044c809ff3
- Add local Whisper (whisper.cpp / faster-whisper) as transcription provider Set TRANSCRIBE_PROVIDER=local with configurable model size and binary path - Upgrade all refine/instruction inputs to resizable textareas across encounter, dictation, hospital course, chart review, well visit, sick visit - Make AI memory injection flexible: physician preferences and corrections are now actively applied (not just "formatting reference"), while still overridable by current prompt instructions
51 lines
2.7 KiB
JavaScript
51 lines
2.7 KiB
JavaScript
const express = require('express');
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const router = express.Router();
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const { callAI } = require('../utils/ai');
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const PROMPTS = require('../utils/prompts');
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const { authMiddleware } = require('../middleware/auth');
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// HPI from encounter
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router.post('/generate-hpi-encounter', authMiddleware, async (req, res) => {
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try {
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const { transcript, patientAge, patientGender, model, setting, physicianMemories } = req.body;
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if (!transcript || !transcript.trim()) return res.status(400).json({ error: 'Transcript empty' });
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const prompt = setting === 'inpatient' ? PROMPTS.hpiInpatient : PROMPTS.hpiEncounter;
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var context = `Patient: ${patientAge || 'Unknown'}, ${patientGender || 'Unknown'}\nSetting: ${setting || 'outpatient'}\n\nTRANSCRIPT:\n${transcript}`;
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if (physicianMemories) context += '\n\n[PHYSICIAN PREFERENCES & LEARNED PATTERNS — Apply these preferences to your output. These reflect how this physician writes notes, their preferred style, terminology, and corrections from past outputs. Adapt your response accordingly, but user instructions in the current prompt take priority if they conflict.]\n' + physicianMemories + '\n[END PREFERENCES]';
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const result = await callAI([
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{ role: 'system', content: prompt },
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{ role: 'user', content: context }
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], { model });
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res.json({ success: true, hpi: result.content, model: result.model });
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} catch (err) {
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res.status(500).json({ error: err.message });
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}
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});
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// HPI from dictation
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router.post('/generate-hpi-dictation', authMiddleware, async (req, res) => {
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try {
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const { transcript, patientAge, patientGender, model, setting, physicianMemories } = req.body;
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if (!transcript || !transcript.trim()) return res.status(400).json({ error: 'Dictation empty' });
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const prompt = setting === 'inpatient' ? PROMPTS.hpiInpatient : PROMPTS.hpiDictation;
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var context = `Patient: ${patientAge || 'Unknown'}, ${patientGender || 'Unknown'}\nSetting: ${setting || 'outpatient'}\n\nDICTATION:\n${transcript}`;
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if (physicianMemories) context += '\n\n[PHYSICIAN PREFERENCES & LEARNED PATTERNS — Apply these preferences to your output. These reflect how this physician writes notes, their preferred style, terminology, and corrections from past outputs. Adapt your response accordingly, but user instructions in the current prompt take priority if they conflict.]\n' + physicianMemories + '\n[END PREFERENCES]';
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const result = await callAI([
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{ role: 'system', content: prompt },
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{ role: 'user', content: context }
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], { model });
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res.json({ success: true, hpi: result.content, model: result.model });
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} catch (err) {
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res.status(500).json({ error: err.message });
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}
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});
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module.exports = router;
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