Add references to standalone examples and notebooks

docs/content/docs/agent-sdk/agent-loops.mdx

@@ -3,6 +3,8 @@ title: Agent Loops
 description: Supported computer-using agent loops and models
 ---
 
+<Callout>A corresponding <a href="https://github.com/trycua/cua/blob/main/notebooks/agent_nb.ipynb" target="_blank">Jupyter Notebook</a> is available for this documentation.</Callout>
+
 An agent can be thought of as a loop - it generates actions, executes them, and repeats until done:
 
 1. **Generate**: Your `model` generates `output_text`, `computer_call`, `function_call`

docs/content/docs/agent-sdk/integrations/hud.mdx

@@ -3,6 +3,8 @@ title: HUD Evals
 description: Use ComputerAgent with HUD for benchmarking and evaluation
 ---
 
+<Callout>A corresponding <a href="https://github.com/trycua/cua/blob/main/notebooks/eval_osworld.ipynb" target="_blank">Jupyter Notebook</a> is available for this documentation.</Callout>
+
 The HUD integration allows an agent to be benchmarked using the [HUD framework](https://www.hud.so/). Through the HUD integration, the agent controls a computer inside HUD, where tests are run to evaluate the success of each task.
 
 ## Installation

docs/content/docs/computer-sdk/computers.mdx

@@ -3,6 +3,8 @@ title: Cua Computers
 description: Understanding cua computer types and connection methods
 ---
 
+<Callout>A corresponding <a href="https://github.com/trycua/cua/blob/main/notebooks/computer_nb.ipynb" target="_blank">Jupyter Notebook</a> and <a href="https://github.com/trycua/cua/tree/main/examples/computer-example-ts" target="_blank">NodeJS project</a> are available for this documentation.</Callout>
+
 Before we can automate apps using AI, we need to first connect to a Computer Server to give the AI a safe environment to execute workflows in.
 
 Cua Computers are preconfigured virtual machines running the Computer Server. They can be either macOS, Linux, or Windows. They're found in either a cloud-native container, or on your host desktop.

docs/content/docs/computer-sdk/sandboxed-python.mdx

@@ -3,6 +3,8 @@ title: Sandboxed Python
 slug: sandboxed-python
 ---
 
+<Callout>A corresponding <a href="https://github.com/trycua/cua/blob/main/examples/sandboxed_functions_examples.py" target="_blank">Python example</a> is available for this documentation.</Callout>
+
 You can run Python functions securely inside a sandboxed virtual environment on a remote Cua Computer. This is useful for executing untrusted user code, isolating dependencies, or providing a safe environment for automation tasks.
 
 ## How It Works

docs/content/docs/libraries/computer-server/index.mdx

@@ -6,6 +6,8 @@ github:
   - https://github.com/trycua/cua/tree/main/libs/python/computer-server
 ---
 
+<Callout>A corresponding <a href="https://github.com/trycua/cua/blob/main/notebooks/computer_server_nb.ipynb" target="_blank">Jupyter Notebook</a> is available for this documentation.</Callout>
+
 The Computer Server API reference documentation is currently under development.
 
 ## Overview

docs/content/docs/libraries/som/index.mdx

@@ -6,6 +6,8 @@ github:
   - https://github.com/trycua/cua/tree/main/libs/python/som
 ---
 
+<Callout>A corresponding <a href="https://github.com/trycua/cua/blob/main/examples/som_examples.py" target="_blank">Python example</a> is available for this documentation.</Callout>
+
 ## Overview
 
 The SOM library provides visual element detection and interaction capabilities. It is based on the [Set-of-Mark](https://arxiv.org/abs/2310.11441) research paper and the [OmniParser](https://github.com/microsoft/OmniParser) model.