@@ -35,3 +35,5 @@ def calculate_predict_price(request, body: PredictPriceInputSchema):
 
     return PredictPriceSchema(price=predicted_price)
 
+
+
@@ -12,24 +12,32 @@ from tools.public_api.models import APIStore
 
 class Deepseek(SimpleService):
     TOKENS_COST = {
-        'deepseek/deepseek-chat': {
-            'input': Decimal('390') / 1_000_000,
-            'output': Decimal('390') / 1_000_000,
+        # 'deepseek/deepseek-chat': {
+        #     'input': Decimal('390') / 1_000_000,
+        #     'output': Decimal('390') / 1_000_000,
+        # },
+        # 'deepseek/deepseek-r1': {
+        #     'input': Decimal('900') / 1_000_000,
+        #     'output': Decimal('900') / 1_000_000,
+        # },
+        # 'deepseek/deepseek-r1:free': {
+        #     'input': Decimal('0'),
+        #     'output': Decimal('0'),
+        # },
+        'deepseek/deepseek-v4-pro': {
+            'input': Decimal('218') / 1_000_000, 
+            'output': Decimal('435') / 1_000_000,
         },
-        'deepseek/deepseek-r1': {
-            'input': Decimal('900') / 1_000_000,
-            'output': Decimal('900') / 1_000_000,
-        },
-        'deepseek/deepseek-r1:free': {
-            'input': Decimal('0'),
-            'output': Decimal('0')
+        'deepseek/deepseek-v4-flash': {
+            'input': Decimal('70') / 1_000_000,
+            'output': Decimal('140') / 1_000_000,
         },
     }
-    PRICE_BIAS = Decimal('0.05')
 
     def calculate_price(self, version: str, input_tokens: int, output_tokens: int) -> Decimal:
         price_map = self.TOKENS_COST[version]
-        price = input_tokens * price_map['input'] + output_tokens * price_map['output'] + self.PRICE_BIAS
+        price = input_tokens * price_map['input'] + output_tokens * price_map['output']
+
         return price.quantize(Decimal('0.1'), rounding='ROUND_UP')
 
     def save_results(self, content: str, t: timedelta, save: bool = True) -> list[Message]:
@@ -47,15 +55,17 @@ 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', '')
+        system_prompt = info.pop('system_prompt', '')
+
         callback_data = {
-            **input_message.info,
+            **info,
         }
         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))
@@ -66,8 +76,11 @@ class Deepseek(SimpleService):
             output_tokens=result[2],
         )
         msgs = self.save_results(result[0], process_time)
+
         return msgs
 
+
+
     def get_chat_history(self, message_limit: int = 10, max_character_limit: int = 1500) -> list[dict[str, str | list]]:
         if isinstance(self.store, Chat):
             air_messages = list(
@@ -100,3 +113,4 @@ class Deepseek(SimpleService):
         while character_length > max_character_limit:
             character_length -= len(memory.pop(0)['content'])
         return memory
+
@@ -1,5 +1,4 @@
 from typing import List, Optional, Any
-
 from ninja import ModelSchema, Schema
 from pydantic import condecimal