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Deepfish

Deepfish is an open-source visual AI workflow editor for connecting generative models into pipelines, executing them and sharing reusable workflows. Its documented integrations include Fal.ai and Replicate, with support listed for text, image, audio, video and 3D generation.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Deepfish — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Deepfish when a visual node editor and reusable workflows are useful for combining supported generative models, or when you want to inspect and run the project locally.

Who it is for

  • Developers building multi-step generative AI workflows.
  • People who want to adapt, fork or share reusable model workflows.
  • Teams evaluating a self-hostable TypeScript application for visual model orchestration.

Documented uses

  • Connect model nodes into a visual generation pipeline.
  • Use Fal.ai and Replicate integrations in a workflow.
  • Import, fork and share community workflows.
  • Handle long-running generation tasks asynchronously through the documented Inngest integration.
Before you choose

Requirements & limits

The project is available as a public repository under the MIT license. The README documents local development setup and required third-party accounts and keys.

  • The documented first-class provider integrations are Fal.ai and Replicate; the README does not enumerate every supported model or operation.
  • The workflow library supports importing, sharing and forking community workflows.
  • The documented execution model is client-directed graph execution, with Inngest used for long-running tasks.
  • Local setup includes PostgreSQL, Docker and credentials for several external services.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up Deepfish locally

Prepare a local development environment and start the Deepfish development server.

Before you start

  • Node.js 18 or later
  • Docker for the local database
  • Accounts and API keys for Clerk, Stripe, Fal.ai, Replicate and Vercel Blob

Steps

  1. Clone the repository and change into its directory.

  2. Install dependencies with npm install.

  3. Copy env.example to .env and fill in the required service keys.

  4. Start PostgreSQL with docker compose up -d, then apply migrations with npx drizzle-kit migrate.

  5. Start the development server with npm run dev.

Expected outcome

A locally running Deepfish development server with its database migrations applied.

Guide limitations

  • The documented setup requires credentials for the listed external services.
  • The README describes a development server, not production deployment.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
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Sources checked
17 October 2026
Original website title
noahgsolomon/deepfish · Official homepage title · retained in its source language
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