gpt4free/g4f/Provider/nexra/NexraBing.py

97 lines
3.5 KiB
Python

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
class NexraBing(AsyncGeneratorProvider, ProviderModelMixin):
label = "Nexra Bing"
url = "https://nexra.aryahcr.cc/documentation/bing/en"
api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements"
working = True
supports_gpt_4 = False
supports_stream = False
default_model = 'Bing (Balanced)'
models = ['Bing (Balanced)', 'Bing (Creative)', 'Bing (Precise)']
model_aliases = {
"gpt-4": "Bing (Balanced)",
"gpt-4": "Bing (Creative)",
"gpt-4": "Bing (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
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
proxy: str = None,
stream: bool = False,
markdown: bool = False,
**kwargs
) -> AsyncResult:
base_model, conversation_style = cls.get_model_and_style(model)
headers = {
"Content-Type": "application/json",
"origin": cls.url,
"referer": f"{cls.url}/chat",
}
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}")
# Yield the complete message
yield complete_message
except ContentTypeError:
raise Exception("Failed to parse response content type.")