fix all broken backlinks

blog/build-your-own-operator-on-macos-1.md

@@ -8,7 +8,7 @@ In this first blogpost, we'll learn how to build our own Computer-Use Operator u
 - **computer-use-preview** is OpenAI's specialized language model trained to understand and interact with computer interfaces through screenshots.
 - A **Computer-Use Agent** is an AI agent that can control a computer just like a human would - clicking buttons, typing text, and interacting with applications.
 
-Our Operator will run in an isolated macOS VM, by making use of our [cua-computer](https://github.com/trycua/cua/tree/main/libs/computer) package and [lume virtualization CLI](https://github.com/trycua/cua/tree/main/libs/lume).
+Our Operator will run in an isolated macOS VM, by making use of our [cua-computer](https://github.com/trycua/cua/tree/main/libs/python/computer) package and [lume virtualization CLI](https://github.com/trycua/cua/tree/main/libs/lume).
 
 Check out what it looks like to use your own Operator from a Gradio app:
 
@@ -567,10 +567,10 @@ In a production setting, you would wrap the action-response cycle in a loop, han
 
 ### Next Steps
 
-In the next blogpost, we'll introduce our Agent framework which abstracts away all these tedious implementation steps. This framework provides a higher-level API that handles the interaction loop between OpenAI's computer-use model and the macOS sandbox, allowing you to focus on building sophisticated applications rather than managing the low-level details we've explored here. Can't wait? Check out the [cua-agent](https://github.com/trycua/cua/tree/main/libs/agent) package!
+In the next blogpost, we'll introduce our Agent framework which abstracts away all these tedious implementation steps. This framework provides a higher-level API that handles the interaction loop between OpenAI's computer-use model and the macOS sandbox, allowing you to focus on building sophisticated applications rather than managing the low-level details we've explored here. Can't wait? Check out the [cua-agent](https://github.com/trycua/cua/tree/main/libs/python/agent) package!
 
 ### Resources
 
 - [OpenAI Computer-Use docs](https://platform.openai.com/docs/guides/tools-computer-use)
-- [cua-computer](https://github.com/trycua/cua/tree/main/libs/computer)
+- [cua-computer](https://github.com/trycua/cua/tree/main/libs/python/computer)
 - [lume](https://github.com/trycua/cua/tree/main/libs/lume)

blog/build-your-own-operator-on-macos-2.md

@@ -171,7 +171,7 @@ The `cua-agent` framework provides multiple agent loop implementations to abstra
 
 - **AgentLoop.OMNI**: The most flexible option that works with virtually any vision-language model including local and open-source ones. Perfect for cost-effective development or when you need to use models without native computer-use capabilities.
 
-These abstractions allow you to easily switch between providers without changing your application code. All loop implementations are available in the [cua-agent GitHub repository](https://github.com/trycua/cua/tree/main/libs/agent/agent/providers).
+These abstractions allow you to easily switch between providers without changing your application code. All loop implementations are available in the [cua-agent GitHub repository](https://github.com/trycua/cua/tree/main/libs/python/agent).
 
 Choosing the right agent loop depends not only on your API access and technical requirements but also on the specific tasks you need to accomplish. To make an informed decision, it's helpful to understand how these underlying models perform across different computing environments – from desktop operating systems to web browsers and mobile interfaces.
 
@@ -674,7 +674,7 @@ With the basics covered, you might want to explore:
 
 ### Resources
 
-- [cua-agent GitHub repository](https://github.com/trycua/cua/tree/main/libs/agent)
+- [cua-agent GitHub repository](https://github.com/trycua/cua/tree/main/libs/python/agent)
 - [Agent Notebook Examples](https://github.com/trycua/cua/blob/main/notebooks/agent_nb.ipynb)
 - [OpenAI Agent SDK Specification](https://platform.openai.com/docs/api-reference/responses)
 - [Anthropic API Documentation](https://docs.anthropic.com/en/api/getting-started)

blog/lume-to-containerization.md

@@ -90,7 +90,7 @@ lume run macos-sequoia-vanilla:latest
 
 ### Lumier: Docker-Style VM Management
 
-[Lumier](https://github.com/trycua/lumier) works differently. It lets you use Docker commands to manage VMs. But here's the key: **Docker is just for packaging, not for isolation**.
+[Lumier](https://github.com/trycua/cua/tree/main/libs/lumier) works differently. It lets you use Docker commands to manage VMs. But here's the key: **Docker is just for packaging, not for isolation**.
 
 What makes Lumier useful:
 

blog/sandboxed-python-execution.md

@@ -378,4 +378,4 @@ Happy coding (safely)!
 
 ---
 
-_Want to dive deeper? Check out our [sandboxed functions examples](https://github.com/trycua/cua/blob/main/examples/sandboxed_functions_examples.py) and [virtual environment tests](https://github.com/trycua/cua/blob/main/tests/venv.py) on GitHub. Questions? Come chat with us on Discord!_
+_Want to dive deeper? Check out our [sandboxed functions examples](https://github.com/trycua/cua/blob/main/examples/sandboxed_functions_examples.py) and [virtual environment tests](https://github.com/trycua/cua/blob/main/tests/test_venv.py) on GitHub. Questions? Come chat with us on Discord!_

blog/training-computer-use-models-trajectories-1.md

@@ -306,6 +306,6 @@ Now that you know how to create and share trajectories, consider these advanced
 
 ### Resources
 
-- [Computer-Use Interface GitHub](https://github.com/trycua/cua/tree/main/libs/computer)
+- [Computer-Use Interface GitHub](https://github.com/trycua/cua/tree/main/libs/python/computer)
 - [Hugging Face Datasets Documentation](https://huggingface.co/docs/datasets)
 - [Example Dataset: ddupont/test-dataset](https://huggingface.co/datasets/ddupont/test-dataset)

blog/ubuntu-docker-support.md

@@ -174,7 +174,7 @@ await computer.run()
 
 ## Links
 
-- **Docker Provider Docs:** [https://cua.ai/docs/computers/docker](https://cua.ai/docs/computers/docker)
+- **Docker Provider Docs:** [https://cua.ai/docs/computers/docker](https://cua.ai/docs/computer-sdk/computers#linux-on-docker)
 - **KasmVNC:** [https://github.com/kasmtech/KasmVNC](https://github.com/kasmtech/KasmVNC)
 - **Container Source:** [https://github.com/trycua/cua/tree/main/libs/kasm](https://github.com/trycua/cua/tree/main/libs/kasm)
 - **Computer SDK:** [https://cua.ai/docs/computer-sdk/computers](https://cua.ai/docs/computer-sdk/computers)

blog/windows-sandbox.md

@@ -239,7 +239,7 @@ But for development, prototyping, and learning Windows RPA workflows, **Windows
 
 - [Windows Sandbox Documentation](https://learn.microsoft.com/en-us/windows/security/application-security/application-isolation/windows-sandbox/)
 - [Cua GitHub Repository](https://github.com/trycua/cua)
-- [Agent UI Documentation](https://github.com/trycua/cua/tree/main/libs/agent)
+- [Agent UI Documentation](https://github.com/trycua/cua/tree/main/libs/python/agent)
 - [Join our Discord Community](https://discord.gg/cua-ai)
 
 ---

libs/lume/README.md

@@ -58,7 +58,7 @@ To get set up with Lume for development, read [these instructions](Development.m
 - [Installation](https://cua.ai/docs/libraries/lume/installation)
 - [Prebuilt Images](https://cua.ai/docs/libraries/lume/prebuilt-images)
 - [CLI Reference](https://cua.ai/docs/libraries/lume/cli-reference)
-- [HTTP API](https://cuai.ai/docs/libraries/lume/http-api)
+- [HTTP API](https://cua.ai/docs/libraries/lume/http-api)
 - [FAQ](https://cua.ai/docs/libraries/lume/faq)
 
 ## Contributing

libs/python/computer-server/README.md

@@ -43,4 +43,4 @@ Refer to this notebook for a step-by-step guide on how to use the Computer-Use S
 - [Commands](https://cua.ai/docs/libraries/computer-server/Commands)
 - [REST-API](https://cua.ai/docs/libraries/computer-server/REST-API)
 - [WebSocket-API](https://cua.ai/docs/libraries/computer-server/WebSocket-API)
-- [Index](https://cua.ai/docs/libraries/computer-server/index)
+- [Index](https://cua.ai/docs/libraries/computer-server)