mounted static html

main.py

@@ -2,6 +2,8 @@ import uuid
 import asyncio
 import transformers
 from fastapi import FastAPI
+from fastapi.staticfiles import StaticFiles
+from fastapi.responses import FileResponse
 from pydantic import BaseModel
 from contextlib import asynccontextmanager
 from transformers import (
@@ -15,7 +17,6 @@ from optimum.onnxruntime import ORTModelForSequenceClassification
 # ----------------------------- #
 transformers.set_seed(42)
 
-# MODEL_NAME = "climatebert/distilroberta-base-climate-sentiment"
 MODEL_NAME = "distilroberta-base-climate-sentiment-onnx-quantized"
 BATCH_PROCESS_INTERVAL = 0.01
 MAX_BATCH_SIZE = 128
@@ -82,7 +83,7 @@ async def process_queue():
 #        Lifespan Handler       #
 # ----------------------------- #
 @asynccontextmanager
-async def lifespan(app: FastAPI):
+async def lifespan(_: FastAPI):
     global classifier
     classifier = load_classifier(MODEL_NAME)
     _ = classifier("Startup warm-up sentence.")
@@ -115,8 +116,9 @@ async def classify(query: Query):
     return {"id": query_id, "result": results.pop(query_id)}
 
 
+app.mount("/", StaticFiles(directory="static", html=True), name="static")
+
+
 @app.get("/")
 def read_root():
-    return {
-        "message": "Welcome to the Sentiment Classification API with Query Batching"
-    }
+    return FileResponse(path="static/index.html", media_type="text/html")