clean up cross-repo links

Author: colleenmcginnis

docs/reference/_how_to_guides.md

@@ -655,7 +655,7 @@ class Post(Document):
 
 The `Document` instances use native python types like `str` and `datetime`. In case of `Object` or `Nested` fields an instance of the `InnerDoc` subclass is used, as in the `add_comment` method in the above example where we are creating an instance of the `Comment` class.
 
-There are some specific types that were created as part of this library to make working with some field types easier, for example the `Range` object used in any of the [range fields](elasticsearch://docs/reference/elasticsearch/mapping-reference/range.md):
+There are some specific types that were created as part of this library to make working with some field types easier, for example the `Range` object used in any of the [range fields](elasticsearch://reference/elasticsearch/mapping-reference/range.md):
 
 ```python
 from elasticsearch.dsl import Document, DateRange, Keyword, Range
@@ -1069,7 +1069,7 @@ class BlogPost(BaseDocument):
         name = 'blog'
 ```
 
-Another use case would be using the [join type](elasticsearch://docs/reference/elasticsearch/mapping-reference/parent-join.md) to have multiple different entities in a single index. You can see an [example](https://github.com/elastic/elasticsearch-py/blob/master/examples/dsl/parent_child.py) of this approach. Note that in this case, if the subclasses don’t define their own Index classes, the mappings are merged and shared between all the subclasses.
+Another use case would be using the [join type](elasticsearch://reference/elasticsearch/mapping-reference/parent-join.md) to have multiple different entities in a single index. You can see an [example](https://github.com/elastic/elasticsearch-py/blob/master/examples/dsl/parent_child.py) of this approach. Note that in this case, if the subclasses don’t define their own Index classes, the mappings are merged and shared between all the subclasses.
 
 
 

docs/reference/async.md

@@ -47,7 +47,7 @@ All APIs that are available under the sync client are also available under the a
 
 [ASGI](https://asgi.readthedocs.io) (Asynchronous Server Gateway Interface) is a way to serve Python web applications making use of async I/O to achieve better performance. Some examples of ASGI frameworks include FastAPI, Django 3.0+, and Starlette. If you’re using one of these frameworks along with Elasticsearch then you should be using `~elasticsearch.AsyncElasticsearch` to avoid blocking the event loop with synchronous network calls for optimal performance.
 
-[Elastic APM](apm-agent-python://docs/reference/index.md) also supports tracing of async Elasticsearch queries just the same as synchronous queries. For an example on how to configure `AsyncElasticsearch` with a popular ASGI framework [FastAPI](https://fastapi.tiangolo.com/) and APM tracing there is a [pre-built example](https://github.com/elastic/elasticsearch-py/tree/master/examples/fastapi-apm) in the `examples/fastapi-apm` directory.
+[Elastic APM](apm-agent-python://reference/index.md) also supports tracing of async Elasticsearch queries just the same as synchronous queries. For an example on how to configure `AsyncElasticsearch` with a popular ASGI framework [FastAPI](https://fastapi.tiangolo.com/) and APM tracing there is a [pre-built example](https://github.com/elastic/elasticsearch-py/tree/master/examples/fastapi-apm) in the `examples/fastapi-apm` directory.
 
 See also the [Using OpenTelemetry](/reference/opentelemetry.md) page.
 

docs/reference/connecting.md

@@ -154,7 +154,7 @@ Running {{es}} without security enabled is not recommended.
 ::::
 
 
-If your cluster is configured with [security explicitly disabled](elasticsearch://docs/reference/elasticsearch/configuration-reference/security-settings.md) then you can connect via HTTP:
+If your cluster is configured with [security explicitly disabled](elasticsearch://reference/elasticsearch/configuration-reference/security-settings.md) then you can connect via HTTP:
 
 ```python
 from elasticsearch import Elasticsearch

docs/reference/esql-pandas.md

@@ -355,7 +355,7 @@ You can now analyze the data with Pandas or you can also continue transforming t
 
 ## Analyze the data with Pandas [analyze-data]
 
-In the next example, the [STATS …​ BY](elasticsearch://docs/reference/query-languages/esql/esql-commands.md#esql-stats-by) command is utilized to count how many employees are speaking a given language. The results are sorted with the `languages` column using [SORT](elasticsearch://docs/reference/query-languages/esql/esql-commands.md#esql-sort):
+In the next example, the [STATS …​ BY](elasticsearch://reference/query-languages/esql/esql-commands.md#esql-stats-by) command is utilized to count how many employees are speaking a given language. The results are sorted with the `languages` column using [SORT](elasticsearch://reference/query-languages/esql/esql-commands.md#esql-sort):
 
 ```python
 response = client.esql.query(

docs/reference/examples.md

@@ -145,7 +145,7 @@ In the [02-hybrid-search.ipynb](https://github.com/elastic/elasticsearch-labs/bl
 
 * Combine results of traditional text-based search with semantic search, for a hybrid search system.
 * Transform fields in the sample dataset into embeddings using the Sentence Transformer model and index them into Elasticsearch.
-* Use the [RRF API](elasticsearch://docs/reference/elasticsearch/rest-apis/reciprocal-rank-fusion.md#rrf-api) to combine the results of a `match` query and a `kNN` semantic search.
+* Use the [RRF API](elasticsearch://reference/elasticsearch/rest-apis/reciprocal-rank-fusion.md#rrf-api) to combine the results of a `match` query and a `kNN` semantic search.
 * Walk through a super simple toy example that demonstrates, step by step, how RRF ranking works.
 
 

docs/reference/integrations.md

@@ -25,7 +25,7 @@ The handling of connections, retries, and pooling is handled by the [Elastic Tra
 
 ## Tracking requests with Opaque ID [opaque-id]
 
-You can enrich your requests against Elasticsearch with an identifier string, that allows you to discover this identifier in [deprecation logs](docs-content://deploy-manage/monitor/logging-configuration/update-elasticsearch-logging-levels.md#deprecation-logging), to support you with [identifying search slow log origin](elasticsearch://docs/reference/elasticsearch/index-settings/slow-log.md) or to help with [identifying running tasks](https://www.elastic.co/docs/api/doc/elasticsearch/group/endpoint-tasks).
+You can enrich your requests against Elasticsearch with an identifier string, that allows you to discover this identifier in [deprecation logs](docs-content://deploy-manage/monitor/logging-configuration/update-elasticsearch-logging-levels.md#deprecation-logging), to support you with [identifying search slow log origin](elasticsearch://reference/elasticsearch/index-settings/slow-log.md) or to help with [identifying running tasks](https://www.elastic.co/docs/api/doc/elasticsearch/group/endpoint-tasks).
 
 The opaque ID can be set via the `opaque_id` parameter via the client `.options()` method: