Running Applications
Running an app is the most important interaction between the user and the Pop App Center.
Whether an application is published from a workflow, imported from someone else, or downloaded from the App Marketplace, the execution process always follows the same standard flow:
Input parameters → Execute → View results → Debug logs (optional)
This chapter explains the full execution lifecycle, interface structure, and debugging methods.
1. Application Runtime Interface Structure
Since the runtime interface is built with the Layout Manager, the appearance of different apps may vary.
However, most apps share the following core components:
1. Input Area (Inputs / Form)
Used for entering required parameters, including:
- Text / number input
- Dropdown selections
- File upload
- Image upload
- JSON editor
- AI model selector
- Switches and options
Once the inputs are filled, the user can start the application.
2. Run Button (Run / Execute)
Usually located under the form or in the top-right corner.
When clicked, it:
- Starts workflow execution
- Disables input controls to prevent repeated clicks
- Displays execution status (running / success / failed)
3. Execution Status Indicators
During execution, the app may display:
| Status | Meaning |
|---|---|
| Running… | Workflow is executing |
| Success | Execution completed successfully |
| Failed | A node encountered an error |
| Stopped | Execution was manually stopped |
2. Workflow Execution Process (Behind the Scenes)
When the user clicks Run, the following happens:
- The app collects all form fields and builds a JSON object
- It sends that data to the workflow engine
- Execution begins from the first node
- Data flows between nodes step by step
- Final outputs are returned to the app
- Output widgets in the layout display the results
The whole flow is automatic — users do not need to intervene.
3. Output Display
The output display area varies depending on layout configuration. It may include:
1. Markdown Viewer
Common for:
- AI text generation
- Report-style applications
- Knowledge base responses
- Explanations and notes
2. Image Output (Image Viewer)
Used for:
- AI-generated images
- Image processing tools
- OCR results preview
3. Table Data Display
Useful for:
- Excel / CSV processing
- Data analytics workflows
4. JSON Viewer
Best for:
- Structured output
- Debug information
- API response data
Supports formatting and collapse/expand.
5. File Downloads
If any workflow node outputs a file, the UI allows direct downloading:
- PDF reports
- Excel spreadsheets
- Images
- Packaged code files
6. Custom Output Components (Advanced)
Such as:
- Charts (pie, bar, line)
- Code highlighters
- Specialized rendering components
As long as the workflow outputs the right format, the UI will display it.
4. Console and Debug Logs
The console displays advanced runtime information, including:
- Each node’s input/output
- AI request parameters and responses
- Error stack traces
- Execution time
- Debug logs
Usually displayed at the bottom or side, collapsible.
Useful for:
- Workflow developers debugging
- Users reporting issues
- Advanced users analyzing behavior
5. Troubleshooting Execution Errors
Here are common failure causes and solutions:
❌ 1. Invalid Input Fields
Examples: missing required values, wrong data type.
➡ Fix: Check required fields, numerical ranges, JSON structure.
❌ 2. AI Errors (Model issues / Invalid API Key)
Symptoms:
- AI node throws errors
- 401 / 429 / timeout
➡ Fix: Verify API key, model settings, or network conditions.
❌ 3. Unsupported File Type or Bad Format
Example: uploading an incorrect file type.
➡ Fix: Ensure the file matches supported formats.
❌ 4. Internal Workflow Node Error
The layout works, but logic fails.
➡ Fix:
Open console → locate failed node → test workflow individually.
❌ 5. AI Output Too Large to Render
Large AI responses may cause rendering issues.
➡ Fix: Reduce output length or refine prompts.
6. Runtime Interaction Behavior
During execution:
- Form inputs are temporarily disabled
- Console begins streaming logs
- Output components update dynamically
- Users may manually stop execution
- Some apps support execution history
After execution:
- Form becomes editable again
- User may adjust parameters and run again
7. Best Practices
✔ Debug the workflow before publishing as an app
Reduces runtime failures significantly.
✔ Provide default values for most fields
Improves usability and reduces user errors.
✔ Keep console hidden for normal users
Most users don’t need debug logs.
✔ Prefer structured output formats
Markdown, tables, charts, JSON improve readability.
8. Summary
Running applications is one of the core experiences in the Pop App Center.
Through input parameters, node execution, output display, and debug logs, users gain full visibility into workflow execution.
Now you understand:
- Full app execution flow
- How results are displayed
- How to inspect console logs
- How to troubleshoot common errors
- The typical structure of a runtime interface