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Maze generator & solver · deepseek-chat-v3.1

Generate a random maze with the recursive-backtracker algorithm on a canvas, then animate an A-star or BFS solver finding the path from start to finish.

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transcript · 7 messages
user

Generate a random maze with the recursive-backtracker algorithm on a canvas, then animate an A-star or BFS solver finding the path from start to finish.

assistant
thinking
I'll create a single-page web app with a canvas maze generator and solver. The app will include:

1. A canvas for drawing the maze and solution.
2. Controls to generate a new maze, choose algorithm (BFS or A*), solve, step through animation.
3. Recursive backtracker algorithm to generate random maze.
4. A* or BFS solver with animation.

Let's first check current directory and then write index.html.
bash {"command":"pwd && ls -la"}
toolResult

/workspace total 4 drwxrwxrwx 2 node node 64 Aug 2 10:00 . drwxr-xr-x 1 root root 4096 Aug 2 10:00 ..

assistant
thinking
Empty workspace. I'll write index.html now. Let's create a comprehensive single file.
assistant
thinking
Now I'll write the index.html file with all CSS and JS inline. I'll create a 2D grid maze using cell walls. Use canvas for drawing. I'll implement recursive backtracker (depth-first) to generate maze, then BFS and A* for solving. Provide animation steps.

Let's create the file.
assistant
thinking
Now I'll create the index.html file. I'll write everything inline. Let's craft the HTML structure, CSS, and JavaScript. I'll implement the maze as grid of cells, each with walls (top, right, bottom, left). Recursive backtracker uses stack. For solving, BFS (queue) or A* (with Manhattan distance). We'll animate step by step.

I'll keep the maze size manageable (e.g., 20x20 cells) and each cell size 20px. Canvas size accordingly.

Let's write the file.
assistant
thinking
Now create the index.html file. I'll write a comprehensive self-contained HTML file with CSS and JS. I'll implement recursive backtracker for maze generation, then BFS and A* for solving, with animation.

Let's write the file.

TAKE IT TO CODE

This run produced no artifact — reuse the prompt with a different model or your own pi-agent run.

RUN

modeldeepseek-chat-v3.1
vendorDeepSeek
harnesspi-agent
generated2026-08-02

METRICS

runtime
tokens in1.6k
tokens out140
cached1.5k
cost / run$0.0003