Force-directed graph · gemini-3.5-flash-lite
Using the pre-provided d3.min.js (global d3), render an interactive force-directed graph of about 40 nodes in several clusters with draggable nodes, hover highlighting of neighbors, and zoom/pan. Define the sample nodes and links inline.
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Using the pre-provided d3.min.js (global d3), render an interactive force-directed graph of about 40 nodes in several clusters with draggable nodes, hover highlighting of neighbors, and zoom/pan. Define the sample nodes and links inline.
{"command":"ls -la"}total 276 drwxr-sr-x. 2 node node 23 Aug 1 17:43 . drwxrwsrwx. 3 root node 16 Aug 1 17:43 .. -rw-r--r--. 1 node node 279706 Aug 1 17:43 d3.min.js
thinking
**Initiating App Design** I've confirmed the presence of `d3.min.js`, and I'm ready to begin designing an interactive force-directed graph web app. I'm aiming for a polished, single-page application, and I'll keep everything self-contained within `index.html`. This means all CSS and JavaScript will be inline within the HTML file. **Defining Data Clusters** I'm now focusing on data generation for the force-directed graph. I've decided on four clusters, each with ten nodes, to represent different areas. The intention is to visualize connections within these clusters. I'm building out a list with frontend, backend, devops, and data science for the first iteration. I'll need to define the connections between the nodes within each cluster. **Expanding Data Categories** I've expanded the data categories for the force-directed graph's second iteration. Cluster 1 will now include frontend, backend (FastAPI, Go, Rust, Java, Spring, GraphQL, PostgreSQL), etc. Cluster 2 has been updated to DevOps (Docker, Kubernetes, Terraform, AWS, GCP, CI/CD, Nginx, Linux, Prometheus, Grafana), etc. Finally, Cluster 3 is Data Science (Pandas, NumPy, PyTorch, TensorFlow, Scikit-Learn, Jupyter, Spark, Airflow, Tableau, Snowflake). I will also focus on defining intra-cluster and inter-cluster links. I also have plans for zooming and panning with `d3.zoom()`, node dragging using `d3.drag()`, hover highlighting, and clicking nodes to open a side panel. I will also incorporate search functionality, and general controls for a more interactive experience.
index.html (30927 bytes)Successfully wrote 30927 bytes to index.html
{"command":"ls -lh index.html"}-rw-r--r--. 1 node node 31K Aug 1 17:43 index.html
I have successfully built and written the single-page interactive force-directed graph web app into `index.html`. ### Features Included: 1. **Self-Contained & Offline-Ready**: Uses the pre-provided `d3.min.js` locally with no external CDN or network requests. 2. **~40 Nodes in 4 Clusters**: - **Frontend** (React, Vue, Svelte, Angular, TypeScript, Tailwind, Webpack, Vite, Jest, Cypress) - **Backend** (Node.js, Express, Python, FastAPI, Go, Rust, Java, Spring, GraphQL, PostgreSQL) - **DevOps & Cloud** (Docker, Kubernetes, Terraform, AWS, GCP, GitHub Actions, Nginx, Linux, Prometheus, Grafana) - **Data & AI** (Pandas, NumPy, PyTorch, TensorFlow, Scikit-Learn, Jupyter, Apache Spark, Airflow, Tableau, Snowflake) 3. **Interactivity**: - **Zoom & Pan**: Smooth zooming and panning across the SVG canvas using `d3.zoom`. - **Draggable Nodes**: Nodes can be dragged around with physics simulation update and position pinning. - **Hover Highlighting**: Hovering over any node highlights it, its immediate neighbors, and connected links while cleanly dimming unrelated elements. - **Node Details & Sidebar**: Clicking any node opens a detailed side panel showing its description, cluster association, and interactive connection links that let you traverse the graph. - **Cluster Legend Filtering**: Clicking a cluster legend item filters/highlights nodes belonging to that cluster. - **Search & Controls**: Search box to instantly find and inspect nodes, plus "Reset View" and "Reheat" simulation buttons.
TAKE IT TO CODE
A single self-contained HTML file — copy it and open in any browser, or reuse the prompt with your own pi-agent run.
RUN
EVALUATION
Force-directed clustered graph with drag and zoom/pan working; click didn't visibly select; keyboard inputs had no effect (expected).
Vision grade · anthropic/claude-sonnet-5
MEASUREMENTS
Raw readings from the capture, not a verdict — the grade above is the only judgement. Percentages are how much of the screen changed; the measure under-reports sparse motion on a dark background.