Update app.py

app.py

@@ -1,59 +1,38 @@
 import os
-import gradio as gr
+from fastapi import FastAPI, Request
+from fastapi.responses import JSONResponse
 from transformers import pipeline
 
+app = FastAPI()
+
 token = os.environ.get("HF_TOKEN")
 
 english_model = None
 urdu_model = None
 
-
 def get_english_model():
     global english_model
     if english_model is None:
-        english_model = pipeline(
-            "text-classification",
-            model="mrgmd01/Finetuned_siebert-sentiment-roberta-large-english",
-            token=token
-        )
+        english_model = pipeline("text-classification", model="mrgmd01/Finetuned_siebert-sentiment-roberta-large-english", token=token)
     return english_model
 
-
 def get_urdu_model():
     global urdu_model
     if urdu_model is None:
-        urdu_model = pipeline(
-            "text-classification",
-            model="mrgmd01/SA_Model_bert-base-multilingual-uncased",
-            token=token
-        )
+        urdu_model = pipeline("text-classification", model="mrgmd01/SA_Model_bert-base-multilingual-uncased", token=token)
     return urdu_model
 
+@app.get("/")
+def root():
+    return {"status": "running"}
 
-def predict(text, language):
+@app.post("/predict")
+async def predict(request: Request):
+    body = await request.json()
+    text = body.get("text", "")
+    language = body.get("language", "english")
     if language in ["urdu", "roman_urdu"]:
         result = get_urdu_model()(text)[0]
     else:
         result = get_english_model()(text)[0]
-
-    return {
-        "label": result["label"],
-        "score": float(result["score"])
-    }
-
-
-iface = gr.Interface(
-    fn=predict,
-    inputs=[
-        gr.Textbox(label="Input Text"),
-        gr.Dropdown(
-            choices=["english", "urdu", "roman_urdu"],
-            value="english",
-            label="Language"
-        )
-    ],
-    outputs="json",
-    title="Multilingual Sentiment Analysis"
-)
-
-iface.launch()
+    return JSONResponse({"label": result["label"], "score": float(result["score"])})