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3896f8cad7
...
c2eecc2f7c
@ -1,212 +0,0 @@
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# Streaming UI Implementation Guide
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## What You'll See
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### ✨ Real-Time Streaming Experience
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When you click "Generate Draft" with streaming enabled, you'll see:
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1. **Instant Feedback** (< 1 second)
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- Button changes to "Streaming... (X tokens)"
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- Linear progress bar appears
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- "Live Generation" section opens automatically
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2. **Content Appears Word-by-Word**
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- HTML content streams in real-time
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- Formatted with headings, paragraphs, lists
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- Pulsing blue border indicates active streaming
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- Token counter updates live
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3. **Completion**
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- Content moves to "Generated Draft" section
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- Image placeholders detected
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- Ready for next step
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## UI Features
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### **Streaming Toggle** ⚡
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```
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☑ Stream content in real-time ⚡
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See content being generated live (much faster feedback)
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```
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- **Checked (default)**: Uses streaming API
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- **Unchecked**: Uses original non-streaming API
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### **Live Generation Section**
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- **Border**: Pulsing blue animation
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- **Auto-scroll**: Follows new content
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- **Max height**: 500px with scroll
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- **Status**: "⚡ Content is being generated in real-time..."
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### **Progress Indicator**
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- **Linear progress bar**: Animated while streaming
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- **Token counter**: "Streaming content in real-time... 234 tokens generated"
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- **Button text**: "Streaming... (234 tokens)"
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### **Error Handling**
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- Errors shown in red alert
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- Streaming stops gracefully
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- Partial content preserved
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## Visual Flow
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```
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┌─────────────────────────────────────┐
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│ Generate Draft Button │
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│ [Streaming... (234 tokens)] │
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└─────────────────────────────────────┘
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↓
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┌─────────────────────────────────────┐
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│ ▓▓▓▓▓▓▓▓░░░░░░░░░░░░░░░░░░░░ │ ← Progress bar
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│ Streaming... 234 tokens generated │
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└─────────────────────────────────────┘
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↓
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┌─────────────────────────────────────┐
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│ ▼ Live Generation │
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│ ┌───────────────────────────────┐ │
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│ │ <h2>Introduction</h2> │ │ ← Pulsing blue border
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│ │ <p>TypeScript is a...</p> │ │
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│ │ <p>It provides...</p> │ │
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│ │ <h2>Key Features</h2> │ │
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│ │ <ul><li>Type safety...</li> │ │
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│ └───────────────────────────────┘ │
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│ ⚡ Content is being generated... │
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└─────────────────────────────────────┘
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↓ (when complete)
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┌─────────────────────────────────────┐
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│ ▼ Generated Draft │
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│ ┌───────────────────────────────┐ │
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│ │ [Full content here] │ │ ← Final content
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│ └───────────────────────────────┘ │
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└─────────────────────────────────────┘
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```
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## Performance Comparison
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### Before (Non-Streaming)
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```
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Click Generate
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↓
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[Wait 60-120 seconds]
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↓
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[Spinner spinning...]
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↓
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[Still waiting...]
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↓
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Content appears all at once
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```
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**User experience**: Feels slow, no feedback
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### After (Streaming)
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```
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Click Generate
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↓
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[< 1 second]
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↓
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First words appear!
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↓
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More content streams in...
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↓
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Can start reading immediately
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↓
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Complete in same time, but feels instant
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```
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**User experience**: Feels fast, engaging, responsive
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## Code Changes
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### Component State
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```typescript
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const [streamingContent, setStreamingContent] = useState('');
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const [tokenCount, setTokenCount] = useState(0);
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const [useStreaming, setUseStreaming] = useState(true);
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```
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### Streaming Logic
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```typescript
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if (useStreaming) {
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await generateContentStream(params, {
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onStart: (data) => console.log('Started:', data.requestId),
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onContent: (data) => {
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setStreamingContent(prev => prev + data.delta);
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setTokenCount(data.tokenCount);
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},
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onDone: (data) => {
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onGeneratedDraft(data.content);
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setGenerating(false);
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},
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onError: (data) => setError(data.error),
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});
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}
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```
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## Styling Details
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### Pulsing Border Animation
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```css
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animation: pulse 2s ease-in-out infinite
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@keyframes pulse {
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0%, 100%: { borderColor: 'primary.main' }
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50%: { borderColor: 'primary.light' }
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}
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```
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### Content Formatting
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- Headings: `mt: 2, mb: 1`
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- Paragraphs: `mb: 1`
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- Lists: `pl: 3, mb: 1`
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- Max height: `500px` with `overflowY: auto`
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## Browser Compatibility
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✅ **Supported**:
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- Chrome/Edge (latest)
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- Firefox (latest)
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- Safari (latest)
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Uses standard Fetch API with ReadableStream - no special polyfills needed.
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## Testing Tips
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1. **Test with short prompt** (see instant results)
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```
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"Write a short paragraph about TypeScript"
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```
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2. **Test with long prompt** (see streaming value)
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```
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"Write a comprehensive 2000-word article about TypeScript best practices"
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```
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3. **Toggle streaming on/off** (compare experiences)
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4. **Test error handling** (disconnect network mid-stream)
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## Troubleshooting
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### Issue: Content not appearing
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**Check**: Browser console for errors
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**Fix**: Ensure API is running on port 3001
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### Issue: Streaming stops mid-way
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**Check**: Network tab for disconnection
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**Fix**: Check server logs for errors
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### Issue: Content not formatted
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**Check**: HTML is being rendered correctly
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**Fix**: Ensure `dangerouslySetInnerHTML` is used
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## Future Enhancements
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1. **Auto-scroll to bottom** as content appears
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2. **Typing sound effect** for engagement
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3. **Word count** alongside token count
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4. **Estimated time remaining** based on tokens/sec
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5. **Pause/Resume** streaming
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6. **Cancel** button with AbortController
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## Conclusion
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The streaming implementation provides a dramatically better user experience with minimal code changes. Users see content appearing within 1 second instead of waiting 60+ seconds, making the application feel much more responsive and modern.
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**Status**: ✅ Fully implemented and ready to use!
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@ -1,10 +1,9 @@
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import { useState } from 'react';
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import { useState } from 'react';
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import { Box, Stack, TextField, Typography, Button, Alert, CircularProgress, FormControlLabel, Checkbox, Link, LinearProgress } from '@mui/material';
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import { Box, Stack, TextField, Typography, Button, Alert, CircularProgress, FormControlLabel, Checkbox, Link } from '@mui/material';
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import SelectedImages from './SelectedImages';
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import SelectedImages from './SelectedImages';
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import CollapsibleSection from './CollapsibleSection';
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import CollapsibleSection from './CollapsibleSection';
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import StepHeader from './StepHeader';
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import StepHeader from './StepHeader';
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import { generateDraft } from '../../services/ai';
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import { generateDraft } from '../../services/ai';
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import { generateContentStream } from '../../services/aiStream';
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import type { Clip } from './StepAssets';
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import type { Clip } from './StepAssets';
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export default function StepGenerate({
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export default function StepGenerate({
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@ -39,9 +38,6 @@ export default function StepGenerate({
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const [generating, setGenerating] = useState(false);
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const [generating, setGenerating] = useState(false);
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const [error, setError] = useState<string>('');
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const [error, setError] = useState<string>('');
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const [useWebSearch, setUseWebSearch] = useState(false);
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const [useWebSearch, setUseWebSearch] = useState(false);
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const [streamingContent, setStreamingContent] = useState('');
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const [tokenCount, setTokenCount] = useState(0);
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const [useStreaming, setUseStreaming] = useState(true);
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return (
|
return (
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<Box sx={{ display: 'grid', gap: 2 }}>
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<Box sx={{ display: 'grid', gap: 2 }}>
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<StepHeader
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<StepHeader
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@ -97,40 +93,22 @@ export default function StepGenerate({
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minRows={4}
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minRows={4}
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placeholder="Example: Write a comprehensive technical article about building a modern blog platform. Include sections on architecture, key features, and deployment. Target audience: developers with React experience."
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placeholder="Example: Write a comprehensive technical article about building a modern blog platform. Include sections on architecture, key features, and deployment. Target audience: developers with React experience."
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/>
|
/>
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<Stack spacing={1}>
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<FormControlLabel
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<FormControlLabel
|
control={
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control={
|
<Checkbox
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<Checkbox
|
checked={useWebSearch}
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checked={useStreaming}
|
onChange={(e) => setUseWebSearch(e.target.checked)}
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onChange={(e) => setUseStreaming(e.target.checked)}
|
/>
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/>
|
}
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}
|
label={
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label={
|
<Box>
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<Box>
|
<Typography variant="body2">Research with web search (gpt-4o-mini-search)</Typography>
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<Typography variant="body2">Stream content in real-time ⚡</Typography>
|
<Typography variant="caption" color="text.secondary">
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<Typography variant="caption" color="text.secondary">
|
AI will search the internet for current information, facts, and statistics
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See content being generated live (much faster feedback)
|
</Typography>
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</Typography>
|
</Box>
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</Box>
|
}
|
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}
|
/>
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/>
|
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<FormControlLabel
|
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control={
|
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<Checkbox
|
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checked={useWebSearch}
|
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onChange={(e) => setUseWebSearch(e.target.checked)}
|
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/>
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}
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label={
|
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<Box>
|
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<Typography variant="body2">Research with web search</Typography>
|
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<Typography variant="caption" color="text.secondary">
|
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AI will search the internet for current information, facts, and statistics
|
|
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</Typography>
|
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</Box>
|
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}
|
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/>
|
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</Stack>
|
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</Stack>
|
</Stack>
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</CollapsibleSection>
|
</CollapsibleSection>
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|
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@ -146,9 +124,6 @@ export default function StepGenerate({
|
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}
|
}
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setGenerating(true);
|
setGenerating(true);
|
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setError('');
|
setError('');
|
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setStreamingContent('');
|
|
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setTokenCount(0);
|
|
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|
|
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try {
|
try {
|
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const transcriptions = postClips
|
const transcriptions = postClips
|
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.filter(c => c.transcript)
|
.filter(c => c.transcript)
|
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@ -158,47 +133,20 @@ export default function StepGenerate({
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const imageUrls = genImageKeys.map(key => `/api/media/obj?key=${encodeURIComponent(key)}`);
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const imageUrls = genImageKeys.map(key => `/api/media/obj?key=${encodeURIComponent(key)}`);
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const referenceUrls = referenceImageKeys.map(key => `/api/media/obj?key=${encodeURIComponent(key)}`);
|
const referenceUrls = referenceImageKeys.map(key => `/api/media/obj?key=${encodeURIComponent(key)}`);
|
||||||
|
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const params = {
|
const result = await generateDraft({
|
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prompt: promptText,
|
prompt: promptText,
|
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audioTranscriptions: transcriptions.length > 0 ? transcriptions : undefined,
|
audioTranscriptions: transcriptions.length > 0 ? transcriptions : undefined,
|
||||||
selectedImageUrls: imageUrls.length > 0 ? imageUrls : undefined,
|
selectedImageUrls: imageUrls.length > 0 ? imageUrls : undefined,
|
||||||
referenceImageUrls: referenceUrls.length > 0 ? referenceUrls : undefined,
|
referenceImageUrls: referenceUrls.length > 0 ? referenceUrls : undefined,
|
||||||
useWebSearch,
|
useWebSearch,
|
||||||
};
|
});
|
||||||
|
|
||||||
if (useStreaming) {
|
onGeneratedDraft(result.content);
|
||||||
// Use streaming API
|
onImagePlaceholders(result.imagePlaceholders);
|
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await generateContentStream(params, {
|
onGenerationSources(result.sources || []);
|
||||||
onStart: (data) => {
|
|
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console.log('Stream started:', data.requestId);
|
|
||||||
},
|
|
||||||
onContent: (data) => {
|
|
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setStreamingContent(prev => prev + data.delta);
|
|
||||||
setTokenCount(data.tokenCount);
|
|
||||||
},
|
|
||||||
onDone: (data) => {
|
|
||||||
console.log('Stream complete:', data.elapsedMs, 'ms');
|
|
||||||
onGeneratedDraft(data.content);
|
|
||||||
onImagePlaceholders(data.imagePlaceholders);
|
|
||||||
onGenerationSources([]);
|
|
||||||
setStreamingContent('');
|
|
||||||
setGenerating(false);
|
|
||||||
},
|
|
||||||
onError: (data) => {
|
|
||||||
setError(data.error);
|
|
||||||
setGenerating(false);
|
|
||||||
},
|
|
||||||
});
|
|
||||||
} else {
|
|
||||||
// Use non-streaming API (original)
|
|
||||||
const result = await generateDraft(params);
|
|
||||||
onGeneratedDraft(result.content);
|
|
||||||
onImagePlaceholders(result.imagePlaceholders);
|
|
||||||
onGenerationSources(result.sources || []);
|
|
||||||
setGenerating(false);
|
|
||||||
}
|
|
||||||
} catch (err: any) {
|
} catch (err: any) {
|
||||||
setError(err?.message || 'Generation failed');
|
setError(err?.message || 'Generation failed');
|
||||||
|
} finally {
|
||||||
setGenerating(false);
|
setGenerating(false);
|
||||||
}
|
}
|
||||||
}}
|
}}
|
||||||
@ -208,7 +156,7 @@ export default function StepGenerate({
|
|||||||
{generating ? (
|
{generating ? (
|
||||||
<>
|
<>
|
||||||
<CircularProgress size={20} sx={{ mr: 1 }} />
|
<CircularProgress size={20} sx={{ mr: 1 }} />
|
||||||
{useStreaming ? `Streaming... (${tokenCount} tokens)` : 'Generating Draft...'}
|
Generating Draft...
|
||||||
</>
|
</>
|
||||||
) : generatedDraft ? (
|
) : generatedDraft ? (
|
||||||
'Re-generate Draft'
|
'Re-generate Draft'
|
||||||
@ -217,45 +165,8 @@ export default function StepGenerate({
|
|||||||
)}
|
)}
|
||||||
</Button>
|
</Button>
|
||||||
{error && <Alert severity="error" sx={{ mt: 1 }}>{error}</Alert>}
|
{error && <Alert severity="error" sx={{ mt: 1 }}>{error}</Alert>}
|
||||||
{generating && useStreaming && (
|
|
||||||
<Box sx={{ mt: 2 }}>
|
|
||||||
<LinearProgress />
|
|
||||||
<Typography variant="caption" sx={{ color: 'text.secondary', mt: 0.5, display: 'block' }}>
|
|
||||||
Streaming content in real-time... {tokenCount} tokens generated
|
|
||||||
</Typography>
|
|
||||||
</Box>
|
|
||||||
)}
|
|
||||||
</Box>
|
</Box>
|
||||||
|
|
||||||
{/* Streaming Content Display (while generating) */}
|
|
||||||
{generating && useStreaming && streamingContent && (
|
|
||||||
<CollapsibleSection title="Live Generation" defaultCollapsed={false}>
|
|
||||||
<Box
|
|
||||||
sx={{
|
|
||||||
p: 2,
|
|
||||||
border: '2px solid',
|
|
||||||
borderColor: 'primary.main',
|
|
||||||
borderRadius: 1,
|
|
||||||
bgcolor: 'background.paper',
|
|
||||||
maxHeight: '500px',
|
|
||||||
overflowY: 'auto',
|
|
||||||
'& h2, & h3': { mt: 2, mb: 1 },
|
|
||||||
'& p': { mb: 1 },
|
|
||||||
'& ul, & ol': { pl: 3, mb: 1 },
|
|
||||||
animation: 'pulse 2s ease-in-out infinite',
|
|
||||||
'@keyframes pulse': {
|
|
||||||
'0%, 100%': { borderColor: 'primary.main' },
|
|
||||||
'50%': { borderColor: 'primary.light' },
|
|
||||||
},
|
|
||||||
}}
|
|
||||||
dangerouslySetInnerHTML={{ __html: streamingContent }}
|
|
||||||
/>
|
|
||||||
<Typography variant="caption" sx={{ color: 'primary.main', mt: 1, display: 'block', fontWeight: 'bold' }}>
|
|
||||||
⚡ Content is being generated in real-time...
|
|
||||||
</Typography>
|
|
||||||
</CollapsibleSection>
|
|
||||||
)}
|
|
||||||
|
|
||||||
{/* Generated Content Display */}
|
{/* Generated Content Display */}
|
||||||
{generatedDraft && (
|
{generatedDraft && (
|
||||||
<CollapsibleSection title="Generated Draft">
|
<CollapsibleSection title="Generated Draft">
|
||||||
|
|||||||
@ -1,169 +0,0 @@
|
|||||||
/**
|
|
||||||
* AI Streaming Service
|
|
||||||
* Handles Server-Sent Events streaming from the AI generation endpoint
|
|
||||||
*/
|
|
||||||
|
|
||||||
export interface StreamCallbacks {
|
|
||||||
onStart?: (data: { requestId: string }) => void;
|
|
||||||
onContent?: (data: { delta: string; tokenCount: number }) => void;
|
|
||||||
onDone?: (data: {
|
|
||||||
content: string;
|
|
||||||
imagePlaceholders: string[];
|
|
||||||
tokenCount: number;
|
|
||||||
model: string;
|
|
||||||
requestId: string;
|
|
||||||
elapsedMs: number;
|
|
||||||
}) => void;
|
|
||||||
onError?: (data: { error: string; requestId?: string; elapsedMs?: number }) => void;
|
|
||||||
}
|
|
||||||
|
|
||||||
export interface GenerateStreamParams {
|
|
||||||
prompt: string;
|
|
||||||
audioTranscriptions?: string[];
|
|
||||||
selectedImageUrls?: string[];
|
|
||||||
referenceImageUrls?: string[];
|
|
||||||
useWebSearch?: boolean;
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Generate AI content with streaming
|
|
||||||
*/
|
|
||||||
export async function generateContentStream(
|
|
||||||
params: GenerateStreamParams,
|
|
||||||
callbacks: StreamCallbacks
|
|
||||||
): Promise<void> {
|
|
||||||
const response = await fetch('http://localhost:3001/api/ai/generate-stream', {
|
|
||||||
method: 'POST',
|
|
||||||
headers: {
|
|
||||||
'Content-Type': 'application/json',
|
|
||||||
},
|
|
||||||
body: JSON.stringify(params),
|
|
||||||
});
|
|
||||||
|
|
||||||
if (!response.ok) {
|
|
||||||
throw new Error(`HTTP error! status: ${response.status}`);
|
|
||||||
}
|
|
||||||
|
|
||||||
if (!response.body) {
|
|
||||||
throw new Error('Response body is null');
|
|
||||||
}
|
|
||||||
|
|
||||||
const reader = response.body.getReader();
|
|
||||||
const decoder = new TextDecoder();
|
|
||||||
let buffer = '';
|
|
||||||
|
|
||||||
try {
|
|
||||||
while (true) {
|
|
||||||
const { done, value } = await reader.read();
|
|
||||||
|
|
||||||
if (done) {
|
|
||||||
break;
|
|
||||||
}
|
|
||||||
|
|
||||||
// Decode chunk and add to buffer
|
|
||||||
buffer += decoder.decode(value, { stream: true });
|
|
||||||
|
|
||||||
// Process complete messages (separated by \n\n)
|
|
||||||
const messages = buffer.split('\n\n');
|
|
||||||
buffer = messages.pop() || ''; // Keep incomplete message in buffer
|
|
||||||
|
|
||||||
for (const message of messages) {
|
|
||||||
if (!message.trim() || !message.startsWith('data: ')) {
|
|
||||||
continue;
|
|
||||||
}
|
|
||||||
|
|
||||||
try {
|
|
||||||
const data = JSON.parse(message.slice(6)); // Remove 'data: ' prefix
|
|
||||||
|
|
||||||
switch (data.type) {
|
|
||||||
case 'start':
|
|
||||||
callbacks.onStart?.(data);
|
|
||||||
break;
|
|
||||||
|
|
||||||
case 'content':
|
|
||||||
callbacks.onContent?.(data);
|
|
||||||
break;
|
|
||||||
|
|
||||||
case 'done':
|
|
||||||
callbacks.onDone?.(data);
|
|
||||||
break;
|
|
||||||
|
|
||||||
case 'error':
|
|
||||||
callbacks.onError?.(data);
|
|
||||||
break;
|
|
||||||
}
|
|
||||||
} catch (err) {
|
|
||||||
console.error('Failed to parse SSE message:', message, err);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
} finally {
|
|
||||||
reader.releaseLock();
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* React hook for streaming AI generation
|
|
||||||
*/
|
|
||||||
export function useAIStream() {
|
|
||||||
const [isStreaming, setIsStreaming] = React.useState(false);
|
|
||||||
const [content, setContent] = React.useState('');
|
|
||||||
const [error, setError] = React.useState<string | null>(null);
|
|
||||||
const [metadata, setMetadata] = React.useState<{
|
|
||||||
imagePlaceholders: string[];
|
|
||||||
tokenCount: number;
|
|
||||||
model: string;
|
|
||||||
requestId: string;
|
|
||||||
elapsedMs: number;
|
|
||||||
} | null>(null);
|
|
||||||
|
|
||||||
const generate = async (params: GenerateStreamParams) => {
|
|
||||||
setIsStreaming(true);
|
|
||||||
setContent('');
|
|
||||||
setError(null);
|
|
||||||
setMetadata(null);
|
|
||||||
|
|
||||||
try {
|
|
||||||
await generateContentStream(params, {
|
|
||||||
onStart: (data) => {
|
|
||||||
console.log('Stream started:', data.requestId);
|
|
||||||
},
|
|
||||||
|
|
||||||
onContent: (data) => {
|
|
||||||
setContent((prev) => prev + data.delta);
|
|
||||||
},
|
|
||||||
|
|
||||||
onDone: (data) => {
|
|
||||||
setContent(data.content);
|
|
||||||
setMetadata({
|
|
||||||
imagePlaceholders: data.imagePlaceholders,
|
|
||||||
tokenCount: data.tokenCount,
|
|
||||||
model: data.model,
|
|
||||||
requestId: data.requestId,
|
|
||||||
elapsedMs: data.elapsedMs,
|
|
||||||
});
|
|
||||||
setIsStreaming(false);
|
|
||||||
},
|
|
||||||
|
|
||||||
onError: (data) => {
|
|
||||||
setError(data.error);
|
|
||||||
setIsStreaming(false);
|
|
||||||
},
|
|
||||||
});
|
|
||||||
} catch (err) {
|
|
||||||
setError(err instanceof Error ? err.message : 'Unknown error');
|
|
||||||
setIsStreaming(false);
|
|
||||||
}
|
|
||||||
};
|
|
||||||
|
|
||||||
return {
|
|
||||||
generate,
|
|
||||||
isStreaming,
|
|
||||||
content,
|
|
||||||
error,
|
|
||||||
metadata,
|
|
||||||
};
|
|
||||||
}
|
|
||||||
|
|
||||||
// Add React import for the hook
|
|
||||||
import React from 'react';
|
|
||||||
@ -1,192 +0,0 @@
|
|||||||
# AI Generate Refactoring Summary
|
|
||||||
|
|
||||||
## Overview
|
|
||||||
Refactored `src/ai-generate.ts` (453 lines) into a clean, maintainable architecture with proper separation of concerns.
|
|
||||||
|
|
||||||
## New Structure
|
|
||||||
|
|
||||||
```
|
|
||||||
apps/api/src/
|
|
||||||
├── routes/
|
|
||||||
│ └── ai.routes.ts # 85 lines - Clean route handlers
|
|
||||||
├── services/
|
|
||||||
│ ├── ai/
|
|
||||||
│ │ ├── AIService.ts # 48 lines - Main orchestrator
|
|
||||||
│ │ ├── contentGenerator.ts # 145 lines - Content generation
|
|
||||||
│ │ ├── metadataGenerator.ts # 63 lines - Metadata generation
|
|
||||||
│ │ └── altTextGenerator.ts # 88 lines - Alt text generation
|
|
||||||
│ └── openai/
|
|
||||||
│ └── client.ts # 36 lines - Singleton client
|
|
||||||
├── utils/
|
|
||||||
│ ├── imageUtils.ts # 65 lines - Image utilities
|
|
||||||
│ ├── contextBuilder.ts # 59 lines - Context building
|
|
||||||
│ ├── responseParser.ts # 63 lines - Response parsing
|
|
||||||
│ └── errorHandler.ts # 60 lines - Error handling
|
|
||||||
├── types/
|
|
||||||
│ └── ai.types.ts # 87 lines - Type definitions
|
|
||||||
└── config/
|
|
||||||
└── prompts.ts # 104 lines - Prompt templates
|
|
||||||
```
|
|
||||||
|
|
||||||
## Benefits Achieved
|
|
||||||
|
|
||||||
### ✅ Maintainability
|
|
||||||
- **Before**: 453 lines in one file
|
|
||||||
- **After**: 12 focused files, largest is 145 lines
|
|
||||||
- Each module has a single, clear responsibility
|
|
||||||
- Easy to locate and fix bugs
|
|
||||||
|
|
||||||
### ✅ Testability
|
|
||||||
- Service methods can be unit tested independently
|
|
||||||
- Utilities can be tested in isolation
|
|
||||||
- OpenAI client can be easily mocked
|
|
||||||
- Clear interfaces for all components
|
|
||||||
|
|
||||||
### ✅ Reusability
|
|
||||||
- Utils can be used across different endpoints
|
|
||||||
- Service can be used outside routes (CLI, jobs, etc.)
|
|
||||||
- Prompts centralized and easy to modify
|
|
||||||
- Image handling logic shared
|
|
||||||
|
|
||||||
### ✅ Type Safety
|
|
||||||
- Full TypeScript coverage with explicit interfaces
|
|
||||||
- Request/response types defined
|
|
||||||
- Compile-time error detection
|
|
||||||
- Better IDE autocomplete and refactoring support
|
|
||||||
|
|
||||||
### ✅ Error Handling
|
|
||||||
- Centralized error handling with consistent format
|
|
||||||
- Detailed logging with request IDs
|
|
||||||
- Debug mode for development
|
|
||||||
- Structured error responses
|
|
||||||
|
|
||||||
## Key Improvements
|
|
||||||
|
|
||||||
### 1. **Separation of Concerns**
|
|
||||||
- **Routes**: Only handle HTTP request/response
|
|
||||||
- **Services**: Business logic and AI orchestration
|
|
||||||
- **Utils**: Reusable helper functions
|
|
||||||
- **Config**: Static configuration and prompts
|
|
||||||
- **Types**: Type definitions and interfaces
|
|
||||||
|
|
||||||
### 2. **OpenAI Client Singleton**
|
|
||||||
- Single instance with optimized configuration
|
|
||||||
- 10-minute timeout for long requests
|
|
||||||
- 2 retry attempts for transient failures
|
|
||||||
- Shared across all AI operations
|
|
||||||
|
|
||||||
### 3. **Specialized Generators**
|
|
||||||
- `ContentGenerator`: Handles gpt-5-2025-08-07 with Chat Completions API
|
|
||||||
- `MetadataGenerator`: Handles gpt-5-2025-08-07 for metadata
|
|
||||||
- `AltTextGenerator`: Handles gpt-5-2025-08-07 for accessibility
|
|
||||||
|
|
||||||
### 4. **Utility Functions**
|
|
||||||
- `imageUtils`: Presigned URLs, format validation, placeholder extraction
|
|
||||||
- `contextBuilder`: Build context from transcriptions and images
|
|
||||||
- `responseParser`: Parse AI responses, strip HTML, handle JSON
|
|
||||||
- `errorHandler`: Consistent error logging and responses
|
|
||||||
|
|
||||||
### 5. **Request Tracking**
|
|
||||||
- Every request gets a unique UUID
|
|
||||||
- Logs include request ID for correlation
|
|
||||||
- Elapsed time tracking
|
|
||||||
- Detailed error context
|
|
||||||
|
|
||||||
## Migration Status
|
|
||||||
|
|
||||||
### ✅ Completed
|
|
||||||
- [x] Type definitions
|
|
||||||
- [x] Configuration extraction
|
|
||||||
- [x] Utility functions
|
|
||||||
- [x] OpenAI client singleton
|
|
||||||
- [x] Service layer implementation
|
|
||||||
- [x] Route handlers refactored
|
|
||||||
- [x] TypeScript compilation verified
|
|
||||||
|
|
||||||
### 🔄 Active
|
|
||||||
- New routes active at `/api/ai/*`
|
|
||||||
- Old `ai-generate.ts` kept as backup (commented out)
|
|
||||||
|
|
||||||
### 📋 Next Steps
|
|
||||||
1. **Test all endpoints**:
|
|
||||||
- POST `/api/ai/generate`
|
|
||||||
- POST `/api/ai/generate-metadata`
|
|
||||||
- POST `/api/ai/generate-alt-text`
|
|
||||||
|
|
||||||
2. **Verify functionality**:
|
|
||||||
- Content generation with reference images
|
|
||||||
- Metadata generation from HTML
|
|
||||||
- Alt text with and without captions
|
|
||||||
- Error handling and logging
|
|
||||||
|
|
||||||
3. **Remove old code** (after validation):
|
|
||||||
- Delete `src/ai-generate.ts`
|
|
||||||
- Remove commented import in `index.ts`
|
|
||||||
|
|
||||||
## Testing Commands
|
|
||||||
|
|
||||||
```bash
|
|
||||||
# Start API server
|
|
||||||
cd apps/api
|
|
||||||
pnpm run dev
|
|
||||||
|
|
||||||
# Test content generation
|
|
||||||
curl -X POST http://localhost:3001/api/ai/generate \
|
|
||||||
-H "Content-Type: application/json" \
|
|
||||||
-d '{"prompt": "Write about TypeScript best practices"}'
|
|
||||||
|
|
||||||
# Test metadata generation
|
|
||||||
curl -X POST http://localhost:3001/api/ai/generate-metadata \
|
|
||||||
-H "Content-Type: application/json" \
|
|
||||||
-d '{"contentHtml": "<h1>Test Article</h1><p>Content here</p>"}'
|
|
||||||
|
|
||||||
# Test alt text generation
|
|
||||||
curl -X POST http://localhost:3001/api/ai/generate-alt-text \
|
|
||||||
-H "Content-Type: application/json" \
|
|
||||||
-d '{"placeholderDescription": "dashboard_screenshot"}'
|
|
||||||
```
|
|
||||||
|
|
||||||
## Rollback Plan
|
|
||||||
|
|
||||||
If issues arise, rollback is simple:
|
|
||||||
|
|
||||||
1. Edit `src/index.ts`:
|
|
||||||
```typescript
|
|
||||||
// Comment out new routes
|
|
||||||
// app.use('/api/ai', aiRoutesNew);
|
|
||||||
|
|
||||||
// Uncomment old routes
|
|
||||||
app.use('/api/ai', aiGenerateRouter);
|
|
||||||
```
|
|
||||||
|
|
||||||
2. Restart server
|
|
||||||
|
|
||||||
3. Old functionality restored immediately
|
|
||||||
|
|
||||||
## File Size Comparison
|
|
||||||
|
|
||||||
| Metric | Before | After |
|
|
||||||
|--------|--------|-------|
|
|
||||||
| Single file | 453 lines | - |
|
|
||||||
| Largest file | 453 lines | 145 lines |
|
|
||||||
| Total files | 1 | 12 |
|
|
||||||
| Average file size | 453 lines | ~70 lines |
|
|
||||||
| Cyclomatic complexity | High | Low |
|
|
||||||
|
|
||||||
## Code Quality Metrics
|
|
||||||
|
|
||||||
- ✅ Single Responsibility Principle
|
|
||||||
- ✅ Dependency Injection ready
|
|
||||||
- ✅ Easy to mock for testing
|
|
||||||
- ✅ Clear module boundaries
|
|
||||||
- ✅ Consistent error handling
|
|
||||||
- ✅ Comprehensive logging
|
|
||||||
- ✅ Type-safe throughout
|
|
||||||
|
|
||||||
## Conclusion
|
|
||||||
|
|
||||||
The refactoring successfully transformed a complex 453-line file into a clean, maintainable architecture with 12 focused modules. Each component has a clear purpose, is independently testable, and follows TypeScript best practices.
|
|
||||||
|
|
||||||
**Status**: ✅ Ready for testing
|
|
||||||
**Risk**: Low (old code preserved for easy rollback)
|
|
||||||
**Impact**: High (significantly improved maintainability)
|
|
||||||
@ -1,301 +0,0 @@
|
|||||||
# AI Content Streaming Guide
|
|
||||||
|
|
||||||
## Overview
|
|
||||||
|
|
||||||
Implemented Server-Sent Events (SSE) streaming for AI content generation to provide real-time feedback during long article generation.
|
|
||||||
|
|
||||||
## Architecture
|
|
||||||
|
|
||||||
### Backend (API)
|
|
||||||
|
|
||||||
**New Files:**
|
|
||||||
- `services/ai/contentGeneratorStream.ts` - Streaming content generator
|
|
||||||
- Updated `routes/ai.routes.ts` - Added `/api/ai/generate-stream` endpoint
|
|
||||||
|
|
||||||
**How It Works:**
|
|
||||||
1. Client sends POST request to `/api/ai/generate-stream`
|
|
||||||
2. Server sets up SSE headers (`text/event-stream`)
|
|
||||||
3. OpenAI streaming API sends chunks as they're generated
|
|
||||||
4. Server forwards each chunk to client via SSE
|
|
||||||
5. Client receives real-time updates
|
|
||||||
|
|
||||||
### Frontend (Admin)
|
|
||||||
|
|
||||||
**New Files:**
|
|
||||||
- `services/aiStream.ts` - Streaming utilities and React hook
|
|
||||||
|
|
||||||
**React Hook:**
|
|
||||||
```typescript
|
|
||||||
const { generate, isStreaming, content, error, metadata } = useAIStream();
|
|
||||||
```
|
|
||||||
|
|
||||||
## API Endpoints
|
|
||||||
|
|
||||||
### Non-Streaming (Original)
|
|
||||||
```
|
|
||||||
POST /api/ai/generate
|
|
||||||
```
|
|
||||||
- Returns complete response after generation finishes
|
|
||||||
- Good for: Short content, background jobs
|
|
||||||
- Response: JSON with full content
|
|
||||||
|
|
||||||
### Streaming (New)
|
|
||||||
```
|
|
||||||
POST /api/ai/generate-stream
|
|
||||||
```
|
|
||||||
- Returns chunks as they're generated
|
|
||||||
- Good for: Long articles, real-time UI updates
|
|
||||||
- Response: Server-Sent Events stream
|
|
||||||
|
|
||||||
## SSE Event Types
|
|
||||||
|
|
||||||
### 1. `start`
|
|
||||||
Sent when streaming begins
|
|
||||||
```json
|
|
||||||
{
|
|
||||||
"type": "start",
|
|
||||||
"requestId": "uuid"
|
|
||||||
}
|
|
||||||
```
|
|
||||||
|
|
||||||
### 2. `content`
|
|
||||||
Sent for each content chunk
|
|
||||||
```json
|
|
||||||
{
|
|
||||||
"type": "content",
|
|
||||||
"delta": "text chunk",
|
|
||||||
"tokenCount": 42
|
|
||||||
}
|
|
||||||
```
|
|
||||||
|
|
||||||
### 3. `done`
|
|
||||||
Sent when generation completes
|
|
||||||
```json
|
|
||||||
{
|
|
||||||
"type": "done",
|
|
||||||
"content": "full content",
|
|
||||||
"imagePlaceholders": ["placeholder1", "placeholder2"],
|
|
||||||
"tokenCount": 1234,
|
|
||||||
"model": "gpt-5-2025-08-07",
|
|
||||||
"requestId": "uuid",
|
|
||||||
"elapsedMs": 45000
|
|
||||||
}
|
|
||||||
```
|
|
||||||
|
|
||||||
### 4. `error`
|
|
||||||
Sent if an error occurs
|
|
||||||
```json
|
|
||||||
{
|
|
||||||
"type": "error",
|
|
||||||
"error": "error message",
|
|
||||||
"requestId": "uuid",
|
|
||||||
"elapsedMs": 1000
|
|
||||||
}
|
|
||||||
```
|
|
||||||
|
|
||||||
## Frontend Usage
|
|
||||||
|
|
||||||
### Option 1: React Hook (Recommended)
|
|
||||||
|
|
||||||
```typescript
|
|
||||||
import { useAIStream } from '@/services/aiStream';
|
|
||||||
|
|
||||||
function MyComponent() {
|
|
||||||
const { generate, isStreaming, content, error, metadata } = useAIStream();
|
|
||||||
|
|
||||||
const handleGenerate = async () => {
|
|
||||||
await generate({
|
|
||||||
prompt: 'Write about TypeScript',
|
|
||||||
selectedImageUrls: [],
|
|
||||||
referenceImageUrls: [],
|
|
||||||
});
|
|
||||||
};
|
|
||||||
|
|
||||||
return (
|
|
||||||
<div>
|
|
||||||
<button onClick={handleGenerate} disabled={isStreaming}>
|
|
||||||
Generate
|
|
||||||
</button>
|
|
||||||
|
|
||||||
{isStreaming && <p>Generating...</p>}
|
|
||||||
|
|
||||||
<div>{content}</div>
|
|
||||||
|
|
||||||
{error && <p>Error: {error}</p>}
|
|
||||||
|
|
||||||
{metadata && (
|
|
||||||
<p>
|
|
||||||
Generated {metadata.tokenCount} tokens in {metadata.elapsedMs}ms
|
|
||||||
</p>
|
|
||||||
)}
|
|
||||||
</div>
|
|
||||||
);
|
|
||||||
}
|
|
||||||
```
|
|
||||||
|
|
||||||
### Option 2: Direct Function Call
|
|
||||||
|
|
||||||
```typescript
|
|
||||||
import { generateContentStream } from '@/services/aiStream';
|
|
||||||
|
|
||||||
await generateContentStream(
|
|
||||||
{
|
|
||||||
prompt: 'Write about TypeScript',
|
|
||||||
},
|
|
||||||
{
|
|
||||||
onStart: (data) => {
|
|
||||||
console.log('Started:', data.requestId);
|
|
||||||
},
|
|
||||||
|
|
||||||
onContent: (data) => {
|
|
||||||
// Append delta to UI
|
|
||||||
appendToEditor(data.delta);
|
|
||||||
},
|
|
||||||
|
|
||||||
onDone: (data) => {
|
|
||||||
console.log('Done!', data.elapsedMs, 'ms');
|
|
||||||
setImagePlaceholders(data.imagePlaceholders);
|
|
||||||
},
|
|
||||||
|
|
||||||
onError: (data) => {
|
|
||||||
showError(data.error);
|
|
||||||
},
|
|
||||||
}
|
|
||||||
);
|
|
||||||
```
|
|
||||||
|
|
||||||
## Benefits
|
|
||||||
|
|
||||||
### 1. **Immediate Feedback**
|
|
||||||
- Users see content being generated in real-time
|
|
||||||
- No more waiting for 2+ minutes with no feedback
|
|
||||||
|
|
||||||
### 2. **Better UX**
|
|
||||||
- Progress indication
|
|
||||||
- Can stop/cancel if needed
|
|
||||||
- Feels more responsive
|
|
||||||
|
|
||||||
### 3. **Lower Perceived Latency**
|
|
||||||
- Users can start reading while generation continues
|
|
||||||
- Time-to-first-byte is much faster
|
|
||||||
|
|
||||||
### 4. **Resilience**
|
|
||||||
- If connection drops, partial content is preserved
|
|
||||||
- Can implement retry logic
|
|
||||||
|
|
||||||
## Performance Comparison
|
|
||||||
|
|
||||||
| Metric | Non-Streaming | Streaming |
|
|
||||||
|--------|---------------|-----------|
|
|
||||||
| Time to first content | 60-120s | <1s |
|
|
||||||
| User feedback | None until done | Real-time |
|
|
||||||
| Memory usage | Full response buffered | Chunks processed |
|
|
||||||
| Cancellable | No | Yes |
|
|
||||||
| Perceived speed | Slow | Fast |
|
|
||||||
|
|
||||||
## Implementation Notes
|
|
||||||
|
|
||||||
### Backend
|
|
||||||
- Uses OpenAI's native streaming API
|
|
||||||
- Forwards chunks without buffering
|
|
||||||
- Handles client disconnection gracefully
|
|
||||||
- Logs request ID for debugging
|
|
||||||
|
|
||||||
### Frontend
|
|
||||||
- Uses Fetch API with ReadableStream
|
|
||||||
- Parses SSE format (`data: {...}\n\n`)
|
|
||||||
- Handles partial messages in buffer
|
|
||||||
- TypeScript types for all events
|
|
||||||
|
|
||||||
## Testing
|
|
||||||
|
|
||||||
### Test Streaming Endpoint
|
|
||||||
|
|
||||||
```bash
|
|
||||||
curl -N -X POST http://localhost:3001/api/ai/generate-stream \
|
|
||||||
-H "Content-Type: application/json" \
|
|
||||||
-d '{"prompt": "Write a short article about TypeScript"}'
|
|
||||||
```
|
|
||||||
|
|
||||||
You should see events streaming in real-time:
|
|
||||||
```
|
|
||||||
data: {"type":"start","requestId":"..."}
|
|
||||||
|
|
||||||
data: {"type":"content","delta":"TypeScript","tokenCount":1}
|
|
||||||
|
|
||||||
data: {"type":"content","delta":" is a","tokenCount":2}
|
|
||||||
|
|
||||||
...
|
|
||||||
|
|
||||||
data: {"type":"done","content":"...","imagePlaceholders":[],...}
|
|
||||||
```
|
|
||||||
|
|
||||||
## Migration Path
|
|
||||||
|
|
||||||
### Phase 1: Add Streaming (Current)
|
|
||||||
- ✅ New `/generate-stream` endpoint
|
|
||||||
- ✅ Keep old `/generate` endpoint
|
|
||||||
- Both work in parallel
|
|
||||||
|
|
||||||
### Phase 2: Update Frontend
|
|
||||||
- Update UI components to use streaming
|
|
||||||
- Add loading states and progress indicators
|
|
||||||
- Test thoroughly
|
|
||||||
|
|
||||||
### Phase 3: Switch Default
|
|
||||||
- Make streaming the default
|
|
||||||
- Keep non-streaming for background jobs
|
|
||||||
|
|
||||||
### Phase 4: Optional Cleanup
|
|
||||||
- Consider deprecating non-streaming endpoint
|
|
||||||
- Or keep both for different use cases
|
|
||||||
|
|
||||||
## Troubleshooting
|
|
||||||
|
|
||||||
### Issue: Stream Stops Mid-Generation
|
|
||||||
**Cause:** Client disconnected or timeout
|
|
||||||
**Solution:** Check network, increase timeout, add reconnection logic
|
|
||||||
|
|
||||||
### Issue: Chunks Arrive Out of Order
|
|
||||||
**Cause:** Not possible with SSE (ordered by design)
|
|
||||||
**Solution:** N/A
|
|
||||||
|
|
||||||
### Issue: Memory Leak
|
|
||||||
**Cause:** Not releasing reader lock
|
|
||||||
**Solution:** Use `finally` block to release (already implemented)
|
|
||||||
|
|
||||||
### Issue: CORS Errors
|
|
||||||
**Cause:** SSE requires proper CORS headers
|
|
||||||
**Solution:** Ensure `Access-Control-Allow-Origin` is set
|
|
||||||
|
|
||||||
## Future Enhancements
|
|
||||||
|
|
||||||
1. **Cancellation**
|
|
||||||
- Add abort controller
|
|
||||||
- Send cancel signal to server
|
|
||||||
- Clean up OpenAI stream
|
|
||||||
|
|
||||||
2. **Reconnection**
|
|
||||||
- Store last received token count
|
|
||||||
- Resume from last position on disconnect
|
|
||||||
|
|
||||||
3. **Progress Bar**
|
|
||||||
- Estimate total tokens
|
|
||||||
- Show percentage complete
|
|
||||||
|
|
||||||
4. **Chunk Size Control**
|
|
||||||
- Batch small chunks for efficiency
|
|
||||||
- Configurable chunk size
|
|
||||||
|
|
||||||
5. **WebSocket Alternative**
|
|
||||||
- Bidirectional communication
|
|
||||||
- Better for interactive features
|
|
||||||
|
|
||||||
## Conclusion
|
|
||||||
|
|
||||||
Streaming provides a significantly better user experience for long-running AI generation tasks. The implementation is production-ready and backward-compatible with existing code.
|
|
||||||
|
|
||||||
**Status**: ✅ Ready to use
|
|
||||||
**Endpoints**:
|
|
||||||
- `/api/ai/generate` (non-streaming)
|
|
||||||
- `/api/ai/generate-stream` (streaming)
|
|
||||||
@ -1,92 +0,0 @@
|
|||||||
export const CONTENT_GENERATION_PROMPT = `You are an expert content writer creating high-quality, comprehensive blog articles for Ghost CMS.
|
|
||||||
|
|
||||||
CRITICAL REQUIREMENTS:
|
|
||||||
1. Generate production-ready HTML content that can be published directly to Ghost
|
|
||||||
2. Use semantic HTML5 tags: <h2>, <h3>, <p>, <ul>, <ol>, <blockquote>, <strong>, <em>
|
|
||||||
3. For images, use this EXACT placeholder format: {{IMAGE:description_of_image}}
|
|
||||||
- Example: {{IMAGE:screenshot_of_dashboard}}
|
|
||||||
- Example: {{IMAGE:team_photo_at_conference}}
|
|
||||||
- Use descriptive, snake_case names that indicate what the image should show
|
|
||||||
4. Structure articles with clear sections using headings
|
|
||||||
5. Write engaging, SEO-friendly content with natural keyword integration
|
|
||||||
6. Include a compelling introduction and conclusion
|
|
||||||
7. Use lists and formatting to improve readability
|
|
||||||
8. Do NOT include <html>, <head>, <body> tags - only the article content
|
|
||||||
9. Do NOT use markdown - use HTML tags only
|
|
||||||
10. Ensure all HTML is valid and properly closed
|
|
||||||
|
|
||||||
CONTENT LENGTH:
|
|
||||||
- Write COMPREHENSIVE, IN-DEPTH articles (aim for 1500-3000+ words)
|
|
||||||
- Don't rush or summarize - provide detailed explanations, examples, and insights
|
|
||||||
- Cover topics thoroughly with multiple sections and subsections
|
|
||||||
- Include practical examples, use cases, and actionable advice
|
|
||||||
- Write as if you're creating a definitive guide on the topic
|
|
||||||
|
|
||||||
OUTPUT FORMAT:
|
|
||||||
Return only the HTML content, ready to be inserted into Ghost's content editor.`;
|
|
||||||
|
|
||||||
export const METADATA_GENERATION_PROMPT = `You are an SEO expert. Generate metadata for blog posts.
|
|
||||||
|
|
||||||
REQUIREMENTS:
|
|
||||||
1. Title: Compelling, SEO-friendly, 50-60 characters
|
|
||||||
2. Tags: 3-5 relevant tags, comma-separated
|
|
||||||
3. Canonical URL: SEO-friendly slug based on title (lowercase, hyphens, no special chars)
|
|
||||||
|
|
||||||
OUTPUT FORMAT (JSON):
|
|
||||||
{
|
|
||||||
"title": "Your Compelling Title Here",
|
|
||||||
"tags": "tag1, tag2, tag3",
|
|
||||||
"canonicalUrl": "your-seo-friendly-slug"
|
|
||||||
}
|
|
||||||
|
|
||||||
Return ONLY valid JSON, no markdown, no explanation.`;
|
|
||||||
|
|
||||||
export const ALT_TEXT_WITH_CAPTION_PROMPT = `You are an accessibility and SEO expert. Generate alt text AND caption for images.
|
|
||||||
|
|
||||||
REQUIREMENTS:
|
|
||||||
Alt Text:
|
|
||||||
- Descriptive and specific (50-125 characters)
|
|
||||||
- Include relevant keywords naturally
|
|
||||||
- Describe what's IN the image, not around it
|
|
||||||
- Don't start with "Image of" or "Picture of"
|
|
||||||
- Concise but informative
|
|
||||||
|
|
||||||
Caption:
|
|
||||||
- Engaging and contextual (1-2 sentences)
|
|
||||||
- Add value beyond the alt text
|
|
||||||
- Can include context, explanation, or insight
|
|
||||||
- SEO-friendly with natural keywords
|
|
||||||
- Reader-friendly and informative
|
|
||||||
|
|
||||||
OUTPUT FORMAT (JSON):
|
|
||||||
{
|
|
||||||
"altText": "Your alt text here",
|
|
||||||
"caption": "Your engaging caption here"
|
|
||||||
}
|
|
||||||
|
|
||||||
EXAMPLES:
|
|
||||||
Input: "dashboard_screenshot"
|
|
||||||
Output: {
|
|
||||||
"altText": "Analytics dashboard showing user engagement metrics and conversion rates",
|
|
||||||
"caption": "Our analytics platform provides real-time insights into user behavior and conversion patterns."
|
|
||||||
}
|
|
||||||
|
|
||||||
Input: "team_photo"
|
|
||||||
Output: {
|
|
||||||
"altText": "Development team collaborating in modern office space",
|
|
||||||
"caption": "The engineering team during our quarterly planning session, where we align on product roadmap priorities."
|
|
||||||
}
|
|
||||||
|
|
||||||
Return ONLY valid JSON, no markdown, no explanation.`;
|
|
||||||
|
|
||||||
export const ALT_TEXT_ONLY_PROMPT = `You are an accessibility and SEO expert. Generate descriptive alt text for images.
|
|
||||||
|
|
||||||
REQUIREMENTS:
|
|
||||||
1. Be descriptive and specific (50-125 characters ideal)
|
|
||||||
2. Include relevant keywords naturally
|
|
||||||
3. Describe what's IN the image, not around it
|
|
||||||
4. Don't start with "Image of" or "Picture of"
|
|
||||||
5. Be concise but informative
|
|
||||||
6. Consider the article context
|
|
||||||
|
|
||||||
Return ONLY the alt text, no quotes, no explanation.`;
|
|
||||||
@ -11,7 +11,6 @@ import draftsRouter from './drafts';
|
|||||||
import postsRouter from './posts';
|
import postsRouter from './posts';
|
||||||
import ghostRouter from './ghost';
|
import ghostRouter from './ghost';
|
||||||
import aiGenerateRouter from './ai-generate';
|
import aiGenerateRouter from './ai-generate';
|
||||||
import aiRoutesNew from './routes/ai.routes';
|
|
||||||
import settingsRouter from './settings';
|
import settingsRouter from './settings';
|
||||||
|
|
||||||
const app = express();
|
const app = express();
|
||||||
@ -32,10 +31,7 @@ app.use('/api/stt', sttRouter);
|
|||||||
app.use('/api/drafts', draftsRouter);
|
app.use('/api/drafts', draftsRouter);
|
||||||
app.use('/api/posts', postsRouter);
|
app.use('/api/posts', postsRouter);
|
||||||
app.use('/api/ghost', ghostRouter);
|
app.use('/api/ghost', ghostRouter);
|
||||||
// Use new refactored AI routes
|
app.use('/api/ai', aiGenerateRouter);
|
||||||
app.use('/api/ai', aiRoutesNew);
|
|
||||||
// Keep old routes temporarily for backward compatibility (can remove after testing)
|
|
||||||
// app.use('/api/ai', aiGenerateRouter);
|
|
||||||
app.use('/api/settings', settingsRouter);
|
app.use('/api/settings', settingsRouter);
|
||||||
app.get('/api/health', (_req, res) => {
|
app.get('/api/health', (_req, res) => {
|
||||||
res.json({ ok: true });
|
res.json({ ok: true });
|
||||||
|
|||||||
@ -1,110 +0,0 @@
|
|||||||
import express from 'express';
|
|
||||||
import crypto from 'crypto';
|
|
||||||
import { AIService } from '../services/ai/AIService';
|
|
||||||
import { ContentGeneratorStream } from '../services/ai/contentGeneratorStream';
|
|
||||||
import { handleAIError } from '../utils/errorHandler';
|
|
||||||
import {
|
|
||||||
GenerateContentRequest,
|
|
||||||
GenerateMetadataRequest,
|
|
||||||
GenerateAltTextRequest,
|
|
||||||
} from '../types/ai.types';
|
|
||||||
|
|
||||||
const router = express.Router();
|
|
||||||
const aiService = new AIService();
|
|
||||||
const contentStreamService = new ContentGeneratorStream();
|
|
||||||
|
|
||||||
/**
|
|
||||||
* POST /api/ai/generate
|
|
||||||
* Generate article content using AI (non-streaming, for backward compatibility)
|
|
||||||
*/
|
|
||||||
router.post('/generate', async (req, res) => {
|
|
||||||
const requestId = crypto.randomUUID();
|
|
||||||
const startTs = Date.now();
|
|
||||||
|
|
||||||
try {
|
|
||||||
const params = req.body as GenerateContentRequest;
|
|
||||||
|
|
||||||
if (!params.prompt) {
|
|
||||||
return res.status(400).json({ error: 'prompt is required' });
|
|
||||||
}
|
|
||||||
|
|
||||||
const result = await aiService.generateContent(params);
|
|
||||||
res.json(result);
|
|
||||||
} catch (err: any) {
|
|
||||||
const elapsedMs = Date.now() - startTs;
|
|
||||||
handleAIError(err, res, requestId, elapsedMs);
|
|
||||||
}
|
|
||||||
});
|
|
||||||
|
|
||||||
/**
|
|
||||||
* POST /api/ai/generate-stream
|
|
||||||
* Generate article content using AI with Server-Sent Events streaming
|
|
||||||
*/
|
|
||||||
router.post('/generate-stream', async (req, res) => {
|
|
||||||
try {
|
|
||||||
const params = req.body as GenerateContentRequest;
|
|
||||||
|
|
||||||
if (!params.prompt) {
|
|
||||||
return res.status(400).json({ error: 'prompt is required' });
|
|
||||||
}
|
|
||||||
|
|
||||||
// Stream the response
|
|
||||||
await contentStreamService.generateStream(params, res);
|
|
||||||
} catch (err: any) {
|
|
||||||
console.error('[AI Routes] Stream error:', err);
|
|
||||||
if (!res.headersSent) {
|
|
||||||
res.status(500).json({
|
|
||||||
error: 'Streaming failed',
|
|
||||||
details: err?.message || 'Unknown error'
|
|
||||||
});
|
|
||||||
}
|
|
||||||
}
|
|
||||||
});
|
|
||||||
|
|
||||||
/**
|
|
||||||
* POST /api/ai/generate-metadata
|
|
||||||
* Generate metadata (title, tags, canonical URL) from content
|
|
||||||
*/
|
|
||||||
router.post('/generate-metadata', async (req, res) => {
|
|
||||||
const requestId = crypto.randomUUID();
|
|
||||||
const startTs = Date.now();
|
|
||||||
|
|
||||||
try {
|
|
||||||
const params = req.body as GenerateMetadataRequest;
|
|
||||||
|
|
||||||
if (!params.contentHtml) {
|
|
||||||
return res.status(400).json({ error: 'contentHtml is required' });
|
|
||||||
}
|
|
||||||
|
|
||||||
const result = await aiService.generateMetadata(params);
|
|
||||||
res.json(result);
|
|
||||||
} catch (err: any) {
|
|
||||||
const elapsedMs = Date.now() - startTs;
|
|
||||||
handleAIError(err, res, requestId, elapsedMs);
|
|
||||||
}
|
|
||||||
});
|
|
||||||
|
|
||||||
/**
|
|
||||||
* POST /api/ai/generate-alt-text
|
|
||||||
* Generate alt text and caption for image placeholder
|
|
||||||
*/
|
|
||||||
router.post('/generate-alt-text', async (req, res) => {
|
|
||||||
const requestId = crypto.randomUUID();
|
|
||||||
const startTs = Date.now();
|
|
||||||
|
|
||||||
try {
|
|
||||||
const params = req.body as GenerateAltTextRequest;
|
|
||||||
|
|
||||||
if (!params.placeholderDescription) {
|
|
||||||
return res.status(400).json({ error: 'placeholderDescription is required' });
|
|
||||||
}
|
|
||||||
|
|
||||||
const result = await aiService.generateAltText(params);
|
|
||||||
res.json(result);
|
|
||||||
} catch (err: any) {
|
|
||||||
const elapsedMs = Date.now() - startTs;
|
|
||||||
handleAIError(err, res, requestId, elapsedMs);
|
|
||||||
}
|
|
||||||
});
|
|
||||||
|
|
||||||
export default router;
|
|
||||||
@ -1,48 +0,0 @@
|
|||||||
import { ContentGenerator } from './contentGenerator';
|
|
||||||
import { MetadataGenerator } from './metadataGenerator';
|
|
||||||
import { AltTextGenerator } from './altTextGenerator';
|
|
||||||
import {
|
|
||||||
GenerateContentRequest,
|
|
||||||
GenerateContentResponse,
|
|
||||||
GenerateMetadataRequest,
|
|
||||||
GenerateMetadataResponse,
|
|
||||||
GenerateAltTextRequest,
|
|
||||||
GenerateAltTextResponse,
|
|
||||||
} from '../../types/ai.types';
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Main AI service orchestrator
|
|
||||||
* Delegates to specialized generators for each task
|
|
||||||
*/
|
|
||||||
export class AIService {
|
|
||||||
private contentGenerator: ContentGenerator;
|
|
||||||
private metadataGenerator: MetadataGenerator;
|
|
||||||
private altTextGenerator: AltTextGenerator;
|
|
||||||
|
|
||||||
constructor() {
|
|
||||||
this.contentGenerator = new ContentGenerator();
|
|
||||||
this.metadataGenerator = new MetadataGenerator();
|
|
||||||
this.altTextGenerator = new AltTextGenerator();
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Generate article content
|
|
||||||
*/
|
|
||||||
async generateContent(params: GenerateContentRequest): Promise<GenerateContentResponse> {
|
|
||||||
return this.contentGenerator.generate(params);
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Generate metadata (title, tags, canonical URL)
|
|
||||||
*/
|
|
||||||
async generateMetadata(params: GenerateMetadataRequest): Promise<GenerateMetadataResponse> {
|
|
||||||
return this.metadataGenerator.generate(params);
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Generate alt text and caption for images
|
|
||||||
*/
|
|
||||||
async generateAltText(params: GenerateAltTextRequest): Promise<GenerateAltTextResponse> {
|
|
||||||
return this.altTextGenerator.generate(params);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
@ -1,81 +0,0 @@
|
|||||||
import { OpenAIClient } from '../openai/client';
|
|
||||||
import { ALT_TEXT_WITH_CAPTION_PROMPT, ALT_TEXT_ONLY_PROMPT } from '../../config/prompts';
|
|
||||||
import { GenerateAltTextRequest, GenerateAltTextResponse } from '../../types/ai.types';
|
|
||||||
import { stripHtmlTags, parseJSONResponse } from '../../utils/responseParser';
|
|
||||||
|
|
||||||
export class AltTextGenerator {
|
|
||||||
private openai = OpenAIClient.getInstance();
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Build context from request parameters
|
|
||||||
*/
|
|
||||||
private buildContext(params: GenerateAltTextRequest): string {
|
|
||||||
let context = `Placeholder description: ${params.placeholderDescription}`;
|
|
||||||
|
|
||||||
if (params.surroundingText) {
|
|
||||||
context += `\n\nSurrounding text:\n${params.surroundingText}`;
|
|
||||||
} else if (params.contentHtml) {
|
|
||||||
const textContent = stripHtmlTags(params.contentHtml);
|
|
||||||
const preview = textContent.slice(0, 1000);
|
|
||||||
context += `\n\nArticle context:\n${preview}`;
|
|
||||||
}
|
|
||||||
|
|
||||||
return context;
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Generate alt text and optionally caption for image placeholder
|
|
||||||
*/
|
|
||||||
async generate(params: GenerateAltTextRequest): Promise<GenerateAltTextResponse> {
|
|
||||||
console.log('[AltTextGenerator] Generating for:', params.placeholderDescription);
|
|
||||||
|
|
||||||
const context = this.buildContext(params);
|
|
||||||
const includeCaption = params.includeCaption !== false;
|
|
||||||
|
|
||||||
const systemPrompt = includeCaption
|
|
||||||
? ALT_TEXT_WITH_CAPTION_PROMPT
|
|
||||||
: ALT_TEXT_ONLY_PROMPT;
|
|
||||||
|
|
||||||
const completion = await this.openai.chat.completions.create({
|
|
||||||
model: 'gpt-5-2025-08-07',
|
|
||||||
messages: [
|
|
||||||
{
|
|
||||||
role: 'system',
|
|
||||||
content: systemPrompt,
|
|
||||||
},
|
|
||||||
{
|
|
||||||
role: 'user',
|
|
||||||
content: context,
|
|
||||||
},
|
|
||||||
],
|
|
||||||
max_completion_tokens: includeCaption ? 200 : 100,
|
|
||||||
});
|
|
||||||
|
|
||||||
const response = completion.choices[0]?.message?.content?.trim() || '';
|
|
||||||
|
|
||||||
if (!response) {
|
|
||||||
throw new Error('No content generated');
|
|
||||||
}
|
|
||||||
|
|
||||||
if (includeCaption) {
|
|
||||||
// Parse JSON response
|
|
||||||
try {
|
|
||||||
const parsed = parseJSONResponse<GenerateAltTextResponse>(response);
|
|
||||||
console.log('[AltTextGenerator] Generated:', parsed);
|
|
||||||
|
|
||||||
return {
|
|
||||||
altText: parsed.altText || '',
|
|
||||||
caption: parsed.caption || '',
|
|
||||||
};
|
|
||||||
} catch (parseErr) {
|
|
||||||
console.error('[AltTextGenerator] JSON parse error:', parseErr);
|
|
||||||
// Fallback: treat as alt text only
|
|
||||||
return { altText: response, caption: '' };
|
|
||||||
}
|
|
||||||
} else {
|
|
||||||
// Alt text only
|
|
||||||
console.log('[AltTextGenerator] Generated alt text:', response);
|
|
||||||
return { altText: response, caption: '' };
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
@ -1,135 +0,0 @@
|
|||||||
import crypto from 'crypto';
|
|
||||||
import { db } from '../../db';
|
|
||||||
import { settings } from '../../db/schema';
|
|
||||||
import { eq } from 'drizzle-orm';
|
|
||||||
import { OpenAIClient } from '../openai/client';
|
|
||||||
import { CONTENT_GENERATION_PROMPT } from '../../config/prompts';
|
|
||||||
import { GenerateContentRequest, GenerateContentResponse } from '../../types/ai.types';
|
|
||||||
import { generatePresignedUrls, filterSupportedImageFormats, extractImagePlaceholders } from '../../utils/imageUtils';
|
|
||||||
import { buildFullContext } from '../../utils/contextBuilder';
|
|
||||||
|
|
||||||
export class ContentGenerator {
|
|
||||||
private openai = OpenAIClient.getInstance();
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Get system prompt from database or use default
|
|
||||||
*/
|
|
||||||
private async getSystemPrompt(): Promise<string> {
|
|
||||||
try {
|
|
||||||
const settingRows = await db
|
|
||||||
.select()
|
|
||||||
.from(settings)
|
|
||||||
.where(eq(settings.key, 'system_prompt'))
|
|
||||||
.limit(1);
|
|
||||||
|
|
||||||
if (settingRows.length > 0) {
|
|
||||||
console.log('[ContentGenerator] Using custom system prompt from settings');
|
|
||||||
return settingRows[0].value;
|
|
||||||
}
|
|
||||||
|
|
||||||
console.log('[ContentGenerator] Using default system prompt');
|
|
||||||
return CONTENT_GENERATION_PROMPT;
|
|
||||||
} catch (err) {
|
|
||||||
console.warn('[ContentGenerator] Failed to load system prompt, using default:', err);
|
|
||||||
return CONTENT_GENERATION_PROMPT;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Generate article content using gpt-5-2025-08-07 model
|
|
||||||
*/
|
|
||||||
async generate(params: GenerateContentRequest): Promise<GenerateContentResponse> {
|
|
||||||
const requestId = crypto.randomUUID();
|
|
||||||
const startTs = Date.now();
|
|
||||||
|
|
||||||
console.log(`[ContentGenerator][${requestId}] Starting generation...`);
|
|
||||||
console.log(`[ContentGenerator][${requestId}] Prompt length:`, params.prompt.length);
|
|
||||||
console.log(`[ContentGenerator][${requestId}] Web search:`, params.useWebSearch);
|
|
||||||
|
|
||||||
try {
|
|
||||||
// Get system prompt
|
|
||||||
const systemPrompt = await this.getSystemPrompt();
|
|
||||||
|
|
||||||
// Generate presigned URLs for reference images
|
|
||||||
let referenceImagePresignedUrls: string[] = [];
|
|
||||||
if (params.referenceImageUrls && params.referenceImageUrls.length > 0) {
|
|
||||||
console.log(`[ContentGenerator][${requestId}] Processing`, params.referenceImageUrls.length, 'reference images');
|
|
||||||
const bucket = process.env.S3_BUCKET || '';
|
|
||||||
referenceImagePresignedUrls = await generatePresignedUrls(params.referenceImageUrls, bucket);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Filter to supported image formats
|
|
||||||
const { supported: supportedImages, skipped } = filterSupportedImageFormats(referenceImagePresignedUrls);
|
|
||||||
if (skipped > 0) {
|
|
||||||
console.log(`[ContentGenerator][${requestId}] Skipped ${skipped} unsupported image formats`);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Build context section
|
|
||||||
const contextSection = buildFullContext({
|
|
||||||
audioTranscriptions: params.audioTranscriptions,
|
|
||||||
selectedImageUrls: params.selectedImageUrls,
|
|
||||||
referenceImageCount: supportedImages.length,
|
|
||||||
});
|
|
||||||
|
|
||||||
const userPrompt = `${params.prompt}${contextSection}`;
|
|
||||||
|
|
||||||
const model = 'gpt-5-2025-08-07';
|
|
||||||
console.log(`[ContentGenerator][${requestId}] Model:`, model, 'ref_images:', supportedImages.length);
|
|
||||||
|
|
||||||
// Build user message content with text and images
|
|
||||||
const userMessageContent: any[] = [
|
|
||||||
{ type: 'text', text: userPrompt },
|
|
||||||
];
|
|
||||||
|
|
||||||
// Add reference images for vision
|
|
||||||
supportedImages.forEach((url) => {
|
|
||||||
userMessageContent.push({
|
|
||||||
type: 'image_url',
|
|
||||||
image_url: { url },
|
|
||||||
});
|
|
||||||
});
|
|
||||||
|
|
||||||
// Call Chat Completions API
|
|
||||||
const completion = await this.openai.chat.completions.create({
|
|
||||||
model,
|
|
||||||
messages: [
|
|
||||||
{
|
|
||||||
role: 'system',
|
|
||||||
content: systemPrompt,
|
|
||||||
},
|
|
||||||
{
|
|
||||||
role: 'user',
|
|
||||||
content: userMessageContent,
|
|
||||||
},
|
|
||||||
],
|
|
||||||
max_completion_tokens: 16384,
|
|
||||||
});
|
|
||||||
|
|
||||||
// Parse output
|
|
||||||
const generatedContent = completion.choices[0]?.message?.content || '';
|
|
||||||
|
|
||||||
if (!generatedContent) {
|
|
||||||
throw new Error('No content generated from AI');
|
|
||||||
}
|
|
||||||
|
|
||||||
const elapsedMs = Date.now() - startTs;
|
|
||||||
console.log(`[ContentGenerator][${requestId}] Success! Length:`, generatedContent.length, 'elapsed:', elapsedMs, 'ms');
|
|
||||||
|
|
||||||
// Extract image placeholders
|
|
||||||
const imagePlaceholders = extractImagePlaceholders(generatedContent);
|
|
||||||
|
|
||||||
return {
|
|
||||||
content: generatedContent,
|
|
||||||
imagePlaceholders,
|
|
||||||
tokensUsed: completion.usage?.total_tokens || 0,
|
|
||||||
model: completion.model || model,
|
|
||||||
requestId,
|
|
||||||
elapsedMs,
|
|
||||||
};
|
|
||||||
} catch (err) {
|
|
||||||
const elapsedMs = Date.now() - startTs;
|
|
||||||
console.error(`[ContentGenerator][${requestId}] Error after ${elapsedMs}ms:`, err);
|
|
||||||
throw err;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
@ -1,177 +0,0 @@
|
|||||||
import crypto from 'crypto';
|
|
||||||
import { Response } from 'express';
|
|
||||||
import { db } from '../../db';
|
|
||||||
import { settings } from '../../db/schema';
|
|
||||||
import { eq } from 'drizzle-orm';
|
|
||||||
import { OpenAIClient } from '../openai/client';
|
|
||||||
import { CONTENT_GENERATION_PROMPT } from '../../config/prompts';
|
|
||||||
import { GenerateContentRequest } from '../../types/ai.types';
|
|
||||||
import { generatePresignedUrls, filterSupportedImageFormats, extractImagePlaceholders } from '../../utils/imageUtils';
|
|
||||||
import { buildFullContext } from '../../utils/contextBuilder';
|
|
||||||
|
|
||||||
export class ContentGeneratorStream {
|
|
||||||
private openai = OpenAIClient.getInstance();
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Get system prompt from database or use default
|
|
||||||
*/
|
|
||||||
private async getSystemPrompt(): Promise<string> {
|
|
||||||
try {
|
|
||||||
const settingRows = await db
|
|
||||||
.select()
|
|
||||||
.from(settings)
|
|
||||||
.where(eq(settings.key, 'system_prompt'))
|
|
||||||
.limit(1);
|
|
||||||
|
|
||||||
if (settingRows.length > 0) {
|
|
||||||
console.log('[ContentGeneratorStream] Using custom system prompt from settings');
|
|
||||||
return settingRows[0].value;
|
|
||||||
}
|
|
||||||
|
|
||||||
console.log('[ContentGeneratorStream] Using default system prompt');
|
|
||||||
return CONTENT_GENERATION_PROMPT;
|
|
||||||
} catch (err) {
|
|
||||||
console.warn('[ContentGeneratorStream] Failed to load system prompt, using default:', err);
|
|
||||||
return CONTENT_GENERATION_PROMPT;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Generate article content with streaming using Server-Sent Events
|
|
||||||
*/
|
|
||||||
async generateStream(params: GenerateContentRequest, res: Response): Promise<void> {
|
|
||||||
const requestId = crypto.randomUUID();
|
|
||||||
const startTs = Date.now();
|
|
||||||
|
|
||||||
console.log(`[ContentGeneratorStream][${requestId}] Starting streaming generation...`);
|
|
||||||
console.log(`[ContentGeneratorStream][${requestId}] Prompt length:`, params.prompt.length);
|
|
||||||
|
|
||||||
try {
|
|
||||||
// Set up SSE headers
|
|
||||||
res.setHeader('Content-Type', 'text/event-stream');
|
|
||||||
res.setHeader('Cache-Control', 'no-cache');
|
|
||||||
res.setHeader('Connection', 'keep-alive');
|
|
||||||
res.setHeader('X-Request-ID', requestId);
|
|
||||||
|
|
||||||
// Send initial metadata
|
|
||||||
res.write(`data: ${JSON.stringify({ type: 'start', requestId })}\n\n`);
|
|
||||||
|
|
||||||
// Get system prompt
|
|
||||||
const systemPrompt = await this.getSystemPrompt();
|
|
||||||
|
|
||||||
// Generate presigned URLs for reference images
|
|
||||||
let referenceImagePresignedUrls: string[] = [];
|
|
||||||
if (params.referenceImageUrls && params.referenceImageUrls.length > 0) {
|
|
||||||
console.log(`[ContentGeneratorStream][${requestId}] Processing`, params.referenceImageUrls.length, 'reference images');
|
|
||||||
const bucket = process.env.S3_BUCKET || '';
|
|
||||||
referenceImagePresignedUrls = await generatePresignedUrls(params.referenceImageUrls, bucket);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Filter to supported image formats
|
|
||||||
const { supported: supportedImages, skipped } = filterSupportedImageFormats(referenceImagePresignedUrls);
|
|
||||||
if (skipped > 0) {
|
|
||||||
console.log(`[ContentGeneratorStream][${requestId}] Skipped ${skipped} unsupported image formats`);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Build context section
|
|
||||||
const contextSection = buildFullContext({
|
|
||||||
audioTranscriptions: params.audioTranscriptions,
|
|
||||||
selectedImageUrls: params.selectedImageUrls,
|
|
||||||
referenceImageCount: supportedImages.length,
|
|
||||||
});
|
|
||||||
|
|
||||||
const userPrompt = `${params.prompt}${contextSection}`;
|
|
||||||
|
|
||||||
const model = 'gpt-5-2025-08-07';
|
|
||||||
console.log(`[ContentGeneratorStream][${requestId}] Model:`, model, 'ref_images:', supportedImages.length);
|
|
||||||
|
|
||||||
// Build user message content with text and images
|
|
||||||
const userMessageContent: any[] = [
|
|
||||||
{ type: 'text', text: userPrompt },
|
|
||||||
];
|
|
||||||
|
|
||||||
// Add reference images for vision
|
|
||||||
supportedImages.forEach((url) => {
|
|
||||||
userMessageContent.push({
|
|
||||||
type: 'image_url',
|
|
||||||
image_url: { url },
|
|
||||||
});
|
|
||||||
});
|
|
||||||
|
|
||||||
// Call Chat Completions API with streaming
|
|
||||||
const stream = await this.openai.chat.completions.create({
|
|
||||||
model,
|
|
||||||
messages: [
|
|
||||||
{
|
|
||||||
role: 'system',
|
|
||||||
content: systemPrompt,
|
|
||||||
},
|
|
||||||
{
|
|
||||||
role: 'user',
|
|
||||||
content: userMessageContent,
|
|
||||||
},
|
|
||||||
],
|
|
||||||
max_completion_tokens: 16384,
|
|
||||||
stream: true,
|
|
||||||
});
|
|
||||||
|
|
||||||
let fullContent = '';
|
|
||||||
let tokenCount = 0;
|
|
||||||
|
|
||||||
// Stream chunks to client
|
|
||||||
for await (const chunk of stream) {
|
|
||||||
const delta = chunk.choices[0]?.delta?.content;
|
|
||||||
|
|
||||||
if (delta) {
|
|
||||||
fullContent += delta;
|
|
||||||
tokenCount++;
|
|
||||||
|
|
||||||
// Send content chunk
|
|
||||||
res.write(`data: ${JSON.stringify({
|
|
||||||
type: 'content',
|
|
||||||
delta,
|
|
||||||
tokenCount
|
|
||||||
})}\n\n`);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Check if client disconnected
|
|
||||||
if (res.writableEnded) {
|
|
||||||
console.log(`[ContentGeneratorStream][${requestId}] Client disconnected`);
|
|
||||||
break;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
const elapsedMs = Date.now() - startTs;
|
|
||||||
console.log(`[ContentGeneratorStream][${requestId}] Streaming complete! Length:`, fullContent.length, 'elapsed:', elapsedMs, 'ms');
|
|
||||||
|
|
||||||
// Extract image placeholders
|
|
||||||
const imagePlaceholders = extractImagePlaceholders(fullContent);
|
|
||||||
|
|
||||||
// Send completion event with metadata
|
|
||||||
res.write(`data: ${JSON.stringify({
|
|
||||||
type: 'done',
|
|
||||||
content: fullContent,
|
|
||||||
imagePlaceholders,
|
|
||||||
tokenCount,
|
|
||||||
model,
|
|
||||||
requestId,
|
|
||||||
elapsedMs
|
|
||||||
})}\n\n`);
|
|
||||||
|
|
||||||
res.end();
|
|
||||||
} catch (err) {
|
|
||||||
const elapsedMs = Date.now() - startTs;
|
|
||||||
console.error(`[ContentGeneratorStream][${requestId}] Error after ${elapsedMs}ms:`, err);
|
|
||||||
|
|
||||||
// Send error event
|
|
||||||
res.write(`data: ${JSON.stringify({
|
|
||||||
type: 'error',
|
|
||||||
error: err instanceof Error ? err.message : 'Unknown error',
|
|
||||||
requestId,
|
|
||||||
elapsedMs
|
|
||||||
})}\n\n`);
|
|
||||||
|
|
||||||
res.end();
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
@ -1,57 +0,0 @@
|
|||||||
import { OpenAIClient } from '../openai/client';
|
|
||||||
import { METADATA_GENERATION_PROMPT } from '../../config/prompts';
|
|
||||||
import { GenerateMetadataRequest, GenerateMetadataResponse } from '../../types/ai.types';
|
|
||||||
import { stripHtmlTags, parseJSONResponse } from '../../utils/responseParser';
|
|
||||||
|
|
||||||
export class MetadataGenerator {
|
|
||||||
private openai = OpenAIClient.getInstance();
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Generate metadata (title, tags, canonical URL) from article content
|
|
||||||
*/
|
|
||||||
async generate(params: GenerateMetadataRequest): Promise<GenerateMetadataResponse> {
|
|
||||||
console.log('[MetadataGenerator] Generating metadata...');
|
|
||||||
|
|
||||||
// Strip HTML and get preview
|
|
||||||
const textContent = stripHtmlTags(params.contentHtml);
|
|
||||||
const preview = textContent.slice(0, 2000);
|
|
||||||
|
|
||||||
const completion = await this.openai.chat.completions.create({
|
|
||||||
model: 'gpt-5-2025-08-07',
|
|
||||||
messages: [
|
|
||||||
{
|
|
||||||
role: 'system',
|
|
||||||
content: METADATA_GENERATION_PROMPT,
|
|
||||||
},
|
|
||||||
{
|
|
||||||
role: 'user',
|
|
||||||
content: `Generate metadata for this article:\n\n${preview}`,
|
|
||||||
},
|
|
||||||
],
|
|
||||||
max_completion_tokens: 300,
|
|
||||||
});
|
|
||||||
|
|
||||||
const response = completion.choices[0]?.message?.content || '';
|
|
||||||
|
|
||||||
if (!response) {
|
|
||||||
throw new Error('No metadata generated');
|
|
||||||
}
|
|
||||||
|
|
||||||
console.log('[MetadataGenerator] Raw response:', response);
|
|
||||||
|
|
||||||
// Parse JSON response
|
|
||||||
try {
|
|
||||||
const metadata = parseJSONResponse<GenerateMetadataResponse>(response);
|
|
||||||
console.log('[MetadataGenerator] Generated:', metadata);
|
|
||||||
|
|
||||||
return {
|
|
||||||
title: metadata.title || '',
|
|
||||||
tags: metadata.tags || '',
|
|
||||||
canonicalUrl: metadata.canonicalUrl || '',
|
|
||||||
};
|
|
||||||
} catch (parseErr) {
|
|
||||||
console.error('[MetadataGenerator] JSON parse error:', parseErr);
|
|
||||||
throw new Error('Failed to parse metadata response');
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
@ -1,37 +0,0 @@
|
|||||||
import OpenAI from 'openai';
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Singleton OpenAI client with optimized configuration
|
|
||||||
*/
|
|
||||||
export class OpenAIClient {
|
|
||||||
private static instance: OpenAI | null = null;
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Get or create the OpenAI client instance
|
|
||||||
*/
|
|
||||||
static getInstance(): OpenAI {
|
|
||||||
if (!this.instance) {
|
|
||||||
const apiKey = process.env.OPENAI_API_KEY;
|
|
||||||
if (!apiKey) {
|
|
||||||
throw new Error('OpenAI API key not configured');
|
|
||||||
}
|
|
||||||
|
|
||||||
this.instance = new OpenAI({
|
|
||||||
apiKey,
|
|
||||||
timeout: 600_000, // 10 minutes for long-running requests
|
|
||||||
maxRetries: 2, // Retry failed requests twice
|
|
||||||
});
|
|
||||||
|
|
||||||
console.log('[OpenAIClient] Initialized with timeout: 600s, maxRetries: 2');
|
|
||||||
}
|
|
||||||
|
|
||||||
return this.instance;
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Reset the instance (useful for testing)
|
|
||||||
*/
|
|
||||||
static reset(): void {
|
|
||||||
this.instance = null;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
@ -1,89 +0,0 @@
|
|||||||
// Request types
|
|
||||||
export interface GenerateContentRequest {
|
|
||||||
prompt: string;
|
|
||||||
audioTranscriptions?: string[];
|
|
||||||
selectedImageUrls?: string[];
|
|
||||||
referenceImageUrls?: string[];
|
|
||||||
useWebSearch?: boolean;
|
|
||||||
}
|
|
||||||
|
|
||||||
export interface GenerateMetadataRequest {
|
|
||||||
contentHtml: string;
|
|
||||||
}
|
|
||||||
|
|
||||||
export interface GenerateAltTextRequest {
|
|
||||||
placeholderDescription: string;
|
|
||||||
contentHtml?: string;
|
|
||||||
surroundingText?: string;
|
|
||||||
includeCaption?: boolean;
|
|
||||||
}
|
|
||||||
|
|
||||||
// Response types
|
|
||||||
export interface GenerateContentResponse {
|
|
||||||
content: string;
|
|
||||||
imagePlaceholders: string[];
|
|
||||||
tokensUsed: number;
|
|
||||||
model: string;
|
|
||||||
sources?: Source[];
|
|
||||||
requestId?: string;
|
|
||||||
elapsedMs?: number;
|
|
||||||
}
|
|
||||||
|
|
||||||
export interface GenerateMetadataResponse {
|
|
||||||
title: string;
|
|
||||||
tags: string;
|
|
||||||
canonicalUrl: string;
|
|
||||||
}
|
|
||||||
|
|
||||||
export interface GenerateAltTextResponse {
|
|
||||||
altText: string;
|
|
||||||
caption: string;
|
|
||||||
}
|
|
||||||
|
|
||||||
// Common types
|
|
||||||
export interface Source {
|
|
||||||
title: string;
|
|
||||||
url: string;
|
|
||||||
}
|
|
||||||
|
|
||||||
export interface AIError {
|
|
||||||
error: string;
|
|
||||||
details: string;
|
|
||||||
requestId?: string;
|
|
||||||
elapsedMs?: number;
|
|
||||||
errorDetails?: {
|
|
||||||
name?: string;
|
|
||||||
status?: number;
|
|
||||||
code?: string;
|
|
||||||
type?: string;
|
|
||||||
param?: string;
|
|
||||||
requestID?: string;
|
|
||||||
cause?: {
|
|
||||||
name?: string;
|
|
||||||
code?: string;
|
|
||||||
message?: string;
|
|
||||||
};
|
|
||||||
};
|
|
||||||
}
|
|
||||||
|
|
||||||
// Internal service types
|
|
||||||
export interface ContextBuildParams {
|
|
||||||
audioTranscriptions?: string[];
|
|
||||||
selectedImageUrls?: string[];
|
|
||||||
referenceImageCount: number;
|
|
||||||
}
|
|
||||||
|
|
||||||
export interface ResponsesAPIOutput {
|
|
||||||
output_text?: string;
|
|
||||||
output?: Array<{
|
|
||||||
type: string;
|
|
||||||
content?: Array<{
|
|
||||||
type: string;
|
|
||||||
text?: string;
|
|
||||||
}>;
|
|
||||||
}>;
|
|
||||||
usage?: {
|
|
||||||
total_tokens?: number;
|
|
||||||
};
|
|
||||||
model?: string;
|
|
||||||
}
|
|
||||||
@ -1,60 +0,0 @@
|
|||||||
import { ContextBuildParams } from '../types/ai.types';
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Build audio transcription context section
|
|
||||||
*/
|
|
||||||
export function buildAudioContext(transcriptions: string[]): string {
|
|
||||||
if (!transcriptions || transcriptions.length === 0) {
|
|
||||||
return '';
|
|
||||||
}
|
|
||||||
|
|
||||||
let context = '\n\nAUDIO TRANSCRIPTIONS:\n';
|
|
||||||
transcriptions.forEach((transcript, idx) => {
|
|
||||||
context += `\n[Transcript ${idx + 1}]:\n${transcript}\n`;
|
|
||||||
});
|
|
||||||
|
|
||||||
return context;
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Build image context section
|
|
||||||
*/
|
|
||||||
export function buildImageContext(
|
|
||||||
selectedImageUrls: string[] | undefined,
|
|
||||||
referenceImageCount: number
|
|
||||||
): string {
|
|
||||||
let context = '';
|
|
||||||
|
|
||||||
// Add information about available images (for article content)
|
|
||||||
if (selectedImageUrls && selectedImageUrls.length > 0) {
|
|
||||||
context += '\n\nAVAILABLE IMAGES FOR ARTICLE:\n';
|
|
||||||
context += `You have ${selectedImageUrls.length} images available. Use {{IMAGE:description}} placeholders where images should be inserted in the article.\n`;
|
|
||||||
context += `Important: You will NOT see these images. Just create descriptive placeholders based on where images would fit naturally in the content.\n`;
|
|
||||||
}
|
|
||||||
|
|
||||||
// Add context about reference images
|
|
||||||
if (referenceImageCount > 0) {
|
|
||||||
context += '\n\nREFERENCE IMAGES (Context Only):\n';
|
|
||||||
context += `You will see ${referenceImageCount} reference images below. These provide visual context to help you understand the topic better.\n`;
|
|
||||||
context += `IMPORTANT: DO NOT create {{IMAGE:...}} placeholders for these reference images. They will NOT appear in the article.\n`;
|
|
||||||
context += `Use these reference images to:\n`;
|
|
||||||
context += `- Better understand the visual style and content\n`;
|
|
||||||
context += `- Get inspiration for descriptions and explanations\n`;
|
|
||||||
context += `- Understand technical details shown in screenshots\n`;
|
|
||||||
context += `- Grasp the overall theme and aesthetic\n`;
|
|
||||||
}
|
|
||||||
|
|
||||||
return context;
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Build full context section from all inputs
|
|
||||||
*/
|
|
||||||
export function buildFullContext(params: ContextBuildParams): string {
|
|
||||||
let context = '';
|
|
||||||
|
|
||||||
context += buildAudioContext(params.audioTranscriptions || []);
|
|
||||||
context += buildImageContext(params.selectedImageUrls, params.referenceImageCount);
|
|
||||||
|
|
||||||
return context;
|
|
||||||
}
|
|
||||||
@ -1,61 +0,0 @@
|
|||||||
import { Response } from 'express';
|
|
||||||
import { AIError } from '../types/ai.types';
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Handle AI service errors with consistent logging and response format
|
|
||||||
*/
|
|
||||||
export function handleAIError(
|
|
||||||
err: any,
|
|
||||||
res: Response,
|
|
||||||
requestId: string,
|
|
||||||
elapsedMs?: number
|
|
||||||
): void {
|
|
||||||
// Log detailed error information
|
|
||||||
console.error(`[AIError][${requestId}] Error details:`, {
|
|
||||||
message: err?.message,
|
|
||||||
name: err?.name,
|
|
||||||
status: err?.status,
|
|
||||||
code: err?.code,
|
|
||||||
type: err?.type,
|
|
||||||
param: err?.param,
|
|
||||||
requestID: err?.requestID,
|
|
||||||
headers: err?.headers,
|
|
||||||
error: err?.error,
|
|
||||||
cause: {
|
|
||||||
name: err?.cause?.name,
|
|
||||||
code: err?.cause?.code,
|
|
||||||
message: err?.cause?.message,
|
|
||||||
},
|
|
||||||
stack: err?.stack,
|
|
||||||
elapsedMs,
|
|
||||||
});
|
|
||||||
|
|
||||||
// Determine if we should include detailed error info in response
|
|
||||||
const debug =
|
|
||||||
process.env.NODE_ENV !== 'production' || process.env.DEBUG_AI_ERRORS === 'true';
|
|
||||||
|
|
||||||
const payload: AIError = {
|
|
||||||
error: 'AI operation failed',
|
|
||||||
details: err?.message || 'Unknown error',
|
|
||||||
requestId,
|
|
||||||
elapsedMs,
|
|
||||||
};
|
|
||||||
|
|
||||||
if (debug) {
|
|
||||||
payload.errorDetails = {
|
|
||||||
name: err?.name,
|
|
||||||
status: err?.status,
|
|
||||||
code: err?.code,
|
|
||||||
type: err?.type,
|
|
||||||
param: err?.param,
|
|
||||||
requestID: err?.requestID,
|
|
||||||
cause: {
|
|
||||||
name: err?.cause?.name,
|
|
||||||
code: err?.cause?.code,
|
|
||||||
message: err?.cause?.message,
|
|
||||||
},
|
|
||||||
};
|
|
||||||
}
|
|
||||||
|
|
||||||
res.status(500).json(payload);
|
|
||||||
}
|
|
||||||
@ -1,70 +0,0 @@
|
|||||||
import { getPresignedUrl } from '../storage/s3';
|
|
||||||
|
|
||||||
const SUPPORTED_IMAGE_FORMATS = /\.(png|jpe?g|gif|webp)(\?|$)/i;
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Generate presigned URLs for reference images
|
|
||||||
*/
|
|
||||||
export async function generatePresignedUrls(
|
|
||||||
imageUrls: string[],
|
|
||||||
bucket: string
|
|
||||||
): Promise<string[]> {
|
|
||||||
const presignedUrls: string[] = [];
|
|
||||||
|
|
||||||
for (const url of imageUrls) {
|
|
||||||
try {
|
|
||||||
// Extract key from URL: /api/media/obj?key=images/abc.png
|
|
||||||
const keyMatch = url.match(/[?&]key=([^&]+)/);
|
|
||||||
if (keyMatch) {
|
|
||||||
const key = decodeURIComponent(keyMatch[1]);
|
|
||||||
const presignedUrl = await getPresignedUrl({
|
|
||||||
bucket,
|
|
||||||
key,
|
|
||||||
expiresInSeconds: 3600, // 1 hour
|
|
||||||
});
|
|
||||||
presignedUrls.push(presignedUrl);
|
|
||||||
console.log('[ImageUtils] Generated presigned URL for:', key);
|
|
||||||
}
|
|
||||||
} catch (err) {
|
|
||||||
console.error('[ImageUtils] Failed to create presigned URL:', err);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
return presignedUrls;
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Filter URLs to only include supported image formats
|
|
||||||
*/
|
|
||||||
export function filterSupportedImageFormats(urls: string[]): {
|
|
||||||
supported: string[];
|
|
||||||
skipped: number;
|
|
||||||
} {
|
|
||||||
const supported: string[] = [];
|
|
||||||
let skipped = 0;
|
|
||||||
|
|
||||||
urls.forEach((url) => {
|
|
||||||
if (SUPPORTED_IMAGE_FORMATS.test(url)) {
|
|
||||||
supported.push(url);
|
|
||||||
} else {
|
|
||||||
skipped++;
|
|
||||||
}
|
|
||||||
});
|
|
||||||
|
|
||||||
return { supported, skipped };
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Extract image placeholders from generated content
|
|
||||||
*/
|
|
||||||
export function extractImagePlaceholders(content: string): string[] {
|
|
||||||
const regex = /\{\{IMAGE:([^}]+)\}\}/g;
|
|
||||||
const placeholders: string[] = [];
|
|
||||||
let match;
|
|
||||||
|
|
||||||
while ((match = regex.exec(content)) !== null) {
|
|
||||||
placeholders.push(match[1]);
|
|
||||||
}
|
|
||||||
|
|
||||||
return placeholders;
|
|
||||||
}
|
|
||||||
@ -1,63 +0,0 @@
|
|||||||
import { ResponsesAPIOutput, Source } from '../types/ai.types';
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Parse JSON response from AI, handling markdown code blocks
|
|
||||||
*/
|
|
||||||
export function parseJSONResponse<T>(response: string): T {
|
|
||||||
const cleaned = response
|
|
||||||
.replace(/```json\n?/g, '')
|
|
||||||
.replace(/```\n?/g, '')
|
|
||||||
.trim();
|
|
||||||
return JSON.parse(cleaned);
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Extract source citations from chat completion annotations
|
|
||||||
*/
|
|
||||||
export function extractSourceCitations(completion: any): Source[] {
|
|
||||||
const sources: Source[] = [];
|
|
||||||
|
|
||||||
if (completion.choices?.[0]?.message?.annotations) {
|
|
||||||
const annotations = completion.choices[0].message.annotations as any[];
|
|
||||||
for (const annotation of annotations) {
|
|
||||||
if (annotation.type === 'url_citation' && annotation.url_citation) {
|
|
||||||
sources.push({
|
|
||||||
title: annotation.url_citation.title || 'Source',
|
|
||||||
url: annotation.url_citation.url,
|
|
||||||
});
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
return sources;
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Parse output from Responses API
|
|
||||||
*/
|
|
||||||
export function parseResponsesAPIOutput(response: ResponsesAPIOutput): string {
|
|
||||||
// Try direct output_text field first
|
|
||||||
if (typeof response.output_text === 'string' && response.output_text.length > 0) {
|
|
||||||
return response.output_text;
|
|
||||||
}
|
|
||||||
|
|
||||||
// Fallback to parsing output array
|
|
||||||
if (Array.isArray(response.output)) {
|
|
||||||
const msg = response.output.find((o: any) => o.type === 'message');
|
|
||||||
if (msg && Array.isArray(msg.content)) {
|
|
||||||
const textPart = msg.content.find((c: any) => c.type === 'output_text');
|
|
||||||
if (textPart?.text) {
|
|
||||||
return textPart.text;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
return '';
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Strip HTML tags from content
|
|
||||||
*/
|
|
||||||
export function stripHtmlTags(html: string): string {
|
|
||||||
return html.replace(/<[^>]*>/g, ' ').replace(/\s+/g, ' ').trim();
|
|
||||||
}
|
|
||||||
Loading…
Reference in New Issue
Block a user