diff options
| -rw-r--r-- | g4f/Provider/TwitterBio.py | 103 | ||||
| -rw-r--r-- | g4f/Provider/__init__.py | 1 | ||||
| -rw-r--r-- | g4f/models.py | 21 |
3 files changed, 115 insertions, 10 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) diff --git a/g4f/Provider/__init__.py b/g4f/Provider/__init__.py index e5234685..83d3e6e1 100644 --- a/g4f/Provider/__init__.py +++ b/g4f/Provider/__init__.py @@ -51,6 +51,7 @@ from .Replicate import Replicate from .ReplicateHome import ReplicateHome from .Rocks import Rocks from .TeachAnything import TeachAnything +from .TwitterBio import TwitterBio from .Upstage import Upstage from .Vercel import Vercel from .WhiteRabbitNeo import WhiteRabbitNeo diff --git a/g4f/models.py b/g4f/models.py index 4176f0a2..a6c259e3 100644 --- a/g4f/models.py +++ b/g4f/models.py @@ -37,6 +37,7 @@ from .Provider import ( Replicate, ReplicateHome, TeachAnything, + TwitterBio, Upstage, You, ) @@ -91,7 +92,7 @@ gpt_35_turbo = Model( name = 'gpt-3.5-turbo', base_provider = 'openai', best_provider = IterListProvider([ - Allyfy, + Allyfy, TwitterBio, ]) ) @@ -140,50 +141,50 @@ gigachat = Model( ### Meta ### meta = Model( name = "meta-ai", - base_provider = "meta", + base_provider = "Meta", best_provider = MetaAI ) llama_3_8b = Model( name = "llama-3-8b", - base_provider = "meta", + base_provider = "Meta", best_provider = IterListProvider([DeepInfra, Replicate]) ) llama_3_70b = Model( name = "llama-3-70b", - base_provider = "meta", + base_provider = "Meta", best_provider = IterListProvider([ReplicateHome, DeepInfra, PerplexityLabs, Replicate]) ) llama_3_1_8b = Model( name = "llama-3.1-8b", - base_provider = "meta", + base_provider = "Meta", best_provider = IterListProvider([Blackbox]) ) llama_3_1_70b = Model( name = "llama-3.1-70b", - base_provider = "meta", + base_provider = "Meta", best_provider = IterListProvider([DDG, HuggingChat, FreeGpt, Blackbox, TeachAnything, HuggingFace]) ) llama_3_1_405b = Model( name = "llama-3.1-405b", - base_provider = "meta", + base_provider = "Meta", best_provider = IterListProvider([HuggingChat, Blackbox, HuggingFace]) ) ### Mistral ### mixtral_8x7b = Model( name = "mixtral-8x7b", - base_provider = "huggingface", - best_provider = IterListProvider([HuggingChat, DDG, ReplicateHome, DeepInfra, HuggingFace,]) + base_provider = "Mistral", + best_provider = IterListProvider([HuggingChat, DDG, ReplicateHome, TwitterBio, DeepInfra, HuggingFace,]) ) mistral_7b = Model( name = "mistral-7b", - base_provider = "huggingface", + base_provider = "Mistral", best_provider = IterListProvider([HuggingChat, HuggingFace, DeepInfra]) ) |