1 files changed, 60 insertions, 58 deletions

diff --git a/g4f/Provider/Nexra.py b/g4f/Provider/Nexra.py
index b2b83837..33e794f6 100644
--- a/g4f/Provider/Nexra.py
+++ b/g4f/Provider/Nexra.py
@@ -1,32 +1,49 @@
 from __future__ import annotations
-import json
-from aiohttp import ClientSession
 
-from ..typing import AsyncResult, Messages
+from aiohttp import ClientSession
 from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
 from .helper import format_prompt
-from ..image import ImageResponse
+from .nexra.NexraBing import NexraBing
+from .nexra.NexraChatGPT import NexraChatGPT
+from .nexra.NexraChatGPT4o import NexraChatGPT4o
+from .nexra.NexraChatGPTWeb import NexraChatGPTWeb
+from .nexra.NexraGeminiPro import NexraGeminiPro
+from .nexra.NexraImageURL import NexraImageURL
+from .nexra.NexraLlama import NexraLlama
+from .nexra.NexraQwen import NexraQwen
 
 class Nexra(AsyncGeneratorProvider, ProviderModelMixin):
     url = "https://nexra.aryahcr.cc"
-    chat_api_endpoint = "https://nexra.aryahcr.cc/api/chat/gpt"
-    image_api_endpoint = "https://nexra.aryahcr.cc/api/image/complements"
     working = True
     supports_gpt_35_turbo = True
     supports_gpt_4 = True
+    supports_stream = True
     supports_system_message = True
     supports_message_history = True
-    
     default_model = 'gpt-3.5-turbo'
-    text_models = [
-        'gpt-4', 'gpt-4-0613', 'gpt-4-32k', 'gpt-4-0314', 'gpt-4-32k-0314',
-        'gpt-3.5-turbo', 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k-0613', 'gpt-3.5-turbo-0301',
-        'gpt-3', 'text-davinci-003', 'text-davinci-002', 'code-davinci-002',
-        'text-curie-001', 'text-babbage-001', 'text-ada-001',
-        'davinci', 'curie', 'babbage', 'ada', 'babbage-002', 'davinci-002',
-    ]
-    image_models = ['dalle', 'dalle2', 'dalle-mini', 'emi']
-    models = [*text_models, *image_models]
+    image_model = 'sdxl-turbo'
+    
+    models = (
+        *NexraBing.models,
+        *NexraChatGPT.models,
+        *NexraChatGPT4o.models,
+        *NexraChatGPTWeb.models,
+        *NexraGeminiPro.models,
+        *NexraImageURL.models,
+        *NexraLlama.models,
+        *NexraQwen.models,
+    )
+
+    model_to_provider = {
+        **{model: NexraChatGPT for model in NexraChatGPT.models},
+        **{model: NexraChatGPT4o for model in NexraChatGPT4o.models},
+        **{model: NexraChatGPTWeb for model in NexraChatGPTWeb.models},
+        **{model: NexraGeminiPro for model in NexraGeminiPro.models},
+        **{model: NexraImageURL for model in NexraImageURL.models},
+        **{model: NexraLlama for model in NexraLlama.models},
+        **{model: NexraQwen for model in NexraQwen.models},
+        **{model: NexraBing for model in NexraBing.models},
+    }
     
     model_aliases = {
         "gpt-4": "gpt-4-0613",
@@ -53,12 +70,20 @@ class Nexra(AsyncGeneratorProvider, ProviderModelMixin):
         "gpt-3": "babbage-002",
         "gpt-3": "davinci-002",
         
+        "gpt-4": "gptweb",
+        
+        "gpt-4": "Bing (Balanced)",
+        "gpt-4": "Bing (Creative)",
+        "gpt-4": "Bing (Precise)",
+        
         "dalle-2": "dalle2",
+        "sdxl": "sdxl-turbo",
     }
-    
+
+
     @classmethod
     def get_model(cls, model: str) -> str:
-        if model in cls.text_models or model in cls.image_models:
+        if model in cls.models:
             return model
         elif model in cls.model_aliases:
             return cls.model_aliases[model]
@@ -66,6 +91,14 @@ class Nexra(AsyncGeneratorProvider, ProviderModelMixin):
             return cls.default_model
 
     @classmethod
+    def get_api_endpoint(cls, model: str) -> str:
+        provider_class = cls.model_to_provider.get(model)
+
+        if provider_class:
+            return provider_class.api_endpoint
+        raise ValueError(f"API endpoint for model {model} not found.")
+
+    @classmethod
     async def create_async_generator(
         cls,
         model: str,
@@ -74,43 +107,12 @@ class Nexra(AsyncGeneratorProvider, ProviderModelMixin):
         **kwargs
     ) -> AsyncResult:
         model = cls.get_model(model)
-        
-        headers = {
-            "Content-Type": "application/json",
-        }
-        
-        async with ClientSession(headers=headers) as session:
-            if model in cls.image_models:
-                # Image generation
-                prompt = messages[-1]['content'] if messages else ""
-                data = {
-                    "prompt": prompt,
-                    "model": model,
-                    "response": "url"
-                }
-                async with session.post(cls.image_api_endpoint, json=data, proxy=proxy) as response:
-                    response.raise_for_status()
-                    result = await response.text()
-                    result_json = json.loads(result.strip('_'))
-                    image_url = result_json['images'][0] if result_json['images'] else None
-                    
-                    if image_url:
-                        yield ImageResponse(images=image_url, alt=prompt)
-            else:
-                # Text completion
-                data = {
-                    "messages": messages,
-                    "prompt": format_prompt(messages),
-                    "model": model,
-                    "markdown": False
-                }
-                async with session.post(cls.chat_api_endpoint, json=data, proxy=proxy) as response:
-                    response.raise_for_status()
-                    result = await response.text()
-                    
-                    try:
-                        json_response = json.loads(result)
-                        gpt_response = json_response.get('gpt', '')
-                        yield gpt_response
-                    except json.JSONDecodeError:
-                        yield result
+        api_endpoint = cls.get_api_endpoint(model)
+
+        provider_class = cls.model_to_provider.get(model)
+
+        if provider_class:
+            async for response in provider_class.create_async_generator(model, messages, proxy, **kwargs):
+                yield response
+        else:
+            raise ValueError(f"Provider for model {model} not found.")