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author | kqlio67 <kqlio67@users.noreply.github.com> | 2024-10-21 19:01:10 +0200 |
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committer | kqlio67 <kqlio67@users.noreply.github.com> | 2024-10-21 19:01:10 +0200 |
commit | 6a3684a7b21c2275a5ba38ed98fc904aced2a5fc (patch) | |
tree | b332e29f6222674a4aa73cbb32820882033c4698 | |
parent | Update provider . (diff) | |
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Diffstat (limited to '')
-rw-r--r-- | g4f/Provider/nexra/NexraBing.py | 142 | ||||
-rw-r--r-- | g4f/models.py | 3 |
2 files changed, 71 insertions, 74 deletions
diff --git a/g4f/Provider/nexra/NexraBing.py b/g4f/Provider/nexra/NexraBing.py index 1e56ded8..755bedd5 100644 --- a/g4f/Provider/nexra/NexraBing.py +++ b/g4f/Provider/nexra/NexraBing.py @@ -1,95 +1,91 @@ from __future__ import annotations -from aiohttp import ClientSession -from aiohttp.client_exceptions import ContentTypeError - -from ...typing import AsyncResult, Messages -from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin -from ..helper import format_prompt import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ..helper import format_prompt -class NexraBing(AsyncGeneratorProvider, ProviderModelMixin): +class NexraBing(AbstractProvider, ProviderModelMixin): label = "Nexra Bing" url = "https://nexra.aryahcr.cc/documentation/bing/en" api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements" - working = False - supports_stream = False + working = True + supports_stream = True - default_model = 'Bing (Balanced)' - models = ['Bing (Balanced)', 'Bing (Creative)', 'Bing (Precise)'] + default_model = 'Balanced' + models = [default_model, 'Creative', 'Precise'] model_aliases = { - "gpt-4": "Bing (Balanced)", - "gpt-4": "Bing (Creative)", - "gpt-4": "Bing (Precise)", + "gpt-4": "Balanced", + "gpt-4": "Creative", + "gpt-4": "Precise", } @classmethod - def get_model_and_style(cls, model: str) -> tuple[str, str]: - # Default to the default model if not found - model = cls.model_aliases.get(model, model) - if model not in cls.models: - model = cls.default_model - - # Extract the base model and conversation style - base_model, conversation_style = model.split(' (') - conversation_style = conversation_style.rstrip(')') - return base_model, conversation_style - + 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( + def create_completion( cls, model: str, messages: Messages, - proxy: str = None, - stream: bool = False, - markdown: bool = False, + stream: bool, **kwargs - ) -> AsyncResult: - base_model, conversation_style = cls.get_model_and_style(model) - + ) -> CreateResult: + model = cls.get_model(model) + headers = { - "Content-Type": "application/json", - "origin": cls.url, - "referer": f"{cls.url}/chat", + 'Content-Type': 'application/json' } - async with ClientSession(headers=headers) as session: - prompt = format_prompt(messages) - data = { - "messages": [ - { - "role": "user", - "content": prompt - } - ], - "conversation_style": conversation_style, - "markdown": markdown, - "stream": stream, - "model": base_model - } - async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: - response.raise_for_status() - try: - # Read the entire response text - text_response = await response.text() - # Split the response on the separator character - segments = text_response.split('\x1e') - - complete_message = "" - for segment in segments: - if not segment.strip(): - continue - try: - response_data = json.loads(segment) - if response_data.get('message'): - complete_message = response_data['message'] - if response_data.get('finish'): - break - except json.JSONDecodeError: - raise Exception(f"Failed to parse segment: {segment}") + + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ], + "conversation_style": model, + "markdown": False, + "stream": stream, + "model": "Bing" + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=True) + + return cls.process_response(response) + + @classmethod + def process_response(cls, response): + if response.status_code != 200: + yield f"Error: {response.status_code}" + return + + full_message = "" + for chunk in response.iter_content(chunk_size=None): + if chunk: + messages = chunk.decode('utf-8').split('\x1e') + for message in messages: + try: + json_data = json.loads(message) + if json_data.get('finish', False): + return + current_message = json_data.get('message', '') + if current_message: + new_content = current_message[len(full_message):] + if new_content: + yield new_content + full_message = current_message + except json.JSONDecodeError: + continue - # Yield the complete message - yield complete_message - except ContentTypeError: - raise Exception("Failed to parse response content type.") + if not full_message: + yield "No message received" diff --git a/g4f/models.py b/g4f/models.py index 99778f0b..493e1c70 100644 --- a/g4f/models.py +++ b/g4f/models.py @@ -39,6 +39,7 @@ from .Provider import ( Liaobots, MagickPen, MetaAI, + NexraBing, NexraBlackbox, NexraChatGPT, NexraChatGPT4o, @@ -150,7 +151,7 @@ gpt_4_turbo = Model( gpt_4 = Model( name = 'gpt-4', base_provider = 'OpenAI', - best_provider = IterListProvider([Chatgpt4Online, Ai4Chat, NexraChatGPT, NexraChatGptV2, NexraChatGptWeb, Airforce, Bing, OpenaiChat, gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider]) + best_provider = IterListProvider([Chatgpt4Online, Ai4Chat, NexraBing, NexraChatGPT, NexraChatGptV2, NexraChatGptWeb, Airforce, Bing, OpenaiChat, gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider]) ) # o1 |