@@ -70,9 +70,20 @@ class Flux(SimpleService):
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
         start_time = time.time()
         version = input_message.info.get('version')
+        user_prompt = self.translate_prompt(input_message.content)
+        prompt = f"""
+        {user_prompt}.
+        Clear main subject and coherent scene context.
+        Balanced composition with readable foreground, midground, and background.
+        Natural, consistent lighting with clean shadows and good tonal balance.
+        Accurate proportions, clean geometry, and stable spatial relationships.
+        Crisp important details, clear textures, and minimal visual artifacts.
+        """
         callback_data = dict(
             {
-                'prompt': self.translate_prompt(input_message.content),
+                'prompt': prompt,
+                'go_fast': False,
+                'output_quality': 100,
                 **input_message.info,
             }
         )
@@ -17,17 +17,14 @@ from payments.selectors.payment_plan_selector import PaymentPlanSelector
 
 
 class Lyria(SimpleService):
-    TOKENS_COST = Decimal('0.6')  # per 1 sec of output audio
+    TOKENS_COST = {'lyria-3': Decimal('12'), 'lyria-3-pro': Decimal('24')}
 
     @classmethod
     def predict_price(cls, content: str, file_exists: bool, info: dict[str, Any]) -> Decimal | None:
-        duration = info.get('duration', 32)
-        price = cls.TOKENS_COST * duration
-        return price.quantize(Decimal('0.1'), rounding='ROUND_UP')
+        return cls.TOKENS_COST[info['version']]
 
-    def calculate_price(self, duration: int) -> Decimal:
-        price = self.TOKENS_COST * duration
-        return price.quantize(Decimal('0.1'), rounding='ROUND_UP')
+    def calculate_price(self, version: str) -> Decimal:
+        return self.TOKENS_COST[version]
 
     def save_results(self, content: str, t: timedelta, audio: str, save: bool = True) -> list[Message]:
         msg = Message(
@@ -41,23 +38,22 @@ class Lyria(SimpleService):
         return [msg]
 
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
-        if (
-            (balance := PaymentPlanSelector(self.store.user).get_current_balance())
-            < (cost := self.TOKENS_COST * 32)
+        version = input_message.info.pop('version', 'lyria-3')
+        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < (
+            cost := self.TOKENS_COST[version]
         ):
             raise InsufficientBalance(balance, cost)
-        callback_data = {
-            'prompt': self.translate_prompt(input_message.content),
-            **input_message.info
-        }
+        callback_data = {'prompt': input_message.content}
+        if file := input_message.file:
+            callback_data.update({'images': [file.url]})
         start_time = time.time()
         try:
-            video = replicate_run(f'google/lyria-2', callback_data)
+            video = replicate_run(f'google/{version}', callback_data)
         except ModelError as exc:
             if any(error in str(exc) for error in ('E005', 'E006', 'sexual')):
                 raise RequestBlocked
             raise GenerationException from exc
         process_time = timedelta(seconds=(time.time() - start_time))
-        self.handle_invoice(input_message.content_object.model, duration=32)
+        self.handle_invoice(input_message.content_object.model, version)
         msgs = self.save_results(input_message.content, process_time, video, save)
         return msgs
@@ -52,9 +52,36 @@ class Midjourney(SimpleService):
 
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
         start_time = time.time()
-        translated_prompt = self.translate_prompt(input_message.content)
-        activation_prompt = f'mdjrny-v4 style a highly detailed {translated_prompt}'
-        callback_data = dict(prompt=activation_prompt, **input_message.info)
+        base_prompt = input_message.content
+        activation_prompt = f"""
+        Transform the user input into a single high-quality photographic image prompt.
+        USER INPUT:
+        {base_prompt}
+        RULES:
+        - Convert input into a realistic visual scene
+        - Keep one clear main subject unless multiple are explicitly required
+        - Ensure the scene looks like a real photograph, not an illustration or CGI
+        STYLE:
+        real-world photography, natural and believable scene, no artificial or cartoon look
+        COMPOSITION:
+        clear subject focus, natural framing, balanced but unposed layout,
+        real depth between foreground, subject, and background
+        CAMERA:
+        professional camera look, 35–85mm lens perspective,
+        natural depth of field, realistic focus and perspective
+        LIGHTING:
+        natural or practical lighting only (sunlight, indoor lamps, ambient light),
+        soft realistic shadows, no artificial glow or dramatic effects
+        COLOR:
+        neutral and realistic color reproduction,
+        slight natural tonal variation, no heavy grading or stylization
+        DETAIL:
+        real materials and textures, natural imperfections,
+        avoid smooth plastic-like or CGI surfaces
+        OUTPUT:
+        Return ONLY a single concise image-generation prompt describing the final scene.
+        """
+        callback_data = dict(prompt=activation_prompt, prompt_optimizer=False,**input_message.info)
         results = replicate_run(self._CALLBACK, callback_data)
         process_time = timedelta(seconds=(time.time() - start_time))
         self.handle_invoice(input_message.content_object.model, input_message=input_message)