Employee Server (Mongo + AI Pipeline)

Architecture is now:

1. AI Planner
2. Mongo Executor
3. AI Analysis Result

No SQL path is used.

MongoDB

Default URI:

mongodb://admin:password@localhost:27017

On startup, the server seeds large dummy administration-style data (1500 employees) into:

• DB: employee_admin
• Collection: employees

Common model environment

Create .env (or set environment variables):

AI_PROVIDER=nvidia
AI_TIMEOUT_MS=30000

MONGO_URI=mongodb://admin:password@localhost:27017
MONGO_DB_NAME=employee_admin
MONGO_COLLECTION=employees

OLLAMA_HOST=http://127.0.0.1:11434
OLLAMA_MODEL=qwen2.5:3b
OLLAMA_CHAT_PATH=/api/chat

OPENAI_API_KEY=
OPENAI_MODEL=gpt-4.1-mini
OPENAI_BASE_URL=https://api.openai.com

CLAUDE_API_KEY=
CLAUDE_MODEL=claude-3-5-sonnet-20241022
CLAUDE_BASE_URL=https://api.anthropic.com
CLAUDE_MAX_TOKENS=2048

NVIDIA_API_KEY=
NVIDIA_MODEL=google/gemma-4-31b-it
NVIDIA_BASE_URL=https://integrate.api.nvidia.com
NVIDIA_MAX_TOKENS=16384
NVIDIA_TOP_P=0.95
NVIDIA_ENABLE_THINKING=true

Supported providers:

• ollama
• openai
• claude
• nvidia

Run

npm install
node test-client.mjs --tests

Interactive:

node test-client.mjs

Example queries

• Who has the highest salary?
• Who earns the least?
• What is the difference between highest and lowest salary?
• What is the average salary?
• How many employees are there?
• List employees in Administration