community[minor]: Add Dria retriever (#17098)

[Dria](https://dria.co/) is a hub of public RAG models for developers to
both contribute and utilize a shared embedding lake. This PR adds a
retriever that can retrieve documents from Dria.

docs/docs/integrations/retrievers/dria_index.ipynb

@@ -0,0 +1,191 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "UYyFIEKEkmHb"
+   },
+   "source": [
+    "# Dria\n",
+    "\n",
+    "Dria is a hub of public RAG models for developers to both contribute and utilize a shared embedding lake. This notebook demonstrates how to use the Dria API for data retrieval tasks."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "VNTFUgK9kmHd"
+   },
+   "source": [
+    "# Installation\n",
+    "\n",
+    "Ensure you have the `dria` package installed. You can install it using pip:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "X--1A8EEkmHd"
+   },
+   "outputs": [],
+   "source": [
+    "%pip install --upgrade --quiet dria"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "xRbRL0SgkmHe"
+   },
+   "source": [
+    "# Configure API Key\n",
+    "\n",
+    "Set up your Dria API key for access."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "id": "hGqOByNMkmHe"
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "os.environ[\"DRIA_API_KEY\"] = \"DRIA_API_KEY\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "nDfAEqQtkmHe"
+   },
+   "source": [
+    "# Initialize Dria Retriever\n",
+    "\n",
+    "Create an instance of `DriaRetriever`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "vlyorgCckmHe"
+   },
+   "outputs": [],
+   "source": [
+    "from langchain.retrievers import DriaRetriever\n",
+    "\n",
+    "api_key = os.getenv(\"DRIA_API_KEY\")\n",
+    "retriever = DriaRetriever(api_key=api_key)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "j7WUY5jBOLQd"
+   },
+   "source": [
+    "# **Create Knowledge Base**\n",
+    "\n",
+    "Create a knowledge on [Dria's Knowledge Hub](https://dria.co/knowledge)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "L5ER81eWOKnt"
+   },
+   "outputs": [],
+   "source": [
+    "contract_id = retriever.create_knowledge_base(\n",
+    "    name=\"France's AI Development\",\n",
+    "    embedding=DriaRetriever.models.jina_embeddings_v2_base_en.value,\n",
+    "    category=\"Artificial Intelligence\",\n",
+    "    description=\"Explore the growth and contributions of France in the field of Artificial Intelligence.\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "9VCTzSFpkmHe"
+   },
+   "source": [
+    "# Add Data\n",
+    "\n",
+    "Load data into your Dria knowledge base."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "xeTMafIekmHf"
+   },
+   "outputs": [],
+   "source": [
+    "texts = [\n",
+    "    \"The first text to add to Dria.\",\n",
+    "    \"Another piece of information to store.\",\n",
+    "    \"More data to include in the Dria knowledge base.\",\n",
+    "]\n",
+    "\n",
+    "ids = retriever.add_texts(texts)\n",
+    "print(\"Data added with IDs:\", ids)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "dy1UlvLCkmHf"
+   },
+   "source": [
+    "# Retrieve Data\n",
+    "\n",
+    "Use the retriever to find relevant documents given a query."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "9y3msv9tkmHf"
+   },
+   "outputs": [],
+   "source": [
+    "query = \"Find information about Dria.\"\n",
+    "result = retriever.get_relevant_documents(query)\n",
+    "for doc in result:\n",
+    "    print(doc)"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.x"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}