0.3.2.6

1 files changed, 181 insertions, 0 deletions

diff --git a/g4f/Provider/Nexra.py b/g4f/Provider/Nexra.py
new file mode 100644
index 00000000..e2c3e197
--- /dev/null
+++ b/g4f/Provider/Nexra.py
@@ -0,0 +1,181 @@
+from __future__ import annotations
+
+import json
+import base64
+from aiohttp import ClientSession
+from typing import AsyncGenerator
+
+from ..typing import AsyncResult, Messages
+from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
+from ..image import ImageResponse
+from .helper import format_prompt
+
+class Nexra(AsyncGeneratorProvider, ProviderModelMixin):
+    url = "https://nexra.aryahcr.cc"
+    api_endpoint_text = "https://nexra.aryahcr.cc/api/chat/gpt"
+    api_endpoint_image = "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'
+    models = [
+        # 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', 'dalle-mini', 'emi'
+    ]
+    
+    image_models = {"dalle", "dalle-mini", "emi"}
+    text_models = set(models) - image_models
+    
+    model_aliases = {
+        "gpt-4": "gpt-4-0613",
+        "gpt-4": "gpt-4-32k",
+        "gpt-4": "gpt-4-0314",
+        "gpt-4": "gpt-4-32k-0314",
+        
+        "gpt-3.5-turbo": "gpt-3.5-turbo-16k",
+        "gpt-3.5-turbo": "gpt-3.5-turbo-0613",
+        "gpt-3.5-turbo": "gpt-3.5-turbo-16k-0613",
+        "gpt-3.5-turbo": "gpt-3.5-turbo-0301",
+        
+        "gpt-3": "text-davinci-003",
+        "gpt-3": "text-davinci-002",
+        "gpt-3": "code-davinci-002",
+        "gpt-3": "text-curie-001",
+        "gpt-3": "text-babbage-001",
+        "gpt-3": "text-ada-001",
+        "gpt-3": "text-ada-001",
+        "gpt-3": "davinci",
+        "gpt-3": "curie",
+        "gpt-3": "babbage",
+        "gpt-3": "ada",
+        "gpt-3": "babbage-002",
+        "gpt-3": "davinci-002",
+    }
+
+    @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
+    async def create_async_generator(
+        cls,
+        model: str,
+        messages: Messages,
+        proxy: str = None,
+        **kwargs
+    ) -> AsyncGenerator[str | ImageResponse, None]:
+        model = cls.get_model(model)
+        
+        if model in cls.image_models:
+            async for result in cls.create_image_async_generator(model, messages, proxy, **kwargs):
+                yield result
+        else:
+            async for result in cls.create_text_async_generator(model, messages, proxy, **kwargs):
+                yield result
+
+    @classmethod
+    async def create_text_async_generator(
+        cls,
+        model: str,
+        messages: Messages,
+        proxy: str = None,
+        **kwargs
+    ) -> AsyncGenerator[str, None]:
+        headers = {
+            "Content-Type": "application/json",
+        }
+        async with ClientSession(headers=headers) as session:
+            data = {
+                "messages": messages,
+                "prompt": format_prompt(messages),
+                "model": model,
+                "markdown": False,
+                "stream": False,
+            }
+            async with session.post(cls.api_endpoint_text, json=data, proxy=proxy) as response:
+                response.raise_for_status()
+                result = await response.text()
+                json_result = json.loads(result)
+                yield json_result["gpt"]
+
+    @classmethod
+    async def create_image_async_generator(
+        cls,
+        model: str,
+        messages: Messages,
+        proxy: str = None,
+        **kwargs
+    ) -> AsyncGenerator[ImageResponse | str, None]:
+        headers = {
+            "Content-Type": "application/json"
+        }
+
+        prompt = messages[-1]['content'] if messages else ""
+
+        data = {
+            "prompt": prompt,
+            "model": model
+        }
+
+        async def process_response(response_text: str) -> ImageResponse | None:
+            json_start = response_text.find('{')
+            if json_start != -1:
+                json_data = response_text[json_start:]
+                try:
+                    response_data = json.loads(json_data)
+                    image_data = response_data.get('images', [])[0]
+                    
+                    if image_data.startswith('data:image/'):
+                        return ImageResponse([image_data], "Generated image")
+                    
+                    try:
+                        base64.b64decode(image_data)
+                        data_uri = f"data:image/jpeg;base64,{image_data}"
+                        return ImageResponse([data_uri], "Generated image")
+                    except:
+                        print("Invalid base64 data")
+                        return None
+                except json.JSONDecodeError:
+                    print("Failed to parse JSON.")
+            else:
+                print("No JSON data found in the response.")
+            return None
+
+        async with ClientSession(headers=headers) as session:
+            async with session.post(cls.api_endpoint_image, json=data, proxy=proxy) as response:
+                response.raise_for_status()
+                response_text = await response.text()
+                
+                image_response = await process_response(response_text)
+                if image_response:
+                    yield image_response
+                else:
+                    yield "Failed to process image data."
+
+    @classmethod
+    async def create_async(
+        cls,
+        model: str,
+        messages: Messages,
+        proxy: str = None,
+        **kwargs
+    ) -> str:
+        async for response in cls.create_async_generator(model, messages, proxy, **kwargs):
+            if isinstance(response, ImageResponse):
+                return response.images[0]
+            return response