0.3.2.6

1 files changed, 103 insertions, 0 deletions

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