from __future__ import annotations import json import requests from ...typing import CreateResult, Messages from ..base_provider import ProviderModelMixin, AbstractProvider from ..helper import format_prompt 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 = True supports_stream = True default_model = 'Balanced' models = [default_model, 'Creative', 'Precise'] model_aliases = { "gpt-4": "Balanced", "gpt-4": "Creative", "gpt-4": "Precise", } @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 def create_completion( cls, model: str, messages: Messages, stream: bool, markdown: bool = False, **kwargs ) -> CreateResult: model = cls.get_model(model) headers = { 'Content-Type': 'application/json' } data = { "messages": [ { "role": "user", "content": format_prompt(messages) } ], "conversation_style": model, "markdown": markdown, "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 if not full_message: yield "No message received"