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refresh Hypermode docs (#109)
* refit for Dgraph integration * . * . * Update introduction.mdx * Update introduction.mdx * Update introduction.mdx * more content * updates * titles
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‎badger/overview.mdx

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---
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title: Overview
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title: Badger
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description: Welcome to the Badger docs!
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mode: "wide"
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sidebarTitle: "Overview"
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"og:title": "Overview - Badger"
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---
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‎community-and-support.mdx

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relevant GitHub repository:
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- [Modus](https://github.com/hypermodeinc/modus/issues)
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- [Hyp CLI](https://github.com/hypermodeinc/hyp-cli/issues)
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- [Dgraph](https://github.com/hypermodeinc/dgraph/issues)
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- [Badger](https://github.com/hypermodeinc/badger/issues)
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- [Hyp CLI](https://github.com/hypermodeinc/hyp-cli/issues)
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All paid Hypermode packages include commercial support. Customers can reach out
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via the Hypermode Console or through email at

‎docs.json

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"groups": [
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{
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"group": "Getting Started",
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"pages": ["introduction", "quickstart"]
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"pages": ["introduction", "semantic-search"]
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},
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{
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"group": "Develop",
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"group": "Graphs",
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"pages": [
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"work-locally",
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"deploy",
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"configure-environment",
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"integrate-api",
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"observe-functions"
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]
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},
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{
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"group": "Tutorials",
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"pages": ["semantic-search"]
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},
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{
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"group": "Manage",
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"pages": [
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"create-project",
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"modify-project",
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"modify-organization",
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"user-management"
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"graphs/overview",
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"graphs/deploy",
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"graphs/connect",
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"graphs/manage-schema",
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"graphs/manage-data",
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"graphs/manage-graph"
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]
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},
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{

‎graphs/connect.mdx

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---
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title: Connect to Graph
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description: Connect to your graph from a SDK, IDE, or Modus
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---
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## Connection strings
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A connection string is a URL that contains all of the necessary information to
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connect to your graph from a Dgraph client or Modus. It is displayed after you
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deploy your graph.
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## Authentication
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Your graph endpoint is protected by bearer token authorization passed in the
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`Authorization` header as an API key. You can find your API key in the console
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alongside your graph connection details. The API key is already included in the
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connection string.
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<Warning>
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If you remove your API key from your graph, it is made publicly accessible
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with no authentication.
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</Warning>
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## Clients
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Dgraph includes a web client and language-specific SDKs for programmatically
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working with your graph. When using the auto-generated GraphQL API, you can use
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any GraphQL client to work with your graph.
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### Ratel
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Dgraph includes Ratel, a web client for easily connecting to and exploring your
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graph. Ratel is available hosted at https://ratel.hypermode.com. To connect to
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your graph, paste your connection string into the Ratel interface and click
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`Connect`.
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### Dgraph SDKs
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Dgraph SDKs are available for a number of languages, including
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[Go](/dgraph/sdks/go), [Python](/dgraph/sdks/python), [Java](/dgraph/sdks/java),
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and [JavaScript](/dgraph/sdks/javascript). The SDKs have been updated to support
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the connection string for connecting to your graph on Hypermode. Ensure you're
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running the latest version of the SDK for your language.
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### GraphQL clients
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When working with your graph through the auto-generated GraphQL API, you can use
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any [GraphQL IDE or client](/dgraph/graphql/connecting) to connect to your
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graph.
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### Modus
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Modus provides a framework for integrating data from your graph into a complete
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AI-ready backend. Learn more on
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[connecting Modus to your graph](/modus/data-fetching#dgraph).

‎graphs/deploy.mdx

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---
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title: Deploy Graph
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description: Deploy a new graph and configure its resources
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---
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From your workspace home, click `Create new graph`. You are prompted to name
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your graph and select the [region](./manage-graph#region-availability) for
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deployment. Once deployed, your [connection string](./connect) is displayed.
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<Frame>
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<img src="/images/graphs/create-graph.png" alt="Create graph" />
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</Frame>

‎graphs/manage-data.mdx

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---
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title: Manage Data
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description: Query, mutate, and bulk manage data from your graph
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---
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Querying (reading) and mutating (writing) data to your graph is simple using an
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[IDE or SDK](./connect). For bulk operations, there are tools for importing,
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exporting, and dropping data.
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## Import data
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Dgraph provides multiple tools for importing data to your graph, whether an
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[initial import to an empty graph](/dgraph/admin/bulk-loader) or an
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[incremental import](/dgraph/admin/live-loader).
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You can also [load CSV-formatted data](/dgraph/admin/import-csv).
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## Export data
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If you need to export data from your graph, please reach out to support and we
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can assist.
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<Note>Self-service for exporting data is coming soon.</Note>
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## Drop data
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Dropping data from your graph is a permanent action and can't be undone. To drop
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data from your graph, you can use the `/alter` endpoint.
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To drop all data from your graph, while maintaining the schema:
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```sh
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curl -X POST https://<my-database>.hypermode.host/dgraph/alter \
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--header "Authorization: Bearer $BEARER_TOKEN" \
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--header "Content-Type: application/json" \
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--data '{"drop_op": "DATA"}'
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```
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For more options, see [Dgraph's documentation](/dgraph/admin/drop-data).

‎graphs/manage-graph.mdx

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---
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title: Manage Graph
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description: Manage your graph's resources and configuration
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---
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## Region availability
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Graphs on Hypermode are available in the following regions:
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| Region | Location |
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| :----- | :-------------------- |
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| `iad1` | Washington, D.C., USA |
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| `pdx1` | Portland, Oregon, USA |
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Additional regions are planned to be available in the near future:
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- Frankfurt, Germany
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- Dublin, Ireland
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- Singapore
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## Scaling
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Graph compute is measured in gigabytes (GB) of memory, with 1 vCPU allocated per
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4 gigabytes of memory. On Hypermode, you're charged for the compute allocated to
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your graph, billed to the second. That means when your graph is scaled to zero,
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you're only billed for the underlying storage.
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### Scale to zero
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By default, new graphs scale to zero after five minutes of inactivity. When a
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new query or mutation is received, the graph scales up and process that request.
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You can configure the scaling behavior for your graph by increasing the idle
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period. Set the idle period to `0` to turn off scale to zero.
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### Autoscaling
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Autoscaling is a feature that automatically scales your graph based on the
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compute and memory load. When under sustained load, the graph scales up to
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handle the additional load. When the load subsides, the graph scales down
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automatically.
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You can configure the autoscaling behavior for your graph by setting the `min`
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and `max` values. The `min` value is the minimum number of compute units the
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graph has, and the `max` value is the maximum number of compute units the graph
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can scale to.
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### Storage
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You are billed only for the storage used by your graph. The storage is
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automatically provisioned and expanded based on the growth of data within your
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graph.
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## Backups
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Your graph on Hypermode is automatically backed up every four hours, with
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backups stored with zonal isolation. To restore your graph to a previous state,
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please reach out to support via the console.
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<Note>User control of backup frequency and restore is coming soon.</Note>

‎graphs/manage-schema.mdx

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---
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title: Manage Schema
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description: Load and update the schema of your graph
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---
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When working with Dgraph, defining a schema is optional! Start schema-less and
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layer on a DQL or GraphQL-based modeling approach when needed.
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## Schema-less default
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Graphs running in Hypermode use Dgraph's `flexible` schema mode. This mode
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allows you to run a mutation without declaring the predicate in your schema.
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When a mutation introduces a new predicate, Dgraph automatically adds it to the
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schema. This can be useful when you're in the early stages of a project and the
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schema is evolving frequently and for allowing AI agents to augment your
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knowledge graph.
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## Deploy a DQL schema
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To deploy a [DQL schema](/dgraph/dql/schema), place the schema in a file
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(`schema.dql` in this case) and make a POST request to the `/dgraph/alter`
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endpoint for your host.
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```sh
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curl -X POST https://<my-database>.hypermode.host/dgraph/alter \
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--header "Authorization: Bearer $BEARER_TOKEN" \
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--header "Content-Type: application/json" \
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--data-binary "@schema.dql"
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```
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## Deploy a GraphQL schema
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To deploy a [GraphQL schema](/dgraph/graphql/schema), place the schema in a file
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(`schema.graphql` in this case) and make a POST request to the
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`/dgraph/admin/schema` endpoint for your host.
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```sh
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curl -X POST https://<my-database>.hypermode.host/dgraph/admin/schema \
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--header "Authorization: Bearer $BEARER_TOKEN" \
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--header "Content-Type: application/json" \
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--data-binary "@schema.graphql"
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```

‎graphs/overview.mdx

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---
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title: Graphs
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description: A fully managed graph database service powered by Dgraph
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mode: "wide"
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sidebarTitle: Overview
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---
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Graphs on Hypermode provides a fully managed [Dgraph](/dgraph) service for
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building and deploying knowledge graphs. This service combines the power of
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Dgraph's distributed graph database with Hypermode's AI development platform,
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offering a seamless experience for developers and organizations of all sizes.
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## Key features
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| Feature | Description |
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| :-------------------------------------------------------- | :------------------------------------------------------------------------------- |
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| [Scale to Zero](./manage-graph#scale-to-zero) | automatically scale down after periods of inactivity and scale back up on demand |
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| [Autoscaling](./manage-graph#autoscaling) | dynamic resource allocation based on workload demands |
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| [Flexible Schema Options](./manage-schema) | start schema-less or define structured schemas using DQL or GraphQL |
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| [Regional Deployment](./manage-graph#region-availability) | deploy in multiple regions for low-latency access |
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| [Modus Integration](/modus/data-fetching#dgraph) | seamlessly integrate with Hypermode's Modus framework for AI-ready backends |
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| [Fully Managed Service](./manage-graph) | deploy, scale, and operate your graph database without infrastructure headaches |
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## Getting started
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To get started with Graphs on Hypermode:
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1. **[Deploy a new graph](./deploy)**: create your graph database
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2. **[Connect to your graph](./connect)**: use connection strings to access your
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graph from various clients
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3. **[Manage your schema](./manage-schema)**: define your graph structure using
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DQL or GraphQL _(optional)_
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4. **[Manage data](./manage-data)**: add, query, and manipulate data in your
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graph
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## Use cases
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Graphs on Hypermode is ideal for:
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- Knowledge graphs for AI apps
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- Social networks and recommendation systems
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- Fraud detection and pattern recognition
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- Content management systems with rich interconnections
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- Complex relationship modeling
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- Any app requiring efficient traversal of connected data
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## Why Graphs on Hypermode?
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Traditional data stores struggle with highly connected data and complex
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relationship queries, which are often found in knowledge graphs. Graph stores
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like Dgraph excel at modeling and querying relationships, making them perfect
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for building with AI services, where connections between data points are as
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important as the data itself.
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Hypermode's managed service eliminates the operational complexity of running
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Dgraph, allowing you to focus on building your app while we handle scaling,
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backups, and infrastructure management.

‎hosted-models.mdx

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---
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Hypermode includes a set of shared models available for integration into your
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app on a pay-per-token basis.
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app.
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Need a bespoke model? You can include a model from
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[Hugging Face](https://huggingface.co/) in your
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[app manifest](/modus/app-manifest) and Hypermode runs and manages it for you.
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`provider: "hugging-face"`, and set `sourceModel` to be the model name as
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specified on Hugging Face.
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To use a Hypermode-hosted model, in your [app manifest](/modus/app-manifest) set
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`connection: "hypermode"`, `provider: "hugging-face"`, and set `sourceModel` to
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be the model name as specified on Hugging Face.
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```json modus.json {3-7}
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## Deployment mode
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We run our most popular models as multi-tenant, shared instances across
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workspaces and customers.
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these shared models at runtime. If the model you use isn't available as a shared

‎hyp-cli.mdx

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description: "Comprehensive reference for the Hyp CLI commands and usage"
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Hyp CLI is a command-line tool for managing your Hypermode account and projects.
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[Hypermode-hosted models](/hosted-models).
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Hyp CLI is a command-line tool for managing your Hypermode account and apps.
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When using Hyp CLI alongside the Modus CLI, your apps automatically connect to
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[Hypermode-hosted models](/hosted-models) when working locally.
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Hypermode console to authenticate. It stores an authentication token locally and
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prompts you to select your organization context.
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### `logout`
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Log out of your Hypermode account. This command clears your local authentication
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token.
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### `link`
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Link your GitHub repo to a Hypermode project. The command adds a default GitHub
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Actions workflow to build your Modus app and a Hypermode GitHub app for
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auto-deployment on commit.
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### `org switch`
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Switch to a different org context within the CLI session.

‎images/graphs/create-graph.png

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