Rename AstraDB

docs/docs/components/vector-stores.mdx

@@ -1,14 +1,15 @@
-import Admonition from '@theme/Admonition';
+import Admonition from "@theme/Admonition";
 
 # Vector Stores
 
 <Admonition type="caution" icon="🚧" title="ZONE UNDER CONSTRUCTION">
   <p>
-        We appreciate your understanding as we polish our documentation – it may contain some rough edges. Share your feedback or report issues to help us improve! 🛠️📝
+    We appreciate your understanding as we polish our documentation – it may
+    contain some rough edges. Share your feedback or report issues to help us
+    improve! 🛠️📝
   </p>
 </Admonition>
 
-
 ### Astra DB
 
 The `Astra DB` is a component for initializing an Astra DB Vector Store from Records. It facilitates the creation of Astra DB-based vector indexes for efficient document storage and retrieval.
@@ -118,7 +119,6 @@ The `Chroma` is a component designed for implementing a Vector Store using Chrom
 
 - **Server SSL Enabled (Optional):** Whether to enable SSL for the Chroma server.
 
-
 - **Input:** Input data for creating the Vector Store.
 
 - **Embedding:** The embeddings to use for the Vector Store.
@@ -129,7 +129,6 @@ For detailed documentation and integration guides, please refer to the [Chroma C
 
 ### Chroma Search
 
-
 The `ChromaSearch` is a component designed for searching a Chroma collection for similar documents. This component integrates with Chroma to facilitate efficient document retrieval based on similarity metrics.
 
 **Params**
@@ -154,7 +153,6 @@ The `ChromaSearch` is a component designed for searching a Chroma collection for
 
 - **Server SSL Enabled (Optional):** Whether SSL is enabled for the Chroma server.
 
-
 ---
 
 ### FAISS
@@ -171,7 +169,6 @@ The `FAISS` is a component designed for ingesting documents into a FAISS Vector
 
 - **Index Name:** The name of the FAISS index.
 
-
 For detailed documentation and integration guides, please refer to the [FAISS Component Documentation](https://faiss.ai/index.html).
 
 ---
@@ -190,10 +187,8 @@ The `FAISSSearch` is a component for searching a FAISS Vector Store for similar
 
 - **Index Name:** The name of the FAISS index.
 
-
 ---
 
-
 ### MongoDB Atlas
 
 The `MongoDBAtlas` is a component used to construct a MongoDB Atlas Vector Search vector store from Records. It facilitates the creation of MongoDB Atlas-based vector stores for efficient document storage and retrieval.
@@ -214,11 +209,8 @@ The `MongoDBAtlas` is a component used to construct a MongoDB Atlas Vector Searc
 
 - **Search Kwargs:** Additional search arguments for MongoDB Atlas.
 
-
 <Admonition type="note" title="Note">
-    <p>
+  <p>Ensure that pymongo is installed to use MongoDB Atlas Vector Store.</p>
-        Ensure that pymongo is installed to use MongoDB Atlas Vector Store.
-    </p>
 </Admonition>
 
 ---
@@ -245,7 +237,6 @@ The `MongoDBAtlasSearch` is a component for searching a MongoDB Atlas Vector Sto
 
 - **Search Kwargs:** Additional search arguments for MongoDB Atlas.
 
-
 ---
 
 ### PGVector
@@ -262,13 +253,12 @@ The `PGVector` is a component for implementing a Vector Store using PostgreSQL.
 
 - **Table:** The name of the table in the PostgreSQL database.
 
-
 For detailed documentation and integration guides, please refer to the [PGVector Component Documentation](https://python.langchain.com/docs/integrations/vectorstores/pgvector).
 
-
 <Admonition type="note" title="Note">
   <p>
-        Ensure that the required PostgreSQL server is accessible and properly configured.
+    Ensure that the required PostgreSQL server is accessible and properly
+    configured.
   </p>
 </Admonition>
 
@@ -290,7 +280,6 @@ The `PGVectorSearch` is a component for searching a PGVector Store for similar d
 
 - **Search Type:** The type of search to perform (e.g., "Similarity", "MMR").
 
-
 ---
 
 ### Pinecone
@@ -315,10 +304,10 @@ The `Pinecone` is a component used to construct a Pinecone wrapper from Records.
 
 - **Pool Threads:** The number of threads to use for Pinecone.
 
-
 <Admonition type="note" title="Note">
   <p>
-        Ensure that the required Pinecone API key and environment are properly configured.
+    Ensure that the required Pinecone API key and environment are properly
+    configured.
   </p>
 </Admonition>
 
@@ -348,7 +337,6 @@ The `PineconeSearch` is a component used to search a Pinecone Vector Store for s
 
 - **Pool Threads:** The number of threads to use for Pinecone.
 
-
 ---
 
 ### Qdrant
@@ -463,7 +451,9 @@ For detailed documentation, please refer to the [Redis Documentation](https://py
 
 <Admonition type="note" title="Note">
   <p>
-        Ensure that the required Redis server connection URL and index name are properly configured. If no documents are provided, a schema must be provided.
+    Ensure that the required Redis server connection URL and index name are
+    properly configured. If no documents are provided, a schema must be
+    provided.
   </p>
 </Admonition>
 
@@ -513,7 +503,8 @@ The `Supabase` is a component for initializing a Supabase Vector Store from text
 
 <Admonition type="note" title="Note">
   <p>
-        Ensure that the required Supabase service key, Supabase URL, and table name are properly configured.
+    Ensure that the required Supabase service key, Supabase URL, and table name
+    are properly configured.
   </p>
 </Admonition>
 
@@ -563,7 +554,8 @@ For detailed documentation and integration guides, please refer to the [Vectara
 
 <Admonition type="note" title="Note">
   <p>
-        If `inputs` are provided, they will be upserted to the corpus. If `files_url` are provided, Vectara will process the files from the URLs.
+    If `inputs` are provided, they will be upserted to the corpus. If
+    `files_url` are provided, Vectara will process the files from the URLs.
   </p>
 </Admonition>
 
@@ -586,6 +578,7 @@ The `VectaraSearch` is a component for searching a Vectara Vector Store for simi
 - **Vectara API Key:** The API key for Vectara.
 
 - **Files Url:** The URL(s) of the file(s) to be used for initializing the Vectara Vector Store (optional).
+
 ---
 
 ### Weaviate
@@ -614,7 +607,12 @@ For detailed documentation and integration guides, please refer to the [Weaviate
 
 <Admonition type="note" title="Note">
   <p>
-        Before using the Weaviate Vector Store component, ensure that you have a Weaviate instance running and accessible at the specified URL. Additionally, make sure to provide the correct API key for authentication if required. Adjust the index name, text key, and attributes according to your dataset and indexing requirements. Finally, ensure that the provided embeddings are compatible with Weaviate's requirements.
+    Before using the Weaviate Vector Store component, ensure that you have a
+    Weaviate instance running and accessible at the specified URL. Additionally,
+    make sure to provide the correct API key for authentication if required.
+    Adjust the index name, text key, and attributes according to your dataset
+    and indexing requirements. Finally, ensure that the provided embeddings are
+    compatible with Weaviate's requirements.
   </p>
 </Admonition>