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https://dev.azure.com/globalhealthx/EMR/_git/helix-engage-server
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feat: team module, multi-stage Dockerfile, doctor utils, AI config overhaul
- Team module: POST /api/team/members (in-place employee creation with temp password + Redis cache), PUT /api/team/members/:id, GET temp password endpoint. Uses signUpInWorkspace — no email invites. - Dockerfile: rewritten as multi-stage build (builder + runtime) so native modules compile for target arch. Fixes darwin→linux crash. - .dockerignore: exclude dist, node_modules, .env, .git, data/ - package-lock.json: regenerated against public npmjs.org (was pointing at localhost:4873 Verdaccio — broke docker builds) - Doctor utils: shared DOCTOR_VISIT_SLOTS_FRAGMENT + normalizeDoctors helper for visit-slot-aware queries across 6 consumers - AI config: full admin CRUD (GET/PUT/POST reset), workspace-scoped setup-state with workspace ID isolation, AI prompt defaults overhaul - Agent config: camelCase field fix for SDK-synced workspaces - Session service: workspace-scoped Redis key prefixing for setup state - Recordings/supervisor/widget services: updated to use doctor-utils shared fragments instead of inline visitingHours queries Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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@@ -235,11 +235,11 @@ The CUSTOMER typically:
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patientSatisfaction: z.string().describe('One-line assessment of patient satisfaction'),
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callOutcome: z.string().describe('One-line summary of what was accomplished'),
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}),
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system: `You are a call quality analyst for Global Hospital Bangalore.
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Analyze the following call recording transcript and provide structured insights.
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Be specific, brief, and actionable. Focus on healthcare context.
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${summary ? `\nCall summary: ${summary}` : ''}
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${topics.length > 0 ? `\nDetected topics: ${topics.join(', ')}` : ''}`,
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system: this.aiConfig.renderPrompt('recordingAnalysis', {
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hospitalName: process.env.HOSPITAL_NAME ?? 'the hospital',
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summaryBlock: summary ? `\nCall summary: ${summary}` : '',
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topicsBlock: topics.length > 0 ? `\nDetected topics: ${topics.join(', ')}` : '',
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}),
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prompt: transcript,
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maxOutputTokens: 500,
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});
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