init backend

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2026-01-10 22:26:16 +01:00
commit 02211eb0be
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.dockerignore Normal file
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python_service/venv

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.gitignore vendored Normal file
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# dependencies (bun install)
node_modules
# output
out
dist
*.tgz
# code coverage
coverage
*.lcov
# logs
logs
_.log
report.[0-9]_.[0-9]_.[0-9]_.[0-9]_.json
# dotenv environment variable files
.env
.env.development.local
.env.test.local
.env.production.local
.env.local
# caches
.eslintcache
.cache
*.tsbuildinfo
# IntelliJ based IDEs
.idea
# Finder (MacOS) folder config
.DS_Store
**/venv

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README.md Normal file
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# desktop
To install dependencies:
```bash
bun install
```
To run:
```bash
bun run index.ts
```
This project was created using `bun init` in bun v1.3.5. [Bun](https://bun.com) is a fast all-in-one JavaScript runtime.

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bun.lock Normal file
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{
"lockfileVersion": 1,
"configVersion": 1,
"workspaces": {
"": {
"name": "desktop",
"devDependencies": {
"@types/bun": "latest",
},
"peerDependencies": {
"typescript": "^5",
},
},
},
"packages": {
"@types/bun": ["@types/bun@1.3.5", "", { "dependencies": { "bun-types": "1.3.5" } }, "sha512-RnygCqNrd3srIPEWBd5LFeUYG7plCoH2Yw9WaZGyNmdTEei+gWaHqydbaIRkIkcbXwhBT94q78QljxN0Sk838w=="],
"@types/node": ["@types/node@25.0.3", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-W609buLVRVmeW693xKfzHeIV6nJGGz98uCPfeXI1ELMLXVeKYZ9m15fAMSaUPBHYLGFsVRcMmSCksQOrZV9BYA=="],
"bun-types": ["bun-types@1.3.5", "", { "dependencies": { "@types/node": "*" } }, "sha512-inmAYe2PFLs0SUbFOWSVD24sg1jFlMPxOjOSSCYqUgn4Hsc3rDc7dFvfVYjFPNHtov6kgUeulV4SxbuIV/stPw=="],
"typescript": ["typescript@5.9.3", "", { "bin": { "tsc": "bin/tsc", "tsserver": "bin/tsserver" } }, "sha512-jl1vZzPDinLr9eUt3J/t7V6FgNEw9QjvBPdysz9KfQDD41fQrC2Y4vKQdiaUpFT4bXlb1RHhLpp8wtm6M5TgSw=="],
"undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
}
}

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# --- Base image with Node + Python ---
FROM ubuntu:22.04
# --- Install system dependencies ---
RUN apt-get update && apt-get install -y \
curl python3 python3-pip git build-essential libgl1 libglvnd0 ffmpeg unzip \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
# --- Install Bun ---
RUN curl -fsSL https://bun.sh/install | bash
ENV PATH="/root/.bun/bin:${PATH}"
# --- Install Python dependencies ---
RUN pip3 install --upgrade pip
RUN pip3 install torch --index-url https://download.pytorch.org/whl/cpu
RUN pip3 install --no-cache-dir fastapi uvicorn pillow open-clip-torch numpy faiss-cpu python-multipart
# --- Copy project files ---
WORKDIR /app
COPY python_service ./python_service
COPY src ./src
COPY package.json .
COPY bun.lock .
# --- Expose ports ---
EXPOSE 3000
# --- Start services ---
# Use & to run Python worker in background, Bun frontend as main process
CMD python3 python_service/app.py & bun run src/index.ts

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package.json Normal file
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{
"name": "desktop",
"module": "src/index.ts",
"type": "module",
"private": true,
"scripts": {
"dev": "bun run src/index.ts"
},
"devDependencies": {
"@types/bun": "latest"
},
"peerDependencies": {
"typescript": "^5"
}
}

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python_service/app.py Normal file
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from fastapi import FastAPI, File, UploadFile
from fastapi.responses import JSONResponse
from fastapi.middleware.cors import CORSMiddleware
from PIL import Image
import torch, open_clip, numpy as np, faiss
import io
app = FastAPI(title="Pokemon Card Image Service")
# --- Allow CORS for Bun / Flutter ---
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_methods=["*"],
allow_headers=["*"],
)
import os
BASE = os.path.dirname(os.path.abspath(__file__))
# --- Configuration ---
FAISS_INDEX_FILE = os.path.join(BASE, "card_index.faiss")
EMBEDDINGS_FILE = os.path.join(BASE, "embeddings.npy")
IDS_FILE = os.path.join(BASE, "ids.npy")
TOP_K = 5
# --- Load CLIP model ---
device = "cuda" if torch.cuda.is_available() else "cpu"
print("Loading model on device:", device)
model, _, preprocess = open_clip.create_model_and_transforms(
"ViT-L-14", pretrained="laion2b_s32b_b82k"
)
model = model.to(device).eval()
# --- Load FAISS index ---
print("Loading FAISS index from disk...")
index = faiss.read_index(FAISS_INDEX_FILE)
# --- Load IDs / metadata ---
ids = np.load(IDS_FILE)
metadata = {idx: {"id": ids[idx], "name": ids[idx]} for idx in range(len(ids))}
print("Service ready! FAISS index contains", index.ntotal, "cards.")
# --- Helper: encode image ---
def encode_image_bytes(image_bytes):
img = Image.open(io.BytesIO(image_bytes)).convert("RGB")
print("Image loaded successfully:", img.size)
with torch.no_grad():
emb = model.encode_image(preprocess(img).unsqueeze(0).to(device))
emb = emb.cpu().numpy()
faiss.normalize_L2(emb)
print("Embedding shape:", emb.shape)
return emb
# --- API endpoint ---
@app.post("/query")
async def query_image(file: UploadFile = File(...)):
try:
image_bytes = await file.read()
print(f"Received {len(image_bytes)} bytes from {file.filename}")
emb = encode_image_bytes(image_bytes)
# --- FAISS search ---
D, I = index.search(emb, TOP_K)
print("FAISS distances:", D)
print("FAISS indices:", I)
results = [metadata[int(i)] for i in I[0]]
return JSONResponse(content={"results": results})
except Exception as e:
print("ERROR during query:", e)
return JSONResponse(content={"error": str(e)}, status_code=500)
# --- Run server ---
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=5001)

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import type { Card } from "./types";
// Placeholder cards array
let cards: Card[] = [
{ id: "swsh1-1", name: "Celebi V", set: "Swsh1", number: "1", imageUrl: "https://assets.tcgdex.net/de/swsh/swsh1/1/high.png" },
{ id: "swsh12-001", name: "Bluzuk", set: "Swsh12", number: "001", imageUrl: "https://assets.tcgdex.net/de/swsh/swsh12/001/high.png" },
];
export function loadCards() {
// Placeholder: you can later load embeddings.npy + FAISS
console.log("Cards module loaded (currently empty)");
}
export function queryCardById(id: string): Card | null {
return cards.find(c => c.id === id) || null;
}
// Example placeholder: return top N matches
export function queryCardByEmbedding(/* embedding */): Card[] {
return cards.slice(0, 5); // dummy top 5
}

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import { serve, spawn } from 'bun';
import { queryCardByEmbedding, queryCardById } from './embeddings';
import type { Card } from './types';
const PYTHON_SERVICE = "http://localhost:5001/query";
const server = serve({
routes: {
"/api/cards/query-image": {
async POST(req) {
try {
const formData = await req.formData();
const file = formData.get("file") as File;
if (!file) return new Response(JSON.stringify({ error: "No file uploaded" }), { status: 400 });
// Forward directly to Python microservice
const body = new FormData();
body.append("file", file);
const resp = await fetch(PYTHON_SERVICE, { method: "POST", body });
const json = await resp.json();
return new Response(JSON.stringify(json), { headers: { "Content-Type": "application/json" } });
} catch (err) {
console.error(err);
return new Response(JSON.stringify({ error: "Failed to query image" }), { status: 500 });
}
},
},
"/api/cards/:id": async (req) => {
const { id } = req.params;
const card = queryCardById(id);
if (!card) return new Response(JSON.stringify({ error: "Card not found" }), { status: 404, headers: { "Content-Type": "application/json" } });
return new Response(JSON.stringify(card), { headers: { "Content-Type": "application/json" } });
},
"/*": async () => {
return new Response("<h1>Pokemon Card Backend</h1>", { headers: { "Content-Type": "text/html" } });
},
/* "/api/cards/query": {
async POST(req) {
try {
const { embedding } = await req.json() as { embedding: number[] };
if (!embedding) return new Response(JSON.stringify({ error: "Missing embedding" }), { status: 400, headers: { "Content-Type": "application/json" } });
const results: Card[] = queryCardByEmbedding(embedding);
return new Response(JSON.stringify(results), { headers: { "Content-Type": "application/json" } });
} catch (err) {
console.error("Error querying card:", err);
return new Response(JSON.stringify({ error: "Failed to query card" }), { status: 500, headers: { "Content-Type": "application/json" } });
}
},
}, */
},
development: process.env.NODE_ENV !== 'production' && {
// Enable browser hot reloading in development
hmr: true,
// Echo console logs from the browser to the server
console: true,
},
});
console.log(`🚀 Server running at ${server.url}`);

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export interface Card {
id: string;
name: string;
set: string;
number: string;
rarity?: string;
variant?: string;
foil?: boolean;
imageUrl: string;
}

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{
"compilerOptions": {
// Environment setup & latest features
"lib": ["ESNext"],
"target": "ESNext",
"module": "Preserve",
"moduleDetection": "force",
"jsx": "react-jsx",
"allowJs": true,
// Bundler mode
"moduleResolution": "bundler",
"allowImportingTsExtensions": true,
"verbatimModuleSyntax": true,
"noEmit": true,
// Best practices
"strict": true,
"skipLibCheck": true,
"noFallthroughCasesInSwitch": true,
"noUncheckedIndexedAccess": true,
"noImplicitOverride": true,
// Some stricter flags (disabled by default)
"noUnusedLocals": false,
"noUnusedParameters": false,
"noPropertyAccessFromIndexSignature": false
}
}