Google Cloud生成式AI助力营销优化的开源项目
这个开源项目展示了Google Cloud生成式AI在营销领域的应用。项目提供了从环境配置到实际使用的详细指南,涵盖营销洞察、受众分析、趋势发现和内容生成等功能。通过整合Vertex AI、BigQuery和Workspace等服务,项目旨在提升营销效率,支持数据驱动决策。项目还包含多个Jupyter笔记本,用于演示核心概念。此外,项目集成了Looker仪表板用于数据可视化,以及Vertex AI Search用于改进内容搜索体验。整体架构设计支持从数据分析到内容生成的全流程营销优化。
This repository provides a deployment guide showcasing the application of Google Cloud's Generative AI for marketing scenarios. It offers detailed, step-by-step guidance for setting up and utilizing the Generative AI tools, including examples of their use in crafting marketing materials like blog posts and social media content.
Additionally, supplementary Jupyter notebooks are provided to aid users in grasping the concepts explored in the demonstration.
The architecture of all the demos that are implemented in this application is as follows.
.
├── app
└── backend_apis
└── frontend
└── notebooks
└── templates
└── installation_scripts
└── tf
/app
: Architecture diagrams./backend_apis
: Source code for backend APIs./frontend
: Source code for the front end UI./notebooks
: Sample notebooks demonstrating the concepts covered in this demonstration./templates
: Workspace Slides, Docs and Sheets templates used in the demonstration./installation_scripts
: Installation scripts used by Terraform./tf
: Terraform installation scripts.In this repository, the following demonstrations are provided:
The notebooks listed below were developed to explain the concepts exposed in this repository:
The following additional (external) notebooks provide supplementary information on the concepts discussed in this repository:
This section outlines the steps to configure the Google Cloud environment that is required in order to run the code provided in this repository.
You will be interacting with the following resources:
In the Google Cloud Console, on the project selector page, select or create a Google Cloud project.
As this is a DEMONSTRATION, you need to be a project owner in order to set up the environment.
From Cloud Shell, run the following commands to enable the required Cloud APIs.
Replace <CHANGE TO YOUR PROJECT ID>
to the id of your project and <CHANGE TO YOUR LOCATION>
to the location where your resources will be deployed.
export PROJECT_ID=<CHANGE TO YOUR PROJECT ID> export LOCATION=<CHANGE TO YOUR LOCATION> gcloud config set project $PROJECT_ID
Enable the services:
gcloud services enable \ run.googleapis.com \ cloudbuild.googleapis.com \ compute.googleapis.com \ cloudresourcemanager.googleapis.com \ iam.googleapis.com \ container.googleapis.com \ cloudapis.googleapis.com \ cloudtrace.googleapis.com \ containerregistry.googleapis.com \ iamcredentials.googleapis.com \ secretmanager.googleapis.com \ firebase.googleapis.com gcloud services enable \ monitoring.googleapis.com \ logging.googleapis.com \ notebooks.googleapis.com \ aiplatform.googleapis.com \ storage.googleapis.com \ datacatalog.googleapis.com \ appengineflex.googleapis.com \ translate.googleapis.com \ admin.googleapis.com \ docs.googleapis.com \ drive.googleapis.com \ sheets.googleapis.com \ slides.googleapis.com \ firestore.googleapis.com
From Cloud Shell, execute the following commands:
<CHANGE TO YOUR PROJECT ID>
with your project ID.export PROJECT_ID=<CHANGE TO YOUR PROJECT ID>
gcloud auth application-default login
gcloud auth application-default $PROJECT_ID
From Cloud Shell, execute the following command:
git clone https://github.com/GoogleCloudPlatform/genai-for-marketing
Open the configuration file and include your project id (line 16) and location (line 17).
From Cloud Shell, navigate to /installation_scripts, install the python packages and execute the following script.
Make sure you have set the environmental variables PROJECT_ID and LOCATION.
cd ./genai-for-marketing/installation_scripts
pip3 install -r requirements.txt
Run the python script to create the BigQuery dataset and the DataCatalog TagTemplate.
python3 1_env_setup_script.py
Follow the steps below to create a search engine for a website using Vertex AI Search.
After you finished creating the Vertex AI Search datastore, navigate back to the Apps
page and copy the ID of the datastore you just created.
Example:
Open the configuration file - line 33 and include the datastore ID. Don't forget to save the configuration file.
Important: Alternatively, you can create a search engine for structure or unstructured data.
In order to render your Looker Dashboards in the Marketing Insights and Campaing Performance pages, you need to update a HTML file with links to them.
<option value="Overview">Overview</option>
<div *ngIf="overview" class="overviewcss"> <iframe width="1000" height="1000" src="https://googledemo.looker.com/embed/dashboards/2131?allow_login_screen=true" ></iframe> </div>
The allow_login_screen=true
in the URL will open the authentication page from Looker to secure the access to your account.
[Optional] If you have your Google Ads and Google Analytics 4 accounts in production, you can deploy the Marketing Analytics Jumpstart
solution to your project, build the Dashboards and link them to the demonstration UI.
Next you will create a Generative AI Agent that will assist the users to answer questions about Google Ads, etc.
agent-id
from the HTML code snippet provided by the platform.
dialogFlowCxAgendId
with the agent-id
.Follow the steps below to setup the Workspace integration with this demonstration.
name-of-the-sa@my-project.iam.gserviceaccount.com
.IMPORTANT: For security reasons, DON'T push this credentials to a public Github repository.
This demonstration will create folders under Google Drive, Google Docs documents, Google Slides presentations and Google Sheets documents.
When we create the Drive folder, we set the permission to all users under a specific domain.
Be aware that this configuration will share the folder with all the users in that domain.
If you want to change that behavior, explore different ways of sharing resources from this documentation:
https://developers.google.com/drive/api/reference/rest/v3/permissions#resource:-permission
[template] Marketing Assets
):
File
and Save as Google Slides
. Take note of the Slides ID from the URL.[template] Gen AI for Marketing Google Doc Template
):
File
and Save as Google Docs
. Take note of the Docs ID from the URL.[template] GenAI for Marketing
):
File
and Save as Google Sheets
. Take note of the Sheets ID from the URL.cd ./genai-for-marketing/backend_apis/
gcloud run deploy genai-marketing --source . --region us-central1 --allow-unauthenticated
https://marketing-image-tlmb7xv43q-uc.a.run.app
Enable Firebase
After you have a Firebase project, you can register your web app with that project.
In the center of the Firebase
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