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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 NexraChatGPT(AbstractProvider, ProviderModelMixin):
label = "Nexra ChatGPT"
url = "https://nexra.aryahcr.cc/documentation/chatgpt/en"
api_endpoint = "https://nexra.aryahcr.cc/api/chat/gpt"
working = True
default_model = 'gpt-3.5-turbo'
models = ['gpt-4', 'gpt-4-0613', 'gpt-4-0314', 'gpt-4-32k-0314', default_model, 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k-0613', 'gpt-3.5-turbo-0301', 'text-davinci-003', 'text-davinci-002', 'code-davinci-002', 'gpt-3', 'text-curie-001', 'text-babbage-001', 'text-ada-001', 'davinci', 'curie', 'babbage', 'ada', 'babbage-002', 'davinci-002']
model_aliases = {
"gpt-4": "gpt-4-0613",
"gpt-4": "gpt-4-32k",
"gpt-4": "gpt-4-0314",
"gpt-4": "gpt-4-32k-0314",
"gpt-3.5-turbo": "gpt-3.5-turbo-16k",
"gpt-3.5-turbo": "gpt-3.5-turbo-0613",
"gpt-3.5-turbo": "gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo": "gpt-3.5-turbo-0301",
"gpt-3": "text-davinci-003",
"gpt-3": "text-davinci-002",
"gpt-3": "code-davinci-002",
"gpt-3": "text-curie-001",
"gpt-3": "text-babbage-001",
"gpt-3": "text-ada-001",
"gpt-3": "text-ada-001",
"gpt-3": "davinci",
"gpt-3": "curie",
"gpt-3": "babbage",
"gpt-3": "ada",
"gpt-3": "babbage-002",
"gpt-3": "davinci-002",
}
@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,
proxy: str = None,
markdown: bool = False,
**kwargs
) -> CreateResult:
model = cls.get_model(model)
headers = {
'Content-Type': 'application/json'
}
data = {
"messages": [],
"prompt": format_prompt(messages),
"model": model,
"markdown": markdown
}
response = requests.post(cls.api_endpoint, headers=headers, json=data)
return cls.process_response(response)
@classmethod
def process_response(cls, response):
if response.status_code == 200:
try:
data = response.json()
return data.get('gpt', '')
except json.JSONDecodeError:
return "Error: Unable to decode JSON response"
else:
return f"Error: {response.status_code}"
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