This Dify workflow creates an end-to-end content pipeline: input a topic, the agent researches relevant information, generates a blog post, social media snippets, and an email newsletter, then formats everything for publishing.
TL;DR — Key Takeaways
- AI Content Generation Pipeline with Dify — Intermediate level
- Tool: Dify
- 5 steps with detailed instructions
- Prerequisites: Dify account, OpenAI/Anthropic API key, CMS API access (optional)
Use Case
Content marketing teams producing daily blog posts, social media, and newsletters from a single topic input.
Prerequisites
Dify account, OpenAI/Anthropic API key, CMS API access (optional)
Workflow Diagram
AI Content Generation Pipeline with Dify
Step-by-Step Guide
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Create Workflow App
In Dify, create a new Workflow app. This allows you to chain multiple LLM calls and tool uses in a visual pipeline. Set the input variable as topic (string type).
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Research Node
Add an LLM node with a research prompt: Research the topic and provide 5 key facts, 3 statistics, and 2 expert quotes. Use a search-enabled model if available. Store output as research_data.
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Content Generation Nodes
Add 3 parallel LLM nodes: 1) Blog post (1500 words, SEO-optimized) using research_data, 2) 3 social media posts (Twitter/LinkedIn/Mastodon), 3) Email newsletter (300 words). Each uses research_data as context.
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Quality Check Node
Add an LLM node that reviews all generated content for factual accuracy, tone consistency, and brand alignment. Output a quality_score and suggested edits. Route back to generation if score < 7/10.
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Output and Integration
Add an output node that formats all content into a single JSON response. Connect to your CMS via API or use Dify webhook to trigger publishing. Schedule with a cron trigger for daily content generation.
Tags
This workflow answers:
- How to set up ai content generation pipeline with dify
- What tools and access you need
- How to troubleshoot common issues