Update app.py

app.py

@@ -1,12 +1,10 @@
 import chromadb
 import requests
 import chromadb.utils.embedding_functions as embedding_functions
-from ai4bharat.transliteration import XlitEngine
 import gradio as gr
 import os
-e = XlitEngine("gu", beam_width=10)
 embeddingfunc = embedding_functions.HuggingFaceEmbeddingFunction(api_key=os.environ["hf_token"],model_name="sentence-transformers/all-MiniLM-L6-v2")
 elibbookAI = chromadb.HttpClient("https://shethjenil-chromadb-server.hf.space/",port=443).get_or_create_collection("jainebooks")
 def qna(query:str,limit:int=1)->list:
-    return [i["contentimg"] for i in elibbookAI.query(embeddingfunc(requests.get(f"https://translate.googleapis.com/translate_a/single?client=gtx&sl=gu&tl=en&dt=t&q={e.translit_sentence(query)['gu']}").json()[0][0][0]),n_results=limit)["metadatas"][0]]
+    return [i["contentimg"] for i in elibbookAI.query(embeddingfunc(requests.get(f"https://translate.googleapis.com/translate_a/single?client=gtx&sl=gu&tl=en&dt=t&q={query}").json()[0][0][0]),n_results=limit)["metadatas"][0]]
 gr.Interface(qna,[gr.Textbox(),gr.Slider(1, 4, value=1, label="Count",step=1)],gr.Gallery()).launch()