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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 NexraChatGPT4o(AbstractProvider, ProviderModelMixin):
label = "Nexra ChatGPT4o"
url = "https://nexra.aryahcr.cc/documentation/chatgpt/en"
api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements"
working = True
supports_stream = True
default_model = "gpt-4o"
models = [default_model]
@classmethod
def get_model(cls, model: str) -> str:
return cls.default_model
@classmethod
def create_completion(
cls,
model: str,
messages: Messages,
stream: bool,
proxy: str = None,
markdown: bool = False,
**kwargs
) -> CreateResult:
model = cls.get_model(model)
headers = {
'Content-Type': 'application/json'
}
data = {
"messages": [
{
"role": "user",
"content": format_prompt(messages)
}
],
"stream": stream,
"markdown": markdown,
"model": model
}
response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream)
if stream:
return cls.process_streaming_response(response)
else:
return cls.process_non_streaming_response(response)
@classmethod
def process_non_streaming_response(cls, response):
if response.status_code == 200:
try:
content = response.text.lstrip(' ')
data = json.loads(content)
return data.get('message', '')
except json.JSONDecodeError:
return "Error: Unable to decode JSON response"
else:
return f"Error: {response.status_code}"
@classmethod
def process_streaming_response(cls, response):
full_message = ""
for line in response.iter_lines(decode_unicode=True):
if line:
try:
line = line.lstrip(' ')
data = json.loads(line)
if data.get('finish'):
break
message = data.get('message', '')
if message and message != full_message:
yield message[len(full_message):]
full_message = message
except json.JSONDecodeError:
pass
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