wwwzhouhui/dify-for-dsl

本项目是基于dify开源项目实现的dsl工作流脚本合集

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Summary Information

Updated 57 minutes ago
Type:Template / ExampleCategory(s):AI App Builders & PlatformsAI Agents & LLM Apps
Added to GitGenius on September 17th, 2026
Created on November 15th, 2024
Open Issues & Pull Requests: 10 (+0)
GitHub issues: Enabled
Number of forks: 742
Total Stargazers: 3,874 (+0)
Total Subscribers: 66 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 23.3 hours
Mean response time: 3.7 days
90th percentile: 6.2 days
Tracked items: 11

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Open issues: 9
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 368 days
Stale 30+ days: 9
Stale 90+ days: 9

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Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

dify-for-dsl is a collection of DSL workflow scripts built on the Dify open-source project.

The project addresses the need for reusable workflow templates within Dify by providing a curated set of pre-built DSL workflows that users can import directly into their Dify instances. Rather than building workflows from scratch, users can leverage these existing scripts as starting points for their own applications. The workflows are designed to be imported through Dify's standard DSL import mechanism, which allows users to load complete workflow definitions into new applications.

This collection is suited for developers and teams already using Dify who want to accelerate their workflow development by studying and adapting existing examples. The project explicitly targets Dify version 0.8.0 and later, so compatibility with that version range is a prerequisite for adoption. Users should treat these workflows as templates for learning and customization rather than as production-ready solutions requiring no modification. The repository functions as a shared resource where workflows can be discovered, imported, and adapted to specific use cases.

The project maintains a straightforward structure centered on DSL workflow files that can be imported directly into Dify applications. Development activity appears focused on expanding the collection of available workflows rather than on framework-level changes or architectural evolution.