mirror of
https://github.com/hwchase17/langchain.git
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9c0f84ae95
Cleaned up the `Integrations/Components/Memory` navbar by shortening the page titles. Updated page titles and file names to consistent formats.
335 lines
9.4 KiB
Plaintext
335 lines
9.4 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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}
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},
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"source": [
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"# Google Spanner\n",
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"> [Google Cloud Spanner](https://cloud.google.com/spanner) is a highly scalable database that combines unlimited scalability with relational semantics, such as secondary indexes, strong consistency, schemas, and SQL providing 99.999% availability in one easy solution.\n",
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"\n",
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"This notebook goes over how to use `Spanner` to store chat message history with the `SpannerChatMessageHistory` class.\n",
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"Learn more about the package on [GitHub](https://github.com/googleapis/langchain-google-spanner-python/).\n",
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"\n",
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"[](https://colab.research.google.com/github/googleapis/langchain-google-spanner-python/blob/main/samples/chat_message_history.ipynb)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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}
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},
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"source": [
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"## Before You Begin\n",
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"\n",
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"To run this notebook, you will need to do the following:\n",
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"\n",
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" * [Create a Google Cloud Project](https://developers.google.com/workspace/guides/create-project)\n",
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" * [Enable the Cloud Spanner API](https://console.cloud.google.com/flows/enableapi?apiid=spanner.googleapis.com)\n",
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" * [Create a Spanner instance](https://cloud.google.com/spanner/docs/create-manage-instances)\n",
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" * [Create a Spanner database](https://cloud.google.com/spanner/docs/create-manage-databases)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 🦜🔗 Library Installation\n",
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"The integration lives in its own `langchain-google-spanner` package, so we need to install it."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%pip install --upgrade --quiet langchain-google-spanner"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**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."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# # Automatically restart kernel after installs so that your environment can access the new packages\n",
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"# import IPython\n",
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"\n",
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"# app = IPython.Application.instance()\n",
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"# app.kernel.do_shutdown(True)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "yygMe6rPWxHS"
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},
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"source": [
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"### 🔐 Authentication\n",
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"Authenticate to Google Cloud as the IAM user logged into this notebook in order to access your Google Cloud Project.\n",
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"\n",
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"* If you are using Colab to run this notebook, use the cell below and continue.\n",
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"* If you are using Vertex AI Workbench, check out the setup instructions [here](https://github.com/GoogleCloudPlatform/generative-ai/tree/main/setup-env)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"id": "PTXN1_DSXj2b"
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},
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"outputs": [],
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"source": [
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"from google.colab import auth\n",
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"\n",
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"auth.authenticate_user()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "NEvB9BoLEulY"
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},
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"source": [
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"### ☁ Set Your Google Cloud Project\n",
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"Set your Google Cloud project so that you can leverage Google Cloud resources within this notebook.\n",
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"\n",
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"If you don't know your project ID, try the following:\n",
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"\n",
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"* Run `gcloud config list`.\n",
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"* Run `gcloud projects list`.\n",
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"* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"cellView": "form",
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"id": "gfkS3yVRE4_W"
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},
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"outputs": [],
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"source": [
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"# @markdown Please fill in the value below with your Google Cloud project ID and then run the cell.\n",
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"\n",
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"PROJECT_ID = \"my-project-id\" # @param {type:\"string\"}\n",
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"\n",
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"# Set the project id\n",
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"!gcloud config set project {PROJECT_ID}"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "rEWWNoNnKOgq"
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},
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"source": [
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"### 💡 API Enablement\n",
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"The `langchain-google-spanner` package requires that you [enable the Spanner API](https://console.cloud.google.com/flows/enableapi?apiid=spanner.googleapis.com) in your Google Cloud Project."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"id": "5utKIdq7KYi5"
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},
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"outputs": [],
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"source": [
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"# enable Spanner API\n",
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"!gcloud services enable spanner.googleapis.com"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "f8f2830ee9ca1e01"
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},
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"source": [
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"## Basic Usage"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "OMvzMWRrR6n7"
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},
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"source": [
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"### Set Spanner database values\n",
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"Find your database values, in the [Spanner Instances page](https://console.cloud.google.com/spanner)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"id": "irl7eMFnSPZr"
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},
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"outputs": [],
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"source": [
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"# @title Set Your Values Here { display-mode: \"form\" }\n",
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"INSTANCE = \"my-instance\" # @param {type: \"string\"}\n",
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"DATABASE = \"my-database\" # @param {type: \"string\"}\n",
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"TABLE_NAME = \"message_store\" # @param {type: \"string\"}"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "qPV8WfWr7O54"
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},
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"source": [
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"### Initialize a table\n",
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"The `SpannerChatMessageHistory` class requires a database table with a specific schema in order to store the chat message history.\n",
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"\n",
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"The helper method `init_chat_history_table()` that can be used to create a table with the proper schema for you."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "TEu4VHArRttE"
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},
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"outputs": [],
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"source": [
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"from langchain_google_spanner import (\n",
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" SpannerChatMessageHistory,\n",
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")\n",
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"\n",
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"SpannerChatMessageHistory.init_chat_history_table(table_name=TABLE_NAME)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### SpannerChatMessageHistory\n",
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"\n",
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"To initialize the `SpannerChatMessageHistory` class you need to provide only 3 things:\n",
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"\n",
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"1. `instance_id` - The name of the Spanner instance\n",
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"1. `database_id` - The name of the Spanner database\n",
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"1. `session_id` - A unique identifier string that specifies an id for the session.\n",
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"1. `table_name` - The name of the table within the database to store the chat message history."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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}
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},
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"outputs": [],
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"source": [
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"message_history = SpannerChatMessageHistory(\n",
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" instance_id=INSTANCE,\n",
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" database_id=DATABASE,\n",
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" table_name=TABLE_NAME,\n",
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" session_id=\"user-session-id\",\n",
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")\n",
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"\n",
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"message_history.add_user_message(\"hi!\")\n",
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"message_history.add_ai_message(\"whats up?\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"message_history.messages"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Custom client\n",
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"The client created by default is the default client. To use a non-default, a [custom client](https://cloud.google.com/spanner/docs/samples/spanner-create-client-with-query-options#spanner_create_client_with_query_options-python) can be passed to the constructor."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from google.cloud import spanner\n",
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"\n",
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"custom_client_message_history = SpannerChatMessageHistory(\n",
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" instance_id=\"my-instance\",\n",
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" database_id=\"my-database\",\n",
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" client=spanner.Client(...),\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Cleaning up\n",
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"\n",
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"When the history of a specific session is obsolete and can be deleted, it can be done the following way.\n",
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"Note: Once deleted, the data is no longer stored in Cloud Spanner and is gone forever."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"message_history = SpannerChatMessageHistory(\n",
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" instance_id=INSTANCE,\n",
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" database_id=DATABASE,\n",
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" table_name=TABLE_NAME,\n",
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" session_id=\"user-session-id\",\n",
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")\n",
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"\n",
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"message_history.clear()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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