Imagine you are a DevOps engineer trying to quickly fix a sudden rise in your server’s CPU use. You need a Grafana dashboard fast, but writing PromQL queries is confusing. Or maybe you are a product manager who wants to see user engagement data but doesn’t know how to use Prometheus. That’s where VizGenie comes in. It’s a free AI tool that turns simple English commands like “Show error rates for checkout service last hour” into a ready-to-use Grafana dashboard within seconds.

Introduction

VizGenie is an AI-powered bridge between your questions and actionable data visualizations. By leveraging large language models (LLMs), it interprets natural language requests, generates accurate PromQL queries, builds Grafana dashboards, and deploys them automatically. Whether you’re monitoring Kubernetes clusters, tracking application performance, or analyzing business metrics, VizGenie eliminates the friction of manual query writing and dashboard setup.

Key Highlights:

🧠 AI-Driven: Translates conversational language into precise PromQL.
⚡ Instant Deployment: Auto-publishes dashboards to your Grafana instance.
🔌 Plug-and-Play: Works seamlessly with Prometheus and Grafana out of the box.

Why We Need VizGenie

  • Time is Precious: Developers spend hours debugging queries instead of solving problems.
  • Democratizing Data: Not everyone knows PromQL, but everyone deserves insights.
  • Human Error: Typos in complex queries lead to misleading graphs. Scalability: Manually creating dashboards for hundreds of services isn’t sustainable.
  • Future-Proofing: With plans to support Elasticsearch, Loki, and more, VizGenie grows with your stack.

Real-World Impact:

  • DevOps Teams: Debug faster with on-the-fly dashboards during incidents.
  • Product Managers: Track KPIs without waiting for engineering support.
  • Startups: Scale monitoring without hiring niche experts.

Try This: Get Started in 5 Minutes

1. Set Up Prerequisites

  • Get a Groq API Key (free via Groq Cloud).
  • Sign in as an org admin, go to Administration → Users and access Service accounts, click Add service account, enter a unique display name, and click Create
  • Ensure Docker/Python 3.x is installed.

2. Clone the Repo 

git clone https://github.com/vsion-x/vizgenie.git
cd vizgenie

3. Configure Environment

Create a .env at the project root with:

GROQ_API_KEY=
GRAFANA_KEY=
PROMETHEUS_HOST=http://localhost # default
GRAFANA_HOST=http://localhost:3000 # default

4. Spin Up the Test Environment (Docker‑Compose) 

docker-compose up

This will launch Grafana, Prometheus, Redis, and any other services defined in docker-compose.yml—giving you a full testing sandbox for VizGenie.

5. Launch the VizGenie UI (Streamlit)

In a new terminal (while your Docker stack is running), run:

pip install -r requirements.txt      # if you haven’t already
streamlit run main.py

Streamlit will open a browser tab with the VizGenie interface.

6. Ask and Visualize!

Type a query like:

“Plot memory usage for all containers over the last 6 hours.”

VizGenie will:
1️⃣ Generate PromQL for your Prometheus data.
2️⃣ Design a Grafana dashboard with relevant panels.
3️⃣ Deploy it to your Grafana instance.

Pro Tip: Use phrases like “Compare request latency between production and staging” for advanced comparisons!

Why You’ll Love It

  • No More Copy-Pasting Dashboards: Each query creates a tailored dashboard.
  • AI That Learns: The more you use it, the better it understands your metrics.
  • Open Source Freedom: Customize prompts, add data sources, or tweak the UI.

Final Thoughts

VizGenie isn’t just about saving time — it’s about making data accessible to everyone in your team. By turning language into visualizations, it breaks down silos between technical and non-technical users. Ready to transform how your team interacts with data?

👉 Star the project on GitHub

👉 Watch the demo video