community: LanceDB integration patch update

docs/docs/integrations/vectorstores/lancedb.ipynb

@@ -12,6 +12,16 @@
     "This notebook shows how to use functionality related to the `LanceDB` vector database based on the Lance data format."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "88ac92c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install -U langchain-openai"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -32,7 +42,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "id": "a0361f5c-e6f4-45f4-b829-11680cf03cec",
    "metadata": {
     "tags": []
@@ -47,25 +57,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "id": "aac9563e",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from langchain.embeddings import OpenAIEmbeddings\n",
-    "from langchain.vectorstores import LanceDB"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 13,
    "id": "a3c3999a",
    "metadata": {},
    "outputs": [],
    "source": [
     "from langchain.document_loaders import TextLoader\n",
+    "from langchain.vectorstores import LanceDB\n",
+    "from langchain_openai import OpenAIEmbeddings\n",
     "from langchain_text_splitters import CharacterTextSplitter\n",
     "\n",
     "loader = TextLoader(\"../../modules/state_of_the_union.txt\")\n",
@@ -75,22 +74,61 @@
     "embeddings = OpenAIEmbeddings()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "e9517bb0",
+   "metadata": {},
+   "source": [
+    "##### For LanceDB cloud, you can invoke the vector store as follows :\n",
+    "\n",
+    "\n",
+    "```python\n",
+    "db_url = \"db://lang_test\" # url of db you created\n",
+    "api_key = \"xxxxx\" # your API key\n",
+    "region=\"us-east-1-dev\"  # your selected region\n",
+    "\n",
+    "vector_store = LanceDB(\n",
+    "    uri=db_url,\n",
+    "    api_key=api_key,\n",
+    "    region=region,\n",
+    "    embedding=embeddings,\n",
+    "    table_name='langchain_test'\n",
+    "    )\n",
+    "```\n"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 7,
    "id": "6e104aee",
    "metadata": {},
    "outputs": [],
    "source": [
     "docsearch = LanceDB.from_documents(documents, embeddings)\n",
-    "\n",
     "query = \"What did the president say about Ketanji Brown Jackson\"\n",
     "docs = docsearch.similarity_search(query)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "f5e1cdfd",
+   "metadata": {},
+   "source": [
+    "Additionaly, to explore the table you can load it into a df or save it in a csv file: \n",
+    "```python\n",
+    "tbl = docsearch.get_table()\n",
+    "print(\"tbl:\", tbl)\n",
+    "pd_df = tbl.to_pandas()\n",
+    "# pd_df.to_csv(\"docsearch.csv\", index=False)\n",
+    "\n",
+    "# you can also create a new vector store object using an older connection object:\n",
+    "vector_store = LanceDB(connection=tbl, embedding=embeddings)\n",
+    "```"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 9,
    "id": "9c608226",
    "metadata": {},
    "outputs": [
@@ -166,7 +204,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 10,
    "id": "a359ed74",
    "metadata": {},
    "outputs": [
@@ -267,7 +305,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

docs/docs/modules/data_connection/indexing.ipynb

@@ -60,7 +60,7 @@
     "   * document addition by id (`add_documents` method with `ids` argument)\n",
     "   * delete by id (`delete` method with `ids` argument)\n",
     "\n",
-    "Compatible Vectorstores: `AnalyticDB`, `AstraDB`, `AwaDB`, `Bagel`, `Cassandra`, `Chroma`, `CouchbaseVectorStore`, `DashVector`, `DatabricksVectorSearch`, `DeepLake`, `Dingo`, `ElasticVectorSearch`, `ElasticsearchStore`, `FAISS`, `HanaDB`, `Milvus`, `MyScale`, `OpenSearchVectorSearch`, `PGVector`, `Pinecone`, `Qdrant`, `Redis`, `Rockset`, `ScaNN`, `SupabaseVectorStore`, `SurrealDBStore`, `TimescaleVector`, `Vald`, `VDMS`, `Vearch`, `VespaStore`, `Weaviate`, `ZepVectorStore`, `TencentVectorDB`, `OpenSearchVectorSearch`.\n",
+    "Compatible Vectorstores: `AnalyticDB`, `AstraDB`, `AwaDB`, `Bagel`, `Cassandra`, `Chroma`, `CouchbaseVectorStore`, `DashVector`, `DatabricksVectorSearch`, `DeepLake`, `Dingo`, `ElasticVectorSearch`, `ElasticsearchStore`, `FAISS`, `HanaDB`, `LanceDB`, `Milvus`, `MyScale`, `OpenSearchVectorSearch`, `PGVector`, `Pinecone`, `Qdrant`, `Redis`, `Rockset`, `ScaNN`, `SupabaseVectorStore`, `SurrealDBStore`, `TimescaleVector`, `Vald`, `VDMS`, `Vearch`, `VespaStore`, `Weaviate`, `ZepVectorStore`, `TencentVectorDB`, `OpenSearchVectorSearch`.\n",
     "  \n",
     "## Caution\n",
     "\n",