@@ -8,6 +8,7 @@ from ml_model.services.djourney import Djourney
 from ml_model.services.epicphotogasm import Epicphotogasm
 from ml_model.services.flux import Flux
 from ml_model.services.fluxproultra import Fluxproultra
+from ml_model.services.gemini import Gemini
 from ml_model.services.granite import Granite
 from ml_model.services.grok import Grok
 from ml_model.services.iconic import Iconic
@@ -0,0 +1,136 @@
+import base64
+import time
+import filetype
+
+from datetime import timedelta
+from decimal import Decimal
+from io import BytesIO
+from PIL import Image
+
+from django.db.models.fields.files import FieldFile
+
+from messages.models import Message
+
+from ml_model.services.base import SimpleService
+from ml_model.tasks import openrouter_run
+
+from tools.chats.models import Chat
+from tools.copywrite.models import Copywrite
+from tools.public_api.models import APIStore
+
+
+class Gemini(SimpleService):
+    """
+    Gemini Service
+    contains abstract method make, which makes a generation
+    """
+
+    TOKENS_COST = {
+        'gemini-2.0-flash-001': {
+            'input': Decimal('20'),
+            'output': Decimal('80'),
+            'input_imgs': Decimal('5.16'),
+        },
+    }
+
+    def calculate_price(self, version: str, input_tokens: int, output_tokens: int, image: FieldFile) -> Decimal:
+        price_map = self.TOKENS_COST[version.split('/')[1]]
+        price = (
+                input_tokens * price_map['input'] / 1_000_000
+                + output_tokens * price_map['output'] / 1_000_000
+        )
+        if image:
+            price += price_map['input_imgs'] / 1_000
+        return price.quantize(Decimal('0.1'), rounding='ROUND_UP')
+
+    def save_results(
+            self, content: str, t: timedelta, save: bool = True
+    ) -> list[Message]:
+        msgs = [
+            Message(
+                content=content,
+                content_object=self.store,
+                elapsed_time=t,
+            )
+        ]
+        if save:
+            return Message.objects.bulk_create(msgs)
+        return msgs
+
+    def make(self, input_message: Message, save: bool = True) -> list[Message]:
+        info = input_message.info.copy()
+        version = info.pop('version')
+        callback_data = {
+            'provider': {'order': ['Google AI Studio']},
+            **input_message.info,
+        }
+        messages = self.get_chat_history()
+        image = input_message.file
+        if image:
+            kind = filetype.guess(image.read(20))
+            mime = kind.mime if kind else 'application/octet-stream'
+            normalized_image = Image.open(image)
+            format = 'jpeg' if kind.extension == 'jpg' else kind.extension
+            buf = BytesIO()
+            normalized_image.save(buf, format=format)
+            image_url = (
+                f'data:{mime};base64,{base64.b64encode(buf.getvalue()).decode("utf-8")}'
+            )
+            buf.close()
+            messages[-1]['content'] = [
+                {
+                    'type': 'text',
+                    'text': input_message.content
+                },
+                {
+                    'type': 'image_url',
+                    'image_url': {
+                        'url': image_url
+                    }
+                }
+            ]
+        start_time = time.time()
+        result = openrouter_run(version, messages, callback_data, self.title)
+        process_time = timedelta(seconds=(time.time() - start_time))
+        self.handle_invoice(
+            input_message.content_object.model,
+            version=version,
+            input_tokens=result[1],
+            output_tokens=result[2],
+            image=image
+        )
+        msgs = self.save_results(result[0], process_time)
+        return msgs
+
+    def get_chat_history(self, message_limit: int = 10, max_character_limit: int = 1500):
+        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]
+                )
+            )
+        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]
+                )
+            )
+        memory = []
+        for msg in air_messages:
+            content = msg.content or ''
+            if msg.from_model:
+                memory.append({'role': 'assistant', 'content': content})
+            else:
+                memory.append({'role': 'user', 'content': content})
+        character_length = sum(len(content['content']) for content in memory)
+        while character_length > max_character_limit:
+            character_length -= len(memory.pop(0))
+        return memory
@@ -3,7 +3,6 @@ SECRET_KEY=testtest
 DEBUG=true
 
 # NEURON MODELS
-OPENROUTER_API_KEY=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
 OPENAI_API_KEY=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
 STABLE_DIFFUSION_API_KEY=sk-fztQxZobaL0SD7PgpmK7XMQlyNivpKFZNJnqAVG2CcbvAP6Z
 REPLICATE_API_KEY=r8_HBk6Ts5UJU60nDOUl1V6Uej4ihAAxUc3HAZLO
@@ -14,6 +13,7 @@ MISTRAL_API_KEY=CYtZSCQXZFzHcpJvWOjWNx4EHjf5kWQc
 DEEPL_API_KEY=4bb58b98-ca95-5978-9be0-ed437df6c15c:fx
 SERPER_API_KEY=ed8e0dbcc26dacf3f7f99fbc8b3add9ada0c793e
 FLUX_API_KEY=dccaf377-aecf-4cf0-aff4-dde47cee340d
+OPENROUTER_API_KEY=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
 
 # EXTERNAL SERVICES
 OPENAI_PROXY_HOST=neuron-proxy:8080