@@ -104,6 +104,7 @@ class Chatgpt(SimpleService):
         start_time = time.time()
         info = input_message.info.copy()
         model_name = info.pop('version', 'gpt-4o')
+        user_system_prompt = info.pop('system_prompt', '')
         input_content = [{'type': 'text', 'text': input_message.content or ''}]
         file = input_message.file
         image = None
@@ -164,13 +165,13 @@ class Chatgpt(SimpleService):
                 runnable=self.llm,
                 get_session_history=lambda _: chat_history,
             )
-            llm_input = HumanMessage(content=input_content)
+            llm_input = [SystemMessage(content=user_system_prompt), HumanMessage(content=input_content)]
             if file and not image:
-                input_tokens = self.count_text_tokens([*chat_history.messages, llm_input, *chunks])
+                input_tokens = self.count_text_tokens([*chat_history.messages, *llm_input, *chunks])
             elif image:
-                input_tokens = self.count_text_tokens([llm_input])
+                input_tokens = self.count_text_tokens(llm_input)
             else:
-                input_tokens = self.count_text_tokens([*chat_history.messages, llm_input])
+                input_tokens = self.count_text_tokens([*chat_history.messages, *llm_input])
             output_tokens = 0
             self.assert_enough_balance(input_tokens, image_size, model=self.llm.model_name)
             if model_name in ('o3-mini', 'gpt-4.5-preview'):
@@ -180,6 +181,7 @@ class Chatgpt(SimpleService):
                     for msg in chat_history.messages
                 ]
                 messages.insert(0, {'role': 'system', 'content': system.content})
+                messages.insert(0, {'role': 'system', 'content': user_system_prompt})
                 if image:
                     messages[-1]['content'] = [
                         {'type': 'text', 'text': input_message.content},
@@ -204,6 +206,7 @@ class Chatgpt(SimpleService):
                 ]
                 if model_name not in ('o1-preview', 'o1-mini'):
                     messages.insert(0, {'role': 'system', 'content': system.content})
+                    messages.insert(0, {'role': 'system', 'content': user_system_prompt})
                 search_context_size = search_context_sizes.get(info.get('web_search', 'Средний контекст'))
                 info['web_search'] = search_context_size
                 json_data = {
@@ -219,7 +222,7 @@ class Chatgpt(SimpleService):
                 }
                 input_tokens, output_tokens, response = self.call_openai_api(proxy=proxy, endpoint='responses',json_data=json_data)
             elif image:
-                response = self.llm.invoke([llm_input])
+                response = self.llm.invoke(llm_input)
                 chat_history.add_ai_message(response)
             elif file:
                 human_messages = []
@@ -253,8 +256,10 @@ class Chatgpt(SimpleService):
                 )
             else:
                 # Somehow this chain doesn't support Vision, even though ChatOpenAI (above) does.
+                if model_name in ('o1-preview', 'o1-mini'):
+                    llm_input.pop(0)
                 response = conversation.invoke(
-                    {'input': llm_input.content[0]['text']},
+                    {'input': llm_input},
                     config={'configurable': {'session_id': 'default'}},
                 )
                 chat_history.add_ai_message(response)
@@ -61,9 +61,13 @@ class Claude(SimpleService):
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
         start_time = time.time()
         version = f'anthropic/{input_message.info.pop("version", "claude-3.7-sonnet:thinking")}'
+        system_prompt = input_message.info.pop('system_prompt', '')
         callback_data = {'provider': {'order': ['Anthropic']}, **input_message.info}
-        messages = self.get_chat_history()
-        messages.append({'role': 'user', 'content': input_message.content})
+        messages = [
+            {'role': 'system', 'content': system_prompt},
+            *self.get_chat_history(),
+            {'role': 'user', 'content': input_message.content}
+        ]
         image = input_message.file
         if image:
             kind = filetype.guess(image.read(20))
@@ -47,11 +47,15 @@ class Deepseek(SimpleService):
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
         info = input_message.info.copy()
         version = info.pop('version')
+        system_prompt = input_message.info.pop('system_prompt', '')
         callback_data = {
             **input_message.info,
         }
-        messages = self.get_chat_history()
-        messages.append({'role': 'user', 'content': input_message.content})
+        messages = [
+            {'role': 'system', 'content': system_prompt},
+            *self.get_chat_history(),
+            {'role': 'user', 'content': input_message.content}
+        ]
         start_time = time.time()
         result = openrouter_run(version, messages, callback_data, 'Deepseek')
         process_time = timedelta(seconds=(time.time() - start_time))