Delete api/providers

api/providers/gizai.py

@@ -1,152 +0,0 @@
-from __future__ import annotations
-
-import json
-from aiohttp import ClientSession
-
-from ..typing import AsyncResult, Messages
-from ..image import ImageResponse
-from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
-from .helper import format_prompt
-
-
-class GizAI(AsyncGeneratorProvider, ProviderModelMixin):
-    url = "https://app.giz.ai/assistant/"
-    api_endpoint = "https://app.giz.ai/api/data/users/inferenceServer.infer"
-    working = True
-
-    supports_system_message = True
-    supports_message_history = True
-
-    # Chat models
-    default_model = 'chat-gemini-flash'
-    chat_models = [
-        default_model,
-        'chat-gemini-pro',
-        'chat-gpt4m',
-        'chat-gpt4',
-        'claude-sonnet',
-        'claude-haiku',
-        'llama-3-70b',
-        'llama-3-8b',
-        'mistral-large',
-        'chat-o1-mini'
-    ]
-
-    # Image models
-    image_models = [
-        'flux1',
-        'sdxl',
-        'sd',
-        'sd35',
-    ]
-
-    models = [*chat_models, *image_models]
-
-    model_aliases = {
-        # Chat model aliases
-        "gemini-flash": "chat-gemini-flash",
-        "gemini-pro": "chat-gemini-pro",
-        "gpt-4o-mini": "chat-gpt4m",
-        "gpt-4o": "chat-gpt4",
-        "claude-3.5-sonnet": "claude-sonnet",
-        "claude-3-haiku": "claude-haiku",
-        "llama-3.1-70b": "llama-3-70b",
-        "llama-3.1-8b": "llama-3-8b",
-        "o1-mini": "chat-o1-mini",
-        # Image model aliases
-        "sd-1.5": "sd",
-        "sd-3.5": "sd35",
-        "flux-schnell": "flux1",
-    }
-
-    @classmethod
-    def get_model(cls, model: str) -> str:
-        if model in cls.models:
-            return model
-        elif model in cls.model_aliases:
-            return cls.model_aliases[model]
-        else:
-            return cls.default_model
-
-    @classmethod
-    def is_image_model(cls, model: str) -> bool:
-        return model in cls.image_models
-
-    @classmethod
-    async def create_async_generator(
-        cls,
-        model: str,
-        messages: Messages,
-        proxy: str = None,
-        **kwargs
-    ) -> AsyncResult:
-        model = cls.get_model(model)
-
-        headers = {
-            'Accept': 'application/json, text/plain, */*',
-            'Accept-Language': 'en-US,en;q=0.9',
-            'Cache-Control': 'no-cache',
-            'Connection': 'keep-alive',
-            'Content-Type': 'application/json',
-            'Origin': 'https://app.giz.ai',
-            'Pragma': 'no-cache',
-            'Sec-Fetch-Dest': 'empty',
-            'Sec-Fetch-Mode': 'cors',
-            'Sec-Fetch-Site': 'same-origin',
-            'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36',
-            'sec-ch-ua': '"Not?A_Brand";v="99", "Chromium";v="130"',
-            'sec-ch-ua-mobile': '?0',
-            'sec-ch-ua-platform': '"Linux"'
-        }
-
-        async with ClientSession() as session:
-            if cls.is_image_model(model):
-                # Image generation
-                prompt = messages[-1]["content"]
-                data = {
-                    "model": model,
-                    "input": {
-                        "width": "1024",
-                        "height": "1024",
-                        "steps": 4,
-                        "output_format": "webp",
-                        "batch_size": 1,
-                        "mode": "plan",
-                        "prompt": prompt
-                    }
-                }
-                async with session.post(
-                    cls.api_endpoint,
-                    headers=headers,
-                    data=json.dumps(data),
-                    proxy=proxy
-                ) as response:
-                    response.raise_for_status()
-                    response_data = await response.json()
-                    if response_data.get('status') == 'completed' and response_data.get('output'):
-                        for url in response_data['output']:
-                            yield ImageResponse(images=url, alt="Generated Image")
-            else:
-                # Chat completion
-                data = {
-                    "model": model,
-                    "input": {
-                        "messages": [
-                            {
-                                "type": "human",
-                                "content": format_prompt(messages)
-                            }
-                        ],
-                        "mode": "plan"
-                    },
-                    "noStream": True
-                }
-                async with session.post(
-                    cls.api_endpoint,
-                    headers=headers,
-                    data=json.dumps(data),
-                    proxy=proxy
-                ) as response:
-                    response.raise_for_status()
-                    result = await response.json()
-                    yield result.get('output', '')