feat: add Custom Node Manager

docs/nodes/creatingNodePack.md

@@ -0,0 +1,154 @@
+# Creating a Node Pack for the Custom Node Manager
+
+This guide explains how to structure your Git repository so it can be installed via InvokeAI's Custom Node Manager.
+
+## Repository Structure
+
+Your repository **is** the node pack. When a user installs it, the entire repo is cloned into the `nodes` directory.
+
+### Minimum Required Structure
+
+```
+my-node-pack/
+├── __init__.py          # Required: imports your node classes
+├── my_node.py           # Your node implementation(s)
+└── README.md            # Recommended: describe your nodes
+```
+
+The `__init__.py` at the root is **mandatory**. Without it, the pack will not be loaded.
+
+### Recommended Structure
+
+```
+my-node-pack/
+├── __init__.py          # Imports all node classes
+├── requirements.txt     # Python dependencies (user-installed)
+├── README.md            # Description, usage, examples
+├── node_one.py          # Node implementation
+├── node_two.py          # Node implementation
+├── utils.py             # Shared utilities
+└── workflows/           # Optional: workflow files
+    ├── example_workflow.json
+    └── advanced_workflow.json
+```
+
+## The `__init__.py` File
+
+This file must import all invocation classes you want to register. Only classes imported here will be available in InvokeAI.
+
+```python
+from .node_one import MyFirstInvocation
+from .node_two import MySecondInvocation
+```
+
+If you have nodes in subdirectories:
+
+```python
+from .nodes.image_tools import CropInvocation, ResizeInvocation
+from .nodes.text_tools import ConcatInvocation
+```
+
+## Dependencies (`requirements.txt` or `pyproject.toml`)
+
+If your nodes require additional Python packages, list them in a `requirements.txt` (or `pyproject.toml`) at the repository root:
+
+```
+numpy>=1.24
+opencv-python>=4.8
+```
+
+The Custom Node Manager **does not** install these dependencies automatically — auto-installing into the running InvokeAI environment risks pulling in incompatible versions and breaking the application. After install, the UI shows the user a toast telling them that manual installation is required, and your README should document the exact install command (e.g. `pip install -r requirements.txt` from inside an activated InvokeAI environment).
+
+**Important:** Avoid pinning versions too tightly. InvokeAI has its own dependencies, and version conflicts can cause issues. Use minimum version constraints (`>=`) where possible.
+
+## Including Workflows
+
+If your repository contains workflow `.json` files, they will be **automatically imported** into the user's workflow library during installation.
+
+### Workflow Detection
+
+The installer recursively scans your repository for `.json` files. A file is recognized as a workflow if it contains both `nodes` and `edges` keys at the top level.
+
+### Tagging
+
+Imported workflows are automatically tagged with `node-pack:<your-repo-name>` so users can filter for them in the workflow library. When the node pack is uninstalled, these workflows are also removed.
+
+### Workflow Format
+
+Workflows should follow the standard InvokeAI workflow format:
+
+```json
+{
+  "name": "My Example Workflow",
+  "author": "Your Name",
+  "description": "Demonstrates how to use MyFirstInvocation",
+  "version": "1.0.0",
+  "contact": "",
+  "tags": "example, my-node-pack",
+  "notes": "",
+  "meta": {
+    "version": "3.0.0",
+    "category": "user"
+  },
+  "exposedFields": [],
+  "nodes": [...],
+  "edges": [...]
+}
+```
+
+**Tip:** The easiest way to create a workflow file is to build the workflow in InvokeAI's workflow editor, then export it via **Save As** and copy the `.json` file into your repository.
+
+## Node Implementation
+
+Each node is a Python class decorated with `@invocation()`. Here's a minimal example:
+
+```python
+from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
+from invokeai.app.invocations.fields import InputField, OutputField
+from invokeai.invocation_api import BaseInvocationOutput, invocation_output
+
+
+@invocation_output("my_output")
+class MyOutput(BaseInvocationOutput):
+    result: str = OutputField(description="The result")
+
+
+@invocation(
+    "my_node",
+    title="My Node",
+    tags=["example", "custom"],
+    category="custom",
+    version="1.0.0",
+)
+class MyInvocation(BaseInvocation):
+    """Does something useful."""
+
+    input_text: str = InputField(default="", description="Input text")
+
+    def invoke(self, context) -> MyOutput:
+        return MyOutput(result=f"Processed: {self.input_text}")
+```
+
+For full details on the invocation API, see the [Invocation API documentation](invocation-api.md).
+
+## Best Practices
+
+- **Use a descriptive repository name** — it becomes the pack name shown in the UI
+- **Include a README.md** with description, screenshots, and usage instructions
+- **Version your nodes** using semver in the `@invocation()` decorator
+- **Don't include large binary files** in your repository (models, weights, etc.)
+- **Test your nodes** by placing the repo in the `nodes` directory before publishing
+- **Include example workflows** so users can get started quickly
+- **Tag your GitHub repository** with `invokeai-node` for discoverability
+- **Avoid name collisions** — choose unique invocation type strings (e.g. `my_pack_resize` instead of just `resize`)
+
+## Testing Your Pack
+
+Before publishing, verify your pack works with the Custom Node Manager:
+
+1. Create a Git repository with your node pack
+2. Push it to GitHub (or any Git host)
+3. In InvokeAI, go to the Nodes tab and install it via the Git URL
+4. Verify your nodes appear in the workflow editor
+5. Verify any included workflows are imported
+6. Test uninstalling — nodes and workflows should be removed

docs/nodes/customNodeManager.md

@@ -0,0 +1,78 @@
+# Custom Node Manager
+
+The Custom Node Manager allows you to install, manage, and remove community node packs directly from the InvokeAI UI — no manual file copying required.
+
+## Accessing the Node Manager
+
+Click the **Nodes** tab (circuit icon) in the left sidebar, between Models and Queue.
+
+## Installing a Node Pack
+
+1. Navigate to the **Nodes** tab
+2. On the right panel, select the **Git Repository URL** tab
+3. Paste the Git URL of the node pack (e.g. `https://github.com/user/my-node-pack.git`)
+4. Click **Install**
+
+The installer will:
+
+- Clone the repository into your `nodes` directory
+- Load the nodes immediately — no restart needed
+- Import any workflow `.json` files found in the repository into your workflow library (tagged with `node-pack:<name>` for easy filtering)
+
+The install progress and results are shown in the **Install Log** at the bottom of the panel.
+
+### Installing Python Dependencies
+
+The installer does **not** automatically run `pip install` for `requirements.txt` or `pyproject.toml`. Auto-installing dependencies into the running InvokeAI environment can pull in incompatible package versions and break the application.
+
+If a node pack ships a `requirements.txt` or `pyproject.toml`, you'll see a warning toast after installation. Install the dependencies yourself by following the instructions in the node pack's documentation (typically `pip install -r requirements.txt` from inside an activated InvokeAI environment, but check the pack's README first). After installing, click the **Reload** button so the new dependencies take effect.
+
+### Security Warning
+
+Custom nodes execute arbitrary Python code on your system. **Only install node packs from authors you trust.** Malicious nodes could harm your system or compromise your data.
+
+## Managing Installed Nodes
+
+The left panel shows all installed node packs with:
+
+- **Pack name**
+- **Number of nodes** provided
+- **Individual node types** as badges
+- **File path** on disk
+
+### Reloading Nodes
+
+Click the **Reload** button to re-scan the nodes directory. This picks up any node packs that were manually added to the directory without using the installer.
+
+### Uninstalling a Node Pack
+
+Click the **Uninstall** button on any node pack. This will:
+
+- Remove the node pack directory
+- Unregister the nodes from the system immediately
+- Remove any workflows that were imported from the pack
+- Update the workflow editor so the nodes are no longer available
+
+No restart is required.
+
+## Scan Folder Tab
+
+The **Scan Folder** tab shows the location of your nodes directory. Node packs placed there manually (e.g. via `git clone`) are automatically detected at startup. Use the **Reload** button to detect newly added packs without restarting.
+
+## Troubleshooting
+
+### Node pack fails to install
+
+- Verify the Git URL is correct and accessible
+- Check that the repository contains an `__init__.py` file at the top level
+- Review the Install Log for error details
+
+### Nodes don't appear after install
+
+- Click the **Reload** button
+- Check that the node pack's `__init__.py` imports its node classes
+- Check the server console for error messages
+
+### Workflows show errors after uninstalling
+
+If you have user-created workflows that reference nodes from an uninstalled pack, those workflows will show errors for the missing node types. Reinstall the pack or remove the affected nodes from the workflow.