Merge branch 'dev' of https://github.com/logspace-ai/langflow into dev
This commit is contained in:
Gabriel Almeida
commit
23eb511560
24 changed files with 640 additions and 88 deletions
28
GCP_DEPLOYMENT.md
Normal file
28
GCP_DEPLOYMENT.md
Normal file
|
|
@ -0,0 +1,28 @@
|
|||
# Run Langflow from a New Google Cloud Project
|
||||
|
||||
This guide will help you set up a Langflow development VM in a Google Cloud Platform project using Google Cloud Shell.
|
||||
|
||||
> **Note**: When Cloud Shell opens, be sure to select **Trust repo**. Some `gcloud` commands might not run in an ephemeral Cloud Shell environment.
|
||||
|
||||
|
||||
## Standard VM
|
||||
[](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/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.
|
||||
<hr>
|
||||
|
||||
## Spot/Preemptible Instance
|
||||
|
||||
[](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial.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.
|
||||
|
||||
## Pricing (approximate)
|
||||
> For a more accurate breakdown of costs, please use the [**GCP Pricing Calculator**](https://cloud.google.com/products/calculator)
|
||||
<br>
|
||||
|
||||
| Component | Regular Cost (Hourly) | Regular Cost (Monthly) | Spot/Preemptible Cost (Hourly) | Spot/Preemptible Cost (Monthly) | Notes |
|
||||
| -------------- | --------------------- | ---------------------- | ------------------------------ | ------------------------------- | ----- |
|
||||
| 100 GB Disk | - | $10/month | - | $10/month | Disk cost remains the same for both regular and Spot/Preemptible VMs |
|
||||
| VM (n1-standard-4) | $0.15/hr | ~$108/month | ~$0.04/hr | ~$29/month | The VM cost can be significantly reduced using a Spot/Preemptible instance |
|
||||
| **Total** | **$0.15/hr** | **~$118/month** | **~$0.04/hr** | **~$39/month** | Total costs for running the VM and disk 24/7 for an entire month |
|
||||
23
README.md
23
README.md
|
|
@ -19,14 +19,31 @@
|
|||
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.
|
||||
|
||||
## 📦 Installation
|
||||
|
||||
### <b>Locally</b>
|
||||
You can install LangFlow from pip:
|
||||
|
||||
`pip install langflow`
|
||||
```shell
|
||||
pip install langflow
|
||||
```
|
||||
|
||||
Next, run:
|
||||
|
||||
`langflow`
|
||||
```shell
|
||||
python -m langflow
|
||||
```
|
||||
or
|
||||
```shell
|
||||
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.
|
||||
|
||||
[](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial_spot.md)
|
||||
|
||||
|
||||
## 🎨 Creating Flows
|
||||
|
||||
|
|
|
|||
89
scripts/deploy_langflow_gcp.sh
Normal file
89
scripts/deploy_langflow_gcp.sh
Normal file
|
|
@ -0,0 +1,89 @@
|
|||
# Set the VM, image, and networking configuration
|
||||
VM_NAME="langflow-dev"
|
||||
IMAGE_FAMILY="debian-11"
|
||||
IMAGE_PROJECT="debian-cloud"
|
||||
BOOT_DISK_SIZE="100GB"
|
||||
ZONE="us-central1-a"
|
||||
REGION="us-central1"
|
||||
VPC_NAME="default"
|
||||
SUBNET_NAME="default"
|
||||
SUBNET_RANGE="10.128.0.0/20"
|
||||
NAT_GATEWAY_NAME="nat-gateway"
|
||||
CLOUD_ROUTER_NAME="nat-client"
|
||||
|
||||
# Set the GCP project's compute region
|
||||
gcloud config set compute/region $REGION
|
||||
|
||||
# Check if the VPC exists, and create it if not
|
||||
vpc_exists=$(gcloud compute networks list --filter="name=$VPC_NAME" --format="value(name)")
|
||||
if [[ -z "$vpc_exists" ]]; then
|
||||
gcloud compute networks create $VPC_NAME --subnet-mode=custom
|
||||
fi
|
||||
|
||||
# Check if the subnet exists, and create it if not
|
||||
subnet_exists=$(gcloud compute networks subnets list --filter="name=$SUBNET_NAME AND region=$REGION" --format="value(name)")
|
||||
if [[ -z "$subnet_exists" ]]; then
|
||||
gcloud compute networks subnets create $SUBNET_NAME --network=$VPC_NAME --region=$REGION --range=$SUBNET_RANGE
|
||||
fi
|
||||
|
||||
# Create a firewall rule to allow TCP port 8080 for all instances in the VPC
|
||||
firewall_8080_exists=$(gcloud compute firewall-rules list --filter="name=allow-tcp-8080" --format="value(name)")
|
||||
if [[ -z "$firewall_8080_exists" ]]; then
|
||||
gcloud compute firewall-rules create allow-tcp-8080 --network $VPC_NAME --allow tcp:8080 --source-ranges 0.0.0.0/0 --direction INGRESS
|
||||
fi
|
||||
|
||||
# Create a firewall rule to allow IAP traffic
|
||||
firewall_iap_exists=$(gcloud compute firewall-rules list --filter="name=allow-iap" --format="value(name)")
|
||||
if [[ -z "$firewall_iap_exists" ]]; then
|
||||
gcloud compute firewall-rules create allow-iap --network $VPC_NAME --allow tcp:80,tcp:443 --source-ranges 35.235.240.0/20 --direction INGRESS
|
||||
fi
|
||||
|
||||
# Define the startup script as a multiline Bash here-doc
|
||||
STARTUP_SCRIPT=$(cat <<'EOF'
|
||||
#!/bin/bash
|
||||
|
||||
# Update and upgrade the system
|
||||
apt -y update
|
||||
apt -y upgrade
|
||||
|
||||
# Install Python 3 pip, Langflow, and Nginx
|
||||
apt -y install python3-pip
|
||||
pip install langflow
|
||||
apt-get -y install nginx
|
||||
|
||||
# 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
|
||||
)
|
||||
|
||||
# Create a temporary file to store the startup script
|
||||
tempfile=$(mktemp)
|
||||
echo "$STARTUP_SCRIPT" > $tempfile
|
||||
|
||||
# Create the VM instance with the specified configuration and startup script
|
||||
gcloud compute instances create $VM_NAME \
|
||||
--image-family $IMAGE_FAMILY \
|
||||
--image-project $IMAGE_PROJECT \
|
||||
--boot-disk-size $BOOT_DISK_SIZE \
|
||||
--machine-type=n1-standard-4 \
|
||||
--metadata-from-file startup-script=$tempfile \
|
||||
--zone $ZONE \
|
||||
--network $VPC_NAME \
|
||||
--subnet $SUBNET_NAME
|
||||
|
||||
# Remove the temporary file after the VM is created
|
||||
rm $tempfile
|
||||
90
scripts/deploy_langflow_gcp_spot.sh
Normal file
90
scripts/deploy_langflow_gcp_spot.sh
Normal file
|
|
@ -0,0 +1,90 @@
|
|||
# Set the VM, image, and networking configuration
|
||||
VM_NAME="langflow-dev"
|
||||
IMAGE_FAMILY="debian-11"
|
||||
IMAGE_PROJECT="debian-cloud"
|
||||
BOOT_DISK_SIZE="100GB"
|
||||
ZONE="us-central1-a"
|
||||
REGION="us-central1"
|
||||
VPC_NAME="default"
|
||||
SUBNET_NAME="default"
|
||||
SUBNET_RANGE="10.128.0.0/20"
|
||||
NAT_GATEWAY_NAME="nat-gateway"
|
||||
CLOUD_ROUTER_NAME="nat-client"
|
||||
|
||||
# Set the GCP project's compute region
|
||||
gcloud config set compute/region $REGION
|
||||
|
||||
# Check if the VPC exists, and create it if not
|
||||
vpc_exists=$(gcloud compute networks list --filter="name=$VPC_NAME" --format="value(name)")
|
||||
if [[ -z "$vpc_exists" ]]; then
|
||||
gcloud compute networks create $VPC_NAME --subnet-mode=custom
|
||||
fi
|
||||
|
||||
# Check if the subnet exists, and create it if not
|
||||
subnet_exists=$(gcloud compute networks subnets list --filter="name=$SUBNET_NAME AND region=$REGION" --format="value(name)")
|
||||
if [[ -z "$subnet_exists" ]]; then
|
||||
gcloud compute networks subnets create $SUBNET_NAME --network=$VPC_NAME --region=$REGION --range=$SUBNET_RANGE
|
||||
fi
|
||||
|
||||
# Create a firewall rule to allow TCP port 8080 for all instances in the VPC
|
||||
firewall_8080_exists=$(gcloud compute firewall-rules list --filter="name=allow-tcp-8080" --format="value(name)")
|
||||
if [[ -z "$firewall_8080_exists" ]]; then
|
||||
gcloud compute firewall-rules create allow-tcp-8080 --network $VPC_NAME --allow tcp:8080 --source-ranges 0.0.0.0/0 --direction INGRESS
|
||||
fi
|
||||
|
||||
# Create a firewall rule to allow IAP traffic
|
||||
firewall_iap_exists=$(gcloud compute firewall-rules list --filter="name=allow-iap" --format="value(name)")
|
||||
if [[ -z "$firewall_iap_exists" ]]; then
|
||||
gcloud compute firewall-rules create allow-iap --network $VPC_NAME --allow tcp:80,tcp:443 --source-ranges 35.235.240.0/20 --direction INGRESS
|
||||
fi
|
||||
|
||||
# Define the startup script as a multiline Bash here-doc
|
||||
STARTUP_SCRIPT=$(cat <<'EOF'
|
||||
#!/bin/bash
|
||||
|
||||
# Update and upgrade the system
|
||||
apt -y update
|
||||
apt -y upgrade
|
||||
|
||||
# Install Python 3 pip, Langflow, and Nginx
|
||||
apt -y install python3-pip
|
||||
pip install langflow
|
||||
apt-get -y install nginx
|
||||
|
||||
# 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
|
||||
)
|
||||
|
||||
# Create a temporary file to store the startup script
|
||||
tempfile=$(mktemp)
|
||||
echo "$STARTUP_SCRIPT" > $tempfile
|
||||
|
||||
# Create the VM instance with the specified configuration and startup script
|
||||
gcloud compute instances create $VM_NAME \
|
||||
--image-family $IMAGE_FAMILY \
|
||||
--image-project $IMAGE_PROJECT \
|
||||
--boot-disk-size $BOOT_DISK_SIZE \
|
||||
--machine-type=n1-standard-4 \
|
||||
--metadata-from-file startup-script=$tempfile \
|
||||
--zone $ZONE \
|
||||
--network $VPC_NAME \
|
||||
--subnet $SUBNET_NAME \
|
||||
-preemptible
|
||||
|
||||
# Remove the temporary file after the VM is created
|
||||
rm $tempfile
|
||||
86
scripts/walkthroughtutorial.md
Normal file
86
scripts/walkthroughtutorial.md
Normal file
|
|
@ -0,0 +1,86 @@
|
|||
# Deploy Langflow on Google Cloud Platform
|
||||
|
||||
**Duration**: 45 minutes
|
||||
**Author**: [Robert Wilkins III](https://www.linkedin.com/in/robertwilkinsiii)
|
||||
|
||||
## Introduction
|
||||
|
||||
In this tutorial, you will learn how to deploy Langflow on [Google Cloud Platform](https://cloud.google.com/) (GCP) using Google Cloud Shell.
|
||||
|
||||
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).
|
||||
|
||||
## Set up your environment
|
||||
|
||||
Before you start, make sure you have the following prerequisites:
|
||||
|
||||
- A GCP account with the necessary permissions to create resources
|
||||
- A project on GCP where you want to deploy Langflow
|
||||
|
||||
[**Select your GCP project**]<walkthrough-project-setup
|
||||
billing="true"
|
||||
apis="compute.googleapis.com,container.googleapis.com">
|
||||
</walkthrough-project-setup>
|
||||
|
||||
|
||||
In the next step, you'll configure the GCP environment and deploy Langflow.
|
||||
|
||||
## Configure the GCP environment and deploy Langflow
|
||||
Run the deploy_langflow_gcp.sh script to configure the GCP environment and deploy Langflow:
|
||||
|
||||
```sh
|
||||
gcloud config set project <walkthrough-project-id/>
|
||||
bash ./deploy_langflow_gcp.sh
|
||||
```
|
||||
|
||||
The script will:
|
||||
|
||||
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
|
||||
3. Create a Compute Engine VM instance with the specified configuration and startup script
|
||||
4. Configure Nginx to serve Langflow on TCP port 8080
|
||||
|
||||
<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.
|
||||
|
||||
In the next step, you'll learn how to connect to the Langflow VM.
|
||||
|
||||
## Connect to the Langflow VM
|
||||
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
|
||||
<br>**or**
|
||||
3. Run the following command to display the URL for your Langflow environment:
|
||||
```bash
|
||||
export LANGFLOW_IP=$(gcloud compute instances list --filter="NAME=langflow-dev" --format="value(EXTERNAL_IP)")
|
||||
|
||||
echo http://$LANGFLOW_IP:8080
|
||||
```
|
||||
|
||||
4. Click on the Langflow URL in cloudshell to be greeted by the Langflow Dev environment
|
||||
|
||||
Congratulations! You have successfully deployed Langflow on Google Cloud Platform.
|
||||
|
||||
<walkthrough-conclusion-trophy></walkthrough-conclusion-trophy>
|
||||
|
||||
## Cleanup
|
||||
If you want to remove the resources created during this tutorial, you can use the following commands:
|
||||
|
||||
```sql
|
||||
gcloud compute instances delete langflow-dev --zone us-central1-a --quiet
|
||||
```
|
||||
The following network settings and services are used during this walkthrough. If you plan to continue using the project after the walkthrough, you may keep these configurations in place.
|
||||
|
||||
However, if you decide to remove them after completing the walkthrough, you can use the following gcloud commands:
|
||||
|
||||
<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-iap --quiet
|
||||
|
||||
gcloud compute networks subnets delete default --region us-central1 --quiet
|
||||
|
||||
gcloud compute networks delete default --quiet
|
||||
```
|
||||
83
scripts/walkthroughtutorial_spot.md
Normal file
83
scripts/walkthroughtutorial_spot.md
Normal file
|
|
@ -0,0 +1,83 @@
|
|||
# Deploy Langflow on Google Cloud Platform
|
||||
|
||||
**Duration**: 45 minutes
|
||||
**Author**: [Robert Wilkins III](https://www.linkedin.com/in/robertwilkinsiii)
|
||||
|
||||
## Introduction
|
||||
|
||||
In this tutorial, you will learn how to deploy Langflow on [Google Cloud Platform](https://cloud.google.com/) (GCP) using Google Cloud Shell.
|
||||
|
||||
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).
|
||||
|
||||
## Set up your environment
|
||||
|
||||
Before you start, make sure you have the following prerequisites:
|
||||
|
||||
- A GCP account with the necessary permissions to create resources
|
||||
- A project on GCP where you want to deploy Langflow
|
||||
|
||||
[**Select your GCP project**]<walkthrough-project-setup
|
||||
billing="true"
|
||||
apis="compute.googleapis.com,container.googleapis.com">
|
||||
</walkthrough-project-setup>
|
||||
|
||||
|
||||
In the next step, you'll configure the GCP environment and deploy Langflow.
|
||||
|
||||
## Configure the GCP environment and deploy Langflow
|
||||
Run the deploy_langflow_gcp_spot.sh script to configure the GCP environment and deploy Langflow:
|
||||
|
||||
```sh
|
||||
gcloud config set project <walkthrough-project-id/>
|
||||
bash ./deploy_langflow_gcp.sh
|
||||
```
|
||||
|
||||
The script will:
|
||||
|
||||
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
|
||||
3. Create a Compute Engine VM instance with the specified configuration and startup script
|
||||
4. Configure Nginx to serve Langflow on TCP port 8080
|
||||
|
||||
> <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.
|
||||
|
||||
In the next step, you'll learn how to connect to the Langflow VM.
|
||||
|
||||
## Connect to the Langflow VM
|
||||
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
|
||||
<br>**or**
|
||||
3. Run the following command to display the URL for your Langflow environment:
|
||||
```bash
|
||||
export LANGFLOW_IP=$(gcloud compute instances list --filter="NAME=langflow-dev" --format="value(EXTERNAL_IP)")
|
||||
|
||||
echo http://$LANGFLOW_IP:8080
|
||||
```
|
||||
|
||||
4. Click on the Langflow URL in cloudshell to be greeted by the Langflow Dev environment
|
||||
|
||||
Congratulations! You have successfully deployed Langflow on Google Cloud Platform.
|
||||
|
||||
<walkthrough-conclusion-trophy></walkthrough-conclusion-trophy>
|
||||
|
||||
## Cleanup
|
||||
If you want to remove the resources created during this tutorial, you can use the following commands:
|
||||
|
||||
```sql
|
||||
gcloud compute instances delete langflow-dev --zone us-central1-a --quiet
|
||||
```
|
||||
The following network settings and services are used during this walkthrough. If you plan to continue using the project after the walkthrough, you may keep these configurations in place.
|
||||
|
||||
However, if you decide to remove them after completing the walkthrough, you can use the following gcloud commands:
|
||||
> <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-iap --quiet
|
||||
|
||||
gcloud compute networks subnets delete default --region us-central1 --quiet
|
||||
|
||||
gcloud compute networks delete default --quiet
|
||||
```
|
||||
|
|
@ -6,6 +6,7 @@ chains:
|
|||
- SeriesCharacterChain
|
||||
- MidJourneyPromptChain
|
||||
- TimeTravelGuideChain
|
||||
- SQLDatabaseChain
|
||||
|
||||
agents:
|
||||
- ZeroShotAgent
|
||||
|
|
@ -40,6 +41,27 @@ tools:
|
|||
- Tool
|
||||
- PythonFunction
|
||||
- JsonSpec
|
||||
- News API
|
||||
- TMDB API
|
||||
- Podcast API
|
||||
- QuerySQLDataBaseTool
|
||||
- InfoSQLDatabaseTool
|
||||
- ListSQLDatabaseTool
|
||||
# - QueryCheckerTool
|
||||
- BingSearchRun
|
||||
- GoogleSearchRun
|
||||
- GoogleSearchResults
|
||||
- JsonListKeysTool
|
||||
- JsonGetValueTool
|
||||
- PythonREPLTool
|
||||
- PythonAstREPLTool
|
||||
- RequestsGetTool
|
||||
- RequestsPostTool
|
||||
- RequestsPatchTool
|
||||
- RequestsPutTool
|
||||
- RequestsDeleteTool
|
||||
- WikipediaQueryRun
|
||||
- WolframAlphaQueryRun
|
||||
|
||||
wrappers:
|
||||
- RequestsWrapper
|
||||
|
|
@ -91,4 +113,16 @@ documentloaders:
|
|||
textsplitters:
|
||||
- CharacterTextSplitter
|
||||
|
||||
utilities:
|
||||
- BingSearchAPIWrapper
|
||||
- GoogleSearchAPIWrapper
|
||||
- GoogleSerperAPIWrapper
|
||||
- SearxResults
|
||||
- SearxSearchWrapper
|
||||
- SerpAPIWrapper
|
||||
- WikipediaAPIWrapper
|
||||
- WolframAlphaAPIWrapper
|
||||
# - ZapierNLAWrapper
|
||||
- SQLDatabase
|
||||
|
||||
dev: false
|
||||
|
|
|
|||
|
|
@ -12,6 +12,9 @@ CUSTOM_NODES = {
|
|||
"VectorStoreRouterAgent": nodes.VectorStoreRouterAgentNode(),
|
||||
"SQLAgent": nodes.SQLAgentNode(),
|
||||
},
|
||||
"utilities": {
|
||||
"SQLDatabase": nodes.SQLDatabaseNode(),
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -202,7 +202,11 @@ class Node:
|
|||
"VectorStoreRouterAgent",
|
||||
"VectorStoreAgent",
|
||||
"VectorStoreInfo",
|
||||
] or self.node_type in ["VectorStoreInfo", "VectorStoreRouterToolkit"]:
|
||||
] or self.node_type in [
|
||||
"VectorStoreInfo",
|
||||
"VectorStoreRouterToolkit",
|
||||
"SQLDatabase",
|
||||
]:
|
||||
return self._built_object
|
||||
return deepcopy(self._built_object)
|
||||
|
||||
|
|
|
|||
|
|
@ -101,6 +101,10 @@ class ChainNode(Node):
|
|||
self.params[key] = value.build(tools=tools, force=force)
|
||||
|
||||
self._build()
|
||||
|
||||
#! Cannot deepcopy SQLDatabaseChain
|
||||
if self.node_type in ["SQLDatabaseChain"]:
|
||||
return self._built_object
|
||||
return deepcopy(self._built_object)
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -9,10 +9,12 @@ from langchain import (
|
|||
memory,
|
||||
requests,
|
||||
text_splitter,
|
||||
utilities,
|
||||
vectorstores,
|
||||
)
|
||||
from langchain.agents import agent_toolkits
|
||||
from langchain.chat_models import ChatOpenAI
|
||||
from langchain.sql_database import SQLDatabase
|
||||
|
||||
from langflow.interface.importing.utils import import_class
|
||||
|
||||
|
|
@ -76,3 +78,9 @@ documentloaders_type_to_cls_dict: dict[str, Any] = {
|
|||
textsplitter_type_to_cls_dict: dict[str, Any] = dict(
|
||||
inspect.getmembers(text_splitter, inspect.isclass)
|
||||
)
|
||||
|
||||
## Utilities
|
||||
utility_type_to_cls_dict: dict[str, Any] = dict(
|
||||
inspect.getmembers(utilities, inspect.isclass)
|
||||
)
|
||||
utility_type_to_cls_dict["SQLDatabase"] = SQLDatabase
|
||||
|
|
|
|||
|
|
@ -10,7 +10,7 @@ from langchain.chat_models.base import BaseChatModel
|
|||
from langchain.llms.base import BaseLLM
|
||||
from langchain.tools import BaseTool
|
||||
|
||||
from langflow.interface.tools.util import get_tool_by_name
|
||||
from langflow.interface.tools.base import tool_creator
|
||||
|
||||
|
||||
def import_module(module_path: str) -> Any:
|
||||
|
|
@ -44,6 +44,7 @@ def import_by_type(_type: str, name: str) -> Any:
|
|||
"vectorstores": import_vectorstore,
|
||||
"documentloaders": import_documentloader,
|
||||
"textsplitters": import_textsplitter,
|
||||
"utilities": import_utility,
|
||||
}
|
||||
if _type == "llms":
|
||||
key = "chat" if "chat" in name.lower() else "llm"
|
||||
|
|
@ -107,7 +108,7 @@ def import_llm(llm: str) -> BaseLLM:
|
|||
def import_tool(tool: str) -> BaseTool:
|
||||
"""Import tool from tool name"""
|
||||
|
||||
return get_tool_by_name(tool)
|
||||
return tool_creator.type_to_loader_dict[tool]["fcn"]
|
||||
|
||||
|
||||
def import_chain(chain: str) -> Type[Chain]:
|
||||
|
|
@ -131,10 +132,16 @@ def import_vectorstore(vectorstore: str) -> Any:
|
|||
|
||||
def import_documentloader(documentloader: str) -> Any:
|
||||
"""Import documentloader from documentloader name"""
|
||||
|
||||
return import_class(f"langchain.document_loaders.{documentloader}")
|
||||
|
||||
|
||||
def import_textsplitter(textsplitter: str) -> Any:
|
||||
"""Import textsplitter from textsplitter name"""
|
||||
return import_class(f"langchain.text_splitter.{textsplitter}")
|
||||
|
||||
|
||||
def import_utility(utility: str) -> Any:
|
||||
"""Import utility from utility name"""
|
||||
if utility == "SQLDatabase":
|
||||
return import_class(f"langchain.sql_database.{utility}")
|
||||
return import_class(f"langchain.utilities.{utility}")
|
||||
|
|
|
|||
|
|
@ -8,6 +8,7 @@ from langflow.interface.prompts.base import prompt_creator
|
|||
from langflow.interface.text_splitters.base import textsplitter_creator
|
||||
from langflow.interface.toolkits.base import toolkits_creator
|
||||
from langflow.interface.tools.base import tool_creator
|
||||
from langflow.interface.utilities.base import utility_creator
|
||||
from langflow.interface.vector_store.base import vectorstore_creator
|
||||
from langflow.interface.wrappers.base import wrapper_creator
|
||||
|
||||
|
|
@ -26,6 +27,7 @@ def get_type_dict():
|
|||
"vectorStore": vectorstore_creator.to_list(),
|
||||
"embeddings": embedding_creator.to_list(),
|
||||
"textSplitters": textsplitter_creator.to_list(),
|
||||
"utilities": utility_creator.to_list(),
|
||||
}
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -82,6 +82,9 @@ def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any:
|
|||
documents = params.pop("documents")
|
||||
text_splitter = class_object(**params)
|
||||
return text_splitter.split_documents(documents)
|
||||
elif base_type == "utilities":
|
||||
if node_type == "SQLDatabase":
|
||||
return class_object.from_uri(params.pop("uri"))
|
||||
|
||||
return class_object(**params)
|
||||
|
||||
|
|
@ -91,7 +94,7 @@ def load_flow_from_json(path: str, build=True):
|
|||
from langflow.graph import Graph
|
||||
|
||||
"""Load flow from json file"""
|
||||
with open(path, "r") as f:
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
flow_graph = json.load(f)
|
||||
data_graph = flow_graph["data"]
|
||||
nodes = data_graph["nodes"]
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
import contextlib
|
||||
import io
|
||||
from typing import Any, Dict
|
||||
from chromadb.errors import NotEnoughElementsException
|
||||
|
||||
from langflow.cache.utils import compute_dict_hash, load_cache, memoize_dict
|
||||
from langflow.graph.graph import Graph
|
||||
|
|
@ -230,6 +231,10 @@ def get_result_and_thought_using_graph(langchain_object, message: str):
|
|||
else:
|
||||
thought = output_buffer.getvalue()
|
||||
|
||||
except NotEnoughElementsException as exc:
|
||||
raise ValueError(
|
||||
"Error: Not enough documents for ChromaDB to index. Try reducing chunk size in TextSplitter."
|
||||
) from exc
|
||||
except Exception as exc:
|
||||
raise ValueError(f"Error: {str(exc)}") from exc
|
||||
return result, thought
|
||||
|
|
|
|||
|
|
@ -1,7 +1,6 @@
|
|||
from typing import Dict, List, Optional
|
||||
|
||||
from langchain.agents.load_tools import (
|
||||
_BASE_TOOLS,
|
||||
_EXTRA_LLM_TOOLS,
|
||||
_EXTRA_OPTIONAL_TOOLS,
|
||||
_LLM_TOOLS,
|
||||
|
|
@ -10,17 +9,16 @@ from langchain.agents.load_tools import (
|
|||
from langflow.custom import customs
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.tools.constants import (
|
||||
ALL_TOOLS_NAMES,
|
||||
CUSTOM_TOOLS,
|
||||
FILE_TOOLS,
|
||||
OTHER_TOOLS,
|
||||
)
|
||||
from langflow.interface.tools.util import (
|
||||
get_tool_by_name,
|
||||
get_tool_params,
|
||||
get_tools_dict,
|
||||
)
|
||||
from langflow.interface.tools.util import get_tool_params
|
||||
from langflow.settings import settings
|
||||
from langflow.template.base import Template, TemplateField
|
||||
from langflow.utils import util
|
||||
from langflow.utils.util import build_template_from_class
|
||||
|
||||
TOOL_INPUTS = {
|
||||
"str": TemplateField(
|
||||
|
|
@ -66,64 +64,81 @@ class ToolCreator(LangChainTypeCreator):
|
|||
@property
|
||||
def type_to_loader_dict(self) -> Dict:
|
||||
if self.tools_dict is None:
|
||||
self.tools_dict = get_tools_dict()
|
||||
all_tools = {}
|
||||
for tool, tool_fcn in ALL_TOOLS_NAMES.items():
|
||||
tool_params = get_tool_params(tool_fcn)
|
||||
tool_name = tool_params.get("name", tool)
|
||||
|
||||
if tool_name in settings.tools or settings.dev:
|
||||
if tool_name == "JsonSpec":
|
||||
tool_params["path"] = tool_params.pop("dict_") # type: ignore
|
||||
all_tools[tool_name] = {
|
||||
"type": tool,
|
||||
"params": tool_params,
|
||||
"fcn": tool_fcn,
|
||||
}
|
||||
|
||||
self.tools_dict = all_tools
|
||||
|
||||
return self.tools_dict
|
||||
|
||||
def get_signature(self, name: str) -> Optional[Dict]:
|
||||
"""Get the signature of a tool."""
|
||||
|
||||
base_classes = ["Tool"]
|
||||
all_tools = {}
|
||||
for tool in self.type_to_loader_dict.keys():
|
||||
tool_fcn = get_tool_by_name(tool)
|
||||
if tool_params := get_tool_params(tool_fcn):
|
||||
tool_name = tool_params.get("name") or str(tool)
|
||||
all_tools[tool_name] = {
|
||||
"type": tool,
|
||||
"params": tool_params,
|
||||
"fcn": tool_fcn,
|
||||
}
|
||||
fields = []
|
||||
params = []
|
||||
tool_params = {}
|
||||
|
||||
# Raise error if name is not in tools
|
||||
if name not in all_tools.keys():
|
||||
if name not in self.type_to_loader_dict.keys():
|
||||
raise ValueError("Tool not found")
|
||||
|
||||
tool_type: str = all_tools[name]["type"] # type: ignore
|
||||
tool_type: str = self.type_to_loader_dict[name]["type"] # type: ignore
|
||||
|
||||
if all_tools[tool_type]["fcn"] in _BASE_TOOLS.values():
|
||||
params = []
|
||||
elif all_tools[tool_type]["fcn"] in _LLM_TOOLS.values():
|
||||
# if tool_type in _BASE_TOOLS.keys():
|
||||
# params = []
|
||||
if tool_type in _LLM_TOOLS.keys():
|
||||
params = ["llm"]
|
||||
elif all_tools[tool_type]["fcn"] in [
|
||||
val[0] for val in _EXTRA_LLM_TOOLS.values()
|
||||
]:
|
||||
n_dict = {val[0]: val[1] for val in _EXTRA_LLM_TOOLS.values()}
|
||||
extra_keys = n_dict[all_tools[tool_type]["fcn"]]
|
||||
elif tool_type in _EXTRA_LLM_TOOLS.keys():
|
||||
extra_keys = _EXTRA_LLM_TOOLS[tool_type][1]
|
||||
params = ["llm"] + extra_keys
|
||||
elif all_tools[tool_type]["fcn"] in [
|
||||
val[0] for val in _EXTRA_OPTIONAL_TOOLS.values()
|
||||
]:
|
||||
n_dict = {val[0]: val[1] for val in _EXTRA_OPTIONAL_TOOLS.values()} # type: ignore
|
||||
extra_keys = n_dict[all_tools[tool_type]["fcn"]]
|
||||
elif tool_type in _EXTRA_OPTIONAL_TOOLS.keys():
|
||||
extra_keys = _EXTRA_OPTIONAL_TOOLS[tool_type][1]
|
||||
params = extra_keys
|
||||
# elif tool_type == "Tool":
|
||||
# params = ["name", "description", "func"]
|
||||
elif tool_type in CUSTOM_TOOLS:
|
||||
# Get custom tool params
|
||||
params = all_tools[name]["params"] # type: ignore
|
||||
params = self.type_to_loader_dict[name]["params"] # type: ignore
|
||||
base_classes = ["function"]
|
||||
if node := customs.get_custom_nodes("tools").get(tool_type):
|
||||
return node
|
||||
elif tool_type in FILE_TOOLS:
|
||||
params = all_tools[name]["params"] # type: ignore
|
||||
if tool_type == "JsonSpec":
|
||||
params["path"] = params.pop("dict_") # type: ignore
|
||||
params = self.type_to_loader_dict[name]["params"] # type: ignore
|
||||
base_classes += [name]
|
||||
else:
|
||||
params = []
|
||||
elif tool_type in OTHER_TOOLS:
|
||||
print(tool_type)
|
||||
tool_dict = build_template_from_class(tool_type, OTHER_TOOLS)
|
||||
fields = tool_dict["template"]
|
||||
|
||||
# Pop unnecessary fields and add name
|
||||
fields.pop("_type") # type: ignore
|
||||
fields.pop("return_direct") # type: ignore
|
||||
fields.pop("verbose") # type: ignore
|
||||
|
||||
tool_params = {
|
||||
"name": fields.pop("name")["value"], # type: ignore
|
||||
"description": fields.pop("description")["value"], # type: ignore
|
||||
}
|
||||
|
||||
fields = [
|
||||
TemplateField(name=name, field_type=field["type"], **field)
|
||||
for name, field in fields.items() # type: ignore
|
||||
]
|
||||
base_classes += tool_dict["base_classes"]
|
||||
|
||||
# Copy the field and add the name
|
||||
fields = []
|
||||
for param in params:
|
||||
field = TOOL_INPUTS.get(param, TOOL_INPUTS["str"]).copy()
|
||||
field.name = param
|
||||
|
|
@ -134,7 +149,7 @@ class ToolCreator(LangChainTypeCreator):
|
|||
|
||||
template = Template(fields=fields, type_name=tool_type)
|
||||
|
||||
tool_params = all_tools[name]["params"]
|
||||
tool_params = {**tool_params, **self.type_to_loader_dict[name]["params"]}
|
||||
return {
|
||||
"template": util.format_dict(template.to_dict()),
|
||||
**tool_params,
|
||||
|
|
@ -144,21 +159,7 @@ class ToolCreator(LangChainTypeCreator):
|
|||
def to_list(self) -> List[str]:
|
||||
"""List all load tools"""
|
||||
|
||||
tools = []
|
||||
|
||||
for tool, fcn in get_tools_dict().items():
|
||||
tool_params = get_tool_params(fcn)
|
||||
|
||||
if tool_params and not tool_params.get("name"):
|
||||
tool_params["name"] = tool
|
||||
|
||||
if tool_params and (
|
||||
tool_params.get("name") in settings.tools
|
||||
or (tool_params.get("name") and settings.dev)
|
||||
):
|
||||
tools.append(tool_params["name"])
|
||||
|
||||
return tools
|
||||
return list(self.type_to_loader_dict.keys())
|
||||
|
||||
|
||||
tool_creator = ToolCreator()
|
||||
|
|
|
|||
|
|
@ -5,12 +5,50 @@ from langchain.agents.load_tools import (
|
|||
_EXTRA_OPTIONAL_TOOLS,
|
||||
_LLM_TOOLS,
|
||||
)
|
||||
from langchain.tools.json.tool import JsonSpec
|
||||
from langchain.tools.bing_search.tool import BingSearchRun
|
||||
from langchain.tools.google_search.tool import GoogleSearchResults, GoogleSearchRun
|
||||
from langchain.tools.json.tool import JsonGetValueTool, JsonListKeysTool, JsonSpec
|
||||
from langchain.tools.python.tool import PythonAstREPLTool, PythonREPLTool
|
||||
from langchain.tools.requests.tool import (
|
||||
RequestsDeleteTool,
|
||||
RequestsGetTool,
|
||||
RequestsPatchTool,
|
||||
RequestsPostTool,
|
||||
RequestsPutTool,
|
||||
)
|
||||
from langchain.tools.sql_database.tool import (
|
||||
InfoSQLDatabaseTool,
|
||||
ListSQLDatabaseTool,
|
||||
QueryCheckerTool,
|
||||
QuerySQLDataBaseTool,
|
||||
)
|
||||
from langchain.tools.wikipedia.tool import WikipediaQueryRun
|
||||
from langchain.tools.wolfram_alpha.tool import WolframAlphaQueryRun
|
||||
|
||||
from langflow.interface.tools.custom import PythonFunction
|
||||
|
||||
FILE_TOOLS = {"JsonSpec": JsonSpec}
|
||||
CUSTOM_TOOLS = {"Tool": Tool, "PythonFunction": PythonFunction}
|
||||
OTHER_TOOLS = {
|
||||
"QuerySQLDataBaseTool": QuerySQLDataBaseTool,
|
||||
"InfoSQLDatabaseTool": InfoSQLDatabaseTool,
|
||||
"ListSQLDatabaseTool": ListSQLDatabaseTool,
|
||||
"QueryCheckerTool": QueryCheckerTool,
|
||||
"BingSearchRun": BingSearchRun,
|
||||
"GoogleSearchRun": GoogleSearchRun,
|
||||
"GoogleSearchResults": GoogleSearchResults,
|
||||
"JsonListKeysTool": JsonListKeysTool,
|
||||
"JsonGetValueTool": JsonGetValueTool,
|
||||
"PythonREPLTool": PythonREPLTool,
|
||||
"PythonAstREPLTool": PythonAstREPLTool,
|
||||
"RequestsGetTool": RequestsGetTool,
|
||||
"RequestsPostTool": RequestsPostTool,
|
||||
"RequestsPatchTool": RequestsPatchTool,
|
||||
"RequestsPutTool": RequestsPutTool,
|
||||
"RequestsDeleteTool": RequestsDeleteTool,
|
||||
"WikipediaQueryRun": WikipediaQueryRun,
|
||||
"WolframAlphaQueryRun": WolframAlphaQueryRun,
|
||||
}
|
||||
ALL_TOOLS_NAMES = {
|
||||
**_BASE_TOOLS,
|
||||
**_LLM_TOOLS, # type: ignore
|
||||
|
|
@ -18,4 +56,5 @@ ALL_TOOLS_NAMES = {
|
|||
**{k: v[0] for k, v in _EXTRA_OPTIONAL_TOOLS.items()},
|
||||
**CUSTOM_TOOLS,
|
||||
**FILE_TOOLS, # type: ignore
|
||||
**OTHER_TOOLS,
|
||||
}
|
||||
|
|
|
|||
|
|
@ -4,29 +4,6 @@ from typing import Dict, Union
|
|||
|
||||
from langchain.agents.tools import Tool
|
||||
|
||||
from langflow.interface.tools.constants import ALL_TOOLS_NAMES
|
||||
|
||||
|
||||
def get_tools_dict():
|
||||
"""Get the tools dictionary."""
|
||||
|
||||
all_tools = {}
|
||||
|
||||
for tool, fcn in ALL_TOOLS_NAMES.items():
|
||||
if tool_params := get_tool_params(fcn):
|
||||
tool_name = tool_params.get("name") or str(tool)
|
||||
all_tools[tool_name] = fcn
|
||||
|
||||
return all_tools
|
||||
|
||||
|
||||
def get_tool_by_name(name: str):
|
||||
"""Get a tool from the tools dictionary."""
|
||||
tools = get_tools_dict()
|
||||
if name not in tools:
|
||||
raise ValueError(f"{name} not found.")
|
||||
return tools[name]
|
||||
|
||||
|
||||
def get_func_tool_params(func, **kwargs) -> Union[Dict, None]:
|
||||
tree = ast.parse(inspect.getsource(func))
|
||||
|
|
@ -113,6 +90,8 @@ def get_tool_params(tool, **kwargs) -> Dict:
|
|||
elif inspect.isclass(tool):
|
||||
# Get the parameters necessary to
|
||||
# instantiate the class
|
||||
|
||||
return get_class_tool_params(tool, **kwargs) or {}
|
||||
|
||||
else:
|
||||
raise ValueError("Tool must be a function or class.")
|
||||
|
|
|
|||
|
|
@ -8,6 +8,7 @@ from langflow.interface.prompts.base import prompt_creator
|
|||
from langflow.interface.text_splitters.base import textsplitter_creator
|
||||
from langflow.interface.toolkits.base import toolkits_creator
|
||||
from langflow.interface.tools.base import tool_creator
|
||||
from langflow.interface.utilities.base import utility_creator
|
||||
from langflow.interface.vector_store.base import vectorstore_creator
|
||||
from langflow.interface.wrappers.base import wrapper_creator
|
||||
|
||||
|
|
@ -42,6 +43,7 @@ def build_langchain_types_dict(): # sourcery skip: dict-assign-update-to-union
|
|||
vectorstore_creator,
|
||||
documentloader_creator,
|
||||
textsplitter_creator,
|
||||
utility_creator,
|
||||
]
|
||||
|
||||
all_types = {}
|
||||
|
|
|
|||
0
src/backend/langflow/interface/utilities/__init__.py
Normal file
0
src/backend/langflow/interface/utilities/__init__.py
Normal file
39
src/backend/langflow/interface/utilities/base.py
Normal file
39
src/backend/langflow/interface/utilities/base.py
Normal file
|
|
@ -0,0 +1,39 @@
|
|||
from typing import Dict, List, Optional
|
||||
|
||||
from langflow.custom.customs import get_custom_nodes
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.custom_lists import utility_type_to_cls_dict
|
||||
from langflow.settings import settings
|
||||
from langflow.utils.logger import logger
|
||||
from langflow.utils.util import build_template_from_class
|
||||
|
||||
|
||||
class UtilityCreator(LangChainTypeCreator):
|
||||
type_name: str = "utilities"
|
||||
|
||||
@property
|
||||
def type_to_loader_dict(self) -> Dict:
|
||||
return utility_type_to_cls_dict
|
||||
|
||||
def get_signature(self, name: str) -> Optional[Dict]:
|
||||
"""Get the signature of a utility."""
|
||||
try:
|
||||
if name in get_custom_nodes(self.type_name).keys():
|
||||
return get_custom_nodes(self.type_name)[name]
|
||||
return build_template_from_class(name, utility_type_to_cls_dict)
|
||||
except ValueError as exc:
|
||||
raise ValueError(f"Utility {name} not found") from exc
|
||||
|
||||
except AttributeError as exc:
|
||||
logger.error(f"Utility {name} not loaded: {exc}")
|
||||
return None
|
||||
|
||||
def to_list(self) -> List[str]:
|
||||
return [
|
||||
utility.__name__
|
||||
for utility in self.type_to_loader_dict.values()
|
||||
if utility.__name__ in settings.utilities or settings.dev
|
||||
]
|
||||
|
||||
|
||||
utility_creator = UtilityCreator()
|
||||
|
|
@ -18,6 +18,7 @@ class Settings(BaseSettings):
|
|||
wrappers: List[str] = []
|
||||
toolkits: List[str] = []
|
||||
textsplitters: List[str] = []
|
||||
utilities: List[str] = []
|
||||
dev: bool = False
|
||||
|
||||
class Config:
|
||||
|
|
@ -42,6 +43,7 @@ class Settings(BaseSettings):
|
|||
self.wrappers = new_settings.wrappers or []
|
||||
self.toolkits = new_settings.toolkits or []
|
||||
self.textsplitters = new_settings.textsplitters or []
|
||||
self.utilities = new_settings.utilities or []
|
||||
self.dev = new_settings.dev or False
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -256,6 +256,29 @@ class CSVAgentNode(FrontendNode):
|
|||
return super().to_dict()
|
||||
|
||||
|
||||
class SQLDatabaseNode(FrontendNode):
|
||||
name: str = "SQLDatabase"
|
||||
template: Template = Template(
|
||||
type_name="sql_database",
|
||||
fields=[
|
||||
TemplateField(
|
||||
field_type="str",
|
||||
required=True,
|
||||
is_list=False,
|
||||
show=True,
|
||||
multiline=False,
|
||||
value="",
|
||||
name="uri",
|
||||
),
|
||||
],
|
||||
)
|
||||
description: str = """SQLAlchemy wrapper around a database."""
|
||||
base_classes: list[str] = ["SQLDatabase"]
|
||||
|
||||
def to_dict(self):
|
||||
return super().to_dict()
|
||||
|
||||
|
||||
class VectorStoreAgentNode(FrontendNode):
|
||||
name: str = "VectorStoreAgent"
|
||||
template: Template = Template(
|
||||
|
|
|
|||
|
|
@ -13,7 +13,8 @@ import {
|
|||
QuestionMarkCircleIcon,
|
||||
FingerPrintIcon,
|
||||
ScissorsIcon,
|
||||
CircleStackIcon
|
||||
CircleStackIcon,
|
||||
Squares2X2Icon
|
||||
} from "@heroicons/react/24/outline";
|
||||
import { Connection, Edge, Node, ReactFlowInstance } from "reactflow";
|
||||
import { FlowType } from "./types/flow";
|
||||
|
|
@ -85,6 +86,7 @@ export const nodeColors: {[char: string]: string} = {
|
|||
textsplitters: "#B47CB5",
|
||||
toolkits:"#DB2C2C",
|
||||
wrappers:"#E6277A",
|
||||
utilities:"#31A3CC",
|
||||
unknown:"#9CA3AF"
|
||||
};
|
||||
|
||||
|
|
@ -103,6 +105,7 @@ export const nodeNames:{[char: string]: string} = {
|
|||
toolkits:"Toolkits",
|
||||
wrappers:"Wrappers",
|
||||
textsplitters: "Text Splitters",
|
||||
utilities:"Utilities",
|
||||
unknown:"Unknown"
|
||||
};
|
||||
|
||||
|
|
@ -121,6 +124,7 @@ export const nodeIcons:{[char: string]: React.ForwardRefExoticComponent<React.SV
|
|||
toolkits:WrenchScrewdriverIcon,
|
||||
textsplitters:ScissorsIcon,
|
||||
wrappers:GiftIcon,
|
||||
utilities:Squares2X2Icon,
|
||||
unknown:QuestionMarkCircleIcon
|
||||
};
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue