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https://github.com/siteboon/claudecodeui.git
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refactor: remove unused whispher transcribe logic
This commit is contained in:
Haileyesus
149
server/index.js
149
server/index.js
@@ -1984,155 +1984,6 @@ function handleShellConnection(ws) {
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console.error('[ERROR] Shell WebSocket error:', error);
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});
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}
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// Audio transcription endpoint
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app.post('/api/transcribe', authenticateToken, async (req, res) => {
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try {
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const multer = (await import('multer')).default;
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const upload = multer({ storage: multer.memoryStorage() });
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// Handle multipart form data
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upload.single('audio')(req, res, async (err) => {
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if (err) {
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return res.status(400).json({ error: 'Failed to process audio file' });
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}
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if (!req.file) {
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return res.status(400).json({ error: 'No audio file provided' });
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}
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const apiKey = process.env.OPENAI_API_KEY;
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if (!apiKey) {
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return res.status(500).json({ error: 'OpenAI API key not configured. Please set OPENAI_API_KEY in server environment.' });
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}
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try {
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// Create form data for OpenAI
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const FormData = (await import('form-data')).default;
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const formData = new FormData();
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formData.append('file', req.file.buffer, {
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filename: req.file.originalname,
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contentType: req.file.mimetype
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});
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formData.append('model', 'whisper-1');
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formData.append('response_format', 'json');
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formData.append('language', 'en');
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// Make request to OpenAI
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const response = await fetch('https://api.openai.com/v1/audio/transcriptions', {
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method: 'POST',
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headers: {
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'Authorization': `Bearer ${apiKey}`,
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...formData.getHeaders()
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},
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body: formData
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});
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if (!response.ok) {
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const errorData = await response.json().catch(() => ({}));
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throw new Error(errorData.error?.message || `Whisper API error: ${response.status}`);
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}
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const data = await response.json();
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let transcribedText = data.text || '';
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// Check if enhancement mode is enabled
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const mode = req.body.mode || 'default';
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// If no transcribed text, return empty
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if (!transcribedText) {
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return res.json({ text: '' });
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}
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// If default mode, return transcribed text without enhancement
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if (mode === 'default') {
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return res.json({ text: transcribedText });
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}
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// Handle different enhancement modes
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try {
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const OpenAI = (await import('openai')).default;
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const openai = new OpenAI({ apiKey });
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let prompt, systemMessage, temperature = 0.7, maxTokens = 800;
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switch (mode) {
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case 'prompt':
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systemMessage = 'You are an expert prompt engineer who creates clear, detailed, and effective prompts.';
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prompt = `You are an expert prompt engineer. Transform the following rough instruction into a clear, detailed, and context-aware AI prompt.
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Your enhanced prompt should:
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1. Be specific and unambiguous
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2. Include relevant context and constraints
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3. Specify the desired output format
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4. Use clear, actionable language
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5. Include examples where helpful
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6. Consider edge cases and potential ambiguities
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Transform this rough instruction into a well-crafted prompt:
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"${transcribedText}"
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Enhanced prompt:`;
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break;
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case 'vibe':
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case 'instructions':
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case 'architect':
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systemMessage = 'You are a helpful assistant that formats ideas into clear, actionable instructions for AI agents.';
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temperature = 0.5; // Lower temperature for more controlled output
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prompt = `Transform the following idea into clear, well-structured instructions that an AI agent can easily understand and execute.
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IMPORTANT RULES:
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- Format as clear, step-by-step instructions
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- Add reasonable implementation details based on common patterns
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- Only include details directly related to what was asked
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- Do NOT add features or functionality not mentioned
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- Keep the original intent and scope intact
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- Use clear, actionable language an agent can follow
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Transform this idea into agent-friendly instructions:
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"${transcribedText}"
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Agent instructions:`;
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break;
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default:
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// No enhancement needed
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break;
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}
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// Only make GPT call if we have a prompt
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if (prompt) {
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const completion = await openai.chat.completions.create({
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model: 'gpt-4o-mini',
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messages: [
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{ role: 'system', content: systemMessage },
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{ role: 'user', content: prompt }
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],
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temperature: temperature,
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max_tokens: maxTokens
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});
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transcribedText = completion.choices[0].message.content || transcribedText;
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}
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} catch (gptError) {
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console.error('GPT processing error:', gptError);
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// Fall back to original transcription if GPT fails
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}
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res.json({ text: transcribedText });
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} catch (error) {
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console.error('Transcription error:', error);
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res.status(500).json({ error: error.message });
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}
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});
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} catch (error) {
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console.error('Endpoint error:', error);
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res.status(500).json({ error: 'Internal server error' });
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}
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});
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// Image upload endpoint
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app.post('/api/projects/:projectName/upload-images', authenticateToken, async (req, res) => {
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try {
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