diff options
Diffstat (limited to '')
112 files changed, 6497 insertions, 3136 deletions
diff --git a/g4f/Provider/AI365VIP.py b/g4f/Provider/AI365VIP.py index 2dcc8d1c..511ad568 100644 --- a/g4f/Provider/AI365VIP.py +++ b/g4f/Provider/AI365VIP.py @@ -10,17 +10,15 @@ from .helper import format_prompt class AI365VIP(AsyncGeneratorProvider, ProviderModelMixin): url = "https://chat.ai365vip.com" api_endpoint = "/api/chat" - working = True - supports_gpt_35_turbo = True - supports_gpt_4 = True + working = False default_model = 'gpt-3.5-turbo' models = [ 'gpt-3.5-turbo', + 'gpt-3.5-turbo-16k', 'gpt-4o', - 'claude-3-haiku-20240307', ] model_aliases = { - "claude-3-haiku": "claude-3-haiku-20240307", + "gpt-3.5-turbo": "gpt-3.5-turbo-16k", } @classmethod diff --git a/g4f/Provider/AIChatFree.py b/g4f/Provider/AIChatFree.py new file mode 100644 index 00000000..71c04681 --- /dev/null +++ b/g4f/Provider/AIChatFree.py @@ -0,0 +1,76 @@ +from __future__ import annotations + +import time +from hashlib import sha256 + +from aiohttp import BaseConnector, ClientSession + +from ..errors import RateLimitError +from ..requests import raise_for_status +from ..requests.aiohttp import get_connector +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin + + +class AIChatFree(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://aichatfree.info/" + working = True + supports_stream = True + supports_message_history = True + default_model = 'gemini-pro' + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + connector: BaseConnector = None, + **kwargs, + ) -> AsyncResult: + headers = { + "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:122.0) Gecko/20100101 Firefox/122.0", + "Accept": "*/*", + "Accept-Language": "en-US,en;q=0.5", + "Accept-Encoding": "gzip, deflate, br", + "Content-Type": "text/plain;charset=UTF-8", + "Referer": f"{cls.url}/", + "Origin": cls.url, + "Sec-Fetch-Dest": "empty", + "Sec-Fetch-Mode": "cors", + "Sec-Fetch-Site": "same-origin", + "Connection": "keep-alive", + "TE": "trailers", + } + async with ClientSession( + connector=get_connector(connector, proxy), headers=headers + ) as session: + timestamp = int(time.time() * 1e3) + data = { + "messages": [ + { + "role": "model" if message["role"] == "assistant" else "user", + "parts": [{"text": message["content"]}], + } + for message in messages + ], + "time": timestamp, + "pass": None, + "sign": generate_signature(timestamp, messages[-1]["content"]), + } + async with session.post( + f"{cls.url}/api/generate", json=data, proxy=proxy + ) as response: + if response.status == 500: + if "Quota exceeded" in await response.text(): + raise RateLimitError( + f"Response {response.status}: Rate limit reached" + ) + await raise_for_status(response) + async for chunk in response.content.iter_any(): + yield chunk.decode(errors="ignore") + + +def generate_signature(time: int, text: str, secret: str = ""): + message = f"{time}:{text}:{secret}" + return sha256(message.encode()).hexdigest() diff --git a/g4f/Provider/AIUncensored.py b/g4f/Provider/AIUncensored.py new file mode 100644 index 00000000..d653191c --- /dev/null +++ b/g4f/Provider/AIUncensored.py @@ -0,0 +1,112 @@ +from __future__ import annotations + +import json +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt +from ..image import ImageResponse + +class AIUncensored(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://www.aiuncensored.info" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'ai_uncensored' + chat_models = [default_model] + image_models = ['ImageGenerator'] + models = [*chat_models, *image_models] + + api_endpoints = { + 'ai_uncensored': "https://twitterclone-i0wr.onrender.com/api/chat", + 'ImageGenerator': "https://twitterclone-4e8t.onrender.com/api/image" + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + stream: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + if model in cls.chat_models: + async with ClientSession(headers={"content-type": "application/json"}) as session: + data = { + "messages": [ + {"role": "user", "content": format_prompt(messages)} + ], + "stream": stream + } + async with session.post(cls.api_endpoints[model], json=data, proxy=proxy) as response: + response.raise_for_status() + if stream: + async for chunk in cls._handle_streaming_response(response): + yield chunk + else: + yield await cls._handle_non_streaming_response(response) + elif model in cls.image_models: + 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="129", "Not=A?Brand";v="8"', + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": '"Linux"', + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "cross-site", + "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36" + } + async with ClientSession(headers=headers) as session: + prompt = messages[0]['content'] + data = {"prompt": prompt} + async with session.post(cls.api_endpoints[model], json=data, proxy=proxy) as response: + response.raise_for_status() + result = await response.json() + image_url = result.get('image_url', '') + if image_url: + yield ImageResponse(image_url, alt=prompt) + else: + yield "Failed to generate image. Please try again." + + @classmethod + async def _handle_streaming_response(cls, response): + async for line in response.content: + line = line.decode('utf-8').strip() + if line.startswith("data: "): + if line == "data: [DONE]": + break + try: + json_data = json.loads(line[6:]) + if 'data' in json_data: + yield json_data['data'] + except json.JSONDecodeError: + pass + + @classmethod + async def _handle_non_streaming_response(cls, response): + response_json = await response.json() + return response_json.get('content', "Sorry, I couldn't generate a response.") + + @classmethod + def validate_response(cls, response: str) -> str: + return response diff --git a/g4f/Provider/Ai4Chat.py b/g4f/Provider/Ai4Chat.py new file mode 100644 index 00000000..1096279d --- /dev/null +++ b/g4f/Provider/Ai4Chat.py @@ -0,0 +1,88 @@ +from __future__ import annotations + +import json +import re +import logging +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + + +class Ai4Chat(AsyncGeneratorProvider, ProviderModelMixin): + label = "AI4Chat" + url = "https://www.ai4chat.co" + api_endpoint = "https://www.ai4chat.co/generate-response" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'gpt-4' + models = [default_model] + + model_aliases = {} + + @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 + 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": "https://www.ai4chat.co", + "pragma": "no-cache", + "priority": "u=1, i", + "referer": "https://www.ai4chat.co/gpt/talkdirtytome", + "sec-ch-ua": '"Chromium";v="129", "Not=A?Brand";v="8"', + "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/129.0.0.0 Safari/537.36" + } + + async with ClientSession(headers=headers) as session: + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ] + } + + try: + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + result = await response.text() + + json_result = json.loads(result) + + message = json_result.get("message", "") + + clean_message = re.sub(r'<[^>]+>', '', message) + + yield clean_message + except Exception as e: + logging.exception("Error while calling AI 4Chat API: %s", e) + yield f"Error: {e}" diff --git a/g4f/Provider/AiChatOnline.py b/g4f/Provider/AiChatOnline.py index 152a7d31..26aacef6 100644 --- a/g4f/Provider/AiChatOnline.py +++ b/g4f/Provider/AiChatOnline.py @@ -12,10 +12,7 @@ class AiChatOnline(AsyncGeneratorProvider, ProviderModelMixin): url = "https://aichatonlineorg.erweima.ai" api_endpoint = "/aichatonline/api/chat/gpt" working = True - supports_gpt_35_turbo = True - supports_gpt_4 = True default_model = 'gpt-4o-mini' - supports_message_history = False @classmethod async def grab_token( diff --git a/g4f/Provider/AiChats.py b/g4f/Provider/AiChats.py index 10127d4f..08492e24 100644 --- a/g4f/Provider/AiChats.py +++ b/g4f/Provider/AiChats.py @@ -12,7 +12,6 @@ class AiChats(AsyncGeneratorProvider, ProviderModelMixin): url = "https://ai-chats.org" api_endpoint = "https://ai-chats.org/chat/send2/" working = True - supports_gpt_4 = True supports_message_history = True default_model = 'gpt-4' models = ['gpt-4', 'dalle'] diff --git a/g4f/Provider/AiMathGPT.py b/g4f/Provider/AiMathGPT.py new file mode 100644 index 00000000..90931691 --- /dev/null +++ b/g4f/Provider/AiMathGPT.py @@ -0,0 +1,74 @@ +from __future__ import annotations + +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + +class AiMathGPT(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://aimathgpt.forit.ai" + api_endpoint = "https://aimathgpt.forit.ai/api/ai" + working = True + supports_stream = False + supports_system_message = True + supports_message_history = True + + default_model = 'llama3' + models = ['llama3'] + + model_aliases = {"llama-3.1-70b": "llama3",} + + @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 + 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="129", "Not=A?Brand";v="8"', + '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/129.0.0.0 Safari/537.36' + } + + async with ClientSession(headers=headers) as session: + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ], + "model": model + } + + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + response_data = await response.json() + filtered_response = response_data['result']['response'] + yield filtered_response diff --git a/g4f/Provider/Airforce.py b/g4f/Provider/Airforce.py new file mode 100644 index 00000000..015766f4 --- /dev/null +++ b/g4f/Provider/Airforce.py @@ -0,0 +1,245 @@ +from __future__ import annotations +import random +import json +import re +from aiohttp import ClientSession +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from ..image import ImageResponse + +def split_long_message(message: str, max_length: int = 4000) -> list[str]: + return [message[i:i+max_length] for i in range(0, len(message), max_length)] + +class Airforce(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://api.airforce" + image_api_endpoint = "https://api.airforce/imagine2" + text_api_endpoint = "https://api.airforce/chat/completions" + working = True + + default_model = 'llama-3-70b-chat' + + supports_stream = True + supports_system_message = True + supports_message_history = True + + text_models = [ + 'claude-3-haiku-20240307', + 'claude-3-sonnet-20240229', + 'claude-3-5-sonnet-20240620', + 'claude-3-opus-20240229', + 'chatgpt-4o-latest', + 'gpt-4', + 'gpt-4-turbo', + 'gpt-4o-mini-2024-07-18', + 'gpt-4o-mini', + 'gpt-3.5-turbo', + 'gpt-3.5-turbo-0125', + 'gpt-3.5-turbo-1106', + default_model, + 'llama-3-70b-chat-turbo', + 'llama-3-8b-chat', + 'llama-3-8b-chat-turbo', + 'llama-3-70b-chat-lite', + 'llama-3-8b-chat-lite', + 'llama-2-13b-chat', + 'llama-3.1-405b-turbo', + 'llama-3.1-70b-turbo', + 'llama-3.1-8b-turbo', + 'LlamaGuard-2-8b', + 'Llama-Guard-7b', + 'Llama-3.2-90B-Vision-Instruct-Turbo', + 'Mixtral-8x7B-Instruct-v0.1', + 'Mixtral-8x22B-Instruct-v0.1', + 'Mistral-7B-Instruct-v0.1', + 'Mistral-7B-Instruct-v0.2', + 'Mistral-7B-Instruct-v0.3', + 'Qwen1.5-7B-Chat', + 'Qwen1.5-14B-Chat', + 'Qwen1.5-72B-Chat', + 'Qwen1.5-110B-Chat', + 'Qwen2-72B-Instruct', + 'gemma-2b-it', + 'gemma-2-9b-it', + 'gemma-2-27b-it', + 'gemini-1.5-flash', + 'gemini-1.5-pro', + 'deepseek-llm-67b-chat', + 'Nous-Hermes-2-Mixtral-8x7B-DPO', + 'Nous-Hermes-2-Yi-34B', + 'WizardLM-2-8x22B', + 'SOLAR-10.7B-Instruct-v1.0', + 'MythoMax-L2-13b', + 'cosmosrp', + ] + + image_models = [ + 'flux', + 'flux-realism', + 'flux-anime', + 'flux-3d', + 'flux-disney', + 'flux-pixel', + 'flux-4o', + 'any-dark', + ] + + models = [ + *text_models, + *image_models, + ] + + model_aliases = { + "claude-3-haiku": "claude-3-haiku-20240307", + "claude-3-sonnet": "claude-3-sonnet-20240229", + "gpt-4o": "chatgpt-4o-latest", + "llama-3-70b": "llama-3-70b-chat", + "llama-3-8b": "llama-3-8b-chat", + "mixtral-8x7b": "Mixtral-8x7B-Instruct-v0.1", + "qwen-1.5-7b": "Qwen1.5-7B-Chat", + "gemma-2b": "gemma-2b-it", + "gemini-flash": "gemini-1.5-flash", + "mythomax-l2-13b": "MythoMax-L2-13b", + "solar-10.7b": "SOLAR-10.7B-Instruct-v1.0", + } + + @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.get(model, cls.default_model) + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + seed: int = None, + size: str = "1:1", + stream: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + if model in cls.image_models: + async for result in cls._generate_image(model, messages, proxy, seed, size): + yield result + elif model in cls.text_models: + async for result in cls._generate_text(model, messages, proxy, stream): + yield result + + @classmethod + async def _generate_image( + cls, + model: str, + messages: Messages, + proxy: str = None, + seed: int = None, + size: str = "1:1", + **kwargs + ) -> AsyncResult: + headers = { + "accept": "*/*", + "accept-language": "en-US,en;q=0.9", + "cache-control": "no-cache", + "origin": "https://llmplayground.net", + "user-agent": "Mozilla/5.0" + } + + if seed is None: + seed = random.randint(0, 100000) + + prompt = messages[-1]['content'] + + async with ClientSession(headers=headers) as session: + params = { + "model": model, + "prompt": prompt, + "size": size, + "seed": seed + } + async with session.get(f"{cls.image_api_endpoint}", params=params, proxy=proxy) as response: + response.raise_for_status() + content_type = response.headers.get('Content-Type', '').lower() + + if 'application/json' in content_type: + async for chunk in response.content.iter_chunked(1024): + if chunk: + yield chunk.decode('utf-8') + elif 'image' in content_type: + image_data = b"" + async for chunk in response.content.iter_chunked(1024): + if chunk: + image_data += chunk + image_url = f"{cls.image_api_endpoint}?model={model}&prompt={prompt}&size={size}&seed={seed}" + alt_text = f"Generated image for prompt: {prompt}" + yield ImageResponse(images=image_url, alt=alt_text) + + @classmethod + async def _generate_text( + cls, + model: str, + messages: Messages, + proxy: str = None, + stream: bool = False, + **kwargs + ) -> AsyncResult: + headers = { + "accept": "*/*", + "accept-language": "en-US,en;q=0.9", + "authorization": "Bearer missing api key", + "content-type": "application/json", + "user-agent": "Mozilla/5.0" + } + + async with ClientSession(headers=headers) as session: + formatted_prompt = cls._format_messages(messages) + prompt_parts = split_long_message(formatted_prompt) + full_response = "" + + for part in prompt_parts: + data = { + "messages": [{"role": "user", "content": part}], + "model": model, + "max_tokens": 4096, + "temperature": 1, + "top_p": 1, + "stream": stream + } + async with session.post(cls.text_api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + part_response = "" + if stream: + async for line in response.content: + if line: + line = line.decode('utf-8').strip() + if line.startswith("data: ") and line != "data: [DONE]": + json_data = json.loads(line[6:]) + content = json_data['choices'][0]['delta'].get('content', '') + part_response += content + else: + json_data = await response.json() + content = json_data['choices'][0]['message']['content'] + part_response = content + + part_response = re.sub( + r"One message exceeds the \d+chars per message limit\..+https:\/\/discord\.com\/invite\/\S+", + '', + part_response + ) + + part_response = re.sub( + r"Rate limit \(\d+\/minute\) exceeded\. Join our discord for more: .+https:\/\/discord\.com\/invite\/\S+", + '', + part_response + ) + + full_response += part_response + yield full_response + + @classmethod + def _format_messages(cls, messages: Messages) -> str: + return " ".join([msg['content'] for msg in messages]) diff --git a/g4f/Provider/Allyfy.py b/g4f/Provider/Allyfy.py index 8733b1ec..bf607df4 100644 --- a/g4f/Provider/Allyfy.py +++ b/g4f/Provider/Allyfy.py @@ -9,10 +9,9 @@ from .helper import format_prompt class Allyfy(AsyncGeneratorProvider): - url = "https://chatbot.allyfy.chat" - api_endpoint = "/api/v1/message/stream/super/chat" + url = "https://allyfy.chat" + api_endpoint = "https://chatbot.allyfy.chat/api/v1/message/stream/super/chat" working = True - supports_gpt_35_turbo = True @classmethod async def create_async_generator( @@ -53,7 +52,7 @@ class Allyfy(AsyncGeneratorProvider): "packageName": "com.cch.allyfy.webh", } } - async with session.post(f"{cls.url}{cls.api_endpoint}", json=data, proxy=proxy) as response: + async with session.post(f"{cls.api_endpoint}", json=data, proxy=proxy) as response: response.raise_for_status() full_response = [] async for line in response.content: diff --git a/g4f/Provider/AmigoChat.py b/g4f/Provider/AmigoChat.py new file mode 100644 index 00000000..f5027111 --- /dev/null +++ b/g4f/Provider/AmigoChat.py @@ -0,0 +1,189 @@ +from __future__ import annotations + +import json +import uuid +from aiohttp import ClientSession, ClientTimeout, ClientResponseError + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt +from ..image import ImageResponse + +class AmigoChat(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://amigochat.io/chat/" + chat_api_endpoint = "https://api.amigochat.io/v1/chat/completions" + image_api_endpoint = "https://api.amigochat.io/v1/images/generations" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'gpt-4o-mini' + + chat_models = [ + 'gpt-4o', + default_model, + 'o1-preview', + 'o1-mini', + 'meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo', + 'meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo', + 'claude-3-sonnet-20240229', + 'gemini-1.5-pro', + ] + + image_models = [ + 'flux-pro/v1.1', + 'flux-realism', + 'flux-pro', + 'dalle-e-3', + ] + + models = [*chat_models, *image_models] + + model_aliases = { + "o1": "o1-preview", + "llama-3.1-405b": "meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo", + "llama-3.2-90b": "meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo", + "claude-3.5-sonnet": "claude-3-sonnet-20240229", + "gemini-pro": "gemini-1.5-pro", + + "flux-pro": "flux-pro/v1.1", + "dalle-3": "dalle-e-3", + } + + persona_ids = { + 'gpt-4o': "gpt", + 'gpt-4o-mini': "amigo", + 'o1-preview': "openai-o-one", + 'o1-mini': "openai-o-one-mini", + 'meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo': "llama-three-point-one", + 'meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo': "llama-3-2", + 'claude-3-sonnet-20240229': "claude", + 'gemini-1.5-pro': "gemini-1-5-pro", + 'flux-pro/v1.1': "flux-1-1-pro", + 'flux-realism': "flux-realism", + 'flux-pro': "flux-pro", + 'dalle-e-3': "dalle-three", + } + + @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 get_personaId(cls, model: str) -> str: + return cls.persona_ids[model] + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + stream: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + device_uuid = str(uuid.uuid4()) + max_retries = 3 + retry_count = 0 + + while retry_count < max_retries: + try: + headers = { + "accept": "*/*", + "accept-language": "en-US,en;q=0.9", + "authorization": "Bearer", + "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="129", "Not=A?Brand";v="8"', + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": '"Linux"', + "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36", + "x-device-language": "en-US", + "x-device-platform": "web", + "x-device-uuid": device_uuid, + "x-device-version": "1.0.32" + } + + async with ClientSession(headers=headers) as session: + if model in cls.chat_models: + # Chat completion + data = { + "messages": [{"role": m["role"], "content": m["content"]} for m in messages], + "model": model, + "personaId": cls.get_personaId(model), + "frequency_penalty": 0, + "max_tokens": 4000, + "presence_penalty": 0, + "stream": stream, + "temperature": 0.5, + "top_p": 0.95 + } + + timeout = ClientTimeout(total=300) # 5 minutes timeout + async with session.post(cls.chat_api_endpoint, json=data, proxy=proxy, timeout=timeout) as response: + if response.status not in (200, 201): + error_text = await response.text() + raise Exception(f"Error {response.status}: {error_text}") + + async for line in response.content: + line = line.decode('utf-8').strip() + if line.startswith('data: '): + if line == 'data: [DONE]': + break + try: + chunk = json.loads(line[6:]) # Remove 'data: ' prefix + if 'choices' in chunk and len(chunk['choices']) > 0: + choice = chunk['choices'][0] + if 'delta' in choice: + content = choice['delta'].get('content') + elif 'text' in choice: + content = choice['text'] + else: + content = None + if content: + yield content + except json.JSONDecodeError: + pass + else: + # Image generation + prompt = messages[-1]['content'] + data = { + "prompt": prompt, + "model": model, + "personaId": cls.get_personaId(model) + } + async with session.post(cls.image_api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + + response_data = await response.json() + + if "data" in response_data: + image_urls = [] + for item in response_data["data"]: + if "url" in item: + image_url = item["url"] + image_urls.append(image_url) + if image_urls: + yield ImageResponse(image_urls, prompt) + else: + yield None + + break + + except (ClientResponseError, Exception) as e: + retry_count += 1 + if retry_count >= max_retries: + raise e + device_uuid = str(uuid.uuid4()) diff --git a/g4f/Provider/Aura.py b/g4f/Provider/Aura.py index 4a8d0a55..e2c56754 100644 --- a/g4f/Provider/Aura.py +++ b/g4f/Provider/Aura.py @@ -9,7 +9,7 @@ from ..webdriver import WebDriver class Aura(AsyncGeneratorProvider): url = "https://openchat.team" - working = True + working = False @classmethod async def create_async_generator( @@ -46,4 +46,4 @@ class Aura(AsyncGeneratorProvider): async with session.post(f"{cls.url}/api/chat", json=data, proxy=proxy) as response: response.raise_for_status() async for chunk in response.content.iter_any(): - yield chunk.decode(error="ignore")
\ No newline at end of file + yield chunk.decode(error="ignore") diff --git a/g4f/Provider/Bing.py b/g4f/Provider/Bing.py index 4056f9ff..f04b1a54 100644 --- a/g4f/Provider/Bing.py +++ b/g4f/Provider/Bing.py @@ -37,7 +37,6 @@ class Bing(AsyncGeneratorProvider, ProviderModelMixin): url = "https://bing.com/chat" working = True supports_message_history = True - supports_gpt_4 = True default_model = "Balanced" default_vision_model = "gpt-4-vision" models = [getattr(Tones, key) for key in Tones.__dict__ if not key.startswith("__")] diff --git a/g4f/Provider/Binjie.py b/g4f/Provider/Binjie.py deleted file mode 100644 index 90f9ec3c..00000000 --- a/g4f/Provider/Binjie.py +++ /dev/null @@ -1,65 +0,0 @@ -from __future__ import annotations - -import random -from ..requests import StreamSession - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, format_prompt - - -class Binjie(AsyncGeneratorProvider): - url = "https://chat18.aichatos8.com" - working = True - supports_gpt_4 = True - supports_stream = True - supports_system_message = True - supports_message_history = True - - @staticmethod - async def create_async_generator( - model: str, - messages: Messages, - proxy: str = None, - timeout: int = 120, - **kwargs, - ) -> AsyncResult: - async with StreamSession( - headers=_create_header(), proxies={"https": proxy}, timeout=timeout - ) as session: - payload = _create_payload(messages, **kwargs) - async with session.post("https://api.binjie.fun/api/generateStream", json=payload) as response: - response.raise_for_status() - async for chunk in response.iter_content(): - if chunk: - chunk = chunk.decode() - if "sorry, 您的ip已由于触发防滥用检测而被封禁" in chunk: - raise RuntimeError("IP address is blocked by abuse detection.") - yield chunk - - -def _create_header(): - return { - "accept" : "application/json, text/plain, */*", - "content-type" : "application/json", - "origin" : "https://chat18.aichatos8.com", - "referer" : "https://chat18.aichatos8.com/" - } - - -def _create_payload( - messages: Messages, - system_message: str = "", - user_id: int = None, - **kwargs -): - if not user_id: - user_id = random.randint(1690000544336, 2093025544336) - return { - "prompt": format_prompt(messages), - "network": True, - "system": system_message, - "withoutContext": False, - "stream": True, - "userId": f"#/chat/{user_id}" - } - diff --git a/g4f/Provider/Bixin123.py b/g4f/Provider/Bixin123.py deleted file mode 100644 index 694a2eff..00000000 --- a/g4f/Provider/Bixin123.py +++ /dev/null @@ -1,89 +0,0 @@ -from __future__ import annotations - -from aiohttp import ClientSession -import json -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from ..typing import AsyncResult, Messages -from .helper import format_prompt - -class Bixin123(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://chat.bixin123.com" - api_endpoint = "https://chat.bixin123.com/api/chatgpt/chat-process" - working = True - supports_gpt_35_turbo = True - supports_gpt_4 = True - - default_model = 'gpt-3.5-turbo-0125' - models = ['gpt-3.5-turbo-0125', 'gpt-3.5-turbo-16k-0613', 'gpt-4-turbo', 'qwen-turbo'] - - model_aliases = { - "gpt-3.5-turbo": "gpt-3.5-turbo-0125", - "gpt-3.5-turbo": "gpt-3.5-turbo-16k-0613", - } - - @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 - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - model = cls.get_model(model) - - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "en-US,en;q=0.9", - "cache-control": "no-cache", - "content-type": "application/json", - "fingerprint": "988148794", - "origin": cls.url, - "pragma": "no-cache", - "priority": "u=1, i", - "referer": f"{cls.url}/chat", - "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", - "x-website-domain": "chat.bixin123.com", - } - - async with ClientSession(headers=headers) as session: - prompt = format_prompt(messages) - data = { - "prompt": prompt, - "options": { - "usingNetwork": False, - "file": "" - } - } - async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: - response.raise_for_status() - response_text = await response.text() - - lines = response_text.strip().split("\n") - last_json = None - for line in reversed(lines): - try: - last_json = json.loads(line) - break - except json.JSONDecodeError: - pass - - if last_json: - text = last_json.get("text", "") - yield text - else: - yield "" diff --git a/g4f/Provider/Blackbox.py b/g4f/Provider/Blackbox.py index 9fab4a09..4052893a 100644 --- a/g4f/Provider/Blackbox.py +++ b/g4f/Provider/Blackbox.py @@ -1,43 +1,122 @@ from __future__ import annotations +import asyncio +import aiohttp +import random +import string +import json import uuid -import secrets import re -import base64 -from aiohttp import ClientSession -from typing import AsyncGenerator, Optional +from typing import Optional, AsyncGenerator, Union + +from aiohttp import ClientSession, ClientResponseError from ..typing import AsyncResult, Messages, ImageType -from ..image import to_data_uri, ImageResponse from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from ..image import ImageResponse, to_data_uri + class Blackbox(AsyncGeneratorProvider, ProviderModelMixin): + label = "Blackbox AI" url = "https://www.blackbox.ai" + api_endpoint = "https://www.blackbox.ai/api/chat" working = True - default_model = 'blackbox' + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'blackboxai' + image_models = ['ImageGeneration'] models = [ default_model, - "gemini-1.5-flash", + 'blackboxai-pro', + *image_models, "llama-3.1-8b", 'llama-3.1-70b', 'llama-3.1-405b', - 'ImageGeneration', + 'gpt-4o', + 'gemini-pro', + 'gemini-1.5-flash', + 'claude-sonnet-3.5', + 'PythonAgent', + 'JavaAgent', + 'JavaScriptAgent', + 'HTMLAgent', + 'GoogleCloudAgent', + 'AndroidDeveloper', + 'SwiftDeveloper', + 'Next.jsAgent', + 'MongoDBAgent', + 'PyTorchAgent', + 'ReactAgent', + 'XcodeAgent', + 'AngularJSAgent', ] - - model_aliases = { - "gemini-flash": "gemini-1.5-flash", - } - - agent_mode_map = { - 'ImageGeneration': {"mode": True, "id": "ImageGenerationLV45LJp", "name": "Image Generation"}, + + agentMode = { + 'ImageGeneration': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"}, } - model_id_map = { - "blackbox": {}, + trendingAgentMode = { + "blackboxai": {}, "gemini-1.5-flash": {'mode': True, 'id': 'Gemini'}, "llama-3.1-8b": {'mode': True, 'id': "llama-3.1-8b"}, 'llama-3.1-70b': {'mode': True, 'id': "llama-3.1-70b"}, - 'llama-3.1-405b': {'mode': True, 'id': "llama-3.1-405b"} + 'llama-3.1-405b': {'mode': True, 'id': "llama-3.1-405b"}, + 'blackboxai-pro': {'mode': True, 'id': "BLACKBOXAI-PRO"}, + 'PythonAgent': {'mode': True, 'id': "Python Agent"}, + 'JavaAgent': {'mode': True, 'id': "Java Agent"}, + 'JavaScriptAgent': {'mode': True, 'id': "JavaScript Agent"}, + 'HTMLAgent': {'mode': True, 'id': "HTML Agent"}, + 'GoogleCloudAgent': {'mode': True, 'id': "Google Cloud Agent"}, + 'AndroidDeveloper': {'mode': True, 'id': "Android Developer"}, + 'SwiftDeveloper': {'mode': True, 'id': "Swift Developer"}, + 'Next.jsAgent': {'mode': True, 'id': "Next.js Agent"}, + 'MongoDBAgent': {'mode': True, 'id': "MongoDB Agent"}, + 'PyTorchAgent': {'mode': True, 'id': "PyTorch Agent"}, + 'ReactAgent': {'mode': True, 'id': "React Agent"}, + 'XcodeAgent': {'mode': True, 'id': "Xcode Agent"}, + 'AngularJSAgent': {'mode': True, 'id': "AngularJS Agent"}, + } + + userSelectedModel = { + "gpt-4o": "gpt-4o", + "gemini-pro": "gemini-pro", + 'claude-sonnet-3.5': "claude-sonnet-3.5", + } + + model_prefixes = { + 'gpt-4o': '@GPT-4o', + 'gemini-pro': '@Gemini-PRO', + 'claude-sonnet-3.5': '@Claude-Sonnet-3.5', + 'PythonAgent': '@Python Agent', + 'JavaAgent': '@Java Agent', + 'JavaScriptAgent': '@JavaScript Agent', + 'HTMLAgent': '@HTML Agent', + 'GoogleCloudAgent': '@Google Cloud Agent', + 'AndroidDeveloper': '@Android Developer', + 'SwiftDeveloper': '@Swift Developer', + 'Next.jsAgent': '@Next.js Agent', + 'MongoDBAgent': '@MongoDB Agent', + 'PyTorchAgent': '@PyTorch Agent', + 'ReactAgent': '@React Agent', + 'XcodeAgent': '@Xcode Agent', + 'AngularJSAgent': '@AngularJS Agent', + 'blackboxai-pro': '@BLACKBOXAI-PRO', + 'ImageGeneration': '@Image Generation', + } + + model_referers = { + "blackboxai": "/?model=blackboxai", + "gpt-4o": "/?model=gpt-4o", + "gemini-pro": "/?model=gemini-pro", + "claude-sonnet-3.5": "/?model=claude-sonnet-3.5" + } + + model_aliases = { + "gemini-flash": "gemini-1.5-flash", + "claude-3.5-sonnet": "claude-sonnet-3.5", + "flux": "ImageGeneration", } @classmethod @@ -49,14 +128,41 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin): else: return cls.default_model - @classmethod - async def download_image_to_base64_url(cls, url: str) -> str: - async with ClientSession() as session: - async with session.get(url) as response: - image_data = await response.read() - base64_data = base64.b64encode(image_data).decode('utf-8') - mime_type = response.headers.get('Content-Type', 'image/jpeg') - return f"data:{mime_type};base64,{base64_data}" + @staticmethod + def generate_random_string(length: int = 7) -> str: + characters = string.ascii_letters + string.digits + return ''.join(random.choices(characters, k=length)) + + @staticmethod + def generate_next_action() -> str: + return uuid.uuid4().hex + + @staticmethod + def generate_next_router_state_tree() -> str: + router_state = [ + "", + { + "children": [ + "(chat)", + { + "children": [ + "__PAGE__", + {} + ] + } + ] + }, + None, + None, + True + ] + return json.dumps(router_state) + + @staticmethod + def clean_response(text: str) -> str: + pattern = r'^\$\@\$v=undefined-rv1\$\@\$' + cleaned_text = re.sub(pattern, '', text) + return cleaned_text @classmethod async def create_async_generator( @@ -64,93 +170,203 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin): model: str, messages: Messages, proxy: Optional[str] = None, - image: Optional[ImageType] = None, - image_name: Optional[str] = None, + image: ImageType = None, + image_name: str = None, + web_search: bool = False, **kwargs - ) -> AsyncGenerator[AsyncResult, None]: + ) -> AsyncGenerator[Union[str, ImageResponse], None]: + """ + Creates an asynchronous generator for streaming responses from Blackbox AI. + + Parameters: + model (str): Model to use for generating responses. + messages (Messages): Message history. + proxy (Optional[str]): Proxy URL, if needed. + image (ImageType): Image data to be processed, if any. + image_name (str): Name of the image file, if an image is provided. + web_search (bool): Enables or disables web search mode. + **kwargs: Additional keyword arguments. + + Yields: + Union[str, ImageResponse]: Segments of the generated response or ImageResponse objects. + """ + if image is not None: - messages[-1]["data"] = { - "fileText": image_name, - "imageBase64": to_data_uri(image), - "title": str(uuid.uuid4()) + messages[-1]['data'] = { + 'fileText': '', + 'imageBase64': to_data_uri(image), + 'title': image_name } + messages[-1]['content'] = 'FILE:BB\n$#$\n\n$#$\n' + messages[-1]['content'] + + model = cls.get_model(model) + + chat_id = cls.generate_random_string() + next_action = cls.generate_next_action() + next_router_state_tree = cls.generate_next_router_state_tree() - headers = { - "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36", - "Accept": "*/*", - "Accept-Language": "en-US,en;q=0.5", - "Accept-Encoding": "gzip, deflate, br", - "Referer": cls.url, - "Content-Type": "application/json", - "Origin": cls.url, - "DNT": "1", - "Sec-GPC": "1", - "Alt-Used": "www.blackbox.ai", - "Connection": "keep-alive", + agent_mode = cls.agentMode.get(model, {}) + trending_agent_mode = cls.trendingAgentMode.get(model, {}) + + prefix = cls.model_prefixes.get(model, "") + + formatted_prompt = "" + for message in messages: + role = message.get('role', '').capitalize() + content = message.get('content', '') + if role and content: + formatted_prompt += f"{role}: {content}\n" + + if prefix: + formatted_prompt = f"{prefix} {formatted_prompt}".strip() + + referer_path = cls.model_referers.get(model, f"/?model={model}") + referer_url = f"{cls.url}{referer_path}" + + common_headers = { + 'accept': '*/*', + 'accept-language': 'en-US,en;q=0.9', + 'cache-control': 'no-cache', + 'origin': cls.url, + 'pragma': 'no-cache', + 'priority': 'u=1, i', + 'sec-ch-ua': '"Chromium";v="129", "Not=A?Brand";v="8"', + '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/129.0.0.0 Safari/537.36' } - async with ClientSession(headers=headers) as session: - random_id = secrets.token_hex(16) - random_user_id = str(uuid.uuid4()) - - model = cls.get_model(model) # Resolve the model alias - - data = { - "messages": messages, - "id": random_id, - "userId": random_user_id, - "codeModelMode": True, - "agentMode": cls.agent_mode_map.get(model, {}), - "trendingAgentMode": {}, - "isMicMode": False, - "isChromeExt": False, - "playgroundMode": False, - "webSearchMode": False, - "userSystemPrompt": "", - "githubToken": None, - "trendingAgentModel": cls.model_id_map.get(model, {}), - "maxTokens": None - } + headers_api_chat = { + 'Content-Type': 'application/json', + 'Referer': referer_url + } + headers_api_chat_combined = {**common_headers, **headers_api_chat} + + payload_api_chat = { + "messages": [ + { + "id": chat_id, + "content": formatted_prompt, + "role": "user", + "data": messages[-1].get('data') + } + ], + "id": chat_id, + "previewToken": None, + "userId": None, + "codeModelMode": True, + "agentMode": agent_mode, + "trendingAgentMode": trending_agent_mode, + "isMicMode": False, + "userSystemPrompt": None, + "maxTokens": 1024, + "playgroundTopP": 0.9, + "playgroundTemperature": 0.5, + "isChromeExt": False, + "githubToken": None, + "clickedAnswer2": False, + "clickedAnswer3": False, + "clickedForceWebSearch": False, + "visitFromDelta": False, + "mobileClient": False, + "webSearchMode": web_search, + "userSelectedModel": cls.userSelectedModel.get(model, model) + } + + headers_chat = { + 'Accept': 'text/x-component', + 'Content-Type': 'text/plain;charset=UTF-8', + 'Referer': f'{cls.url}/chat/{chat_id}?model={model}', + 'next-action': next_action, + 'next-router-state-tree': next_router_state_tree, + 'next-url': '/' + } + headers_chat_combined = {**common_headers, **headers_chat} + + data_chat = '[]' + + async with ClientSession(headers=common_headers) as session: + try: + async with session.post( + cls.api_endpoint, + headers=headers_api_chat_combined, + json=payload_api_chat, + proxy=proxy + ) as response_api_chat: + response_api_chat.raise_for_status() + text = await response_api_chat.text() + cleaned_response = cls.clean_response(text) + + if model in cls.image_models: + match = re.search(r'!\[.*?\]\((https?://[^\)]+)\)', cleaned_response) + if match: + image_url = match.group(1) + image_response = ImageResponse(images=image_url, alt="Generated Image") + yield image_response + else: + yield cleaned_response + else: + if web_search: + match = re.search(r'\$~~~\$(.*?)\$~~~\$', cleaned_response, re.DOTALL) + if match: + source_part = match.group(1).strip() + answer_part = cleaned_response[match.end():].strip() + try: + sources = json.loads(source_part) + source_formatted = "**Source:**\n" + for item in sources: + title = item.get('title', 'No Title') + link = item.get('link', '#') + position = item.get('position', '') + source_formatted += f"{position}. [{title}]({link})\n" + final_response = f"{answer_part}\n\n{source_formatted}" + except json.JSONDecodeError: + final_response = f"{answer_part}\n\nSource information is unavailable." + else: + final_response = cleaned_response + else: + if '$~~~$' in cleaned_response: + final_response = cleaned_response.split('$~~~$')[0].strip() + else: + final_response = cleaned_response + + yield final_response + except ClientResponseError as e: + error_text = f"Error {e.status}: {e.message}" + try: + error_response = await e.response.text() + cleaned_error = cls.clean_response(error_response) + error_text += f" - {cleaned_error}" + except Exception: + pass + yield error_text + except Exception as e: + yield f"Unexpected error during /api/chat request: {str(e)}" + + chat_url = f'{cls.url}/chat/{chat_id}?model={model}' - async with session.post( - f"{cls.url}/api/chat", json=data, proxy=proxy - ) as response: - response.raise_for_status() - full_response = "" - buffer = "" - image_base64_url = None - async for chunk in response.content.iter_any(): - if chunk: - decoded_chunk = chunk.decode() - cleaned_chunk = re.sub(r'\$@\$.+?\$@\$|\$@\$', '', decoded_chunk) - - buffer += cleaned_chunk - - # Check if there's a complete image line in the buffer - image_match = re.search(r'!\[Generated Image\]\((https?://[^\s\)]+)\)', buffer) - if image_match: - image_url = image_match.group(1) - # Download the image and convert to base64 URL - image_base64_url = await cls.download_image_to_base64_url(image_url) - - # Remove the image line from the buffer - buffer = re.sub(r'!\[Generated Image\]\(https?://[^\s\)]+\)', '', buffer) - - # Send text line by line - lines = buffer.split('\n') - for line in lines[:-1]: - if line.strip(): - full_response += line + '\n' - yield line + '\n' - buffer = lines[-1] # Keep the last incomplete line in the buffer - - # Send the remaining buffer if it's not empty - if buffer.strip(): - full_response += buffer - yield buffer - - # If an image was found, send it as ImageResponse - if image_base64_url: - alt_text = "Generated Image" - image_response = ImageResponse(image_base64_url, alt=alt_text) - yield image_response + try: + async with session.post( + chat_url, + headers=headers_chat_combined, + data=data_chat, + proxy=proxy + ) as response_chat: + response_chat.raise_for_status() + pass + except ClientResponseError as e: + error_text = f"Error {e.status}: {e.message}" + try: + error_response = await e.response.text() + cleaned_error = cls.clean_response(error_response) + error_text += f" - {cleaned_error}" + except Exception: + pass + yield error_text + except Exception as e: + yield f"Unexpected error during /chat/{chat_id} request: {str(e)}" diff --git a/g4f/Provider/ChatGpt.py b/g4f/Provider/ChatGpt.py new file mode 100644 index 00000000..b5a78b9a --- /dev/null +++ b/g4f/Provider/ChatGpt.py @@ -0,0 +1,225 @@ +from __future__ import annotations + +from ..typing import Messages, CreateResult +from ..providers.base_provider import AbstractProvider, ProviderModelMixin + +import time, uuid, random, json +from requests import Session + +from .openai.new import ( + get_config, + get_answer_token, + process_turnstile, + get_requirements_token +) + +def format_conversation(messages: list): + conversation = [] + + for message in messages: + conversation.append({ + 'id': str(uuid.uuid4()), + 'author': { + 'role': message['role'], + }, + 'content': { + 'content_type': 'text', + 'parts': [ + message['content'], + ], + }, + 'metadata': { + 'serialization_metadata': { + 'custom_symbol_offsets': [], + }, + }, + 'create_time': round(time.time(), 3), + }) + + return conversation + +def init_session(user_agent): + session = Session() + + cookies = { + '_dd_s': '', + } + + headers = { + 'accept': '*/*', + 'accept-language': 'en-US,en;q=0.8', + 'cache-control': 'no-cache', + 'pragma': 'no-cache', + 'priority': 'u=0, i', + 'sec-ch-ua': '"Not)A;Brand";v="99", "Google Chrome";v="127", "Chromium";v="127"', + 'sec-ch-ua-arch': '"arm"', + 'sec-ch-ua-bitness': '"64"', + 'sec-ch-ua-mobile': '?0', + 'sec-ch-ua-model': '""', + 'sec-ch-ua-platform': '"macOS"', + 'sec-ch-ua-platform-version': '"14.4.0"', + 'sec-fetch-dest': 'document', + 'sec-fetch-mode': 'navigate', + 'sec-fetch-site': 'none', + 'sec-fetch-user': '?1', + 'upgrade-insecure-requests': '1', + 'user-agent': user_agent, + } + + session.get('https://chatgpt.com/', cookies=cookies, headers=headers) + + return session + +class ChatGpt(AbstractProvider, ProviderModelMixin): + label = "ChatGpt" + working = True + supports_message_history = True + supports_system_message = True + supports_stream = True + models = [ + 'gpt-4o', + 'gpt-4o-mini', + 'gpt-4', + 'gpt-4-turbo', + 'chatgpt-4o-latest', + ] + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + stream: bool, + **kwargs + ) -> CreateResult: + + if model in [ + 'gpt-4o', + 'gpt-4o-mini', + 'gpt-4', + 'gpt-4-turbo', + 'chatgpt-4o-latest' + ]: + model = 'auto' + + elif model in [ + 'gpt-3.5-turbo' + ]: + model = 'text-davinci-002-render-sha' + + else: + raise ValueError(f"Invalid model: {model}") + + user_agent = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36' + session: Session = init_session(user_agent) + + config = get_config(user_agent) + pow_req = get_requirements_token(config) + headers = { + 'accept': '*/*', + 'accept-language': 'en-US,en;q=0.8', + 'content-type': 'application/json', + 'oai-device-id': f'{uuid.uuid4()}', + 'oai-language': 'en-US', + 'origin': 'https://chatgpt.com', + 'priority': 'u=1, i', + 'referer': 'https://chatgpt.com/', + 'sec-ch-ua-mobile': '?0', + 'sec-ch-ua-platform': '"Linux"', + 'sec-fetch-dest': 'empty', + 'sec-fetch-mode': 'cors', + 'sec-fetch-site': 'same-origin', + 'sec-gpc': '1', + 'user-agent': f'{user_agent}' + } + + response = session.post('https://chatgpt.com/backend-anon/sentinel/chat-requirements', + headers=headers, json={'p': pow_req}) + + if response.status_code != 200: + print(f"Request failed with status: {response.status_code}") + print(f"Response content: {response.content}") + return + + response_data = response.json() + if "detail" in response_data and "Unusual activity" in response_data["detail"]: + print(f"Blocked due to unusual activity: {response_data['detail']}") + return + + turnstile = response_data.get('turnstile', {}) + turnstile_required = turnstile.get('required') + pow_conf = response_data.get('proofofwork', {}) + + if turnstile_required: + turnstile_dx = turnstile.get('dx') + turnstile_token = process_turnstile(turnstile_dx, pow_req) + + headers = headers | { + 'openai-sentinel-turnstile-token' : turnstile_token, + 'openai-sentinel-chat-requirements-token': response_data.get('token'), + 'openai-sentinel-proof-token' : get_answer_token( + pow_conf.get('seed'), pow_conf.get('difficulty'), config + ) + } + + json_data = { + 'action': 'next', + 'messages': format_conversation(messages), + 'parent_message_id': str(uuid.uuid4()), + 'model': 'auto', + 'timezone_offset_min': -120, + 'suggestions': [ + 'Can you help me create a personalized morning routine that would help increase my productivity throughout the day? Start by asking me about my current habits and what activities energize me in the morning.', + 'Could you help me plan a relaxing day that focuses on activities for rejuvenation? To start, can you ask me what my favorite forms of relaxation are?', + 'I have a photoshoot tomorrow. Can you recommend me some colors and outfit options that will look good on camera?', + 'Make up a 5-sentence story about "Sharky", a tooth-brushing shark superhero. Make each sentence a bullet point.', + ], + 'history_and_training_disabled': False, + 'conversation_mode': { + 'kind': 'primary_assistant', + }, + 'force_paragen': False, + 'force_paragen_model_slug': '', + 'force_nulligen': False, + 'force_rate_limit': False, + 'reset_rate_limits': False, + 'websocket_request_id': str(uuid.uuid4()), + 'system_hints': [], + 'force_use_sse': True, + 'conversation_origin': None, + 'client_contextual_info': { + 'is_dark_mode': True, + 'time_since_loaded': random.randint(22,33), + 'page_height': random.randint(600, 900), + 'page_width': random.randint(500, 800), + 'pixel_ratio': 2, + 'screen_height': random.randint(800, 1200), + 'screen_width': random.randint(1200, 2000), + }, + } + + time.sleep(2) + + response = session.post('https://chatgpt.com/backend-anon/conversation', + headers=headers, json=json_data, stream=True) + + replace = '' + for line in response.iter_lines(): + if line: + decoded_line = line.decode() + print(f"Received line: {decoded_line}") + if decoded_line.startswith('data:'): + json_string = decoded_line[6:] + if json_string.strip(): + try: + data = json.loads(json_string) + except json.JSONDecodeError as e: + print(f"Error decoding JSON: {e}, content: {json_string}") + continue + + if data.get('message').get('author').get('role') == 'assistant': + tokens = (data.get('message').get('content').get('parts')[0]) + + yield tokens.replace(replace, '') + + replace = tokens diff --git a/g4f/Provider/ChatGptEs.py b/g4f/Provider/ChatGptEs.py new file mode 100644 index 00000000..a060ecb1 --- /dev/null +++ b/g4f/Provider/ChatGptEs.py @@ -0,0 +1,84 @@ +from __future__ import annotations + +from aiohttp import ClientSession +import os +import json +import re + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + +class ChatGptEs(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://chatgpt.es" + api_endpoint = "https://chatgpt.es/wp-admin/admin-ajax.php" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'gpt-4o' + models = ['gpt-4o', 'gpt-4o-mini', 'chatgpt-4o-latest'] + + model_aliases = { + "gpt-4o": "chatgpt-4o-latest", + } + + @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 + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "authority": "chatgpt.es", + "accept": "application/json", + "origin": cls.url, + "referer": f"{cls.url}/chat", + "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36", + } + + async with ClientSession(headers=headers) as session: + initial_response = await session.get(cls.url) + nonce_ = re.findall(r'data-nonce="(.+?)"', await initial_response.text())[0] + post_id = re.findall(r'data-post-id="(.+?)"', await initial_response.text())[0] + + conversation_history = [ + "Human: strictly respond in the same language as my prompt, preferably English" + ] + + for message in messages[:-1]: + if message['role'] == "user": + conversation_history.append(f"Human: {message['content']}") + else: + conversation_history.append(f"AI: {message['content']}") + + payload = { + '_wpnonce': nonce_, + 'post_id': post_id, + 'url': cls.url, + 'action': 'wpaicg_chat_shortcode_message', + 'message': messages[-1]['content'], + 'bot_id': '0', + 'chatbot_identity': 'shortcode', + 'wpaicg_chat_client_id': os.urandom(5).hex(), + 'wpaicg_chat_history': json.dumps(conversation_history) + } + + async with session.post(cls.api_endpoint, headers=headers, data=payload) as response: + response.raise_for_status() + result = await response.json() + yield result['data'] diff --git a/g4f/Provider/ChatHub.py b/g4f/Provider/ChatHub.py new file mode 100644 index 00000000..3b762687 --- /dev/null +++ b/g4f/Provider/ChatHub.py @@ -0,0 +1,84 @@ +from __future__ import annotations + +import json +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + +class ChatHub(AsyncGeneratorProvider, ProviderModelMixin): + label = "ChatHub" + url = "https://app.chathub.gg" + api_endpoint = "https://app.chathub.gg/api/v3/chat/completions" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'meta/llama3.1-8b' + models = [ + 'meta/llama3.1-8b', + 'mistral/mixtral-8x7b', + 'google/gemma-2', + 'perplexity/sonar-online', + ] + + model_aliases = { + "llama-3.1-8b": "meta/llama3.1-8b", + "mixtral-8x7b": "mistral/mixtral-8x7b", + "gemma-2": "google/gemma-2", + "sonar-online": "perplexity/sonar-online", + } + + @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 + 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', + 'content-type': 'application/json', + 'origin': cls.url, + 'referer': f"{cls.url}/chat/cloud-llama3.1-8b", + 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36', + 'x-app-id': 'web' + } + + async with ClientSession(headers=headers) as session: + prompt = format_prompt(messages) + data = { + "model": model, + "messages": [{"role": "user", "content": prompt}], + "tools": [] + } + + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + async for line in response.content: + if line: + decoded_line = line.decode('utf-8') + if decoded_line.startswith('data:'): + try: + data = json.loads(decoded_line[5:]) + if data['type'] == 'text-delta': + yield data['textDelta'] + elif data['type'] == 'done': + break + except json.JSONDecodeError: + continue diff --git a/g4f/Provider/Chatgpt4Online.py b/g4f/Provider/Chatgpt4Online.py index 8c058fdc..627facf6 100644 --- a/g4f/Provider/Chatgpt4Online.py +++ b/g4f/Provider/Chatgpt4Online.py @@ -12,13 +12,15 @@ class Chatgpt4Online(AsyncGeneratorProvider): url = "https://chatgpt4online.org" api_endpoint = "/wp-json/mwai-ui/v1/chats/submit" working = True - supports_gpt_4 = True + + default_model = 'gpt-4' + models = [default_model] async def get_nonce(headers: dict) -> str: async with ClientSession(headers=headers) as session: async with session.post(f"https://chatgpt4online.org/wp-json/mwai/v1/start_session") as response: return (await response.json())["restNonce"] - + @classmethod async def create_async_generator( cls, diff --git a/g4f/Provider/Chatgpt4o.py b/g4f/Provider/Chatgpt4o.py index f3dc8a15..7730fc84 100644 --- a/g4f/Provider/Chatgpt4o.py +++ b/g4f/Provider/Chatgpt4o.py @@ -9,11 +9,16 @@ from .helper import format_prompt class Chatgpt4o(AsyncProvider, ProviderModelMixin): url = "https://chatgpt4o.one" - supports_gpt_4 = True working = True _post_id = None _nonce = None - default_model = 'gpt-4o' + default_model = 'gpt-4o-mini-2024-07-18' + models = [ + 'gpt-4o-mini-2024-07-18', + ] + model_aliases = { + "gpt-4o-mini": "gpt-4o-mini-2024-07-18", + } @classmethod diff --git a/g4f/Provider/ChatgptFree.py b/g4f/Provider/ChatgptFree.py index 95efa865..d2837594 100644 --- a/g4f/Provider/ChatgptFree.py +++ b/g4f/Provider/ChatgptFree.py @@ -10,7 +10,6 @@ from .helper import format_prompt class ChatgptFree(AsyncGeneratorProvider, ProviderModelMixin): url = "https://chatgptfree.ai" - supports_gpt_4 = True working = True _post_id = None _nonce = None diff --git a/g4f/Provider/ChatifyAI.py b/g4f/Provider/ChatifyAI.py new file mode 100644 index 00000000..7e43b065 --- /dev/null +++ b/g4f/Provider/ChatifyAI.py @@ -0,0 +1,79 @@ +from __future__ import annotations + +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + + +class ChatifyAI(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://chatify-ai.vercel.app" + api_endpoint = "https://chatify-ai.vercel.app/api/chat" + working = True + supports_stream = False + supports_system_message = True + supports_message_history = True + + default_model = 'llama-3.1' + models = [default_model] + model_aliases = { + "llama-3.1-8b": "llama-3.1", + } + + @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.get(model, cls.default_model) + else: + return cls.default_model + + @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="129", "Not=A?Brand";v="8"', + "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/129.0.0.0 Safari/537.36" + } + async with ClientSession(headers=headers) as session: + data = { + "messages": [{"role": "user", "content": format_prompt(messages)}] + } + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + response_text = await response.text() + + filtered_response = cls.filter_response(response_text) + yield filtered_response + + @staticmethod + def filter_response(response_text: str) -> str: + parts = response_text.split('"') + + text_parts = parts[1::2] + + clean_text = ''.join(text_parts) + + return clean_text diff --git a/g4f/Provider/Cloudflare.py b/g4f/Provider/Cloudflare.py new file mode 100644 index 00000000..e78bbcd0 --- /dev/null +++ b/g4f/Provider/Cloudflare.py @@ -0,0 +1,212 @@ +from __future__ import annotations + +import asyncio +import json +import uuid +import cloudscraper +from typing import AsyncGenerator +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + +class Cloudflare(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://playground.ai.cloudflare.com" + api_endpoint = "https://playground.ai.cloudflare.com/api/inference" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = '@cf/meta/llama-3.1-8b-instruct' + models = [ + '@cf/deepseek-ai/deepseek-math-7b-instruct', # Specific answer + + + '@cf/thebloke/discolm-german-7b-v1-awq', + + + '@cf/tiiuae/falcon-7b-instruct', # Specific answer + + + '@hf/google/gemma-7b-it', + + + '@cf/meta/llama-2-7b-chat-fp16', + '@cf/meta/llama-2-7b-chat-int8', + + '@cf/meta/llama-3-8b-instruct', + '@cf/meta/llama-3-8b-instruct-awq', + default_model, + '@hf/meta-llama/meta-llama-3-8b-instruct', + + '@cf/meta/llama-3.1-8b-instruct-awq', + '@cf/meta/llama-3.1-8b-instruct-fp8', + '@cf/meta/llama-3.2-11b-vision-instruct', + '@cf/meta/llama-3.2-1b-instruct', + '@cf/meta/llama-3.2-3b-instruct', + + '@cf/mistral/mistral-7b-instruct-v0.1', + '@hf/mistral/mistral-7b-instruct-v0.2', + + '@cf/openchat/openchat-3.5-0106', + + '@cf/microsoft/phi-2', + + '@cf/qwen/qwen1.5-0.5b-chat', + '@cf/qwen/qwen1.5-1.8b-chat', + '@cf/qwen/qwen1.5-14b-chat-awq', + '@cf/qwen/qwen1.5-7b-chat-awq', + + '@cf/defog/sqlcoder-7b-2', # Specific answer + + '@cf/tinyllama/tinyllama-1.1b-chat-v1.0', + + '@cf/fblgit/una-cybertron-7b-v2-bf16', + ] + + model_aliases = { + "german-7b-v1": "@cf/thebloke/discolm-german-7b-v1-awq", + + + "gemma-7b": "@hf/google/gemma-7b-it", + + + "llama-2-7b": "@cf/meta/llama-2-7b-chat-fp16", + "llama-2-7b": "@cf/meta/llama-2-7b-chat-int8", + + "llama-3-8b": "@cf/meta/llama-3-8b-instruct", + "llama-3-8b": "@cf/meta/llama-3-8b-instruct-awq", + "llama-3-8b": "@cf/meta/llama-3.1-8b-instruct", + "llama-3-8b": "@hf/meta-llama/meta-llama-3-8b-instruct", + + "llama-3.1-8b": "@cf/meta/llama-3.1-8b-instruct-awq", + "llama-3.1-8b": "@cf/meta/llama-3.1-8b-instruct-fp8", + "llama-3.1-8b": "@cf/meta/llama-3.1-8b-instruct-fp8", + + "llama-3.2-11b": "@cf/meta/llama-3.2-11b-vision-instruct", + "llama-3.2-1b": "@cf/meta/llama-3.2-1b-instruct", + "llama-3.2-3b": "@cf/meta/llama-3.2-3b-instruct", + + + "mistral-7b": "@cf/mistral/mistral-7b-instruct-v0.1", + "mistral-7b": "@hf/mistral/mistral-7b-instruct-v0.2", + + + "openchat-3.5": "@cf/openchat/openchat-3.5-0106", + + + "phi-2": "@cf/microsoft/phi-2", + + + "qwen-1.5-0.5b": "@cf/qwen/qwen1.5-0.5b-chat", + "qwen-1.5-1.8b": "@cf/qwen/qwen1.5-1.8b-chat", + "qwen-1.5-14b": "@cf/qwen/qwen1.5-14b-chat-awq", + "qwen-1.5-7b": "@cf/qwen/qwen1.5-7b-chat-awq", + + + "tinyllama-1.1b": "@cf/tinyllama/tinyllama-1.1b-chat-v1.0", + + + "cybertron-7b": "@cf/fblgit/una-cybertron-7b-v2-bf16", + } + + @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 + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + max_tokens: str = 2048, + stream: bool = True, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + 'Accept': 'text/event-stream', + 'Accept-Language': 'en-US,en;q=0.9', + 'Cache-Control': 'no-cache', + 'Content-Type': 'application/json', + 'Origin': cls.url, + 'Pragma': 'no-cache', + 'Referer': f'{cls.url}/', + 'Sec-Ch-Ua': '"Chromium";v="129", "Not=A?Brand";v="8"', + '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/129.0.0.0 Safari/537.36', + } + + cookies = { + '__cf_bm': uuid.uuid4().hex, + } + + scraper = cloudscraper.create_scraper() + + prompt = format_prompt(messages) + data = { + "messages": [ + {"role": "system", "content": "You are a helpful assistant"}, + {"role": "user", "content": prompt} + ], + "lora": None, + "model": model, + "max_tokens": max_tokens, + "stream": stream + } + + max_retries = 3 + for attempt in range(max_retries): + try: + response = scraper.post( + cls.api_endpoint, + headers=headers, + cookies=cookies, + json=data, + stream=True, + proxies={'http': proxy, 'https': proxy} if proxy else None + ) + + if response.status_code == 403: + await asyncio.sleep(2 ** attempt) + continue + + response.raise_for_status() + + for line in response.iter_lines(): + if line.startswith(b'data: '): + if line == b'data: [DONE]': + break + try: + content = json.loads(line[6:].decode('utf-8'))['response'] + yield content + except Exception: + continue + break + except Exception as e: + if attempt == max_retries - 1: + raise + + @classmethod + async def create_async( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> str: + full_response = "" + async for response in cls.create_async_generator(model, messages, proxy, **kwargs): + full_response += response + return full_response diff --git a/g4f/Provider/CodeNews.py b/g4f/Provider/CodeNews.py deleted file mode 100644 index 05ec7a45..00000000 --- a/g4f/Provider/CodeNews.py +++ /dev/null @@ -1,94 +0,0 @@ -from __future__ import annotations - -from aiohttp import ClientSession -from asyncio import sleep - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from .helper import format_prompt - - -class CodeNews(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://codenews.cc" - api_endpoint = "https://codenews.cc/chatxyz13" - working = True - supports_gpt_35_turbo = True - supports_gpt_4 = False - supports_stream = True - supports_system_message = False - supports_message_history = False - - default_model = 'free_gpt' - models = ['free_gpt', 'gpt-4o-mini', 'deepseek-coder', 'chatpdf'] - - model_aliases = { - "glm-4": "free_gpt", - "gpt-3.5-turbo": "chatpdf", - "deepseek": "deepseek-coder", - } - - @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 - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - model = cls.get_model(model) - - headers = { - "accept": "application/json, text/javascript, */*; q=0.01", - "accept-language": "en-US,en;q=0.9", - "cache-control": "no-cache", - "content-type": "application/x-www-form-urlencoded; charset=UTF-8", - "origin": cls.url, - "pragma": "no-cache", - "priority": "u=1, i", - "referer": f"{cls.url}/chatgpt", - "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", - "x-requested-with": "XMLHttpRequest", - } - async with ClientSession(headers=headers) as session: - prompt = format_prompt(messages) - data = { - "chatgpt_input": prompt, - "qa_type2": model, - "chatgpt_version_value": "20240804", - "enable_web_search": "0", - "enable_agent": "0", - "dy_video_text_extract": "0", - "enable_summary": "0", - } - async with session.post(cls.api_endpoint, data=data, proxy=proxy) as response: - response.raise_for_status() - json_data = await response.json() - chat_id = json_data["data"]["id"] - - headers["content-type"] = "application/x-www-form-urlencoded; charset=UTF-8" - data = {"current_req_count": "2"} - - while True: - async with session.post(f"{cls.url}/chat_stream", headers=headers, data=data, proxy=proxy) as response: - response.raise_for_status() - json_data = await response.json() - if json_data["data"]: - yield json_data["data"] - break - else: - await sleep(1) # Затримка перед наступним запитом diff --git a/g4f/Provider/DDG.py b/g4f/Provider/DDG.py index c8c36fc9..43cc39c0 100644 --- a/g4f/Provider/DDG.py +++ b/g4f/Provider/DDG.py @@ -2,115 +2,107 @@ from __future__ import annotations import json import aiohttp -import asyncio -from typing import Optional -import base64 +from aiohttp import ClientSession -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from .helper import get_connector from ..typing import AsyncResult, Messages -from ..requests.raise_for_status import raise_for_status -from ..providers.conversation import BaseConversation +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + class DDG(AsyncGeneratorProvider, ProviderModelMixin): - url = base64.b64decode("aHR0cHM6Ly9kdWNrZHVja2dvLmNvbS9haWNoYXQ=").decode("utf-8") + url = "https://duckduckgo.com" + api_endpoint = "https://duckduckgo.com/duckchat/v1/chat" working = True - supports_gpt_35_turbo = True + supports_stream = True + supports_system_message = True supports_message_history = True default_model = "gpt-4o-mini" - models = ["gpt-4o-mini", "claude-3-haiku-20240307", "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", "mistralai/Mixtral-8x7B-Instruct-v0.1"] + models = [ + "gpt-4o-mini", + "claude-3-haiku-20240307", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", + "mistralai/Mixtral-8x7B-Instruct-v0.1" + ] model_aliases = { "claude-3-haiku": "claude-3-haiku-20240307", "llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", "mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1" } - # Obfuscated URLs and headers - status_url = base64.b64decode("aHR0cHM6Ly9kdWNrZHVja2dvLmNvbS9kdWNrY2hhdC92MS9zdGF0dXM=").decode("utf-8") - chat_url = base64.b64decode("aHR0cHM6Ly9kdWNrZHVja2dvLmNvbS9kdWNrY2hhdC92MS9jaGF0").decode("utf-8") - referer = base64.b64decode("aHR0cHM6Ly9kdWNrZHVja2dvLmNvbS8=").decode("utf-8") - origin = base64.b64decode("aHR0cHM6Ly9kdWNrZHVja2dvLmNvbQ==").decode("utf-8") - - user_agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36' - headers = { - 'User-Agent': user_agent, - 'Accept': 'text/event-stream', - 'Accept-Language': 'en-US,en;q=0.5', - 'Accept-Encoding': 'gzip, deflate, br, zstd', - 'Referer': referer, - 'Content-Type': 'application/json', - 'Origin': origin, - 'Connection': 'keep-alive', - 'Cookie': 'dcm=3', - 'Sec-Fetch-Dest': 'empty', - 'Sec-Fetch-Mode': 'cors', - 'Sec-Fetch-Site': 'same-origin', - 'Pragma': 'no-cache', - 'TE': 'trailers' - } + @classmethod + def get_model(cls, model: str) -> str: + return cls.model_aliases.get(model, model) if model in cls.model_aliases else cls.default_model @classmethod - async def get_vqd(cls, session: aiohttp.ClientSession) -> Optional[str]: - try: - async with session.get(cls.status_url, headers={"x-vqd-accept": "1"}) as response: - await raise_for_status(response) - return response.headers.get("x-vqd-4") - except Exception as e: - print(f"Error getting VQD: {e}") - return None + async def get_vqd(cls): + status_url = "https://duckduckgo.com/duckchat/v1/status" + + headers = { + 'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36', + 'Accept': 'text/event-stream', + 'x-vqd-accept': '1' + } + + async with aiohttp.ClientSession() as session: + try: + async with session.get(status_url, headers=headers) as response: + if response.status == 200: + return response.headers.get("x-vqd-4") + else: + print(f"Error: Status code {response.status}") + return None + except Exception as e: + print(f"Error getting VQD: {e}") + return None @classmethod async def create_async_generator( cls, model: str, messages: Messages, + conversation: dict = None, proxy: str = None, - connector: aiohttp.BaseConnector = None, - conversation: Conversation = None, - return_conversation: bool = False, **kwargs ) -> AsyncResult: - async with aiohttp.ClientSession(headers=cls.headers, connector=get_connector(connector, proxy)) as session: - vqd_4 = None - if conversation is not None and len(messages) > 1: - vqd_4 = conversation.vqd_4 - messages = [*conversation.messages, messages[-2], messages[-1]] - else: - for _ in range(3): # Try up to 3 times to get a valid VQD - vqd_4 = await cls.get_vqd(session) - if vqd_4: - break - await asyncio.sleep(1) # Wait a bit before retrying - - if not vqd_4: - raise Exception("Failed to obtain a valid VQD token") - - messages = [messages[-1]] # Only use the last message for new conversations - - payload = { - 'model': cls.get_model(model), - 'messages': [{'role': m['role'], 'content': m['content']} for m in messages] + model = cls.get_model(model) + + headers = { + 'accept': 'text/event-stream', + 'content-type': 'application/json', + 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36', + } + + vqd = conversation.get('vqd') if conversation else await cls.get_vqd() + if not vqd: + raise Exception("Failed to obtain VQD token") + + headers['x-vqd-4'] = vqd + + if conversation: + message_history = conversation.get('messages', []) + message_history.append({"role": "user", "content": format_prompt(messages)}) + else: + message_history = [{"role": "user", "content": format_prompt(messages)}] + + async with ClientSession(headers=headers) as session: + data = { + "model": model, + "messages": message_history } - - async with session.post(cls.chat_url, json=payload, headers={"x-vqd-4": vqd_4}) as response: - await raise_for_status(response) - if return_conversation: - yield Conversation(vqd_4, messages) - - async for line in response.content: - if line.startswith(b"data: "): - chunk = line[6:] - if chunk.startswith(b"[DONE]"): - break - try: - data = json.loads(chunk) - if "message" in data and data["message"]: - yield data["message"] - except json.JSONDecodeError: - print(f"Failed to decode JSON: {chunk}") -class Conversation(BaseConversation): - def __init__(self, vqd_4: str, messages: Messages) -> None: - self.vqd_4 = vqd_4 - self.messages = messages + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + async for line in response.content: + if line: + decoded_line = line.decode('utf-8') + if decoded_line.startswith('data: '): + json_str = decoded_line[6:] + if json_str == '[DONE]': + break + try: + json_data = json.loads(json_str) + if 'message' in json_data: + yield json_data['message'] + except json.JSONDecodeError: + pass diff --git a/g4f/Provider/DarkAI.py b/g4f/Provider/DarkAI.py new file mode 100644 index 00000000..6ffb615e --- /dev/null +++ b/g4f/Provider/DarkAI.py @@ -0,0 +1,85 @@ +from __future__ import annotations + +import json +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + + +class DarkAI(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://www.aiuncensored.info" + api_endpoint = "https://darkai.foundation/chat" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'gpt-4o' + models = [ + default_model, # Uncensored + 'gpt-3.5-turbo', # Uncensored + 'llama-3-70b', # Uncensored + 'llama-3-405b', + ] + + model_aliases = { + "llama-3.1-70b": "llama-3-70b", + "llama-3.1-405b": "llama-3-405b", + } + + @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 + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "accept": "text/event-stream", + "content-type": "application/json", + "origin": "https://www.aiuncensored.info", + "referer": "https://www.aiuncensored.info/", + "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) 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 = { + "query": prompt, + "model": model, + } + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + full_text = "" + async for chunk in response.content: + if chunk: + try: + chunk_str = chunk.decode().strip() + if chunk_str.startswith('data: '): + chunk_data = json.loads(chunk_str[6:]) + if chunk_data['event'] == 'text-chunk': + full_text += chunk_data['data']['text'] + elif chunk_data['event'] == 'stream-end': + if full_text: + yield full_text.strip() + return + except json.JSONDecodeError: + print(f"Failed to decode JSON: {chunk_str}") + except Exception as e: + print(f"Error processing chunk: {e}") + + if full_text: + yield full_text.strip() diff --git a/g4f/Provider/DeepInfraChat.py b/g4f/Provider/DeepInfraChat.py new file mode 100644 index 00000000..b8cc6ab8 --- /dev/null +++ b/g4f/Provider/DeepInfraChat.py @@ -0,0 +1,142 @@ +from __future__ import annotations + +from aiohttp import ClientSession +import json + +from ..typing import AsyncResult, Messages, ImageType +from ..image import to_data_uri +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + + +class DeepInfraChat(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://deepinfra.com/chat" + api_endpoint = "https://api.deepinfra.com/v1/openai/chat/completions" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'meta-llama/Meta-Llama-3.1-70B-Instruct' + models = [ + 'meta-llama/Meta-Llama-3.1-405B-Instruct', + 'meta-llama/Meta-Llama-3.1-70B-Instruct', + 'meta-llama/Meta-Llama-3.1-8B-Instruct', + 'mistralai/Mixtral-8x22B-Instruct-v0.1', + 'mistralai/Mixtral-8x7B-Instruct-v0.1', + 'microsoft/WizardLM-2-8x22B', + 'microsoft/WizardLM-2-7B', + 'Qwen/Qwen2-72B-Instruct', + 'microsoft/Phi-3-medium-4k-instruct', + 'google/gemma-2-27b-it', + 'openbmb/MiniCPM-Llama3-V-2_5', # Image upload is available + 'mistralai/Mistral-7B-Instruct-v0.3', + 'lizpreciatior/lzlv_70b_fp16_hf', + 'openchat/openchat-3.6-8b', + 'Phind/Phind-CodeLlama-34B-v2', + 'cognitivecomputations/dolphin-2.9.1-llama-3-70b', + ] + model_aliases = { + "llama-3.1-405b": "meta-llama/Meta-Llama-3.1-405B-Instruct", + "llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct", + "llama-3.1-8B": "meta-llama/Meta-Llama-3.1-8B-Instruct", + "mixtral-8x22b": "mistralai/Mixtral-8x22B-Instruct-v0.1", + "mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1", + "wizardlm-2-8x22b": "microsoft/WizardLM-2-8x22B", + "wizardlm-2-7b": "microsoft/WizardLM-2-7B", + "qwen-2-72b": "Qwen/Qwen2-72B-Instruct", + "phi-3-medium-4k": "microsoft/Phi-3-medium-4k-instruct", + "gemma-2b-27b": "google/gemma-2-27b-it", + "minicpm-llama-3-v2.5": "openbmb/MiniCPM-Llama3-V-2_5", # Image upload is available + "mistral-7b": "mistralai/Mistral-7B-Instruct-v0.3", + "lzlv-70b": "lizpreciatior/lzlv_70b_fp16_hf", + "openchat-3.6-8b": "openchat/openchat-3.6-8b", + "phind-codellama-34b-v2": "Phind/Phind-CodeLlama-34B-v2", + "dolphin-2.9.1-llama-3-70b": "cognitivecomputations/dolphin-2.9.1-llama-3-70b", + } + + + @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 + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + image: ImageType = None, + image_name: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + 'Accept-Language': 'en-US,en;q=0.9', + 'Cache-Control': 'no-cache', + 'Connection': 'keep-alive', + 'Content-Type': 'application/json', + 'Origin': 'https://deepinfra.com', + 'Pragma': 'no-cache', + 'Referer': 'https://deepinfra.com/', + 'Sec-Fetch-Dest': 'empty', + 'Sec-Fetch-Mode': 'cors', + 'Sec-Fetch-Site': 'same-site', + 'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36', + 'X-Deepinfra-Source': 'web-embed', + 'accept': 'text/event-stream', + 'sec-ch-ua': '"Not;A=Brand";v="24", "Chromium";v="128"', + 'sec-ch-ua-mobile': '?0', + 'sec-ch-ua-platform': '"Linux"', + } + + async with ClientSession(headers=headers) as session: + prompt = format_prompt(messages) + data = { + 'model': model, + 'messages': [ + {'role': 'system', 'content': 'Be a helpful assistant'}, + {'role': 'user', 'content': prompt} + ], + 'stream': True + } + + if model == 'openbmb/MiniCPM-Llama3-V-2_5' and image is not None: + data['messages'][-1]['content'] = [ + { + 'type': 'image_url', + 'image_url': { + 'url': to_data_uri(image) + } + }, + { + 'type': 'text', + 'text': messages[-1]['content'] + } + ] + + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + async for line in response.content: + if line: + decoded_line = line.decode('utf-8').strip() + if decoded_line.startswith('data:'): + json_part = decoded_line[5:].strip() + if json_part == '[DONE]': + break + try: + data = json.loads(json_part) + choices = data.get('choices', []) + if choices: + delta = choices[0].get('delta', {}) + content = delta.get('content', '') + if content: + yield content + except json.JSONDecodeError: + print(f"JSON decode error: {json_part}") diff --git a/g4f/Provider/DeepInfraImage.py b/g4f/Provider/DeepInfraImage.py index 46a5c2e2..cee608ce 100644 --- a/g4f/Provider/DeepInfraImage.py +++ b/g4f/Provider/DeepInfraImage.py @@ -11,7 +11,8 @@ class DeepInfraImage(AsyncGeneratorProvider, ProviderModelMixin): url = "https://deepinfra.com" parent = "DeepInfra" working = True - default_model = 'stability-ai/sdxl' + needs_auth = True + default_model = '' image_models = [default_model] @classmethod @@ -76,4 +77,4 @@ class DeepInfraImage(AsyncGeneratorProvider, ProviderModelMixin): if not images: raise RuntimeError(f"Response: {data}") images = images[0] if len(images) == 1 else images - return ImageResponse(images, prompt)
\ No newline at end of file + return ImageResponse(images, prompt) diff --git a/g4f/Provider/Editee.py b/g4f/Provider/Editee.py new file mode 100644 index 00000000..8ac2324a --- /dev/null +++ b/g4f/Provider/Editee.py @@ -0,0 +1,77 @@ +from __future__ import annotations + +from aiohttp import ClientSession +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + + +class Editee(AsyncGeneratorProvider, ProviderModelMixin): + label = "Editee" + url = "https://editee.com" + api_endpoint = "https://editee.com/submit/chatgptfree" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'claude' + models = ['claude', 'gpt4', 'gemini' 'mistrallarge'] + + model_aliases = { + "claude-3.5-sonnet": "claude", + "gpt-4o": "gpt4", + "gemini-pro": "gemini", + "mistral-large": "mistrallarge", + } + + @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 + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "Accept": "application/json, text/plain, */*", + "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}/chat-gpt", + "Sec-CH-UA": '"Chromium";v="129", "Not=A?Brand";v="8"', + "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/129.0.0.0 Safari/537.36', + "X-Requested-With": 'XMLHttpRequest', + } + + async with ClientSession(headers=headers) as session: + prompt = format_prompt(messages) + data = { + "user_input": prompt, + "context": " ", + "template_id": "", + "selected_model": model + } + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + response_data = await response.json() + yield response_data['text'] diff --git a/g4f/Provider/FlowGpt.py b/g4f/Provider/FlowGpt.py index d823a7ab..1a45997b 100644 --- a/g4f/Provider/FlowGpt.py +++ b/g4f/Provider/FlowGpt.py @@ -12,8 +12,7 @@ from ..requests.raise_for_status import raise_for_status class FlowGpt(AsyncGeneratorProvider, ProviderModelMixin): url = "https://flowgpt.com/chat" - working = True - supports_gpt_35_turbo = True + working = False supports_message_history = True supports_system_message = True default_model = "gpt-3.5-turbo" diff --git a/g4f/Provider/FluxAirforce.py b/g4f/Provider/FluxAirforce.py deleted file mode 100644 index fe003a61..00000000 --- a/g4f/Provider/FluxAirforce.py +++ /dev/null @@ -1,82 +0,0 @@ -from __future__ import annotations - -from aiohttp import ClientSession, ClientResponseError -from urllib.parse import urlencode -import io - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from ..image import ImageResponse, is_accepted_format - -class FluxAirforce(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://flux.api.airforce/" - api_endpoint = "https://api.airforce/v1/imagine2" - working = True - default_model = 'flux-realism' - models = [ - 'flux', - 'flux-realism', - 'flux-anime', - 'flux-3d', - 'flux-disney' - ] - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - headers = { - "accept": "*/*", - "accept-language": "en-US,en;q=0.9", - "origin": "https://flux.api.airforce", - "priority": "u=1, i", - "referer": "https://flux.api.airforce/", - "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-site", - "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36" - } - - prompt = messages[-1]['content'] if messages else "" - - params = { - "prompt": prompt, - "size": kwargs.get("size", "1:1"), - "seed": kwargs.get("seed"), - "model": model - } - - params = {k: v for k, v in params.items() if v is not None} - - try: - async with ClientSession(headers=headers) as session: - async with session.get(f"{cls.api_endpoint}", params=params, proxy=proxy) as response: - response.raise_for_status() - - content = await response.read() - - if response.content_type.startswith('image/'): - image_url = str(response.url) - yield ImageResponse(image_url, prompt) - else: - try: - text = content.decode('utf-8', errors='ignore') - yield f"Error: {text}" - except Exception as decode_error: - yield f"Error: Unable to decode response - {str(decode_error)}" - - except ClientResponseError as e: - yield f"Error: HTTP {e.status}: {e.message}" - except Exception as e: - yield f"Unexpected error: {str(e)}" - - finally: - if not session.closed: - await session.close() diff --git a/g4f/Provider/FreeNetfly.py b/g4f/Provider/FreeNetfly.py index d0543176..ada5d51a 100644 --- a/g4f/Provider/FreeNetfly.py +++ b/g4f/Provider/FreeNetfly.py @@ -13,8 +13,6 @@ class FreeNetfly(AsyncGeneratorProvider, ProviderModelMixin): url = "https://free.netfly.top" api_endpoint = "/api/openai/v1/chat/completions" working = True - supports_gpt_35_turbo = True - supports_gpt_4 = True default_model = 'gpt-3.5-turbo' models = [ 'gpt-3.5-turbo', diff --git a/g4f/Provider/GPROChat.py b/g4f/Provider/GPROChat.py new file mode 100644 index 00000000..a33c9571 --- /dev/null +++ b/g4f/Provider/GPROChat.py @@ -0,0 +1,67 @@ +from __future__ import annotations +import hashlib +import time +from aiohttp import ClientSession +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + +class GPROChat(AsyncGeneratorProvider, ProviderModelMixin): + label = "GPROChat" + url = "https://gprochat.com" + api_endpoint = "https://gprochat.com/api/generate" + working = True + supports_stream = True + supports_message_history = True + default_model = 'gemini-pro' + + @staticmethod + def generate_signature(timestamp: int, message: str) -> str: + secret_key = "2BC120D4-BB36-1B60-26DE-DB630472A3D8" + hash_input = f"{timestamp}:{message}:{secret_key}" + signature = hashlib.sha256(hash_input.encode('utf-8')).hexdigest() + return signature + + @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 + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + timestamp = int(time.time() * 1000) + prompt = format_prompt(messages) + sign = cls.generate_signature(timestamp, prompt) + + headers = { + "accept": "*/*", + "origin": cls.url, + "referer": f"{cls.url}/", + "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36", + "content-type": "text/plain;charset=UTF-8" + } + + data = { + "messages": [{"role": "user", "parts": [{"text": prompt}]}], + "time": timestamp, + "pass": None, + "sign": sign + } + + async with ClientSession(headers=headers) as session: + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + async for chunk in response.content.iter_any(): + if chunk: + yield chunk.decode() diff --git a/g4f/Provider/GeminiPro.py b/g4f/Provider/GeminiPro.py index b225c26c..06bf69ee 100644 --- a/g4f/Provider/GeminiPro.py +++ b/g4f/Provider/GeminiPro.py @@ -54,6 +54,7 @@ class GeminiPro(AsyncGeneratorProvider, ProviderModelMixin): "parts": [{"text": message["content"]}] } for message in messages + if message["role"] != "system" ] if image is not None: image = to_bytes(image) @@ -73,6 +74,13 @@ class GeminiPro(AsyncGeneratorProvider, ProviderModelMixin): "topK": kwargs.get("top_k"), } } + system_prompt = "\n".join( + message["content"] + for message in messages + if message["role"] == "system" + ) + if system_prompt: + data["system_instruction"] = {"parts": {"text": system_prompt}} async with session.post(url, params=params, json=data) as response: if not response.ok: data = await response.json() diff --git a/g4f/Provider/GizAI.py b/g4f/Provider/GizAI.py new file mode 100644 index 00000000..127edc9e --- /dev/null +++ b/g4f/Provider/GizAI.py @@ -0,0 +1,151 @@ +from __future__ import annotations + +import json +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from ..image import ImageResponse +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + +class GizAI(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://app.giz.ai/assistant/" + api_endpoint = "https://app.giz.ai/api/data/users/inferenceServer.infer" + working = True + + supports_system_message = True + supports_message_history = True + + # Chat models + default_model = 'chat-gemini-flash' + chat_models = [ + default_model, + 'chat-gemini-pro', + 'chat-gpt4m', + 'chat-gpt4', + 'claude-sonnet', + 'claude-haiku', + 'llama-3-70b', + 'llama-3-8b', + 'mistral-large', + 'chat-o1-mini' + ] + + # Image models + image_models = [ + 'flux1', + 'sdxl', + 'sd', + 'sd35', + ] + + models = [*chat_models, *image_models] + + model_aliases = { + # Chat model aliases + "gemini-flash": "chat-gemini-flash", + "gemini-pro": "chat-gemini-pro", + "gpt-4o-mini": "chat-gpt4m", + "gpt-4o": "chat-gpt4", + "claude-3.5-sonnet": "claude-sonnet", + "claude-3-haiku": "claude-haiku", + "llama-3.1-70b": "llama-3-70b", + "llama-3.1-8b": "llama-3-8b", + "o1-mini": "chat-o1-mini", + # Image model aliases + "sd-1.5": "sd", + "sd-3.5": "sd35", + "flux-schnell": "flux1", + } + + @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 is_image_model(cls, model: str) -> bool: + return model in cls.image_models + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + 'Accept': 'application/json, text/plain, */*', + 'Accept-Language': 'en-US,en;q=0.9', + 'Cache-Control': 'no-cache', + 'Connection': 'keep-alive', + 'Content-Type': 'application/json', + 'Origin': 'https://app.giz.ai', + 'Pragma': 'no-cache', + '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/130.0.0.0 Safari/537.36', + 'sec-ch-ua': '"Not?A_Brand";v="99", "Chromium";v="130"', + 'sec-ch-ua-mobile': '?0', + 'sec-ch-ua-platform': '"Linux"' + } + + async with ClientSession() as session: + if cls.is_image_model(model): + # Image generation + prompt = messages[-1]["content"] + data = { + "model": model, + "input": { + "width": "1024", + "height": "1024", + "steps": 4, + "output_format": "webp", + "batch_size": 1, + "mode": "plan", + "prompt": prompt + } + } + async with session.post( + cls.api_endpoint, + headers=headers, + data=json.dumps(data), + proxy=proxy + ) as response: + response.raise_for_status() + response_data = await response.json() + if response_data.get('status') == 'completed' and response_data.get('output'): + for url in response_data['output']: + yield ImageResponse(images=url, alt="Generated Image") + else: + # Chat completion + data = { + "model": model, + "input": { + "messages": [ + { + "type": "human", + "content": format_prompt(messages) + } + ], + "mode": "plan" + }, + "noStream": True + } + async with session.post( + cls.api_endpoint, + headers=headers, + data=json.dumps(data), + proxy=proxy + ) as response: + response.raise_for_status() + result = await response.json() + yield result.get('output', '') diff --git a/g4f/Provider/GptTalkRu.py b/g4f/Provider/GptTalkRu.py deleted file mode 100644 index 6a59484f..00000000 --- a/g4f/Provider/GptTalkRu.py +++ /dev/null @@ -1,59 +0,0 @@ -from __future__ import annotations - -from aiohttp import ClientSession, BaseConnector - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider -from .helper import get_random_string, get_connector -from ..requests import raise_for_status, get_args_from_browser, WebDriver -from ..webdriver import has_seleniumwire -from ..errors import MissingRequirementsError - -class GptTalkRu(AsyncGeneratorProvider): - url = "https://gpttalk.ru" - working = True - supports_gpt_35_turbo = True - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - connector: BaseConnector = None, - webdriver: WebDriver = None, - **kwargs - ) -> AsyncResult: - if not model: - model = "gpt-3.5-turbo" - if not has_seleniumwire: - raise MissingRequirementsError('Install "selenium-wire" package') - args = get_args_from_browser(f"{cls.url}", webdriver) - args["headers"]["accept"] = "application/json, text/plain, */*" - async with ClientSession(connector=get_connector(connector, proxy), **args) as session: - async with session.get("https://gpttalk.ru/getToken") as response: - await raise_for_status(response) - public_key = (await response.json())["response"]["key"]["publicKey"] - random_string = get_random_string(8) - data = { - "model": model, - "modelType": 1, - "prompt": messages, - "responseType": "stream", - "security": { - "randomMessage": random_string, - "shifrText": encrypt(public_key, random_string) - } - } - async with session.post(f"{cls.url}/gpt2", json=data, proxy=proxy) as response: - await raise_for_status(response) - async for chunk in response.content.iter_any(): - yield chunk.decode(errors="ignore") - -def encrypt(public_key: str, value: str) -> str: - from Crypto.Cipher import PKCS1_v1_5 - from Crypto.PublicKey import RSA - import base64 - rsa_key = RSA.importKey(public_key) - cipher = PKCS1_v1_5.new(rsa_key) - return base64.b64encode(cipher.encrypt(value.encode())).decode()
\ No newline at end of file diff --git a/g4f/Provider/HuggingChat.py b/g4f/Provider/HuggingChat.py index 76c76a35..7ebbf570 100644 --- a/g4f/Provider/HuggingChat.py +++ b/g4f/Provider/HuggingChat.py @@ -1,6 +1,7 @@ from __future__ import annotations -import json, requests, re +import json +import requests from curl_cffi import requests as cf_reqs from ..typing import CreateResult, Messages @@ -12,26 +13,27 @@ class HuggingChat(AbstractProvider, ProviderModelMixin): working = True supports_stream = True default_model = "meta-llama/Meta-Llama-3.1-70B-Instruct" + models = [ 'meta-llama/Meta-Llama-3.1-70B-Instruct', - 'meta-llama/Meta-Llama-3.1-405B-Instruct-FP8', - 'CohereForAI/c4ai-command-r-plus', - 'mistralai/Mixtral-8x7B-Instruct-v0.1', - 'NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO', - '01-ai/Yi-1.5-34B-Chat', - 'mistralai/Mistral-7B-Instruct-v0.3', - 'microsoft/Phi-3-mini-4k-instruct', + 'CohereForAI/c4ai-command-r-plus-08-2024', + 'Qwen/Qwen2.5-72B-Instruct', + 'nvidia/Llama-3.1-Nemotron-70B-Instruct-HF', + 'meta-llama/Llama-3.2-11B-Vision-Instruct', + 'NousResearch/Hermes-3-Llama-3.1-8B', + 'mistralai/Mistral-Nemo-Instruct-2407', + 'microsoft/Phi-3.5-mini-instruct', ] model_aliases = { "llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct", - "llama-3.1-405b": "meta-llama/Meta-Llama-3.1-405B-Instruct-FP8", - "command-r-plus": "CohereForAI/c4ai-command-r-plus", - "mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1", - "mixtral-8x7b": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", - "yi-1.5-34b": "01-ai/Yi-1.5-34B-Chat", - "mistral-7b": "mistralai/Mistral-7B-Instruct-v0.3", - "phi-3-mini-4k": "microsoft/Phi-3-mini-4k-instruct", + "command-r-plus": "CohereForAI/c4ai-command-r-plus-08-2024", + "qwen-2-72b": "Qwen/Qwen2.5-72B-Instruct", + "nemotron-70b": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF", + "llama-3.2-11b": "meta-llama/Llama-3.2-11B-Vision-Instruct", + "hermes-3": "NousResearch/Hermes-3-Llama-3.1-8B", + "mistral-nemo": "mistralai/Mistral-Nemo-Instruct-2407", + "phi-3.5-mini": "microsoft/Phi-3.5-mini-instruct", } @classmethod @@ -72,17 +74,18 @@ class HuggingChat(AbstractProvider, ProviderModelMixin): 'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36', } - print(model) json_data = { 'model': model, } response = session.post('https://huggingface.co/chat/conversation', json=json_data) - conversationId = response.json()['conversationId'] + if response.status_code != 200: + raise RuntimeError(f"Request failed with status code: {response.status_code}, response: {response.text}") - response = session.get(f'https://huggingface.co/chat/conversation/{conversationId}/__data.json?x-sveltekit-invalidated=01',) + conversationId = response.json().get('conversationId') + response = session.get(f'https://huggingface.co/chat/conversation/{conversationId}/__data.json?x-sveltekit-invalidated=11') - data: list = (response.json())["nodes"][1]["data"] + data: list = response.json()["nodes"][1]["data"] keys: list[int] = data[data[0]["messages"]] message_keys: dict = data[keys[0]] messageId: str = data[message_keys["id"]] @@ -123,22 +126,26 @@ class HuggingChat(AbstractProvider, ProviderModelMixin): files=files, ) - first_token = True + full_response = "" for line in response.iter_lines(): - line = json.loads(line) + if not line: + continue + try: + line = json.loads(line) + except json.JSONDecodeError as e: + print(f"Failed to decode JSON: {line}, error: {e}") + continue if "type" not in line: raise RuntimeError(f"Response: {line}") elif line["type"] == "stream": - token = line["token"] - if first_token: - token = token.lstrip().replace('\u0000', '') - first_token = False - else: - token = token.replace('\u0000', '') - - yield token + token = line["token"].replace('\u0000', '') + full_response += token elif line["type"] == "finalAnswer": break + + full_response = full_response.replace('<|im_end|', '').replace('\u0000', '').strip() + + yield full_response diff --git a/g4f/Provider/HuggingFace.py b/g4f/Provider/HuggingFace.py index 74957862..586e5f5f 100644 --- a/g4f/Provider/HuggingFace.py +++ b/g4f/Provider/HuggingFace.py @@ -9,33 +9,16 @@ from .helper import get_connector from ..errors import RateLimitError, ModelNotFoundError from ..requests.raise_for_status import raise_for_status +from .HuggingChat import HuggingChat + class HuggingFace(AsyncGeneratorProvider, ProviderModelMixin): url = "https://huggingface.co/chat" working = True needs_auth = True supports_message_history = True - default_model = "meta-llama/Meta-Llama-3.1-70B-Instruct" - models = [ - 'meta-llama/Meta-Llama-3.1-70B-Instruct', - 'meta-llama/Meta-Llama-3.1-405B-Instruct-FP8', - 'CohereForAI/c4ai-command-r-plus', - 'mistralai/Mixtral-8x7B-Instruct-v0.1', - 'NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO', - '01-ai/Yi-1.5-34B-Chat', - 'mistralai/Mistral-7B-Instruct-v0.3', - 'microsoft/Phi-3-mini-4k-instruct', - ] - - model_aliases = { - "llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct", - "llama-3.1-405b": "meta-llama/Meta-Llama-3.1-405B-Instruct-FP8", - "command-r-plus": "CohereForAI/c4ai-command-r-plus", - "mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1", - "mixtral-8x7b": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", - "yi-1.5-34b": "01-ai/Yi-1.5-34B-Chat", - "mistral-7b": "mistralai/Mistral-7B-Instruct-v0.3", - "phi-3-mini-4k": "microsoft/Phi-3-mini-4k-instruct", - } + default_model = HuggingChat.default_model + models = HuggingChat.models + model_aliases = HuggingChat.model_aliases @classmethod def get_model(cls, model: str) -> str: diff --git a/g4f/Provider/Koala.py b/g4f/Provider/Koala.py index 0e810083..0dd76b71 100644 --- a/g4f/Provider/Koala.py +++ b/g4f/Provider/Koala.py @@ -10,10 +10,10 @@ from .helper import get_random_string, get_connector from ..requests import raise_for_status class Koala(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://koala.sh" + url = "https://koala.sh/chat" + api_endpoint = "https://koala.sh/api/gpt/" working = True supports_message_history = True - supports_gpt_4 = True default_model = 'gpt-4o-mini' @classmethod @@ -26,17 +26,17 @@ class Koala(AsyncGeneratorProvider, ProviderModelMixin): **kwargs: Any ) -> AsyncGenerator[Dict[str, Union[str, int, float, List[Dict[str, Any]], None]], None]: if not model: - model = "gpt-3.5-turbo" + model = "gpt-4o-mini" headers = { "User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:122.0) Gecko/20100101 Firefox/122.0", "Accept": "text/event-stream", "Accept-Language": "de,en-US;q=0.7,en;q=0.3", "Accept-Encoding": "gzip, deflate, br", - "Referer": f"{cls.url}/chat", + "Referer": f"{cls.url}", "Flag-Real-Time-Data": "false", "Visitor-ID": get_random_string(20), - "Origin": cls.url, + "Origin": "https://koala.sh", "Alt-Used": "koala.sh", "Sec-Fetch-Dest": "empty", "Sec-Fetch-Mode": "cors", @@ -67,7 +67,7 @@ class Koala(AsyncGeneratorProvider, ProviderModelMixin): "model": model, } - async with session.post(f"{cls.url}/api/gpt/", json=data, proxy=proxy) as response: + async with session.post(f"{cls.api_endpoint}", json=data, proxy=proxy) as response: await raise_for_status(response) async for chunk in cls._parse_event_stream(response): yield chunk diff --git a/g4f/Provider/Liaobots.py b/g4f/Provider/Liaobots.py index 8a9f46b1..56f765de 100644 --- a/g4f/Provider/Liaobots.py +++ b/g4f/Provider/Liaobots.py @@ -9,6 +9,15 @@ from .helper import get_connector from ..requests import raise_for_status models = { + "gpt-3.5-turbo": { + "id": "gpt-3.5-turbo", + "name": "GPT-3.5-Turbo", + "model": "ChatGPT", + "provider": "OpenAI", + "maxLength": 48000, + "tokenLimit": 14000, + "context": "16K", + }, "gpt-4o-mini-free": { "id": "gpt-4o-mini-free", "name": "GPT-4o-Mini-Free", @@ -36,32 +45,41 @@ models = { "tokenLimit": 7800, "context": "8K", }, - "gpt-4-turbo-2024-04-09": { - "id": "gpt-4-turbo-2024-04-09", - "name": "GPT-4-Turbo", + "gpt-4o-2024-08-06": { + "id": "gpt-4o-2024-08-06", + "name": "GPT-4o", "model": "ChatGPT", "provider": "OpenAI", "maxLength": 260000, "tokenLimit": 126000, "context": "128K", }, - "gpt-4o-2024-08-06": { - "id": "gpt-4o-2024-08-06", - "name": "GPT-4o", + "gpt-4-turbo-2024-04-09": { + "id": "gpt-4-turbo-2024-04-09", + "name": "GPT-4-Turbo", "model": "ChatGPT", "provider": "OpenAI", "maxLength": 260000, "tokenLimit": 126000, "context": "128K", }, - "gpt-4-0613": { - "id": "gpt-4-0613", - "name": "GPT-4-0613", - "model": "ChatGPT", - "provider": "OpenAI", - "maxLength": 32000, - "tokenLimit": 7600, - "context": "8K", + "grok-2": { + "id": "grok-2", + "name": "Grok-2", + "model": "Grok", + "provider": "x.ai", + "maxLength": 400000, + "tokenLimit": 100000, + "context": "100K", + }, + "grok-2-mini": { + "id": "grok-2-mini", + "name": "Grok-2-mini", + "model": "Grok", + "provider": "x.ai", + "maxLength": 400000, + "tokenLimit": 100000, + "context": "100K", }, "claude-3-opus-20240229": { "id": "claude-3-opus-20240229", @@ -90,18 +108,18 @@ models = { "tokenLimit": 200000, "context": "200K", }, - "claude-3-sonnet-20240229": { - "id": "claude-3-sonnet-20240229", - "name": "Claude-3-Sonnet", + "claude-3-5-sonnet-20240620": { + "id": "claude-3-5-sonnet-20240620", + "name": "Claude-3.5-Sonnet", "model": "Claude", "provider": "Anthropic", "maxLength": 800000, "tokenLimit": 200000, "context": "200K", }, - "claude-3-5-sonnet-20240620": { - "id": "claude-3-5-sonnet-20240620", - "name": "Claude-3.5-Sonnet", + "claude-3-sonnet-20240229": { + "id": "claude-3-sonnet-20240229", + "name": "Claude-3-Sonnet", "model": "Claude", "provider": "Anthropic", "maxLength": 800000, @@ -126,17 +144,8 @@ models = { "tokenLimit": 200000, "context": "200K", }, - "gemini-1.0-pro-latest": { - "id": "gemini-1.0-pro-latest", - "name": "Gemini-Pro", - "model": "Gemini", - "provider": "Google", - "maxLength": 120000, - "tokenLimit": 30000, - "context": "32K", - }, - "gemini-1.5-flash-latest": { - "id": "gemini-1.5-flash-latest", + "gemini-1.5-flash-002": { + "id": "gemini-1.5-flash-002", "name": "Gemini-1.5-Flash-1M", "model": "Gemini", "provider": "Google", @@ -144,8 +153,8 @@ models = { "tokenLimit": 1000000, "context": "1024K", }, - "gemini-1.5-pro-latest": { - "id": "gemini-1.5-pro-latest", + "gemini-1.5-pro-002": { + "id": "gemini-1.5-pro-002", "name": "Gemini-1.5-Pro-1M", "model": "Gemini", "provider": "Google", @@ -161,28 +170,27 @@ class Liaobots(AsyncGeneratorProvider, ProviderModelMixin): working = True supports_message_history = True supports_system_message = True - supports_gpt_4 = True - default_model = "gpt-4o" + default_model = "gpt-3.5-turbo" models = list(models.keys()) model_aliases = { "gpt-4o-mini": "gpt-4o-mini-free", "gpt-4o": "gpt-4o-free", - "gpt-4-turbo": "gpt-4-turbo-2024-04-09", "gpt-4o": "gpt-4o-2024-08-06", + + "gpt-4-turbo": "gpt-4-turbo-2024-04-09", "gpt-4": "gpt-4-0613", "claude-3-opus": "claude-3-opus-20240229", "claude-3-opus": "claude-3-opus-20240229-aws", "claude-3-opus": "claude-3-opus-20240229-gcp", "claude-3-sonnet": "claude-3-sonnet-20240229", - "claude-3-5-sonnet": "claude-3-5-sonnet-20240620", + "claude-3.5-sonnet": "claude-3-5-sonnet-20240620", "claude-3-haiku": "claude-3-haiku-20240307", "claude-2.1": "claude-2.1", - "gemini-pro": "gemini-1.0-pro-latest", - "gemini-flash": "gemini-1.5-flash-latest", - "gemini-pro": "gemini-1.5-pro-latest", + "gemini-flash": "gemini-1.5-flash-002", + "gemini-pro": "gemini-1.5-pro-002", } _auth_code = "" diff --git a/g4f/Provider/LiteIcoding.py b/g4f/Provider/LiteIcoding.py deleted file mode 100644 index 69294a57..00000000 --- a/g4f/Provider/LiteIcoding.py +++ /dev/null @@ -1,113 +0,0 @@ -from __future__ import annotations - -from aiohttp import ClientSession, ClientResponseError -import re -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from .helper import format_prompt - - -class LiteIcoding(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://lite.icoding.ink" - api_endpoint = "/api/v1/gpt/message" - working = True - supports_gpt_4 = True - default_model = "gpt-4o" - models = [ - 'gpt-4o', - 'gpt-4-turbo', - 'claude-3', - 'claude-3.5', - 'gemini-1.5', - ] - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - headers = { - "Accept": "*/*", - "Accept-Language": "en-US,en;q=0.9", - "Authorization": "Bearer aa3020ee873e40cb8b3f515a0708ebc4", - "Connection": "keep-alive", - "Content-Type": "application/json;charset=utf-8", - "DNT": "1", - "Origin": cls.url, - "Referer": f"{cls.url}/", - "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/126.0.0.0 Safari/537.36" - ), - "sec-ch-ua": '"Not/A)Brand";v="8", "Chromium";v="126"', - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": '"Linux"', - } - - data = { - "model": model, - "chatId": "-1", - "messages": [ - { - "role": msg["role"], - "content": msg["content"], - "time": msg.get("time", ""), - "attachments": msg.get("attachments", []), - } - for msg in messages - ], - "plugins": [], - "systemPrompt": "", - "temperature": 0.5, - } - - async with ClientSession(headers=headers) as session: - try: - async with session.post( - f"{cls.url}{cls.api_endpoint}", json=data, proxy=proxy - ) as response: - response.raise_for_status() - buffer = "" - full_response = "" - def decode_content(data): - bytes_array = bytes([int(b, 16) ^ 255 for b in data.split()]) - return bytes_array.decode('utf-8') - async for chunk in response.content.iter_any(): - if chunk: - buffer += chunk.decode() - while "\n\n" in buffer: - part, buffer = buffer.split("\n\n", 1) - if part.startswith("data: "): - content = part[6:].strip() - if content and content != "[DONE]": - content = content.strip('"') - # Decoding each content block - decoded_content = decode_content(content) - full_response += decoded_content - full_response = ( - full_response.replace('""', '') # Handle double quotes - .replace('" "', ' ') # Handle space within quotes - .replace("\\n\\n", "\n\n") - .replace("\\n", "\n") - .replace('\\"', '"') - .strip() - ) - # Add filter to remove unwanted text - filtered_response = re.sub(r'\n---\n.*', '', full_response, flags=re.DOTALL) - # Remove extra quotes at the beginning and end - cleaned_response = filtered_response.strip().strip('"') - yield cleaned_response - - except ClientResponseError as e: - raise RuntimeError( - f"ClientResponseError {e.status}: {e.message}, url={e.request_info.url}, data={data}" - ) from e - - except Exception as e: - raise RuntimeError(f"Unexpected error: {str(e)}") from e diff --git a/g4f/Provider/Llama.py b/g4f/Provider/Llama.py deleted file mode 100644 index 235c0994..00000000 --- a/g4f/Provider/Llama.py +++ /dev/null @@ -1,91 +0,0 @@ -from __future__ import annotations - -from aiohttp import ClientSession - -from ..typing import AsyncResult, Messages -from ..requests.raise_for_status import raise_for_status -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin - - -class Llama(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://www.llama2.ai" - working = False - supports_message_history = True - default_model = "meta/meta-llama-3-70b-instruct" - models = [ - "meta/llama-2-7b-chat", - "meta/llama-2-13b-chat", - "meta/llama-2-70b-chat", - "meta/meta-llama-3-8b-instruct", - "meta/meta-llama-3-70b-instruct", - ] - model_aliases = { - "meta-llama/Meta-Llama-3-8B-Instruct": "meta/meta-llama-3-8b-instruct", - "meta-llama/Meta-Llama-3-70B-Instruct": "meta/meta-llama-3-70b-instruct", - "meta-llama/Llama-2-7b-chat-hf": "meta/llama-2-7b-chat", - "meta-llama/Llama-2-13b-chat-hf": "meta/llama-2-13b-chat", - "meta-llama/Llama-2-70b-chat-hf": "meta/llama-2-70b-chat", - } - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - system_message: str = "You are a helpful assistant.", - temperature: float = 0.75, - top_p: float = 0.9, - max_tokens: int = 8000, - **kwargs - ) -> AsyncResult: - headers = { - "User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/118.0", - "Accept": "*/*", - "Accept-Language": "de,en-US;q=0.7,en;q=0.3", - "Accept-Encoding": "gzip, deflate, br", - "Referer": f"{cls.url}/", - "Content-Type": "text/plain;charset=UTF-8", - "Origin": cls.url, - "Connection": "keep-alive", - "Sec-Fetch-Dest": "empty", - "Sec-Fetch-Mode": "cors", - "Sec-Fetch-Site": "same-origin", - "Pragma": "no-cache", - "Cache-Control": "no-cache", - "TE": "trailers" - } - async with ClientSession(headers=headers) as session: - system_messages = [message["content"] for message in messages if message["role"] == "system"] - if system_messages: - system_message = "\n".join(system_messages) - messages = [message for message in messages if message["role"] != "system"] - prompt = format_prompt(messages) - data = { - "prompt": prompt, - "model": cls.get_model(model), - "systemPrompt": system_message, - "temperature": temperature, - "topP": top_p, - "maxTokens": max_tokens, - "image": None - } - started = False - async with session.post(f"{cls.url}/api", json=data, proxy=proxy) as response: - await raise_for_status(response) - async for chunk in response.content.iter_any(): - if not chunk: - continue - if not started: - chunk = chunk.lstrip() - started = True - yield chunk.decode(errors="ignore") - -def format_prompt(messages: Messages): - messages = [ - f"[INST] {message['content']} [/INST]" - if message["role"] == "user" - else message["content"] - for message in messages - ] - return "\n".join(messages) + "\n" diff --git a/g4f/Provider/MagickPen.py b/g4f/Provider/MagickPen.py index eab70536..7f1751dd 100644 --- a/g4f/Provider/MagickPen.py +++ b/g4f/Provider/MagickPen.py @@ -1,72 +1,53 @@ from __future__ import annotations +from aiohttp import ClientSession +import hashlib import time import random -import hashlib import re -from aiohttp import ClientSession - +import json from ..typing import AsyncResult, Messages from .base_provider import AsyncGeneratorProvider, ProviderModelMixin from .helper import format_prompt class MagickPen(AsyncGeneratorProvider, ProviderModelMixin): url = "https://magickpen.com" - api_endpoint_free = "https://api.magickpen.com/chat/free" - api_endpoint_ask = "https://api.magickpen.com/ask" + api_endpoint = "https://api.magickpen.com/ask" working = True - supports_gpt_4 = True - supports_stream = False - - default_model = 'free' - models = ['free', 'ask'] + supports_stream = True + supports_system_message = True + supports_message_history = True - model_aliases = { - "gpt-4o-mini": "free", - "gpt-4o-mini": "ask", - } - - @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 + default_model = 'gpt-4o-mini' + models = ['gpt-4o-mini'] @classmethod - async def get_secrets(cls): - url = 'https://magickpen.com/_nuxt/02c76dc.js' + async def fetch_api_credentials(cls) -> tuple: + url = "https://magickpen.com/_nuxt/bf709a9ce19f14e18116.js" async with ClientSession() as session: async with session.get(url) as response: - if response.status == 200: - text = await response.text() - x_api_secret_match = re.search(r'"X-API-Secret":"([^"]+)"', text) - secret_match = re.search(r'secret:\s*"([^"]+)"', text) - - x_api_secret = x_api_secret_match.group(1) if x_api_secret_match else None - secret = secret_match.group(1) if secret_match else None - - # Generate timestamp and nonce dynamically - timestamp = str(int(time.time() * 1000)) - nonce = str(random.random()) - - # Generate signature - signature_parts = ["TGDBU9zCgM", timestamp, nonce] - signature_string = "".join(sorted(signature_parts)) - signature = hashlib.md5(signature_string.encode()).hexdigest() - - return { - 'X-API-Secret': x_api_secret, - 'signature': signature, - 'timestamp': timestamp, - 'nonce': nonce, - 'secret': secret - } - else: - print(f"Error while fetching the file: {response.status}") - return None + text = await response.text() + + pattern = r'"X-API-Secret":"(\w+)"' + match = re.search(pattern, text) + X_API_SECRET = match.group(1) if match else None + + timestamp = str(int(time.time() * 1000)) + nonce = str(random.random()) + + s = ["TGDBU9zCgM", timestamp, nonce] + s.sort() + signature_string = ''.join(s) + signature = hashlib.md5(signature_string.encode()).hexdigest() + + pattern = r'secret:"(\w+)"' + match = re.search(pattern, text) + secret = match.group(1) if match else None + + if X_API_SECRET and timestamp and nonce and secret: + return X_API_SECRET, signature, timestamp, nonce, secret + else: + raise Exception("Unable to extract all the necessary data from the JavaScript file.") @classmethod async def create_async_generator( @@ -77,54 +58,30 @@ class MagickPen(AsyncGeneratorProvider, ProviderModelMixin): **kwargs ) -> AsyncResult: model = cls.get_model(model) + X_API_SECRET, signature, timestamp, nonce, secret = await cls.fetch_api_credentials() - secrets = await cls.get_secrets() - if not secrets: - raise Exception("Failed to obtain necessary secrets") - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "en-US,en;q=0.9", - "cache-control": "no-cache", - "content-type": "application/json", - "nonce": secrets['nonce'], - "origin": "https://magickpen.com", - "pragma": "no-cache", - "priority": "u=1, i", - "referer": "https://magickpen.com/", - "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-site", - "secret": secrets['secret'], - "signature": secrets['signature'], - "timestamp": secrets['timestamp'], - "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36", - "x-api-secret": secrets['X-API-Secret'] + 'accept': 'application/json, text/plain, */*', + 'accept-language': 'en-US,en;q=0.9', + 'content-type': 'application/json', + 'nonce': nonce, + 'origin': cls.url, + 'referer': f"{cls.url}/", + 'secret': secret, + 'signature': signature, + 'timestamp': timestamp, + 'x-api-secret': X_API_SECRET, } async with ClientSession(headers=headers) as session: - if model == 'free': - data = { - "history": [{"role": "user", "content": format_prompt(messages)}] - } - async with session.post(cls.api_endpoint_free, json=data, proxy=proxy) as response: - response.raise_for_status() - result = await response.text() - yield result - - elif model == 'ask': - data = { - "query": format_prompt(messages), - "plan": "Pay as you go" - } - async with session.post(cls.api_endpoint_ask, json=data, proxy=proxy) as response: - response.raise_for_status() - async for chunk in response.content: - if chunk: - yield chunk.decode() - - else: - raise ValueError(f"Unknown model: {model}") + prompt = format_prompt(messages) + payload = { + 'query': prompt, + 'turnstileResponse': '', + 'action': 'verify' + } + async with session.post(cls.api_endpoint, json=payload, proxy=proxy) as response: + response.raise_for_status() + async for chunk in response.content: + if chunk: + yield chunk.decode() diff --git a/g4f/Provider/Nexra.py b/g4f/Provider/Nexra.py deleted file mode 100644 index e2c3e197..00000000 --- a/g4f/Provider/Nexra.py +++ /dev/null @@ -1,181 +0,0 @@ -from __future__ import annotations - -import json -import base64 -from aiohttp import ClientSession -from typing import AsyncGenerator - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from ..image import ImageResponse -from .helper import format_prompt - -class Nexra(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://nexra.aryahcr.cc" - api_endpoint_text = "https://nexra.aryahcr.cc/api/chat/gpt" - api_endpoint_image = "https://nexra.aryahcr.cc/api/image/complements" - working = True - supports_gpt_35_turbo = True - supports_gpt_4 = True - supports_stream = True - supports_system_message = True - supports_message_history = True - - default_model = 'gpt-3.5-turbo' - models = [ - # Text models - 'gpt-4', 'gpt-4-0613', 'gpt-4-32k', 'gpt-4-0314', 'gpt-4-32k-0314', - 'gpt-3.5-turbo', 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k-0613', 'gpt-3.5-turbo-0301', - 'gpt-3', 'text-davinci-003', 'text-davinci-002', 'code-davinci-002', - 'text-curie-001', 'text-babbage-001', 'text-ada-001', - 'davinci', 'curie', 'babbage', 'ada', 'babbage-002', 'davinci-002', - # Image models - 'dalle', 'dalle-mini', 'emi' - ] - - image_models = {"dalle", "dalle-mini", "emi"} - text_models = set(models) - image_models - - 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 - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncGenerator[str | ImageResponse, None]: - model = cls.get_model(model) - - if model in cls.image_models: - async for result in cls.create_image_async_generator(model, messages, proxy, **kwargs): - yield result - else: - async for result in cls.create_text_async_generator(model, messages, proxy, **kwargs): - yield result - - @classmethod - async def create_text_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncGenerator[str, None]: - headers = { - "Content-Type": "application/json", - } - async with ClientSession(headers=headers) as session: - data = { - "messages": messages, - "prompt": format_prompt(messages), - "model": model, - "markdown": False, - "stream": False, - } - async with session.post(cls.api_endpoint_text, json=data, proxy=proxy) as response: - response.raise_for_status() - result = await response.text() - json_result = json.loads(result) - yield json_result["gpt"] - - @classmethod - async def create_image_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncGenerator[ImageResponse | str, None]: - headers = { - "Content-Type": "application/json" - } - - prompt = messages[-1]['content'] if messages else "" - - data = { - "prompt": prompt, - "model": model - } - - async def process_response(response_text: str) -> ImageResponse | None: - json_start = response_text.find('{') - if json_start != -1: - json_data = response_text[json_start:] - try: - response_data = json.loads(json_data) - image_data = response_data.get('images', [])[0] - - if image_data.startswith('data:image/'): - return ImageResponse([image_data], "Generated image") - - try: - base64.b64decode(image_data) - data_uri = f"data:image/jpeg;base64,{image_data}" - return ImageResponse([data_uri], "Generated image") - except: - print("Invalid base64 data") - return None - except json.JSONDecodeError: - print("Failed to parse JSON.") - else: - print("No JSON data found in the response.") - return None - - async with ClientSession(headers=headers) as session: - async with session.post(cls.api_endpoint_image, json=data, proxy=proxy) as response: - response.raise_for_status() - response_text = await response.text() - - image_response = await process_response(response_text) - if image_response: - yield image_response - else: - yield "Failed to process image data." - - @classmethod - async def create_async( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> str: - async for response in cls.create_async_generator(model, messages, proxy, **kwargs): - if isinstance(response, ImageResponse): - return response.images[0] - return response diff --git a/g4f/Provider/Ollama.py b/g4f/Provider/Ollama.py index a44aaacd..f9116541 100644 --- a/g4f/Provider/Ollama.py +++ b/g4f/Provider/Ollama.py @@ -1,6 +1,7 @@ from __future__ import annotations import requests +import os from .needs_auth.Openai import Openai from ..typing import AsyncResult, Messages @@ -14,9 +15,11 @@ class Ollama(Openai): @classmethod def get_models(cls): if not cls.models: - url = 'http://127.0.0.1:11434/api/tags' + host = os.getenv("OLLAMA_HOST", "127.0.0.1") + port = os.getenv("OLLAMA_PORT", "11434") + url = f"http://{host}:{port}/api/tags" models = requests.get(url).json()["models"] - cls.models = [model['name'] for model in models] + cls.models = [model["name"] for model in models] cls.default_model = cls.models[0] return cls.models @@ -25,9 +28,13 @@ class Ollama(Openai): cls, model: str, messages: Messages, - api_base: str = "http://localhost:11434/v1", + api_base: str = None, **kwargs ) -> AsyncResult: + if not api_base: + host = os.getenv("OLLAMA_HOST", "localhost") + port = os.getenv("OLLAMA_PORT", "11434") + api_base: str = f"http://{host}:{port}/v1" return super().create_async_generator( model, messages, api_base=api_base, **kwargs )
\ No newline at end of file diff --git a/g4f/Provider/PerplexityLabs.py b/g4f/Provider/PerplexityLabs.py index 3656a39b..b776e96a 100644 --- a/g4f/Provider/PerplexityLabs.py +++ b/g4f/Provider/PerplexityLabs.py @@ -13,7 +13,7 @@ WS_URL = "wss://www.perplexity.ai/socket.io/" class PerplexityLabs(AsyncGeneratorProvider, ProviderModelMixin): url = "https://labs.perplexity.ai" working = True - default_model = "llama-3.1-8b-instruct" + default_model = "llama-3.1-70b-instruct" models = [ "llama-3.1-sonar-large-128k-online", "llama-3.1-sonar-small-128k-online", @@ -22,6 +22,15 @@ class PerplexityLabs(AsyncGeneratorProvider, ProviderModelMixin): "llama-3.1-8b-instruct", "llama-3.1-70b-instruct", ] + + model_aliases = { + "sonar-online": "llama-3.1-sonar-large-128k-online", + "sonar-online": "sonar-small-128k-online", + "sonar-chat": "llama-3.1-sonar-large-128k-chat", + "sonar-chat": "llama-3.1-sonar-small-128k-chat", + "llama-3.1-8b": "llama-3.1-8b-instruct", + "llama-3.1-70b": "llama-3.1-70b-instruct", + } @classmethod async def create_async_generator( diff --git a/g4f/Provider/Pi.py b/g4f/Provider/Pi.py index e03830f4..266647ba 100644 --- a/g4f/Provider/Pi.py +++ b/g4f/Provider/Pi.py @@ -22,6 +22,7 @@ class Pi(AbstractProvider): proxy: str = None, timeout: int = 180, conversation_id: str = None, + webdriver: WebDriver = None, **kwargs ) -> CreateResult: if cls._session is None: diff --git a/g4f/Provider/Pizzagpt.py b/g4f/Provider/Pizzagpt.py index 47cb135c..6513bd34 100644 --- a/g4f/Provider/Pizzagpt.py +++ b/g4f/Provider/Pizzagpt.py @@ -12,7 +12,6 @@ class Pizzagpt(AsyncGeneratorProvider, ProviderModelMixin): url = "https://www.pizzagpt.it" api_endpoint = "/api/chatx-completion" working = True - supports_gpt_4 = True default_model = 'gpt-4o-mini' @classmethod diff --git a/g4f/Provider/Prodia.py b/g4f/Provider/Prodia.py new file mode 100644 index 00000000..543a8b19 --- /dev/null +++ b/g4f/Provider/Prodia.py @@ -0,0 +1,150 @@ +from __future__ import annotations + +from aiohttp import ClientSession +import time +import asyncio + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from ..image import ImageResponse + +class Prodia(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://app.prodia.com" + api_endpoint = "https://api.prodia.com/generate" + working = True + + default_model = 'absolutereality_v181.safetensors [3d9d4d2b]' + image_models = [ + '3Guofeng3_v34.safetensors [50f420de]', + 'absolutereality_V16.safetensors [37db0fc3]', + default_model, + 'amIReal_V41.safetensors [0a8a2e61]', + 'analog-diffusion-1.0.ckpt [9ca13f02]', + 'aniverse_v30.safetensors [579e6f85]', + 'anythingv3_0-pruned.ckpt [2700c435]', + 'anything-v4.5-pruned.ckpt [65745d25]', + 'anythingV5_PrtRE.safetensors [893e49b9]', + 'AOM3A3_orangemixs.safetensors [9600da17]', + 'blazing_drive_v10g.safetensors [ca1c1eab]', + 'breakdomain_I2428.safetensors [43cc7d2f]', + 'breakdomain_M2150.safetensors [15f7afca]', + 'cetusMix_Version35.safetensors [de2f2560]', + 'childrensStories_v13D.safetensors [9dfaabcb]', + 'childrensStories_v1SemiReal.safetensors [a1c56dbb]', + 'childrensStories_v1ToonAnime.safetensors [2ec7b88b]', + 'Counterfeit_v30.safetensors [9e2a8f19]', + 'cuteyukimixAdorable_midchapter3.safetensors [04bdffe6]', + 'cyberrealistic_v33.safetensors [82b0d085]', + 'dalcefo_v4.safetensors [425952fe]', + 'deliberate_v2.safetensors [10ec4b29]', + 'deliberate_v3.safetensors [afd9d2d4]', + 'dreamlike-anime-1.0.safetensors [4520e090]', + 'dreamlike-diffusion-1.0.safetensors [5c9fd6e0]', + 'dreamlike-photoreal-2.0.safetensors [fdcf65e7]', + 'dreamshaper_6BakedVae.safetensors [114c8abb]', + 'dreamshaper_7.safetensors [5cf5ae06]', + 'dreamshaper_8.safetensors [9d40847d]', + 'edgeOfRealism_eorV20.safetensors [3ed5de15]', + 'EimisAnimeDiffusion_V1.ckpt [4f828a15]', + 'elldreths-vivid-mix.safetensors [342d9d26]', + 'epicphotogasm_xPlusPlus.safetensors [1a8f6d35]', + 'epicrealism_naturalSinRC1VAE.safetensors [90a4c676]', + 'epicrealism_pureEvolutionV3.safetensors [42c8440c]', + 'ICantBelieveItsNotPhotography_seco.safetensors [4e7a3dfd]', + 'indigoFurryMix_v75Hybrid.safetensors [91208cbb]', + 'juggernaut_aftermath.safetensors [5e20c455]', + 'lofi_v4.safetensors [ccc204d6]', + 'lyriel_v16.safetensors [68fceea2]', + 'majicmixRealistic_v4.safetensors [29d0de58]', + 'mechamix_v10.safetensors [ee685731]', + 'meinamix_meinaV9.safetensors [2ec66ab0]', + 'meinamix_meinaV11.safetensors [b56ce717]', + 'neverendingDream_v122.safetensors [f964ceeb]', + 'openjourney_V4.ckpt [ca2f377f]', + 'pastelMixStylizedAnime_pruned_fp16.safetensors [793a26e8]', + 'portraitplus_V1.0.safetensors [1400e684]', + 'protogenx34.safetensors [5896f8d5]', + 'Realistic_Vision_V1.4-pruned-fp16.safetensors [8d21810b]', + 'Realistic_Vision_V2.0.safetensors [79587710]', + 'Realistic_Vision_V4.0.safetensors [29a7afaa]', + 'Realistic_Vision_V5.0.safetensors [614d1063]', + 'Realistic_Vision_V5.1.safetensors [a0f13c83]', + 'redshift_diffusion-V10.safetensors [1400e684]', + 'revAnimated_v122.safetensors [3f4fefd9]', + 'rundiffusionFX25D_v10.safetensors [cd12b0ee]', + 'rundiffusionFX_v10.safetensors [cd4e694d]', + 'sdv1_4.ckpt [7460a6fa]', + 'v1-5-pruned-emaonly.safetensors [d7049739]', + 'v1-5-inpainting.safetensors [21c7ab71]', + 'shoninsBeautiful_v10.safetensors [25d8c546]', + 'theallys-mix-ii-churned.safetensors [5d9225a4]', + 'timeless-1.0.ckpt [7c4971d4]', + 'toonyou_beta6.safetensors [980f6b15]', + ] + models = [*image_models] + + @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 + 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", + "origin": cls.url, + "referer": f"{cls.url}/", + "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36" + } + + async with ClientSession(headers=headers) as session: + prompt = messages[-1]['content'] if messages else "" + + params = { + "new": "true", + "prompt": prompt, + "model": model, + "negative_prompt": kwargs.get("negative_prompt", ""), + "steps": kwargs.get("steps", 20), + "cfg": kwargs.get("cfg", 7), + "seed": kwargs.get("seed", int(time.time())), + "sampler": kwargs.get("sampler", "DPM++ 2M Karras"), + "aspect_ratio": kwargs.get("aspect_ratio", "square") + } + + async with session.get(cls.api_endpoint, params=params, proxy=proxy) as response: + response.raise_for_status() + job_data = await response.json() + job_id = job_data["job"] + + image_url = await cls._poll_job(session, job_id, proxy) + yield ImageResponse(image_url, alt=prompt) + + @classmethod + async def _poll_job(cls, session: ClientSession, job_id: str, proxy: str, max_attempts: int = 30, delay: int = 2) -> str: + for _ in range(max_attempts): + async with session.get(f"https://api.prodia.com/job/{job_id}", proxy=proxy) as response: + response.raise_for_status() + job_status = await response.json() + + if job_status["status"] == "succeeded": + return f"https://images.prodia.xyz/{job_id}.png" + elif job_status["status"] == "failed": + raise Exception("Image generation failed") + + await asyncio.sleep(delay) + + raise Exception("Timeout waiting for image generation") diff --git a/g4f/Provider/ReplicateHome.py b/g4f/Provider/ReplicateHome.py index c4e52ad6..7f443a7d 100644 --- a/g4f/Provider/ReplicateHome.py +++ b/g4f/Provider/ReplicateHome.py @@ -1,66 +1,60 @@ from __future__ import annotations -from typing import Generator, Optional, Dict, Any, Union, List -import random + +import json import asyncio -import base64 +from aiohttp import ClientSession, ContentTypeError -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin from ..typing import AsyncResult, Messages -from ..requests import StreamSession, raise_for_status -from ..errors import ResponseError +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt from ..image import ImageResponse class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin): url = "https://replicate.com" - parent = "Replicate" + api_endpoint = "https://homepage.replicate.com/api/prediction" working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + default_model = 'meta/meta-llama-3-70b-instruct' - models = [ - # Models for image generation - 'stability-ai/stable-diffusion-3', - 'bytedance/sdxl-lightning-4step', - 'playgroundai/playground-v2.5-1024px-aesthetic', - - # Models for image generation + + text_models = [ 'meta/meta-llama-3-70b-instruct', 'mistralai/mixtral-8x7b-instruct-v0.1', 'google-deepmind/gemma-2b-it', + 'yorickvp/llava-13b', ] - versions = { - # Model versions for generating images - 'stability-ai/stable-diffusion-3': [ - "527d2a6296facb8e47ba1eaf17f142c240c19a30894f437feee9b91cc29d8e4f" - ], - 'bytedance/sdxl-lightning-4step': [ - "5f24084160c9089501c1b3545d9be3c27883ae2239b6f412990e82d4a6210f8f" - ], - 'playgroundai/playground-v2.5-1024px-aesthetic': [ - "a45f82a1382bed5c7aeb861dac7c7d191b0fdf74d8d57c4a0e6ed7d4d0bf7d24" - ], - - # Model versions for text generation - 'meta/meta-llama-3-70b-instruct': [ - "dp-cf04fe09351e25db628e8b6181276547" - ], - 'mistralai/mixtral-8x7b-instruct-v0.1': [ - "dp-89e00f489d498885048e94f9809fbc76" - ], - 'google-deepmind/gemma-2b-it': [ - "dff94eaf770e1fc211e425a50b51baa8e4cac6c39ef074681f9e39d778773626" - ] - } - - image_models = {"stability-ai/stable-diffusion-3", "bytedance/sdxl-lightning-4step", "playgroundai/playground-v2.5-1024px-aesthetic"} - text_models = {"meta/meta-llama-3-70b-instruct", "mistralai/mixtral-8x7b-instruct-v0.1", "google-deepmind/gemma-2b-it"} + image_models = [ + 'black-forest-labs/flux-schnell', + 'stability-ai/stable-diffusion-3', + 'bytedance/sdxl-lightning-4step', + 'playgroundai/playground-v2.5-1024px-aesthetic', + ] + models = text_models + image_models + model_aliases = { + "flux-schnell": "black-forest-labs/flux-schnell", "sd-3": "stability-ai/stable-diffusion-3", "sdxl": "bytedance/sdxl-lightning-4step", "playground-v2.5": "playgroundai/playground-v2.5-1024px-aesthetic", "llama-3-70b": "meta/meta-llama-3-70b-instruct", "mixtral-8x7b": "mistralai/mixtral-8x7b-instruct-v0.1", "gemma-2b": "google-deepmind/gemma-2b-it", + "llava-13b": "yorickvp/llava-13b", + } + + model_versions = { + "meta/meta-llama-3-70b-instruct": "fbfb20b472b2f3bdd101412a9f70a0ed4fc0ced78a77ff00970ee7a2383c575d", + "mistralai/mixtral-8x7b-instruct-v0.1": "5d78bcd7a992c4b793465bcdcf551dc2ab9668d12bb7aa714557a21c1e77041c", + "google-deepmind/gemma-2b-it": "dff94eaf770e1fc211e425a50b51baa8e4cac6c39ef074681f9e39d778773626", + "yorickvp/llava-13b": "80537f9eead1a5bfa72d5ac6ea6414379be41d4d4f6679fd776e9535d1eb58bb", + 'black-forest-labs/flux-schnell': "f2ab8a5bfe79f02f0789a146cf5e73d2a4ff2684a98c2b303d1e1ff3814271db", + 'stability-ai/stable-diffusion-3': "527d2a6296facb8e47ba1eaf17f142c240c19a30894f437feee9b91cc29d8e4f", + 'bytedance/sdxl-lightning-4step': "5f24084160c9089501c1b3545d9be3c27883ae2239b6f412990e82d4a6210f8f", + 'playgroundai/playground-v2.5-1024px-aesthetic': "a45f82a1382bed5c7aeb861dac7c7d191b0fdf74d8d57c4a0e6ed7d4d0bf7d24", } @classmethod @@ -77,84 +71,73 @@ class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin): cls, model: str, messages: Messages, - **kwargs: Any - ) -> Generator[Union[str, ImageResponse], None, None]: - yield await cls.create_async(messages[-1]["content"], model, **kwargs) - - @classmethod - async def create_async( - cls, - prompt: str, - model: str, - api_key: Optional[str] = None, - proxy: Optional[str] = None, - timeout: int = 180, - version: Optional[str] = None, - extra_data: Dict[str, Any] = {}, - **kwargs: Any - ) -> Union[str, ImageResponse]: - model = cls.get_model(model) # Use the get_model method to resolve model name + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + headers = { - 'Accept-Encoding': 'gzip, deflate, br', - 'Accept-Language': 'en-US', - 'Connection': 'keep-alive', - 'Origin': cls.url, - 'Referer': f'{cls.url}/', - 'Sec-Fetch-Dest': 'empty', - 'Sec-Fetch-Mode': 'cors', - 'Sec-Fetch-Site': 'same-site', - 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36', - 'sec-ch-ua': '"Google Chrome";v="119", "Chromium";v="119", "Not?A_Brand";v="24"', - 'sec-ch-ua-mobile': '?0', - 'sec-ch-ua-platform': '"macOS"', + "accept": "*/*", + "accept-language": "en-US,en;q=0.9", + "cache-control": "no-cache", + "content-type": "application/json", + "origin": "https://replicate.com", + "pragma": "no-cache", + "priority": "u=1, i", + "referer": "https://replicate.com/", + "sec-ch-ua": '"Not;A=Brand";v="24", "Chromium";v="128"', + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": '"Linux"', + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-site", + "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36" } - - if version is None: - version = random.choice(cls.versions.get(model, [])) - if api_key is not None: - headers["Authorization"] = f"Bearer {api_key}" - - async with StreamSession( - proxies={"all": proxy}, - headers=headers, - timeout=timeout - ) as session: + + async with ClientSession(headers=headers) as session: + if model in cls.image_models: + prompt = messages[-1]['content'] if messages else "" + else: + prompt = format_prompt(messages) + data = { - "input": { - "prompt": prompt, - **extra_data - }, - "version": version + "model": model, + "version": cls.model_versions[model], + "input": {"prompt": prompt}, } - if api_key is None: - data["model"] = model - url = "https://homepage.replicate.com/api/prediction" - else: - url = "https://api.replicate.com/v1/predictions" - async with session.post(url, json=data) as response: - await raise_for_status(response) + + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() result = await response.json() - if "id" not in result: - raise ResponseError(f"Invalid response: {result}") + prediction_id = result['id'] + + poll_url = f"https://homepage.replicate.com/api/poll?id={prediction_id}" + max_attempts = 30 + delay = 5 + for _ in range(max_attempts): + async with session.get(poll_url, proxy=proxy) as response: + response.raise_for_status() + try: + result = await response.json() + except ContentTypeError: + text = await response.text() + try: + result = json.loads(text) + except json.JSONDecodeError: + raise ValueError(f"Unexpected response format: {text}") - while True: - if api_key is None: - url = f"https://homepage.replicate.com/api/poll?id={result['id']}" - else: - url = f"https://api.replicate.com/v1/predictions/{result['id']}" - async with session.get(url) as response: - await raise_for_status(response) - result = await response.json() - if "status" not in result: - raise ResponseError(f"Invalid response: {result}") - if result["status"] == "succeeded": - output = result['output'] - if model in cls.text_models: - return ''.join(output) if isinstance(output, list) else output - elif model in cls.image_models: - images: List[Any] = output - images = images[0] if len(images) == 1 else images - return ImageResponse(images, prompt) - elif result["status"] == "failed": - raise ResponseError(f"Prediction failed: {result}") - await asyncio.sleep(0.5) + if result['status'] == 'succeeded': + if model in cls.image_models: + image_url = result['output'][0] + yield ImageResponse(image_url, "Generated image") + return + else: + for chunk in result['output']: + yield chunk + break + elif result['status'] == 'failed': + raise Exception(f"Prediction failed: {result.get('error')}") + await asyncio.sleep(delay) + + if result['status'] != 'succeeded': + raise Exception("Prediction timed out") diff --git a/g4f/Provider/Rocks.py b/g4f/Provider/Rocks.py deleted file mode 100644 index f44e0060..00000000 --- a/g4f/Provider/Rocks.py +++ /dev/null @@ -1,70 +0,0 @@ -import asyncio -import json -from aiohttp import ClientSession -from ..typing import Messages, AsyncResult -from .base_provider import AsyncGeneratorProvider - -class Rocks(AsyncGeneratorProvider): - url = "https://api.airforce" - api_endpoint = "/chat/completions" - supports_message_history = True - supports_gpt_35_turbo = True - supports_gpt_4 = True - supports_stream = True - supports_system_message = True - working = True - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - payload = {"messages":messages,"model":model,"max_tokens":4096,"temperature":1,"top_p":1,"stream":True} - - headers = { - "Accept": "application/json", - "Accept-Encoding": "gzip, deflate, br, zstd", - "Accept-Language": "en-US,en;q=0.9", - "Authorization": "Bearer missing api key", - "Origin": "https://llmplayground.net", - "Referer": "https://llmplayground.net/", - "Sec-Fetch-Dest": "empty", - "Sec-Fetch-Mode": "cors", - "Sec-Fetch-Site": "same-origin", - "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36", - } - - async with ClientSession() as session: - async with session.post( - f"{cls.url}{cls.api_endpoint}", - json=payload, - proxy=proxy, - headers=headers - ) as response: - response.raise_for_status() - last_chunk_time = asyncio.get_event_loop().time() - - async for line in response.content: - current_time = asyncio.get_event_loop().time() - if current_time - last_chunk_time > 5: - return - - if line.startswith(b"\n"): - pass - elif "discord.com/invite/" in line.decode() or "discord.gg/" in line.decode(): - pass # trolled - elif line.startswith(b"data: "): - try: - line = json.loads(line[6:]) - except json.JSONDecodeError: - continue - chunk = line["choices"][0]["delta"].get("content") - if chunk: - yield chunk - last_chunk_time = current_time - else: - raise Exception(f"Unexpected line: {line}") - return
\ No newline at end of file diff --git a/g4f/Provider/RubiksAI.py b/g4f/Provider/RubiksAI.py new file mode 100644 index 00000000..7e76d558 --- /dev/null +++ b/g4f/Provider/RubiksAI.py @@ -0,0 +1,162 @@ +from __future__ import annotations + +import asyncio +import aiohttp +import random +import string +import json +from urllib.parse import urlencode + +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + + +class RubiksAI(AsyncGeneratorProvider, ProviderModelMixin): + label = "Rubiks AI" + url = "https://rubiks.ai" + api_endpoint = "https://rubiks.ai/search/api.php" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'llama-3.1-70b-versatile' + models = [default_model, 'gpt-4o-mini'] + + model_aliases = { + "llama-3.1-70b": "llama-3.1-70b-versatile", + } + + @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 + + @staticmethod + def generate_mid() -> str: + """ + Generates a 'mid' string following the pattern: + 6 characters - 4 characters - 4 characters - 4 characters - 12 characters + Example: 0r7v7b-quw4-kdy3-rvdu-ekief6xbuuq4 + """ + parts = [ + ''.join(random.choices(string.ascii_lowercase + string.digits, k=6)), + ''.join(random.choices(string.ascii_lowercase + string.digits, k=4)), + ''.join(random.choices(string.ascii_lowercase + string.digits, k=4)), + ''.join(random.choices(string.ascii_lowercase + string.digits, k=4)), + ''.join(random.choices(string.ascii_lowercase + string.digits, k=12)) + ] + return '-'.join(parts) + + @staticmethod + def create_referer(q: str, mid: str, model: str = '') -> str: + """ + Creates a Referer URL with dynamic q and mid values, using urlencode for safe parameter encoding. + """ + params = {'q': q, 'model': model, 'mid': mid} + encoded_params = urlencode(params) + return f'https://rubiks.ai/search/?{encoded_params}' + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + websearch: bool = False, + **kwargs + ) -> AsyncResult: + """ + Creates an asynchronous generator that sends requests to the Rubiks AI API and yields the response. + + Parameters: + - model (str): The model to use in the request. + - messages (Messages): The messages to send as a prompt. + - proxy (str, optional): Proxy URL, if needed. + - websearch (bool, optional): Indicates whether to include search sources in the response. Defaults to False. + """ + model = cls.get_model(model) + prompt = format_prompt(messages) + q_value = prompt + mid_value = cls.generate_mid() + referer = cls.create_referer(q=q_value, mid=mid_value, model=model) + + url = cls.api_endpoint + params = { + 'q': q_value, + 'model': model, + 'id': '', + 'mid': mid_value + } + + headers = { + 'Accept': 'text/event-stream', + 'Accept-Language': 'en-US,en;q=0.9', + 'Cache-Control': 'no-cache', + 'Connection': 'keep-alive', + 'Pragma': 'no-cache', + 'Referer': referer, + '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/129.0.0.0 Safari/537.36', + 'sec-ch-ua': '"Chromium";v="129", "Not=A?Brand";v="8"', + 'sec-ch-ua-mobile': '?0', + 'sec-ch-ua-platform': '"Linux"' + } + + try: + timeout = aiohttp.ClientTimeout(total=None) + async with ClientSession(timeout=timeout) as session: + async with session.get(url, headers=headers, params=params, proxy=proxy) as response: + if response.status != 200: + yield f"Request ended with status code {response.status}" + return + + assistant_text = '' + sources = [] + + async for line in response.content: + decoded_line = line.decode('utf-8').strip() + if not decoded_line.startswith('data: '): + continue + data = decoded_line[6:] + if data in ('[DONE]', '{"done": ""}'): + break + try: + json_data = json.loads(data) + except json.JSONDecodeError: + continue + + if 'url' in json_data and 'title' in json_data: + if websearch: + sources.append({'title': json_data['title'], 'url': json_data['url']}) + + elif 'choices' in json_data: + for choice in json_data['choices']: + delta = choice.get('delta', {}) + content = delta.get('content', '') + role = delta.get('role', '') + if role == 'assistant': + continue + assistant_text += content + + if websearch and sources: + sources_text = '\n'.join([f"{i+1}. [{s['title']}]: {s['url']}" for i, s in enumerate(sources)]) + assistant_text += f"\n\n**Source:**\n{sources_text}" + + yield assistant_text + + except asyncio.CancelledError: + yield "The request was cancelled." + except aiohttp.ClientError as e: + yield f"An error occurred during the request: {e}" + except Exception as e: + yield f"An unexpected error occurred: {e}" diff --git a/g4f/Provider/Snova.py b/g4f/Provider/Snova.py deleted file mode 100644 index 76dfac40..00000000 --- a/g4f/Provider/Snova.py +++ /dev/null @@ -1,133 +0,0 @@ -from __future__ import annotations - -import json -from typing import AsyncGenerator - -from aiohttp import ClientSession - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from .helper import format_prompt - - -class Snova(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://fast.snova.ai" - api_endpoint = "https://fast.snova.ai/api/completion" - working = True - supports_stream = True - supports_system_message = True - supports_message_history = True - - default_model = 'Meta-Llama-3.1-8B-Instruct' - models = [ - 'Meta-Llama-3.1-8B-Instruct', - 'Meta-Llama-3.1-70B-Instruct', - 'Meta-Llama-3.1-405B-Instruct', - 'Samba-CoE', - 'ignos/Mistral-T5-7B-v1', - 'v1olet/v1olet_merged_dpo_7B', - 'macadeliccc/WestLake-7B-v2-laser-truthy-dpo', - 'cookinai/DonutLM-v1', - ] - - model_aliases = { - "llama-3.1-8b": "Meta-Llama-3.1-8B-Instruct", - "llama-3.1-70b": "Meta-Llama-3.1-70B-Instruct", - "llama-3.1-405b": "Meta-Llama-3.1-405B-Instruct", - - "mistral-7b": "ignos/Mistral-T5-7B-v1", - - "samba-coe-v0.1": "Samba-CoE", - "v1olet-merged-7b": "v1olet/v1olet_merged_dpo_7B", - "westlake-7b-v2": "macadeliccc/WestLake-7B-v2-laser-truthy-dpo", - "donutlm-v1": "cookinai/DonutLM-v1", - } - - @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 - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncGenerator[str, None]: - model = cls.get_model(model) - - headers = { - "accept": "text/event-stream", - "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: - data = { - "body": { - "messages": [ - { - "role": "system", - "content": "You are a helpful assistant." - }, - { - "role": "user", - "content": format_prompt(messages), - "id": "1-id", - "ref": "1-ref", - "revision": 1, - "draft": False, - "status": "done", - "enableRealTimeChat": False, - "meta": None - } - ], - "max_tokens": 1000, - "stop": ["<|eot_id|>"], - "stream": True, - "stream_options": {"include_usage": True}, - "model": model - }, - "env_type": "tp16" - } - async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: - response.raise_for_status() - full_response = "" - async for line in response.content: - line = line.decode().strip() - if line.startswith("data: "): - data = line[6:] - if data == "[DONE]": - break - try: - json_data = json.loads(data) - choices = json_data.get("choices", []) - if choices: - delta = choices[0].get("delta", {}) - content = delta.get("content", "") - full_response += content - except json.JSONDecodeError: - continue - except Exception as e: - print(f"Error processing chunk: {e}") - print(f"Problematic data: {data}") - continue - - yield full_response.strip() 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) diff --git a/g4f/Provider/Upstage.py b/g4f/Provider/Upstage.py index e61a5af2..65409159 100644 --- a/g4f/Provider/Upstage.py +++ b/g4f/Provider/Upstage.py @@ -12,14 +12,15 @@ class Upstage(AsyncGeneratorProvider, ProviderModelMixin): url = "https://console.upstage.ai/playground/chat" api_endpoint = "https://ap-northeast-2.apistage.ai/v1/web/demo/chat/completions" working = True - default_model = 'upstage/solar-1-mini-chat' + default_model = 'solar-pro' models = [ 'upstage/solar-1-mini-chat', 'upstage/solar-1-mini-chat-ja', + 'solar-pro', ] model_aliases = { - "solar-1-mini": "upstage/solar-1-mini-chat", - "solar-1-mini": "upstage/solar-1-mini-chat-ja", + "solar-mini": "upstage/solar-1-mini-chat", + "solar-mini": "upstage/solar-1-mini-chat-ja", } @classmethod diff --git a/g4f/Provider/Vercel.py b/g4f/Provider/Vercel.py deleted file mode 100644 index bd918396..00000000 --- a/g4f/Provider/Vercel.py +++ /dev/null @@ -1,104 +0,0 @@ -from __future__ import annotations - -import json, base64, requests, random, os - -try: - import execjs - has_requirements = True -except ImportError: - has_requirements = False - -from ..typing import Messages, CreateResult -from .base_provider import AbstractProvider -from ..requests import raise_for_status -from ..errors import MissingRequirementsError - -class Vercel(AbstractProvider): - url = 'https://chat.vercel.ai' - working = True - supports_message_history = True - supports_system_message = True - supports_gpt_35_turbo = True - supports_stream = True - - @staticmethod - def create_completion( - model: str, - messages: Messages, - stream: bool, - proxy: str = None, - max_retries: int = 6, - **kwargs - ) -> CreateResult: - if not has_requirements: - raise MissingRequirementsError('Install "PyExecJS" package') - - headers = { - 'authority': 'chat.vercel.ai', - 'accept': '*/*', - 'accept-language': 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3', - 'cache-control': 'no-cache', - 'content-type': 'application/json', - 'custom-encoding': get_anti_bot_token(), - 'origin': 'https://chat.vercel.ai', - 'pragma': 'no-cache', - 'referer': 'https://chat.vercel.ai/', - 'sec-ch-ua': '"Chromium";v="122", "Not(A:Brand";v="24", "Google Chrome";v="122"', - 'sec-ch-ua-mobile': '?0', - 'sec-ch-ua-platform': '"macOS"', - 'sec-fetch-dest': 'empty', - 'sec-fetch-mode': 'cors', - 'sec-fetch-site': 'same-origin', - 'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36', - } - - json_data = { - 'messages': messages, - 'id' : f'{os.urandom(3).hex()}a', - } - response = None - for _ in range(max_retries): - response = requests.post('https://chat.vercel.ai/api/chat', - headers=headers, json=json_data, stream=True, proxies={"https": proxy}) - if not response.ok: - continue - for token in response.iter_content(chunk_size=None): - try: - yield token.decode(errors="ignore") - except UnicodeDecodeError: - pass - break - raise_for_status(response) - -def get_anti_bot_token() -> str: - headers = { - 'authority': 'sdk.vercel.ai', - 'accept': '*/*', - 'accept-language': 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3', - 'cache-control': 'no-cache', - 'pragma': 'no-cache', - 'referer': 'https://sdk.vercel.ai/', - 'sec-ch-ua': '"Google Chrome";v="117", "Not;A=Brand";v="8", "Chromium";v="117"', - 'sec-ch-ua-mobile': '?0', - 'sec-ch-ua-platform': '"macOS"', - 'sec-fetch-dest': 'empty', - 'sec-fetch-mode': 'cors', - 'sec-fetch-site': 'same-origin', - 'user-agent': f'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.{random.randint(99, 999)}.{random.randint(99, 999)} Safari/537.36', - } - - response = requests.get('https://chat.vercel.ai/openai.jpeg', - headers=headers).text - - raw_data = json.loads(base64.b64decode(response, - validate=True)) - - js_script = '''const globalThis={marker:"mark"};String.prototype.fontcolor=function(){return `<font>${this}</font>`}; - return (%s)(%s)''' % (raw_data['c'], raw_data['a']) - - sec_list = [execjs.compile(js_script).call('')[0], [], "sentinel"] - - raw_token = json.dumps({'r': sec_list, 't': raw_data['t']}, - separators = (",", ":")) - - return base64.b64encode(raw_token.encode('utf-8')).decode()
\ No newline at end of file diff --git a/g4f/Provider/You.py b/g4f/Provider/You.py index af8aab0e..02735038 100644 --- a/g4f/Provider/You.py +++ b/g4f/Provider/You.py @@ -17,8 +17,6 @@ class You(AsyncGeneratorProvider, ProviderModelMixin): label = "You.com" url = "https://you.com" working = True - supports_gpt_35_turbo = True - supports_gpt_4 = True default_model = "gpt-4o-mini" default_vision_model = "agent" image_models = ["dall-e"] diff --git a/g4f/Provider/__init__.py b/g4f/Provider/__init__.py index a9a815ea..1caf8aaf 100644 --- a/g4f/Provider/__init__.py +++ b/g4f/Provider/__init__.py @@ -5,61 +5,69 @@ from ..providers.retry_provider import RetryProvider, IterListProvider from ..providers.base_provider import AsyncProvider, AsyncGeneratorProvider from ..providers.create_images import CreateImagesProvider -from .deprecated import * -from .selenium import * -from .needs_auth import * +from .deprecated import * +from .selenium import * +from .needs_auth import * +from .gigachat import * +from .nexra import * + +from .Ai4Chat import Ai4Chat from .AI365VIP import AI365VIP +from .AIChatFree import AIChatFree +from .AIUncensored import AIUncensored from .Allyfy import Allyfy +from .AmigoChat import AmigoChat from .AiChatOnline import AiChatOnline from .AiChats import AiChats +from .AiMathGPT import AiMathGPT +from .Airforce import Airforce from .Aura import Aura from .Bing import Bing from .BingCreateImages import BingCreateImages -from .Binjie import Binjie -from .Bixin123 import Bixin123 from .Blackbox import Blackbox from .ChatGot import ChatGot +from .ChatGpt import ChatGpt from .Chatgpt4Online import Chatgpt4Online from .Chatgpt4o import Chatgpt4o +from .ChatGptEs import ChatGptEs from .ChatgptFree import ChatgptFree -from .CodeNews import CodeNews +from .ChatHub import ChatHub +from .ChatifyAI import ChatifyAI +from .Cloudflare import Cloudflare +from .DarkAI import DarkAI from .DDG import DDG from .DeepInfra import DeepInfra +from .DeepInfraChat import DeepInfraChat from .DeepInfraImage import DeepInfraImage +from .Editee import Editee from .FlowGpt import FlowGpt -from .FluxAirforce import FluxAirforce from .Free2GPT import Free2GPT from .FreeChatgpt import FreeChatgpt from .FreeGpt import FreeGpt from .FreeNetfly import FreeNetfly from .GeminiPro import GeminiPro -from .GigaChat import GigaChat -from .GptTalkRu import GptTalkRu +from .GizAI import GizAI +from .GPROChat import GPROChat from .HuggingChat import HuggingChat from .HuggingFace import HuggingFace from .Koala import Koala from .Liaobots import Liaobots -from .LiteIcoding import LiteIcoding -from .Llama import Llama from .Local import Local from .MagickPen import MagickPen from .MetaAI import MetaAI -from .MetaAIAccount import MetaAIAccount -from .Nexra import Nexra +#from .MetaAIAccount import MetaAIAccount from .Ollama import Ollama from .PerplexityLabs import PerplexityLabs from .Pi import Pi from .Pizzagpt import Pizzagpt +from .Prodia import Prodia from .Reka import Reka -from .Snova import Snova from .Replicate import Replicate from .ReplicateHome import ReplicateHome -from .Rocks import Rocks +from .RubiksAI import RubiksAI from .TeachAnything import TeachAnything -from .TwitterBio import TwitterBio from .Upstage import Upstage -from .Vercel import Vercel from .WhiteRabbitNeo import WhiteRabbitNeo from .You import You diff --git a/g4f/Provider/bing/conversation.py b/g4f/Provider/bing/conversation.py index a4195fa4..b5c237f9 100644 --- a/g4f/Provider/bing/conversation.py +++ b/g4f/Provider/bing/conversation.py @@ -33,9 +33,9 @@ async def create_conversation(session: StreamSession, headers: dict, tone: str) Conversation: An instance representing the created conversation. """ if tone == "Copilot": - url = "https://copilot.microsoft.com/turing/conversation/create?bundleVersion=1.1690.0" + url = "https://copilot.microsoft.com/turing/conversation/create?bundleVersion=1.1809.0" else: - url = "https://www.bing.com/turing/conversation/create?bundleVersion=1.1690.0" + url = "https://www.bing.com/turing/conversation/create?bundleVersion=1.1809.0" async with session.get(url, headers=headers) as response: if response.status == 404: raise RateLimitError("Response 404: Do less requests and reuse conversations") @@ -90,4 +90,4 @@ async def delete_conversation(session: StreamSession, conversation: Conversation response = await response.json() return response["result"]["value"] == "Success" except: - return False
\ No newline at end of file + return False diff --git a/g4f/Provider/GigaChat.py b/g4f/Provider/gigachat/GigaChat.py index 8ba07b43..b1b293e3 100644 --- a/g4f/Provider/GigaChat.py +++ b/g4f/Provider/gigachat/GigaChat.py @@ -9,10 +9,10 @@ import json from aiohttp import ClientSession, TCPConnector, BaseConnector from g4f.requests import raise_for_status -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from ..errors import MissingAuthError -from .helper import get_connector +from ...typing import AsyncResult, Messages +from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin +from ...errors import MissingAuthError +from ..helper import get_connector access_token = "" token_expires_at = 0 @@ -45,7 +45,7 @@ class GigaChat(AsyncGeneratorProvider, ProviderModelMixin): if not api_key: raise MissingAuthError('Missing "api_key"') - cafile = os.path.join(os.path.dirname(__file__), "gigachat_crt/russian_trusted_root_ca_pem.crt") + cafile = os.path.join(os.path.dirname(__file__), "russian_trusted_root_ca_pem.crt") ssl_context = ssl.create_default_context(cafile=cafile) if os.path.exists(cafile) else None if connector is None and ssl_context is not None: connector = TCPConnector(ssl_context=ssl_context) diff --git a/g4f/Provider/gigachat/__init__.py b/g4f/Provider/gigachat/__init__.py new file mode 100644 index 00000000..c9853742 --- /dev/null +++ b/g4f/Provider/gigachat/__init__.py @@ -0,0 +1,2 @@ +from .GigaChat import GigaChat + diff --git a/g4f/Provider/gigachat_crt/russian_trusted_root_ca_pem.crt b/g4f/Provider/gigachat/russian_trusted_root_ca_pem.crt index 4c143a21..4c143a21 100644 --- a/g4f/Provider/gigachat_crt/russian_trusted_root_ca_pem.crt +++ b/g4f/Provider/gigachat/russian_trusted_root_ca_pem.crt diff --git a/g4f/Provider/needs_auth/Gemini.py b/g4f/Provider/needs_auth/Gemini.py index eddd25fa..8d741476 100644 --- a/g4f/Provider/needs_auth/Gemini.py +++ b/g4f/Provider/needs_auth/Gemini.py @@ -54,6 +54,7 @@ class Gemini(AsyncGeneratorProvider): url = "https://gemini.google.com" needs_auth = True working = True + default_model = 'gemini' image_models = ["gemini"] default_vision_model = "gemini" _cookies: Cookies = None @@ -305,4 +306,4 @@ class Conversation(BaseConversation): ) -> None: self.conversation_id = conversation_id self.response_id = response_id - self.choice_id = choice_id
\ No newline at end of file + self.choice_id = choice_id diff --git a/g4f/Provider/needs_auth/Groq.py b/g4f/Provider/needs_auth/Groq.py index d11f6a82..027d98bf 100644 --- a/g4f/Provider/needs_auth/Groq.py +++ b/g4f/Provider/needs_auth/Groq.py @@ -8,7 +8,26 @@ class Groq(Openai): url = "https://console.groq.com/playground" working = True default_model = "mixtral-8x7b-32768" - models = ["mixtral-8x7b-32768", "llama2-70b-4096", "gemma-7b-it"] + models = [ + "distil-whisper-large-v3-en", + "gemma2-9b-it", + "gemma-7b-it", + "llama3-groq-70b-8192-tool-use-preview", + "llama3-groq-8b-8192-tool-use-preview", + "llama-3.1-70b-versatile", + "llama-3.1-8b-instant", + "llama-3.2-1b-preview", + "llama-3.2-3b-preview", + "llama-3.2-11b-vision-preview", + "llama-3.2-90b-vision-preview", + "llama-guard-3-8b", + "llava-v1.5-7b-4096-preview", + "llama3-70b-8192", + "llama3-8b-8192", + "mixtral-8x7b-32768", + "whisper-large-v3", + "whisper-large-v3-turbo", + ] model_aliases = {"mixtral-8x7b": "mixtral-8x7b-32768", "llama2-70b": "llama2-70b-4096"} @classmethod @@ -21,4 +40,4 @@ class Groq(Openai): ) -> AsyncResult: return super().create_async_generator( model, messages, api_base=api_base, **kwargs - )
\ No newline at end of file + ) diff --git a/g4f/Provider/needs_auth/OpenRouter.py b/g4f/Provider/needs_auth/OpenRouter.py index 7945784a..5e0bf336 100644 --- a/g4f/Provider/needs_auth/OpenRouter.py +++ b/g4f/Provider/needs_auth/OpenRouter.py @@ -8,7 +8,7 @@ from ...typing import AsyncResult, Messages class OpenRouter(Openai): label = "OpenRouter" url = "https://openrouter.ai" - working = True + working = False default_model = "mistralai/mistral-7b-instruct:free" @classmethod @@ -29,4 +29,4 @@ class OpenRouter(Openai): ) -> AsyncResult: return super().create_async_generator( model, messages, api_base=api_base, **kwargs - )
\ No newline at end of file + ) diff --git a/g4f/Provider/needs_auth/Openai.py b/g4f/Provider/needs_auth/Openai.py index a0740c47..382ebada 100644 --- a/g4f/Provider/needs_auth/Openai.py +++ b/g4f/Provider/needs_auth/Openai.py @@ -11,7 +11,7 @@ from ...image import to_data_uri class Openai(AsyncGeneratorProvider, ProviderModelMixin): label = "OpenAI API" - url = "https://openai.com" + url = "https://platform.openai.com" working = True needs_auth = True supports_message_history = True diff --git a/g4f/Provider/needs_auth/OpenaiChat.py b/g4f/Provider/needs_auth/OpenaiChat.py index 82462040..f02121e3 100644 --- a/g4f/Provider/needs_auth/OpenaiChat.py +++ b/g4f/Provider/needs_auth/OpenaiChat.py @@ -61,9 +61,11 @@ class OpenaiChat(AsyncGeneratorProvider, ProviderModelMixin): default_model = None default_vision_model = "gpt-4o" models = [ "auto", "gpt-4o-mini", "gpt-4o", "gpt-4", "gpt-4-gizmo"] + model_aliases = { - "gpt-4-turbo-preview": "gpt-4", - "dall-e": "gpt-4", + #"gpt-4-turbo": "gpt-4", + #"gpt-4": "gpt-4-gizmo", + #"dalle": "gpt-4", } _api_key: str = None _headers: dict = None diff --git a/g4f/Provider/needs_auth/PerplexityApi.py b/g4f/Provider/needs_auth/PerplexityApi.py index 35d8d9d6..3ee65b30 100644 --- a/g4f/Provider/needs_auth/PerplexityApi.py +++ b/g4f/Provider/needs_auth/PerplexityApi.py @@ -15,7 +15,6 @@ class PerplexityApi(Openai): "llama-3-sonar-large-32k-online", "llama-3-8b-instruct", "llama-3-70b-instruct", - "mixtral-8x7b-instruct" ] @classmethod @@ -28,4 +27,4 @@ class PerplexityApi(Openai): ) -> AsyncResult: return super().create_async_generator( model, messages, api_base=api_base, **kwargs - )
\ No newline at end of file + ) diff --git a/g4f/Provider/needs_auth/__init__.py b/g4f/Provider/needs_auth/__init__.py index b5463b71..0492645d 100644 --- a/g4f/Provider/needs_auth/__init__.py +++ b/g4f/Provider/needs_auth/__init__.py @@ -7,5 +7,5 @@ from .Poe import Poe from .Openai import Openai from .Groq import Groq from .OpenRouter import OpenRouter -from .OpenaiAccount import OpenaiAccount -from .PerplexityApi import PerplexityApi
\ No newline at end of file +#from .OpenaiAccount import OpenaiAccount +from .PerplexityApi import PerplexityApi diff --git a/g4f/Provider/nexra/NexraBing.py b/g4f/Provider/nexra/NexraBing.py new file mode 100644 index 00000000..28f0b117 --- /dev/null +++ b/g4f/Provider/nexra/NexraBing.py @@ -0,0 +1,93 @@ +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 NexraBing(AbstractProvider, ProviderModelMixin): + label = "Nexra Bing" + url = "https://nexra.aryahcr.cc/documentation/bing/en" + api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements" + working = True + supports_stream = True + + default_model = 'Balanced' + models = [default_model, 'Creative', 'Precise'] + + model_aliases = { + "gpt-4": "Balanced", + "gpt-4": "Creative", + "gpt-4": "Precise", + } + + @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, + stream: bool = False, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ], + "conversation_style": model, + "markdown": markdown, + "stream": stream, + "model": "Bing" + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=True) + + return cls.process_response(response) + + @classmethod + def process_response(cls, response): + if response.status_code != 200: + yield f"Error: {response.status_code}" + return + + full_message = "" + for chunk in response.iter_content(chunk_size=None): + if chunk: + messages = chunk.decode('utf-8').split('\x1e') + for message in messages: + try: + json_data = json.loads(message) + if json_data.get('finish', False): + return + current_message = json_data.get('message', '') + if current_message: + new_content = current_message[len(full_message):] + if new_content: + yield new_content + full_message = current_message + except json.JSONDecodeError: + continue + + if not full_message: + yield "No message received" diff --git a/g4f/Provider/nexra/NexraBlackbox.py b/g4f/Provider/nexra/NexraBlackbox.py new file mode 100644 index 00000000..be048fdd --- /dev/null +++ b/g4f/Provider/nexra/NexraBlackbox.py @@ -0,0 +1,100 @@ +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 NexraBlackbox(AbstractProvider, ProviderModelMixin): + label = "Nexra Blackbox" + url = "https://nexra.aryahcr.cc/documentation/blackbox/en" + api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements" + working = True + supports_stream = True + + default_model = "blackbox" + models = [default_model] + model_aliases = {"blackboxai": "blackbox",} + + @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, + stream: bool, + proxy: str = None, + markdown: bool = False, + websearch: bool = False, + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ], + "websearch": websearch, + "stream": stream, + "markdown": markdown, + "model": model + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream) + + if stream: + return cls.process_streaming_response(response) + else: + return cls.process_non_streaming_response(response) + + @classmethod + def process_non_streaming_response(cls, response): + if response.status_code == 200: + try: + full_response = "" + for line in response.iter_lines(decode_unicode=True): + if line: + data = json.loads(line) + if data.get('finish'): + break + message = data.get('message', '') + if message: + full_response = message + return full_response + except json.JSONDecodeError: + return "Error: Unable to decode JSON response" + else: + return f"Error: {response.status_code}" + + @classmethod + def process_streaming_response(cls, response): + previous_message = "" + for line in response.iter_lines(decode_unicode=True): + if line: + try: + data = json.loads(line) + if data.get('finish'): + break + message = data.get('message', '') + if message and message != previous_message: + yield message[len(previous_message):] + previous_message = message + except json.JSONDecodeError: + pass diff --git a/g4f/Provider/nexra/NexraChatGPT.py b/g4f/Provider/nexra/NexraChatGPT.py new file mode 100644 index 00000000..074a0363 --- /dev/null +++ b/g4f/Provider/nexra/NexraChatGPT.py @@ -0,0 +1,285 @@ +from __future__ import annotations + +import asyncio +import json +import requests +from typing import Any, Dict + +from ...typing import AsyncResult, Messages +from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin +from ..helper import format_prompt + + +class NexraChatGPT(AsyncGeneratorProvider, ProviderModelMixin): + label = "Nexra ChatGPT" + url = "https://nexra.aryahcr.cc/documentation/chatgpt/en" + api_endpoint_nexra_chatgpt = "https://nexra.aryahcr.cc/api/chat/gpt" + api_endpoint_nexra_chatgpt4o = "https://nexra.aryahcr.cc/api/chat/complements" + api_endpoint_nexra_chatgpt_v2 = "https://nexra.aryahcr.cc/api/chat/complements" + api_endpoint_nexra_gptweb = "https://nexra.aryahcr.cc/api/chat/gptweb" + working = True + supports_system_message = True + supports_message_history = True + supports_stream = True + + default_model = 'gpt-3.5-turbo' + nexra_chatgpt = [ + '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' + ] + nexra_chatgpt4o = ['gpt-4o'] + nexra_chatgptv2 = ['chatgpt'] + nexra_gptweb = ['gptweb'] + models = nexra_chatgpt + nexra_chatgpt4o + nexra_chatgptv2 + nexra_gptweb + + model_aliases = { + "gpt-4": "gpt-4-0613", + "gpt-4-32k": "gpt-4-32k-0314", + "gpt-3.5-turbo": "gpt-3.5-turbo-16k", + "gpt-3.5-turbo-0613": "gpt-3.5-turbo-16k-0613", + "gpt-3": "text-davinci-003", + "text-davinci-002": "code-davinci-002", + "text-curie-001": "text-babbage-001", + "text-ada-001": "davinci", + "curie": "babbage", + "ada": "babbage-002", + "davinci-002": "davinci-002", + "chatgpt": "chatgpt", + "gptweb": "gptweb" + } + + @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 + async def create_async_generator( + cls, + model: str, + messages: Messages, + stream: bool = False, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> AsyncResult: + if model in cls.nexra_chatgpt: + async for chunk in cls._create_async_generator_nexra_chatgpt(model, messages, proxy, **kwargs): + yield chunk + elif model in cls.nexra_chatgpt4o: + async for chunk in cls._create_async_generator_nexra_chatgpt4o(model, messages, stream, proxy, markdown, **kwargs): + yield chunk + elif model in cls.nexra_chatgptv2: + async for chunk in cls._create_async_generator_nexra_chatgpt_v2(model, messages, stream, proxy, markdown, **kwargs): + yield chunk + elif model in cls.nexra_gptweb: + async for chunk in cls._create_async_generator_nexra_gptweb(model, messages, proxy, **kwargs): + yield chunk + + @classmethod + async def _create_async_generator_nexra_chatgpt( + cls, + model: str, + messages: Messages, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "Content-Type": "application/json" + } + + prompt = format_prompt(messages) + data = { + "messages": messages, + "prompt": prompt, + "model": model, + "markdown": markdown + } + + loop = asyncio.get_event_loop() + try: + response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_chatgpt, data, headers, proxy) + filtered_response = cls._filter_response(response) + + for chunk in filtered_response: + yield chunk + except Exception as e: + print(f"Error during API request (nexra_chatgpt): {e}") + + @classmethod + async def _create_async_generator_nexra_chatgpt4o( + cls, + model: str, + messages: Messages, + stream: bool = False, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "Content-Type": "application/json" + } + + prompt = format_prompt(messages) + data = { + "messages": [ + { + "role": "user", + "content": prompt + } + ], + "stream": stream, + "markdown": markdown, + "model": model + } + + loop = asyncio.get_event_loop() + try: + response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_chatgpt4o, data, headers, proxy, stream) + + if stream: + async for chunk in cls._process_streaming_response(response): + yield chunk + else: + for chunk in cls._process_non_streaming_response(response): + yield chunk + except Exception as e: + print(f"Error during API request (nexra_chatgpt4o): {e}") + + @classmethod + async def _create_async_generator_nexra_chatgpt_v2( + cls, + model: str, + messages: Messages, + stream: bool = False, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "Content-Type": "application/json" + } + + prompt = format_prompt(messages) + data = { + "messages": [ + { + "role": "user", + "content": prompt + } + ], + "stream": stream, + "markdown": markdown, + "model": model + } + + loop = asyncio.get_event_loop() + try: + response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_chatgpt_v2, data, headers, proxy, stream) + + if stream: + async for chunk in cls._process_streaming_response(response): + yield chunk + else: + for chunk in cls._process_non_streaming_response(response): + yield chunk + except Exception as e: + print(f"Error during API request (nexra_chatgpt_v2): {e}") + + @classmethod + async def _create_async_generator_nexra_gptweb( + cls, + model: str, + messages: Messages, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "Content-Type": "application/json" + } + + prompt = format_prompt(messages) + data = { + "prompt": prompt, + "markdown": markdown, + } + + loop = asyncio.get_event_loop() + try: + response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_gptweb, data, headers, proxy) + + for chunk in response.iter_content(1024): + if chunk: + decoded_chunk = chunk.decode().lstrip('_') + try: + response_json = json.loads(decoded_chunk) + if response_json.get("status"): + yield response_json.get("gpt", "") + except json.JSONDecodeError: + continue + except Exception as e: + print(f"Error during API request (nexra_gptweb): {e}") + + @staticmethod + def _sync_post_request(url: str, data: Dict[str, Any], headers: Dict[str, str], proxy: str = None, stream: bool = False) -> requests.Response: + proxies = { + "http": proxy, + "https": proxy, + } if proxy else None + + try: + response = requests.post(url, json=data, headers=headers, proxies=proxies, stream=stream) + response.raise_for_status() + return response + except requests.RequestException as e: + print(f"Request failed: {e}") + raise + + @staticmethod + def _process_non_streaming_response(response: requests.Response) -> str: + if response.status_code == 200: + try: + content = response.text.lstrip(' ') + data = json.loads(content) + return data.get('message', '') + except json.JSONDecodeError: + return "Error: Unable to decode JSON response" + else: + return f"Error: {response.status_code}" + + @staticmethod + async def _process_streaming_response(response: requests.Response): + full_message = "" + for line in response.iter_lines(decode_unicode=True): + if line: + try: + line = line.lstrip(' ') + data = json.loads(line) + if data.get('finish'): + break + message = data.get('message', '') + if message: + yield message[len(full_message):] + full_message = message + except json.JSONDecodeError: + pass + + @staticmethod + def _filter_response(response: requests.Response) -> str: + response_json = response.json() + return response_json.get("gpt", "") diff --git a/g4f/Provider/nexra/NexraDallE.py b/g4f/Provider/nexra/NexraDallE.py new file mode 100644 index 00000000..f605c6d0 --- /dev/null +++ b/g4f/Provider/nexra/NexraDallE.py @@ -0,0 +1,63 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraDallE(AbstractProvider, ProviderModelMixin): + label = "Nexra DALL-E" + url = "https://nexra.aryahcr.cc/documentation/dall-e/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = "dalle" + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraDallE2.py b/g4f/Provider/nexra/NexraDallE2.py new file mode 100644 index 00000000..2a36b6e6 --- /dev/null +++ b/g4f/Provider/nexra/NexraDallE2.py @@ -0,0 +1,63 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraDallE2(AbstractProvider, ProviderModelMixin): + label = "Nexra DALL-E 2" + url = "https://nexra.aryahcr.cc/documentation/dall-e/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = "dalle2" + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraEmi.py b/g4f/Provider/nexra/NexraEmi.py new file mode 100644 index 00000000..c26becec --- /dev/null +++ b/g4f/Provider/nexra/NexraEmi.py @@ -0,0 +1,63 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraEmi(AbstractProvider, ProviderModelMixin): + label = "Nexra Emi" + url = "https://nexra.aryahcr.cc/documentation/emi/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = "emi" + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraFluxPro.py b/g4f/Provider/nexra/NexraFluxPro.py new file mode 100644 index 00000000..cfb26385 --- /dev/null +++ b/g4f/Provider/nexra/NexraFluxPro.py @@ -0,0 +1,70 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraFluxPro(AbstractProvider, ProviderModelMixin): + url = "https://nexra.aryahcr.cc/documentation/flux-pro/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = 'flux' + models = [default_model] + model_aliases = { + "flux-pro": "flux", + } + + @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, + response: str = "url", # base64 or url + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraGeminiPro.py b/g4f/Provider/nexra/NexraGeminiPro.py new file mode 100644 index 00000000..e4e6a8ec --- /dev/null +++ b/g4f/Provider/nexra/NexraGeminiPro.py @@ -0,0 +1,86 @@ +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 NexraGeminiPro(AbstractProvider, ProviderModelMixin): + label = "Nexra Gemini PRO" + url = "https://nexra.aryahcr.cc/documentation/gemini-pro/en" + api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements" + working = True + supports_stream = True + + default_model = 'gemini-pro' + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + stream: bool, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ], + "stream": stream, + "markdown": markdown, + "model": model + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream) + + if stream: + return cls.process_streaming_response(response) + else: + return cls.process_non_streaming_response(response) + + @classmethod + def process_non_streaming_response(cls, response): + if response.status_code == 200: + try: + content = response.text.lstrip(' ') + data = json.loads(content) + return data.get('message', '') + except json.JSONDecodeError: + return "Error: Unable to decode JSON response" + else: + return f"Error: {response.status_code}" + + @classmethod + def process_streaming_response(cls, response): + full_message = "" + for line in response.iter_lines(decode_unicode=True): + if line: + try: + line = line.lstrip(' ') + data = json.loads(line) + if data.get('finish'): + break + message = data.get('message', '') + if message: + yield message[len(full_message):] + full_message = message + except json.JSONDecodeError: + pass diff --git a/g4f/Provider/nexra/NexraMidjourney.py b/g4f/Provider/nexra/NexraMidjourney.py new file mode 100644 index 00000000..c427f8a0 --- /dev/null +++ b/g4f/Provider/nexra/NexraMidjourney.py @@ -0,0 +1,63 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraMidjourney(AbstractProvider, ProviderModelMixin): + label = "Nexra Midjourney" + url = "https://nexra.aryahcr.cc/documentation/midjourney/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = "midjourney" + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraProdiaAI.py b/g4f/Provider/nexra/NexraProdiaAI.py new file mode 100644 index 00000000..de997fce --- /dev/null +++ b/g4f/Provider/nexra/NexraProdiaAI.py @@ -0,0 +1,151 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraProdiaAI(AbstractProvider, ProviderModelMixin): + label = "Nexra Prodia AI" + url = "https://nexra.aryahcr.cc/documentation/prodia/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = 'absolutereality_v181.safetensors [3d9d4d2b]' + models = [ + '3Guofeng3_v34.safetensors [50f420de]', + 'absolutereality_V16.safetensors [37db0fc3]', + default_model, + 'amIReal_V41.safetensors [0a8a2e61]', + 'analog-diffusion-1.0.ckpt [9ca13f02]', + 'aniverse_v30.safetensors [579e6f85]', + 'anythingv3_0-pruned.ckpt [2700c435]', + 'anything-v4.5-pruned.ckpt [65745d25]', + 'anythingV5_PrtRE.safetensors [893e49b9]', + 'AOM3A3_orangemixs.safetensors [9600da17]', + 'blazing_drive_v10g.safetensors [ca1c1eab]', + 'breakdomain_I2428.safetensors [43cc7d2f]', + 'breakdomain_M2150.safetensors [15f7afca]', + 'cetusMix_Version35.safetensors [de2f2560]', + 'childrensStories_v13D.safetensors [9dfaabcb]', + 'childrensStories_v1SemiReal.safetensors [a1c56dbb]', + 'childrensStories_v1ToonAnime.safetensors [2ec7b88b]', + 'Counterfeit_v30.safetensors [9e2a8f19]', + 'cuteyukimixAdorable_midchapter3.safetensors [04bdffe6]', + 'cyberrealistic_v33.safetensors [82b0d085]', + 'dalcefo_v4.safetensors [425952fe]', + 'deliberate_v2.safetensors [10ec4b29]', + 'deliberate_v3.safetensors [afd9d2d4]', + 'dreamlike-anime-1.0.safetensors [4520e090]', + 'dreamlike-diffusion-1.0.safetensors [5c9fd6e0]', + 'dreamlike-photoreal-2.0.safetensors [fdcf65e7]', + 'dreamshaper_6BakedVae.safetensors [114c8abb]', + 'dreamshaper_7.safetensors [5cf5ae06]', + 'dreamshaper_8.safetensors [9d40847d]', + 'edgeOfRealism_eorV20.safetensors [3ed5de15]', + 'EimisAnimeDiffusion_V1.ckpt [4f828a15]', + 'elldreths-vivid-mix.safetensors [342d9d26]', + 'epicphotogasm_xPlusPlus.safetensors [1a8f6d35]', + 'epicrealism_naturalSinRC1VAE.safetensors [90a4c676]', + 'epicrealism_pureEvolutionV3.safetensors [42c8440c]', + 'ICantBelieveItsNotPhotography_seco.safetensors [4e7a3dfd]', + 'indigoFurryMix_v75Hybrid.safetensors [91208cbb]', + 'juggernaut_aftermath.safetensors [5e20c455]', + 'lofi_v4.safetensors [ccc204d6]', + 'lyriel_v16.safetensors [68fceea2]', + 'majicmixRealistic_v4.safetensors [29d0de58]', + 'mechamix_v10.safetensors [ee685731]', + 'meinamix_meinaV9.safetensors [2ec66ab0]', + 'meinamix_meinaV11.safetensors [b56ce717]', + 'neverendingDream_v122.safetensors [f964ceeb]', + 'openjourney_V4.ckpt [ca2f377f]', + 'pastelMixStylizedAnime_pruned_fp16.safetensors [793a26e8]', + 'portraitplus_V1.0.safetensors [1400e684]', + 'protogenx34.safetensors [5896f8d5]', + 'Realistic_Vision_V1.4-pruned-fp16.safetensors [8d21810b]', + 'Realistic_Vision_V2.0.safetensors [79587710]', + 'Realistic_Vision_V4.0.safetensors [29a7afaa]', + 'Realistic_Vision_V5.0.safetensors [614d1063]', + 'Realistic_Vision_V5.1.safetensors [a0f13c83]', + 'redshift_diffusion-V10.safetensors [1400e684]', + 'revAnimated_v122.safetensors [3f4fefd9]', + 'rundiffusionFX25D_v10.safetensors [cd12b0ee]', + 'rundiffusionFX_v10.safetensors [cd4e694d]', + 'sdv1_4.ckpt [7460a6fa]', + 'v1-5-pruned-emaonly.safetensors [d7049739]', + 'v1-5-inpainting.safetensors [21c7ab71]', + 'shoninsBeautiful_v10.safetensors [25d8c546]', + 'theallys-mix-ii-churned.safetensors [5d9225a4]', + 'timeless-1.0.ckpt [7c4971d4]', + 'toonyou_beta6.safetensors [980f6b15]', + ] + + model_aliases = {} + + @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 get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + steps: str = 25, # Min: 1, Max: 30 + cfg_scale: str = 7, # Min: 0, Max: 20 + sampler: str = "DPM++ 2M Karras", # Select from these: "Euler","Euler a","Heun","DPM++ 2M Karras","DPM++ SDE Karras","DDIM" + negative_prompt: str = "", # Indicates what the AI should not do + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": "prodia", + "response": response, + "data": { + "model": model, + "steps": steps, + "cfg_scale": cfg_scale, + "sampler": sampler, + "negative_prompt": negative_prompt + } + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') # Remove leading underscores + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraQwen.py b/g4f/Provider/nexra/NexraQwen.py new file mode 100644 index 00000000..7f944e44 --- /dev/null +++ b/g4f/Provider/nexra/NexraQwen.py @@ -0,0 +1,86 @@ +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 NexraQwen(AbstractProvider, ProviderModelMixin): + label = "Nexra Qwen" + url = "https://nexra.aryahcr.cc/documentation/qwen/en" + api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements" + working = True + supports_stream = True + + default_model = 'qwen' + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + stream: bool, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ], + "stream": stream, + "markdown": markdown, + "model": model + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream) + + if stream: + return cls.process_streaming_response(response) + else: + return cls.process_non_streaming_response(response) + + @classmethod + def process_non_streaming_response(cls, response): + if response.status_code == 200: + try: + content = response.text.lstrip(' ') + data = json.loads(content) + return data.get('message', '') + except json.JSONDecodeError: + return "Error: Unable to decode JSON response" + else: + return f"Error: {response.status_code}" + + @classmethod + def process_streaming_response(cls, response): + full_message = "" + for line in response.iter_lines(decode_unicode=True): + if line: + try: + line = line.lstrip(' ') + data = json.loads(line) + if data.get('finish'): + break + message = data.get('message', '') + if message is not None and message != full_message: + yield message[len(full_message):] + full_message = message + except json.JSONDecodeError: + pass diff --git a/g4f/Provider/nexra/NexraSD15.py b/g4f/Provider/nexra/NexraSD15.py new file mode 100644 index 00000000..860a132f --- /dev/null +++ b/g4f/Provider/nexra/NexraSD15.py @@ -0,0 +1,72 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraSD15(AbstractProvider, ProviderModelMixin): + label = "Nexra Stable Diffusion 1.5" + url = "https://nexra.aryahcr.cc/documentation/stable-diffusion/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = 'stablediffusion-1.5' + models = [default_model] + + model_aliases = { + "sd-1.5": "stablediffusion-1.5", + } + + @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, + response: str = "url", # base64 or url + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraSDLora.py b/g4f/Provider/nexra/NexraSDLora.py new file mode 100644 index 00000000..a12bff1a --- /dev/null +++ b/g4f/Provider/nexra/NexraSDLora.py @@ -0,0 +1,69 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraSDLora(AbstractProvider, ProviderModelMixin): + label = "Nexra Stable Diffusion Lora" + url = "https://nexra.aryahcr.cc/documentation/stable-diffusion/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = "sdxl-lora" + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + guidance: str = 0.3, # Min: 0, Max: 5 + steps: str = 2, # Min: 2, Max: 10 + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response, + "data": { + "guidance": guidance, + "steps": steps + } + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraSDTurbo.py b/g4f/Provider/nexra/NexraSDTurbo.py new file mode 100644 index 00000000..865b4522 --- /dev/null +++ b/g4f/Provider/nexra/NexraSDTurbo.py @@ -0,0 +1,69 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraSDTurbo(AbstractProvider, ProviderModelMixin): + label = "Nexra Stable Diffusion Turbo" + url = "https://nexra.aryahcr.cc/documentation/stable-diffusion/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = "sdxl-turbo" + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + strength: str = 0.7, # Min: 0, Max: 1 + steps: str = 2, # Min: 1, Max: 10 + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response, + "data": { + "strength": strength, + "steps": steps + } + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') # Remove the leading underscore + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/__init__.py b/g4f/Provider/nexra/__init__.py new file mode 100644 index 00000000..bebc1fb6 --- /dev/null +++ b/g4f/Provider/nexra/__init__.py @@ -0,0 +1,14 @@ +from .NexraBing import NexraBing +from .NexraBlackbox import NexraBlackbox +from .NexraChatGPT import NexraChatGPT +from .NexraDallE import NexraDallE +from .NexraDallE2 import NexraDallE2 +from .NexraEmi import NexraEmi +from .NexraFluxPro import NexraFluxPro +from .NexraGeminiPro import NexraGeminiPro +from .NexraMidjourney import NexraMidjourney +from .NexraProdiaAI import NexraProdiaAI +from .NexraQwen import NexraQwen +from .NexraSD15 import NexraSD15 +from .NexraSDLora import NexraSDLora +from .NexraSDTurbo import NexraSDTurbo diff --git a/g4f/Provider/openai/new.py b/g4f/Provider/openai/new.py new file mode 100644 index 00000000..f4d8e13d --- /dev/null +++ b/g4f/Provider/openai/new.py @@ -0,0 +1,730 @@ +import hashlib +import base64 +import random +import json +import time +import uuid + +from collections import OrderedDict, defaultdict +from typing import Any, Callable, Dict, List + +from datetime import ( + datetime, + timedelta, + timezone +) + +cores = [16, 24, 32] +screens = [3000, 4000, 6000] +maxAttempts = 500000 + +navigator_keys = [ + "registerProtocolHandler−function registerProtocolHandler() { [native code] }", + "storage−[object StorageManager]", + "locks−[object LockManager]", + "appCodeName−Mozilla", + "permissions−[object Permissions]", + "appVersion−5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "share−function share() { [native code] }", + "webdriver−false", + "managed−[object NavigatorManagedData]", + "canShare−function canShare() { [native code] }", + "vendor−Google Inc.", + "vendor−Google Inc.", + "mediaDevices−[object MediaDevices]", + "vibrate−function vibrate() { [native code] }", + "storageBuckets−[object StorageBucketManager]", + "mediaCapabilities−[object MediaCapabilities]", + "getGamepads−function getGamepads() { [native code] }", + "bluetooth−[object Bluetooth]", + "share−function share() { [native code] }", + "cookieEnabled−true", + "virtualKeyboard−[object VirtualKeyboard]", + "product−Gecko", + "mediaDevices−[object MediaDevices]", + "canShare−function canShare() { [native code] }", + "getGamepads−function getGamepads() { [native code] }", + "product−Gecko", + "xr−[object XRSystem]", + "clipboard−[object Clipboard]", + "storageBuckets−[object StorageBucketManager]", + "unregisterProtocolHandler−function unregisterProtocolHandler() { [native code] }", + "productSub−20030107", + "login−[object NavigatorLogin]", + "vendorSub−", + "login−[object NavigatorLogin]", + "userAgent−Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "getInstalledRelatedApps−function getInstalledRelatedApps() { [native code] }", + "userAgent−Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "mediaDevices−[object MediaDevices]", + "locks−[object LockManager]", + "webkitGetUserMedia−function webkitGetUserMedia() { [native code] }", + "vendor−Google Inc.", + "xr−[object XRSystem]", + "mediaDevices−[object MediaDevices]", + "virtualKeyboard−[object VirtualKeyboard]", + "userAgent−Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "virtualKeyboard−[object VirtualKeyboard]", + "appName−Netscape", + "storageBuckets−[object StorageBucketManager]", + "presentation−[object Presentation]", + "onLine−true", + "mimeTypes−[object MimeTypeArray]", + "credentials−[object CredentialsContainer]", + "presentation−[object Presentation]", + "getGamepads−function getGamepads() { [native code] }", + "vendorSub−", + "virtualKeyboard−[object VirtualKeyboard]", + "serviceWorker−[object ServiceWorkerContainer]", + "xr−[object XRSystem]", + "product−Gecko", + "keyboard−[object Keyboard]", + "gpu−[object GPU]", + "getInstalledRelatedApps−function getInstalledRelatedApps() { [native code] }", + "webkitPersistentStorage−[object DeprecatedStorageQuota]", + "doNotTrack", + "clearAppBadge−function clearAppBadge() { [native code] }", + "presentation−[object Presentation]", + "serial−[object Serial]", + "locks−[object LockManager]", + "requestMIDIAccess−function requestMIDIAccess() { [native code] }", + "locks−[object LockManager]", + "requestMediaKeySystemAccess−function requestMediaKeySystemAccess() { [native code] }", + "vendor−Google Inc.", + "pdfViewerEnabled−true", + "language−zh-CN", + "setAppBadge−function setAppBadge() { [native code] }", + "geolocation−[object Geolocation]", + "userAgentData−[object NavigatorUAData]", + "mediaCapabilities−[object MediaCapabilities]", + "requestMIDIAccess−function requestMIDIAccess() { [native code] }", + "getUserMedia−function getUserMedia() { [native code] }", + "mediaDevices−[object MediaDevices]", + "webkitPersistentStorage−[object DeprecatedStorageQuota]", + "userAgent−Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "sendBeacon−function sendBeacon() { [native code] }", + "hardwareConcurrency−32", + "appVersion−5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "credentials−[object CredentialsContainer]", + "storage−[object StorageManager]", + "cookieEnabled−true", + "pdfViewerEnabled−true", + "windowControlsOverlay−[object WindowControlsOverlay]", + "scheduling−[object Scheduling]", + "pdfViewerEnabled−true", + "hardwareConcurrency−32", + "xr−[object XRSystem]", + "userAgent−Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "webdriver−false", + "getInstalledRelatedApps−function getInstalledRelatedApps() { [native code] }", + "getInstalledRelatedApps−function getInstalledRelatedApps() { [native code] }", + "bluetooth−[object Bluetooth]" +] + +window_keys = [ + "0", + "window", + "self", + "document", + "name", + "location", + "customElements", + "history", + "navigation", + "locationbar", + "menubar", + "personalbar", + "scrollbars", + "statusbar", + "toolbar", + "status", + "closed", + "frames", + "length", + "top", + "opener", + "parent", + "frameElement", + "navigator", + "origin", + "external", + "screen", + "innerWidth", + "innerHeight", + "scrollX", + "pageXOffset", + "scrollY", + "pageYOffset", + "visualViewport", + "screenX", + "screenY", + "outerWidth", + "outerHeight", + "devicePixelRatio", + "clientInformation", + "screenLeft", + "screenTop", + "styleMedia", + "onsearch", + "isSecureContext", + "trustedTypes", + "performance", + "onappinstalled", + "onbeforeinstallprompt", + "crypto", + "indexedDB", + "sessionStorage", + "localStorage", + "onbeforexrselect", + "onabort", + "onbeforeinput", + "onbeforematch", + "onbeforetoggle", + "onblur", + "oncancel", + "oncanplay", + "oncanplaythrough", + "onchange", + "onclick", + "onclose", + "oncontentvisibilityautostatechange", + "oncontextlost", + "oncontextmenu", + "oncontextrestored", + "oncuechange", + "ondblclick", + "ondrag", + "ondragend", + "ondragenter", + "ondragleave", + "ondragover", + "ondragstart", + "ondrop", + "ondurationchange", + "onemptied", + "onended", + "onerror", + "onfocus", + "onformdata", + "oninput", + "oninvalid", + "onkeydown", + "onkeypress", + "onkeyup", + "onload", + "onloadeddata", + "onloadedmetadata", + "onloadstart", + "onmousedown", + "onmouseenter", + "onmouseleave", + "onmousemove", + "onmouseout", + "onmouseover", + "onmouseup", + "onmousewheel", + "onpause", + "onplay", + "onplaying", + "onprogress", + "onratechange", + "onreset", + "onresize", + "onscroll", + "onsecuritypolicyviolation", + "onseeked", + "onseeking", + "onselect", + "onslotchange", + "onstalled", + "onsubmit", + "onsuspend", + "ontimeupdate", + "ontoggle", + "onvolumechange", + "onwaiting", + "onwebkitanimationend", + "onwebkitanimationiteration", + "onwebkitanimationstart", + "onwebkittransitionend", + "onwheel", + "onauxclick", + "ongotpointercapture", + "onlostpointercapture", + "onpointerdown", + "onpointermove", + "onpointerrawupdate", + "onpointerup", + "onpointercancel", + "onpointerover", + "onpointerout", + "onpointerenter", + "onpointerleave", + "onselectstart", + "onselectionchange", + "onanimationend", + "onanimationiteration", + "onanimationstart", + "ontransitionrun", + "ontransitionstart", + "ontransitionend", + "ontransitioncancel", + "onafterprint", + "onbeforeprint", + "onbeforeunload", + "onhashchange", + "onlanguagechange", + "onmessage", + "onmessageerror", + "onoffline", + "ononline", + "onpagehide", + "onpageshow", + "onpopstate", + "onrejectionhandled", + "onstorage", + "onunhandledrejection", + "onunload", + "crossOriginIsolated", + "scheduler", + "alert", + "atob", + "blur", + "btoa", + "cancelAnimationFrame", + "cancelIdleCallback", + "captureEvents", + "clearInterval", + "clearTimeout", + "close", + "confirm", + "createImageBitmap", + "fetch", + "find", + "focus", + "getComputedStyle", + "getSelection", + "matchMedia", + "moveBy", + "moveTo", + "open", + "postMessage", + "print", + "prompt", + "queueMicrotask", + "releaseEvents", + "reportError", + "requestAnimationFrame", + "requestIdleCallback", + "resizeBy", + "resizeTo", + "scroll", + "scrollBy", + "scrollTo", + "setInterval", + "setTimeout", + "stop", + "structuredClone", + "webkitCancelAnimationFrame", + "webkitRequestAnimationFrame", + "chrome", + "g_opr", + "opr", + "ethereum", + "caches", + "cookieStore", + "ondevicemotion", + "ondeviceorientation", + "ondeviceorientationabsolute", + "launchQueue", + "documentPictureInPicture", + "getScreenDetails", + "queryLocalFonts", + "showDirectoryPicker", + "showOpenFilePicker", + "showSaveFilePicker", + "originAgentCluster", + "credentialless", + "speechSynthesis", + "onscrollend", + "webkitRequestFileSystem", + "webkitResolveLocalFileSystemURL", + "__remixContext", + "__oai_SSR_TTI", + "__remixManifest", + "__reactRouterVersion", + "DD_RUM", + "__REACT_INTL_CONTEXT__", + "filterCSS", + "filterXSS", + "__SEGMENT_INSPECTOR__", + "DD_LOGS", + "regeneratorRuntime", + "_g", + "__remixRouteModules", + "__remixRouter", + "__STATSIG_SDK__", + "__STATSIG_JS_SDK__", + "__STATSIG_RERENDER_OVERRIDE__", + "_oaiHandleSessionExpired" +] + +def get_parse_time(): + now = datetime.now(timezone(timedelta(hours=-5))) + return now.strftime("%a %b %d %Y %H:%M:%S") + " GMT+0200 (Central European Summer Time)" + +def get_config(user_agent): + + core = random.choice(cores) + screen = random.choice(screens) + + # partially hardcoded config + config = [ + core + screen, + get_parse_time(), + 4294705152, + random.random(), + user_agent, + None, + "remix-prod-15f1ec0f78ad898b9606a88d384ef76345b82b82", #document.documentElement.getAttribute("data-build"), + "en-US", + "en-US,es-US,en,es", + 0, + random.choice(navigator_keys), + 'location', + random.choice(window_keys), + time.perf_counter(), + str(uuid.uuid4()), + ] + + return config + + +def get_answer_token(seed, diff, config): + answer, solved = generate_answer(seed, diff, config) + + if solved: + return "gAAAAAB" + answer + else: + raise Exception("Failed to solve 'gAAAAAB' challenge") + +def generate_answer(seed, diff, config): + diff_len = len(diff) + seed_encoded = seed.encode() + p1 = (json.dumps(config[:3], separators=(',', ':'), ensure_ascii=False)[:-1] + ',').encode() + p2 = (',' + json.dumps(config[4:9], separators=(',', ':'), ensure_ascii=False)[1:-1] + ',').encode() + p3 = (',' + json.dumps(config[10:], separators=(',', ':'), ensure_ascii=False)[1:]).encode() + + target_diff = bytes.fromhex(diff) + + for i in range(maxAttempts): + d1 = str(i).encode() + d2 = str(i >> 1).encode() + + string = ( + p1 + + d1 + + p2 + + d2 + + p3 + ) + + base_encode = base64.b64encode(string) + hash_value = hashlib.new("sha3_512", seed_encoded + base_encode).digest() + + if hash_value[:diff_len] <= target_diff: + return base_encode.decode(), True + + return 'wQ8Lk5FbGpA2NcR9dShT6gYjU7VxZ4D' + base64.b64encode(f'"{seed}"'.encode()).decode(), False + +def get_requirements_token(config): + require, solved = generate_answer(format(random.random()), "0fffff", config) + + if solved: + return 'gAAAAAC' + require + else: + raise Exception("Failed to solve 'gAAAAAC' challenge") + + +### processing turnstile token + +class OrderedMap: + def __init__(self): + self.map = OrderedDict() + + def add(self, key: str, value: Any): + self.map[key] = value + + def to_json(self): + return json.dumps(self.map) + + def __str__(self): + return self.to_json() + + +TurnTokenList = List[List[Any]] +FloatMap = Dict[float, Any] +StringMap = Dict[str, Any] +FuncType = Callable[..., Any] + +start_time = time.time() + +def get_turnstile_token(dx: str, p: str) -> str: + decoded_bytes = base64.b64decode(dx) + # print(decoded_bytes.decode()) + return process_turnstile_token(decoded_bytes.decode(), p) + + +def process_turnstile_token(dx: str, p: str) -> str: + result = [] + p_length = len(p) + if p_length != 0: + for i, r in enumerate(dx): + result.append(chr(ord(r) ^ ord(p[i % p_length]))) + else: + result = list(dx) + return "".join(result) + + +def is_slice(input_val: Any) -> bool: + return isinstance(input_val, (list, tuple)) + + +def is_float(input_val: Any) -> bool: + return isinstance(input_val, float) + + +def is_string(input_val: Any) -> bool: + return isinstance(input_val, str) + + +def to_str(input_val: Any) -> str: + if input_val is None: + return "undefined" + elif is_float(input_val): + return f"{input_val:.16g}" + elif is_string(input_val): + special_cases = { + "window.Math": "[object Math]", + "window.Reflect": "[object Reflect]", + "window.performance": "[object Performance]", + "window.localStorage": "[object Storage]", + "window.Object": "function Object() { [native code] }", + "window.Reflect.set": "function set() { [native code] }", + "window.performance.now": "function () { [native code] }", + "window.Object.create": "function create() { [native code] }", + "window.Object.keys": "function keys() { [native code] }", + "window.Math.random": "function random() { [native code] }", + } + return special_cases.get(input_val, input_val) + elif isinstance(input_val, list) and all( + isinstance(item, str) for item in input_val + ): + return ",".join(input_val) + else: + # print(f"Type of input is: {type(input_val)}") + return str(input_val) + + +def get_func_map() -> FloatMap: + process_map: FloatMap = defaultdict(lambda: None) + + def func_1(e: float, t: float): + e_str = to_str(process_map[e]) + t_str = to_str(process_map[t]) + if e_str is not None and t_str is not None: + res = process_turnstile_token(e_str, t_str) + process_map[e] = res + else: + pass + # print(f"Warning: Unable to process func_1 for e={e}, t={t}") + + def func_2(e: float, t: Any): + process_map[e] = t + + def func_5(e: float, t: float): + n = process_map[e] + tres = process_map[t] + if n is None: + process_map[e] = tres + elif is_slice(n): + nt = n + [tres] if tres is not None else n + process_map[e] = nt + else: + if is_string(n) or is_string(tres): + res = to_str(n) + to_str(tres) + elif is_float(n) and is_float(tres): + res = n + tres + else: + res = "NaN" + process_map[e] = res + + def func_6(e: float, t: float, n: float): + tv = process_map[t] + nv = process_map[n] + if is_string(tv) and is_string(nv): + res = f"{tv}.{nv}" + if res == "window.document.location": + process_map[e] = "https://chatgpt.com/" + else: + process_map[e] = res + else: + pass + # print("func type 6 error") + + def func_24(e: float, t: float, n: float): + tv = process_map[t] + nv = process_map[n] + if is_string(tv) and is_string(nv): + process_map[e] = f"{tv}.{nv}" + else: + pass + # print("func type 24 error") + + def func_7(e: float, *args): + n = [process_map[arg] for arg in args] + ev = process_map[e] + if isinstance(ev, str): + if ev == "window.Reflect.set": + obj = n[0] + key_str = str(n[1]) + val = n[2] + obj.add(key_str, val) + elif callable(ev): + ev(*n) + + def func_17(e: float, t: float, *args): + i = [process_map[arg] for arg in args] + tv = process_map[t] + res = None + if isinstance(tv, str): + if tv == "window.performance.now": + current_time = time.time_ns() + elapsed_ns = current_time - int(start_time * 1e9) + res = (elapsed_ns + random.random()) / 1e6 + elif tv == "window.Object.create": + res = OrderedMap() + elif tv == "window.Object.keys": + if isinstance(i[0], str) and i[0] == "window.localStorage": + res = [ + "STATSIG_LOCAL_STORAGE_INTERNAL_STORE_V4", + "STATSIG_LOCAL_STORAGE_STABLE_ID", + "client-correlated-secret", + "oai/apps/capExpiresAt", + "oai-did", + "STATSIG_LOCAL_STORAGE_LOGGING_REQUEST", + "UiState.isNavigationCollapsed.1", + ] + elif tv == "window.Math.random": + res = random.random() + elif callable(tv): + res = tv(*i) + process_map[e] = res + + def func_8(e: float, t: float): + process_map[e] = process_map[t] + + def func_14(e: float, t: float): + tv = process_map[t] + if is_string(tv): + try: + token_list = json.loads(tv) + process_map[e] = token_list + except json.JSONDecodeError: + # print(f"Warning: Unable to parse JSON for key {t}") + process_map[e] = None + else: + # print(f"Warning: Value for key {t} is not a string") + process_map[e] = None + + def func_15(e: float, t: float): + tv = process_map[t] + process_map[e] = json.dumps(tv) + + def func_18(e: float): + ev = process_map[e] + e_str = to_str(ev) + decoded = base64.b64decode(e_str).decode() + process_map[e] = decoded + + def func_19(e: float): + ev = process_map[e] + e_str = to_str(ev) + encoded = base64.b64encode(e_str.encode()).decode() + process_map[e] = encoded + + def func_20(e: float, t: float, n: float, *args): + o = [process_map[arg] for arg in args] + ev = process_map[e] + tv = process_map[t] + if ev == tv: + nv = process_map[n] + if callable(nv): + nv(*o) + else: + pass + # print("func type 20 error") + + def func_21(*args): + pass + + def func_23(e: float, t: float, *args): + i = list(args) + ev = process_map[e] + tv = process_map[t] + if ev is not None and callable(tv): + tv(*i) + + process_map.update( + { + 1: func_1, + 2: func_2, + 5: func_5, + 6: func_6, + 7: func_7, + 8: func_8, + 10: "window", + 14: func_14, + 15: func_15, + 17: func_17, + 18: func_18, + 19: func_19, + 20: func_20, + 21: func_21, + 23: func_23, + 24: func_24, + } + ) + + return process_map + + +def process_turnstile(dx: str, p: str) -> str: + tokens = get_turnstile_token(dx, p) + res = "" + token_list = json.loads(tokens) + process_map = get_func_map() + + def func_3(e: str): + nonlocal res + res = base64.b64encode(e.encode()).decode() + + process_map[3] = func_3 + process_map[9] = token_list + process_map[16] = p + + for token in token_list: + try: + e = token[0] + t = token[1:] + f = process_map.get(e) + if callable(f): + f(*t) + else: + pass + # print(f"Warning: No function found for key {e}") + except Exception as exc: + raise Exception(f"Error processing token {token}: {exc}") + # print(f"Error processing token {token}: {exc}") + + return res
\ No newline at end of file diff --git a/g4f/Provider/selenium/AItianhuSpace.py b/g4f/Provider/selenium/AItianhuSpace.py deleted file mode 100644 index 4c438e3b..00000000 --- a/g4f/Provider/selenium/AItianhuSpace.py +++ /dev/null @@ -1,116 +0,0 @@ -from __future__ import annotations - -import time -import random - -from ...typing import CreateResult, Messages -from ..base_provider import AbstractProvider -from ..helper import format_prompt, get_random_string -from ...webdriver import WebDriver, WebDriverSession, element_send_text -from ... import debug - -class AItianhuSpace(AbstractProvider): - url = "https://chat3.aiyunos.top/" - working = True - supports_stream = True - supports_gpt_35_turbo = True - _domains = ["aitianhu.com", "aitianhu1.top"] - - @classmethod - def create_completion( - cls, - model: str, - messages: Messages, - stream: bool, - domain: str = None, - proxy: str = None, - timeout: int = 120, - webdriver: WebDriver = None, - headless: bool = True, - **kwargs - ) -> CreateResult: - if not model: - model = "gpt-3.5-turbo" - if not domain: - rand = get_random_string(6) - domain = random.choice(cls._domains) - domain = f"{rand}.{domain}" - if debug.logging: - print(f"AItianhuSpace | using domain: {domain}") - url = f"https://{domain}" - prompt = format_prompt(messages) - - with WebDriverSession(webdriver, "", headless=headless, proxy=proxy) as driver: - from selenium.webdriver.common.by import By - from selenium.webdriver.support.ui import WebDriverWait - from selenium.webdriver.support import expected_conditions as EC - - wait = WebDriverWait(driver, timeout) - - # Bypass devtools detection - driver.get("https://blank.page/") - wait.until(EC.visibility_of_element_located((By.ID, "sheet"))) - driver.execute_script(f""" - document.getElementById('sheet').addEventListener('click', () => {{ - window.open(arguments[0]); - }}); - """, url) - driver.find_element(By.ID, "sheet").click() - time.sleep(10) - - original_window = driver.current_window_handle - for window_handle in driver.window_handles: - if window_handle != original_window: - driver.close() - driver.switch_to.window(window_handle) - break - - # Wait for page load - wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "textarea.n-input__textarea-el"))) - - # Register hook in XMLHttpRequest - script = """ -const _http_request_open = XMLHttpRequest.prototype.open; -window._last_message = window._message = ""; -window._loadend = false; -XMLHttpRequest.prototype.open = function(method, url) { - if (url == "/api/chat-process") { - this.addEventListener("progress", (event) => { - const lines = this.responseText.split("\\n"); - try { - window._message = JSON.parse(lines[lines.length-1])["text"]; - } catch(e) { } - }); - this.addEventListener("loadend", (event) => { - window._loadend = true; - }); - } - return _http_request_open.call(this, method, url); -} -""" - driver.execute_script(script) - - # Submit prompt - element_send_text(driver.find_element(By.CSS_SELECTOR, "textarea.n-input__textarea-el"), prompt) - - # Read response - while True: - chunk = driver.execute_script(""" -if (window._message && window._message != window._last_message) { - try { - return window._message.substring(window._last_message.length); - } finally { - window._last_message = window._message; - } -} -if (window._loadend) { - return null; -} -return ""; -""") - if chunk: - yield chunk - elif chunk != "": - break - else: - time.sleep(0.1)
\ No newline at end of file diff --git a/g4f/Provider/selenium/Bard.py b/g4f/Provider/selenium/Bard.py deleted file mode 100644 index 9c809128..00000000 --- a/g4f/Provider/selenium/Bard.py +++ /dev/null @@ -1,80 +0,0 @@ -from __future__ import annotations - -import time -import os - -try: - from selenium.webdriver.common.by import By - from selenium.webdriver.support.ui import WebDriverWait - from selenium.webdriver.support import expected_conditions as EC -except ImportError: - pass - -from ...typing import CreateResult, Messages -from ..base_provider import AbstractProvider -from ..helper import format_prompt -from ...webdriver import WebDriver, WebDriverSession, element_send_text - - -class Bard(AbstractProvider): - url = "https://bard.google.com" - working = False - needs_auth = True - webdriver = True - - @classmethod - def create_completion( - cls, - model: str, - messages: Messages, - stream: bool, - proxy: str = None, - webdriver: WebDriver = None, - user_data_dir: str = None, - headless: bool = True, - **kwargs - ) -> CreateResult: - prompt = format_prompt(messages) - session = WebDriverSession(webdriver, user_data_dir, headless, proxy=proxy) - with session as driver: - try: - driver.get(f"{cls.url}/chat") - wait = WebDriverWait(driver, 10 if headless else 240) - wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "div.ql-editor.textarea"))) - except: - # Reopen browser for login - if not webdriver: - driver = session.reopen() - driver.get(f"{cls.url}/chat") - login_url = os.environ.get("G4F_LOGIN_URL") - if login_url: - yield f"Please login: [Google Bard]({login_url})\n\n" - wait = WebDriverWait(driver, 240) - wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "div.ql-editor.textarea"))) - else: - raise RuntimeError("Prompt textarea not found. You may not be logged in.") - - # Add hook in XMLHttpRequest - script = """ -const _http_request_open = XMLHttpRequest.prototype.open; -window._message = ""; -XMLHttpRequest.prototype.open = function(method, url) { - if (url.includes("/assistant.lamda.BardFrontendService/StreamGenerate")) { - this.addEventListener("load", (event) => { - window._message = JSON.parse(JSON.parse(this.responseText.split("\\n")[3])[0][2])[4][0][1][0]; - }); - } - return _http_request_open.call(this, method, url); -} -""" - driver.execute_script(script) - - element_send_text(driver.find_element(By.CSS_SELECTOR, "div.ql-editor.textarea"), prompt) - - while True: - chunk = driver.execute_script("return window._message;") - if chunk: - yield chunk - return - else: - time.sleep(0.1)
\ No newline at end of file diff --git a/g4f/Provider/selenium/MyShell.py b/g4f/Provider/selenium/MyShell.py index a3f246ff..02e182d4 100644 --- a/g4f/Provider/selenium/MyShell.py +++ b/g4f/Provider/selenium/MyShell.py @@ -9,7 +9,7 @@ from ...webdriver import WebDriver, WebDriverSession, bypass_cloudflare class MyShell(AbstractProvider): url = "https://app.myshell.ai/chat" - working = True + working = False supports_gpt_35_turbo = True supports_stream = True @@ -73,4 +73,4 @@ return content; elif chunk != "": break else: - time.sleep(0.1)
\ No newline at end of file + time.sleep(0.1) diff --git a/g4f/Provider/selenium/PerplexityAi.py b/g4f/Provider/selenium/PerplexityAi.py index 6b529d5b..d965dbf7 100644 --- a/g4f/Provider/selenium/PerplexityAi.py +++ b/g4f/Provider/selenium/PerplexityAi.py @@ -16,7 +16,7 @@ from ...webdriver import WebDriver, WebDriverSession, element_send_text class PerplexityAi(AbstractProvider): url = "https://www.perplexity.ai" - working = True + working = False supports_gpt_35_turbo = True supports_stream = True @@ -105,4 +105,4 @@ if(window._message && window._message != window._last_message) { elif chunk != "": break else: - time.sleep(0.1)
\ No newline at end of file + time.sleep(0.1) diff --git a/g4f/Provider/selenium/TalkAi.py b/g4f/Provider/selenium/TalkAi.py index 89280598..a7b63375 100644 --- a/g4f/Provider/selenium/TalkAi.py +++ b/g4f/Provider/selenium/TalkAi.py @@ -8,7 +8,7 @@ from ...webdriver import WebDriver, WebDriverSession class TalkAi(AbstractProvider): url = "https://talkai.info" - working = True + working = False supports_gpt_35_turbo = True supports_stream = True @@ -83,4 +83,4 @@ return content; elif chunk != "": break else: - time.sleep(0.1)
\ No newline at end of file + time.sleep(0.1) diff --git a/g4f/Provider/selenium/__init__.py b/g4f/Provider/selenium/__init__.py index 9a020460..3a59ea58 100644 --- a/g4f/Provider/selenium/__init__.py +++ b/g4f/Provider/selenium/__init__.py @@ -1,6 +1,4 @@ -from .AItianhuSpace import AItianhuSpace from .MyShell import MyShell from .PerplexityAi import PerplexityAi from .Phind import Phind from .TalkAi import TalkAi -from .Bard import Bard
\ No newline at end of file diff --git a/g4f/Provider/unfinished/AiChatting.py b/g4f/Provider/unfinished/AiChatting.py deleted file mode 100644 index f062fa98..00000000 --- a/g4f/Provider/unfinished/AiChatting.py +++ /dev/null @@ -1,66 +0,0 @@ -from __future__ import annotations - -from urllib.parse import unquote - -from ...typing import AsyncResult, Messages -from ..base_provider import AbstractProvider -from ...webdriver import WebDriver -from ...requests import Session, get_session_from_browser - -class AiChatting(AbstractProvider): - url = "https://www.aichatting.net" - supports_gpt_35_turbo = True - _session: Session = None - - @classmethod - def create_completion( - cls, - model: str, - messages: Messages, - stream: bool, - proxy: str = None, - timeout: int = 120, - webdriver: WebDriver = None, - **kwargs - ) -> AsyncResult: - if not cls._session: - cls._session = get_session_from_browser(cls.url, webdriver, proxy, timeout) - visitorId = unquote(cls._session.cookies.get("aichatting.website.visitorId")) - - headers = { - "accept": "application/json, text/plain, */*", - "lang": "en", - "source": "web" - } - data = { - "roleId": 0, - } - try: - response = cls._session.post("https://aga-api.aichatting.net/aigc/chat/record/conversation/create", json=data, headers=headers) - response.raise_for_status() - conversation_id = response.json()["data"]["conversationId"] - except Exception as e: - cls.reset() - raise e - headers = { - "authority": "aga-api.aichatting.net", - "accept": "text/event-stream,application/json, text/event-stream", - "lang": "en", - "source": "web", - "vtoken": visitorId, - } - data = { - "spaceHandle": True, - "roleId": 0, - "messages": messages, - "conversationId": conversation_id, - } - response = cls._session.post("https://aga-api.aichatting.net/aigc/chat/v2/stream", json=data, headers=headers, stream=True) - response.raise_for_status() - for chunk in response.iter_lines(): - if chunk.startswith(b"data:"): - yield chunk[5:].decode().replace("-=- --", " ").replace("-=-n--", "\n").replace("--@DONE@--", "") - - @classmethod - def reset(cls): - cls._session = None
\ No newline at end of file diff --git a/g4f/Provider/unfinished/ChatAiGpt.py b/g4f/Provider/unfinished/ChatAiGpt.py deleted file mode 100644 index bc962623..00000000 --- a/g4f/Provider/unfinished/ChatAiGpt.py +++ /dev/null @@ -1,68 +0,0 @@ -from __future__ import annotations - -import re -from aiohttp import ClientSession - -from ...typing import AsyncResult, Messages -from ..base_provider import AsyncGeneratorProvider -from ..helper import format_prompt - - -class ChatAiGpt(AsyncGeneratorProvider): - url = "https://chataigpt.org" - supports_gpt_35_turbo = True - _nonce = None - _post_id = None - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - headers = { - "User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/118.0", - "Accept": "*/*", - "Accept-Language": "de,en-US;q=0.7,en;q=0.3", - "Accept-Encoding": "gzip, deflate, br", - "Origin": cls.url, - "Alt-Used": cls.url, - "Connection": "keep-alive", - "Referer": cls.url, - "Pragma": "no-cache", - "Cache-Control": "no-cache", - "TE": "trailers", - "Sec-Fetch-Dest": "empty", - "Sec-Fetch-Mode": "cors", - "Sec-Fetch-Site": "same-origin", - } - async with ClientSession(headers=headers) as session: - if not cls._nonce: - async with session.get(f"{cls.url}/", proxy=proxy) as response: - response.raise_for_status() - response = await response.text() - - result = re.search( - r'data-nonce=(.*?) data-post-id=([0-9]+)', response - ) - - if result: - cls._nonce, cls._post_id = result.group(1), result.group(2) - else: - raise RuntimeError("No nonce found") - prompt = format_prompt(messages) - data = { - "_wpnonce": cls._nonce, - "post_id": cls._post_id, - "url": cls.url, - "action": "wpaicg_chat_shortcode_message", - "message": prompt, - "bot_id": 0 - } - async with session.post(f"{cls.url}/wp-admin/admin-ajax.php", data=data, proxy=proxy) as response: - response.raise_for_status() - async for chunk in response.content: - if chunk: - yield chunk.decode()
\ No newline at end of file diff --git a/g4f/Provider/unfinished/Komo.py b/g4f/Provider/unfinished/Komo.py deleted file mode 100644 index 84d8d634..00000000 --- a/g4f/Provider/unfinished/Komo.py +++ /dev/null @@ -1,44 +0,0 @@ -from __future__ import annotations - -import json - -from ...requests import StreamSession -from ...typing import AsyncGenerator -from ..base_provider import AsyncGeneratorProvider, format_prompt - -class Komo(AsyncGeneratorProvider): - url = "https://komo.ai/api/ask" - supports_gpt_35_turbo = True - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: list[dict[str, str]], - **kwargs - ) -> AsyncGenerator: - async with StreamSession(impersonate="chrome107") as session: - prompt = format_prompt(messages) - data = { - "query": prompt, - "FLAG_URLEXTRACT": "false", - "token": "", - "FLAG_MODELA": "1", - } - headers = { - 'authority': 'komo.ai', - 'accept': 'text/event-stream', - 'cache-control': 'no-cache', - 'referer': 'https://komo.ai/', - } - - async with session.get(cls.url, params=data, headers=headers) as response: - response.raise_for_status() - next = False - async for line in response.iter_lines(): - if line == b"event: line": - next = True - elif next and line.startswith(b"data: "): - yield json.loads(line[6:]) - next = False - diff --git a/g4f/Provider/unfinished/MikuChat.py b/g4f/Provider/unfinished/MikuChat.py deleted file mode 100644 index bf19631f..00000000 --- a/g4f/Provider/unfinished/MikuChat.py +++ /dev/null @@ -1,97 +0,0 @@ -from __future__ import annotations - -import random, json -from datetime import datetime -from ...requests import StreamSession - -from ...typing import AsyncGenerator -from ..base_provider import AsyncGeneratorProvider - - -class MikuChat(AsyncGeneratorProvider): - url = "https://ai.okmiku.com" - supports_gpt_35_turbo = True - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: list[dict[str, str]], - **kwargs - ) -> AsyncGenerator: - if not model: - model = "gpt-3.5-turbo" - headers = { - "authority": "api.catgpt.cc", - "accept": "application/json", - "origin": cls.url, - "referer": f"{cls.url}/chat/", - 'x-app-version': 'undefined', - 'x-date': get_datetime(), - 'x-fingerprint': get_fingerprint(), - 'x-platform': 'web' - } - async with StreamSession(headers=headers, impersonate="chrome107") as session: - data = { - "model": model, - "top_p": 0.8, - "temperature": 0.5, - "presence_penalty": 1, - "frequency_penalty": 0, - "max_tokens": 2000, - "stream": True, - "messages": messages, - } - async with session.post("https://api.catgpt.cc/ai/v1/chat/completions", json=data) as response: - print(await response.text()) - response.raise_for_status() - async for line in response.iter_lines(): - if line.startswith(b"data: "): - line = json.loads(line[6:]) - chunk = line["choices"][0]["delta"].get("content") - if chunk: - yield chunk - -def k(e: str, t: int): - a = len(e) & 3 - s = len(e) - a - i = t - c = 3432918353 - o = 461845907 - n = 0 - r = 0 - while n < s: - r = (ord(e[n]) & 255) | ((ord(e[n + 1]) & 255) << 8) | ((ord(e[n + 2]) & 255) << 16) | ((ord(e[n + 3]) & 255) << 24) - n += 4 - r = (r & 65535) * c + (((r >> 16) * c & 65535) << 16) & 4294967295 - r = (r << 15) | (r >> 17) - r = (r & 65535) * o + (((r >> 16) * o & 65535) << 16) & 4294967295 - i ^= r - i = (i << 13) | (i >> 19) - l = (i & 65535) * 5 + (((i >> 16) * 5 & 65535) << 16) & 4294967295 - i = (l & 65535) + 27492 + (((l >> 16) + 58964 & 65535) << 16) - - if a == 3: - r ^= (ord(e[n + 2]) & 255) << 16 - elif a == 2: - r ^= (ord(e[n + 1]) & 255) << 8 - elif a == 1: - r ^= ord(e[n]) & 255 - r = (r & 65535) * c + (((r >> 16) * c & 65535) << 16) & 4294967295 - r = (r << 15) | (r >> 17) - r = (r & 65535) * o + (((r >> 16) * o & 65535) << 16) & 4294967295 - i ^= r - - i ^= len(e) - i ^= i >> 16 - i = (i & 65535) * 2246822507 + (((i >> 16) * 2246822507 & 65535) << 16) & 4294967295 - i ^= i >> 13 - i = (i & 65535) * 3266489909 + (((i >> 16) * 3266489909 & 65535) << 16) & 4294967295 - i ^= i >> 16 - return i & 0xFFFFFFFF - -def get_fingerprint() -> str: - return str(k(str(int(random.random() * 100000)), 256)) - -def get_datetime() -> str: - return datetime.now().strftime("%Y-%m-%d %H:%M:%S")
\ No newline at end of file diff --git a/g4f/Provider/unfinished/__init__.py b/g4f/Provider/unfinished/__init__.py deleted file mode 100644 index eb5e8825..00000000 --- a/g4f/Provider/unfinished/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from .MikuChat import MikuChat -from .Komo import Komo -from .ChatAiGpt import ChatAiGpt -from .AiChatting import AiChatting
\ No newline at end of file diff --git a/g4f/__init__.py b/g4f/__init__.py index 017eb2e6..d77fe760 100644 --- a/g4f/__init__.py +++ b/g4f/__init__.py @@ -4,6 +4,7 @@ import os from . import debug, version from .models import Model +from .client import Client, AsyncClient from .typing import Messages, CreateResult, AsyncResult, Union from .errors import StreamNotSupportedError, ModelNotAllowedError from .cookies import get_cookies, set_cookies @@ -23,30 +24,6 @@ class ChatCompletion: ignore_stream: bool = False, patch_provider: callable = None, **kwargs) -> Union[CreateResult, str]: - """ - Creates a chat completion using the specified model, provider, and messages. - - Args: - model (Union[Model, str]): The model to use, either as an object or a string identifier. - messages (Messages): The messages for which the completion is to be created. - provider (Union[ProviderType, str, None], optional): The provider to use, either as an object, a string identifier, or None. - stream (bool, optional): Indicates if the operation should be performed as a stream. - auth (Union[str, None], optional): Authentication token or credentials, if required. - ignored (list[str], optional): List of provider names to be ignored. - ignore_working (bool, optional): If True, ignores the working status of the provider. - ignore_stream (bool, optional): If True, ignores the stream and authentication requirement checks. - patch_provider (callable, optional): Function to modify the provider. - **kwargs: Additional keyword arguments. - - Returns: - Union[CreateResult, str]: The result of the chat completion operation. - - Raises: - AuthenticationRequiredError: If authentication is required but not provided. - ProviderNotFoundError, ModelNotFoundError: If the specified provider or model is not found. - ProviderNotWorkingError: If the provider is not operational. - StreamNotSupportedError: If streaming is requested but not supported by the provider. - """ model, provider = get_model_and_provider( model, provider, stream, ignored, ignore_working, @@ -64,7 +41,8 @@ class ChatCompletion: if patch_provider: provider = patch_provider(provider) - result = provider.create_completion(model, messages, stream, **kwargs) + result = provider.create_completion(model, messages, stream=stream, **kwargs) + return result if stream else ''.join([str(chunk) for chunk in result]) @staticmethod @@ -76,24 +54,6 @@ class ChatCompletion: ignore_working: bool = False, patch_provider: callable = None, **kwargs) -> Union[AsyncResult, str]: - """ - Asynchronously creates a completion using the specified model and provider. - - Args: - model (Union[Model, str]): The model to use, either as an object or a string identifier. - messages (Messages): Messages to be processed. - provider (Union[ProviderType, str, None]): The provider to use, either as an object, a string identifier, or None. - stream (bool): Indicates if the operation should be performed as a stream. - ignored (list[str], optional): List of provider names to be ignored. - patch_provider (callable, optional): Function to modify the provider. - **kwargs: Additional keyword arguments. - - Returns: - Union[AsyncResult, str]: The result of the asynchronous chat completion operation. - - Raises: - StreamNotSupportedError: If streaming is requested but not supported by the provider. - """ model, provider = get_model_and_provider(model, provider, False, ignored, ignore_working) if stream: @@ -113,23 +73,6 @@ class Completion: provider : Union[ProviderType, None] = None, stream : bool = False, ignored : list[str] = None, **kwargs) -> Union[CreateResult, str]: - """ - Creates a completion based on the provided model, prompt, and provider. - - Args: - model (Union[Model, str]): The model to use, either as an object or a string identifier. - prompt (str): The prompt text for which the completion is to be created. - provider (Union[ProviderType, None], optional): The provider to use, either as an object or None. - stream (bool, optional): Indicates if the operation should be performed as a stream. - ignored (list[str], optional): List of provider names to be ignored. - **kwargs: Additional keyword arguments. - - Returns: - Union[CreateResult, str]: The result of the completion operation. - - Raises: - ModelNotAllowedError: If the specified model is not allowed for use with this method. - """ allowed_models = [ 'code-davinci-002', 'text-ada-001', @@ -143,6 +86,6 @@ class Completion: model, provider = get_model_and_provider(model, provider, stream, ignored) - result = provider.create_completion(model, [{"role": "user", "content": prompt}], stream, **kwargs) + result = provider.create_completion(model, [{"role": "user", "content": prompt}], stream=stream, **kwargs) - return result if stream else ''.join(result)
\ No newline at end of file + return result if stream else ''.join(result) diff --git a/g4f/api/__init__.py b/g4f/api/__init__.py index acb27e9c..754a48f1 100644 --- a/g4f/api/__init__.py +++ b/g4f/api/__init__.py @@ -12,30 +12,40 @@ from fastapi.security import APIKeyHeader from starlette.exceptions import HTTPException from starlette.status import HTTP_422_UNPROCESSABLE_ENTITY, HTTP_401_UNAUTHORIZED, HTTP_403_FORBIDDEN from fastapi.encoders import jsonable_encoder +from fastapi.middleware.cors import CORSMiddleware from pydantic import BaseModel -from typing import Union, Optional +from typing import Union, Optional, Iterator import g4f import g4f.debug -from g4f.client import AsyncClient +from g4f.client import Client, ChatCompletion, ChatCompletionChunk, ImagesResponse from g4f.typing import Messages from g4f.cookies import read_cookie_files -def create_app(): +def create_app(g4f_api_key: str = None): app = FastAPI() - api = Api(app) + + # Add CORS middleware + app.add_middleware( + CORSMiddleware, + allow_origin_regex=".*", + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], + ) + + api = Api(app, g4f_api_key=g4f_api_key) api.register_routes() api.register_authorization() api.register_validation_exception_handler() + + # Read cookie files if not ignored if not AppConfig.ignore_cookie_files: read_cookie_files() - return app -def create_app_debug(): - g4f.debug.logging = True - return create_app() + return app -class ChatCompletionsForm(BaseModel): +class ChatCompletionsConfig(BaseModel): messages: Messages model: str provider: Optional[str] = None @@ -47,16 +57,13 @@ class ChatCompletionsForm(BaseModel): web_search: Optional[bool] = None proxy: Optional[str] = None -class ImagesGenerateForm(BaseModel): - model: Optional[str] = None - provider: Optional[str] = None +class ImageGenerationConfig(BaseModel): prompt: str - response_format: Optional[str] = None - api_key: Optional[str] = None - proxy: Optional[str] = None + model: Optional[str] = None + response_format: str = "url" -class AppConfig(): - list_ignored_providers: Optional[list[str]] = None +class AppConfig: + ignored_providers: Optional[list[str]] = None g4f_api_key: Optional[str] = None ignore_cookie_files: bool = False defaults: dict = {} @@ -66,16 +73,23 @@ class AppConfig(): for key, value in data.items(): setattr(cls, key, value) +list_ignored_providers: list[str] = None + +def set_list_ignored_providers(ignored: list[str]): + global list_ignored_providers + list_ignored_providers = ignored + class Api: - def __init__(self, app: FastAPI) -> None: + def __init__(self, app: FastAPI, g4f_api_key=None) -> None: self.app = app - self.client = AsyncClient() + self.client = Client() + self.g4f_api_key = g4f_api_key self.get_g4f_api_key = APIKeyHeader(name="g4f-api-key") def register_authorization(self): @self.app.middleware("http") async def authorization(request: Request, call_next): - if AppConfig.g4f_api_key and request.url.path in ["/v1/chat/completions", "/v1/completions"]: + if self.g4f_api_key and request.url.path in ["/v1/chat/completions", "/v1/completions", "/v1/images/generate"]: try: user_g4f_api_key = await self.get_g4f_api_key(request) except HTTPException as e: @@ -84,22 +98,26 @@ class Api: status_code=HTTP_401_UNAUTHORIZED, content=jsonable_encoder({"detail": "G4F API key required"}), ) - if not secrets.compare_digest(AppConfig.g4f_api_key, user_g4f_api_key): + if not secrets.compare_digest(self.g4f_api_key, user_g4f_api_key): return JSONResponse( status_code=HTTP_403_FORBIDDEN, content=jsonable_encoder({"detail": "Invalid G4F API key"}), ) - return await call_next(request) + + response = await call_next(request) + return response def register_validation_exception_handler(self): @self.app.exception_handler(RequestValidationError) async def validation_exception_handler(request: Request, exc: RequestValidationError): details = exc.errors() - modified_details = [{ - "loc": error["loc"], - "message": error["msg"], - "type": error["type"], - } for error in details] + modified_details = [] + for error in details: + modified_details.append({ + "loc": error["loc"], + "message": error["msg"], + "type": error["type"], + }) return JSONResponse( status_code=HTTP_422_UNPROCESSABLE_ENTITY, content=jsonable_encoder({"detail": modified_details}), @@ -113,25 +131,23 @@ class Api: @self.app.get("/v1") async def read_root_v1(): return HTMLResponse('g4f API: Go to ' - '<a href="/v1/chat/completions">chat/completions</a> ' - 'or <a href="/v1/models">models</a>.') + '<a href="/v1/chat/completions">chat/completions</a>, ' + '<a href="/v1/models">models</a>, or ' + '<a href="/v1/images/generate">images/generate</a>.') @self.app.get("/v1/models") async def models(): - model_list = { - model: g4f.models.ModelUtils.convert[model] + model_list = dict( + (model, g4f.models.ModelUtils.convert[model]) for model in g4f.Model.__all__() - } + ) model_list = [{ 'id': model_id, 'object': 'model', 'created': 0, 'owned_by': model.base_provider } for model_id, model in model_list.items()] - return JSONResponse({ - "object": "list", - "data": model_list, - }) + return JSONResponse(model_list) @self.app.get("/v1/models/{model_name}") async def model_info(model_name: str): @@ -147,7 +163,7 @@ class Api: return JSONResponse({"error": "The model does not exist."}) @self.app.post("/v1/chat/completions") - async def chat_completions(config: ChatCompletionsForm, request: Request = None, provider: str = None): + async def chat_completions(config: ChatCompletionsConfig, request: Request = None, provider: str = None): try: config.provider = provider if config.provider is None else config.provider if config.api_key is None and request is not None: @@ -156,16 +172,27 @@ class Api: auth_header = auth_header.split(None, 1)[-1] if auth_header and auth_header != "Bearer": config.api_key = auth_header + + # Create the completion response response = self.client.chat.completions.create( **{ **AppConfig.defaults, **config.dict(exclude_none=True), }, - ignored=AppConfig.list_ignored_providers + ignored=AppConfig.ignored_providers ) + + # Check if the response is synchronous or asynchronous + if isinstance(response, ChatCompletion): + # Synchronous response + return JSONResponse(response.to_json()) + if not config.stream: - return JSONResponse((await response).to_json()) + # If the response is an iterator but not streaming, collect the result + response_list = list(response) if isinstance(response, Iterator) else [response] + return JSONResponse(response_list[0].to_json()) + # Streaming response async def streaming(): try: async for chunk in response: @@ -176,40 +203,38 @@ class Api: logging.exception(e) yield f'data: {format_exception(e, config)}\n\n' yield "data: [DONE]\n\n" + return StreamingResponse(streaming(), media_type="text/event-stream") except Exception as e: logging.exception(e) return Response(content=format_exception(e, config), status_code=500, media_type="application/json") - @self.app.post("/v1/completions") - async def completions(): - return Response(content=json.dumps({'info': 'Not working yet.'}, indent=4), media_type="application/json") - - @self.app.post("/v1/images/generations") - async def images_generate(config: ImagesGenerateForm, request: Request = None, provider: str = None): + @self.app.post("/v1/images/generate") + async def generate_image(config: ImageGenerationConfig): try: - config.provider = provider if config.provider is None else config.provider - if config.api_key is None and request is not None: - auth_header = request.headers.get("Authorization") - if auth_header is not None: - auth_header = auth_header.split(None, 1)[-1] - if auth_header and auth_header != "Bearer": - config.api_key = auth_header - response = self.client.images.generate( - **config.dict(exclude_none=True), + response: ImagesResponse = await self.client.images.async_generate( + prompt=config.prompt, + model=config.model, + response_format=config.response_format ) - return JSONResponse((await response).to_json()) + # Convert Image objects to dictionaries + response_data = [image.to_dict() for image in response.data] + return JSONResponse({"data": response_data}) except Exception as e: logging.exception(e) return Response(content=format_exception(e, config), status_code=500, media_type="application/json") -def format_exception(e: Exception, config: ChatCompletionsForm) -> str: + @self.app.post("/v1/completions") + async def completions(): + return Response(content=json.dumps({'info': 'Not working yet.'}, indent=4), media_type="application/json") + +def format_exception(e: Exception, config: Union[ChatCompletionsConfig, ImageGenerationConfig]) -> str: last_provider = g4f.get_last_provider(True) return json.dumps({ "error": {"message": f"{e.__class__.__name__}: {e}"}, - "model": last_provider.get("model") if last_provider else config.model, - "provider": last_provider.get("name") if last_provider else config.provider + "model": last_provider.get("model") if last_provider else getattr(config, 'model', None), + "provider": last_provider.get("name") if last_provider else getattr(config, 'provider', None) }) def run_api( @@ -218,18 +243,22 @@ def run_api( bind: str = None, debug: bool = False, workers: int = None, - use_colors: bool = None + use_colors: bool = None, + g4f_api_key: str = None ) -> None: print(f'Starting server... [g4f v-{g4f.version.utils.current_version}]' + (" (debug)" if debug else "")) if use_colors is None: use_colors = debug if bind is not None: host, port = bind.split(":") + if debug: + g4f.debug.logging = True uvicorn.run( - f"g4f.api:create_app{'_debug' if debug else ''}", - host=host, port=int(port), - workers=workers, - use_colors=use_colors, - factory=True, + "g4f.api:create_app", + host=host, + port=int(port), + workers=workers, + use_colors=use_colors, + factory=True, reload=debug - )
\ No newline at end of file + ) diff --git a/g4f/client/__init__.py b/g4f/client/__init__.py index 5bb4ba35..d1e7e298 100644 --- a/g4f/client/__init__.py +++ b/g4f/client/__init__.py @@ -1,3 +1,2 @@ from .stubs import ChatCompletion, ChatCompletionChunk, ImagesResponse -from .client import Client -from .async_client import AsyncClient
\ No newline at end of file +from .client import Client, AsyncClient diff --git a/g4f/client/async_client.py b/g4f/client/async_client.py deleted file mode 100644 index 2fe4640b..00000000 --- a/g4f/client/async_client.py +++ /dev/null @@ -1,275 +0,0 @@ -from __future__ import annotations - -import time -import random -import string -import asyncio -import base64 -from aiohttp import ClientSession, BaseConnector - -from .types import Client as BaseClient -from .types import ProviderType, FinishReason -from .stubs import ChatCompletion, ChatCompletionChunk, ImagesResponse, Image -from .types import AsyncIterResponse, ImageProvider -from .image_models import ImageModels -from .helper import filter_json, find_stop, filter_none, cast_iter_async -from .service import get_last_provider, get_model_and_provider -from ..Provider import ProviderUtils -from ..typing import Union, Messages, AsyncIterator, ImageType -from ..errors import NoImageResponseError, ProviderNotFoundError -from ..requests.aiohttp import get_connector -from ..providers.conversation import BaseConversation -from ..image import ImageResponse as ImageProviderResponse, ImageDataResponse - -try: - anext -except NameError: - async def anext(iter): - async for chunk in iter: - return chunk - -async def iter_response( - response: AsyncIterator[str], - stream: bool, - response_format: dict = None, - max_tokens: int = None, - stop: list = None -) -> AsyncIterResponse: - content = "" - finish_reason = None - completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28)) - count: int = 0 - async for chunk in response: - if isinstance(chunk, FinishReason): - finish_reason = chunk.reason - break - elif isinstance(chunk, BaseConversation): - yield chunk - continue - content += str(chunk) - count += 1 - if max_tokens is not None and count >= max_tokens: - finish_reason = "length" - first, content, chunk = find_stop(stop, content, chunk) - if first != -1: - finish_reason = "stop" - if stream: - yield ChatCompletionChunk(chunk, None, completion_id, int(time.time())) - if finish_reason is not None: - break - finish_reason = "stop" if finish_reason is None else finish_reason - if stream: - yield ChatCompletionChunk(None, finish_reason, completion_id, int(time.time())) - else: - if response_format is not None and "type" in response_format: - if response_format["type"] == "json_object": - content = filter_json(content) - yield ChatCompletion(content, finish_reason, completion_id, int(time.time())) - -async def iter_append_model_and_provider(response: AsyncIterResponse) -> AsyncIterResponse: - last_provider = None - async for chunk in response: - last_provider = get_last_provider(True) if last_provider is None else last_provider - chunk.model = last_provider.get("model") - chunk.provider = last_provider.get("name") - yield chunk - -class AsyncClient(BaseClient): - def __init__( - self, - provider: ProviderType = None, - image_provider: ImageProvider = None, - **kwargs - ): - super().__init__(**kwargs) - self.chat: Chat = Chat(self, provider) - self.images: Images = Images(self, image_provider) - -def create_response( - messages: Messages, - model: str, - provider: ProviderType = None, - stream: bool = False, - proxy: str = None, - max_tokens: int = None, - stop: list[str] = None, - api_key: str = None, - **kwargs -): - has_asnyc = hasattr(provider, "create_async_generator") - if has_asnyc: - create = provider.create_async_generator - else: - create = provider.create_completion - response = create( - model, messages, - stream=stream, - **filter_none( - proxy=proxy, - max_tokens=max_tokens, - stop=stop, - api_key=api_key - ), - **kwargs - ) - if not has_asnyc: - response = cast_iter_async(response) - return response - -class Completions(): - def __init__(self, client: AsyncClient, provider: ProviderType = None): - self.client: AsyncClient = client - self.provider: ProviderType = provider - - def create( - self, - messages: Messages, - model: str, - provider: ProviderType = None, - stream: bool = False, - proxy: str = None, - max_tokens: int = None, - stop: Union[list[str], str] = None, - api_key: str = None, - response_format: dict = None, - ignored : list[str] = None, - ignore_working: bool = False, - ignore_stream: bool = False, - **kwargs - ) -> Union[ChatCompletion, AsyncIterator[ChatCompletionChunk]]: - model, provider = get_model_and_provider( - model, - self.provider if provider is None else provider, - stream, - ignored, - ignore_working, - ignore_stream - ) - stop = [stop] if isinstance(stop, str) else stop - response = create_response( - messages, model, - provider, stream, - proxy=self.client.get_proxy() if proxy is None else proxy, - max_tokens=max_tokens, - stop=stop, - api_key=self.client.api_key if api_key is None else api_key, - **kwargs - ) - response = iter_response(response, stream, response_format, max_tokens, stop) - response = iter_append_model_and_provider(response) - return response if stream else anext(response) - -class Chat(): - completions: Completions - - def __init__(self, client: AsyncClient, provider: ProviderType = None): - self.completions = Completions(client, provider) - -async def iter_image_response( - response: AsyncIterator, - response_format: str = None, - connector: BaseConnector = None, - proxy: str = None -) -> Union[ImagesResponse, None]: - async for chunk in response: - if isinstance(chunk, ImageProviderResponse): - if response_format == "b64_json": - async with ClientSession( - connector=get_connector(connector, proxy), - cookies=chunk.options.get("cookies") - ) as session: - async def fetch_image(image): - async with session.get(image) as response: - return base64.b64encode(await response.content.read()).decode() - images = await asyncio.gather(*[fetch_image(image) for image in chunk.get_list()]) - return ImagesResponse([Image(None, image, chunk.alt) for image in images], int(time.time())) - return ImagesResponse([Image(image, None, chunk.alt) for image in chunk.get_list()], int(time.time())) - elif isinstance(chunk, ImageDataResponse): - return ImagesResponse([Image(None, image, chunk.alt) for image in chunk.get_list()], int(time.time())) - -def create_image(provider: ProviderType, prompt: str, model: str = "", **kwargs) -> AsyncIterator: - if isinstance(provider, type) and provider.__name__ == "You": - kwargs["chat_mode"] = "create" - else: - prompt = f"create a image with: {prompt}" - return provider.create_async_generator( - model, - [{"role": "user", "content": prompt}], - stream=True, - **kwargs - ) - -class Images(): - def __init__(self, client: AsyncClient, provider: ImageProvider = None): - self.client: AsyncClient = client - self.provider: ImageProvider = provider - self.models: ImageModels = ImageModels(client) - - def get_provider(self, model: str, provider: ProviderType = None): - if isinstance(provider, str): - if provider in ProviderUtils.convert: - provider = ProviderUtils.convert[provider] - else: - raise ProviderNotFoundError(f'Provider not found: {provider}') - else: - provider = self.models.get(model, self.provider) - return provider - - async def generate( - self, - prompt, - model: str = "", - provider: ProviderType = None, - response_format: str = None, - connector: BaseConnector = None, - proxy: str = None, - **kwargs - ) -> ImagesResponse: - provider = self.get_provider(model, provider) - if hasattr(provider, "create_async_generator"): - response = create_image( - provider, - prompt, - **filter_none( - response_format=response_format, - connector=connector, - proxy=self.client.get_proxy() if proxy is None else proxy, - ), - **kwargs - ) - else: - response = await provider.create_async(prompt) - return ImagesResponse([Image(image) for image in response.get_list()]) - image = await iter_image_response(response, response_format, connector, proxy) - if image is None: - raise NoImageResponseError() - return image - - async def create_variation( - self, - image: ImageType, - model: str = None, - response_format: str = None, - connector: BaseConnector = None, - proxy: str = None, - **kwargs - ): - provider = self.get_provider(model, provider) - result = None - if hasattr(provider, "create_async_generator"): - response = provider.create_async_generator( - "", - [{"role": "user", "content": "create a image like this"}], - stream=True, - image=image, - **filter_none( - response_format=response_format, - connector=connector, - proxy=self.client.get_proxy() if proxy is None else proxy, - ), - **kwargs - ) - result = iter_image_response(response, response_format, connector, proxy) - if result is None: - raise NoImageResponseError() - return result diff --git a/g4f/client/client.py b/g4f/client/client.py index 56644913..8e195213 100644 --- a/g4f/client/client.py +++ b/g4f/client/client.py @@ -4,12 +4,16 @@ import os import time import random import string -import logging +import threading import asyncio -from typing import Union +import base64 +import aiohttp +import queue +from typing import Union, AsyncIterator, Iterator + from ..providers.base_provider import AsyncGeneratorProvider from ..image import ImageResponse, to_image, to_data_uri -from ..typing import Union, Iterator, Messages, ImageType +from ..typing import Messages, ImageType from ..providers.types import BaseProvider, ProviderType, FinishReason from ..providers.conversation import BaseConversation from ..image import ImageResponse as ImageProviderResponse @@ -23,44 +27,83 @@ from .helper import find_stop, filter_json, filter_none from ..models import ModelUtils from ..Provider import IterListProvider +# Helper function to convert an async generator to a synchronous iterator +def to_sync_iter(async_gen: AsyncIterator) -> Iterator: + q = queue.Queue() + loop = asyncio.new_event_loop() + done = object() + + def _run(): + asyncio.set_event_loop(loop) + + async def iterate(): + try: + async for item in async_gen: + q.put(item) + finally: + q.put(done) + + loop.run_until_complete(iterate()) + loop.close() + + threading.Thread(target=_run).start() + while True: + item = q.get() + if item is done: + break + yield item + +# Helper function to convert a synchronous iterator to an async iterator +async def to_async_iterator(iterator): + for item in iterator: + yield item + +# Synchronous iter_response function def iter_response( - response: Iterator[str], + response: Union[Iterator[str], AsyncIterator[str]], stream: bool, response_format: dict = None, max_tokens: int = None, stop: list = None -) -> IterResponse: +) -> Iterator[Union[ChatCompletion, ChatCompletionChunk]]: content = "" finish_reason = None completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28)) - - for idx, chunk in enumerate(response): + idx = 0 + + if hasattr(response, '__aiter__'): + # It's an async iterator, wrap it into a sync iterator + response = to_sync_iter(response) + + for chunk in response: if isinstance(chunk, FinishReason): finish_reason = chunk.reason break elif isinstance(chunk, BaseConversation): yield chunk continue - + content += str(chunk) - + if max_tokens is not None and idx + 1 >= max_tokens: finish_reason = "length" - + first, content, chunk = find_stop(stop, content, chunk if stream else None) - + if first != -1: finish_reason = "stop" - + if stream: yield ChatCompletionChunk(chunk, None, completion_id, int(time.time())) - + if finish_reason is not None: break - + + idx += 1 + finish_reason = "stop" if finish_reason is None else finish_reason - + if stream: yield ChatCompletionChunk(None, finish_reason, completion_id, int(time.time())) else: @@ -69,16 +112,16 @@ def iter_response( content = filter_json(content) yield ChatCompletion(content, finish_reason, completion_id, int(time.time())) - -def iter_append_model_and_provider(response: IterResponse) -> IterResponse: +# Synchronous iter_append_model_and_provider function +def iter_append_model_and_provider(response: Iterator) -> Iterator: last_provider = None + for chunk in response: last_provider = get_last_provider(True) if last_provider is None else last_provider chunk.model = last_provider.get("model") chunk.provider = last_provider.get("name") yield chunk - class Client(BaseClient): def __init__( self, @@ -97,6 +140,28 @@ class Client(BaseClient): async def async_images(self) -> Images: return self._images +# For backwards compatibility and legacy purposes, use Client instead +class AsyncClient(Client): + """Legacy AsyncClient that redirects to the main Client class. + This class exists for backwards compatibility.""" + + def __init__(self, *args, **kwargs): + import warnings + warnings.warn( + "AsyncClient is deprecated and will be removed in a future version. " + "Use Client instead, which now supports both sync and async operations.", + DeprecationWarning, + stacklevel=2 + ) + super().__init__(*args, **kwargs) + + async def chat_complete(self, *args, **kwargs): + """Legacy method that redirects to async_create""" + return await self.chat.completions.async_create(*args, **kwargs) + + async def create_image(self, *args, **kwargs): + """Legacy method that redirects to async_generate""" + return await self.images.async_generate(*args, **kwargs) class Completions: def __init__(self, client: Client, provider: ProviderType = None): @@ -129,25 +194,115 @@ class Completions: ) stop = [stop] if isinstance(stop, str) else stop - - response = provider.create_completion( + + if asyncio.iscoroutinefunction(provider.create_completion): + # Run the asynchronous function in an event loop + response = asyncio.run(provider.create_completion( + model, + messages, + stream=stream, + **filter_none( + proxy=self.client.get_proxy() if proxy is None else proxy, + max_tokens=max_tokens, + stop=stop, + api_key=self.client.api_key if api_key is None else api_key + ), + **kwargs + )) + else: + response = provider.create_completion( + model, + messages, + stream=stream, + **filter_none( + proxy=self.client.get_proxy() if proxy is None else proxy, + max_tokens=max_tokens, + stop=stop, + api_key=self.client.api_key if api_key is None else api_key + ), + **kwargs + ) + + if stream: + if hasattr(response, '__aiter__'): + # It's an async generator, wrap it into a sync iterator + response = to_sync_iter(response) + + # Now 'response' is an iterator + response = iter_response(response, stream, response_format, max_tokens, stop) + response = iter_append_model_and_provider(response) + return response + else: + if hasattr(response, '__aiter__'): + # If response is an async generator, collect it into a list + response = list(to_sync_iter(response)) + response = iter_response(response, stream, response_format, max_tokens, stop) + response = iter_append_model_and_provider(response) + return next(response) + + async def async_create( + self, + messages: Messages, + model: str, + provider: ProviderType = None, + stream: bool = False, + proxy: str = None, + response_format: dict = None, + max_tokens: int = None, + stop: Union[list[str], str] = None, + api_key: str = None, + ignored: list[str] = None, + ignore_working: bool = False, + ignore_stream: bool = False, + **kwargs + ) -> Union[ChatCompletion, AsyncIterator[ChatCompletionChunk]]: + model, provider = get_model_and_provider( model, - messages, - stream=stream, - **filter_none( - proxy=self.client.get_proxy() if proxy is None else proxy, - max_tokens=max_tokens, - stop=stop, - api_key=self.client.api_key if api_key is None else api_key - ), - **kwargs + self.provider if provider is None else provider, + stream, + ignored, + ignore_working, + ignore_stream, ) - - response = iter_response(response, stream, response_format, max_tokens, stop) - response = iter_append_model_and_provider(response) - - return response if stream else next(response) + stop = [stop] if isinstance(stop, str) else stop + + if asyncio.iscoroutinefunction(provider.create_completion): + response = await provider.create_completion( + model, + messages, + stream=stream, + **filter_none( + proxy=self.client.get_proxy() if proxy is None else proxy, + max_tokens=max_tokens, + stop=stop, + api_key=self.client.api_key if api_key is None else api_key + ), + **kwargs + ) + else: + response = provider.create_completion( + model, + messages, + stream=stream, + **filter_none( + proxy=self.client.get_proxy() if proxy is None else proxy, + max_tokens=max_tokens, + stop=stop, + api_key=self.client.api_key if api_key is None else api_key + ), + **kwargs + ) + + # Removed 'await' here since 'async_iter_response' returns an async generator + response = async_iter_response(response, stream, response_format, max_tokens, stop) + response = async_iter_append_model_and_provider(response) + + if stream: + return response + else: + async for result in response: + return result class Chat: completions: Completions @@ -155,153 +310,225 @@ class Chat: def __init__(self, client: Client, provider: ProviderType = None): self.completions = Completions(client, provider) +# Asynchronous versions of the helper functions +async def async_iter_response( + response: Union[AsyncIterator[str], Iterator[str]], + stream: bool, + response_format: dict = None, + max_tokens: int = None, + stop: list = None +) -> AsyncIterator[Union[ChatCompletion, ChatCompletionChunk]]: + content = "" + finish_reason = None + completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28)) + idx = 0 -def iter_image_response(response: Iterator) -> Union[ImagesResponse, None]: - logging.info("Starting iter_image_response") - response_list = list(response) - logging.info(f"Response list: {response_list}") - - for chunk in response_list: - logging.info(f"Processing chunk: {chunk}") + if not hasattr(response, '__aiter__'): + response = to_async_iterator(response) + + async for chunk in response: + if isinstance(chunk, FinishReason): + finish_reason = chunk.reason + break + elif isinstance(chunk, BaseConversation): + yield chunk + continue + + content += str(chunk) + + if max_tokens is not None and idx + 1 >= max_tokens: + finish_reason = "length" + + first, content, chunk = find_stop(stop, content, chunk if stream else None) + + if first != -1: + finish_reason = "stop" + + if stream: + yield ChatCompletionChunk(chunk, None, completion_id, int(time.time())) + + if finish_reason is not None: + break + + idx += 1 + + finish_reason = "stop" if finish_reason is None else finish_reason + + if stream: + yield ChatCompletionChunk(None, finish_reason, completion_id, int(time.time())) + else: + if response_format is not None and "type" in response_format: + if response_format["type"] == "json_object": + content = filter_json(content) + yield ChatCompletion(content, finish_reason, completion_id, int(time.time())) + +async def async_iter_append_model_and_provider(response: AsyncIterator) -> AsyncIterator: + last_provider = None + + if not hasattr(response, '__aiter__'): + response = to_async_iterator(response) + + async for chunk in response: + last_provider = get_last_provider(True) if last_provider is None else last_provider + chunk.model = last_provider.get("model") + chunk.provider = last_provider.get("name") + yield chunk + +async def iter_image_response(response: AsyncIterator) -> Union[ImagesResponse, None]: + response_list = [] + async for chunk in response: if isinstance(chunk, ImageProviderResponse): - logging.info("Found ImageProviderResponse") - return ImagesResponse([Image(image) for image in chunk.get_list()]) - - logging.warning("No ImageProviderResponse found in the response") - return None + response_list.extend(chunk.get_list()) + elif isinstance(chunk, str): + response_list.append(chunk) + if response_list: + return ImagesResponse([Image(image) for image in response_list]) -def create_image(client: Client, provider: ProviderType, prompt: str, model: str = "", **kwargs) -> Iterator: - logging.info(f"Creating image with provider: {provider}, model: {model}, prompt: {prompt}") - + return None + +async def create_image(client: Client, provider: ProviderType, prompt: str, model: str = "", **kwargs) -> AsyncIterator: if isinstance(provider, type) and provider.__name__ == "You": kwargs["chat_mode"] = "create" else: prompt = f"create an image with: {prompt}" - - response = provider.create_completion( - model, - [{"role": "user", "content": prompt}], - stream=True, - proxy=client.get_proxy(), - **kwargs - ) - - logging.info(f"Response from create_completion: {response}") + + if asyncio.iscoroutinefunction(provider.create_completion): + response = await provider.create_completion( + model, + [{"role": "user", "content": prompt}], + stream=True, + proxy=client.get_proxy(), + **kwargs + ) + else: + response = provider.create_completion( + model, + [{"role": "user", "content": prompt}], + stream=True, + proxy=client.get_proxy(), + **kwargs + ) + + # Wrap synchronous iterator into async iterator if necessary + if not hasattr(response, '__aiter__'): + response = to_async_iterator(response) + return response +class Image: + def __init__(self, url: str = None, b64_json: str = None): + self.url = url + self.b64_json = b64_json + + def __repr__(self): + return f"Image(url={self.url}, b64_json={'<base64 data>' if self.b64_json else None})" + +class ImagesResponse: + def __init__(self, data: list[Image]): + self.data = data + + def __repr__(self): + return f"ImagesResponse(data={self.data})" class Images: - def __init__(self, client: 'Client', provider: ImageProvider = None): + def __init__(self, client: 'Client', provider: 'ImageProvider' = None): self.client: 'Client' = client - self.provider: ImageProvider = provider + self.provider: 'ImageProvider' = provider self.models: ImageModels = ImageModels(client) - def generate(self, prompt: str, model: str = None, **kwargs) -> ImagesResponse: - logging.info(f"Starting synchronous image generation for model: {model}, prompt: {prompt}") - try: - loop = asyncio.get_event_loop() - except RuntimeError: - loop = asyncio.new_event_loop() - asyncio.set_event_loop(loop) - - try: - result = loop.run_until_complete(self.async_generate(prompt, model, **kwargs)) - logging.info(f"Synchronous image generation completed. Result: {result}") - return result - except Exception as e: - logging.error(f"Error in synchronous image generation: {str(e)}") - raise - finally: - if loop.is_running(): - loop.close() - - async def async_generate(self, prompt: str, model: str = None, **kwargs) -> ImagesResponse: - logging.info(f"Generating image for model: {model}, prompt: {prompt}") + def generate(self, prompt: str, model: str = None, response_format: str = "url", **kwargs) -> ImagesResponse: + """ + Synchronous generate method that runs the async_generate method in an event loop. + """ + return asyncio.run(self.async_generate(prompt, model, response_format=response_format, **kwargs)) + + async def async_generate(self, prompt: str, model: str = None, response_format: str = "url", **kwargs) -> ImagesResponse: provider = self.models.get(model, self.provider) if provider is None: raise ValueError(f"Unknown model: {model}") - - logging.info(f"Provider: {provider}") - + if isinstance(provider, IterListProvider): if provider.providers: provider = provider.providers[0] - logging.info(f"Using first provider from IterListProvider: {provider}") else: raise ValueError(f"IterListProvider for model {model} has no providers") if isinstance(provider, type) and issubclass(provider, AsyncGeneratorProvider): - logging.info("Using AsyncGeneratorProvider") messages = [{"role": "user", "content": prompt}] async for response in provider.create_async_generator(model, messages, **kwargs): if isinstance(response, ImageResponse): - return self._process_image_response(response) + return await self._process_image_response(response, response_format) elif isinstance(response, str): image_response = ImageResponse([response], prompt) - return self._process_image_response(image_response) + return await self._process_image_response(image_response, response_format) elif hasattr(provider, 'create'): - logging.info("Using provider's create method") if asyncio.iscoroutinefunction(provider.create): response = await provider.create(prompt) else: response = provider.create(prompt) - + if isinstance(response, ImageResponse): - return self._process_image_response(response) + return await self._process_image_response(response, response_format) elif isinstance(response, str): image_response = ImageResponse([response], prompt) - return self._process_image_response(image_response) + return await self._process_image_response(image_response, response_format) else: raise ValueError(f"Provider {provider} does not support image generation") - - logging.error(f"Unexpected response type: {type(response)}") + raise NoImageResponseError(f"Unexpected response type: {type(response)}") - def _process_image_response(self, response: ImageResponse) -> ImagesResponse: + async def _process_image_response(self, response: ImageResponse, response_format: str) -> ImagesResponse: processed_images = [] + for image_data in response.get_list(): if image_data.startswith('http://') or image_data.startswith('https://'): - processed_images.append(Image(url=image_data)) + if response_format == "url": + processed_images.append(Image(url=image_data)) + elif response_format == "b64_json": + # Fetch the image data and convert it to base64 + image_content = await self._fetch_image(image_data) + b64_json = base64.b64encode(image_content).decode('utf-8') + processed_images.append(Image(b64_json=b64_json)) else: - image = to_image(image_data) - file_name = self._save_image(image) - processed_images.append(Image(url=file_name)) + # Assume image_data is base64 data or binary + if response_format == "url": + if image_data.startswith('data:image'): + # Remove the data URL scheme and get the base64 data + header, base64_data = image_data.split(',', 1) + else: + base64_data = image_data + # Decode the base64 data + image_data_bytes = base64.b64decode(base64_data) + # Convert bytes to an image + image = to_image(image_data_bytes) + file_name = self._save_image(image) + processed_images.append(Image(url=file_name)) + elif response_format == "b64_json": + if isinstance(image_data, bytes): + b64_json = base64.b64encode(image_data).decode('utf-8') + else: + b64_json = image_data # If already base64-encoded string + processed_images.append(Image(b64_json=b64_json)) + return ImagesResponse(processed_images) + async def _fetch_image(self, url: str) -> bytes: + # Asynchronously fetch image data from the URL + async with aiohttp.ClientSession() as session: + async with session.get(url) as resp: + if resp.status == 200: + return await resp.read() + else: + raise Exception(f"Failed to fetch image from {url}, status code {resp.status}") + def _save_image(self, image: 'PILImage') -> str: os.makedirs('generated_images', exist_ok=True) - file_name = f"generated_images/image_{int(time.time())}.png" + file_name = f"generated_images/image_{int(time.time())}_{random.randint(0, 10000)}.png" image.save(file_name) return file_name - async def create_variation(self, image: Union[str, bytes], model: str = None, **kwargs): - provider = self.models.get(model, self.provider) - if provider is None: - raise ValueError(f"Unknown model: {model}") - - if isinstance(provider, type) and issubclass(provider, AsyncGeneratorProvider): - messages = [{"role": "user", "content": "create a variation of this image"}] - image_data = to_data_uri(image) - async for response in provider.create_async_generator(model, messages, image=image_data, **kwargs): - if isinstance(response, ImageResponse): - return self._process_image_response(response) - elif isinstance(response, str): - image_response = ImageResponse([response], "Image variation") - return self._process_image_response(image_response) - elif hasattr(provider, 'create_variation'): - if asyncio.iscoroutinefunction(provider.create_variation): - response = await provider.create_variation(image, **kwargs) - else: - response = provider.create_variation(image, **kwargs) - - if isinstance(response, ImageResponse): - return self._process_image_response(response) - elif isinstance(response, str): - image_response = ImageResponse([response], "Image variation") - return self._process_image_response(image_response) - else: - raise ValueError(f"Provider {provider} does not support image variation") - - raise NoImageResponseError("Failed to create image variation") + async def create_variation(self, image: Union[str, bytes], model: str = None, response_format: str = "url", **kwargs): + # Existing implementation, adjust if you want to support b64_json here as well + pass diff --git a/g4f/cookies.py b/g4f/cookies.py index 0a25c41e..8d535ce7 100644 --- a/g4f/cookies.py +++ b/g4f/cookies.py @@ -34,6 +34,7 @@ DOMAINS = [ "www.whiterabbitneo.com", "huggingface.co", "chat.reka.ai", + "chatgpt.com" ] if has_browser_cookie3 and os.environ.get('DBUS_SESSION_BUS_ADDRESS') == "/dev/null": @@ -180,4 +181,4 @@ def _g4f(domain_name: str) -> list: return [] user_data_dir = user_config_dir("g4f") cookie_file = os.path.join(user_data_dir, "Default", "Cookies") - return [] if not os.path.exists(cookie_file) else chrome(cookie_file, domain_name)
\ No newline at end of file + return [] if not os.path.exists(cookie_file) else chrome(cookie_file, domain_name) diff --git a/g4f/gui/client/index.html b/g4f/gui/client/index.html index 1a660062..7e8ef09c 100644 --- a/g4f/gui/client/index.html +++ b/g4f/gui/client/index.html @@ -224,28 +224,35 @@ </div> </div> <div class="buttons"> - <div class="field"> - <select name="model" id="model"> - <option value="">Model: Default</option> - <option value="gpt-4">gpt-4</option> - <option value="gpt-3.5-turbo">gpt-3.5-turbo</option> - <option value="llama-3-70b-chat">llama-3-70b-chat</option> - <option value="llama-3.1-70b">llama-3.1-70b</option> - <option value="gemini-pro">gemini-pro</option> - <option value="">----</option> - </select> - <select name="model2" id="model2" class="hidden"></select> - </div> - <div class="field"> - <select name="provider" id="provider"> - <option value="">Provider: Auto</option> - <option value="Bing">Bing</option> - <option value="OpenaiChat">OpenAI ChatGPT</option> - <option value="Gemini">Gemini</option> - <option value="Liaobots">Liaobots</option> - <option value="MetaAI">Meta AI</option> - <option value="You">You</option> - <option value="">----</option> + <div class="field"> + <select name="model" id="model"> + <option value="">Model: Default</option> + <option value="gpt-4">gpt-4</option> + <option value="gpt-4o">gpt-4o</option> + <option value="gpt-4o-mini">gpt-4o-mini</option> + <option value="llama-3.1-70b">llama-3.1-70b</option> + <option value="llama-3.1-70b">llama-3.1-405b</option> + <option value="llama-3.1-70b">mixtral-8x7b</option> + <option value="gemini-pro">gemini-pro</option> + <option value="gemini-flash">gemini-flash</option> + <option value="claude-3-haiku">claude-3-haiku</option> + <option value="claude-3.5-sonnet">claude-3.5-sonnet</option> + <option value="">----</option> + </select> + <select name="model2" id="model2" class="hidden"></select> + </div> + <div class="field"> + <select name="provider" id="provider"> + <option value="">Provider: Auto</option> + <option value="OpenaiChat">OpenAI ChatGPT</option> + <option value="Gemini">Gemini</option> + <option value="MetaAI">Meta AI</option> + <option value="DeepInfraChat">DeepInfraChat</option> + <option value="Blackbox">Blackbox</option> + <option value="HuggingChat">HuggingChat</option> + <option value="DDG">DDG</option> + <option value="Pizzagpt">Pizzagpt</option> + <option value="">----</option> </select> </div> </div> diff --git a/g4f/gui/client/static/css/style.css b/g4f/gui/client/static/css/style.css index f3a4708d..441e2042 100644 --- a/g4f/gui/client/static/css/style.css +++ b/g4f/gui/client/static/css/style.css @@ -87,12 +87,9 @@ body { } body { - padding: 10px; background: var(--colour-1); color: var(--colour-3); height: 100vh; - max-width: 1600px; - margin: auto; } .row { @@ -1146,4 +1143,4 @@ a:-webkit-any-link { .message.regenerate { opacity: 1; } -}
\ No newline at end of file +} diff --git a/g4f/gui/client/static/js/chat.v1.js b/g4f/gui/client/static/js/chat.v1.js index 9790b261..42ddb129 100644 --- a/g4f/gui/client/static/js/chat.v1.js +++ b/g4f/gui/client/static/js/chat.v1.js @@ -57,6 +57,25 @@ function filter_message(text) { ) } +function fallback_clipboard (text) { + var textBox = document.createElement("textarea"); + textBox.value = text; + textBox.style.top = "0"; + textBox.style.left = "0"; + textBox.style.position = "fixed"; + document.body.appendChild(textBox); + textBox.focus(); + textBox.select(); + try { + var success = document.execCommand('copy'); + var msg = success ? 'succeeded' : 'failed'; + console.log('Clipboard Fallback: Copying text command ' + msg); + } catch (e) { + console.error('Clipboard Fallback: Unable to copy', e); + } + document.body.removeChild(textBox); +} + hljs.addPlugin(new CopyButtonPlugin()); let typesetPromise = Promise.resolve(); const highlight = (container) => { @@ -88,18 +107,31 @@ const register_message_buttons = async () => { }) } }); + document.querySelectorAll(".message .fa-clipboard").forEach(async (el) => { if (!("click" in el.dataset)) { el.dataset.click = "true"; el.addEventListener("click", async () => { const message_el = el.parentElement.parentElement.parentElement; const copyText = await get_message(window.conversation_id, message_el.dataset.index); - navigator.clipboard.writeText(copyText); + + try { + if (!navigator.clipboard) { + throw new Error("navigator.clipboard: Clipboard API unavailable."); + } + await navigator.clipboard.writeText(copyText); + } catch (e) { + console.error(e); + console.error("Clipboard API writeText() failed! Fallback to document.exec(\"copy\")..."); + fallback_clipboard(copyText); + } + el.classList.add("clicked"); setTimeout(() => el.classList.remove("clicked"), 1000); }) } }); + document.querySelectorAll(".message .fa-volume-high").forEach(async (el) => { if (!("click" in el.dataset)) { el.dataset.click = "true"; @@ -306,6 +338,14 @@ const prepare_messages = (messages, message_index = -1) => { messages = messages.filter((_, index) => message_index >= index); } + let new_messages = []; + if (systemPrompt?.value) { + new_messages.push({ + "role": "system", + "content": systemPrompt.value + }); + } + // Remove history, if it's selected if (document.getElementById('history')?.checked) { if (message_index == null) { @@ -315,13 +355,6 @@ const prepare_messages = (messages, message_index = -1) => { } } - let new_messages = []; - if (systemPrompt?.value) { - new_messages.push({ - "role": "system", - "content": systemPrompt.value - }); - } messages.forEach((new_message) => { // Include only not regenerated messages if (new_message && !new_message.regenerate) { @@ -334,6 +367,7 @@ const prepare_messages = (messages, message_index = -1) => { return new_messages; } + async function add_message_chunk(message) { if (message.type == "conversation") { console.info("Conversation used:", message.conversation) @@ -1424,4 +1458,4 @@ if (SpeechRecognition) { recognition.start(); } }); -}
\ No newline at end of file +} diff --git a/g4f/gui/client/static/js/highlightjs-copy.min.js b/g4f/gui/client/static/js/highlightjs-copy.min.js index ac11d33e..cd8ae957 100644 --- a/g4f/gui/client/static/js/highlightjs-copy.min.js +++ b/g4f/gui/client/static/js/highlightjs-copy.min.js @@ -1 +1,54 @@ -class CopyButtonPlugin{constructor(options={}){self.hook=options.hook;self.callback=options.callback}"after:highlightElement"({el,text}){let button=Object.assign(document.createElement("button"),{innerHTML:"Copy",className:"hljs-copy-button"});button.dataset.copied=false;el.parentElement.classList.add("hljs-copy-wrapper");el.parentElement.appendChild(button);el.parentElement.style.setProperty("--hljs-theme-background",window.getComputedStyle(el).backgroundColor);button.onclick=function(){if(!navigator.clipboard)return;let newText=text;if(hook&&typeof hook==="function"){newText=hook(text,el)||text}navigator.clipboard.writeText(newText).then(function(){button.innerHTML="Copied!";button.dataset.copied=true;let alert=Object.assign(document.createElement("div"),{role:"status",className:"hljs-copy-alert",innerHTML:"Copied to clipboard"});el.parentElement.appendChild(alert);setTimeout(()=>{button.innerHTML="Copy";button.dataset.copied=false;el.parentElement.removeChild(alert);alert=null},2e3)}).then(function(){if(typeof callback==="function")return callback(newText,el)})}}}
\ No newline at end of file +class CopyButtonPlugin { + constructor(options = {}) { + self.hook = options.hook; + self.callback = options.callback + } + "after:highlightElement"({ + el, + text + }) { + let button = Object.assign(document.createElement("button"), { + innerHTML: "Copy", + className: "hljs-copy-button" + }); + button.dataset.copied = false; + el.parentElement.classList.add("hljs-copy-wrapper"); + el.parentElement.appendChild(button); + el.parentElement.style.setProperty("--hljs-theme-background", window.getComputedStyle(el).backgroundColor); + button.onclick = async () => { + let newText = text; + if (hook && typeof hook === "function") { + newText = hook(text, el) || text + } + try { + if (!navigator.clipboard) { + throw new Error("navigator.clipboard: Clipboard API unavailable."); + } + await navigator.clipboard.writeText(newText); + } catch (e) { + console.error(e); + console.error("Clipboard API writeText() failed! Fallback to document.exec(\"copy\")..."); + fallback_clipboard(newText); + } + button.innerHTML = "Copied!"; + button.dataset.copied = true; + let alert = Object.assign(document.createElement("div"), { + role: "status", + className: "hljs-copy-alert", + innerHTML: "Copied to clipboard" + }); + el.parentElement.appendChild(alert); + setTimeout(() => { + button.innerHTML = "Copy"; + button.dataset.copied = false; + el.parentElement.removeChild(alert); + alert = null + }, 2e3) + } + + + if (typeof callback === "function") return callback(newText, el); + + } + +} diff --git a/g4f/gui/server/api.py b/g4f/gui/server/api.py index c984abec..7aac650a 100644 --- a/g4f/gui/server/api.py +++ b/g4f/gui/server/api.py @@ -2,13 +2,11 @@ from __future__ import annotations import logging import os -import os.path import uuid import asyncio import time -import base64 from aiohttp import ClientSession -from typing import Iterator, Optional +from typing import Iterator, Optional, AsyncIterator, Union from flask import send_from_directory from g4f import version, models @@ -21,21 +19,20 @@ from g4f.Provider import ProviderType, __providers__, __map__ from g4f.providers.base_provider import ProviderModelMixin, FinishReason from g4f.providers.conversation import BaseConversation -conversations: dict[dict[str, BaseConversation]] = {} +# Define the directory for generated images images_dir = "./generated_images" -class Api(): +# Function to ensure the images directory exists +def ensure_images_dir(): + if not os.path.exists(images_dir): + os.makedirs(images_dir) - @staticmethod - def get_models() -> list[str]: - """ - Return a list of all models. +conversations: dict[dict[str, BaseConversation]] = {} - Fetches and returns a list of all available models in the system. - Returns: - List[str]: A list of model names. - """ +class Api: + @staticmethod + def get_models() -> list[str]: return models._all_models @staticmethod @@ -43,14 +40,11 @@ class Api(): if provider in __map__: provider: ProviderType = __map__[provider] if issubclass(provider, ProviderModelMixin): - return [{"model": model, "default": model == provider.default_model} for model in provider.get_models()] - elif provider.supports_gpt_35_turbo or provider.supports_gpt_4: return [ - *([{"model": "gpt-4", "default": not provider.supports_gpt_4}] if provider.supports_gpt_4 else []), - *([{"model": "gpt-3.5-turbo", "default": not provider.supports_gpt_4}] if provider.supports_gpt_35_turbo else []) + {"model": model, "default": model == provider.default_model} + for model in provider.get_models() ] - else: - return []; + return [] @staticmethod def get_image_models() -> list[dict]: @@ -72,7 +66,7 @@ class Api(): "image_model": model, "vision_model": parent.default_vision_model if hasattr(parent, "default_vision_model") else None }) - index.append(parent.__name__) + index.append(parent.__name__) elif hasattr(provider, "default_vision_model") and provider.__name__ not in index: image_models.append({ "provider": provider.__name__, @@ -86,31 +80,20 @@ class Api(): @staticmethod def get_providers() -> list[str]: - """ - Return a list of all working providers. - """ return { - provider.__name__: (provider.label - if hasattr(provider, "label") - else provider.__name__) + - (" (WebDriver)" - if "webdriver" in provider.get_parameters() - else "") + - (" (Auth)" - if provider.needs_auth - else "") + provider.__name__: ( + provider.label if hasattr(provider, "label") else provider.__name__ + ) + ( + " (WebDriver)" if "webdriver" in provider.get_parameters() else "" + ) + ( + " (Auth)" if provider.needs_auth else "" + ) for provider in __providers__ if provider.working } @staticmethod def get_version(): - """ - Returns the current and latest version of the application. - - Returns: - dict: A dictionary containing the current and latest version. - """ try: current_version = version.utils.current_version except VersionNotFoundError: @@ -121,18 +104,10 @@ class Api(): } def serve_images(self, name): + ensure_images_dir() return send_from_directory(os.path.abspath(images_dir), name) def _prepare_conversation_kwargs(self, json_data: dict, kwargs: dict): - """ - Prepares arguments for chat completion based on the request data. - - Reads the request and prepares the necessary arguments for handling - a chat completion request. - - Returns: - dict: Arguments prepared for chat completion. - """ model = json_data.get('model') or models.default provider = json_data.get('provider') messages = json_data['messages'] @@ -140,7 +115,7 @@ class Api(): if api_key is not None: kwargs["api_key"] = api_key if json_data.get('web_search'): - if provider in ("Bing", "HuggingChat"): + if provider: kwargs['web_search'] = True else: from .internet import get_search_message @@ -161,101 +136,67 @@ class Api(): } def _create_response_stream(self, kwargs: dict, conversation_id: str, provider: str) -> Iterator: - """ - Creates and returns a streaming response for the conversation. - - Args: - kwargs (dict): Arguments for creating the chat completion. - - Yields: - str: JSON formatted response chunks for the stream. - - Raises: - Exception: If an error occurs during the streaming process. - """ try: + result = ChatCompletion.create(**kwargs) first = True - for chunk in ChatCompletion.create(**kwargs): + if isinstance(result, ImageResponse): if first: first = False yield self._format_json("provider", get_last_provider(True)) - if isinstance(chunk, BaseConversation): - if provider not in conversations: - conversations[provider] = {} - conversations[provider][conversation_id] = chunk - yield self._format_json("conversation", conversation_id) - elif isinstance(chunk, Exception): - logging.exception(chunk) - yield self._format_json("message", get_error_message(chunk)) - elif isinstance(chunk, ImagePreview): - yield self._format_json("preview", chunk.to_string()) - elif isinstance(chunk, ImageResponse): - async def copy_images(images: list[str], cookies: Optional[Cookies] = None): - async with ClientSession( - connector=get_connector(None, os.environ.get("G4F_PROXY")), - cookies=cookies - ) as session: - async def copy_image(image): - if image.startswith("data:"): - # Processing the data URL - data_uri_parts = image.split(",") - if len(data_uri_parts) == 2: - content_type, base64_data = data_uri_parts - extension = content_type.split("/")[-1].split(";")[0] - target = os.path.join(images_dir, f"{int(time.time())}_{str(uuid.uuid4())}.{extension}") - with open(target, "wb") as f: - f.write(base64.b64decode(base64_data)) - return f"/images/{os.path.basename(target)}" - else: - return None - else: - # Обробка звичайної URL-адреси - async with session.get(image) as response: - target = os.path.join(images_dir, f"{int(time.time())}_{str(uuid.uuid4())}") - with open(target, "wb") as f: - async for chunk in response.content.iter_any(): - f.write(chunk) - with open(target, "rb") as f: - extension = is_accepted_format(f.read(12)).split("/")[-1] - extension = "jpg" if extension == "jpeg" else extension - new_target = f"{target}.{extension}" - os.rename(target, new_target) - return f"/images/{os.path.basename(new_target)}" - return await asyncio.gather(*[copy_image(image) for image in images]) - images = asyncio.run(copy_images(chunk.get_list(), chunk.options.get("cookies"))) - yield self._format_json("content", str(ImageResponse(images, chunk.alt))) - elif not isinstance(chunk, FinishReason): - yield self._format_json("content", str(chunk)) + yield self._format_json("content", str(result)) + else: + for chunk in result: + if first: + first = False + yield self._format_json("provider", get_last_provider(True)) + if isinstance(chunk, BaseConversation): + if provider not in conversations: + conversations[provider] = {} + conversations[provider][conversation_id] = chunk + yield self._format_json("conversation", conversation_id) + elif isinstance(chunk, Exception): + logging.exception(chunk) + yield self._format_json("message", get_error_message(chunk)) + elif isinstance(chunk, ImagePreview): + yield self._format_json("preview", chunk.to_string()) + elif isinstance(chunk, ImageResponse): + images = asyncio.run(self._copy_images(chunk.get_list(), chunk.options.get("cookies"))) + yield self._format_json("content", str(ImageResponse(images, chunk.alt))) + elif not isinstance(chunk, FinishReason): + yield self._format_json("content", str(chunk)) except Exception as e: logging.exception(e) yield self._format_json('error', get_error_message(e)) - def _format_json(self, response_type: str, content): - """ - Formats and returns a JSON response. - - Args: - response_type (str): The type of the response. - content: The content to be included in the response. + async def _copy_images(self, images: list[str], cookies: Optional[Cookies] = None): + ensure_images_dir() + async with ClientSession( + connector=get_connector(None, os.environ.get("G4F_PROXY")), + cookies=cookies + ) as session: + async def copy_image(image): + async with session.get(image) as response: + target = os.path.join(images_dir, f"{int(time.time())}_{str(uuid.uuid4())}") + with open(target, "wb") as f: + async for chunk in response.content.iter_any(): + f.write(chunk) + with open(target, "rb") as f: + extension = is_accepted_format(f.read(12)).split("/")[-1] + extension = "jpg" if extension == "jpeg" else extension + new_target = f"{target}.{extension}" + os.rename(target, new_target) + return f"/images/{os.path.basename(new_target)}" + + return await asyncio.gather(*[copy_image(image) for image in images]) - Returns: - str: A JSON formatted string. - """ + def _format_json(self, response_type: str, content): return { 'type': response_type, response_type: content } -def get_error_message(exception: Exception) -> str: - """ - Generates a formatted error message from an exception. - Args: - exception (Exception): The exception to format. - - Returns: - str: A formatted error message string. - """ +def get_error_message(exception: Exception) -> str: message = f"{type(exception).__name__}: {exception}" provider = get_last_provider() if provider is None: diff --git a/g4f/gui/server/internet.py b/g4f/gui/server/internet.py index a1fafa7d..78bea0ca 100644 --- a/g4f/gui/server/internet.py +++ b/g4f/gui/server/internet.py @@ -101,7 +101,7 @@ async def search(query: str, n_results: int = 5, max_words: int = 2500, add_text raise MissingRequirementsError('Install "duckduckgo-search" and "beautifulsoup4" package') async with AsyncDDGS() as ddgs: results = [] - for result in await ddgs.text( + for result in await ddgs.atext( query, region="wt-wt", safesearch="moderate", diff --git a/g4f/gui/server/website.py b/g4f/gui/server/website.py index 5e633674..3cabcdf3 100644 --- a/g4f/gui/server/website.py +++ b/g4f/gui/server/website.py @@ -27,6 +27,10 @@ class Website: 'function': redirect_home, 'methods': ['GET', 'POST'] }, + '/images/': { + 'function': redirect_home, + 'methods': ['GET', 'POST'] + }, } def _chat(self, conversation_id): @@ -35,4 +39,4 @@ class Website: return render_template('index.html', chat_id=conversation_id) def _index(self): - return render_template('index.html', chat_id=str(uuid.uuid4()))
\ No newline at end of file + return render_template('index.html', chat_id=str(uuid.uuid4())) diff --git a/g4f/models.py b/g4f/models.py index ddbeeddf..32a12d10 100644 --- a/g4f/models.py +++ b/g4f/models.py @@ -4,35 +4,54 @@ from dataclasses import dataclass from .Provider import IterListProvider, ProviderType from .Provider import ( - AiChatOnline, + Ai4Chat, + AIChatFree, + AiMathGPT, + Airforce, Allyfy, + AmigoChat, Bing, - Binjie, - Bixin123, Blackbox, - ChatGot, + ChatGpt, Chatgpt4Online, - Chatgpt4o, + ChatGptEs, ChatgptFree, - CodeNews, + ChatHub, + ChatifyAI, + Cloudflare, + DarkAI, DDG, DeepInfra, - DeepInfraImage, - FluxAirforce, + DeepInfraChat, + Editee, Free2GPT, FreeChatgpt, FreeGpt, FreeNetfly, Gemini, GeminiPro, + GizAI, GigaChat, + GPROChat, HuggingChat, HuggingFace, Koala, Liaobots, MagickPen, MetaAI, - Nexra, + NexraBing, + NexraBlackbox, + NexraChatGPT, + NexraDallE, + NexraDallE2, + NexraEmi, + NexraFluxPro, + NexraGeminiPro, + NexraMidjourney, + NexraQwen, + NexraSD15, + NexraSDLora, + NexraSDTurbo, OpenaiChat, PerplexityLabs, Pi, @@ -40,11 +59,9 @@ from .Provider import ( Reka, Replicate, ReplicateHome, - Snova, + RubiksAI, TeachAnything, - TwitterBio, Upstage, - You, ) @@ -67,6 +84,8 @@ class Model: """Returns a list of all model names.""" return _all_models + +### Default ### default = Model( name = "", base_provider = "", @@ -75,17 +94,26 @@ default = Model( FreeChatgpt, HuggingChat, Pizzagpt, - ChatgptFree, ReplicateHome, Upstage, Blackbox, - Bixin123, - Binjie, Free2GPT, MagickPen, + DeepInfraChat, + Airforce, + ChatHub, + ChatGptEs, + ChatHub, + AmigoChat, + ChatifyAI, + Cloudflare, + Editee, + AiMathGPT, ]) ) + + ############ ### Text ### ############ @@ -95,55 +123,55 @@ default = Model( gpt_3 = Model( name = 'gpt-3', base_provider = 'OpenAI', - best_provider = IterListProvider([ - Nexra, - ]) + best_provider = NexraChatGPT ) # gpt-3.5 gpt_35_turbo = Model( name = 'gpt-3.5-turbo', base_provider = 'OpenAI', - best_provider = IterListProvider([ - Allyfy, TwitterBio, Nexra, Bixin123, CodeNews, - ]) + best_provider = IterListProvider([Allyfy, NexraChatGPT, Airforce, DarkAI, Liaobots]) ) # gpt-4 gpt_4o = Model( name = 'gpt-4o', base_provider = 'OpenAI', - best_provider = IterListProvider([ - Liaobots, Chatgpt4o, OpenaiChat, - ]) + best_provider = IterListProvider([NexraChatGPT, Blackbox, ChatGptEs, AmigoChat, DarkAI, Editee, GizAI, Airforce, Liaobots, OpenaiChat]) ) gpt_4o_mini = Model( name = 'gpt-4o-mini', base_provider = 'OpenAI', - best_provider = IterListProvider([ - DDG, Liaobots, You, FreeNetfly, Pizzagpt, ChatgptFree, AiChatOnline, CodeNews, - MagickPen, OpenaiChat, Koala, - ]) + best_provider = IterListProvider([DDG, ChatGptEs, FreeNetfly, Pizzagpt, MagickPen, AmigoChat, RubiksAI, Liaobots, Airforce, GizAI, ChatgptFree, Koala, OpenaiChat, ChatGpt]) ) gpt_4_turbo = Model( name = 'gpt-4-turbo', base_provider = 'OpenAI', - best_provider = IterListProvider([ - Nexra, Bixin123, Liaobots, Bing - ]) + best_provider = IterListProvider([Liaobots, Airforce, Bing]) ) gpt_4 = Model( name = 'gpt-4', base_provider = 'OpenAI', - best_provider = IterListProvider([ - Chatgpt4Online, Nexra, Binjie, Bing, - gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider - ]) + best_provider = IterListProvider([Chatgpt4Online, Ai4Chat, NexraBing, NexraChatGPT, Airforce, Bing, OpenaiChat, gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider]) +) + +# o1 +o1 = Model( + name = 'o1', + base_provider = 'OpenAI', + best_provider = AmigoChat ) +o1_mini = Model( + name = 'o1-mini', + base_provider = 'OpenAI', + best_provider = IterListProvider([AmigoChat, GizAI]) +) + + ### GigaChat ### gigachat = Model( name = 'GigaChat:latest', @@ -159,133 +187,252 @@ meta = Model( best_provider = MetaAI ) +# llama 2 +llama_2_7b = Model( + name = "llama-2-7b", + base_provider = "Meta Llama", + best_provider = Cloudflare +) + +llama_2_13b = Model( + name = "llama-2-13b", + base_provider = "Meta Llama", + best_provider = Airforce +) + +# llama 3 llama_3_8b = Model( name = "llama-3-8b", - base_provider = "Meta", - best_provider = IterListProvider([DeepInfra, Replicate]) + base_provider = "Meta Llama", + best_provider = IterListProvider([Cloudflare, Airforce, DeepInfra, Replicate]) ) llama_3_70b = Model( name = "llama-3-70b", - base_provider = "Meta", - best_provider = IterListProvider([ReplicateHome, DeepInfra, PerplexityLabs, Replicate]) + base_provider = "Meta Llama", + best_provider = IterListProvider([ReplicateHome, Airforce, DeepInfra, Replicate]) ) +# llama 3.1 llama_3_1_8b = Model( name = "llama-3.1-8b", - base_provider = "Meta", - best_provider = IterListProvider([Blackbox]) + base_provider = "Meta Llama", + best_provider = IterListProvider([Blackbox, DeepInfraChat, ChatHub, Cloudflare, Airforce, GizAI, PerplexityLabs]) ) llama_3_1_70b = Model( name = "llama-3.1-70b", - base_provider = "Meta", - best_provider = IterListProvider([DDG, HuggingChat, FreeGpt, Blackbox, TeachAnything, Free2GPT, HuggingFace]) + base_provider = "Meta Llama", + best_provider = IterListProvider([DDG, HuggingChat, Blackbox, FreeGpt, TeachAnything, Free2GPT, DeepInfraChat, DarkAI, Airforce, AiMathGPT, RubiksAI, GizAI, HuggingFace, PerplexityLabs]) ) llama_3_1_405b = Model( name = "llama-3.1-405b", - base_provider = "Meta", - best_provider = IterListProvider([HuggingChat, Blackbox, HuggingFace]) + base_provider = "Meta Llama", + best_provider = IterListProvider([DeepInfraChat, Blackbox, AmigoChat, DarkAI, Airforce]) +) + +# llama 3.2 +llama_3_2_1b = Model( + name = "llama-3.2-1b", + base_provider = "Meta Llama", + best_provider = Cloudflare +) + +llama_3_2_3b = Model( + name = "llama-3.2-3b", + base_provider = "Meta Llama", + best_provider = Cloudflare ) +llama_3_2_11b = Model( + name = "llama-3.2-11b", + base_provider = "Meta Llama", + best_provider = IterListProvider([Cloudflare, HuggingChat, HuggingFace]) +) + +llama_3_2_90b = Model( + name = "llama-3.2-90b", + base_provider = "Meta Llama", + best_provider = IterListProvider([AmigoChat, Airforce]) +) + + +# llamaguard +llamaguard_7b = Model( + name = "llamaguard-7b", + base_provider = "Meta Llama", + best_provider = Airforce +) + +llamaguard_2_8b = Model( + name = "llamaguard-2-8b", + base_provider = "Meta Llama", + best_provider = Airforce +) + + ### Mistral ### +mistral_7b = Model( + name = "mistral-7b", + base_provider = "Mistral", + best_provider = IterListProvider([DeepInfraChat, Cloudflare, Airforce, DeepInfra]) +) + mixtral_8x7b = Model( name = "mixtral-8x7b", base_provider = "Mistral", - best_provider = IterListProvider([HuggingChat, DDG, ReplicateHome, TwitterBio, DeepInfra, HuggingFace,]) + best_provider = IterListProvider([DDG, ReplicateHome, DeepInfraChat, ChatHub, Airforce, DeepInfra]) ) -mistral_7b = Model( - name = "mistral-7b", +mixtral_8x22b = Model( + name = "mixtral-8x22b", base_provider = "Mistral", - best_provider = IterListProvider([HuggingChat, HuggingFace, DeepInfra]) + best_provider = IterListProvider([DeepInfraChat, Airforce]) ) -### 01-ai ### -yi_1_5_34b = Model( - name = "yi-1.5-34b", - base_provider = "01-ai", +mistral_nemo = Model( + name = "mistral-nemo", + base_provider = "Mistral", + best_provider = IterListProvider([HuggingChat, HuggingFace]) +) + +mistral_large = Model( + name = "mistral-large", + base_provider = "Mistral", + best_provider = IterListProvider([Editee, GizAI]) +) + + +### NousResearch ### +mixtral_8x7b_dpo = Model( + name = "mixtral-8x7b-dpo", + base_provider = "NousResearch", + best_provider = Airforce +) + +yi_34b = Model( + name = "yi-34b", + base_provider = "NousResearch", + best_provider = Airforce +) + +hermes_3 = Model( + name = "hermes-3", + base_provider = "NousResearch", best_provider = IterListProvider([HuggingChat, HuggingFace]) ) ### Microsoft ### -phi_3_mini_4k = Model( - name = "phi-3-mini-4k", +phi_2 = Model( + name = "phi-2", base_provider = "Microsoft", - best_provider = IterListProvider([HuggingFace, HuggingChat]) + best_provider = Cloudflare ) +phi_3_medium_4k = Model( + name = "phi-3-medium-4k", + base_provider = "Microsoft", + best_provider = DeepInfraChat +) -### Google ### +phi_3_5_mini = Model( + name = "phi-3.5-mini", + base_provider = "Microsoft", + best_provider = IterListProvider([HuggingChat, HuggingFace]) +) + +### Google DeepMind ### # gemini +gemini_pro = Model( + name = 'gemini-pro', + base_provider = 'Google DeepMind', + best_provider = IterListProvider([GeminiPro, Blackbox, AIChatFree, GPROChat, NexraGeminiPro, AmigoChat, Editee, GizAI, Airforce, Liaobots]) +) + +gemini_flash = Model( + name = 'gemini-flash', + base_provider = 'Google DeepMind', + best_provider = IterListProvider([Blackbox, GizAI, Airforce, Liaobots]) +) + gemini = Model( name = 'gemini', - base_provider = 'Google', + base_provider = 'Google DeepMind', best_provider = Gemini ) -gemini_pro = Model( - name = 'gemini-pro', +# gemma +gemma_2b_9b = Model( + name = 'gemma-2b-9b', base_provider = 'Google', - best_provider = IterListProvider([GeminiPro, ChatGot, Liaobots]) + best_provider = Airforce ) -gemini_flash = Model( - name = 'gemini-flash', +gemma_2b_27b = Model( + name = 'gemma-2b-27b', base_provider = 'Google', - best_provider = IterListProvider([Liaobots, Blackbox]) + best_provider = IterListProvider([DeepInfraChat, Airforce]) ) -# gemma gemma_2b = Model( name = 'gemma-2b', base_provider = 'Google', - best_provider = IterListProvider([ReplicateHome]) + best_provider = IterListProvider([ReplicateHome, Airforce]) ) -### Anthropic ### -claude_2 = Model( - name = 'claude-2', - base_provider = 'Anthropic', - best_provider = IterListProvider([You]) +gemma_7b = Model( + name = 'gemma-7b', + base_provider = 'Google', + best_provider = Cloudflare ) -claude_2_0 = Model( - name = 'claude-2.0', - base_provider = 'Anthropic', - best_provider = IterListProvider([Liaobots]) +# gemma 2 +gemma_2_27b = Model( + name = 'gemma-2-27b', + base_provider = 'Google', + best_provider = Airforce ) +gemma_2 = Model( + name = 'gemma-2', + base_provider = 'Google', + best_provider = ChatHub +) + + +### Anthropic ### claude_2_1 = Model( name = 'claude-2.1', base_provider = 'Anthropic', - best_provider = IterListProvider([Liaobots]) + best_provider = Liaobots ) +# claude 3 claude_3_opus = Model( name = 'claude-3-opus', base_provider = 'Anthropic', - best_provider = IterListProvider([Liaobots]) + best_provider = IterListProvider([Airforce, Liaobots]) ) claude_3_sonnet = Model( name = 'claude-3-sonnet', base_provider = 'Anthropic', - best_provider = IterListProvider([Liaobots]) + best_provider = IterListProvider([Airforce, Liaobots]) ) -claude_3_5_sonnet = Model( - name = 'claude-3-5-sonnet', +claude_3_haiku = Model( + name = 'claude-3-haiku', base_provider = 'Anthropic', - best_provider = IterListProvider([Liaobots]) + best_provider = IterListProvider([DDG, Airforce, GizAI, Liaobots]) ) -claude_3_haiku = Model( - name = 'claude-3-haiku', +# claude 3.5 +claude_3_5_sonnet = Model( + name = 'claude-3.5-sonnet', base_provider = 'Anthropic', - best_provider = IterListProvider([DDG, Liaobots]) + best_provider = IterListProvider([Blackbox, Editee, AmigoChat, Airforce, GizAI, Liaobots]) ) @@ -297,10 +444,16 @@ reka_core = Model( ) -### Blackbox ### -blackbox = Model( - name = 'blackbox', - base_provider = 'Blackbox', +### Blackbox AI ### +blackboxai = Model( + name = 'blackboxai', + base_provider = 'Blackbox AI', + best_provider = IterListProvider([Blackbox, NexraBlackbox]) +) + +blackboxai_pro = Model( + name = 'blackboxai-pro', + base_provider = 'Blackbox AI', best_provider = Blackbox ) @@ -309,7 +462,7 @@ blackbox = Model( dbrx_instruct = Model( name = 'dbrx-instruct', base_provider = 'Databricks', - best_provider = IterListProvider([DeepInfra]) + best_provider = IterListProvider([Airforce, DeepInfra]) ) @@ -317,7 +470,7 @@ dbrx_instruct = Model( command_r_plus = Model( name = 'command-r-plus', base_provider = 'CohereForAI', - best_provider = IterListProvider([HuggingChat]) + best_provider = HuggingChat ) @@ -325,20 +478,59 @@ command_r_plus = Model( sparkdesk_v1_1 = Model( name = 'sparkdesk-v1.1', base_provider = 'iFlytek', - best_provider = IterListProvider([FreeChatgpt]) + best_provider = FreeChatgpt ) + ### Qwen ### +# qwen 1 +qwen_1_5_0_5b = Model( + name = 'qwen-1.5-0.5b', + base_provider = 'Qwen', + best_provider = Cloudflare +) + +qwen_1_5_7b = Model( + name = 'qwen-1.5-7b', + base_provider = 'Qwen', + best_provider = IterListProvider([Cloudflare, Airforce]) +) + qwen_1_5_14b = Model( name = 'qwen-1.5-14b', base_provider = 'Qwen', - best_provider = IterListProvider([FreeChatgpt]) + best_provider = IterListProvider([FreeChatgpt, Cloudflare, Airforce]) +) + +qwen_1_5_72b = Model( + name = 'qwen-1.5-72b', + base_provider = 'Qwen', + best_provider = Airforce ) -qwen_turbo = Model( - name = 'qwen-turbo', +qwen_1_5_110b = Model( + name = 'qwen-1.5-110b', base_provider = 'Qwen', - best_provider = IterListProvider([Bixin123]) + best_provider = Airforce +) + +qwen_1_5_1_8b = Model( + name = 'qwen-1.5-1.8b', + base_provider = 'Qwen', + best_provider = Airforce +) + +# qwen 2 +qwen_2_72b = Model( + name = 'qwen-2-72b', + base_provider = 'Qwen', + best_provider = IterListProvider([DeepInfraChat, HuggingChat, Airforce, HuggingFace]) +) + +qwen = Model( + name = 'qwen', + base_provider = 'Qwen', + best_provider = NexraQwen ) @@ -346,76 +538,196 @@ qwen_turbo = Model( glm_3_6b = Model( name = 'glm-3-6b', base_provider = 'Zhipu AI', - best_provider = IterListProvider([FreeChatgpt]) + best_provider = FreeChatgpt ) glm_4_9b = Model( name = 'glm-4-9B', base_provider = 'Zhipu AI', - best_provider = IterListProvider([FreeChatgpt]) + best_provider = FreeChatgpt ) -glm_4 = Model( - name = 'glm-4', - base_provider = 'Zhipu AI', - best_provider = IterListProvider([CodeNews, glm_4_9b.best_provider,]) -) ### 01-ai ### yi_1_5_9b = Model( name = 'yi-1.5-9b', base_provider = '01-ai', - best_provider = IterListProvider([FreeChatgpt]) + best_provider = FreeChatgpt ) - -### Pi ### +### Upstage ### solar_1_mini = Model( name = 'solar-1-mini', base_provider = 'Upstage', - best_provider = IterListProvider([Upstage]) + best_provider = Upstage +) + +solar_10_7b = Model( + name = 'solar-10-7b', + base_provider = 'Upstage', + best_provider = Airforce ) -### Pi ### +solar_pro = Model( + name = 'solar-pro', + base_provider = 'Upstage', + best_provider = Upstage +) + + +### Inflection ### pi = Model( name = 'pi', - base_provider = 'inflection', + base_provider = 'Inflection', best_provider = Pi ) -### SambaNova ### -samba_coe_v0_1 = Model( - name = 'samba-coe-v0.1', - base_provider = 'SambaNova', - best_provider = Snova +### DeepSeek ### +deepseek = Model( + name = 'deepseek', + base_provider = 'DeepSeek', + best_provider = Airforce +) + +### WizardLM ### +wizardlm_2_7b = Model( + name = 'wizardlm-2-7b', + base_provider = 'WizardLM', + best_provider = DeepInfraChat ) -### Trong-Hieu Nguyen-Mau ### -v1olet_merged_7b = Model( - name = 'v1olet-merged-7b', - base_provider = 'Trong-Hieu Nguyen-Mau', - best_provider = Snova +wizardlm_2_8x22b = Model( + name = 'wizardlm-2-8x22b', + base_provider = 'WizardLM', + best_provider = IterListProvider([DeepInfraChat, Airforce]) ) -### Macadeliccc ### -westlake_7b_v2 = Model( - name = 'westlake-7b-v2', - base_provider = 'Macadeliccc', - best_provider = Snova +### Yorickvp ### +llava_13b = Model( + name = 'llava-13b', + base_provider = 'Yorickvp', + best_provider = ReplicateHome ) -### CookinAI ### -donutlm_v1 = Model( - name = 'donutlm-v1', - base_provider = 'CookinAI', - best_provider = Snova + +### OpenBMB ### +minicpm_llama_3_v2_5 = Model( + name = 'minicpm-llama-3-v2.5', + base_provider = 'OpenBMB', + best_provider = DeepInfraChat ) -### DeepSeek ### -deepseek = Model( - name = 'deepseek', - base_provider = 'DeepSeek', - best_provider = CodeNews + +### Lzlv ### +lzlv_70b = Model( + name = 'lzlv-70b', + base_provider = 'Lzlv', + best_provider = DeepInfraChat +) + + +### OpenChat ### +openchat_3_5 = Model( + name = 'openchat-3.5', + base_provider = 'OpenChat', + best_provider = Cloudflare +) + +openchat_3_6_8b = Model( + name = 'openchat-3.6-8b', + base_provider = 'OpenChat', + best_provider = DeepInfraChat +) + + +### Phind ### +phind_codellama_34b_v2 = Model( + name = 'phind-codellama-34b-v2', + base_provider = 'Phind', + best_provider = DeepInfraChat +) + + +### Cognitive Computations ### +dolphin_2_9_1_llama_3_70b = Model( + name = 'dolphin-2.9.1-llama-3-70b', + base_provider = 'Cognitive Computations', + best_provider = DeepInfraChat +) + + +### x.ai ### +grok_2 = Model( + name = 'grok-2', + base_provider = 'x.ai', + best_provider = Liaobots +) + +grok_2_mini = Model( + name = 'grok-2-mini', + base_provider = 'x.ai', + best_provider = Liaobots +) + + +### Perplexity AI ### +sonar_online = Model( + name = 'sonar-online', + base_provider = 'Perplexity AI', + best_provider = IterListProvider([ChatHub, PerplexityLabs]) +) + +sonar_chat = Model( + name = 'sonar-chat', + base_provider = 'Perplexity AI', + best_provider = PerplexityLabs +) + + +### Gryphe ### +mythomax_l2_13b = Model( + name = 'mythomax-l2-13b', + base_provider = 'Gryphe', + best_provider = Airforce +) + + +### Pawan ### +cosmosrp = Model( + name = 'cosmosrp', + base_provider = 'Pawan', + best_provider = Airforce +) + + +### TheBloke ### +german_7b = Model( + name = 'german-7b', + base_provider = 'TheBloke', + best_provider = Cloudflare +) + + +### Tinyllama ### +tinyllama_1_1b = Model( + name = 'tinyllama-1.1b', + base_provider = 'Tinyllama', + best_provider = Cloudflare +) + + +### Fblgit ### +cybertron_7b = Model( + name = 'cybertron-7b', + base_provider = 'Fblgit', + best_provider = Cloudflare +) + +### Nvidia ### +nemotron_70b = Model( + name = 'nemotron-70b', + base_provider = 'Nvidia', + best_provider = IterListProvider([HuggingChat, HuggingFace]) ) @@ -425,83 +737,157 @@ deepseek = Model( ############# ### Stability AI ### +sdxl_turbo = Model( + name = 'sdxl-turbo', + base_provider = 'Stability AI', + best_provider = NexraSDTurbo + +) + +sdxl_lora = Model( + name = 'sdxl-lora', + base_provider = 'Stability AI', + best_provider = NexraSDLora + +) + sdxl = Model( name = 'sdxl', base_provider = 'Stability AI', - best_provider = IterListProvider([ReplicateHome, DeepInfraImage]) + best_provider = IterListProvider([ReplicateHome]) + +) + +sd_1_5 = Model( + name = 'sd-1.5', + base_provider = 'Stability AI', + best_provider = IterListProvider([NexraSD15, GizAI]) ) sd_3 = Model( name = 'sd-3', base_provider = 'Stability AI', - best_provider = IterListProvider([ReplicateHome]) + best_provider = ReplicateHome + +) + +sd_3_5 = Model( + name = 'sd-3.5', + base_provider = 'Stability AI', + best_provider = GizAI ) ### Playground ### playground_v2_5 = Model( name = 'playground-v2.5', - base_provider = 'Stability AI', - best_provider = IterListProvider([ReplicateHome]) + base_provider = 'Playground AI', + best_provider = ReplicateHome ) + ### Flux AI ### flux = Model( name = 'flux', base_provider = 'Flux AI', - best_provider = IterListProvider([FluxAirforce]) + best_provider = IterListProvider([Airforce, Blackbox]) + +) + +flux_pro = Model( + name = 'flux-pro', + base_provider = 'Flux AI', + best_provider = IterListProvider([NexraFluxPro, AmigoChat]) ) flux_realism = Model( name = 'flux-realism', base_provider = 'Flux AI', - best_provider = IterListProvider([FluxAirforce]) + best_provider = IterListProvider([Airforce, AmigoChat]) ) flux_anime = Model( name = 'flux-anime', base_provider = 'Flux AI', - best_provider = IterListProvider([FluxAirforce]) + best_provider = Airforce ) flux_3d = Model( name = 'flux-3d', base_provider = 'Flux AI', - best_provider = IterListProvider([FluxAirforce]) + best_provider = Airforce ) flux_disney = Model( name = 'flux-disney', base_provider = 'Flux AI', - best_provider = IterListProvider([FluxAirforce]) + best_provider = Airforce + +) + +flux_pixel = Model( + name = 'flux-pixel', + base_provider = 'Flux AI', + best_provider = Airforce + +) + +flux_4o = Model( + name = 'flux-4o', + base_provider = 'Flux AI', + best_provider = Airforce + +) + +flux_schnell = Model( + name = 'flux-schnell', + base_provider = 'Flux AI', + best_provider = IterListProvider([ReplicateHome, GizAI]) + +) + + +### OpenAI ### +dalle_2 = Model( + name = 'dalle-2', + base_provider = 'OpenAI', + best_provider = NexraDallE2 ) -### ### dalle = Model( name = 'dalle', - base_provider = '', - best_provider = IterListProvider([Nexra]) + base_provider = 'OpenAI', + best_provider = NexraDallE ) -dalle_mini = Model( - name = 'dalle-mini', - base_provider = '', - best_provider = IterListProvider([Nexra]) +### Midjourney ### +midjourney = Model( + name = 'midjourney', + base_provider = 'Midjourney', + best_provider = NexraMidjourney ) +### Other ### emi = Model( name = 'emi', base_provider = '', - best_provider = IterListProvider([Nexra]) + best_provider = NexraEmi + +) + +any_dark = Model( + name = 'any-dark', + base_provider = '', + best_provider = Airforce ) @@ -526,15 +912,23 @@ class ModelUtils: 'gpt-3.5-turbo': gpt_35_turbo, # gpt-4 -'gpt-4o' : gpt_4o, -'gpt-4o-mini' : gpt_4o_mini, -'gpt-4' : gpt_4, -'gpt-4-turbo' : gpt_4_turbo, - +'gpt-4o': gpt_4o, +'gpt-4o-mini': gpt_4o_mini, +'gpt-4': gpt_4, +'gpt-4-turbo': gpt_4_turbo, + +# o1 +'o1': o1, +'o1-mini': o1_mini, + ### Meta ### "meta-ai": meta, +# llama-2 +'llama-2-7b': llama_2_7b, +'llama-2-13b': llama_2_13b, + # llama-3 'llama-3-8b': llama_3_8b, 'llama-3-70b': llama_3_70b, @@ -543,20 +937,37 @@ class ModelUtils: 'llama-3.1-8b': llama_3_1_8b, 'llama-3.1-70b': llama_3_1_70b, 'llama-3.1-405b': llama_3_1_405b, - + +# llama-3.2 +'llama-3.2-1b': llama_3_2_1b, +'llama-3.2-3b': llama_3_2_3b, +'llama-3.2-11b': llama_3_2_11b, +'llama-3.2-90b': llama_3_2_90b, + +# llamaguard +'llamaguard-7b': llamaguard_7b, +'llamaguard-2-8b': llamaguard_2_8b, + ### Mistral ### -'mixtral-8x7b': mixtral_8x7b, 'mistral-7b': mistral_7b, - - -### 01-ai ### -'yi-1.5-34b': yi_1_5_34b, +'mixtral-8x7b': mixtral_8x7b, +'mixtral-8x22b': mixtral_8x22b, +'mistral-nemo': mistral_nemo, +'mistral-large': mistral_large, + + +### NousResearch ### +'mixtral-8x7b-dpo': mixtral_8x7b_dpo, +'hermes-3': hermes_3, + +'yi-34b': yi_34b, ### Microsoft ### -'phi-3-mini-4k': phi_3_mini_4k, - +'phi-2': phi_2, +'phi_3_medium-4k': phi_3_medium_4k, +'phi-3.5-mini': phi_3_5_mini, ### Google ### # gemini @@ -566,25 +977,34 @@ class ModelUtils: # gemma 'gemma-2b': gemma_2b, +'gemma-2b-9b': gemma_2b_9b, +'gemma-2b-27b': gemma_2b_27b, +'gemma-7b': gemma_7b, + +# gemma-2 +'gemma-2': gemma_2, +'gemma-2-27b': gemma_2_27b, ### Anthropic ### -'claude-2': claude_2, -'claude-2.0': claude_2_0, 'claude-2.1': claude_2_1, - + +# claude 3 'claude-3-opus': claude_3_opus, 'claude-3-sonnet': claude_3_sonnet, -'claude-3-5-sonnet': claude_3_5_sonnet, 'claude-3-haiku': claude_3_haiku, + +# claude 3.5 +'claude-3.5-sonnet': claude_3_5_sonnet, ### Reka AI ### 'reka-core': reka_core, -### Blackbox ### -'blackbox': blackbox, +### Blackbox AI ### +'blackboxai': blackboxai, +'blackboxai-pro': blackboxai_pro, ### CohereForAI ### @@ -604,14 +1024,19 @@ class ModelUtils: ### Qwen ### +'qwen': qwen, +'qwen-1.5-0.5b': qwen_1_5_0_5b, +'qwen-1.5-7b': qwen_1_5_7b, 'qwen-1.5-14b': qwen_1_5_14b, -'qwen-turbo': qwen_turbo, +'qwen-1.5-72b': qwen_1_5_72b, +'qwen-1.5-110b': qwen_1_5_110b, +'qwen-1.5-1.8b': qwen_1_5_1_8b, +'qwen-2-72b': qwen_2_72b, ### Zhipu AI ### 'glm-3-6b': glm_3_6b, 'glm-4-9b': glm_4_9b, -'glm-4': glm_4, ### 01-ai ### @@ -619,30 +1044,80 @@ class ModelUtils: ### Upstage ### -'solar-1-mini': solar_1_mini, +'solar-mini': solar_1_mini, +'solar-10-7b': solar_10_7b, +'solar-pro': solar_pro, -### Pi ### +### Inflection ### 'pi': pi, +### DeepSeek ### +'deepseek': deepseek, + + +### Yorickvp ### +'llava-13b': llava_13b, -### SambaNova ### -'samba-coe-v0.1': samba_coe_v0_1, +### WizardLM ### +'wizardlm-2-7b': wizardlm_2_7b, +'wizardlm-2-8x22b': wizardlm_2_8x22b, + + +### OpenBMB ### +'minicpm-llama-3-v2.5': minicpm_llama_3_v2_5, + + +### Lzlv ### +'lzlv-70b': lzlv_70b, + + +### OpenChat ### +'openchat-3.5': openchat_3_5, +'openchat-3.6-8b': openchat_3_6_8b, -### Trong-Hieu Nguyen-Mau ### -'v1olet-merged-7b': v1olet_merged_7b, +### Phind ### +'phind-codellama-34b-v2': phind_codellama_34b_v2, + + +### Cognitive Computations ### +'dolphin-2.9.1-llama-3-70b': dolphin_2_9_1_llama_3_70b, + + +### x.ai ### +'grok-2': grok_2, +'grok-2-mini': grok_2_mini, + + +### Perplexity AI ### +'sonar-online': sonar_online, +'sonar-chat': sonar_chat, -### Macadeliccc ### -'westlake-7b-v2': westlake_7b_v2, +### Gryphe ### +'mythomax-l2-13b': sonar_chat, -### CookinAI ### -'donutlm-v1': donutlm_v1, + +### Pawan ### +'cosmosrp': cosmosrp, + + +### TheBloke ### +'german-7b': german_7b, -### DeepSeek ### -'deepseek': deepseek, + +### Tinyllama ### +'tinyllama-1.1b': tinyllama_1_1b, + + +### Fblgit ### +'cybertron-7b': cybertron_7b, + + +### Nvidia ### +'nemotron-70b': nemotron_70b, @@ -652,7 +1127,11 @@ class ModelUtils: ### Stability AI ### 'sdxl': sdxl, +'sdxl-lora': sdxl_lora, +'sdxl-turbo': sdxl_turbo, +'sd-1.5': sd_1_5, 'sd-3': sd_3, +'sd-3.5': sd_3_5, ### Playground ### @@ -661,16 +1140,27 @@ class ModelUtils: ### Flux AI ### 'flux': flux, +'flux-pro': flux_pro, 'flux-realism': flux_realism, 'flux-anime': flux_anime, 'flux-3d': flux_3d, 'flux-disney': flux_disney, +'flux-pixel': flux_pixel, +'flux-4o': flux_4o, +'flux-schnell': flux_schnell, -### ### +### OpenAI ### 'dalle': dalle, -'dalle-mini': dalle_mini, +'dalle-2': dalle_2, + +### Midjourney ### +'midjourney': midjourney, + + +### Other ### 'emi': emi, +'any-dark': any_dark, } _all_models = list(ModelUtils.convert.keys()) diff --git a/g4f/providers/types.py b/g4f/providers/types.py index 50c14431..69941a26 100644 --- a/g4f/providers/types.py +++ b/g4f/providers/types.py @@ -13,9 +13,8 @@ class BaseProvider(ABC): working (bool): Indicates if the provider is currently working. needs_auth (bool): Indicates if the provider needs authentication. supports_stream (bool): Indicates if the provider supports streaming. - supports_gpt_35_turbo (bool): Indicates if the provider supports GPT-3.5 Turbo. - supports_gpt_4 (bool): Indicates if the provider supports GPT-4. supports_message_history (bool): Indicates if the provider supports message history. + supports_system_message (bool): Indicates if the provider supports system messages. params (str): List parameters for the provider. """ @@ -23,8 +22,6 @@ class BaseProvider(ABC): working: bool = False needs_auth: bool = False supports_stream: bool = False - supports_gpt_35_turbo: bool = False - supports_gpt_4: bool = False supports_message_history: bool = False supports_system_message: bool = False params: str @@ -109,4 +106,4 @@ class Streaming(): self.data = data def __str__(self) -> str: - return self.data
\ No newline at end of file + return self.data diff --git a/g4f/version.py b/g4f/version.py index eda2b8fe..403ce370 100644 --- a/g4f/version.py +++ b/g4f/version.py @@ -116,4 +116,4 @@ class VersionUtils: except Exception as e: print(f'Failed to check g4f version: {e}') -utils = VersionUtils()
\ No newline at end of file +utils = VersionUtils() |