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4
GCP_DEPLOYMENT.md
View file

@ -6,14 +6,14 @@ This guide will help you set up a Langflow development VM in a Google Cloud Plat
## Standard VM ## Standard VM
[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial.md) [![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/logspace-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial.md)
This script sets up a Debian-based VM with the Langflow package, Nginx, and the necessary configurations to run the Langflow Dev environment. This script sets up a Debian-based VM with the Langflow package, Nginx, and the necessary configurations to run the Langflow Dev environment.
<hr> <hr>
## Spot/Preemptible Instance ## Spot/Preemptible Instance
[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial.md) [![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial_spot.md)
When running as a [spot (preemptible) instance](https://cloud.google.com/compute/docs/instances/preemptible), the code and VM will behave the same way as in a regular instance, executing the startup script to configure the environment, install necessary dependencies, and run the Langflow application. However, **due to the nature of spot instances, the VM may be terminated at any time if Google Cloud needs to reclaim the resources**. This makes spot instances suitable for fault-tolerant, stateless, or interruptible workloads that can handle unexpected terminations and restarts. When running as a [spot (preemptible) instance](https://cloud.google.com/compute/docs/instances/preemptible), the code and VM will behave the same way as in a regular instance, executing the startup script to configure the environment, install necessary dependencies, and run the Langflow application. However, **due to the nature of spot instances, the VM may be terminated at any time if Google Cloud needs to reclaim the resources**. This makes spot instances suitable for fault-tolerant, stateless, or interruptible workloads that can handle unexpected terminations and restarts.

9
README.md
View file

@ -37,6 +37,15 @@ or
langflow langflow
``` ```
### Deploy Langflow on Google Cloud Platform
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.
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.
[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/logspace-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial_spot.md)
### Deploy Langflow on Google Cloud Platform ### Deploy Langflow on Google Cloud Platform
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. 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.

2
docker-compose.yml
View file

@ -17,6 +17,8 @@ services:
dockerfile: ./dev.Dockerfile dockerfile: ./dev.Dockerfile
args: args:
- BACKEND_URL=http://backend:7860 - BACKEND_URL=http://backend:7860
environment:
- VITE_PROXY_TARGET=http://backend:7860
ports: ports:
- "3000:3000" - "3000:3000"
volumes: volumes:

49
poetry.lock generated
View file

@ -511,14 +511,14 @@ files = [
[[package]] [[package]]
name = "chromadb" name = "chromadb"
version = "0.3.22" version = "0.3.23"
description = "Chroma." description = "Chroma."
category = "main" category = "main"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
files = [ files = [
{file = "chromadb-0.3.22-py3-none-any.whl", hash = "sha256:54b58e562ab8a63194ce3b453633ce351475193de2184845f0577db969f1cf49"}, {file = "chromadb-0.3.23-py3-none-any.whl", hash = "sha256:c1e04fddff0916243895bedeffc1977745328f62404d70981eb1a0cb9dcdfaf3"},
{file = "chromadb-0.3.22.tar.gz", hash = "sha256:41acb262c2c7bb41afecd50737f440dce3fdaa3d3fe1749d0e4be1ffc8699e63"}, {file = "chromadb-0.3.23.tar.gz", hash = "sha256:87fa922c92e2e90fb48234b435e9d4f0c61646fbd1526062f53f63326fc21228"},
] ]
[package.dependencies] [package.dependencies]
@ -1180,20 +1180,19 @@ grpc = ["grpcio (>=1.44.0,<2.0.0dev)"]
[[package]] [[package]]
name = "gptcache" name = "gptcache"
version = "0.1.23" version = "0.1.24"
description = "GPTCache, a powerful caching library that can be used to speed up and lower the cost of chat applications that rely on the LLM service. GPTCache works as a memcache for AIGC applications, similar to how Redis works for traditional applications." description = "GPTCache, a powerful caching library that can be used to speed up and lower the cost of chat applications that rely on the LLM service. GPTCache works as a memcache for AIGC applications, similar to how Redis works for traditional applications."
category = "main" category = "main"
optional = false optional = false
python-versions = ">=3.8.1" python-versions = ">=3.8.1"
files = [ files = [
{file = "gptcache-0.1.23-py3-none-any.whl", hash = "sha256:8bcd366e1dd5de432e113831afdea97493f090372a752a42b9ff16cb8c818635"}, {file = "gptcache-0.1.24-py3-none-any.whl", hash = "sha256:070aad4867ab915a7b5db3a886e9f0289e52d1cb92a407c984b0241298079750"},
{file = "gptcache-0.1.23.tar.gz", hash = "sha256:5b5e3ef6f5df35f948bd203d1e33f3985459e60be436547529ff8b31f245238d"}, {file = "gptcache-0.1.24.tar.gz", hash = "sha256:aa591cb00898d457a50a5e0cd137d0119e86819c110ce6c7bce2adafeae0a467"},
] ]
[package.dependencies] [package.dependencies]
cachetools = "*" cachetools = "*"
numpy = "*" numpy = "*"
openai = "*"
requests = "*" requests = "*"
[[package]] [[package]]
@ -1528,14 +1527,14 @@ files = [
[[package]] [[package]]
name = "ipykernel" name = "ipykernel"
version = "6.23.0" version = "6.23.1"
description = "IPython Kernel for Jupyter" description = "IPython Kernel for Jupyter"
category = "dev" category = "dev"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
files = [ files = [
{file = "ipykernel-6.23.0-py3-none-any.whl", hash = "sha256:fc886f1dcdc0ec17f277e4d21fd071c857d381adcb04f3f3735d25325ca323c6"}, {file = "ipykernel-6.23.1-py3-none-any.whl", hash = "sha256:77aeffab056c21d16f1edccdc9e5ccbf7d96eb401bd6703610a21be8b068aadc"},
{file = "ipykernel-6.23.0.tar.gz", hash = "sha256:bd6f487d9e2744c84f6e667d46462d7647a4c862e70e08282f05a52b9d4b705f"}, {file = "ipykernel-6.23.1.tar.gz", hash = "sha256:1aba0ae8453e15e9bc6b24e497ef6840114afcdb832ae597f32137fa19d42a6f"},
] ]
[package.dependencies] [package.dependencies]
@ -1735,13 +1734,13 @@ qdrant = ["qdrant-client (>=1.1.2,<2.0.0)"]
[[package]] [[package]]
name = "llama-cpp-python" name = "llama-cpp-python"
version = "0.1.23" version = "0.1.50"
description = "A Python wrapper for llama.cpp" description = "A Python wrapper for llama.cpp"
category = "main" category = "main"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
files = [ files = [
{file = "llama_cpp_python-0.1.23.tar.gz", hash = "sha256:323a937e68e04251b5ad1804922e05d15c8b6bfbcf7c3e683a7b39a20e165ebf"}, {file = "llama_cpp_python-0.1.50.tar.gz", hash = "sha256:e305ae1b9f135f94afd8dd227701e6a1cd36db9c28f736b830ec364127c00bb9"},
] ]
[package.dependencies] [package.dependencies]
@ -4143,23 +4142,23 @@ scipy = ["scipy"]
[[package]] [[package]]
name = "tornado" name = "tornado"
version = "6.3.1" version = "6.3.2"
description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed." description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
category = "dev" category = "dev"
optional = false optional = false
python-versions = ">= 3.8" python-versions = ">= 3.8"
files = [ files = [
{file = "tornado-6.3.1-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:db181eb3df8738613ff0a26f49e1b394aade05034b01200a63e9662f347d4415"}, {file = "tornado-6.3.2-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:c367ab6c0393d71171123ca5515c61ff62fe09024fa6bf299cd1339dc9456829"},
{file = "tornado-6.3.1-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:b4e7b956f9b5e6f9feb643ea04f07e7c6b49301e03e0023eedb01fa8cf52f579"}, {file = "tornado-6.3.2-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:b46a6ab20f5c7c1cb949c72c1994a4585d2eaa0be4853f50a03b5031e964fc7c"},
{file = "tornado-6.3.1-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9661aa8bc0e9d83d757cd95b6f6d1ece8ca9fd1ccdd34db2de381e25bf818233"}, {file = "tornado-6.3.2-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c2de14066c4a38b4ecbbcd55c5cc4b5340eb04f1c5e81da7451ef555859c833f"},
{file = "tornado-6.3.1-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:81c17e0cc396908a5e25dc8e9c5e4936e6dfd544c9290be48bd054c79bcad51e"}, {file = "tornado-6.3.2-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:05615096845cf50a895026f749195bf0b10b8909f9be672f50b0fe69cba368e4"},
{file = "tornado-6.3.1-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a27a1cfa9997923f80bdd962b3aab048ac486ad8cfb2f237964f8ab7f7eb824b"}, {file = "tornado-6.3.2-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5b17b1cf5f8354efa3d37c6e28fdfd9c1c1e5122f2cb56dac121ac61baa47cbe"},
{file = "tornado-6.3.1-cp38-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:d7117f3c7ba5d05813b17a1f04efc8e108a1b811ccfddd9134cc68553c414864"}, {file = "tornado-6.3.2-cp38-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:29e71c847a35f6e10ca3b5c2990a52ce38b233019d8e858b755ea6ce4dcdd19d"},
{file = "tornado-6.3.1-cp38-abi3-musllinux_1_1_i686.whl", hash = "sha256:ffdce65a281fd708da5a9def3bfb8f364766847fa7ed806821a69094c9629e8a"}, {file = "tornado-6.3.2-cp38-abi3-musllinux_1_1_i686.whl", hash = "sha256:834ae7540ad3a83199a8da8f9f2d383e3c3d5130a328889e4cc991acc81e87a0"},
{file = "tornado-6.3.1-cp38-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:90f569a35a8ec19bde53aa596952071f445da678ec8596af763b9b9ce07605e6"}, {file = "tornado-6.3.2-cp38-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:6a0848f1aea0d196a7c4f6772197cbe2abc4266f836b0aac76947872cd29b411"},
{file = "tornado-6.3.1-cp38-abi3-win32.whl", hash = "sha256:3455133b9ff262fd0a75630af0a8ee13564f25fb4fd3d9ce239b8a7d3d027bf8"}, {file = "tornado-6.3.2-cp38-abi3-win32.whl", hash = "sha256:7efcbcc30b7c654eb6a8c9c9da787a851c18f8ccd4a5a3a95b05c7accfa068d2"},
{file = "tornado-6.3.1-cp38-abi3-win_amd64.whl", hash = "sha256:1285f0691143f7ab97150831455d4db17a267b59649f7bd9700282cba3d5e771"}, {file = "tornado-6.3.2-cp38-abi3-win_amd64.whl", hash = "sha256:0c325e66c8123c606eea33084976c832aa4e766b7dff8aedd7587ea44a604cdf"},
{file = "tornado-6.3.1.tar.gz", hash = "sha256:5e2f49ad371595957c50e42dd7e5c14d64a6843a3cf27352b69c706d1b5918af"}, {file = "tornado-6.3.2.tar.gz", hash = "sha256:4b927c4f19b71e627b13f3db2324e4ae660527143f9e1f2e2fb404f3a187e2ba"},
] ]
[[package]] [[package]]
@ -4840,4 +4839,4 @@ cffi = ["cffi (>=1.11)"]
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = "^3.9" python-versions = "^3.9"
content-hash = "d914f734f4ff1bcbe8e678d46b20b73c3565b3af6f5dd0ac0359fae800c6bf2e" content-hash = "be5c3e25247d4a0c313de54d07f4a027253877a5b8fbbf7830030a43a02c2911"

4
pyproject.toml
View file

@ -1,6 +1,6 @@
[tool.poetry] [tool.poetry]
name = "langflow" name = "langflow"
version = "0.0.71" version = "0.0.73"
description = "A Python package with a built-in web application" description = "A Python package with a built-in web application"
authors = ["Logspace <contact@logspace.ai>"] authors = ["Logspace <contact@logspace.ai>"]
maintainers = [ maintainers = [
@ -37,7 +37,7 @@ pandas = "^1.5.3"
chromadb = "^0.3.21" chromadb = "^0.3.21"
huggingface-hub = "^0.13.3" huggingface-hub = "^0.13.3"
rich = "^13.3.3" rich = "^13.3.3"
llama-cpp-python = "0.1.23" llama-cpp-python = "0.1.50"
networkx = "^3.1" networkx = "^3.1"
unstructured = "^0.5.11" unstructured = "^0.5.11"
pypdf = "^3.7.1" pypdf = "^3.7.1"

29
scripts/deploy_langflow_gcp.sh
View file

@ -26,16 +26,16 @@ if [[ -z "$subnet_exists" ]]; then
gcloud compute networks subnets create $SUBNET_NAME --network=$VPC_NAME --region=$REGION --range=$SUBNET_RANGE gcloud compute networks subnets create $SUBNET_NAME --network=$VPC_NAME --region=$REGION --range=$SUBNET_RANGE
fi fi
# Create a firewall rule to allow TCP port 8080 for all instances in the VPC # Create a firewall rule to allow TCP port 7860 for all instances in the VPC
firewall_8080_exists=$(gcloud compute firewall-rules list --filter="name=allow-tcp-8080" --format="value(name)") firewall_7860_exists=$(gcloud compute firewall-rules list --filter="name=allow-tcp-7860" --format="value(name)")
if [[ -z "$firewall_8080_exists" ]]; then if [[ -z "$firewall_7860_exists" ]]; then
gcloud compute firewall-rules create allow-tcp-8080 --network $VPC_NAME --allow tcp:8080 --source-ranges 0.0.0.0/0 --direction INGRESS gcloud compute firewall-rules create allow-tcp-7860 --network $VPC_NAME --allow tcp:7860 --source-ranges 0.0.0.0/0 --direction INGRESS
fi fi
# Create a firewall rule to allow IAP traffic # Create a firewall rule to allow IAP traffic
firewall_iap_exists=$(gcloud compute firewall-rules list --filter="name=allow-iap" --format="value(name)") firewall_iap_exists=$(gcloud compute firewall-rules list --filter="name=allow-iap" --format="value(name)")
if [[ -z "$firewall_iap_exists" ]]; then if [[ -z "$firewall_iap_exists" ]]; then
gcloud compute firewall-rules create allow-iap --network $VPC_NAME --allow tcp:80,tcp:443 --source-ranges 35.235.240.0/20 --direction INGRESS gcloud compute firewall-rules create allow-iap --network $VPC_NAME --allow tcp:80,tcp:443,tcp:22,:tcp:3389 --source-ranges 35.235.240.0/20 --direction INGRESS
fi fi
# Define the startup script as a multiline Bash here-doc # Define the startup script as a multiline Bash here-doc
@ -49,24 +49,7 @@ apt -y upgrade
# Install Python 3 pip, Langflow, and Nginx # Install Python 3 pip, Langflow, and Nginx
apt -y install python3-pip apt -y install python3-pip
pip install langflow pip install langflow
apt-get -y install nginx langflow --host 0.0.0.0 --port 7860
# Configure Nginx for Langflow
touch /etc/nginx/sites-available/langflow-app
echo "server {
listen 0.0.0.0:8080;
location / {
proxy_pass http://127.0.0.1:7860;
proxy_set_header Host "\$host";
proxy_set_header X-Real-IP "\$remote_addr";
proxy_set_header X-Forwarded-For "\$proxy_add_x_forwarded_for";
}
}" >> /etc/nginx/sites-available/langflow-app
ln -s /etc/nginx/sites-available/langflow-app /etc/nginx/sites-enabled/
sudo nginx -t
sudo systemctl restart nginx
langflow
EOF EOF
) )

31
scripts/deploy_langflow_gcp_spot.sh
View file

@ -26,16 +26,16 @@ if [[ -z "$subnet_exists" ]]; then
gcloud compute networks subnets create $SUBNET_NAME --network=$VPC_NAME --region=$REGION --range=$SUBNET_RANGE gcloud compute networks subnets create $SUBNET_NAME --network=$VPC_NAME --region=$REGION --range=$SUBNET_RANGE
fi fi
# Create a firewall rule to allow TCP port 8080 for all instances in the VPC # Create a firewall rule to allow TCP port 7860 for all instances in the VPC
firewall_8080_exists=$(gcloud compute firewall-rules list --filter="name=allow-tcp-8080" --format="value(name)") firewall_7860_exists=$(gcloud compute firewall-rules list --filter="name=allow-tcp-7860" --format="value(name)")
if [[ -z "$firewall_8080_exists" ]]; then if [[ -z "$firewall_7860_exists" ]]; then
gcloud compute firewall-rules create allow-tcp-8080 --network $VPC_NAME --allow tcp:8080 --source-ranges 0.0.0.0/0 --direction INGRESS gcloud compute firewall-rules create allow-tcp-7860 --network $VPC_NAME --allow tcp:7860 --source-ranges 0.0.0.0/0 --direction INGRESS
fi fi
# Create a firewall rule to allow IAP traffic # Create a firewall rule to allow IAP traffic
firewall_iap_exists=$(gcloud compute firewall-rules list --filter="name=allow-iap" --format="value(name)") firewall_iap_exists=$(gcloud compute firewall-rules list --filter="name=allow-iap" --format="value(name)")
if [[ -z "$firewall_iap_exists" ]]; then if [[ -z "$firewall_iap_exists" ]]; then
gcloud compute firewall-rules create allow-iap --network $VPC_NAME --allow tcp:80,tcp:443 --source-ranges 35.235.240.0/20 --direction INGRESS gcloud compute firewall-rules create allow-iap --network $VPC_NAME --allow tcp:80,tcp:443,tcp:22,:tcp:3389 --source-ranges 35.235.240.0/20 --direction INGRESS
fi fi
# Define the startup script as a multiline Bash here-doc # Define the startup script as a multiline Bash here-doc
@ -49,24 +49,7 @@ apt -y upgrade
# Install Python 3 pip, Langflow, and Nginx # Install Python 3 pip, Langflow, and Nginx
apt -y install python3-pip apt -y install python3-pip
pip install langflow pip install langflow
apt-get -y install nginx langflow --host 0.0.0.0 --port 7860
# Configure Nginx for Langflow
touch /etc/nginx/sites-available/langflow-app
echo "server {
listen 0.0.0.0:8080;
location / {
proxy_pass http://127.0.0.1:7860;
proxy_set_header Host "\$host";
proxy_set_header X-Real-IP "\$remote_addr";
proxy_set_header X-Forwarded-For "\$proxy_add_x_forwarded_for";
}
}" >> /etc/nginx/sites-available/langflow-app
ln -s /etc/nginx/sites-available/langflow-app /etc/nginx/sites-enabled/
sudo nginx -t
sudo systemctl restart nginx
langflow
EOF EOF
) )
@ -84,7 +67,7 @@ gcloud compute instances create $VM_NAME \
--zone $ZONE \ --zone $ZONE \
--network $VPC_NAME \ --network $VPC_NAME \
--subnet $SUBNET_NAME \ --subnet $SUBNET_NAME \
-preemptible --preemptible
# Remove the temporary file after the VM is created # Remove the temporary file after the VM is created
rm $tempfile rm $tempfile

8
scripts/walkthroughtutorial.md
View file

@ -37,7 +37,7 @@ The script will:
1. Check if the required resources (VPC, subnet, firewall rules, and Cloud Router) exist and create them if needed 1. Check if the required resources (VPC, subnet, firewall rules, and Cloud Router) exist and create them if needed
2. Create a startup script to install Python, Langflow, and Nginx 2. Create a startup script to install Python, Langflow, and Nginx
3. Create a Compute Engine VM instance with the specified configuration and startup script 3. Create a Compute Engine VM instance with the specified configuration and startup script
4. Configure Nginx to serve Langflow on TCP port 8080 4. Run Langflow to serve content on TCP port 7860
<walkthrough-pin-section-icon></walkthrough-pin-section-icon> <walkthrough-pin-section-icon></walkthrough-pin-section-icon>
> The process may take approximately 30 minutes to complete. Rest assured that progress is being made, and you'll be able to proceed once the process is finished. > The process may take approximately 30 minutes to complete. Rest assured that progress is being made, and you'll be able to proceed once the process is finished.
@ -47,13 +47,13 @@ In the next step, you'll learn how to connect to the Langflow VM.
## Connect to the Langflow VM ## Connect to the Langflow VM
To connect to your new Langflow VM, follow these steps: To connect to your new Langflow VM, follow these steps:
1. Navigate to the [VM instances](https://console.cloud.google.com/compute/instances) page and click on the external IP for your VM. Make sure to use HTTP and set the port to 8080 1. Navigate to the [VM instances](https://console.cloud.google.com/compute/instances) page and click on the external IP for your VM. Make sure to use HTTP and set the port to 7860
<br>**or** <br>**or**
3. Run the following command to display the URL for your Langflow environment: 3. Run the following command to display the URL for your Langflow environment:
```bash ```bash
export LANGFLOW_IP=$(gcloud compute instances list --filter="NAME=langflow-dev" --format="value(EXTERNAL_IP)") export LANGFLOW_IP=$(gcloud compute instances list --filter="NAME=langflow-dev" --format="value(EXTERNAL_IP)")
echo http://$LANGFLOW_IP:8080 echo http://$LANGFLOW_IP:7860
``` ```
4. Click on the Langflow URL in cloudshell to be greeted by the Langflow Dev environment 4. Click on the Langflow URL in cloudshell to be greeted by the Langflow Dev environment
@ -76,7 +76,7 @@ However, if you decide to remove them after completing the walkthrough, you can
> These commands will delete the firewall rules and network configurations created during the walkthrough. Make sure to run them only if you no longer need these settings. > These commands will delete the firewall rules and network configurations created during the walkthrough. Make sure to run them only if you no longer need these settings.
``` ```
gcloud compute firewall-rules delete allow-tcp-8080 --quiet gcloud compute firewall-rules delete allow-tcp-7860 --quiet
gcloud compute firewall-rules delete allow-iap --quiet gcloud compute firewall-rules delete allow-iap --quiet

10
scripts/walkthroughtutorial_spot.md
View file

@ -29,7 +29,7 @@ Run the deploy_langflow_gcp_spot.sh script to configure the GCP environment and
```sh ```sh
gcloud config set project <walkthrough-project-id/> gcloud config set project <walkthrough-project-id/>
bash ./deploy_langflow_gcp.sh bash ./deploy_langflow_gcp_spot.sh
``` ```
The script will: The script will:
@ -37,7 +37,7 @@ The script will:
1. Check if the required resources (VPC, subnet, firewall rules, and Cloud Router) exist and create them if needed 1. Check if the required resources (VPC, subnet, firewall rules, and Cloud Router) exist and create them if needed
2. Create a startup script to install Python, Langflow, and Nginx 2. Create a startup script to install Python, Langflow, and Nginx
3. Create a Compute Engine VM instance with the specified configuration and startup script 3. Create a Compute Engine VM instance with the specified configuration and startup script
4. Configure Nginx to serve Langflow on TCP port 8080 4. Run Langflow to serve content on TCP port 7860
> <walkthrough-pin-section-icon></walkthrough-pin-section-icon> The process may take approximately 30 minutes to complete. Rest assured that progress is being made, and you'll be able to proceed once the process is finished. > <walkthrough-pin-section-icon></walkthrough-pin-section-icon> The process may take approximately 30 minutes to complete. Rest assured that progress is being made, and you'll be able to proceed once the process is finished.
@ -46,13 +46,13 @@ In the next step, you'll learn how to connect to the Langflow VM.
## Connect to the Langflow VM ## Connect to the Langflow VM
To connect to your new Langflow VM, follow these steps: To connect to your new Langflow VM, follow these steps:
1. Navigate to the [VM instances](https://console.cloud.google.com/compute/instances) page and click on the external IP for your VM. Make sure to use HTTP and set the port to 8080 1. Navigate to the [VM instances](https://console.cloud.google.com/compute/instances) page and click on the external IP for your VM. Make sure to use HTTP and set the port to 7860
<br>**or** <br>**or**
3. Run the following command to display the URL for your Langflow environment: 3. Run the following command to display the URL for your Langflow environment:
```bash ```bash
export LANGFLOW_IP=$(gcloud compute instances list --filter="NAME=langflow-dev" --format="value(EXTERNAL_IP)") export LANGFLOW_IP=$(gcloud compute instances list --filter="NAME=langflow-dev" --format="value(EXTERNAL_IP)")
echo http://$LANGFLOW_IP:8080 echo http://$LANGFLOW_IP:7860
``` ```
4. Click on the Langflow URL in cloudshell to be greeted by the Langflow Dev environment 4. Click on the Langflow URL in cloudshell to be greeted by the Langflow Dev environment
@ -73,7 +73,7 @@ However, if you decide to remove them after completing the walkthrough, you can
> <walkthrough-pin-section-icon></walkthrough-pin-section-icon> These commands will delete the firewall rules and network configurations created during the walkthrough. Make sure to run them only if you no longer need these settings. > <walkthrough-pin-section-icon></walkthrough-pin-section-icon> These commands will delete the firewall rules and network configurations created during the walkthrough. Make sure to run them only if you no longer need these settings.
``` ```
gcloud compute firewall-rules delete allow-tcp-8080 --quiet gcloud compute firewall-rules delete allow-tcp-7860 --quiet
gcloud compute firewall-rules delete allow-iap --quiet gcloud compute firewall-rules delete allow-iap --quiet

6
src/backend/langflow/interface/loading.py
View file

@ -54,7 +54,7 @@ def instantiate_based_on_type(class_object, base_type, node_type, params):
if base_type == "agents": if base_type == "agents":
return instantiate_agent(class_object, params) return instantiate_agent(class_object, params)
elif base_type == "prompts": elif base_type == "prompts":
return instantiate_prompt(class_object, node_type, params) return instantiate_prompt(node_type, class_object, params)
elif base_type == "tools": elif base_type == "tools":
return instantiate_tool(node_type, class_object, params) return instantiate_tool(node_type, class_object, params)
elif base_type == "toolkits": elif base_type == "toolkits":
@ -77,7 +77,7 @@ def instantiate_agent(class_object, params):
return load_agent_executor(class_object, params) return load_agent_executor(class_object, params)
def instantiate_prompt(class_object, node_type, params): def instantiate_prompt(node_type, class_object, params):
if node_type == "ZeroShotPrompt": if node_type == "ZeroShotPrompt":
if "tools" not in params: if "tools" not in params:
params["tools"] = [] params["tools"] = []
@ -96,7 +96,7 @@ def instantiate_tool(node_type, class_object, params):
raise ValueError("Function should be a string") raise ValueError("Function should be a string")
elif node_type.lower() == "tool": elif node_type.lower() == "tool":
return class_object(**params) return class_object(**params)
return None # Or some other default action return class_object(**params)
def instantiate_toolkit(node_type, class_object, params): def instantiate_toolkit(node_type, class_object, params):

2
src/frontend/dev.Dockerfile
View file

@ -23,4 +23,4 @@ RUN chmod +x set_proxy.sh && \
USER node USER node
RUN npm install --loglevel warn RUN npm install --loglevel warn
CMD ["npm", "start"] CMD ["npm", "run", "dev:docker"]

1
src/frontend/package.json
View file

@ -35,6 +35,7 @@
"web-vitals": "^2.1.4" "web-vitals": "^2.1.4"
}, },
"scripts": { "scripts": {
"dev:docker": "vite --host 0.0.0.0",
"start": "vite", "start": "vite",
"build": "vite build", "build": "vite build",
"serve": "vite preview" "serve": "vite preview"

2
src/frontend/src/components/chatComponent/chatMessage/index.tsx
View file

@ -7,7 +7,7 @@ import { useState } from "react";
import { ChatMessageType } from "../../../types/chat"; import { ChatMessageType } from "../../../types/chat";
import { nodeColors } from "../../../utils"; import { nodeColors } from "../../../utils";
import Convert from "ansi-to-html"; import Convert from "ansi-to-html";
var convert = new Convert({newline:true}); const convert = new Convert({ newline: true });
export default function ChatMessage({ chat }: { chat: ChatMessageType }) { export default function ChatMessage({ chat }: { chat: ChatMessageType }) {
const [hidden, setHidden] = useState(true); const [hidden, setHidden] = useState(true);

68
src/frontend/src/contexts/tabsContext.tsx
View file

@ -38,7 +38,7 @@ export function TabsProvider({ children }: { children: ReactNode }) {
const { setNoticeData } = useContext(alertContext); const { setNoticeData } = useContext(alertContext);
const [tabIndex, setTabIndex] = useState(0); const [tabIndex, setTabIndex] = useState(0);
const [flows, setFlows] = useState<Array<FlowType>>([]); const [flows, setFlows] = useState<Array<FlowType>>([]);
const [id, setId] = useState(""); const [id, setId] = useState(uuidv4());
const { templates } = useContext(typesContext); const { templates } = useContext(typesContext);
const newNodeId = useRef(0); const newNodeId = useRef(0);
@ -47,46 +47,50 @@ export function TabsProvider({ children }: { children: ReactNode }) {
return newNodeId.current; return newNodeId.current;
} }
function save() { function save() {
if (flows.length !== 0) //disabled until flows can be saved on local storage again without bugs
window.localStorage.setItem( // if (flows.length !== 0)
"tabsData", // window.localStorage.setItem(
JSON.stringify({ tabIndex, flows, id, nodeId: newNodeId.current }) // "tabsData",
); // JSON.stringify({ tabIndex, flows, id, nodeId: newNodeId.current })
// );
} }
useEffect(() => { useEffect(() => {
//disabled until flows can be saved on local storage again without bugs
//save tabs locally //save tabs locally
save(); // save();
}, [flows, id, tabIndex, newNodeId]); }, [flows, id, tabIndex, newNodeId]);
useEffect(() => { // useEffect(() => {
//get tabs locally saved // //get tabs locally saved
let cookie = window.localStorage.getItem("tabsData"); // let cookie = window.localStorage.getItem("tabsData");
if (cookie && Object.keys(templates).length > 0) { // if (cookie && Object.keys(templates).length > 0) {
let cookieObject: LangFlowState = JSON.parse(cookie); // let cookieObject: LangFlowState = JSON.parse(cookie);
cookieObject.flows.forEach((flow) => { // cookieObject.flows.forEach((flow) => {
flow.data.nodes.forEach((node) => { // flow.data.nodes.forEach((node) => {
if (Object.keys(templates[node.data.type]["template"]).length > 0) { // if (Object.keys(templates[node.data.type]["template"]).length > 0) {
node.data.node.template = updateTemplate( // node.data.node.template = updateTemplate(
templates[node.data.type][ // templates[node.data.type][
"template" // "template"
] as unknown as APITemplateType, // ] as unknown as APITemplateType,
// node.data.node.template as APITemplateType
// );
// }
// });
// });
// setTabIndex(cookieObject.tabIndex);
// setFlows(cookieObject.flows);
// setId(cookieObject.id);
// newNodeId.current = cookieObject.nodeId;
// }
// }, [templates]);
node.data.node.template as APITemplateType
);
}
});
});
setTabIndex(cookieObject.tabIndex);
setFlows(cookieObject.flows);
setId(cookieObject.id);
newNodeId.current = cookieObject.nodeId;
}
}, [templates]);
function hardReset() { function hardReset() {
newNodeId.current = 0; newNodeId.current = 0;
setTabIndex(0); setTabIndex(0);
setFlows([]); setFlows([]);
setId(""); setId(uuidv4());
} }
/** /**
@ -182,7 +186,7 @@ export function TabsProvider({ children }: { children: ReactNode }) {
let newFlow: FlowType = { let newFlow: FlowType = {
description, description,
name: flow?.name ?? "New Flow", name: flow?.name ?? "New Flow",
id: id.toString(), id: uuidv4(),
data, data,
}; };

1
src/frontend/src/modals/ApiModal/index.tsx
View file

@ -45,6 +45,7 @@ export default function ApiModal({ flowName }) {
} }
const pythonApiCode = `import requests const pythonApiCode = `import requests
import json
API_URL = "${window.location.protocol}//${window.location.host}/predict" API_URL = "${window.location.protocol}//${window.location.host}/predict"

1
src/frontend/src/modals/chatModal/chatMessage/index.tsx
View file

@ -14,6 +14,7 @@ import { CodeBlock } from "./codeBlock";
import Convert from "ansi-to-html"; import Convert from "ansi-to-html";
export default function ChatMessage({ chat, lockChat }: { chat: ChatMessageType, lockChat: boolean }) { export default function ChatMessage({ chat, lockChat }: { chat: ChatMessageType, lockChat: boolean }) {
const convert = new Convert({ newline: true });
const [message, setMessage] = useState(""); const [message, setMessage] = useState("");
const imgRef = useRef(null); const imgRef = useRef(null);
useEffect(() => { useEffect(() => {

21
src/frontend/src/modals/chatModal/index.tsx
View file

@ -30,10 +30,16 @@ export default function ChatModal({
const ws = useRef<WebSocket | null>(null); const ws = useRef<WebSocket | null>(null);
const [lockChat, setLockChat] = useState(false); const [lockChat, setLockChat] = useState(false);
const isOpen = useRef(open); const isOpen = useRef(open);
const id = useRef(flow.id);
useEffect(() => { useEffect(() => {
isOpen.current = open; isOpen.current = open;
}, [open]); }, [open]);
useEffect(() => {
id.current = flow.id;
},[flow.id])
var isStream = false; var isStream = false;
const addChatHistory = ( const addChatHistory = (
@ -164,10 +170,9 @@ export default function ChatModal({
try { try {
const urlWs = const urlWs =
process.env.NODE_ENV === "development" process.env.NODE_ENV === "development"
? `ws://localhost:7860/chat/${flow.id}` ? `ws://localhost:7860/chat/${id.current}`
: `${window.location.protocol === "https:" ? "wss" : "ws"}://${window.location.host : `${window.location.protocol === "https:" ? "wss" : "ws"}://${window.location.host
}/chat/${flow.id}`; }/chat/${id.current}`;
const newWs = new WebSocket(urlWs); const newWs = new WebSocket(urlWs);
newWs.onopen = () => { newWs.onopen = () => {
console.log("WebSocket connection established!"); console.log("WebSocket connection established!");
@ -184,6 +189,10 @@ export default function ChatModal({
}; };
newWs.onerror = (ev) => { newWs.onerror = (ev) => {
console.log(ev, "error"); console.log(ev, "error");
if(flow.id===""){
connectWS();
}
else{
setErrorData({ setErrorData({
title: "There was an error on web connection, please: ", title: "There was an error on web connection, please: ",
list: [ list: [
@ -192,9 +201,14 @@ export default function ChatModal({
"Check if the backend is up", "Check if the backend is up",
], ],
}); });
}
}; };
ws.current = newWs; ws.current = newWs;
} catch { } catch {
if(flow.id===""){
connectWS();
}
else{
setErrorData({ setErrorData({
title: "There was an error on web connection, please: ", title: "There was an error on web connection, please: ",
list: [ list: [
@ -205,6 +219,7 @@ export default function ChatModal({
}); });
} }
} }
}
useEffect(() => { useEffect(() => {
connectWS(); connectWS();

22
src/frontend/vite.config.ts
View file

@ -1,16 +1,14 @@
import { defineConfig } from 'vite'; import { defineConfig } from "vite";
import react from '@vitejs/plugin-react-swc'; import react from "@vitejs/plugin-react-swc";
const apiRoutes = [ const apiRoutes = ["/all", "/predict", "^/validate/*", "^/chat/*"];
'/all',
'/predict', // Use environment variable to determine the target.
'^/validate/*', const target = process.env.VITE_PROXY_TARGET || "http://127.0.0.1:7860";
'^/chat/*',
];
const proxyTargets = apiRoutes.reduce((proxyObj, route) => { const proxyTargets = apiRoutes.reduce((proxyObj, route) => {
proxyObj[route] = { proxyObj[route] = {
target: 'http://127.0.0.1:7860', target: target,
changeOrigin: true, changeOrigin: true,
secure: false, secure: false,
ws: true, ws: true,
@ -21,14 +19,14 @@ const proxyTargets = apiRoutes.reduce((proxyObj, route) => {
export default defineConfig(() => { export default defineConfig(() => {
return { return {
build: { build: {
outDir: 'build', outDir: "build",
}, },
plugins: [react()], plugins: [react()],
server: { server: {
port: 3000, port: 3000,
proxy: { proxy: {
...proxyTargets ...proxyTargets,
} },
}, },
}; };
}); });