ZaloCRM is a production-grade, multi-tenant customer relationship management system deeply integrated with the Vietnamese Zalo messaging platform. It serves real-estate sales teams by unifying contact management, real-time chat, lead scoring/automation, appointment scheduling, media library, RBAC, privacy controls, and third-party integrations (Facebook Lead Ads, Telegram bridge, Google Sheets). The system is deployed as a Node.js/Fastify monolith with PostgreSQL (Prisma ORM), Redis (BullMQ queues, rate limiting), MinIO/S3-compatible storage, and Socket.IO for real-time events. It relies on the unofficial Zalo SDK (zca-js) for messaging operations and supports multiple AI providers (Anthropic, Gemini, OpenAI) for reply drafting, sentiment analysis, and appointment parsing. The architecture follows an open-core model: the Community edition ships with extension stubs (`_ee-stubs`) that are replaced in the Enterprise edition. Key entry points include auth routes (JWT with rotating refresh tokens), Zalo account management (QR login, reconnect), friend sync (cron-driven diff-then-emit), and a rich chat operations module (reactions, edits, forwards). Background jobs handle lead pool assignment, care session monitoring, scoring decay, and engagement pattern classification. The system maintains strong data invariants through Prisma extensions (tenant context, RLS preparation, safe-contact-write) and a custom privacy layer that redacts private-nick messages based on viewer role. Data flows center on the Zalo account pool: inbound messages are ingested via socket listeners or friend sync, routed to conversations via a global-aware resolver, and triggers automation hooks (care sessions, auto-tags, sequence advancement). Analytics are derived from daily engagement materialization and scoring engine (4 dimensions with weights). External dependencies are managed via Redis-backed rate limiters, while storage operations are abstracted behind a `StorageDriver` interface with local/R2 implementations. The codebase is actively maintained with daily commits, extensive Prisma migrations, and a comprehensive test suite covering privacy invariants, merge policies, and regression scenarios.
This repository contains Dreamhouse, a Salesforce sample application for real estate property management built with Lightning Web Components (LWC) and Apex. It demonstrates key Salesforce platform capabilities including custom objects (Property__c, Broker__c), flexible page layouts, Lightning Message Service for inter-component communication, and mobile features like barcode scanning and geolocation. The application provides a property explorer with filtering, pagination, map visualization (using Leaflet), and a property creation flow with geocoding via OpenStreetMap. It also includes sample data import, accessibility testing, and comprehensive CI/CD pipelines. The codebase is well-structured with separate Apex controllers, reusable LWC components, and Jest unit tests, representing a professional implementation of Salesforce development best practices. While primarily an application, it includes sample data (JSON files) that could be considered a minor data aspect, but the dominant character is application.