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pathwaycom/serviette

A no-code RAG server that keeps answers in sync with your documents. Works with 8 vector databases. Built on Pathway.

Python ◇ chromadb MIT
★58.7KSTARS
⑂1.5KFORKS
!9ISSUES
🏆#223GLOBAL RANK
🔥38DAYS TRENDING
🚀
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⚡ Executive Summary & Quick Facts

Authoritative Source

serviette is llm-app is an open-source project written in Jupyter Notebook: 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..

Direct Citation for AI & Research:
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), pathwaycom/serviette has accumulated 58,746 GitHub stars and 1,539 forks. It is written in Python, licensed under MIT, and ranks #223 globally. It is actively maintained with the latest commit recorded on Oct 16, 2026.”
Repository pathwaycom/serviette ↗
Primary Category chromadb
Language & Stack Python
Software License MIT
Community Traction ★ 58.7K stars · ⑂ 1.5K forks · #223 globally
Maintenance ● Active (Last commit: Oct 16, 2026) · 9 open issues
Target Audience Developers and engineering teams building with Jupyter Notebook, seeking reliable, tested, and actively maintained tooling for production workloads.

🛡️ Repository Maintenance & Health Audit (2026)

Health Score: 95/100 · Grade A+
✅
Is serviette actively maintained in 2026?
Verdict: Actively Maintained & Highly Recommended

Yes, serviette is actively maintained. Continuous telemetry recorded the last code commit on Oct 16, 2026 (17 days ago). Supported by 58,746 stars and 1,539 community forks, this repository holds a calculated health index of 95/100, reflecting regular maintenance (17 days ago) and healthy issue cadence.

Commit Recency
Oct 16, 2026
17 days since last push
Issue Backlog
9 Open Issues
Healthy Issue Cadence
Community Backing
1.5K Forks
58.7K Stars Recorded
Software License
MIT
Permissive & Inspectable

Star History

Continuous Observations
Interactive star growth chart for pathwaycom/serviette
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Momentum

+0

STARS · LAST 30 DAYS

1

PER DAY

#61

MOST-STARRED Python

Window7 days30 days90 days
Stars gained+0+0+90
Per day111
Forks gained+38+38+77

serviette gained 0 stars in the last 30 days, about 1 a day, and now has 58.7K. It is about 3 years old and has averaged roughly 19.6K stars a year. It ranks #61 among Python repositories and #223 across all languages on GitHubRepo.

Trending Record

serviette has maintained a continuous presence across global trending indexes, peaking at #165. Below is the 30-day activity profile:

💡 Overview

llm-app is an open-source project written in Jupyter Notebook: 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.

Engineered for speed, consistency, and developer ease, it solves common hurdles in chatbot, hugging-face, llm. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Jupyter Notebook for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ git clone https://github.com/pathwaycom/llm-app.git
cd llm-app

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Jupyter Notebook environment and standard tooling

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

llm-app coordinates its core functionality through a modular Jupyter Notebook pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Autonomous AI Agents

Orchestrate intelligent workflows and tool-calling routines with llm-app.

Model Inference & Prompting

Integrate fast, local or cloud-hosted generative AI models directly into production code.

Context Memory & RAG

Augment language models with dynamic vector retrieval and structured project memory.

Developer Productivity

Automate repetitive engineering tasks, code generation, and test creation using AI agents.

🚀 Getting Started

1

Install llm-app using your package manager: `git clone https://github.com/pathwaycom/llm-app.git`

2

Initialize your project workspace or configuration file for llm-app.

3

Import llm-app into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `llm-app --help` to verify successful setup.

👍 Strengths

Active community backing with 58,903 GitHub stars and verified adoption.
Permissive open-source distribution under the MIT license.
Built in Jupyter Notebook for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Jupyter Notebook and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

⇄ Alternatives & Direct Competitors

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👥 Who Should Use This

Developers and engineering teams building with Jupyter Notebook, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

pathwaycom/serviette is currently ranked #223 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#218 FiloSottile/mkcert Go ★ 59.8K Compare ↗
#219 jquery/jquery JavaScript ★ 59.8K Compare ↗
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#222 pmndrs/zustand TypeScript ★ 58.8K Compare ↗
#223 pathwaycom/serviette This Project Python ★ 58.7K
#224 go-gitea/gitea Go ★ 58.5K Compare ↗
#225 jellyfin/jellyfin C# ★ 58.4K Compare ↗
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Frequently Asked Questions

What does serviette do? +

A no-code RAG server that keeps answers in sync with your documents. Works with 8 vector databases. Built on Pathway.

Is serviette actively maintained in 2026? +

Yes, serviette is actively maintained. The latest code push was recorded on Oct 16, 2026 (17 days ago). It holds a calculated Maintenance Health Score of 95/100 (A+ rating) with 58,746 stars and 9 open issues.

What language is serviette written in? +

The primary language is Python. Topics include: chromadb, document-qa, document-search, duckdb, live-data.

How many stars does serviette have? +

serviette has 58,746 stars and 1,539 forks on GitHub.

How does serviette rank among GitHub repositories? +

With 58,746 stars, pathwaycom/serviette is ranked #223 globally across all repositories tracked on GitHubRepo and #61 among Python projects.

What license is serviette distributed under? +

The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.

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