jyapayne/langflow
1
0
Fork 0
Code Issues Pull requests Projects Releases 1 Packages Wiki Activity Actions

docs: Touchup cloud provider deployment pages (#9241)

Browse source 
* recreate 9232 because brokne build

* fix links

* fix nav level

---------

Co-authored-by: Mendon Kissling <59585235+mendonk@users.noreply.github.com>
This commit is contained in:
April I. Murphy 2025-07-30 06:09:56 -07:00 • committed by GitHub
commit 47be23e02a
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
11 changed files with 54 additions and 51 deletions
Download patch file Download diff file Expand all files Collapse all files

2
docs/docs/Components/components-custom-components.mdx
View file

@ -235,7 +235,7 @@ def some_method(self):
By default, Langflow looks for custom components in the `langflow/components` directory.
If you're creating custom components in a different location using the [`LANGFLOW_COMPONENTS_PATH`](/environment-variables#LANGFLOW_COMPONENTS_PATH) environment variable, components must be organized in a specific directory structure to be properly loaded and displayed in the UI:
If you're creating custom components in a different location using the `LANGFLOW_COMPONENTS_PATH` [environment variable](/environment-variables), components must be organized in a specific directory structure to be properly loaded and displayed in the UI:
```
/your/custom/components/path/ # Base directory set by LANGFLOW_COMPONENTS_PATH

2
docs/docs/Components/components-data.mdx
View file

@ -115,7 +115,7 @@ For more information about uploading files and working with files in flows, see
### File type and size limits
By default, the maximum file size is 100 MB.
To modify this value, change the [`--max-file-size-upload` environment variable](/environment-variables#LANGFLOW_MAX_FILE_SIZE_UPLOAD).
To modify this value, change the `--max-file-size-upload` [environment variable](/environment-variables).
<details>
<summary>Supported file types</summary>

2
docs/docs/Concepts/concepts-file-management.mdx
View file

@ -94,7 +94,7 @@ For videos, see the **Twelve Labs** and **YouTube** [bundles](/components-bundle
## Set the maximum file size
By default, the maximum file size is 100 MB.
To modify this value, change the [`--max-file-size-upload` environment variable](/environment-variables#LANGFLOW_MAX_FILE_SIZE_UPLOAD).
To modify this value, change the `--max-file-size-upload` [environment variable](/environment-variables).
## See also

8
docs/docs/Configuration/environment-variables.mdx
View file

@ -181,10 +181,10 @@ The following table lists the environment variables supported by Langflow.
| `LANGFLOW_PORT` | Integer | `7860` | The port on which the Langflow server runs. The server automatically selects a free port if the specified port is in use. See [`--port`](./configuration-cli.mdx#run-port). |
| `LANGFLOW_PROMETHEUS_ENABLED` | Boolean | `false` | Expose Prometheus metrics. |
| `LANGFLOW_PROMETHEUS_PORT` | Integer | `9090` | Set the port on which Langflow exposes Prometheus metrics. |
| `LANGFLOW_REDIS_CACHE_EXPIRE` | Integer | `3600` | See [`LANGFLOW_CACHE_TYPE`](#LANGFLOW_CACHE_TYPE). |
| `LANGFLOW_REDIS_DB` | Integer | `0` | See [`LANGFLOW_CACHE_TYPE`](#LANGFLOW_CACHE_TYPE). |
| `LANGFLOW_REDIS_HOST` | String | `localhost` | See [`LANGFLOW_CACHE_TYPE`](#LANGFLOW_CACHE_TYPE). |
| `LANGFLOW_REDIS_PORT` | String | `6379` | See [`LANGFLOW_CACHE_TYPE`](#LANGFLOW_CACHE_TYPE). |
| `LANGFLOW_REDIS_CACHE_EXPIRE` | Integer | `3600` | See `LANGFLOW_CACHE_TYPE`. |
| `LANGFLOW_REDIS_DB` | Integer | `0` | See `LANGFLOW_CACHE_TYPE`. |
| `LANGFLOW_REDIS_HOST` | String | `localhost` | See `LANGFLOW_CACHE_TYPE`. |
| `LANGFLOW_REDIS_PORT` | String | `6379` | See `LANGFLOW_CACHE_TYPE`. |
| `LANGFLOW_REDIS_PASSWORD` | String | Not set | Password for Redis authentication when using Redis cache type. |
| `LANGFLOW_REMOVE_API_KEYS` | Boolean | `false` | Remove API keys from the projects saved in the database. See [`--remove-api-keys`](./configuration-cli.mdx#run-remove-api-keys). |
| `LANGFLOW_SAVE_DB_IN_CONFIG_DIR` | Boolean | `false` | Save the Langflow database in `LANGFLOW_CONFIG_DIR` instead of in the Langflow package directory. Note, when this variable is set to default (`false`), the database isn't shared between different virtual environments and the database is deleted when you uninstall Langflow. |

28
docs/docs/Deployment/deployment-gcp.mdx
View file

@ -3,27 +3,25 @@ title: Deploy Langflow on Google Cloud Platform
slug: /deployment-gcp
---
This guide demonstrates deploying Langflow on Google Cloud Platform.
This guide demonstrates how to deploy Langflow on Google Cloud Platform with a Cloud Shell script that walks through the process of setting up a Debian-based VM with the Langflow package, Nginx, and the necessary configurations to run the Langflow development environment in GCP.
To deploy Langflow on Google Cloud Platform using Cloud Shell, use the below script.
To use this script, you need a [Google Cloud](https://console.cloud.google.com/) project with the necessary permissions to create resources.
The script guides you through setting up a Debian-based VM with the Langflow package, Nginx, and the necessary configurations to run the Langflow dev environment in GCP.
## Prerequisites
* A [Google Cloud](https://console.cloud.google.com/) project with the necessary permissions to create resources
## Deploy Langflow in GCP
1. Click the following button to launch Cloud Shell:
1. Follow this link to launch the Cloud Shell with the GCP deployment script from the Langflow repository:
[![Deploy to Google Cloud](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial.md)
2. Click **Trust repo**. Some gcloud commands may not run in an ephemeral Cloud Shell environment.
3. Click **Start** and follow the tutorial to deploy Langflow.
2. Click **Trust repo**.
## Pricing
Some `gcloud` commands may not run in an ephemeral Cloud Shell environment.
This deployment uses a [spot (preemptible) instance](https://cloud.google.com/compute/docs/instances/preemptible), which is a cost-effective option for running Langflow. However, **due to the nature of spot instances, the VM may be terminated at any time if Google Cloud needs to reclaim the resources**.
3. Click **Start**, and then follow the tutorial to deploy Langflow.
:::info
This deployment uses a [spot (preemptible) instance](https://cloud.google.com/compute/docs/instances/preemptible) as a cost-effective option to demonstrate how to deploy Langflow on GCP.
However, due to the nature of spot instances, the VM can be terminated at any time if Google Cloud needs to reclaim the resources.
For a more stable deployment, consider using a regular VM instance instead of a spot instance.
For more information, see the [GCP pricing calculator](https://cloud.google.com/products/calculator?hl=en).
:::

19
docs/docs/Deployment/deployment-hugging-face-spaces.mdx
View file

@ -1,21 +1,18 @@
---
title: Deploy Langflow on HuggingFace Spaces
title: Deploy Langflow on Hugging Face Spaces
slug: /deployment-hugging-face-spaces
---
This guide explains how to deploy Langflow on [HuggingFace Spaces](https://huggingface.co/spaces/).
This guide explains how to deploy Langflow on [Hugging Face Spaces](https://huggingface.co/spaces/).
1. Go to the [Langflow Space](https://huggingface.co/spaces/Langflow/Langflow?duplicate=true).
2. Click **Duplicate Space**.
3. In the configuration dialog, do the following:
- Enter a name for your Space.
- Select either public or private visibility.
- Click **Duplicate Space**
3. Configure the duplicated Space:
1. Enter a name for your Space.
2. Select either public or private visibility.
3. Click **Duplicate Space**.
![Hugging Face deployment dialog](/img/hugging-face-deployment.png)
Wait for the setup to complete. You'll be redirected to your new Space automatically.
Your Langflow instance is now ready to use.
When setup is complete, you're redirected to your new Space automatically, and your Langflow instance is ready to use.

2
docs/docs/Deployment/deployment-prod-best-practices.mdx
View file

@ -12,7 +12,7 @@ Langflow can be deployed in two distinct environments.
* [**Langflow runtime**](/deployment-kubernetes-prod): The **Langflow runtime** is a headless or backend-only mode. The server exposes your flow as an endpoint, and runs only the processes necessary to serve your flow, with PostgreSQL as the database for improved scalability. Use the Langflow **runtime** to deploy your flows if you don't require the frontend for visual development. The Langflow runtime can be deployed on [Docker](/deployment-docker) or [Kubernetes](/deployment-kubernetes-prod).
:::tip
You can start Langflow in headless mode with the [`LANGFLOW_BACKEND_ONLY`](/environment-variables#LANGFLOW_BACKEND_ONLY) environment variable.
You can start Langflow in headless mode with the `LANGFLOW_BACKEND_ONLY` [environment variable](/environment-variables).
:::
Deploying on Kubernetes offers the following advantages:

23
docs/docs/Deployment/deployment-railway.mdx
View file

@ -1,20 +1,23 @@
---
title: Deploy Langflow on Railway
description: Deploy Langflow to Railway using a one-click template
slug: /deployment-railway
---
This guide explains how to deploy Langflow on [Railway](https://railway.app/), a cloud infrastructure platform that provides auto-deploy, managed databases, and automatic scaling.
This guide explains how to [deploy Langflow on Railway](https://railway.com/?utm_medium=integration&utm_source=docs&utm_campaign=langflow), a cloud infrastructure platform that provides auto-deploy, managed databases, and automatic scaling.
1. Click the following button to go to Railway:
1. Create a Railway account.
[![Deploy on Railway](/logos/railway-deploy.svg)](https://railway.app/template/JMXEWp?referralCode=MnPSdg)
A Hobby account on Railway is sufficient for Langflow's dual-core CPU and 2 GB RAM requirements. For more information, see [Railway pricing](https://railway.com/pricing?utm_medium=integration&utm_source=docs&utm_campaign=langflow).
2. Click **Deploy Now**.
Railway automatically does the following:
- Sets up the infrastructure.
- Deploys Langflow.
- Starts the application.
2. Follow this link to deploy the Langflow template on Railway:
Wait for the deployment to complete.
[![Deploy on Railway](/logos/railway-deploy.svg)](https://railway.com/new/template/JMXEWp?referralCode=MnPSdg&utm_medium=integration&utm_source=docs&utm_campaign=langflow)
Your Langflow instance is now ready to use.
3. Optional: Add any custom configuration for your Langflow deployment.
The Langflow Railway template automatically sets up the infrastructure, deploys Langflow, and then starts the application.
4. Wait for the deployment to complete.
5. Navigate to your Langflow instance at your deployment's public URL, such as `https://APP-NAME.up.railway.app`.

9
docs/docs/Deployment/deployment-render.mdx
View file

@ -7,15 +7,14 @@ This guide explains how to deploy Langflow on [Render](https://render.com/), a c
1. Prepare a Render instance that can support Langflow.
Langflow requires at least 2 GB of RAM to run, so you must use a **Standard** or better Render instance type.
Langflow requires at least 2 GB of RAM to run, so you must use a Render instance type of **Standard** or better.
This requires a paid Render account.
For more information, see [Render Web Services](https://render.com/docs/web-services) and [Render pricing](https://render.com/pricing).
2. Click the following button to go to Render:
2. Follow this link to start a Langflow deployment on Render:
[![Deploy to Render](/logos/render-deploy.svg)](https://render.com/deploy?repo=https%3A%2F%2Fgithub.com%2Flangflow-ai%2Flangflow%2Ftree%2Fdev)
3. Enter a blueprint name, and then select the branch for your `render.yaml` file.
3. Enter a blueprint name, select the branch for your `render.yaml` file, and then click **Deploy Blueprint**.
4. Click **Deploy Blueprint**, and then wait for the deployment to complete.
Once complete, your Langflow instance is ready to use.
When deployment is complete, your Langflow instance is ready to use.

2
docs/docs/Develop/memory.mdx
View file

@ -82,7 +82,7 @@ LANGFLOW_CACHE_TYPE=Async
Alternative caching options can be configured, but options other than the default asynchronous, in-memory cache are not supported.
The default behavior is suitable for most use cases.
For other options, see [`LANGFLOW_CACHE_TYPE`](/environment-variables#LANGFLOW_CACHE_TYPE).
For other options, see the `LANGFLOW_CACHE_TYPE` [environment variable](/environment-variables).
## Store chat memory