Setup & Installation
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This page describes the requirements and procedures for setting up and deploying the NeXifyAI platform. NeXifyAI utilizes a multi-layered architecture involving a Python-based FastAPI backend, a React frontend, and multiple database integrations including MongoDB, Supabase (PostgreSQL), and Qdrant for vector storage.
Sources: SETUP.md:3-7, SETUP.md:79-90, WORKSPACE.md:23-26
System Requirements
Before starting the installation, you must ensure your environment meets the following minimum version requirements:
| Component | Requirement |
|---|---|
| Python | 3.11+ |
| Node.js | 18+ (20+ recommended for Workspace) |
| MongoDB | Local instance or Atlas |
| Database | Supabase Project (PostgreSQL) |
| Vector DB | Qdrant (Local via Docker) |
Sources: SETUP.md:4-7, WORKSPACE.md:14-15
1. Environment Configuration
The platform requires several API keys and connection strings to operate. You must create .env files for each service by copying the provided templates.
# General setup
cp backend/.env.template backend/.env
# Workspace specific configuration
# Copy .env.example to each service directory
Sources: SETUP.md:11-12, WORKSPACE.md:20-21
Mandatory Configuration Keys
The backend will fail to start if the following keys are missing:
| Key | Service | Purpose |
|---|---|---|
MONGO_URL | MongoDB | Primary document storage |
ALT_SUPABASE_POSTGRESQL | Supabase | Relational data for Oracle/Audit |
ALT_SUPABASE_SERVICE_ROLE_KEY | Supabase API | Database administrative access |
NEXIFY_API_KEY | NeXify LLM | AI model connectivity |
ARCEE_API_KEY | Arcee AI | Master Orchestrator access |
MEM0_API_KEY | mem0 | Brain memory management |
SECRET_KEY | Internal | JWT signing (min 32 characters) |
Sources: SETUP.md:16-23, WORKSPACE.md:23-26
2. Backend Installation
The backend runs on FastAPI and requires Python 3.11.
- Navigate to the backend or service directory.
- Initialize a virtual environment:
python -m venv venv && source venv/bin/activate. - Install dependencies:
pip install -r requirements.txt. - Start the server:
uvicorn server:app --host 0.0.0.0 --port 8001 --reload.
Sources: SETUP.md:35-39, WORKSPACE.md:4-7
3. Frontend Installation
The frontend is built with React 18 and Vite.
- Navigate to the frontend or web application directory (e.g.,
apps/web). - Install packages:
npm installoryarn install. - Start the development server:
npm startoryarn start.
Sources: SETUP.md:43-46, WORKSPACE.md:10-11, apps/web/README.md:27-31
4. Database & Infrastructure Setup
The platform initializes database schemas automatically upon the first start.
Supabase Schema
The system checks for the existence of several core tables. If missing, they must be created manually via the Supabase Dashboard:
oracle_tasks: Manages AI agent task lifecycles.ai_agents: Stores agent definitions.audit_logs: Tracks system and agent changes.knowledge_base: Stores structured expertise.
Sources: SETUP.md:62-65
Vector Brain (Qdrant)
NeXifyAI uses Qdrant for high-dimensional vector storage. This should be run via Docker.
The diagram shows the relationship between the Qdrant vector database and the specific collections used for the platform's "Brain" functionality.
Sources: WORKSPACE.md:23-26, apps/web/public/health.html:81-85
5. Deployment & Containerization
Docker Deployment
For production environments or Coolify deployments, use the following Docker structure for the backend:
FROM python:3.11-slim
WORKDIR /app
COPY backend/ .
RUN pip install -r requirements.txt
CMD ["uvicorn", "server:app", "--host", "0.0.0.0", "--port", "8001"]
Sources: SETUP.md:55-58
Build Optimizations
The frontend build process includes several optimizations to manage bundle size:
- Manual Chunking: Separates large libraries like
three.js,framer-motion, and@unovis. - Sourcemaps: Disabled in production for security and performance.
- Vercel: Recommended platform for frontend hosting.
Sources: apps/web/README.md:36-39, apps/web/README.md:62-64
6. Verification and Health Checks
After installation, verify the system status by accessing the health endpoint:
curl http://localhost:8001/api/health
A successful installation returns a "healthy" status for all critical services including MongoDB, Supabase, and the AI providers (NeXify, Arcee, mem0).
Sources: SETUP.md:50-51, apps/web/public/health.html:110-115
Health Status Flow
The following sequence shows how the health dashboard retrieves system status.
The diagram illustrates the polling mechanism used by the health dashboard to monitor service availability and compliance scores.
Sources: apps/web/public/health.html:105-130, SETUP.md:52-60
Summary
Setting up NeXifyAI requires a coordinated configuration of Python and Node.js environments alongside multiple data providers. Proper environment key configuration is the most critical step for successful service orchestration. Once configured, the platform utilizes automated schema checks and health monitoring to maintain operative excellence.
Sources: SETUP.md:79-90, WORKSPACE.md:29-30