Generates full-stack application templates with FastAPI backend and React frontend, including OpenAI ChatGPT integration. Benefits developers by accelerating project setup and reducing boilerplate code.
git clone https://github.com/umairalipathan1980/Claude-Skill-for-Full-Stack-Application-Development.gitGenerates full-stack application templates with FastAPI backend and React frontend, including OpenAI ChatGPT integration. Benefits developers by accelerating project setup and reducing boilerplate code.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/umairalipathan1980/Claude-Skill-for-Full-Stack-Application-DevelopmentCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Generate a full-stack application template with a FastAPI backend and React frontend for a [COMPANY] in the [INDUSTRY] sector. Include OpenAI ChatGPT integration and CORS configuration. Use [DATA] as sample data for the application.
# Full-Stack Application Template
## Backend (FastAPI)
```python
from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
app = FastAPI()
# CORS Configuration
app.add_middleware(
CORSMiddleware,
allow_origins=["http://localhost:5173"],
allow_credentials=True,
allow_methods=[""],
allow_headers=[""],
)
# Sample Data
sample_data = {
"products": [
{"id": 1, "name": "Product A", "price": 19.99},
{"id": 2, "name": "Product B", "price": 29.99},
]
}
# Endpoint to get all products
@app.get("/products/")
async def get_products():
return sample_data["products"]
# Endpoint to get a specific product
@app.get("/products/{product_id}")
async def get_product(product_id: int):
for product in sample_data["products"]:
if product["id"] == product_id:
return product
raise HTTPException(status_code=404, detail="Product not found")
# ChatGPT Integration
@app.post("/chat/")
async def chat_with_gpt(message: str):
# Integration with ChatGPT API
response = openai.Completion.create(
engine="text-davinci-002",
prompt=message,
max_tokens=150
)
return response.choices[0].text
```
## Frontend (React with Vite)
```jsx
import React, { useState, useEffect } from 'react';
import axios from 'axios';
function App() {
const [products, setProducts] = useState([]);
const [message, setMessage] = useState('');
const [response, setResponse] = useState('');
useEffect(() => {
axios.get('http://localhost:8000/products/')
.then(response => {
setProducts(response.data);
})
.catch(error => {
console.error('Error fetching products:', error);
});
}, []);
const handleChatSubmit = async (e) => {
e.preventDefault();
try {
const res = await axios.post('http://localhost:8000/chat/', { message });
setResponse(res.data);
} catch (error) {
console.error('Error sending message:', error);
}
};
return (
<div>
<h1>Product List</h1>
<ul>
{products.map(product => (
<li key={product.id}>{product.name} - ${product.price}</li>
))}
</ul>
<form onSubmit={handleChatSubmit}>
<input
type="text"
value={message}
onChange={(e) => setMessage(e.target.value)}
placeholder="Type your message"
/>
<button type="submit">Send</button>
</form>
{response && <div>
<h2>ChatGPT Response</h2>
<p>{response}</p>
</div>}
</div>
);
}
export default App;
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