Use relative refs

JR-1991 · JR-1991 · commit 30b4db393e5a · 2026-06-16T23:19:46.000+02:00
diff --git a/docs/src/content/docs/apis/overview.mdx b/docs/src/content/docs/apis/overview.mdx
@@ -12,27 +12,27 @@ pyDataverse provides several low-level API classes that offer direct access to D
 <CardGrid>
   <LinkCard
     title="Native API"
-    href="/apis/native"
+    href="../native/"
     description="Primary low-level client for collections, datasets, files, and metadata operations."
   />
   <LinkCard
     title="Data Access API"
-    href="/apis/data-access"
+    href="../data-access/"
     description="Specialized file retrieval, downloads, streaming, and access management."
   />
   <LinkCard
     title="Semantic API"
-    href="/apis/semantic"
+    href="../semantic/"
     description="JSON-LD metadata, RDF conversion, SPARQL queries, and knowledge graphs."
   />
   <LinkCard
     title="Metrics API"
-    href="/apis/metrics"
+    href="../metrics/"
     description="Usage statistics, analytics, and insights into content distribution."
   />
   <LinkCard
     title="Search API"
-    href="/apis/search"
+    href="../search/"
     description="Full-text search across collections, datasets, and files with advanced filtering."
   />
 </CardGrid>
diff --git a/docs/src/content/docs/filesystem/browsing.mdx b/docs/src/content/docs/filesystem/browsing.mdx
@@ -97,7 +97,7 @@ To avoid re-fetching the dataset's file listing on every call, `DataverseFS`
 caches it for `cache_ttl` seconds (default `60`). Writes through the filesystem
 clear this cache automatically, so newly written files appear immediately. If you
 change the dataset out-of-band (for example via the low-level
-[Native API](/apis/native/)) and want the filesystem to see it right away, call:
+[Native API](../../apis/native/)) and want the filesystem to see it right away, call:
 
 ```python
 fs.invalidate_cache()
diff --git a/docs/src/content/docs/filesystem/connecting.mdx b/docs/src/content/docs/filesystem/connecting.mdx
@@ -42,7 +42,7 @@ otherwise a `ValueError` is raised.
 
 ## From a high-level `Dataset`
 
-If you are already working with the [high-level API](/high-level/dataset/), every
+If you are already working with the [high-level API](../../high-level/dataset/), every
 `Dataset` exposes a ready-to-use filesystem via its `fs` property. This reuses the
 dataset's existing API clients and credentials, so you don't repeat the base URL
 or token:
@@ -114,5 +114,5 @@ fs = fsspec.filesystem(
 )
 ```
 
-See [pandas & the fsspec ecosystem](/filesystem/pandas/) for the URL-based form
+See [pandas & the fsspec ecosystem](../pandas/) for the URL-based form
 that lets tools open dataset files without constructing a filesystem at all.
diff --git a/docs/src/content/docs/filesystem/overview.mdx b/docs/src/content/docs/filesystem/overview.mdx
@@ -11,7 +11,7 @@ instance, you can browse, read, write, and delete files using the standard
 fsspec interface (`ls`, `info`, `open`, `cat`, `rm`, `find`, `glob`, ...) plus a
 few Dataverse-specific helpers for tabular data.
 
-It is the same machinery that powers the high-level [`Dataset`](/high-level/dataset/)
+It is the same machinery that powers the high-level [`Dataset`](../../high-level/dataset/)
 file operations — `dataset.open(...)`, `dataset.files`, `dataset.upload_file(...)`
 all delegate to a `DataverseFS` under the hood — but you can also use it directly
 whenever you want a filesystem-style view of a dataset.
@@ -55,32 +55,32 @@ with fs.open("data/notes.txt", "r") as f:   # stream a file
 <CardGrid>
   <LinkCard
     title="Connecting"
-    href="/filesystem/connecting"
+    href="../connecting/"
     description="Create a DataverseFS — directly, from a URL, or from a high-level Dataset."
   />
   <LinkCard
     title="Browsing & metadata"
-    href="/filesystem/browsing"
+    href="../browsing/"
     description="List, glob, and inspect files; read rich Dataverse metadata."
   />
   <LinkCard
     title="Reading files"
-    href="/filesystem/reading"
+    href="../reading/"
     description="Stream file content in text or binary, including byte-range reads."
   />
   <LinkCard
     title="Writing files"
-    href="/filesystem/writing"
+    href="../writing/"
     description="Create, replace, and delete files; attach metadata on upload."
   />
   <LinkCard
     title="Tabular data"
-    href="/filesystem/tabular"
+    href="../tabular/"
     description="Load ingested tabular files straight into pandas DataFrames."
   />
   <LinkCard
     title="pandas & the fsspec ecosystem"
-    href="/filesystem/pandas"
+    href="../pandas/"
     description="Read datasets by URL from pandas, Dask, Polars, and the command line."
   />
 </CardGrid>
diff --git a/docs/src/content/docs/filesystem/pandas.mdx b/docs/src/content/docs/filesystem/pandas.mdx
@@ -54,7 +54,7 @@ df = pd.read_csv(url, sep="\t")
 
 :::tip
 If you'd rather not remember the delimiter, use
-[`fs.open_tabular(...)`](/filesystem/tabular/) instead — it detects the format
+[`fs.open_tabular(...)`](../tabular/) instead — it detects the format
 from the file's MIME type and returns a DataFrame directly.
 :::
 
@@ -154,5 +154,5 @@ df.to_csv(
 )
 ```
 
-See [Writing files](/filesystem/writing/) for the details of how uploads stream
+See [Writing files](../writing/) for the details of how uploads stream
 and how to attach metadata.
diff --git a/docs/src/content/docs/filesystem/reading.mdx b/docs/src/content/docs/filesystem/reading.mdx
@@ -24,7 +24,7 @@ with fs.open("data/image.png", "rb") as f:
 ```
 
 Text mode returns a handle that still exposes the underlying Dataverse file's
-attributes (see [Writing files](/filesystem/writing/#reading-back-the-uploaded-files-id)),
+attributes (see [Writing files](../writing/#reading-back-the-uploaded-files-id)),
 so you don't lose anything by working with text.
 
 ## Seeking and partial reads
@@ -80,7 +80,7 @@ fs.get("data/", "local_dir/", recursive=True)
 Reading an **ingested tabular** file (a `.tab` produced by Dataverse) returns the
 reconstructed tab-delimited text, including the header row Dataverse stores
 separately. If you want the data as a DataFrame rather than raw bytes, use the
-helpers on the [Tabular data](/filesystem/tabular/) page instead.
+helpers on the [Tabular data](../tabular/) page instead.
 :::
 
 ## How it works
diff --git a/docs/src/content/docs/filesystem/tabular.mdx b/docs/src/content/docs/filesystem/tabular.mdx
@@ -90,5 +90,5 @@ dataset (or call `fs.invalidate_cache()`) once ingest has completed.
 
 Everything above goes through pyDataverse. If you'd rather hand a URL to pandas,
 Dask, or Polars and let them read it directly, see
-[pandas & the fsspec ecosystem](/filesystem/pandas/) — including a complete,
+[pandas & the fsspec ecosystem](../pandas/) — including a complete,
 runnable example against a public dataset.
diff --git a/docs/src/content/docs/getting-started.mdx b/docs/src/content/docs/getting-started.mdx
@@ -55,12 +55,12 @@ For many use cases this pattern is all you need to get started. As you become mo
 <CardGrid>
   <LinkCard
     title="High-Level API"
-    href="/high-level/concept/"
+    href="../high-level/concept/"
     description="Learn about the high-level API classes for working with Dataverse installations, collections, datasets, and files."
   />
   <LinkCard
     title="Direct APIs"
-    href="/apis/overview/"
+    href="../apis/overview/"
     description="Explore the low-level API classes for direct access to Dataverse REST endpoints."
   />
 </CardGrid>
diff --git a/docs/src/content/docs/high-level/collection.mdx b/docs/src/content/docs/high-level/collection.mdx
@@ -38,7 +38,7 @@ The identifier determines how the collection is accessed and referenced. String
 
 ## Accessing Collections
 
-Collections are typically accessed through the [`Dataverse`](/high-level/Dataverse/) class or as sub-collections of other collections:
+Collections are typically accessed through the [`Dataverse`](../dataverse/) class or as sub-collections of other collections:
 
 ```python
 from pyDataverse import Dataverse
@@ -374,12 +374,12 @@ This example demonstrates the typical workflow: fetching a collection, browsing
 
 ## Related Classes
 
-- **[`Dataverse`](/high-level/Dataverse/)** - Factory class for creating and managing collections and datasets
-- **[`Dataset`](/high-level/dataset/)** - Represents a Dataverse dataset that can be created within or accessed from collections
-- **[`File`](/high-level/file/)** - Represents an individual file within a dataset
+- **[`Dataverse`](../dataverse/)** - Factory class for creating and managing collections and datasets
+- **[`Dataset`](../dataset/)** - Represents a Dataverse dataset that can be created within or accessed from collections
+- **[`File`](../file/)** - Represents an individual file within a dataset
 
 ## See Also
 
-- [Dataverse Documentation](/high-level/Dataverse/) - Learn more about creating and managing collections
-- [Dataset Documentation](/high-level/dataset/) - Learn more about working with datasets within collections
-- [File Documentation](/high-level/file/) - Learn more about working with files in datasets
+- [Dataverse Documentation](../dataverse/) - Learn more about creating and managing collections
+- [Dataset Documentation](../dataset/) - Learn more about working with datasets within collections
+- [File Documentation](../file/) - Learn more about working with files in datasets
diff --git a/docs/src/content/docs/high-level/concept.mdx b/docs/src/content/docs/high-level/concept.mdx
@@ -20,22 +20,22 @@ pyDataverse provides four main classes that correspond to the Dataverse hierarch
 <CardGrid>
   <LinkCard
     title="Dataverse"
-    href="/high-level/dataverse/"
+    href="../dataverse/"
     description="Main entry point connecting to a Dataverse installation. Factory for creating datasets and accessing collections, metrics, and API clients."
   />
   <LinkCard
     title="Collection"
-    href="/high-level/collection/"
+    href="../collection/"
     description="Organizational containers that group related datasets. Support hierarchical nesting and have their own metadata and permissions."
   />
   <LinkCard
     title="Dataset"
-    href="/high-level/dataset/"
+    href="../dataset/"
     description="Containers for research outputs with structured metadata blocks and files. Independently citable research objects with persistent identifiers."
   />
   <LinkCard
     title="File"
-    href="/high-level/file/"
+    href="../file/"
     description="Individual research artifacts within datasets. Support reading, downloading, metadata management, and pandas integration for tabular data."
   />
 </CardGrid>
diff --git a/docs/src/content/docs/high-level/dataset.mdx b/docs/src/content/docs/high-level/dataset.mdx
@@ -49,7 +49,7 @@ Datasets can be created in several ways:
 
 ### Creating New Datasets
 
-Datasets are typically created using the [`Dataverse`](/high-level/Dataverse/) class's `create_dataset()` method or a [`Collection`](/high-level/collection/)'s `create_dataset()` method:
+Datasets are typically created using the [`Dataverse`](../dataverse/) class's `create_dataset()` method or a [`Collection`](../collection/)'s `create_dataset()` method:
 
 ```python
 from pyDataverse import Dataverse
@@ -747,12 +747,12 @@ fetched_dataset.open_in_browser()
 
 ## Related Classes
 
-- **[`Dataverse`](/high-level/Dataverse/)** - Factory class for creating and managing datasets
-- **[`Collection`](/high-level/collection/)** - Represents a Dataverse collection that can contain datasets
-- **[`File`](/high-level/file/)** - Represents an individual file within a dataset
+- **[`Dataverse`](../dataverse/)** - Factory class for creating and managing datasets
+- **[`Collection`](../collection/)** - Represents a Dataverse collection that can contain datasets
+- **[`File`](../file/)** - Represents an individual file within a dataset
 
 ## See Also
 
-- [Dataverse Documentation](/high-level/Dataverse/) - Learn more about creating and managing datasets
-- [Collection Documentation](/high-level/collection/) - Learn more about collections and organizing datasets
-- [File Documentation](/high-level/file/) - Learn more about working with individual files
+- [Dataverse Documentation](../dataverse/) - Learn more about creating and managing datasets
+- [Collection Documentation](../collection/) - Learn more about collections and organizing datasets
+- [File Documentation](../file/) - Learn more about working with individual files
diff --git a/docs/src/content/docs/high-level/dataverse.mdx b/docs/src/content/docs/high-level/dataverse.mdx
@@ -5,7 +5,7 @@ description: The main factory class for creating and managing Dataverse datasets
 
 The `Dataverse` class is the main entry point for working with a Dataverse installation. It establishes a connection to a Dataverse server and provides methods to create new datasets, retrieve existing ones, browse collections, and access all available features.
 
-When you instantiate a `Dataverse` object, it automatically connects to the server and retrieves information about available metadata blocks. This eliminates the need to manually configure complex metadata structures. The class handles this configuration automatically. It functions as a factory for creating [`Dataset`](/high-level/dataset/) instances with properly configured metadata blocks and provides convenient access to collections, metrics, and various API clients.
+When you instantiate a `Dataverse` object, it automatically connects to the server and retrieves information about available metadata blocks. This eliminates the need to manually configure complex metadata structures. The class handles this configuration automatically. It functions as a factory for creating [`Dataset`](../dataset/) instances with properly configured metadata blocks and provides convenient access to collections, metrics, and various API clients.
 
 ## Overview
 
@@ -98,7 +98,7 @@ Authors and contacts are provided as Python dictionaries that use curly braces `
 
 The `subjects` parameter accepts a list of predefined subject categories that organize datasets by research area. Common subjects include "Agricultural Sciences", "Physics", and "Social Sciences". You can specify multiple subjects for datasets that span multiple research areas.
 
-After creating the dataset, it is ready to use locally, but it has not yet been uploaded to the server. You can add files to it, modify its metadata, and upload it when you are ready. See the [`Dataset`](/high-level/dataset/) documentation for more details on working with datasets after they are created.
+After creating the dataset, it is ready to use locally, but it has not yet been uploaded to the server. You can add files to it, modify its metadata, and upload it when you are ready. See the [`Dataset`](../dataset/) documentation for more details on working with datasets after they are created.
 
 ## Accessing Collections and Datasets
 
@@ -265,16 +265,16 @@ This is primarily useful for advanced users who need to work with JSON schemas o
 
 The `Dataverse` class works closely with several other classes in the pyDataverse library:
 
-- **[`Dataset`](/high-level/dataset/)**: Represents a Dataverse dataset with metadata blocks and files. This is what you get when you create or fetch a dataset. It provides methods for adding files, modifying metadata, and uploading to the server.
+- **[`Dataset`](../dataset/)**: Represents a Dataverse dataset with metadata blocks and files. This is what you get when you create or fetch a dataset. It provides methods for adding files, modifying metadata, and uploading to the server.
 
-- **[`Collection`](/high-level/collection/)**: Represents a Dataverse collection (sub-dataverse). Collections organize datasets into groups. You can browse datasets within a collection, create new datasets, and manage collection metadata.
+- **[`Collection`](../collection/)**: Represents a Dataverse collection (sub-dataverse). Collections organize datasets into groups. You can browse datasets within a collection, create new datasets, and manage collection metadata.
 
-- **[`File`](/high-level/file/)**: Represents a file within a dataset. Files are the actual data files (like CSV files, images, code, and similar content) that are stored in datasets. The `File` class provides methods for reading, downloading, and managing files.
+- **[`File`](../file/)**: Represents a file within a dataset. Files are the actual data files (like CSV files, images, code, and similar content) that are stored in datasets. The `File` class provides methods for reading, downloading, and managing files.
 
-- **[`NativeApi`](/apis/native-api/)**: Low level API client for direct Dataverse API calls. This is what the `Dataverse` class uses internally, but you can also use it directly if you need more control or want to perform operations that are not yet wrapped in high level methods.
+- **[`NativeApi`](../../apis/native/)**: Low level API client for direct Dataverse API calls. This is what the `Dataverse` class uses internally, but you can also use it directly if you need more control or want to perform operations that are not yet wrapped in high level methods.
 
 ## See Also
 
-- **[Dataset Documentation](/high-level/dataset/)**: Learn more about working with datasets, including adding files, modifying metadata, and uploading content to the server.
-- **[Collection Documentation](/high-level/collection/)**: Learn more about collections, including browsing content and managing collection metadata.
-- **[Native API Documentation](/apis/native-api/)**: Detailed reference for advanced users who need direct API access.
+- **[Dataset Documentation](../dataset/)**: Learn more about working with datasets, including adding files, modifying metadata, and uploading content to the server.
+- **[Collection Documentation](../collection/)**: Learn more about collections, including browsing content and managing collection metadata.
+- **[Native API Documentation](../../apis/native/)**: Detailed reference for advanced users who need direct API access.
diff --git a/docs/src/content/docs/high-level/file.mdx b/docs/src/content/docs/high-level/file.mdx
@@ -31,7 +31,7 @@ A `File` instance contains key attributes that identify it and connect it to its
 
 - **`identifier`** (int): The unique integer identifier assigned to the file by the Dataverse server. This identifier is used for all API operations involving the file and remains constant throughout the file's lifetime. It's a frozen attribute, meaning it cannot be changed after the File object is created.
 
-- **`dataset`** (Dataset): A reference to the parent [`Dataset`](/high-level/dataset/) instance that contains this file. This provides access to dataset-level operations and ensures the file knows its context within the dataset structure.
+- **`dataset`** (Dataset): A reference to the parent [`Dataset`](../dataset/) instance that contains this file. This provides access to dataset-level operations and ensures the file knows its context within the dataset structure.
 
 The identifier is the primary way to reference a file in API calls, while the dataset reference enables file operations that require dataset context, such as reading file contents or accessing dataset-level properties.
 
@@ -324,12 +324,12 @@ This example demonstrates the typical workflow: accessing files through a datase
 
 ## Related Classes
 
-- **[`Dataset`](/high-level/dataset/)** - Represents a Dataverse dataset that contains files
-- **[`Dataverse`](/high-level/Dataverse/)** - Factory class for creating and managing datasets and collections
-- **[`Collection`](/high-level/collection/)** - Represents a Dataverse collection that can contain datasets with files
+- **[`Dataset`](../dataset/)** - Represents a Dataverse dataset that contains files
+- **[`Dataverse`](../dataverse/)** - Factory class for creating and managing datasets and collections
+- **[`Collection`](../collection/)** - Represents a Dataverse collection that can contain datasets with files
 
 ## See Also
 
-- [Dataset Documentation](/high-level/dataset/) - Learn more about working with datasets and their files
-- [Dataverse Documentation](/high-level/Dataverse/) - Learn more about creating and managing datasets
-- [Collection Documentation](/high-level/collection/) - Learn more about collections and organizing datasets
+- [Dataset Documentation](../dataset/) - Learn more about working with datasets and their files
+- [Dataverse Documentation](../dataverse/) - Learn more about creating and managing datasets
+- [Collection Documentation](../collection/) - Learn more about collections and organizing datasets
diff --git a/docs/src/content/docs/high-level/search.mdx b/docs/src/content/docs/high-level/search.mdx
diff --git a/docs/src/content/docs/installation.mdx b/docs/src/content/docs/installation.mdx
diff --git a/docs/src/content/docs/mcp/overview.mdx b/docs/src/content/docs/mcp/overview.mdx
diff --git a/docs/src/content/docs/mcp/tools.mdx b/docs/src/content/docs/mcp/tools.mdx
