submit-to-store

docs/docs/contributing/contribute-component.md

@@ -1,20 +1,47 @@
+import ZoomableImage from "/src/theme/ZoomableImage.js";
+
 # How to contribute components?
 
 As of Langflow 1.0 alpha, new components are added as objects of the [CustomComponent](https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/interface/custom/custom_component/custom_component.py) class and any dependencies are added to the [pyproject.toml](https://github.com/langflow-ai/langflow/blob/dev/pyproject.toml#L27) file.
 
 ## Add an example component
 
-You have a new document loader called **MyCustomEmbedding** and it would look awesome in Langflow.
+You have a new document loader called **MyCustomDocumentLoader** and it would look awesome in Langflow.
 
-1. Write your loader as an object of the [CustomComponent](https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/interface/custom/custom_component/custom_component.py) class. You'll create a new class, `MyCustomEmbeddingComponent`, that will inherit from `CustomComponent` and override the base class's methods.
+1. Write your loader as an object of the [CustomComponent](https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/interface/custom/custom_component/custom_component.py) class. You'll create a new class, `MyCustomDocumentLoader`, that will inherit from `CustomComponent` and override the base class's methods.
 2. Define optional attributes like `display_name`, `description`, and `documentation` to provide information about your custom component.
 3. Implement the `build_config` method to define the configuration options for your custom component.
 4. Implement the `build` method to define the logic for taking input parameters specified in the `build_config` method and returning the desired output.
 5. Add the code to the [/components/document_loaders](https://github.com/langflow-ai/langflow/tree/dev/src/backend/base/langflow/components) folder.
-6. Add the dependency to [/document_loaders/\_\_init\_\_.py](https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/components/documentloaders/__init__.py) as `from .MyCustomEmbedding import MyCustomEmbeddingComponent`.
+6. Add the dependency to [/document_loaders/\_\_init\_\_.py](https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/components/documentloaders/__init__.py) as `from .MyCustomEmbedding import MyCustomDocumentLoader`.
 7. Add any new dependencies to the outer [pyproject.toml](https://github.com/langflow-ai/langflow/blob/dev/pyproject.toml#L27) file.
+8. Submit documentation for your component. For this example, you'd submit documentation to the [loaders page](https://github.com/langflow-ai/langflow/blob/dev/docs/docs/components/loaders.mdx).
 8. Submit your changes as a pull request. The Langflow team will have a look, suggest changes, and add your component to Langflow.
 
-
+## User Sharing
+
+You might want to share and test your custom component with others, but don't need it merged into the main source code.
+
+If so, you can share your component on the Langflow store.
+
+1. [Register at the Langflow store](https://www.langflow.store/login/).
+2. Undergo pre-validation before receiving an API key.
+3. To deploy your amazing component directly to the Langflow store, without it being merged into the main source code, navigate to your flow, and then click **Share**.
+The share window appears:
+
+<ZoomableImage
+  alt="Docusaurus themed image"
+  sources={{
+    light: "img/add-component-to-store.png",
+    dark: "img/add-component-to-store.png",
+  }}
+  style={{ width: "50%", margin: "20px auto" }}
+/>
+
+5. Choose whether you want to flow to be public or private.
+You can also **Export** your flow as a JSON file from this window.
+When you're ready to share the flow, click **Share Flow**.
+You should see a **Flow shared successfully** popup.
+6. To confirm, navigate to the **Langflow Store** and filter results by **Created By Me**. You should see your new flow on the **Langflow Store**.