@@ -215,6 +215,7 @@ DATABASES = {
         'HOST': env.str('POSTGRES_HOST'),
         'PORT': env.str('POSTGRES_PORT'),
         'CONN_HEALTH_CHECKS': True,
+        'DISABLE_SERVER_SIDE_CURSOR': False
     }
 }
 
@@ -161,7 +161,7 @@ class Chatgpt(SimpleService):
             self.llm.tiktoken_model_name = 'gpt-4'
             if model_name not in self.TOKENS_COST.keys():
                 raise Exception(_('No matching version found'))
-            chat_history = self.get_chat_history()
+            chat_history = self.get_chat_history(model_name=model_name)
             if model_name in ('o1-preview', 'o1-mini'):
                 chat_history.messages.pop(0)
             conversation = RunnableWithMessageHistory(
@@ -296,33 +296,41 @@ class Chatgpt(SimpleService):
             return msgs
         raise GenerationException
 
-    def get_chat_history(
-        self,
-        message_limit: int = 10,
-        token_limit: int = 580,  # ~ 1 AIR Token with GPT 3.5
-    ) -> InMemoryChatMessageHistory:
+    def get_chat_history(self, model_name: str) -> InMemoryChatMessageHistory:
         if isinstance(self.store, Chat):
-            air_messages = list(
-                reversed(
-                    Message.objects.filter(
-                        chats_chats_messages=self.store,
-                        is_deleted=False,
-                        is_sent=True,
-                    ).order_by('-created_at')[:message_limit]
-                )
-            )
+            air_messages = Message.objects.filter(
+                chats_chats_messages=self.store,
+                is_deleted=False,
+                is_sent=True,
+            ).order_by('-created_at')
         elif isinstance(self.store, APIStore):
             air_messages = []
         elif isinstance(self.store, Copywrite):
-            air_messages = list(
-                reversed(
-                    Message.objects.filter(
-                        copywrite_copywrites_messages=self.store,
-                        is_deleted=False,
-                        is_sent=True,
-                    ).order_by('-created_at')[:message_limit]
-                )
-            )
+            air_messages = Message.objects.filter(
+                copywrite_copywrites_messages=self.store,
+                is_deleted=False,
+                is_sent=True,
+            ).order_by('-created_at')
+
+        token_limits = {
+            'o3-mini': 100_000,
+            'o1-preview': 100_000,
+            'gpt-4o-mini': 64_000,
+            'gpt-4o': 64_000,
+            'gpt-4.5-preview': 64_000,
+        }
+        tokens = 0
+        history: List[BaseMessage] = []
+        for message in air_messages.iterator(5):
+            air_message = [
+                AIMessage(content=message.content or '')
+                if message.from_model else
+                HumanMessage(content=message.content or '')
+            ]
+            if self.count_text_tokens(air_message) + tokens > token_limits[model_name]:
+                break
+            tokens += self.count_text_tokens(air_message)
+            history.append(air_message[0])
         memory = InMemoryChatMessageHistory()
         memory.add_message(SystemMessage(
                 content=(
@@ -331,20 +339,7 @@ class Chatgpt(SimpleService):
                     'Любая информация должна быть преобразована в простой строковый текст (str).'
                 )
             ))
-        for msg in air_messages:
-            content = msg.content or ''
-            if msg.from_model:
-                memory.add_message(AIMessage(content=content))
-            else:
-                memory.add_message(HumanMessage(content=content))
-
-        messages = memory.messages
-        tokens = self.llm.get_num_tokens_from_messages(messages)
-
-        while tokens > token_limit:
-            messages.pop(1)
-            tokens = self.llm.get_num_tokens_from_messages(messages)
-
+        memory.add_messages(list(reversed(history)))
         return memory
 
     def assert_enough_balance(
@@ -581,7 +576,7 @@ class Chatgpt(SimpleService):
                 'top_p': input_message.info.pop('top_p', 0.5),
             },
         )
-        chat_history = self.get_chat_history()
+        chat_history = self.get_chat_history(model_name=input_message.info.pop('version', 'gpt-3.5-turbo'))
         conversation = ConversationChain(
             llm=self.llm,
             memory=chat_history,