dataframe using Pandera
 
 ### In Queue

rsts/howto/enable_and_use_schedules.rst

@@ -98,7 +98,7 @@ assigned to the ``triggered_time`` input you could define the following launch p
         fixed_inputs={"an_input": 3},
     )
 
-Please see a more complete example in the :std:ref:`cookbook <cookbook:Scheduling workflow executions with launch plans>`.
+Please see a more complete example in the :std:ref:`User Guide <cookbook:sphx_glr_auto_deployment_workflow_lp_schedules.py>`.
 
 Activating a schedule
 =====================

rsts/howto/launchplans.rst

@@ -13,7 +13,7 @@ When to use launchplans?
 - I want to share my workflow to another user but also make sure that some inputs can be overridden if needed.
 - I want to share my workflow with another user but make sure that some inputs are never changed.
 
-For preliminary examples on using launch plans in code, check out the canonical :std:ref:`cookbook <cookbook:launch_plans>` examples.
+For preliminary examples on using launch plans in code, check out the canonical :std:ref:`User Guide <cookbook:sphx_glr_auto_core_flyte_basics_lp.py>` examples.
 
 Partial Inputs for Launchplans
 ==============================

rsts/howto/notifications.rst

@@ -30,7 +30,7 @@ For example
     # This launch plan triggers email notifications when the workflow execution it triggered reaches the phase `SUCCEEDED`.
     my_notifiying_lp = LaunchPlan.create(
         "my_notifiying_lp",
-        my_workflow_defintiion,
+        my_workflow_definition,
         default_inputs={"a": 4},
         notifications=[
             Email(
@@ -41,7 +41,7 @@ For example
     )
 
 
-See detailed usage examples in the :std:ref:`cookbook <cookbook:Getting notifications on workflow termination>`
+See detailed usage examples in the :std:ref:`User Guide <cookbook:sphx_glr_auto_deployment_workflow_lp_notifications.py>`
 
 Notifications can be combined with schedules to automatically alert you when a scheduled job succeeds or fails.
 

rsts/index.rst

@@ -56,7 +56,7 @@ Meet Flyte
 
 .. raw:: html
 
-   <p style="color: #808080; font-weight: 350; font-size: 25px; padding: 0 10% 0 10%; padding-top: 10px; padding-bottom: 10px;"> The workflow automation platform for complex, mission-critical data and ML processes at scale </p>
+   <p style="color: #808080; font-weight: 350; font-size: 25px; padding-top: 10px; padding-bottom: 10px;"> The workflow automation platform for complex, mission-critical data and ML processes at scale </p>
 
 
 Flyte is an open-source, container-native, structured programming and distributed processing platform. It enables highly concurrent, scalable and maintainable workflows for machine learning and data processing.

rsts/plugins/spark_k8s.rst

@@ -48,7 +48,7 @@ You can optionally configure the Plugin as per the - `backend Config Structure <
 
 Spark in Flytekit
 ========================
-For a more complete example refer to :std:ref:`Cookbook Spark Plugin <sphx_glr_auto_plugins_k8s_spark>`
+For a more complete example refer to the :std:ref:`User Guide <cookbook:sphx_glr_auto_integrations_kubernetes_k8s_spark>`
 
 #. Ensure you have ``flytekit>=0.16.0``
 #. Enable Spark in backend, following the previous section.