googleapis · kurtismassey · Aug 10, 2024 · Aug 11, 2024 · Sep 11, 2024 · Sep 11, 2024
@@ -0,0 +1,189 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Google Firestore (Native Mode)\n",
+    "\n",
+    "> [Firestore](https://cloud.google.com/firestore) is a serverless document-oriented database that scales to meet any demand. Extend your database application to build AI-powered experiences leveraging Firestore's LangChain integrations.\n",
+    "\n",
+    "This notebook goes over how to use [Firestore](https://cloud.google.com/firestore) as a record manager for [langchain indexing](https://python.langchain.com/v0.1/docs/modules/data_connection/indexing/) your Vectorstore.\n",
+    "\n",
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/googleapis/langchain-google-firestore-python/blob/main/docs/record_manager.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Before You Begin\n",
+    "\n",
+    "To run this notebook, you will need to do the following:\n",
+    "\n",
+    "* [Create a Google Cloud Project](https://developers.google.com/workspace/guides/create-project)\n",
+    "* [Enable the Firestore API](https://console.cloud.google.com/flows/enableapi?apiid=firestore.googleapis.com)\n",
+    "* [Create a Firestore database](https://cloud.google.com/firestore/docs/manage-databases)\n",
+    "\n",
+    "After confirmed access to database in the runtime environment of this notebook, filling the following values and run the cell before running example scripts."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @markdown Please specify a source for demo purpose.\n",
+    "COLLECTION_NAME = \"test\"  # @param {type:\"CollectionReference\"|\"string\"}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 🦜🔗 Library Installation\n",
+    "\n",
+    "The integration lives in its own `langchain-google-firestore` package, so we need to install it. For this notebook, we will also install `langchain-google-genai` to use Google Generative AI embeddings."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install --upgrade --quiet langchain langchain-google-firestore langchain-google-vertexai"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Colab only**: Uncomment the following cell to restart the kernel or use the button to restart the kernel. For Vertex AI Workbench you can restart the terminal using the button on top."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Automatically restart kernel after installs so that your environment can access the new packages\n",
+    "# import IPython\n",
+    "\n",
+    "# app = IPython.Application.instance()\n",
+    "# app.kernel.do_shutdown(True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### ☁ Set Your Google Cloud Project\n",
+    "Set your Google Cloud project so that you can leverage Google Cloud resources within this notebook.\n",
+    "\n",
+    "If you don't know your project ID, try the following:\n",
+    "\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @markdown Please fill in the value below with your Google Cloud project ID and then run the cell.\n",
+    "\n",
+    "PROJECT_ID = \"extensions-testing\"  # @param {type:\"string\"}\n",
+    "\n",
+    "# Set the project id\n",
+    "!gcloud config set project {PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 🔐 Authentication\n",
+    "\n",
+    "Authenticate to Google Cloud as the IAM user logged into this notebook in order to access your Google Cloud Project.\n",
+    "\n",
+    "- If you are using Colab to run this notebook, use the cell below and continue.\n",
+    "- If you are using Vertex AI Workbench, check out the setup instructions [here](https://github.com/GoogleCloudPlatform/generative-ai/tree/main/setup-env)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from google.colab import auth\n",
+    "\n",
+    "auth.authenticate_user()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Basic Usage"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Initialize FirestoreRecordManager\n",
+    "\n",
+    "`FirestoreRecordManager` allows you to index your vectorstore in a Firestore database. You can use it to store references to embeddings from any model, including those from Google Generative AI."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.indexes import index\n",
+    "from langchain_core.documents import Document\n",
+    "from langchain_google_firestore import FirestoreVectorStore, FirestoreRecordManager\n",
+    "from langchain_google_vertexai import VertexAIEmbeddings\n",
+    "\n",
+    "namespace = f\"firstore/{COLLECTION_NAME}\"\n",
+    "record_manager = FirestoreRecordManager(namespace)\n",
+    "\n",
+    "embedding = VertexAIEmbeddings(model_name=\"textembedding-gecko@latest\")\n",
+    "vectorstore = FirestoreVectorStore(\n",
+    "    collection=COLLECTION_NAME,\n",
+    "    embedding_service=embedding\n",
+    ")\n",
+    "\n",
+    "doc1 = Document(page_content=\"test-doc-1-content\", metadata={\"source\": \"test-doc-1.txt\"})\n",
+    "doc2 = Document(page_content=\"test-doc-2-content\", metadata={\"source\": \"test-doc-2.txt\"})\n",
+    "doc3 = Document(page_content=\"test-doc-3-content\", metadata={\"source\": \"test-doc-3.txt\"})\n",
+    "\n",
+    "results = index(\n",
+    "    [doc1, doc2, doc3],\n",
+    "    record_manager,\n",
+    "    vectorstore,\n",
+    "    cleanup=\"incremental\",\n",
+    "    source_id_key=\"source\",\n",
+    ")\n",
+    "\n",
+    "print(results)"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
@@ -15,12 +15,14 @@
 from .chat_message_history import FirestoreChatMessageHistory
 from .document_loader import FirestoreLoader, FirestoreSaver
 from .vectorstores import FirestoreVectorStore
+from .record_manager import FirestoreRecordManager
 from .version import __version__
 
 __all__ = [
     "FirestoreChatMessageHistory",
     "FirestoreLoader",
     "FirestoreSaver",
     "FirestoreVectorStore",
+    "FirestoreRecordManager",
     "__version__",
 ]