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from fastapi import FastAPI, Request, Form
from fastapi.responses import HTMLResponse
from fastapi.templating import Jinja2Templates
from fastapi.staticfiles import StaticFiles
from pipeline.inference_pipeline import predict_batch, load_model
import numpy as np
import ast
app = FastAPI()
templates = Jinja2Templates(directory="app/templates")
app.mount("/static", StaticFiles(directory="app/static"), name="static")
model = load_model()
@app.get("/", response_class=HTMLResponse)
async def form_get(request: Request):
return templates.TemplateResponse("index.html", {"request": request})
@app.post("/", response_class=HTMLResponse)
async def form_post(request: Request, series: str = Form(...)):
try:
parsed_input = ast.literal_eval(series)
input_data = np.array(parsed_input, dtype=np.float32)
if len(input_data.shape) == 2:
input_data = np.expand_dims(input_data, axis=0)
preds = predict_batch(input_data, model)
return templates.TemplateResponse("index.html", {"request": request, "result": preds})
except Exception as e:
return templates.TemplateResponse("index.html", {"request": request, "result": f"❌ Error: {e}"})
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