Before you start
- Create the first administrator, then select provider/model nodes and save their credentials in Flowise
- Create or import an agent flow and protect its prediction API with an API key
- No model weights or ready-made autonomous flow are installed
- Persist SQLite, uploaded files and credential encryption keys together
- Tool execution uses this service's restricted container
- After deployment, open Custom domains, verify the site URL hostname, and apply routing and TLS before using login or callbacks
Configuration that needs your attention
Use a stable HTTPS origin and five persistent signing, session and encryption secret references.
Create the administrator, choose model nodes, add provider credentials and protect the prediction API inside Flowise.
Persist SQLite, uploaded files and credential keys together. The template does not install a ready-made autonomous flow or model weights.
Required secrets
Configure these scoped secrets during deployment review in your Hakopod installation. Secret values stay out of the application TOML.
-
credential-encryption-key -
session-secret -
token-hash-secret -
token-refresh-secret -
token-signing-secret
This preset needs a public site URL. Set the correct origin before starting the application.
Use this preset
- Open the Catalog in your own Hakopod dashboard and select Flowise.
- Choose the project, environment, and application name. Set the required values and secret references.
- Review the generated configuration, resource requests, networking, and storage plan.
- Deploy, then inspect readiness and logs. Configure backups for persistent data before relying on the service.
Read the upstream setup documentation ↗
View native TOML and setup notes ↗
Pinned container image
docker.io/flowiseai/flowise:3.1.4@sha256:3922767afb52a5777759fd8b28a3c9eee864daea96018a791f2429eae2a76571
The catalog pins this image for reproducibility. Review upstream updates and compatibility before changing it.