configure cloudshell to run walkthrough
This commit is contained in:
Robert Wilkins III
Gabriel Luiz Freitas Almeida
parent
ff3817903f
commit
50b24f9443
5 changed files with 266 additions and 10 deletions
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@ -1,7 +1,7 @@
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# Running Langflow from a new Google Cloud project
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This guide will help you set up a Langflow Dev VM in a Google Cloud Platform project using Google Cloud Shell.
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[](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts&shellonly=true&tutorial=gcp_setup_tutorial.yaml)
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[](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial.md)
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## Run the following in your GCP cloudshell:
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10
README.md
10
README.md
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@ -19,7 +19,7 @@
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LangFlow is a GUI for [LangChain](https://github.com/hwchase17/langchain), designed with [react-flow](https://github.com/wbkd/react-flow) to provide an effortless way to experiment and prototype flows with drag-and-drop components and a chat box.
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## 📦 Installation
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### <b>Locally</b>
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You can install LangFlow from pip:
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`pip install langflow`
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@ -28,6 +28,14 @@ Next, run:
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`langflow`
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### Deploy Langflow on Google Cloud Platform
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Follow our step-by-step guide to deploy Langflow on Google Cloud Platform (GCP) using Google Cloud Shell. The guide is available in the [Langflow in Google Cloud Platform](GCP_DEPLOYMENT.md) document.
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Alternatively, click the "Open in Cloud Shell" button below to launch Google Cloud Shell, clone the Langflow repository, and start an interactive tutorial that will guide you through the process of setting up the necessary resources and deploying Langflow on your GCP project.
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[](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts&shellonly=true&tutorial=GCP_SETUP_TUTORIAL.md)
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## 🎨 Creating Flows
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Creating flows with LangFlow is easy. Simply drag sidebar components onto the canvas and connect them together to create your pipeline. LangFlow provides a range of [LangChain components](https://langchain.readthedocs.io/en/latest/reference.html) to choose from, including LLMs, prompt serializers, agents, and chains.
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# Set the VM, image, and networking configuration
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VM_NAME="langflow-dev"
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IMAGE_FAMILY="debian-11"
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IMAGE_PROJECT="debian-cloud"
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BOOT_DISK_SIZE="100GB"
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ZONE="us-central1-a"
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REGION="us-central1"
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VPC_NAME="default"
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SUBNET_NAME="default"
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SUBNET_RANGE="10.128.0.0/20"
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NAT_GATEWAY_NAME="nat-gateway"
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CLOUD_ROUTER_NAME="nat-client"
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# Set the GCP project's compute region
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gcloud config set compute/region $REGION
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# Check if the VPC exists, and create it if not
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vpc_exists=$(gcloud compute networks list --filter="name=$VPC_NAME" --format="value(name)")
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if [[ -z "$vpc_exists" ]]; then
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gcloud compute networks create $VPC_NAME --subnet-mode=custom
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fi
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# Check if the subnet exists, and create it if not
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subnet_exists=$(gcloud compute networks subnets list --filter="name=$SUBNET_NAME AND region=$REGION" --format="value(name)")
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if [[ -z "$subnet_exists" ]]; then
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gcloud compute networks subnets create $SUBNET_NAME --network=$VPC_NAME --region=$REGION --range=$SUBNET_RANGE
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fi
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# Create a firewall rule to allow TCP port 8080 for all instances in the VPC
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firewall_8080_exists=$(gcloud compute firewall-rules list --filter="name=allow-tcp-8080" --format="value(name)")
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if [[ -z "$firewall_8080_exists" ]]; then
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gcloud compute firewall-rules create allow-tcp-8080 --network $VPC_NAME --allow tcp:8080 --source-ranges 0.0.0.0/0 --direction INGRESS
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fi
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# Create a firewall rule to allow IAP traffic
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firewall_iap_exists=$(gcloud compute firewall-rules list --filter="name=allow-iap" --format="value(name)")
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if [[ -z "$firewall_iap_exists" ]]; then
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gcloud compute firewall-rules create allow-iap --network $VPC_NAME --allow tcp:80,tcp:443 --source-ranges 35.235.240.0/20 --direction INGRESS
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fi
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# Create the Cloud Router and NAT Gateway
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cloud_router_exists=$(gcloud compute routers list --filter="name=$CLOUD_ROUTER_NAME" --format="value(name)")
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if [[ -z "$cloud_router_exists" ]]; then
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gcloud compute routers create $CLOUD_ROUTER_NAME --network $VPC_NAME --region $REGION
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fi
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nat_exists=$(gcloud compute routers list --filter="name=$CLOUD_ROUTER_NAME" --format="value(nats.name)")
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if [[ -z "$nat_exists" ]]; then
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gcloud compute routers nats create $NAT_GATEWAY_NAME --router $CLOUD_ROUTER_NAME --auto-allocate-nat-external-ips --nat-all-subnet-ip-ranges --enable-logging --region $REGION
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fi
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# Define the startup script as a multiline Bash here-doc
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STARTUP_SCRIPT=$(cat <<'EOF'
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#!/bin/bash
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# Update and upgrade the system
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apt -y update
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apt -y upgrade
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# Install Python 3 pip, Langflow, and Nginx
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apt -y install python3-pip
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pip install langflow
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apt-get -y install nginx
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# Configure Nginx for Langflow
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touch /etc/nginx/sites-available/langflow-app
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echo "server {
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listen 0.0.0.0:8080;
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location / {
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proxy_pass http://127.0.0.1:7860;
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proxy_set_header Host "\$host";
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proxy_set_header X-Real-IP "\$remote_addr";
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proxy_set_header X-Forwarded-For "\$proxy_add_x_forwarded_for";
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}
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}" >> /etc/nginx/sites-available/langflow-app
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ln -s /etc/nginx/sites-available/langflow-app /etc/nginx/sites-enabled/
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sudo nginx -t
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sudo systemctl restart nginx
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langflow
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EOF
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)
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# Create a temporary file to store the startup script
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tempfile=$(mktemp)
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echo "$STARTUP_SCRIPT" > $tempfile
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# Create the VM instance with the specified configuration and startup script
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gcloud compute instances create $VM_NAME \
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--image-family $IMAGE_FAMILY \
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--image-project $IMAGE_PROJECT \
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--boot-disk-size $BOOT_DISK_SIZE \
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--machine-type=n1-standard-4 \
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--metadata-from-file startup-script=$tempfile \
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--zone $ZONE \
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--network $VPC_NAME \
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--subnet $SUBNET_NAME
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# Remove the temporary file after the VM is created
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rm $tempfile
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@ -1,10 +1,80 @@
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title: Setting up Langflow on GCP
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description: This tutorial guides you through setting up Langflow on GCP
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steps:
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- title: Running setup script
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content: |
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Running the setup script to create resources and deploy Langflow on GCP.
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title: Deploy Langflow on Google Cloud Platform
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duration: 45m
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author: Your Name
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environment:
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cwd: working_dir
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repo:
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url: https://github.com/genome21/langflow
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working_dir: scripts
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steps:
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- title: Introduction
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content: |
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In this tutorial, you will learn how to deploy Langflow on Google Cloud Platform (GCP) using Google Cloud Shell.
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This tutorial assumes you have a GCP account and basic knowledge of Google Cloud Shell. If you're not familiar with Cloud Shell, you can review the [Cloud Shell documentation](https://cloud.google.com/shell/docs).
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- title: Set up your environment
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content: |
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Before you start, make sure you have the following prerequisites:
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- A GCP account with the necessary permissions to create resources
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- A project on GCP where you want to deploy Langflow
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<walkthrough-project-setup></walkthrough-project-setup>
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In the next step, you'll clone the Langflow repository and navigate to the `scripts` directory.
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- title: Clone the repository and navigate to the scripts directory
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content: |
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Run the following commands to clone the Langflow repository and navigate to the `scripts` directory:
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```bash
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source gcp_setup.sh
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```
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git clone https://github.com/genome21/langflow
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cd langflow/scripts
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```
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In the next step, you'll configure the GCP environment and deploy Langflow.
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- title: Configure the GCP environment and deploy Langflow
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content: |
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Run the `deploy_langflow_gcp.sh` script to configure the GCP environment and deploy Langflow:
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```
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./deploy_langflow_gcp.sh
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```
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The script will:
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1. Check if the required resources (VPC, subnet, firewall rules, and Cloud Router) exist and create them if needed
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2. Create a startup script to install Python, Langflow, and Nginx
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3. Create a Compute Engine VM instance with the specified configuration and startup script
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4. Configure Nginx to serve Langflow on TCP port 8080
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In the next step, you'll learn how to connect to the Langflow VM.
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- title: Connect to the Langflow VM
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content: |
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To connect to your new Langflow VM, follow these steps:
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1. Navigate to the [VM instances](https://console.cloud.google.com/compute/instances) page
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2. Click on the external IP for your VM
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3. Add port 8080 (assuming your VM external IP is 192.168.0.1):
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http://192.168.0.1:8080
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4. You will be greeted by the Langflow Dev environment
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Congratulations! You have successfully deployed Langflow on Google Cloud Platform.
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- title: Cleanup
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content: |
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If you want to remove the resources created during this tutorial, you can use the following commands:
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```
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gcloud compute instances delete langflow-dev --zone us-central1-a --quiet
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gcloud compute routers nats delete nat-gateway --router nat-client --region us-central1 --quiet
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gcloud compute routers delete nat-client --region us-central1 --quiet
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gcloud compute firewall-rules delete allow-tcp-8080 --quiet
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gcloud compute firewall-rules delete allow-iap --quiet
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gcloud compute networks subnets delete default --region us-central1 --quiet
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gcloud compute networks delete default --quiet
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``
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78
scripts/walkthroughtutorial.md
Normal file
78
scripts/walkthroughtutorial.md
Normal file
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@ -0,0 +1,78 @@
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# Deploy Langflow on Google Cloud Platform
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**Duration**: 45 minutes
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**Author**: [Robert Wilkins III](https://www.linkedin.com/in/robertwilkinsiii)
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## Introduction
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In this tutorial, you will learn how to deploy Langflow on [Google Cloud Platform](https://cloud.google.com/) (GCP) using Google Cloud Shell.
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This tutorial assumes you have a GCP account and basic knowledge of Google Cloud Shell. If you're not familiar with Cloud Shell, you can review the [Cloud Shell documentation](https://cloud.google.com/shell/docs).
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## Set up your environment
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Before you start, make sure you have the following prerequisites:
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- A GCP account with the necessary permissions to create resources
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- A project on GCP where you want to deploy Langflow
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[**Select your GCP project**]<walkthrough-project-setup></walkthrough-project-setup>
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In the next step, you'll clone the Langflow repository and navigate to the `scripts` directory.
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## Clone the repository and navigate to the scripts directory
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Run the following commands to clone the Langflow repository and navigate to the `scripts` directory:
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```bash
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git clone https://github.com/genome21/langflow
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cd langflow/scripts
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```
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In the next step, you'll configure the GCP environment and deploy Langflow.
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## Configure the GCP environment and deploy Langflow
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Run the deploy_langflow_gcp.sh script to configure the GCP environment and deploy Langflow:
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```bash
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./deploy_langflow_gcp.sh
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```
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The script will:
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1. Check if the required resources (VPC, subnet, firewall rules, and Cloud Router) exist and create them if needed
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2. Create a startup script to install Python, Langflow, and Nginx
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3. Create a Compute Engine VM instance with the specified configuration and startup script
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4. Configure Nginx to serve Langflow on TCP port 8080
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In the next step, you'll learn how to connect to the Langflow VM.
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## Connect to the Langflow VM
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To connect to your new Langflow VM, follow these steps:
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1. Navigate to the [VM instances](https://console.cloud.google.com/compute/instances) page
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2. Click on the external IP for your VM
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3. Add port 8080 (assuming your VM external IP is 192.168.0.1):
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http://192.168.0.1:8080
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4. You will be greeted by the Langflow Dev environment
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Congratulations! You have successfully deployed Langflow on Google Cloud Platform.
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## Cleanup
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If you want to remove the resources created during this tutorial, you can use the following commands:
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```sql
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gcloud compute instances delete langflow-dev --zone us-central1-a --quiet
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gcloud compute routers nats delete nat-gateway --router nat-client --region us-central1 --quiet
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gcloud compute routers delete nat-client --region us-central1 --quiet
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gcloud compute firewall-rules delete allow-tcp-8080 --quiet
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gcloud compute firewall-rules delete allow-iap --quiet
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gcloud compute networks subnets delete default --region us-central1 --quiet
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gcloud compute networks delete default --quiet
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```
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