Add Couchbase vector store docs

integrations/langchain/vector-stores/README.md

@@ -3,6 +3,7 @@
 A vector store or vector database refers to a type of database system that specializes in storing and retrieving high-dimensional numerical vectors. Vector stores are designed to efficiently manage and index these vectors, allowing for fast similarity searches.
 
 * [Chroma](chroma.md)
+* [Couchbase](couchbase.md)
 * [Pinecone](pinecone.md)
 * [Qdrant](qdrant.md)
 * [SingleStore](singlestore-1.md)

integrations/langchain/vector-stores/couchbase.md

@@ -0,0 +1,154 @@
+# Couchbase
+
+## Prerequisites
+
+- Couchbase Cluster (Self Managed or Capella) version 7.6+  with [Search Service](https://docs.couchbase.com/server/current/fts/fts-introduction.html)
+
+
+### Setup Database Configuration
+
+#### Capella Setup
+
+To know more about connecting to your Capella cluster, please follow the [instructions](https://docs.couchbase.com/cloud/get-started/connect.html).
+
+Specifically, you need to do the following:
+
+- Create the [database credentials](https://docs.couchbase.com/cloud/clusters/manage-database-users.html) to access cluster via SDK
+- [Allow access](https://docs.couchbase.com/cloud/clusters/allow-ip-address.html) to the Cluster from the IP on which the application is running.
+
+#### Self Managed Setup
+
+- Follow [Couchbase Installation Options](/tutorial-couchbase-installation-options) for installing the latest Couchbase Database Server Instance. Make sure to add the [Search Service](https://docs.couchbase.com/server/current/fts/fts-introduction.html)
+
+
+### Create the Search Index on Full Text Service
+
+We need to create the Search Index on the Full Text Service in Couchbase. For example, you can import the following index using the instructions.
+
+- [Couchbase Capella](https://docs.couchbase.com/cloud/search/import-search-index.html)
+
+  - Copy the index definition to a new file index.json
+  - Import the file in Capella using the instructions in the documentation.
+  - Click on Create Index to create the index.
+
+- [Couchbase Server](https://docs.couchbase.com/server/current/search/import-search-index.html)
+
+  - Click on Search -> Add Index -> Import
+  - Copy the following Index definition in the Import screen
+  - Click on Create Index to create the index.
+
+You may also create a vector index using Search UI on both [Couchbase Capella](https://docs.couchbase.com/cloud/vector-search/create-vector-search-index-ui.html) and [Couchbase Self Managed Server](https://docs.couchbase.com/server/current/vector-search/create-vector-search-index-ui.html)
+
+
+#### Index Definition
+
+Here, we are creating the index `vector-index` on the documents. We are defining an index on the `testing` bucket's `_default` scope on the `_default` collection with the vector field set to `embedding` with 1536 dimensions and the text field set to `text`. We are also indexing and storing all the fields under `metadata` in the document as a dynamic mapping to account for varying document structures. The similarity metric is set to `dot_product`. If there is a change in these parameters, please adapt the index accordingly.
+
+```json
+{
+  "name": "vector-index",
+  "type": "fulltext-index",
+  "params": {
+    "doc_config": {
+      "docid_prefix_delim": "",
+      "docid_regexp": "",
+      "mode": "type_field",
+      "type_field": "type"
+    },
+    "mapping": {
+      "default_analyzer": "standard",
+      "default_datetime_parser": "dateTimeOptional",
+      "default_field": "_all",
+      "default_mapping": {
+        "dynamic": true,
+        "enabled": true,
+        "properties": {
+          "metadata": {
+            "dynamic": true,
+            "enabled": true
+          },
+          "embedding": {
+            "enabled": true,
+            "dynamic": false,
+            "fields": [
+              {
+                "dims": 1536,
+                "index": true,
+                "name": "embedding",
+                "similarity": "dot_product",
+                "type": "vector",
+                "vector_index_optimized_for": "recall"
+              }
+            ]
+          },
+          "text": {
+            "enabled": true,
+            "dynamic": false,
+            "fields": [
+              {
+                "index": true,
+                "name": "text",
+                "store": true,
+                "type": "text"
+              }
+            ]
+          }
+        }
+      },
+      "default_type": "_default",
+      "docvalues_dynamic": false,
+      "index_dynamic": true,
+      "store_dynamic": true,
+      "type_field": "_type"
+    },
+    "store": {
+      "indexType": "scorch",
+      "segmentVersion": 16
+    }
+  },
+  "sourceType": "gocbcore",
+  "sourceName": "testing",
+  "sourceParams": {},
+  "planParams": {
+    "maxPartitionsPerPIndex": 103,
+    "indexPartitions": 10,
+    "numReplicas": 0
+  }
+}
+```
+
+## Setup
+
+1. Add a new **Couchbase** node on canvas.
+2. Create new Couchbase credential using the connection string, username, password for the cluster.
+
+<figure><img src="../../../.gitbook/assets/couchbase/1.png" alt="" width="563"><figcaption></figcaption></figure>
+
+4. Enter the required fields into the **Couchbase** node:
+   * Select the above created credential from the dropdown
+   * Bucket name
+   * Scope name
+   * Collection name
+   * Index name
+
+<figure><img src="../../../.gitbook/assets/couchbase/2.png" alt="" width="239"><figcaption></figcaption></figure>
+
+5. **Document** input can be connected with any node under [**Document Loader**](../document-loaders/) category.
+6. **Embeddings** input can be connected with any node under [**Embeddings**](../embeddings/) category.
+
+7. Now you can start upserting data with Couchbase:
+
+<figure><img src="../../../.gitbook/assets/couchbase/3.png" alt="" width="900"><figcaption></figcaption></figure>
+
+<figure><img src="../../../.gitbook/assets/couchbase/4.png" alt="" width="900"><figcaption></figcaption></figure>
+
+
+8. Start querying!
+
+<figure><img src="../../../.gitbook/assets/couchbase/5.png" alt="" width="900"><figcaption></figcaption></figure>
+
+
+## Resources
+
+* [Couchbase documentation](https://docs.couchbase.com/home/index.html)
+* [LangChain JS Couchbase](https://js.langchain.com/docs/integrations/vectorstores/couchbase)