import json
import gradio as gr
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from fastapi.responses import HTMLResponse
# Store the lists data (in-memory database)
lists = {}
# Define a model for the incoming request data
class DataRequest(BaseModel):
list_name: str
items: list
# For Hugging Face Spaces, we need to define the Gradio app first
with gr.Blocks() as demo:
# Create a simple interface to show the data
gr.Markdown("# UniShare Data Viewer")
output_text = gr.Textbox(label="Stored Data")
def show_data():
return json.dumps(lists, indent=4)
refresh_btn = gr.Button("Refresh Data")
refresh_btn.click(fn=show_data, inputs=[], outputs=[output_text])
# Initialize with current data
demo.load(fn=show_data, inputs=[], outputs=[output_text])
# Create FastAPI app
app = FastAPI()
# Endpoint for storing data
@app.post("/store_data")
async def store_data(data: DataRequest):
list_name = data.list_name
items = data.items
if list_name not in lists:
lists[list_name] = []
lists[list_name].append(items)
return {"message": f"Data stored successfully for {list_name}"}
# Endpoint to get data
@app.get("/api/data")
async def get_data():
return lists
# HTML interface endpoint
@app.get("/app", response_class=HTMLResponse)
def read_root():
return """
UniShare
"""
# This is crucial for Hugging Face Spaces
app = gr.mount_gradio_app(app, demo, path="/")