diff options
Diffstat (limited to 'g4f/Provider/Nexra.py')
| -rw-r--r-- | g4f/Provider/Nexra.py | 118 |
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.") |