gpt4free/g4f/Provider/TwitterBio.py

104 lines
3.7 KiB
Python

from __future__ import annotations
import json
import re
from aiohttp import ClientSession
from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
from .helper import format_prompt
class TwitterBio(AsyncGeneratorProvider, ProviderModelMixin):
url = "https://www.twitterbio.io"
api_endpoint_mistral = "https://www.twitterbio.io/api/mistral"
api_endpoint_openai = "https://www.twitterbio.io/api/openai"
working = True
supports_gpt_35_turbo = True
default_model = 'gpt-3.5-turbo'
models = [
'mistralai/Mixtral-8x7B-Instruct-v0.1',
'gpt-3.5-turbo',
]
model_aliases = {
"mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1",
}
@classmethod
def get_model(cls, model: str) -> str:
if model in cls.models:
return model
return cls.default_model
@staticmethod
def format_text(text: str) -> str:
text = re.sub(r'\s+', ' ', text.strip())
text = re.sub(r'\s+([,.!?])', r'\1', text)
return text
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
proxy: str = None,
**kwargs
) -> AsyncResult:
model = cls.get_model(model)
headers = {
"accept": "*/*",
"accept-language": "en-US,en;q=0.9",
"cache-control": "no-cache",
"content-type": "application/json",
"origin": cls.url,
"pragma": "no-cache",
"priority": "u=1, i",
"referer": f"{cls.url}/",
"sec-ch-ua": '"Chromium";v="127", "Not)A;Brand";v="99"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"Linux"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-origin",
"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36"
}
async with ClientSession(headers=headers) as session:
prompt = format_prompt(messages)
data = {
"prompt": f'{prompt}.'
}
if model == 'mistralai/Mixtral-8x7B-Instruct-v0.1':
api_endpoint = cls.api_endpoint_mistral
elif model == 'gpt-3.5-turbo':
api_endpoint = cls.api_endpoint_openai
else:
raise ValueError(f"Unsupported model: {model}")
async with session.post(api_endpoint, json=data, proxy=proxy) as response:
response.raise_for_status()
buffer = ""
async for line in response.content:
line = line.decode('utf-8').strip()
if line.startswith('data: '):
try:
json_data = json.loads(line[6:])
if model == 'mistralai/Mixtral-8x7B-Instruct-v0.1':
if 'choices' in json_data and len(json_data['choices']) > 0:
text = json_data['choices'][0].get('text', '')
if text:
buffer += text
elif model == 'gpt-3.5-turbo':
text = json_data.get('text', '')
if text:
buffer += text
except json.JSONDecodeError:
continue
elif line == 'data: [DONE]':
break
if buffer:
yield cls.format_text(buffer)