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Merge pull request #35 from spinframework/docs/cloud-refs-part1
docs(*): update or remove relative /cloud refs
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content/v1/cli-reference.md

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{{ startTab "v1.3"}}
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The `spin cloud` command is implemented by the [Fermyon Cloud Plugin](/cloud/cloud-command-reference).
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The `spin cloud` command is implemented by the [Fermyon Cloud Plugin](https://developer.fermyon.com/cloud/cloud-command-reference).
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The `spin cloud` command is implemented by the [Fermyon Cloud Plugin](/cloud/cloud-command-reference).
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The `spin cloud` command is implemented by the [Fermyon Cloud Plugin](https://developer.fermyon.com/cloud/cloud-command-reference).
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The `spin cloud` command is implemented by the [Fermyon Cloud Plugin](/cloud/cloud-command-reference).
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The `spin cloud` command is implemented by the [Fermyon Cloud Plugin](https://developer.fermyon.com/cloud/cloud-command-reference).
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The `spin cloud deploy` command is implemented by the [Fermyon Cloud Plugin](/cloud/cloud-command-reference#spin-cloud-deploy).
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The `spin cloud deploy` command is implemented by the [Fermyon Cloud Plugin](https://developer.fermyon.com/cloud/cloud-command-reference#spin-cloud-deploy).
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The `spin cloud deploy` command is implemented by the [Fermyon Cloud Plugin](/cloud/cloud-command-reference#spin-cloud-deploy).
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The `spin cloud deploy` command is implemented by the [Fermyon Cloud Plugin](https://developer.fermyon.com/cloud/cloud-command-reference#spin-cloud-deploy).
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The `spin cloud deploy` command is implemented by the [Fermyon Cloud Plugin](/cloud/cloud-command-reference#spin-cloud-deploy).
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The `spin cloud deploy` command is implemented by the [Fermyon Cloud Plugin](https://developer.fermyon.com/cloud/cloud-command-reference#spin-cloud-deploy).
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The `spin cloud login` command is implemented by the [Fermyon Cloud Plugin](/cloud/cloud-command-reference#spin-cloud-login).
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The `spin cloud login` command is implemented by the [Fermyon Cloud Plugin](https://developer.fermyon.com/cloud/cloud-command-reference#spin-cloud-login).
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The `spin cloud login` command is implemented by the [Fermyon Cloud Plugin](/cloud/cloud-command-reference#spin-cloud-login).
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The `spin cloud login` command is implemented by the [Fermyon Cloud Plugin](https://developer.fermyon.com/cloud/cloud-command-reference#spin-cloud-login).
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The `spin cloud login` command is implemented by the [Fermyon Cloud Plugin](/cloud/cloud-command-reference#spin-cloud-login).
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The `spin cloud login` command is implemented by the [Fermyon Cloud Plugin](https://developer.fermyon.com/cloud/cloud-command-reference#spin-cloud-login).
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The `spin cloud variables` command is implemented by the [Fermyon Cloud Plugin](/cloud/cloud-command-reference#spin-cloud-variables).
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The `spin cloud variables` command is implemented by the [Fermyon Cloud Plugin](https://developer.fermyon.com/cloud/cloud-command-reference#spin-cloud-variables).
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The `spin cloud variables` command is implemented by the [Fermyon Cloud Plugin](/cloud/cloud-command-reference#spin-cloud-variables).
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The `spin cloud variables` command is implemented by the [Fermyon Cloud Plugin](https://developer.fermyon.com/cloud/cloud-command-reference#spin-cloud-variables).
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The `spin cloud variables` command is implemented by the [Fermyon Cloud Plugin](/cloud/cloud-command-reference#spin-cloud-variables).
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The `spin cloud variables` command is implemented by the [Fermyon Cloud Plugin](https://developer.fermyon.com/cloud/cloud-command-reference#spin-cloud-variables).
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content/v1/dynamic-configuration.md

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auth_token = "<auth_token>"
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```
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Currently, the remote compute option requires a user to deploy their own LLM proxy service. On Fermyon Cloud, users can do this using the [`cloud-gpu` plugin](https://github.com/spinframework/spin-cloud-gpu). If you prefer to create and deploy your own proxy service, you can find a reference implementation of the proxy protocol in the [`spin-cloud-gpu plugin repository`](https://github.com/spinframework/spin-cloud-gpu/blob/main/fermyon-cloud-gpu/src/index.ts).
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Currently, the remote compute option requires a user to deploy their own LLM proxy service. On Fermyon Cloud, users can do this using the [`cloud-gpu` plugin](https://github.com/fermyon/spin-cloud-gpu). If you prefer to create and deploy your own proxy service, you can find a reference implementation of the proxy protocol in the [`spin-cloud-gpu plugin repository`](https://github.com/fermyon/spin-cloud-gpu/blob/main/fermyon-cloud-gpu/src/index.ts).
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By default, components will not have access to the LLM models unless granted explicit access through the `component.ai_models` entry in the component manifest within `spin.toml`. See [Serverless AI](./serverless-ai-api-guide) for more details.

content/v1/running-apps.md

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- Learn how to [create and update a Spin application](writing-apps)
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- Learn about how to [configure your application at runtime](dynamic-configuration)
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- See how to [package and distribute your application](registry-tutorial)
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- Try deploying your application to run in the [Fermyon Cloud](/cloud/quickstart)

content/v1/see-what-people-have-built-with-spin.md

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- Try [running your application locally](running-apps)
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- Learn about how to [configure your application at runtime](dynamic-configuration)
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- Look up details in the [application manifest reference](manifest-reference)
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- Try deploying a Spin application to the [Fermyon Cloud](/cloud/quickstart)

content/v1/serverless-ai-hello-world.md

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**Using the Cloud-GPU plugin to test locally**
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To avoid having to deploy the app for every change, you can use the [Cloud-GPU plugin](https://github.com/spinframework/spin-cloud-gpu) to deploy locally, with the LLM running in the cloud. While the app is hosted locally (running on `localhost`), every inferencing request is sent to the LLM that is running in the cloud. Follow the steps to use the `cloud-gpu` plugin.
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To avoid having to deploy the app for every change, you can use the [Cloud-GPU plugin](https://github.com/fermyon/spin-cloud-gpu) to deploy locally, with the LLM running in the cloud. While the app is hosted locally (running on `localhost`), every inferencing request is sent to the LLM that is running in the cloud. Follow the steps to use the `cloud-gpu` plugin.
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**Note**: This plugin works only with spin v1.5.1 and above.
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First, install the plugin using the command:
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$ spin plugins install -u https://github.com/spinframework/spin-cloud-gpu/releases/download/canary/cloud-gpu.json -y
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$ spin plugins install -u https://github.com/fermyon/spin-cloud-gpu/releases/download/canary/cloud-gpu.json -y
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Let’s initialize the plugin. This command essentially deploys the Spin app to a Cloud GPU proxy and generates a runtime-config:

content/v1/spin-application-structure.md

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- Discover how Spin application authors [design and organise applications](see-what-people-have-built-with-spin)
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- Learn about how to [configure your application at runtime](dynamic-configuration)
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- Look up details in the [application manifest reference](manifest-reference)
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- Try deploying a Spin application to the [Fermyon Cloud](/cloud/quickstart)

content/v1/sqlite-api-guide.md

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```
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> Note: To deploy your Database application to Fermyon Cloud using `spin cloud deploy`, see the [SQLite Database](/cloud/noops-sql-db#accessing-private-beta) section in the documentation. It covers signing up for the private beta and setting up your Cloud database tables and initial data.
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> Note: To deploy your Database application to Fermyon Cloud using `spin cloud deploy`, see the [SQLite Database](https://developer.fermyon.com/cloud/noops-sql-db#accessing-private-beta) section in the documentation. It covers signing up for the private beta and setting up your Cloud database tables and initial data.
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## Using SQLite Storage From Applications
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content/v1/writing-apps.md

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- Discover how Spin application authors [design and organise applications](see-what-people-have-built-with-spin)
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- Learn about how to [configure your application at runtime](dynamic-configuration)
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- Look up details in the [application manifest reference](manifest-reference)
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- Try deploying a Spin application to the [Fermyon Cloud](/cloud/quickstart)

content/v2/ai-sentiment-analysis-api-tutorial.md

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Next, we need to create the appropriate folder structure from within the application directory (alongside our `spin.toml` file). The code below demonstrates the variations in folder structure depending on which model is being used. Once the folder structure is in place, we then fetch the pre-trained AI model for our application:
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> Note: Optional, but highly recommended, is to use the [Spin Cloud GPU component](https://github.com/spinframework/spin-cloud-gpu). This offloads inferencing to Fermyon Cloud GPUs, and thus requires a free account to [Fermyon Cloud Serverless AI](https://www.fermyon.com/serverless-ai). This would replace the following steps of having to download the three models below.
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> Note: Optional, but highly recommended, is to use the [Spin Cloud GPU component](https://github.com/fermyon/spin-cloud-gpu). This offloads inferencing to Fermyon Cloud GPUs, and thus requires a free account to [Fermyon Cloud Serverless AI](https://www.fermyon.com/serverless-ai). This would replace the following steps of having to download the three models below.
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**llama2-chat example download**
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content/v2/build.md

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## Next Steps
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- Try [running your application locally](running-apps)
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- Try deploying a Spin application to the [Fermyon Cloud](/cloud/quickstart)

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