start

Author: stevhliu

docs/source/en/_toctree.yml

@@ -112,6 +112,8 @@
   sections:
   - local: modular_diffusers/overview
     title: Overview
+  - local: modular_diffusers/end_to_end_guide
+    title: Quickstart
   - local: modular_diffusers/modular_pipeline
     title: Modular Pipeline
   - local: modular_diffusers/components_manager
@@ -126,12 +128,34 @@
     title: Loop Sequential Pipeline Blocks
   - local: modular_diffusers/auto_pipeline_blocks
     title: Auto Pipeline Blocks
-  - local: modular_diffusers/end_to_end_guide
-    title: End-to-End Example
-
-- title: Training
-  isExpanded: false
-  sections:
+  title: Modular Diffusers
+- sections:
+  - local: using-diffusers/consisid
+    title: ConsisID
+  - local: using-diffusers/sdxl
+    title: Stable Diffusion XL
+  - local: using-diffusers/sdxl_turbo
+    title: SDXL Turbo
+  - local: using-diffusers/kandinsky
+    title: Kandinsky
+  - local: using-diffusers/omnigen
+    title: OmniGen
+  - local: using-diffusers/pag
+    title: PAG
+  - local: using-diffusers/inference_with_lcm
+    title: Latent Consistency Model
+  - local: using-diffusers/shap-e
+    title: Shap-E
+  - local: using-diffusers/diffedit
+    title: DiffEdit
+  - local: using-diffusers/inference_with_tcd_lora
+    title: Trajectory Consistency Distillation-LoRA
+  - local: using-diffusers/svd
+    title: Stable Video Diffusion
+  - local: using-diffusers/marigold_usage
+    title: Marigold Computer Vision
+  title: Specific pipeline examples
+- sections:
   - local: training/overview
     title: Overview
   - local: training/create_dataset

docs/source/en/modular_diffusers/overview.md

@@ -10,33 +10,31 @@ an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express o
 specific language governing permissions and limitations under the License.
 -->
 
-# Getting Started with Modular Diffusers
+# Overview
 
-<Tip warning={true}>
+> [!WARNING]
+> ⚠︎ Modular Diffusers is still under active development and it's API may change.
 
-🧪 **Experimental Feature**: Modular Diffusers is an experimental feature we are actively developing. The API may be subject to breaking changes.
+Modular Diffusers is a unified pipeline system that simplifies your workflow with *pipeline blocks*.
 
-</Tip>
+- Blocks are reusable and you only create new blocks that are unique to your pipeline.
+- Blocks can be mixed and matched to adapt to or create a pipeline for a specific workflow or multiple workflows.
 
-With Modular Diffusers, we introduce a unified pipeline system that simplifies how you work with diffusion models. Instead of creating separate pipelines for each task, Modular Diffusers lets you:
+The Modular Diffusers docs are organized as shown below.
 
-**Write Only What's New**: You won't need to write an entire pipeline from scratch every time you have a new use case. You can create pipeline blocks just for your new workflow's unique aspects and reuse existing blocks for existing functionalities. 
+## Quickstart
 
-**Assemble Like LEGO®**: You can mix and match between blocks in flexible ways. This allows you to write dedicated blocks unique to specific workflows, and then assemble different blocks into a pipeline that can be used more conveniently for multiple workflows. 
+- A [quickstart](./end_to_end_guide) start for implementing an example workflow with Modular Diffusers.
 
+## ModularPipeline
 
-Here's how our guides are organized to help you navigate the Modular Diffusers documentation:
+- [ModularPipeline](./modular_pipeline) shows you how to build with pipeline blocks and convert them into an executable [`ModularPipeline`].
+- [ComponentsManager](./components_manager) shows you how to manage and reuse components across multiple pipelines.
 
-### 🚀 Running Pipelines
-- **[Modular Pipeline Guide](./modular_pipeline.md)** - How to use predefined blocks to build a pipeline and run it
-- **[Components Manager Guide](./components_manager.md)** - How to manage and reuse components across multiple pipelines
+## ModularPipelineBlocks
 
-### 📚 Creating PipelineBlocks
-- **[Pipeline and Block States](./modular_diffusers_states.md)** - Understanding PipelineState and BlockState
-- **[Pipeline Block](./pipeline_block.md)** - How to write custom PipelineBlocks
-- **[SequentialPipelineBlocks](sequential_pipeline_blocks.md)** - Connecting blocks in sequence
-- **[LoopSequentialPipelineBlocks](./loop_sequential_pipeline_blocks.md)** - Creating iterative workflows
-- **[AutoPipelineBlocks](./auto_pipeline_blocks.md)** - Conditional block selection
-
-### 🎯 Practical Examples
-- **[End-to-End Example](./end_to_end_guide.md)** - Complete end-to-end examples including sharing your workflow in huggingface hub and deplying UI nodes
+- [States](./modular_diffusers_states) explains how data is shared and communicated between pipeline blocks and [`ModularPipeline`].
+- [PipelineBlock](./pipeline_block) is the most basic unit of a [`ModularPipeline`] and this guide shows you how to create one.
+- [SequentialPipelineBlocks](./sequential_pipeline_blocks) is a type of block that chains multiple blocks so they run one after another, passing data along the chain. This guide shows you how to create [`SequentialPipelineBlocks`] and how they connect and work together.
+- [LoopSequentialPipelineBlocks](./loop_sequential_pipeline_blocks) is a type of block that runs a series of blocks in a loop. This guide shows you how to create [`LoopSequentialPipelineBlocks`].
+- [AutoPipelineBlocks](./auto_pipeline_blocks) is a type of block that automatically chooses which blocks to run based on the input. This guide shows you how to create [`AutoPipelineBlocks`].

src/diffusers/__init__.py

@@ -61,6 +61,12 @@
         "is_unidecode_available",
         "logging",
     ],
+    "image_processor": [
+        "VaeImageProcessor",
+    ],
+    "video_processor": [
+        "VideoProcessor",
+    ],
 }
 
 try: