serviette

Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.

⭐ 58,797 stars on GitHub · 🍴 1,510 forks · 📜 License: mit · 💻 Language: Python

What is serviette?

Self-hosted cloud storage — Dropbox/Google Drive equivalent but on your server. Full sync, share, and integration features.

Main components

No code. Configure everything in one YAML file (or generate it with
Any vector DB — 8 backends. DuckDB (embedded, zero setup — the default),
Zero-setup default. DuckDB is the default backend: an embedded
Live & incremental. Built on Pathway: additions, edits and deletions
Multiple sources. Local filesystem, Google Drive, S3/MinIO, SharePoint
Multimodal out of the box. Text, Office documents, PDFs (with tables
Reuses Pathway's LLM xpack. Parsers, splitters and embedders are used
Decoupled & scalable. Indexer and API server are independent processes

The biggest strength is extremely low per-GB cost vs commercial cloud — pay only VPS + disk, no bandwidth/file fees.

Best for SMB teams, freelancers, agencies sharing files with clients without size/bandwidth limits.

Topics: the project is tagged with popular topics:

🏷️ chromadb
🏷️ document-qa
🏷️ document-search
🏷️ duckdb
🏷️ live-data
🏷️ llm
🏷️ milvus
🏷️ mongodb
🏷️ no-code
🏷️ pathway

📸 Screenshots

Left: indexer PSS over time for corpora from 100 MB to 50 GB, from the run before the allocator tuning; every curve reaches its plateau in the first minutes and holds it for hours. Right: connector-worker extra memory across six corpus sizes follows ~318 bytes per watched file

Breakdown of the 10 GB corpus peak as measured in the run before the allocator tuning (8.8 GB): three quarters is the local PyTorch embedding stack across 8 workers; file-watch metadata is about 1.1 GB; supervisors and shared code make up the rest

Quick install

See the README for detailed install instructions. Most projects support Docker — if the repo has a Dockerfile, use:

git clone https://github.com/pathwaycom/serviette.git
cd serviette
docker build -t serviette .
docker run -d -p 8080:8080 serviette

Minimum system requirements

Component	Recommended
RAM	2048 MB
CPU	2 vCPU
Disk	25 GB SSD
OS	Ubuntu 22.04 LTS / Debian 12
Docker	24.0+

⚡ Deploy fast on VSIS

Use the VSIS VPS Lite 2GB RAM / 2 vCPU / 25GB SSD (~104k/tháng) plan from VSIS.NET — high-speed VN-based VPS, 24/7 support, ideal for running serviette smoothly.

🎯 Benefits:

One-command docker compose up -d deploy in 2 minutes
Dedicated IPv4, root access, unmetered domestic bandwidth
Daily snapshot backup
Free install assistance from the VSIS team

👉 See matching VPS plans at vsis.net

Resources

🔗 GitHub: pathwaycom/serviette
🌐 Homepage: https://pathway.com/developers/templates/
📚 Official docs: see README in the repo
💬 Community: GitHub Issues + Discussions

Article compiled from GitHub data on 15/10/2026. Star/fork counts may have changed — see live numbers via the GitHub link.