partners: add langchain-vdms (#29857)

**Description:** Deprecate vdms in community, add integration
langchain-vdms, and update any related files
**Issue:** n/a
**Dependencies:** langchain-vdms
**Twitter handle:** n/a

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>

docs/docs/integrations/providers/vdms.mdx

@@ -9,53 +9,35 @@
 ### Install Client
 
 ```bash
-pip install vdms
+pip install langchain-vdms
 ```
 
 ### Install Database
 
 There are two ways to get started with VDMS:
 
-#### Install VDMS on your local machine via docker
-```bash
-    docker run -d -p 55555:55555 intellabs/vdms:latest
-```
-
-#### Install VDMS directly on your local machine
-Please see [installation instructions](https://github.com/IntelLabs/vdms/blob/master/INSTALL.md).
 
+1. Install VDMS on your local machine via docker
+    ```bash
+        docker run -d -p 55555:55555 intellabs/vdms:latest
+    ```
 
+2. Install VDMS directly on your local machine. Please see
+[installation instructions](https://github.com/IntelLabs/vdms/blob/master/INSTALL.md).
 
 ## VectorStore
 
-The vector store is a simple wrapper around VDMS. It provides a simple interface to store and retrieve data.
+To import this vectorstore:
 
 ```python
-from langchain_community.document_loaders import TextLoader
-from langchain.text_splitter import CharacterTextSplitter
-
-loader = TextLoader("./state_of_the_union.txt")
-documents = loader.load()
-text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=0)
-docs = text_splitter.split_documents(documents)
-
-from langchain_community.vectorstores import VDMS
-from langchain_community.vectorstores.vdms import VDMS_Client
-from langchain_huggingface import HuggingFaceEmbeddings
-
-client = VDMS_Client("localhost", 55555)
-model_name = "sentence-transformers/all-mpnet-base-v2"
-vectorstore = VDMS.from_documents(
-    docs,
-    client=client,
-    collection_name="langchain-demo",
-    embedding_function=HuggingFaceEmbeddings(model_name=model_name),
-    engine="FaissFlat"
-    distance_strategy="L2",
-)
-
-query = "What did the president say about Ketanji Brown Jackson"
-results = vectorstore.similarity_search(query)
+from langchain_vdms import VDMS
+from langchain_vdms.vectorstores import VDMS
 ```
 
-For a more detailed walkthrough of the VDMS wrapper, see [this notebook](/docs/integrations/vectorstores/vdms)
+To import the VDMS Client connector:
+
+```python
+from langchain_vdms.vectorstores import VDMS_Client
+```
+
+For a more detailed walkthrough of the VDMS wrapper, see [this guide](/docs/integrations/vectorstores/vdms).