chore: complete backends dependency tags (docarray#328)

alaeddine-13 · web-flow · commit 022db38e05b7 · 2022-05-06T09:34:22.000+02:00
* chore: add dep tags for backends

* docs: document usage and installation
diff --git a/docs/advanced/document-store/annlite.md b/docs/advanced/document-store/annlite.md
@@ -4,7 +4,7 @@
 One can use [Annlite](https://github.com/jina-ai/annlite) as the document store for DocumentArray. It is useful when one wants to have faster Document retrieval on embeddings, i.e. `.match()`, `.find()`.
 
 ````{tip}
-This feature requires `annlite`. You can install it via `pip install "docarray[full]".` 
+This feature requires `annlite`. You can install it via `pip install "docarray[annlite]".` 
 ````
 
 
diff --git a/docs/advanced/document-store/elasticsearch.md b/docs/advanced/document-store/elasticsearch.md
@@ -4,7 +4,7 @@
 One can use [Elasticsearch](https://www.elastic.co) as the document store for DocumentArray. It is useful when one wants to have faster Document retrieval on embeddings, i.e. `.match()`, `.find()`.
 
 ````{tip}
-This feature requires `elasticsearch`. You can install it via `pip install "docarray[full]".` 
+This feature requires `elasticsearch`. You can install it via `pip install "docarray[elasticsearch]".` 
 ````
 
 ## Usage
diff --git a/docs/advanced/document-store/qdrant.md b/docs/advanced/document-store/qdrant.md
@@ -4,7 +4,7 @@
 One can use [Qdrant](https://qdrant.tech) as the document store for DocumentArray. It is useful when one wants to have faster Document retrieval on embeddings, i.e. `.match()`, `.find()`.
 
 ````{tip}
-This feature requires `qdrant-client`. You can install it via `pip install "docarray[full]".` 
+This feature requires `qdrant-client`. You can install it via `pip install "docarray[qdrant]".` 
 ````
 
 ## Usage
diff --git a/docs/advanced/document-store/weaviate.md b/docs/advanced/document-store/weaviate.md
@@ -4,7 +4,7 @@
 One can use [Weaviate](https://www.semi.technology) as the document store for DocumentArray. It is useful when one wants to have faster Document retrieval on embeddings, i.e. `.match()`, `.find()`.
 
 ````{tip}
-This feature requires `weaviate-client`. You can install it via `pip install "docarray[full]".` 
+This feature requires `weaviate-client`. You can install it via `pip install "docarray[weaviate]".` 
 ````
 
 Here is a video tutorial that guides you to build a simple image search using Weaviate and Docarray.
diff --git a/setup.py b/setup.py
@@ -62,18 +62,24 @@
             'av',
             'fastapi',
             'uvicorn',
+            'strawberry-graphql',
             'weaviate-client~=3.3.0',
             'annlite>=0.3.0',
             'qdrant-client~=0.7.1',
-            'strawberry-graphql',
             'elasticsearch>=8.0.1',
         ],
         'qdrant': [
-            'qdrant-client~=0.7.0',
+            'qdrant-client~=0.7.1',
         ],
         'annlite': [
             'annlite>=0.3.0',
         ],
+        'weaviate': [
+            'weaviate-client~=3.3.0',
+        ],
+        'elasticsearch': [
+            'elasticsearch>=8.0.1',
+        ],
         'test': [
             'pytest',
             'pytest-timeout',
@@ -95,6 +101,7 @@
             'transformers>=4.16.2',
             'weaviate-client~=3.3.0',
             'annlite>=0.3.0',
+            'elasticsearch>=8.0.1',
             'jina',
         ],
     },
