DSL examples for Dify AI workflows
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This repository provides a collection of open-source Dify workflow examples, demonstrating practical applications of Dify's AI application DSL. It's designed for developers new to Dify, enterprise teams standardizing processes, educators, and the open-source community looking to collaborate on automation solutions. The primary benefit is enabling users to quickly build and deploy complex AI workflows by leveraging pre-built, commented examples.
How It Works
The project showcases Dify workflows that integrate with external services via Flask backends and HTTP requests. These workflows leverage Large Language Models (LLMs) for tasks like data generation, content extraction, summarization, and translation. Examples include generating Excel files, creating PPTs, producing Word documents, recognizing invoice data, analyzing GitHub projects, generating mind maps, and processing web content for knowledge bases. The approach emphasizes "workflow-as-code" for standardization and reusability.
Quick Start & Requirements
Excel_Flask_Dify/Excel_flask_Service
), and run the Flask service using python3 <service_script.py>
. Then, import the corresponding .yml
DSL file into Dify and configure HTTP request nodes with the Flask service URL.openpyxl
for Excel, python-docx
for Word, Pillow
for image processing). Some workflows may require specific LLM models or external tools like ComfyUI.Highlighted Details
.yml
DSL files for easy import into Dify.Maintenance & Community
Licensing & Compatibility
Limitations & Caveats
3 days ago
1 week