natural-frontend 0.0.1

A wrapper for FastAPI to automatically generate a frontend

From backend to frontend with one line
Don't waste hours generating a frontend for your users.

Features

• Natural Frontend understands your codebase and the potential user personas for your product.
• On the /frontend endpoint, select a user personas and NF generates a tailored frontend.

Coming soon:

• Save your generated frontends to modify them later.
• Use local models instead of openai.

Usage

⬇️ Installation

With pip: pip install natural-frontend

➕ Add to your code

Just add one-line to your api project:

from fastapi import FastAPI
from natural_frontend import NaturalFrontend

openai_key = "sk-..."

app = FastAPI()
app = NaturalFrontend(app, openai_key)

@app.get("/books")
async def get_books():
    return books_db


@app.post("/books")
async def add_book(book: Book):
    books_db.append(book.dict())
    return {"message": "Book added successfully"}

class Book(BaseModel):
    id: int
    title: str
    author: str
    genre: str

⚙️ Options

You can provide options to customize your Natural Frontend:

nf_options = NaturalFrontendOptions(
   colors={"primary": "lightblue", "secondary": "purple"},
   personas=[{"Bookworm": "Loves to look for new books"}],
   cache_expiry_time=600,
   frontend_endpoint="frontend",
)

app = NaturalFrontend(app, openai_key, nf_options)

Documentation of options:

• colors: Customize the colors of the frontend. Use two keys: "primary" and "secondary".
• personas: Add custom personas for your frontend. NF will guess more until there's 5 personas.
• cache_expiry_time: Set the time in seconds before the generation cache expires.
• frontend_endpoint: Change the endpoint of the frontend.

Development

We're happy to get contributors working with us! Follow the instructions below to quickly setup yo

Running the Application

0. (Optional) Use virtualenv to quickly setup your environment: virtualenv venv && source venv/bin/activate

1. Install the required packages: pip install -r requirements.txt

2. Run the example application: uvicorn app.main:app --reload

(With Docker)

1. Make sure you have Docker installed

2. Run docker compose up --build