fix 404's in the docs (#860)

javisperez · web-flow · commit e84d8f0cf222 · 2025-05-02T17:56:36.000-04:00
Signed-off-by: Javis Pérez &lt;javis@jozu.com&gt;
diff --git a/README.md b/README.md
@@ -38,7 +38,7 @@ For our friends in the EU - ModelKits are the perfect way to create a library of
 
 * 🚢 Create a **[runnable container from a ModelKit](https://tinyurl.com/5b76p5u3)** with one command! Read [KitOps deploy docs](https://kitops.org/docs/deploy/) for details.
 * 🥂 Get the most out of KitOps' ModelKits by using them with the **[Jozu Hub](https://jozu.ml/)** repository. Or, continue using ModelKits with your existing OCI registry (even on-premises and air-gapped).
-* 🛠️ Use KitOps with Dagger pipelines using our modules from the [Daggerverse](https://daggerverse.dev/mod/github.com/kitops-ml/daggerverse/kit).
+* 🛠️ Use KitOps with Dagger pipelines using our modules from the [Daggerverse](https://github.com/kitops-ml/daggerverse).
 * ⛑️ [KitOps works great with Red Hat](https://developers.redhat.com/articles/2024/09/16/enhance-llms-instructlab-kitops) InstructLab and Quay.io products.
 
 
@@ -48,7 +48,7 @@ For our friends in the EU - ModelKits are the perfect way to create a library of
 * 🏭 **[Versioning](https://kitops.org/docs/cli/cli-reference/#kit-tag):** Each ModelKit is tagged so everyone knows which dataset and model work together.
 * 🔒 **[Tamper-proofing](https://kitops.org/docs/modelkit/spec/):** Each ModelKit package includes an SHA digest for itself, and every artifact it holds.
 * 🤩 **[Selective-unpacking](https://kitops.org/docs/cli/cli-reference/#kit-unpack):** Unpack only what you need from a ModelKit with the `kit unpack --filter` command - just the model, just the dataset and code, or any other combination.
-* 🤖 **[Automation](https://github.com/marketplace/actions/setup-kit-cli):** Pack or unpack a ModelKit locally or as part of your CI/CD workflow for testing, integration, or deployment (e.g. [GitHub Actions](https://github.com/marketplace/actions/setup-kit-cli) or [Dagger](https://daggerverse.dev/mod/github.com/kitops-ml/daggerverse/kit).
+* 🤖 **[Automation](https://github.com/marketplace/actions/setup-kit-cli):** Pack or unpack a ModelKit locally or as part of your CI/CD workflow for testing, integration, or deployment (e.g. [GitHub Actions](https://github.com/marketplace/actions/setup-kit-cli) or [Dagger](https://github.com/kitops-ml/daggerverse).
 * 🐳 **[Deploy containers](https://kitops.org/docs/deploy/):** Generate a basic or custom docker container from any ModelKit.
 * 🚢 **[Kubernetes-ready](https://kitops.org/docs/deploy/):** Generate a Kubernetes / KServe deployment config from any ModelKit.
 * 🪛 **[LLM fine-tuning](https://dev.to/kitops/fine-tune-your-first-large-language-model-llm-with-lora-llamacpp-and-kitops-in-5-easy-steps-1g7f):** Use KitOps to fine-tune a large language model using LoRA.
@@ -57,7 +57,7 @@ For our friends in the EU - ModelKits are the perfect way to create a library of
 * 🌈 **[Standards-based](https://kitops.org/docs/modelkit/compatibility/):** Store ModelKits in any OCI 1.1-compliant container or artifact registry.
 * 🥧 **[Simple syntax](https://kitops.org/docs/kitfile/kf-overview/):** Kitfiles are easy to write and read, using a familiar YAML syntax.
 * 🩰 **[Flexible](https://kitops.org/docs/kitfile/format/#model):** Reference base models using `model parts`, or store key-value pairs (or any YAML-compatible JSON data) in your Kitfile - use it to keep features, hyperparameters, links to MLOps tool experiments, or validation output.
-* 🏃‍♂️‍➡️ **[Run locally](./docs/src/docs/dev-mode.md):** Kit's Dev Mode lets you run an LLM locally, configure it, and prompt/chat with it instantly.
+* 🏃‍♂️‍➡️ **[Run locally](./docs/src/docs/deploy.md#running-llms-locally):** Kit's Dev Mode lets you run an LLM locally, configure it, and prompt/chat with it instantly.
 * 🤗 **Universal:** ModelKits can be used with any AI, ML, or LLM project - even multi-modal models.
 
 ### See KitOps in Action
@@ -98,10 +98,10 @@ We ❤️ our KitOps community and contributors. To learn more about the many wa
 
 #### 📢 KitOps Community Calls (bi-weekly)
 
-**Wednesdays @ 13:30 – 14:00**  
-**Time zone**: America/Toronto  
-**Video call link**: [Google Meet](https://meet.google.com/zfq-uprp-csd)  
-Or dial: (CA) +1 647-736-3184 PIN: 144 931 404#  
+**Wednesdays @ 13:30 – 14:00**
+**Time zone**: America/Toronto
+**Video call link**: [Google Meet](https://meet.google.com/zfq-uprp-csd)
+Or dial: (CA) +1 647-736-3184 PIN: 144 931 404#
 More phone numbers: [Phone Numbers](https://tel.meet/zfq-uprp-csd?pin=1283456375953)
 
 ### A Community Built on Respect
diff --git a/docs/README.md b/docs/README.md
@@ -3,7 +3,7 @@
 
 # KitOps Documentation
 
-This is the documentation for [KitsOps](https://kitops.org). You can read the docs at https://kitops.org/docs/overview.html.
+This is the documentation for [KitsOps](https://kitops.org). You can read the docs at https://kitops.org/docs/overview/.
 
 ## Table of Contents
 
diff --git a/docs/src/docs/get-started.md b/docs/src/docs/get-started.md
@@ -15,7 +15,7 @@ In this guide, we'll use ModelKits and the kit CLI to easily:
 * Package the ModelKit as a container or Kubernetes deployment
 
 :::info
-If you're more interested in using KitOps with [MLFlow](../pykitops/mlflow.md) or [CI/CD pipelines](../pykitops/cicd.md) check out our integrations section.
+If you're more interested in using KitOps with [MLFlow](../integrations/mlflow.md) or [CI/CD pipelines](../integrations/cicd.md) check out our integrations section.
 :::
 
 ## Before we start...
@@ -151,8 +151,8 @@ If you'd like to learn more about using Kit, try our [Next Steps with Kit](../ne
 * Tagging ModelKits
 * Keeping your registry tidy
 
-Or, if you want to run an LLM-based ModelKit locally try our [dev mode](../dev-mode/).
+Or, if you want to run an LLM-based ModelKit locally try our [dev mode](../deploy/#running-llms-locally).
 
-Finally, if you're building workflows using Dagger you can use KitOps through our [Daggerverse modules](https://daggerverse.dev/mod/github.com/kitops-ml/daggerverse/kit). Or get the [GitHub Action for Kit](https://github.com/marketplace/actions/setup-kit-cli).
+Finally, if you're building workflows using Dagger you can use KitOps through our [Daggerverse modules](https://github.com/kitops-ml/daggerverse). Or get the [GitHub Action for Kit](https://github.com/marketplace/actions/setup-kit-cli).
 
 Thanks for taking some time to play with Kit. We'd love to hear what you think. Feel free to drop us an [issue in our GitHub repository](https://github.com/kitops-ml/kitops/issues) or join [our Discord server](https://discord.gg/Tapeh8agYy).
diff --git a/docs/src/docs/integrations/cicd.md b/docs/src/docs/integrations/cicd.md
@@ -3,14 +3,14 @@ description: Use KitOps ModelKits to add AI/ML to your CI/CD tool's pipelines.
 ---
 # Using KitOps ModelKits from a CI/CD Tool
 
-To get the most out of KitOps secure ModelKits, many teams and organizations create, push, or pull ModelKits as part of their CI/CD pipelines. For example, when a team finishes tuning of a model, a pipeline will create a ModelKit that includes the model, the tuning dataset used, the artifacts generated by the successful experiment run, and the results of that experiment run. 
+To get the most out of KitOps secure ModelKits, many teams and organizations create, push, or pull ModelKits as part of their CI/CD pipelines. For example, when a team finishes tuning of a model, a pipeline will create a ModelKit that includes the model, the tuning dataset used, the artifacts generated by the successful experiment run, and the results of that experiment run.
 
 Typically this is done by installing the Kit CLI and running `kit` commands as tasks in the pipeline.
 
 The KitOps community has shared some of their CI/CD tool integrations:
 * GitHub Actions: [Tutorial](https://jozu.com/blog/automating-ml-pipeline-with-modelkits-github-actions/), and [Action](https://github.com/marketplace/actions/setup-kit-cli)
 * Red Hat OpenShift Pipelines: [Tutorial](https://jozu.com/blog/how-to-turn-your-openshift-pipelines-into-an-mlops-pipeline)
 * ArgoCD: [Tutorial](https://jozu.com/blog/deploying-ml-projects-with-argo-cd/)
-* Dagger: [Tutorial](https://jozu.com/blog/building-an-mlops-pipeline-with-dagger-io-and-kitops/), and [Module](https://daggerverse.dev/mod/github.com/kitops-ml/daggerverse/kit@fc53d7802be6553298f4f54dd73cc1c1913d4ce6)
+* Dagger: [Tutorial](https://jozu.com/blog/building-an-mlops-pipeline-with-dagger-io-and-kitops/), and [Module](https://github.com/kitops-ml/daggerverse)
 
-**Questions or suggestions?** Drop an [issue in our GitHub repository](https://github.com/kitops-ml/kitops/issues) or join [our Discord server](https://discord.gg/Tapeh8agYy) to get support or share your feedback.
+**Questions or suggestions?** Drop an [issue in our GitHub repository](https://github.com/kitops-ml/kitops/issues) or join [our Discord server](https://discord.gg/Tapeh8agYy) to get support or share your feedback.
diff --git a/docs/src/docs/integrations/mlflow.md b/docs/src/docs/integrations/mlflow.md
@@ -3,7 +3,7 @@ description: Use KitOps PyKitOps Python library to automate ModelKit creation wi
 ---
 # MLFlow and KitOps ModelKits
 
-Many KitOps users automate the creation of secure and tamper-proof [ModelKits](../modelkit/intro.md) for each experiment run in MLFlow. This gives the team and organization a library of models that they can reproduce on any infrastructure.
+Many KitOps users automate the creation of secure and tamper-proof [ModelKits](../../modelkit/intro.md) for each experiment run in MLFlow. This gives the team and organization a library of models that they can reproduce on any infrastructure.
 
 ::tip
 You can follow the instructions below, or in a [community-generated tutorial](https://jozu.com/blog/how-to-use-kitops-with-mlflow/)
@@ -33,7 +33,7 @@ The `ModelKitManager` is then used to pack and upload the artifacts as a ModelKi
 
 In the following code:
 `artifact_location` = the directory where the experiment run artifacts were saved
-`name` = the name of the ModelKit as it will be displayed in the [Kitfile](../kitfile/kf-overview.md)
+`name` = the name of the ModelKit as it will be displayed in the [Kitfile](../../kitfile/kf-overview.md)
 `modelkit_tag` = a name for the ModelKit, for example "latest"
 
 ```py
@@ -42,7 +42,7 @@ from kitops.modelkit.manager import ModelKitManager
 from kitops.modelkit.user import UserCredentials
 from kitops.cli import kit
 
-# A password can be read from Environment Variables or .env files: JOZU_PASSWORD=<secret password> 
+# A password can be read from Environment Variables or .env files: JOZU_PASSWORD=<secret password>
 # Add in your own username from the registry that you are accessing, e.g. username=bmicklea
 creds = UserCredentials(username=username, registry="jozu.ml")
 
@@ -62,4 +62,4 @@ kit.init(directory=artifact_location, name=name, description="my cool project",
 manager.pack_and_push_modelkit(with_login_and_logout=False)
 ```
 
-**Questions or suggestions?** Drop an [issue in our GitHub repository](https://github.com/kitops-ml/kitops/issues) or join [our Discord server](https://discord.gg/Tapeh8agYy) to get support or share your feedback.
+**Questions or suggestions?** Drop an [issue in our GitHub repository](https://github.com/kitops-ml/kitops/issues) or join [our Discord server](https://discord.gg/Tapeh8agYy) to get support or share your feedback.
diff --git a/docs/src/docs/modelkit/compatibility.md b/docs/src/docs/modelkit/compatibility.md
@@ -32,7 +32,7 @@ The most fully-featured repository for ModelKits is the [Jozu Hub](https://jozu.
 
 ### Pre-Built Workflows
 
-* Dagger: see [Kit modules for Dagger](https://daggerverse.dev/mod/github.com/kitops-ml/daggerverse/kit) in the Daggerverse
+* Dagger: see [Kit modules for Dagger](https://github.com/kitops-ml/daggerverse) in the Daggerverse
 * GitHub Actions: Kit CLI for [GitHub Actions](https://github.com/marketplace/actions/setup-kit-cli)
 
 ## Other Compatible Tools
diff --git a/docs/src/docs/use-cases.md b/docs/src/docs/use-cases.md
@@ -22,7 +22,7 @@ Security conscious organizations often can't allow internal teams to use any pub
 * They don't match the organization's security testing requirements
 * Their provenance isn't understood
 
-In these cases teams may use a pipeline (with [GitHub Actions](https://github.com/marketplace/actions/setup-kit-cli), [Dagger](https://daggerverse.dev/mod/github.com/kitops-ml/daggerverse/kit), or [another tool](../modelkit/compatibility/)) to pull models or sample datasets from Hugging Face, run them through a battery of tests, then publish them in tamper-proof and signed ModelKits to their private container registry.
+In these cases teams may use a pipeline (with [GitHub Actions](https://github.com/marketplace/actions/setup-kit-cli), [Dagger](https://github.com/kitops-ml/daggerverse), or [another tool](../modelkit/compatibility/)) to pull models or sample datasets from Hugging Face, run them through a battery of tests, then publish them in tamper-proof and signed ModelKits to their private container registry.
 
 This ensures that:
 * __Everyone has a library of safe, immutable, and signed ModelKits__ speeding development without compromising security
@@ -33,7 +33,7 @@ This ensures that:
 * __Organizations are protected against vendor shifts__ in their MLOps and Serving Infrastructure domains (this also gives them negotiating leverage with vendors)
 
 **Get Started:**
-* [Kit Dagger Modules](https://daggerverse.dev/mod/github.com/kitops-ml/daggerverse/kit): Kit Dagger modules make it easy to pack and selectively unpack ModelKits to speed pipelines.
+* [Kit Dagger Modules](https://github.com/kitops-ml/daggerverse): Kit Dagger modules make it easy to pack and selectively unpack ModelKits to speed pipelines.
 * [Kit GitHub Action](https://github.com/marketplace/actions/setup-kit-cli): Our Kit GitHub Action is used to build hundreds of ModelKits every day as part of pipelines.
 * [Learn to pack and unpack ModelKits](../get-started/)
 * [Create containers or Kubernetes deployments directly from ModelKits](../deploy/)
