diff options
Diffstat (limited to '')
-rw-r--r-- | docs/providers-and-models.md | 14 | ||||
-rw-r--r-- | g4f/Provider/__init__.py | 2 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraBing.py | 93 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraBlackbox.py | 100 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraChatGPT.py | 285 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraDallE.py | 63 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraDallE2.py | 63 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraEmi.py | 63 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraFluxPro.py | 70 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraGeminiPro.py | 86 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraMidjourney.py | 63 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraProdiaAI.py | 151 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraQwen.py | 86 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraSD15.py | 72 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraSDLora.py | 69 | ||||
-rw-r--r-- | g4f/Provider/nexra/NexraSDTurbo.py | 69 | ||||
-rw-r--r-- | g4f/Provider/nexra/__init__.py | 14 | ||||
-rw-r--r-- | g4f/models.py | 112 |
18 files changed, 5 insertions, 1470 deletions
diff --git a/docs/providers-and-models.md b/docs/providers-and-models.md index 85be81cc..e34d2539 100644 --- a/docs/providers-and-models.md +++ b/docs/providers-and-models.md @@ -49,20 +49,6 @@ This document provides an overview of various AI providers and models, including |[liaobots.work](https://liaobots.work)|`g4f.Provider.Liaobots`|`gpt-3.5-turbo, gpt-4o-mini, gpt-4o, gpt-4-turbo, grok-2, grok-2-mini, claude-3-opus, claude-3-sonnet, claude-3-5-sonnet, claude-3-haiku, claude-2.1, gemini-flash, gemini-pro`|❌|❌|✔|![Active](https://img.shields.io/badge/Active-brightgreen)|❌| |[magickpen.com](https://magickpen.com)|`g4f.Provider.MagickPen`|`gpt-4o-mini`|❌|❌|✔|![Active](https://img.shields.io/badge/Active-brightgreen)|❌| |[meta.ai](https://www.meta.ai)|`g4f.Provider.MetaAI`|✔|✔|?|?|![Active](https://img.shields.io/badge/Active-brightgreen)|✔| -|[nexra.aryahcr.cc/bing](https://nexra.aryahcr.cc/documentation/bing/en)|`g4f.Provider.NexraBing`|✔|❌|❌|✔|![Disabled](https://img.shields.io/badge/Disabled-red)|❌| -|[nexra.aryahcr.cc/blackbox](https://nexra.aryahcr.cc/documentation/blackbox/en)|`g4f.Provider.NexraBlackbox`|`blackboxai` |❌|❌|✔|![Active](https://img.shields.io/badge/Active-brightgreen)|❌| -|[nexra.aryahcr.cc/chatgpt](https://nexra.aryahcr.cc/documentation/chatgpt/en)|`g4f.Provider.NexraChatGPT`|`gpt-4, gpt-3.5-turbo, gpt-3, gpt-4o` |❌|❌|✔|![Active](https://img.shields.io/badge/Active-brightgreen)|❌| -|[nexra.aryahcr.cc/dall-e](https://nexra.aryahcr.cc/documentation/dall-e/en)|`g4f.Provider.NexraDallE`|❌|`dalle`|❌|❌|![Active](https://img.shields.io/badge/Active-brightgreen)|❌| -|[nexra.aryahcr.cc/dall-e](https://nexra.aryahcr.cc/documentation/dall-e/en)|`g4f.Provider.NexraDallE2`|❌|`dalle-2`|❌|❌|![Active](https://img.shields.io/badge/Active-brightgreen)|❌| -|[nexra.aryahcr.cc/emi](https://nexra.aryahcr.cc/documentation/emi/en)|`g4f.Provider.NexraEmi`|❌|`emi`|❌|❌|![Active](https://img.shields.io/badge/Active-brightgreen)|❌| -|[nexra.aryahcr.cc/flux-pro](https://nexra.aryahcr.cc/documentation/flux-pro/en)|`g4f.Provider.NexraFluxPro`|❌|`flux-pro`|❌|❌|![Active](https://img.shields.io/badge/Active-brightgreen)|❌| -|[nexra.aryahcr.cc/gemini-pro](https://nexra.aryahcr.cc/documentation/gemini-pro/en)|`g4f.Provider.NexraGeminiPro`|`gemini-pro`|❌|❌|❌|![Active](https://img.shields.io/badge/Active-brightgreen)|❌| -|[nexra.aryahcr.cc/midjourney](https://nexra.aryahcr.cc/documentation/midjourney/en)|`g4f.Provider.NexraMidjourney`|❌|`midjourney`|❌|❌|![Active](https://img.shields.io/badge/Active-brightgreen)|❌| -|[nexra.aryahcr.cc/prodia](https://nexra.aryahcr.cc/documentation/prodia/en)|`g4f.Provider.NexraProdiaAI`|❌|✔|❌|❌|![Active](https://img.shields.io/badge/Active-brightgreen)|❌| -|[nexra.aryahcr.cc/qwen](https://nexra.aryahcr.cc/documentation/qwen/en)|`g4f.Provider.NexraQwen`|`qwen`|❌|❌|✔|![Active](https://img.shields.io/badge/Active-brightgreen)|❌| -|[nexra.aryahcr.cc/stable-diffusion](https://nexra.aryahcr.cc/documentation/stable-diffusion/en)|`g4f.Provider.NexraSD15`|❌|`sd-1.5`|❌|❌|![Active](https://img.shields.io/badge/Active-brightgreen)|❌ -|[nexra.aryahcr.cc/stable-diffusion](https://nexra.aryahcr.cc/documentation/stable-diffusion/en)|`g4f.Provider.NexraSDLora`|❌|`sdxl-lora`|❌|❌|![Active](https://img.shields.io/badge/Active-brightgreen)|❌ -|[nexra.aryahcr.cc/stable-diffusion](https://nexra.aryahcr.cc/documentation/stable-diffusion/en)|`g4f.Provider.NexraSDTurbo`|❌|`sdxl-turbo`|❌|❌|![Active](https://img.shields.io/badge/Active-brightgreen)|❌ |[platform.openai.com](https://platform.openai.com/)|`g4f.Provider.Openai`|✔|❌|✔||![Unknown](https://img.shields.io/badge/Unknown-grey)|✔| |[chatgpt.com](https://chatgpt.com/)|`g4f.Provider.OpenaiChat`|`gpt-4o, gpt-4o-mini, gpt-4`|❌|✔||![Unknown](https://img.shields.io/badge/Unknown-grey)|✔| |[www.perplexity.ai)](https://www.perplexity.ai)|`g4f.Provider.PerplexityAi`|✔|❌|❌|?|![Disabled](https://img.shields.io/badge/Disabled-red)|❌| diff --git a/g4f/Provider/__init__.py b/g4f/Provider/__init__.py index 19ddaa53..f720a643 100644 --- a/g4f/Provider/__init__.py +++ b/g4f/Provider/__init__.py @@ -11,8 +11,6 @@ from .needs_auth import * from .not_working import * from .local import * -from .nexra import * - from .AI365VIP import AI365VIP from .AIChatFree import AIChatFree from .AIUncensored import AIUncensored diff --git a/g4f/Provider/nexra/NexraBing.py b/g4f/Provider/nexra/NexraBing.py deleted file mode 100644 index 28f0b117..00000000 --- a/g4f/Provider/nexra/NexraBing.py +++ /dev/null @@ -1,93 +0,0 @@ -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 deleted file mode 100644 index be048fdd..00000000 --- a/g4f/Provider/nexra/NexraBlackbox.py +++ /dev/null @@ -1,100 +0,0 @@ -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 deleted file mode 100644 index 074a0363..00000000 --- a/g4f/Provider/nexra/NexraChatGPT.py +++ /dev/null @@ -1,285 +0,0 @@ -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 deleted file mode 100644 index f605c6d0..00000000 --- a/g4f/Provider/nexra/NexraDallE.py +++ /dev/null @@ -1,63 +0,0 @@ -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 deleted file mode 100644 index 2a36b6e6..00000000 --- a/g4f/Provider/nexra/NexraDallE2.py +++ /dev/null @@ -1,63 +0,0 @@ -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 deleted file mode 100644 index c26becec..00000000 --- a/g4f/Provider/nexra/NexraEmi.py +++ /dev/null @@ -1,63 +0,0 @@ -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 deleted file mode 100644 index cfb26385..00000000 --- a/g4f/Provider/nexra/NexraFluxPro.py +++ /dev/null @@ -1,70 +0,0 @@ -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 deleted file mode 100644 index e4e6a8ec..00000000 --- a/g4f/Provider/nexra/NexraGeminiPro.py +++ /dev/null @@ -1,86 +0,0 @@ -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 deleted file mode 100644 index c427f8a0..00000000 --- a/g4f/Provider/nexra/NexraMidjourney.py +++ /dev/null @@ -1,63 +0,0 @@ -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 deleted file mode 100644 index de997fce..00000000 --- a/g4f/Provider/nexra/NexraProdiaAI.py +++ /dev/null @@ -1,151 +0,0 @@ -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 deleted file mode 100644 index 7f944e44..00000000 --- a/g4f/Provider/nexra/NexraQwen.py +++ /dev/null @@ -1,86 +0,0 @@ -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 deleted file mode 100644 index 860a132f..00000000 --- a/g4f/Provider/nexra/NexraSD15.py +++ /dev/null @@ -1,72 +0,0 @@ -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 deleted file mode 100644 index a12bff1a..00000000 --- a/g4f/Provider/nexra/NexraSDLora.py +++ /dev/null @@ -1,69 +0,0 @@ -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 deleted file mode 100644 index 865b4522..00000000 --- a/g4f/Provider/nexra/NexraSDTurbo.py +++ /dev/null @@ -1,69 +0,0 @@ -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 deleted file mode 100644 index bebc1fb6..00000000 --- a/g4f/Provider/nexra/__init__.py +++ /dev/null @@ -1,14 +0,0 @@ -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/models.py b/g4f/models.py index 241b56b9..1223e785 100644 --- a/g4f/models.py +++ b/g4f/models.py @@ -32,19 +32,6 @@ from .Provider import ( Liaobots, MagickPen, MetaAI, - NexraBing, - NexraBlackbox, - NexraChatGPT, - NexraDallE, - NexraDallE2, - NexraEmi, - NexraFluxPro, - NexraGeminiPro, - NexraMidjourney, - NexraQwen, - NexraSD15, - NexraSDLora, - NexraSDTurbo, OpenaiChat, PerplexityLabs, Pi, @@ -107,25 +94,18 @@ default = Model( ############ ### OpenAI ### -# gpt-3 -gpt_3 = Model( - name = 'gpt-3', - base_provider = 'OpenAI', - best_provider = NexraChatGPT -) - # gpt-3.5 gpt_35_turbo = Model( name = 'gpt-3.5-turbo', base_provider = 'OpenAI', - best_provider = IterListProvider([DarkAI, NexraChatGPT, Airforce, Liaobots, Allyfy]) + best_provider = IterListProvider([DarkAI, Airforce, Liaobots, Allyfy]) ) # gpt-4 gpt_4o = Model( name = 'gpt-4o', base_provider = 'OpenAI', - best_provider = IterListProvider([Blackbox, ChatGptEs, DarkAI, NexraChatGPT, Airforce, ChatGpt, Liaobots, OpenaiChat]) + best_provider = IterListProvider([Blackbox, ChatGptEs, DarkAI, Airforce, ChatGpt, Liaobots, OpenaiChat]) ) gpt_4o_mini = Model( @@ -143,7 +123,7 @@ gpt_4_turbo = Model( gpt_4 = Model( name = 'gpt-4', base_provider = 'OpenAI', - best_provider = IterListProvider([Chatgpt4Online, Ai4Chat, NexraBing, NexraChatGPT, ChatGpt, Airforce, Bing, OpenaiChat, gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider]) + best_provider = IterListProvider([Chatgpt4Online, Ai4Chat, ChatGpt, Airforce, Bing, OpenaiChat, gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider]) ) # o1 @@ -342,7 +322,7 @@ phi_3_5_mini = Model( gemini_pro = Model( name = 'gemini-pro', base_provider = 'Google DeepMind', - best_provider = IterListProvider([GeminiPro, Blackbox, AIChatFree, FreeGpt, NexraGeminiPro, Airforce, Liaobots]) + best_provider = IterListProvider([GeminiPro, Blackbox, AIChatFree, FreeGpt, Airforce, Liaobots]) ) gemini_flash = Model( @@ -430,7 +410,7 @@ reka_core = Model( blackboxai = Model( name = 'blackboxai', base_provider = 'Blackbox AI', - best_provider = IterListProvider([Blackbox, NexraBlackbox]) + best_provider = Blackbox ) blackboxai_pro = Model( @@ -501,12 +481,6 @@ qwen_2_5_72b = Model( best_provider = Airforce ) -qwen = Model( - name = 'qwen', - base_provider = 'Qwen', - best_provider = NexraQwen -) - ### Upstage ### solar_10_7b = Model( name = 'solar-10-7b', @@ -683,20 +657,6 @@ zephyr_7b = 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', @@ -704,13 +664,6 @@ sdxl = Model( ) -sd_1_5 = Model( - name = 'sd-1.5', - base_provider = 'Stability AI', - best_provider = IterListProvider([NexraSD15]) - -) - sd_3 = Model( name = 'sd-3', base_provider = 'Stability AI', @@ -735,13 +688,6 @@ flux = Model( ) -flux_pro = Model( - name = 'flux-pro', - base_provider = 'Flux AI', - best_provider = IterListProvider([NexraFluxPro]) - -) - flux_realism = Model( name = 'flux-realism', base_provider = 'Flux AI', @@ -792,37 +738,7 @@ flux_schnell = Model( ) -### OpenAI ### -dalle_2 = Model( - name = 'dalle-2', - base_provider = 'OpenAI', - best_provider = NexraDallE2 - -) - -dalle = Model( - name = 'dalle', - base_provider = 'OpenAI', - best_provider = NexraDallE - -) - -### Midjourney ### -midjourney = Model( - name = 'midjourney', - base_provider = 'Midjourney', - best_provider = NexraMidjourney - -) - ### Other ### -emi = Model( - name = 'emi', - base_provider = '', - best_provider = NexraEmi - -) - any_dark = Model( name = 'any-dark', base_provider = '', @@ -844,9 +760,6 @@ class ModelUtils: ############ ### OpenAI ### -# gpt-3 -'gpt-3': gpt_3, - # gpt-3.5 'gpt-3.5-turbo': gpt_35_turbo, @@ -959,8 +872,6 @@ class ModelUtils: ### Qwen ### -'qwen': qwen, - # qwen 1.5 'qwen-1.5-5b': qwen_1_5_5b, 'qwen-1.5-7b': qwen_1_5_7b, @@ -1063,9 +974,6 @@ class ModelUtils: ### Stability AI ### 'sdxl': sdxl, -'sdxl-lora': sdxl_lora, -'sdxl-turbo': sdxl_turbo, -'sd-1.5': sd_1_5, 'sd-3': sd_3, @@ -1075,7 +983,6 @@ class ModelUtils: ### Flux AI ### 'flux': flux, -'flux-pro': flux_pro, 'flux-realism': flux_realism, 'flux-anime': flux_anime, 'flux-3d': flux_3d, @@ -1085,16 +992,7 @@ class ModelUtils: 'flux-schnell': flux_schnell, -### OpenAI ### -'dalle': dalle, -'dalle-2': dalle_2, - -### Midjourney ### -'midjourney': midjourney, - - ### Other ### -'emi': emi, 'any-dark': any_dark, } |