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--- |
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title: n8n Workflow Generator |
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emoji: 🚀 |
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colorFrom: red |
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colorTo: green |
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sdk: gradio |
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sdk_version: 4.16.0 |
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app_file: app.py |
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pinned: false |
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license: apache-2.0 |
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--- |
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# n8n Workflow Generator |
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Generate n8n workflows using natural language! This app uses a fine-tuned **Qwen2.5-Coder-1.5B** model to convert plain English descriptions into working n8n workflows. |
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## 🎯 Performance |
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- **Overall Test Score:** 92.4% |
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- **Training Examples:** 247 curated workflows |
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- **Validation Examples:** 44 |
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## 🚀 Features |
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- **Natural Language Input:** Describe workflows in plain English |
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- **Visual Preview:** See your workflow nodes and connections |
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- **TypeScript DSL:** Get clean, production-ready code |
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- **n8n JSON Export:** Import directly into your n8n instance |
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- **Adjustable Parameters:** Control creativity and output length |
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## 📊 Test Results by Category |
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| Category | Score | |
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|----------|-------| |
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| Basic Workflows | 100% | |
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| Complexity | 96% | |
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| Error Handling | 80% | |
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| Loops | 67% | |
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| Branching | 67% | |
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| **Overall** | **92.4%** | |
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## 💡 Example Prompts |
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Try these prompts to see what the model can do: |
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- "Create a webhook that sends data to Slack" |
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- "Schedule that runs daily and backs up database to Google Drive" |
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- "Webhook receives form data, validates email, saves to Airtable" |
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- "Monitor RSS feed and post new items to Twitter" |
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- "Fetch GitHub issues, if priority is high send to Slack, else email" |
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## 🛠️ How It Works |
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1. **Input:** You describe your workflow in natural language |
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2. **Generation:** Fine-tuned Qwen2.5-Coder-1.5B generates TypeScript DSL |
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3. **Conversion:** Code is converted to n8n JSON format |
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4. **Visualization:** Workflow structure is displayed visually |
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5. **Export:** Copy and import into your n8n instance |
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## 📝 Model Details |
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- **Base Model:** Qwen/Qwen2.5-Coder-1.5B-Instruct |
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- **Fine-tuning Method:** LoRA (Low-Rank Adaptation) |
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- **Dataset:** Curated n8n workflows from GitHub |
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- **Training Framework:** Transformers + PEFT |
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## 🎓 Training Details |
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- **LoRA Rank:** 16 |
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- **LoRA Alpha:** 32 |
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- **Learning Rate:** 2e-4 |
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- **Training Strategy:** Early stopping with validation monitoring |
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- **Hardware:** NVIDIA Tesla T4 GPU |
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## 📖 Usage Tips |
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- **Be specific:** More details = better results |
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- **Use n8n terminology:** Mention specific nodes like "webhook", "Slack", "HTTP Request" |
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- **Describe the flow:** "When X happens, do Y, then Z" |
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- **Adjust temperature:** Lower (0.1-0.3) for consistency, higher (0.5-0.8) for creativity |
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## 🔧 Limitations |
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- Works best with common n8n patterns |
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- May struggle with very complex branching (>5 conditions) |
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- Advanced error handling might need manual refinement |
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- Custom node configurations may need adjustment |
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## 📄 License |
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Apache 2.0 |
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## 🙏 Acknowledgments |
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Built with: |
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- [Qwen2.5-Coder](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct) |
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- [Hugging Face Transformers](https://github.com/huggingface/transformers) |
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- [PEFT](https://github.com/huggingface/peft) |
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- [Gradio](https://gradio.app) |
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