Update app.py

app.py

@@ -10,6 +10,7 @@ from datetime import datetime
 import re
 import time
 import random
+from bs4 import BeautifulSoup
 
 
 def flip_text(prompt, key):
@@ -19,44 +20,69 @@ def flip_text(prompt, key):
     url_api1 = os.getenv("url_api1")
     url_api2 = os.getenv("url_api2")
 
+    model_gr = os.getenv("model_gr")
+    headers_a = os.getenv("headers_gr")
+    a = eval(str(headers_a))
+    api_gr = os.getenv("api_gr")
+    
     if str(key).lower() == str(key_os).lower():
         try:
-            print(prompt)
-            headers = os.getenv("headers")
-            url_api = os.getenv("url_api")
-            
-            headers = eval(str(headers))
-            json_data = {'prompt': prompt, 'n': 1,'size': '1024x1024','response_format': 'b64_json','model': 'dall-e-3','quality': 'hd',}
-            response = requests.post(f"{url_api}", headers=headers, json=json_data)
-            js = response.json()
-            if "content_policy_violation" in str(js):
-                return "https://myneuralnetworks.ru/static/img/zp.jpg"
-            else:
-                photo = response.json()['data'][0]['b64_json']
-                photo = Image.open(io.BytesIO(base64.decodebytes(bytes(photo, "utf-8"))))
-            return photo
+            with closing(create_connection(f"{api_gr}", timeout=60, header=a)) as conn:
+                conn.send('{"fn_index":46,"session_hash":""}')
+                conn.send(f'{{"data":["{model_gr}",null,4096,"gpt-3.5-turbo","{prompt}","",1,1,[],null,"","1024x1024"],"event_data":null,"fn_index":46,"session_hash":""}}')
+                while True:
+                    conn_s = conn.recv()
+                    print(conn_s)
+                    status = json.loads(conn_s)['msg']
+                    print(status)
+                    if status == 'estimation':
+                        continue
+                    if status == 'process_starts':
+                        continue
+                    if status == 'process_generating':
+                        continue
+                    if status == 'process_completed':
+                        s = BeautifulSoup(str(conn_s), 'html.parser')
+                        return str(s.find('img').get('src')).replace(r'\"', '')
+                        break
         except:
-            send_time = str(datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
-            url_id1 = os.getenv("url_id1")
-            r_m = requests.post("https://myneuralnetworks.ru/get_key_dalle/", data={"key": url_id1})
-            key_a = r_m.json()['result']
-            
-            headers = {'authorization': key_a}
-            json_data = {'apiSource': 'gpt-all-tools'}
-            response = requests.post(f'{url_api1}', headers=headers, json=json_data)
-            chatUuid = response.json()['data']['chatUuid']
-            
-            json_data2 = {
-                'prompt': f'Нарисуй {prompt}',
-                'chatUuid': chatUuid,
-                'sendTime': send_time,
-                'attachments': [],
-            }
-            
-            response2 = requests.post(f'{url_api2}', headers=headers, json=json_data2)
-            url_pattern = r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\(\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+'
-            urls = re.findall(url_pattern, str(response2.text))
-            return urls[0]
+            try:
+                print(prompt)
+                headers = os.getenv("headers")
+                url_api = os.getenv("url_api")
+                
+                headers = eval(str(headers))
+                json_data = {'prompt': prompt, 'n': 1,'size': '1024x1024','response_format': 'b64_json','model': 'dall-e-3','quality': 'hd',}
+                response = requests.post(f"{url_api}", headers=headers, json=json_data)
+                js = response.json()
+                if "content_policy_violation" in str(js):
+                    return "https://myneuralnetworks.ru/static/img/zp.jpg"
+                else:
+                    photo = response.json()['data'][0]['b64_json']
+                    photo = Image.open(io.BytesIO(base64.decodebytes(bytes(photo, "utf-8"))))
+                return photo
+            except:
+                send_time = str(datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
+                url_id1 = os.getenv("url_id1")
+                r_m = requests.post("https://myneuralnetworks.ru/get_key_dalle/", data={"key": url_id1})
+                key_a = r_m.json()['result']
+                
+                headers = {'authorization': key_a}
+                json_data = {'apiSource': 'gpt-all-tools'}
+                response = requests.post(f'{url_api1}', headers=headers, json=json_data)
+                chatUuid = response.json()['data']['chatUuid']
+                
+                json_data2 = {
+                    'prompt': f'Нарисуй {prompt}',
+                    'chatUuid': chatUuid,
+                    'sendTime': send_time,
+                    'attachments': [],
+                }
+                
+                response2 = requests.post(f'{url_api2}', headers=headers, json=json_data2)
+                url_pattern = r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\(\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+'
+                urls = re.findall(url_pattern, str(response2.text))
+                return urls[0]
             
     else:
         return "https://myneuralnetworks.ru/static/img/zp2.jpg"