1 files changed, 0 insertions, 103 deletions
diff --git a/g4f/Provider/TwitterBio.py b/g4f/Provider/TwitterBio.py
deleted file mode 100644
index c143e4ff..00000000
--- a/g4f/Provider/TwitterBio.py
+++ /dev/null
@@ -1,103 +0,0 @@
-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)