replaced openai with our NER model

app.py

@@ -4,6 +4,7 @@ import gradio as gr
 import numpy as np
 import openai
 import ast
+from transformers import pipeline
 import os
 
 from openai_api import OpenAI_API
@@ -24,7 +25,7 @@ def get_text(input_img):
 def get_parsed_address(input_img):
 
     address_full_text = get_text(input_img)
-    return openai_response(address_full_text)
+    return ner_response(address_full_text)
 
 
 def save_deta_db(input):
@@ -41,62 +42,33 @@ def clear_textbox(value):
     return gr.update(value="")
 
 
-# Open API on change
 def text_dict(input):
     eval_result = ast.literal_eval(input)
     return (
-        str(eval_result["city"]),
-        str(eval_result["distinct"]),
-        str(eval_result["neighbourhood"]),
-        str(eval_result["street"]),
-        str(eval_result["address"]),
-        str(eval_result["tel"]),
-        str(eval_result["name_surname"]),
+        str(eval_result["il"]),
+        str(eval_result["ilce"]),
+        str(eval_result["mahalle"]),
+        str(eval_result["sokak"]),
+        str(eval_result["Apartman/site"]),
         str(eval_result["no"]),
+        str(eval_result["ad-soyad"]),
+        str(eval_result["dis kapi no"]),
     )
 
 
-def openai_response(ocr_input):
-    prompt = f"""Tabular Data Extraction You are a highly intelligent and accurate tabular data extractor from 
-            plain text input and especially from emergency text that carries address information, your inputs can be text 
-            of arbitrary size, but the output should be in [{{'tabular': {{'entity_type': 'entity'}} }}] JSON format Force it 
-            to only extract keys that are shared as an example in the examples section, if a key value is not found in the 
-            text input, then it should be ignored. Have only city, distinct, neighbourhood, 
-            street, no, tel, name_surname, address Examples:
-            
-            Input: Deprem sırasında evimizde yer alan adresimiz: İstanbul, Beşiktaş, Yıldız Mahallesi, Cumhuriyet Caddesi No: 35, cep telefonu numaram 5551231256, adim Ahmet Yilmaz 
-            Output: {{'city': 'İstanbul', 'distinct': 'Beşiktaş', 'neighbourhood': 'Yıldız Mahallesi', 'street': 'Cumhuriyet Caddesi', 'no': '35', 'tel': '5551231256', 'name_surname': 'Ahmet Yılmaz', 'address': 'İstanbul, Beşiktaş, Yıldız Mahallesi, Cumhuriyet Caddesi No: 35'}}
-            
-            Input: 5.29 PMO $ 0 87 DEVREMİZ ÖZGÜR ORÇAN ARKADAŞIMIZA ULAŞAMIYORUZ BEYOĞLU MAH FEVZİ ÇAKMAK CAD. NO.58-TÜRKOĞLUI KAHRAMANMARAŞ 5524357578 AdReSe YaKIN OLANLAR VEYA ULASANLAR LÜTFEN BiLGILENDIRSIN .
-            Output: {{'city': 'Kahramanmaraş', 'distinct': 'Türkoğlu', 'neighbourhood': 'Beyoğlu Mahallesi', 'street': 'Çakmak Caddesi', 'no': '58', 'tel': '5524357578', 'name_surname': 'Özgür Orçan', 'address': 'Beyoğlu Mahallesi, Çakmak Caddesi, No:58 Türkoğlu/Kahramanmaraş'}}
-
-            Input: Ahmet @ozknhmt Ekim 2021 tarihinde katıldı - 2 Takipçi Takip ettiğin kimse takip etmiyor AKEVLER MAH. 432SK RÜYA APT ANT(BEDİİ SABUNCU KARŞISI) ANTAKYA HATAY MERVE BELANLI ses veriyor ancak hiçbiryardım ekibi olmadığı için kurtaramryoruz içeri girip, lütfen acil yardım_ İsim: Merve Belanlı tel 542 757 5484 Ö0 12.07
-            Output: {{'city': 'Hatay', 'distinct': 'Antakya', 'neighbourhood': 'Akevler Mahallesi', 'street': '432 Sokak', 'no': '', 'tel': '5427575484', 'name_surname': 'Merve Belanlı', 'address': 'Akevler Mahallesi, 432 Sokak, Rüya Apt. Antakya/Hatay'}}
-            
-            Input: 14:04 Sümerler Cemil Şükrü Çolokoğlu ilköğretim okulu karşısı 3 9öçük altında yardım bekyouk Lütfen herkes paylogsın
-            Output: {{'city': '', 'distinct': '', 'neighbourhood': 'Sümerler Mahallesi', 'street': 'Cemil Şükrü Çolokoğlu İlköğretim Okulu Karşısı', 'no': '', 'tel': '', 'name_surname': '', 'address': 'Sümerler Mahallesi, Cemil Şükrü Çolokoğlu İlköğretim Okulu Karşısı'}}
-                        
-            Input: {ocr_input}
-            Output:
-        """
+def ner_response(ocr_input):
+
+    ner_pipe = pipeline("token-classification","deprem-ml/deprem-ner", aggregation_strategy="first")
+    predictions = ner_pipe(ocr_input)
+    resp = {}
 
-    openai_client = OpenAI_API()
-    response = openai_client.single_request(prompt)
-    print(resp)
-    resp = response["choices"][0]["text"]
-    resp = eval(resp.replace("'{", "{").replace("}'", "}"))
+    for item in predictions:
+        print(item)
+        key = item["entity_group"]
+        resp[key] = item["word"]
+    
     resp["input"] = ocr_input
-    dict_keys = [
-        "city",
-        "distinct",
-        "neighbourhood",
-        "street",
-        "no",
-        "tel",
-        "name_surname",
-        "address",
-        "input",
-    ]
+    dict_keys = ["il", "ilce", "mahalle", "sokak", "Apartman/site", "no", "ad-soyad", "dis kapi no"]
     for key in dict_keys:
         if key not in resp.keys():
             resp[key] = ""
@@ -126,24 +98,24 @@ with gr.Blocks() as demo:
 
     with gr.Column():
         with gr.Row():
-            city = gr.Textbox(label="İl", interactive=True, show_progress=False)
-            distinct = gr.Textbox(label="İlçe", interactive=True, show_progress=False)
+            il = gr.Textbox(label="İl", interactive=True, show_progress=False)
+            ilce = gr.Textbox(label="İlçe", interactive=True, show_progress=False)
         with gr.Row():
-            neighbourhood = gr.Textbox(
+            mahalle = gr.Textbox(
                 label="Mahalle", interactive=True, show_progress=False
             )
-            street = gr.Textbox(
+            sokak = gr.Textbox(
                 label="Sokak/Cadde/Bulvar", interactive=True, show_progress=False
             )
         with gr.Row():
-            tel = gr.Textbox(label="Telefon", interactive=True, show_progress=False)
+            no = gr.Textbox(label="Telefon", interactive=True, show_progress=False)
         with gr.Row():
-            name_surname = gr.Textbox(
+            ad_soyad = gr.Textbox(
                 label="İsim Soyisim", interactive=True, show_progress=False
             )
-            address = gr.Textbox(label="Adres", interactive=True, show_progress=False)
+            apartman = gr.Textbox(label="apartman", interactive=True, show_progress=False)
         with gr.Row():
-            no = gr.Textbox(label="Kapı No", interactive=True, show_progress=False)
+            dis_kapi_no = gr.Textbox(label="Kapı No", interactive=True, show_progress=False)
 
     img_area_button.click(
         get_parsed_address,
@@ -153,13 +125,14 @@ with gr.Blocks() as demo:
     )
 
     text_area_button.click(
-        openai_response, text_area, open_api_text, api_name="upload-text"
+        ner_response, text_area, open_api_text, api_name="upload-text"
     )
 
+
     open_api_text.change(
         text_dict,
         open_api_text,
-        [city, distinct, neighbourhood, street, address, tel, name_surname, no],
+        [il, ilce, mahalle, sokak, no, apartman, ad_soyad, dis_kapi_no],
     )
     ocr_button = gr.Button(value="Sadece OCR kullan")
     ocr_button.click(
@@ -172,9 +145,9 @@ with gr.Blocks() as demo:
     submit_button.click(save_deta_db, open_api_text)
     done_text = gr.Textbox(label="Done", value="Not Done", visible=False)
     submit_button.click(update_component, outputs=done_text)
-    for txt in [city, distinct, neighbourhood, street, address, tel, name_surname, no]:
+    for txt in [il, ilce, mahalle, sokak, apartman, no, ad_soyad, dis_kapi_no]:
         submit_button.click(fn=clear_textbox, inputs=txt, outputs=txt)
 
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()