diff options
| -rw-r--r-- | g4f/Provider/Nexra.py | 130 | ||||
| -rw-r--r-- | g4f/Provider/__init__.py | 2 | ||||
| -rw-r--r-- | g4f/models.py | 27 |
3 files changed, 128 insertions, 31 deletions
diff --git a/g4f/Provider/Nexra.py b/g4f/Provider/Nexra.py index 4914b930..e2c3e197 100644 --- a/g4f/Provider/Nexra.py +++ b/g4f/Provider/Nexra.py @@ -1,16 +1,19 @@ 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 = "https://nexra.aryahcr.cc/api/chat/gpt" + 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 @@ -20,34 +23,19 @@ class Nexra(AsyncGeneratorProvider, ProviderModelMixin): default_model = 'gpt-3.5-turbo' models = [ - # Working with text - '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', + # 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", @@ -90,9 +78,24 @@ class Nexra(AsyncGeneratorProvider, ProviderModelMixin): messages: Messages, proxy: str = None, **kwargs - ) -> AsyncResult: + ) -> 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", } @@ -104,8 +107,75 @@ class Nexra(AsyncGeneratorProvider, ProviderModelMixin): "markdown": False, "stream": False, } - async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + 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 diff --git a/g4f/Provider/__init__.py b/g4f/Provider/__init__.py index 10499fdf..6488a814 100644 --- a/g4f/Provider/__init__.py +++ b/g4f/Provider/__init__.py @@ -12,7 +12,7 @@ from .needs_auth import * from .AI365VIP import AI365VIP from .Allyfy import Allyfy from .AiChatOnline import AiChatOnline -from .AiChats import AiChats +from .AiChats import AiChats from .Aura import Aura from .Bing import Bing from .BingCreateImages import BingCreateImages diff --git a/g4f/models.py b/g4f/models.py index d0cb9f49..456a2f38 100644 --- a/g4f/models.py +++ b/g4f/models.py @@ -461,6 +461,28 @@ flux_disney = Model( ) +### ### +dalle = Model( + name = 'dalle', + base_provider = '', + best_provider = IterListProvider([Nexra]) + +) + +dalle_mini = Model( + name = 'dalle-mini', + base_provider = '', + best_provider = IterListProvider([Nexra]) + +) + +emi = Model( + name = 'emi', + base_provider = '', + best_provider = IterListProvider([Nexra]) + +) + class ModelUtils: """ Utility class for mapping string identifiers to Model instances. @@ -617,6 +639,11 @@ class ModelUtils: 'flux-3d': flux_3d, 'flux-disney': flux_disney, + +### ### +'dalle': dalle, +'dalle-mini': dalle_mini, +'emi': emi, } _all_models = list(ModelUtils.convert.keys()) |