NVIDIA-AI-Blueprints/video-search-and-summarization
NVIDIA AI Blueprint for video search and summarization (VSS) is a GPU-accelerated reference architecture for building video analytics agents with real-time verified alerts, visual Q&A, and automated reporting. The VSS Blueprint uses vision language models (VLMs) such as NVIDIA Cosmos, LLMs such as NVIDIA Nemotron, RAG, and NVIDIA NIMs.
⚡ Executive Summary & Quick Facts
Authoritative Sourcevideo-search-and-summarization is video-search-and-summarization is an open-source project written in Python: NVIDIA AI Blueprint for video search and summarization (VSS) is a GPU-accelerated reference architecture for building video analytics agents with real-time verified alerts, visual Q&A, and automated reporting. The VSS Blueprint uses vision language models (VLMs) such as NVIDIA Cosmos, LLMs such as NVIDIA Nemotron, RAG, and NVIDIA NIMs..
| Repository | NVIDIA-AI-Blueprints/video-search-and-summarization ↗ |
|---|---|
| Primary Category | computer vision |
| Language & Stack | Python |
| Software License | Apache-2.0 |
| Community Traction | ★ 1.9K stars · ⑂ 412 forks · #4,599 globally |
| Maintenance | ● Active (Last commit: Oct 19, 2026) · 244 open issues |
| Target Audience | Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads. |
Star History
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+48
STARS · LAST 30 DAYS
2
PER DAY
#630
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +38 | +48 | +180 |
| Per day | 5 | 2 | 2 |
| Forks gained | +11 | +8 | +21 |
video-search-and-summarization gained 48 stars in the last 30 days, about 2 a day, and now has 1.9K. It is about 2 years old and has averaged roughly 967 stars a year. It ranks #630 among Python repositories and #4,599 across all languages on GitHubRepo.
Trending Record
3
DAYS ON TRENDING
#4166
BEST RANK
Oct 19, 2026
FIRST APPEARANCE
Active
STATUS TODAY
video-search-and-summarization has maintained a continuous presence across global trending indexes, peaking at #4166. Below is the 30-day activity profile:
💡 Overview
video-search-and-summarization is an open-source project written in Python: NVIDIA AI Blueprint for video search and summarization (VSS) is a GPU-accelerated reference architecture for building video analytics agents with real-time verified alerts, visual Q&A, and automated reporting. The VSS Blueprint uses vision language models (VLMs) such as NVIDIA Cosmos, LLMs such as NVIDIA Nemotron, RAG, and NVIDIA NIMs.
Engineered for speed, consistency, and developer ease, it solves common hurdles in computer-vision, generative-ai, long-video-understanding. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install video-search-and-summarization⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
video-search-and-summarization coordinates its core functionality through a modular Python 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 video-search-and-summarization.
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
Install video-search-and-summarization using your package manager: `pip install video-search-and-summarization`
Initialize your project workspace or configuration file for video-search-and-summarization.
Import video-search-and-summarization into your codebase or invoke it directly from your terminal.
Execute your test suite or run `video-search-and-summarization --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
NVIDIA-AI-Blueprints/video-search-and-summarization is currently ranked #4,599 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
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Frequently Asked Questions
What does video-search-and-summarization do? +
NVIDIA AI Blueprint for video search and summarization (VSS) is a GPU-accelerated reference architecture for building video analytics agents with real-time verified alerts, visual Q&A, and automated reporting. The VSS Blueprint uses vision language models (VLMs) such as NVIDIA Cosmos, LLMs such as NVIDIA Nemotron, RAG, and NVIDIA NIMs.
What language is video-search-and-summarization written in? +
The primary language is Python. Topics include: computer-vision, generative-ai, long-video-understanding, model-context-protocol, multimodal-ai.
Is video-search-and-summarization actively maintained? +
Yes, the last recorded push was on Oct 19, 2026 with 244 open issues being tracked.
How many stars does video-search-and-summarization have? +
video-search-and-summarization has 1,933 stars and 412 forks on GitHub.
How does video-search-and-summarization rank among GitHub repositories? +
With 1,933 stars, NVIDIA-AI-Blueprints/video-search-and-summarization is ranked #4,599 globally across all repositories tracked on GitHubRepo and #630 among Python projects.
What license is video-search-and-summarization distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
