Update app.py

app.py

@@ -7,7 +7,11 @@ import gradio as gr
 from PIL import Image
 import base64
 from utils import HocrParser
+import google.generativeai as genai
 
+api_key = 'AIzaSyB7-RzBwTAfVA-7ZGk2mEOQwOxshpwzhpM' # put your API key here
+genai.configure(api_key=api_key)
+geminiModel = genai.GenerativeModel(model_name='gemini-pro')
 predictor = ocr_predictor(det_arch='db_mobilenet_v3_large', reco_arch='crnn_vgg16_bn',pretrained=True)
 predictor.reco_predictor.model.cfg['vocab']='0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ!”#$%&’()*+,-./:;<=>?@[]^_`{|}~°£€¥¢฿áàảạãăắằẳẵặâấầẩẫậéèẻẽẹêếềểễệóòỏõọôốồổộỗơớờởợỡúùủũụưứừửữựiíìỉĩịýỳỷỹỵÁÀẢẠÃĂẮẰẲẴẶÂẤẦẨẪẬÉÈẺẼẸÊẾỀỂỄỆÓÒỎÕỌÔỐỒỔỘỖƠỚỜỞỢỠÚÙỦŨỤƯỨỪỬỮỰIÍÌỈĨỊÝỲỶỸỴ'
 title="DocTR OCR (PDL Demo)"
@@ -29,7 +33,11 @@ def greet(img):
             res=res + " " + obj3.value
         res=res + "\n"
       res=res + "\n"
-
+    # generate text
+    prompt = "take this peace of information and give all the information in point wise better format also give some recomendation related to them: " + res
+    # print(prompt)
+    response  = geminiModel.generate_content(prompt)
+    res = response.text
     _output_name = "RESULT_OCR.txt"
     _output_name_pdf="RESULT_OCR.pdf"