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Corey Johnson 2025-07-14 14:47:30 -07:00
parent 90f6fb7c51
commit 6dbbd74c01
15 changed files with 402 additions and 168 deletions
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@ -59,20 +59,6 @@
"typescript": "^5",
},
},
"packages/project-whitespace": {
"name": "@workspace/project-whitespace",
"dependencies": {
"@workshop/nano-remix": "workspace:*",
"@workshop/shared": "workspace:*",
"hono": "catalog:",
},
"devDependencies": {
"@types/bun": "latest",
},
"peerDependencies": {
"typescript": "^5",
},
},
"packages/query": {
"name": "@workshop/query",
"dependencies": {
@ -101,7 +87,7 @@
"@openai/agents": "^0.0.10",
"discord.js": "^14.19.3",
"luxon": "^3.6.1",
"zod": "^3.25.57",
"zod": "3.25.67",
},
"devDependencies": {
"@types/bun": "latest",
@ -148,6 +134,20 @@
"@types/bun": "latest",
},
},
"packages/whiteboard": {
"name": "@workshop/whiteboard",
"dependencies": {
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"@openai/agents": "^0.0.11",
"@workshop/nano-remix": "workspace:*",
"@workshop/shared": "workspace:*",
"hono": "catalog:",
"zod": "3.25.67",
},
"devDependencies": {
"@types/bun": "latest",
},
},
},
"catalog": {
"hono": "^4.8.0",
@ -159,13 +159,13 @@
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@ -179,9 +179,11 @@
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@ -189,7 +191,7 @@
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@ -209,11 +211,11 @@
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@ -237,10 +239,12 @@
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"@workspace/project-whitespace": ["@workspace/project-whitespace@workspace:packages/project-whitespace"],
"@workshop/whiteboard": ["@workshop/whiteboard@workspace:packages/whiteboard"],
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@ -285,7 +293,7 @@
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@ -349,9 +357,9 @@
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"@modelcontextprotocol/sdk/raw-body/http-errors/depd": ["depd@2.0.0", "", {}, "sha512-g7nH6P6dyDioJogAAGprGpCtVImJhpPk/roCzdb3fIh61/s/nPsfR6onyMwkCAR/OlC3yBC0lESvUoQEAssIrw=="],
@ -972,5 +958,7 @@
"@modelcontextprotocol/sdk/raw-body/http-errors/setprototypeof": ["setprototypeof@1.2.0", "", {}, "sha512-E5LDX7Wrp85Kil5bhZv46j8jOeboKq5JMmYM3gVGdGH8xFpPWXUMsNrlODCrkoxMEeNi/XZIwuRvY4XNwYMJpw=="],
"@modelcontextprotocol/sdk/raw-body/http-errors/statuses": ["statuses@2.0.1", "", {}, "sha512-RwNA9Z/7PrK06rYLIzFMlaF+l73iwpzsqRIFgbMLbTcLD6cOao82TaWefPXQvB2fOC4AjuYSEndS7N/mTCbkdQ=="],
"@workshop/whiteboard/@openai/agents/@openai/agents-realtime/ws": ["ws@8.18.3", "", { "peerDependencies": { "bufferutil": "^4.0.1", "utf-8-validate": ">=5.0.2" }, "optionalPeers": ["bufferutil", "utf-8-validate"] }, "sha512-PEIGCY5tSlUt50cqyMXfCzX+oOPqN0vuGqWzbcJ2xvnkzkq46oOpz7dQaTDBdfICb4N14+GARUDw2XV2N4tvzg=="],
}
}

25
packages/iago/bun.lock
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@ -1,25 +0,0 @@
{
"lockfileVersion": 1,
"workspaces": {
"": {
"name": "iago",
"devDependencies": {
"@types/bun": "latest",
},
"peerDependencies": {
"typescript": "^5",
},
},
},
"packages": {
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}
}

2
packages/nano-remix/tsconfig.json
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@ -1,7 +1,7 @@
{
"compilerOptions": {
// Environment setup & latest features
"lib": ["ESNext", "dom"],
"lib": ["ESNext", "DOM"],
"target": "ESNext",
"module": "Preserve",
"moduleDetection": "force",

8
packages/project-whiteboard/src/routes/index.tsx
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@ -1,8 +0,0 @@
export default function Index() {
return (
<div>
<h1>PROJECT WHITEBOARD</h1>
<img src="/whiteboard.jpeg" alt="Project Whiteboard" />
</div>
)
}

33
packages/query/bun.lock
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@ -1,33 +0,0 @@
{
"lockfileVersion": 1,
"workspaces": {
"": {
"name": "query",
"dependencies": {
"@planetscale/database": "^1.19.0",
"reflect-metadata": "^0.2.2",
},
"devDependencies": {
"@types/bun": "latest",
},
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"packages": {
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"undici-types": ["undici-types@6.21.0", "", {}, "sha512-iwDZqg0QAGrg9Rav5H4n0M64c3mkR59cJ6wQp+7C4nI0gsmExaedaYLNO44eT4AtBBwjbTiGPMlt2Md0T9H9JQ=="],
}
}

2
packages/spike/package.json
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@ -15,7 +15,7 @@
"@openai/agents": "^0.0.10",
"discord.js": "^14.19.3",
"luxon": "^3.6.1",
"zod": "^3.25.57"
"zod": "3.25.67"
},
"devDependencies": {
"@types/luxon": "^3.6.2",

1
packages/whiteboard/.env.example Normal file
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@ -0,0 +1 @@
GEMINI_API_KEY=

0
packages/project-whiteboard/.gitignore → packages/whiteboard/.gitignore vendored
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0
packages/project-whiteboard/README.md → packages/whiteboard/README.md
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12
packages/project-whiteboard/package.json → packages/whiteboard/package.json
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@ -1,5 +1,5 @@
{
"name": "@workshop/project-whiteboard",
"name": "@workshop/whiteboard",
"module": "index.ts",
"type": "module",
"private": true,
@ -9,14 +9,14 @@
"subdomain:dev": "bun run --hot src/server.ts"
},
"dependencies": {
"@workshop/shared": "workspace:*",
"@google/genai": "^1.9.0",
"@openai/agents": "^0.0.11",
"@workshop/nano-remix": "workspace:*",
"hono": "catalog:"
"@workshop/shared": "workspace:*",
"hono": "catalog:",
"zod": "3.25.67"
},
"devDependencies": {
"@types/bun": "latest"
},
"peerDependencies": {
"typescript": "^5"
}
}

0
packages/project-whiteboard/public/whiteboard.jpeg → packages/whiteboard/public/whiteboard.jpeg
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157
packages/whiteboard/src/ai.ts Normal file
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@ -0,0 +1,157 @@
import { GoogleGenAI, Type } from "@google/genai"
import { z, ZodObject } from "zod"
import { Agent, run, user, type AgentInputItem } from "@openai/agents"
export const getGeminiResponse = async <T = StructuredResponse>(
imageArrayBuffer: ArrayBuffer,
prompt: string
): Promise<T | undefined> => {
try {
const ai = new GoogleGenAI({})
const base64ImageData = Buffer.from(imageArrayBuffer).toString("base64")
const contents = [
{
inlineData: {
mimeType: "image/jpeg",
data: base64ImageData,
},
},
{ text: prompt },
]
const response = await ai.models.generateContent({
model: "gemini-2.5-pro",
contents: contents,
config: {
responseMimeType: "application/json",
responseSchema: whiteboardSchema,
},
})
console.log(`🌭 i am starting`)
const responseText = response.text
if (!responseText) {
throw new Error("No response received from Gemini")
}
try {
return JSON.parse(responseText)
} catch (parseError) {
console.error("Failed to parse JSON response:", responseText)
console.error("Parse error:", parseError)
return undefined
}
} catch (error) {
console.error("Error generating structured AI response:", error)
return undefined
}
}
// Zod schema for structured response
const StructuredResponseSchema = z.object({
description: z.string(),
summary: z.string(),
elements: z.array(
z.object({
type: z.string(),
box_2d: z.object({
ymin: z.number().describe("Normalized ymin coordinate (0-1000)"),
xmin: z.number().describe("Normalized xmin coordinate (0-1000)"),
ymax: z.number().describe("Normalized ymax coordinate (0-1000)"),
xmax: z.number().describe("Normalized xmax coordinate (0-1000)"),
}),
label: z.string(),
})
),
})
export const getOpenAIResponse = async <T = StructuredResponse>(
imageArrayBuffer: ArrayBuffer,
prompt: string
): Promise<T | undefined> => {
try {
const base64ImageData = Buffer.from(imageArrayBuffer).toString("base64")
// Create an agent without outputType for now
const agent = new Agent({
name: "Whiteboard Analyzer",
outputType: StructuredResponseSchema,
model: "gpt-4o",
instructions: prompt,
})
// Create input with image and prompt
const input: AgentInputItem[] = [
user([
{
type: "input_image",
image: `data:image/jpeg;base64,${base64ImageData}`,
},
]),
]
const result = await run(agent, input)
if (!result.finalOutput) {
throw new Error("No response received from OpenAI Agent")
}
return result.finalOutput as T
} catch (error) {
console.error("Error generating structured AI response:", error)
return
}
}
export type StructuredResponse = z.infer<typeof StructuredResponseSchema>
const whiteboardSchema = {
type: Type.OBJECT,
properties: {
description: {
type: Type.STRING,
},
summary: {
type: Type.STRING,
},
elements: {
type: Type.ARRAY,
items: {
type: Type.OBJECT,
properties: {
type: {
type: Type.STRING,
},
box_2d: {
type: Type.OBJECT,
properties: {
ymin: {
type: Type.NUMBER,
description: "Normalized ymin coordinate (0-1000)",
},
xmin: {
type: Type.NUMBER,
description: "Normalized xmin coordinate (0-1000)",
},
ymax: {
type: Type.NUMBER,
description: "Normalized ymax coordinate (0-1000)",
},
xmax: {
type: Type.NUMBER,
description: "Normalized xmax coordinate (0-1000)",
},
},
required: ["ymin", "xmin", "ymax", "xmax"],
},
label: {
type: Type.STRING,
},
},
required: ["type", "box_2d", "label"],
},
},
},
required: ["description", "summary", "elements"],
}

154
packages/whiteboard/src/routes/index.tsx Normal file
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@ -0,0 +1,154 @@
import { ensure } from "@workshop/shared/utils"
import { useAction, Form } from "@workshop/nano-remix"
import { useEffect, useRef, useState } from "hono/jsx"
import { getGeminiResponse } from "../ai"
const categories = ["hand drawn circle", "hand drawn square", "hand drawn arrow"]
const prompts = {
default: `Detect all of the of the following objects: ${categories}. The box_2d should be an object with ymin, xmin, ymax, xmax properties normalized to 0-1000.`,
simple: `Detect the 2d bounding boxes of the following objects: ${categories}.`,
}
export const action = async (req: Request, params: {}) => {
const url = new URL(req.url)
const imageUrl = new URL("whiteboard.jpeg", url.origin).toString()
const imageResponse = await fetch(imageUrl)
const imageBuffer = await imageResponse.arrayBuffer()
const response = await getGeminiResponse(imageBuffer, prompts.default)
return {
summary: response?.summary,
description: response?.description,
elements: response?.elements || [],
}
}
export default function Index() {
const canvasRef = useRef<HTMLCanvasElement>(null)
const [image, setImage] = useState<HTMLImageElement | null>(null)
const { data, error, loading } = useAction<typeof action>()
useEffect(() => {
const img = new Image()
img.onload = () => {
setImage(img)
ensure(canvasRef.current, "Canvas ref must be set before loading image")
canvasRef.current.width = img.width
canvasRef.current.height = img.height
}
img.src = "/whiteboard.jpeg"
}, [])
useEffect(() => {
const canvas = canvasRef.current
const ctx = canvas?.getContext("2d")
if (!image) return
ensure(canvas, "Canvas ref must be set before drawing")
ensure(ctx, "Canvas context must be available before drawing")
ctx.clearRect(0, 0, canvas.width, canvas.height)
ctx.drawImage(image, 0, 0)
// Draw AI detected elements with box_2d format
data?.elements.forEach((element, index) => {
const { ymin, xmin, ymax, xmax } = element.box_2d
ensure(ymin && xmin && ymax && xmax, "Box 2D coordinates must be defined")
// Convert normalized coordinates (0-1000) to actual canvas coordinates
const x = (xmin / 1000) * canvas.width
const y = (ymin / 1000) * canvas.height
const width = ((xmax - xmin) / 1000) * canvas.width
const height = ((ymax - ymin) / 1000) * canvas.height
// Draw bounding box
ctx.strokeStyle = "#ff00ff" // Magenta for AI detections
ctx.lineWidth = 3
ctx.strokeRect(x, y, width, height) // Draw label
ctx.fillStyle = "#ff00ff"
ctx.font = "14px Arial"
ctx.fillText(`${element.label}`, x, y - 5)
})
}, [image, data?.elements])
return (
<div class="p-5">
<h1 class="text-3xl font-bold mb-5">PROJECT WHITEBOARD</h1>
<form>hi</form>
<Form name="analyzeWhiteboard">
<button
type="submit"
class="bg-blue-500 text-white px-4 py-2 rounded hover:bg-blue-600 transition-colors"
>
Analyze Whiteboard
</button>
</Form>
<div class="mb-4">
<h2 class="text-xl font-semibold mb-2">AI Analysis: {loading ? "Loading..." : ""}</h2>
<p class="mb-2">
<strong>Description:</strong> {data?.description}
</p>
<p class="mb-2">
<strong>Summary:</strong> {data?.summary}
</p>
<p class="mb-2">
<strong>Detected Elements:</strong> {data?.elements.length}
</p>
<ul class="list-disc list-inside mb-4">
{data?.elements.map((element, index) => (
<li key={index}>
<span class="text-magenta-600 font-medium">{element.type}</span>: {element.label} at box_2d: [
{element.box_2d.ymin}, {element.box_2d.xmin}, {element.box_2d.ymax}, {element.box_2d.xmax}]
</li>
))}
</ul>
</div>
<div class="border-2 border-gray-300 inline-block">
<canvas ref={canvasRef} class="max-w-full h-auto" />
</div>
</div>
)
}
const sampleResponse = {
description:
"The image displays a whiteboard with various hand-drawn shapes and text in different colors. Shapes include several circles and one rectangle, along with an arrow. There are also written words and a wavy line, and a smiley face.",
elements: [
{
box_2d: { ymin: 45, xmin: 70, ymax: 275, xmax: 300 },
label: "blue circle",
type: "hand drawn circle",
},
{
box_2d: { ymin: 305, xmin: 160, ymax: 405, xmax: 295 },
label: "green smiley face",
type: "hand drawn circle",
},
{
box_2d: { ymin: 290, xmin: 400, ymax: 380, xmax: 500 },
label: "green circle with red cross",
type: "hand drawn circle",
},
{
box_2d: { ymin: 455, xmin: 450, ymax: 600, xmax: 560 },
label: "grey circle",
type: "hand drawn circle",
},
{
box_2d: { ymin: 620, xmin: 100, ymax: 740, xmax: 350 },
label: "blue rectangle",
type: "hand drawn square",
},
{
box_2d: { ymin: 460, xmin: 370, ymax: 530, xmax: 450 },
label: "arrow pointing to circle",
type: "hand drawn arrow",
},
],
summary: "A whiteboard showing hand-drawn circles, a rectangle, an arrow, and text.",
}

0
packages/project-whiteboard/src/server.ts → packages/whiteboard/src/server.ts
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0
packages/project-whiteboard/tsconfig.json → packages/whiteboard/tsconfig.json
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