--- title: DataVision AI emoji: ๐Ÿ“Š colorFrom: blue colorTo: indigo sdk: docker app_port: 7860 pinned: false ---
DataVision logo

DataVision AI

Autonomous analytics, business intelligence, AutoML, computer vision, and team collaboration in one platform.

Live application ยท Product user guide (PDF)

## What DataVision provides - Interactive dashboards with slicers, KPI cards, business charts, AI explanations, exports, and themes. - AI Analyst for grounded questions about uploaded datasets. - AutoML, predictions, forecasts, reports, vector search, and data pipelines. - Computer Vision for detection, classification, segmentation, pose estimation, and OCR. - Persistent collaboration with channels, replies, reactions, pinning, and message deletion. - Developer API keys, webhooks, usage reporting, and embed tools. ## Run locally Requirements: Python 3.11+, Node.js 20+, and PostgreSQL for persistent production data. ```bash # Backend cd backend python -m venv .venv .venv\Scripts\activate pip install -r requirements.txt python main.py # Frontend (in a second terminal) cd frontend npm install npm run dev ``` The frontend opens at `http://localhost:5173`. ## Configuration Create `backend/.env` with your production settings. Do not commit secrets. ```env DATABASE_URL=postgresql+asyncpg://user:password@host:5432/datavision GROQ_API_KEY=your_key JWT_SECRET=a_long_random_secret ENVIRONMENT=development CORS_ORIGINS=http://localhost:5173 ``` ## Deployment Pushes to `main` run the GitHub Actions workflows in `.github/workflows/`. Configure these GitHub secrets before deployment: - `HF_TOKEN` (Hugging Face write token) - Optional `HF_SPACE` (defaults to `datavision-ai/Datavision`) Set `DATABASE_URL`, `GROQ_API_KEY`, and `JWT_SECRET` in your Hugging Face Space settings. See [HUGGINGFACE_DEPLOYMENT.md](HUGGINGFACE_DEPLOYMENT.md) for the checklist. ## User guide The updated guide is available here: [DataVision AI Product User Guide](frontend/public/DataVision_AI_Product_User_Guide.pdf). ## Validation ```bash cd frontend npm run build ``` ```bash cd backend python -m py_compile main.py api/v1/endpoints/collaboration.py ```