Pushing to prod PR#511 onward

README.md

@@ -8,9 +8,9 @@ This is the home for the user-facing documentation and related infrastructure fo
 
 We believe in the power of collaboration and welcome contributions from the community. If you've noticed an issue or have ideas for improvement, please create a pull request or submit an issue. A member of ValidMind's documentation team will review your suggestions and support you in contributing to the docs. 
 
-- Follow the [Quickstart](https://docs.validmind.ai/get-started/developer/try-with-jupyterhub.html) for a 15-minute introduction to the Developer Framework and ValidMind Platform.
+- Follow the [Quickstart](https://docs.validmind.ai/get-started/developer/try-with-jupyterhub.html) for a 15-minute introduction to the ValidMind Library and ValidMind Platform.
 
-- Read the [Developer Framework docs](https://docs.validmind.ai/developer/get-started-developer-framework.html) for more information about ValidMind's open source tests and Jupyter notebooks.
+- Read the [ValidMind Library docs](https://docs.validmind.ai/developer/get-started-validmind-library.html) for more information about ValidMind's open source tests and Jupyter notebooks.
 
 - Join the [Community Slack](https://docs.validmind.ai/about/contributing/join-community.html) to ask questions, get support, and connect with Model Risk Management (MRM) practioners.
 

internal/templates/jupyter-notebooks/about-validmind.ipynb

@@ -0,0 +1,63 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## About ValidMind\n",
+    "\n",
+    "ValidMind is a suite of tools for managing model risk, including risk associated with AI and statistical models. \n",
+    "\n",
+    "You use the ValidMind Library to automate documentation and validation tests, and then use the ValidMind Platform to collaborate on model documentation. Together, these products simplify model risk management, facilitate compliance with regulations and institutional standards, and enhance collaboration between yourself and model validators.\n",
+    "\n",
+    "### Before you begin\n",
+    "\n",
+    "This notebook assumes you have basic familiarity with Python, including an understanding of how functions work. If you are new to Python, you can still run the notebook but we recommend further familiarizing yourself with the language. \n",
+    "\n",
+    "If you encounter errors due to missing modules in your Python environment, install the modules with `pip install`, and then re-run the notebook. For more help, refer to [Installing Python Modules](https://docs.python.org/3/installing/index.html).\n",
+    "\n",
+    "### New to ValidMind?\n",
+    "\n",
+    "If you haven't already seen our [Get started with the ValidMind Library](https://docs.validmind.ai/guide/get-started-validmind-library.html), we recommend you explore the available resources for developers at some point. There, you can learn more about documenting models, find code samples, or read our developer reference.\n",
+    "\n",
+    "<div class=\"alert alert-block alert-info\" style=\"background-color: #B5B5B510; color: black; border: 1px solid #083E44; border-left-width: 5px; box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.2);border-radius: 5px;\"><span style=\"color: #083E44;\"><b>For access to all features available in this notebook, create a free ValidMind account.</b></span>\n",
+    "<br></br>\n",
+    "Signing up is FREE — <a href=\"https://docs.validmind.ai/guide/configuration/register-with-validmind.html\" style=\"color: #DE257E;\"><b>Register with ValidMind</b></a></div>\n",
+    "\n",
+    "### Key concepts\n",
+    "\n",
+    "**Model documentation**: A structured and detailed record pertaining to a model, encompassing key components such as its underlying assumptions, methodologies, data sources, inputs, performance metrics, evaluations, limitations, and intended uses. It serves to ensure transparency, adherence to regulatory requirements, and a clear understanding of potential risks associated with the model’s application.\n",
+    "\n",
+    "**Documentation template**: Functions as a test suite and lays out the structure of model documentation, segmented into various sections and sub-sections. Documentation templates define the structure of your model documentation, specifying the tests that should be run, and how the results should be displayed.\n",
+    "\n",
+    "**Tests**: A function contained in the ValidMind Library, designed to run a specific quantitative test on the dataset or model. Tests are the building blocks of ValidMind, used to evaluate and document models and datasets, and can be run individually or as part of a suite defined by your model documentation template.\n",
+    "\n",
+    "**Metrics**: A subset of tests that do not have thresholds. In the context of this notebook, metrics and tests can be thought of as interchangeable concepts.\n",
+    "\n",
+    "**Custom metrics**: Custom metrics are functions that you define to evaluate your model or dataset. These functions can be registered with the ValidMind Library to be used in the ValidMind Platform.\n",
+    "\n",
+    "**Inputs**: Objects to be evaluated and documented in the ValidMind Library. They can be any of the following:\n",
+    "\n",
+    "  - **model**: A single model that has been initialized in ValidMind with [`vm.init_model()`](/validmind/validmind.html#init_model).\n",
+    "  - **dataset**: Single dataset that has been initialized in ValidMind with [`vm.init_dataset()`](/validmind/validmind.html#init_dataset).\n",
+    "  - **models**: A list of ValidMind models - usually this is used when you want to compare multiple models in your custom metric.\n",
+    "  - **datasets**: A list of ValidMind datasets - usually this is used when you want to compare multiple datasets in your custom metric. See this [example](/notebooks/how_to/run_tests_that_require_multiple_datasets.ipynb) for more information.\n",
+    "\n",
+    "**Parameters**: Additional arguments that can be passed when running a ValidMind test, used to pass additional information to a metric, customize its behavior, or provide additional context.\n",
+    "\n",
+    "**Outputs**: Custom metrics can return elements like tables or plots. Tables may be a list of dictionaries (each representing a row) or a pandas DataFrame. Plots may be matplotlib or plotly figures.\n",
+    "\n",
+    "**Test suites**: Collections of tests designed to run together to automate and generate model documentation end-to-end for specific use-cases.\n",
+    "\n",
+    "Example: the [`classifier_full_suite`](/validmind/validmind/test_suites/classifier.html#ClassifierFullSuite) test suite runs tests from the [`tabular_dataset`](/validmind/validmind/test_suites/tabular_datasets.html) and [`classifier`](/validmind/validmind/test_suites/classifier.html) test suites to fully document the data and model sections for binary classification model use-cases."
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

internal/templates/jupyter-notebooks/install-initialize-validmind.ipynb

@@ -0,0 +1,75 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Install the ValidMind Library\n",
+    "\n",
+    "To install the library:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install -q validmind"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Initialize the ValidMind Library\n",
+    "\n",
+    "ValidMind generates a unique _code snippet_ for each registered model to connect with your developer environment. You initialize the ValidMind Library with this code snippet, which ensures that your documentation and tests are uploaded to the correct model when you run the notebook.\n",
+    "\n",
+    "### Get your code snippet\n",
+    "\n",
+    "1. In a browser, [log in to ValidMind](https://docs.validmind.ai/guide/configuration/log-in-to-validmind.html).\n",
+    "\n",
+    "2. In the left sidebar, navigate to **Model Inventory** and click **+ Register new model**.\n",
+    "\n",
+    "3. Enter the model details and click **Continue**. ([Need more help?](https://docs.validmind.ai/guide/model-inventory/register-models-in-inventory.html))\n",
+    "\n",
+    "   For example, to register a model for use with this notebook, select:\n",
+    "\n",
+    "   - Documentation template: `Template name here`\n",
+    "   - Use case: `Use case here`\n",
+    "\n",
+    "   You can fill in other options according to your preference.\n",
+    "\n",
+    "4. Go to **Getting Started** and click **Copy snippet to clipboard**.\n",
+    "\n",
+    "Next, replace this placeholder with your own code snippet:\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Replace with your code snippet\n",
+    "\n",
+    "import validmind as vm\n",
+    "\n",
+    "vm.init(\n",
+    "    api_host=\"https://api.prod.validmind.ai/api/v1/tracking\",\n",
+    "    api_key=\"...\",\n",
+    "    api_secret=\"...\",\n",
+    "    model=\"...\",\n",
+    ")"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}