mirror of
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Merge pull request #2262 from kqlio67/main
Enhance G4F: Provider Removal, Documentation Updates, and Provider Enhancements
This commit is contained in:
Tekky
GitHub
commit
6d19ba6956
@ -14,19 +14,18 @@
|
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|[aichatfree.info](https://aichatfree.info)|`g4f.Provider.AIChatFree`|`gemini-pro`|❌|❌|✔||❌|
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|[aichatonline.org](https://aichatonline.org)|`g4f.Provider.AiChatOnline`|`gpt-4o-mini`|❌|❌|?||❌|
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|[ai-chats.org](https://ai-chats.org)|`g4f.Provider.AiChats`|`gpt-4`|`dalle`|❌|?||❌|
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|[api.airforce](https://api.airforce)|`g4f.Provider.Airforce`|`llama-2-13b, llama-3-70b, llama-3-8b, llama-3.1-405b, llama-3.1-70b, llama-3.1-8b, mixtral-8x7b, mixtral-8x22b, mistral-7b, mixtral-8x7b-dpo, qwen-1.5-72b, qwen-1.5-110b, qwen-2-72b, gemma-2b, gemma-2b-9b, gemma-2b-27b, deepseek, yi-34b, wizardlm-2-8x22b, solar-10-7b, sh-n-7b, sparkdesk-v1.1,gpt-4o, gpt-4o-mini, gpt-3.5-turbo, gemini-flash, gemini-pro, dbrx-instruct`|`flux, flux-realism', flux-anime, flux-3d, flux-disney, flux-pixel, flux-4o, any-dark, dalle-3`|❌|✔||❌|
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|[api.airforce](https://api.airforce)|`g4f.Provider.Airforce`|`gpt-4, gpt-4-turbo, gpt-4o-mini, gpt-3.5-turbo, gpt-4o, claude-3-haiku, claude-3-sonnet, claude-3-5-sonnet, claude-3-opus, llama-3-70b, llama-3-8b, llama-2-13b, llama-3.1-405b, llama-3.1-70b, llama-3.1-8b, llamaguard-2-8b, llamaguard-7b, llama-3.2-90b, mixtral-8x7b mixtral-8x22b, mistral-7b, qwen-1.5-7b, qwen-1.5-14b, qwen-1.5-72b, qwen-1.5-110b, qwen-2-72b, gemma-2b, gemma-2-9b, gemma-2-27b, gemini-flash, gemini-pro, deepseek, mixtral-8x7b-dpo, yi-34b, wizardlm-2-8x22b, solar-10.7b, mythomax-l2-13b, cosmosrp`|`flux, flux-realism', flux-anime, flux-3d, flux-disney, flux-pixel, flux-4o, any-dark, dalle-3`|❌|✔||❌|
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|[allyfy.chat](https://allyfy.chat/)|`g4f.Provider.Allyfy`|`gpt-3.5-turbo`|❌|❌|✔||❌|
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|[openchat.team](https://openchat.team/)|`g4f.Provider.Aura`|✔|❌|❌|?||❌|
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|[bing.com](https://bing.com/chat)|`g4f.Provider.Bing`|`gpt-4`|✔|`gpt-4-vision`|✔||❌+✔|
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|[bing.com/images](https://www.bing.com/images/create)|`g4f.Provider.BingCreateImages`|`❌|✔|❌|❌||✔|
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|[chat18.aichatos8.com](https://chat18.aichatos8.com)|`g4f.Provider.Binjie`|`gpt-4`|❌|❌|✔||❌|
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|[chat.bixin123.com](https://chat.bixin123.com)|`g4f.Provider.Bixin123`|`gpt-3.5-turbo, gpt-4-turbo, qwen-turbo`|❌|❌||||
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|[blackbox.ai](https://www.blackbox.ai)|`g4f.Provider.Blackbox`|`blackbox, gemini-flash, llama-3.1-8b, llama-3.1-70b, llama-3.1-405b, gpt-4o, gemini-pro, claude-3.5-sonnet`|`flux`|✔|✔||❌|
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|[blackbox.ai](https://www.blackbox.ai)|`g4f.Provider.Blackbox`|`blackbox, gemini-flash, llama-3.1-8b, llama-3.1-70b, gpt-4o, gemini-pro, claude-3.5-sonnet`|`flux`|✔|✔||❌|
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|[chatgot.one](https://www.chatgot.one/)|`g4f.Provider.ChatGot`|`gemini-pro`|❌|❌|✔||❌|
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|[chatgpt.com](https://chatgpt.com)|`g4f.Provider.ChatGpt`|`?`|`?`|`?`|?| |❌|
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|[chatgpt.es](https://chatgpt.es)|`g4f.Provider.ChatGptEs`|`gpt-4o, gpt-4o-mini`|❌|❌|✔||❌|
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|[chatgpt4online.org](https://chatgpt4online.org)|`g4f.Provider.Chatgpt4Online`|`gpt-4`|❌|❌|✔||❌|
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|[chatgpt4o.one](https://chatgpt4o.one)|`g4f.Provider.Chatgpt4o`|`gpt-4o-mini`|❌|❌|❌||❌|
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|[chatgpt4o.one](https://chatgpt4o.one)|`g4f.Provider.Chatgpt4o`|✔|❌|❌|❌||❌|
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|[chatgptfree.ai](https://chatgptfree.ai)|`g4f.Provider.ChatgptFree`|`gpt-4o-mini`|❌|❌|?||❌|
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|[app.chathub.gg](https://app.chathub.gg)|`g4f.Provider.ChatHub`|`llama-3.1-8b, mixtral-8x7b, gemma-2, sonar-online`|❌|❌|✔||❌|
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|[duckduckgo.com](https://duckduckgo.com/duckchat/v1/chat)|`g4f.Provider.DDG`|`gpt-4o-mini, claude-3-haiku, llama-3.1-70b, mixtral-8x7b`|❌|❌|✔||❌|
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@ -43,7 +42,7 @@
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|[developers.sber.ru](https://developers.sber.ru/gigachat)|`g4f.Provider.GigaChat`|✔|❌|❌|✔||✔|
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|[gprochat.com](https://gprochat.com)|`g4f.Provider.GPROChat`|`gemini-pro`|❌|❌|✔||❌|
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|[console.groq.com/playground](https://console.groq.com/playground)|`g4f.Provider.Groq`|✔|❌|❌|?||✔|
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|[huggingface.co/chat](https://huggingface.co/chat)|`g4f.Provider.HuggingChat`|`llama-3.1-70b, command-r-plus, mixtral-8x7b, mixtral-8x7b-dpo, mistral-7b, phi-3-mini-4k`|❌|❌|✔||❌|
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|[huggingface.co/chat](https://huggingface.co/chat)|`g4f.Provider.HuggingChat`|`llama-3.1-70b, command-r-plus, qwen-2-72b, llama-3.2-11b, hermes-3, mistral-nemo, phi-3.5-mini`|❌|❌|✔||❌|
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|[huggingface.co](https://huggingface.co/chat)|`g4f.Provider.HuggingFace`|✔|❌|❌|✔||❌|
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|[koala.sh/chat](https://koala.sh/chat)|`g4f.Provider.Koala`|`gpt-4o-mini`|❌|❌|?||❌|
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|[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`|❌|❌|✔||❌|
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@ -82,10 +81,10 @@
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|Model|Base Provider|Provider|Website|
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|--|--|--|-|
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|gpt-3|OpenAI|1+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-base)|
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|gpt-3.5-turbo|OpenAI|6+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-3-5-turbo)|
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|gpt-4|OpenAI|6+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)|
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|gpt-4-turbo|OpenAI|2+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)|
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|gpt-4o-mini|OpenAI|12+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4o-mini)|
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|gpt-3.5-turbo|OpenAI|4+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-3-5-turbo)|
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|gpt-4|OpenAI|28+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)|
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|gpt-4-turbo|OpenAI|4+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)|
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|gpt-4o-mini|OpenAI|11+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4o-mini)|
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|gpt-4o|OpenAI|6+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4o)|
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|llama-2-13b|Meta Llama|1+ Providers|[llama.com](https://www.llama.com/llama2/)|
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|llama-3|Meta Llama|4+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3/)|
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@ -94,26 +93,30 @@
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|llama-3.1|Meta Llama|16+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|
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|llama-3.1-8b|Meta Llama|5+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|
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|llama-3.1-70b|Meta Llama|9+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|
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|llama-3.1-405b|Meta Llama|3+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|
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|llama-3.1-405b|Meta Llama|2+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|
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|llama-3.2-90b|Meta Llama|1+ Providers|[ai.meta.com](https://ai.meta.com/blog/llama-3-2-connect-2024-vision-edge-mobile-devices/)|
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|llamaguard-7b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/LlamaGuard-7b)|
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|llamaguard-2-8b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/Meta-Llama-Guard-2-8B)|
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|mistral-7b|Mistral AI|3+ Providers|[mistral.ai](https://mistral.ai/news/announcing-mistral-7b/)|
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|mixtral-8x7b|Mistral AI|6+ Providers|[mistral.ai](https://mistral.ai/news/mixtral-of-experts/)|
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|mixtral-8x22b|Mistral AI|2+ Providers|[mistral.ai](https://mistral.ai/news/mixtral-8x22b/)|
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|mixtral-8x7b-dpo|NousResearch|2+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO)|
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|mixtral-8x7b-dpo|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO)|
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|gemini|Google DeepMind|9+ Providers|[deepmind.google](http://deepmind.google/technologies/gemini/)|
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|gemini-flash|Google DeepMind|3+ Providers|[deepmind.google](https://deepmind.google/technologies/gemini/flash/)|
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|gemini-pro|Google DeepMind|6+ Providers|[deepmind.google](https://deepmind.google/technologies/gemini/pro/)|
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|gemma-2b|Google|4+ Providers|[huggingface.co](https://huggingface.co/google/gemma-2b)|
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|gemma-2b-9b|Google|1+ Providers|[huggingface.co](https://huggingface.co/google/gemma-2-9b)|
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|gemma-2b-27b|Google|2+ Providers|[huggingface.co](https://huggingface.co/google/gemma-2-27b)|
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|gemma-2|Google|1+ Providers|[huggingface.co](https://huggingface.co/blog/gemma2)|
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|claude-2|Anthropic|1+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-2)|
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|gemma-2|Google|2+ Providers|[huggingface.co](https://huggingface.co/blog/gemma2)|
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|gemma_2_27b|Google|1+ Providers|[huggingface.co](https://huggingface.co/blog/gemma2)|
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|claude-2|Anthropic|2+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-2)|
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|claude-2.0|Anthropic|1+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-2)|
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|claude-3|Anthropic|5+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-family)|
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|claude-3-haiku|Anthropic|2+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-haiku)|
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|claude-3-sonnet|Anthropic|1+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-5-sonnet)|
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|claude-3-opus|Anthropic|1+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-family)|
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|claude-3.5|Anthropic|2+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-5-sonnet)|
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|claude-3.5-sonnet|Anthropic|1+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-5-sonnet)|
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|claude-3|Anthropic|7+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-family)|
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|claude-3-haiku|Anthropic|3+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-haiku)|
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|claude-3-sonnet|Anthropic|2+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-family)|
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|claude-3-opus|Anthropic|2+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-family)|
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|claude-3.5|Anthropic|4+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-5-sonnet)|
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|claude-3.5-sonnet|Anthropic|3+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-5-sonnet)|
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|blackbox|Blackbox AI|1+ Providers|[docs.blackbox.chat](https://docs.blackbox.chat/blackbox-ai-1)|
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|yi-34b|01-ai|1+ Providers|[huggingface.co](https://huggingface.co/01-ai/Yi-34B)|
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|yi-1.5-9b|01-ai|1+ Providers|[huggingface.co](https://huggingface.co/01-ai/Yi-1.5-9B)|
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@ -121,9 +124,10 @@
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|phi-3-medium-4k|Microsoft|1+ Providers|[huggingface.co](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct)|
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|dbrx-instruct|Databricks|1+ Providers|[huggingface.co](https://huggingface.co/databricks/dbrx-instruct)|
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|command-r-plus|CohereForAI|1+ Providers|[docs.cohere.com](https://docs.cohere.com/docs/command-r-plus)|
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|sparkdesk-v1.1|iFlytek|2+ Providers|[xfyun.cn](https://www.xfyun.cn/doc/spark/Guide.html)|
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|qwen|Qwen|7+ Providers|[huggingface.co](https://huggingface.co/Qwen)|
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|qwen-1.5-14b|Qwen|1+ Providers|[huggingface.co](https://huggingface.co/Qwen/Qwen1.5-14B)|
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|sparkdesk-v1.1|iFlytek|1+ Providers|[xfyun.cn](https://www.xfyun.cn/doc/spark/Guide.html)|
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|qwen|Qwen|6+ Providers|[huggingface.co](https://huggingface.co/Qwen)|
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|qwen-1.5-14b|Qwen|2+ Providers|[huggingface.co](https://huggingface.co/Qwen/Qwen1.5-14B)|
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|qwen-1.5-7b|Qwen|1+ Providers|[huggingface.co](https://huggingface.co/Qwen/Qwen1.5-7B)|
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|qwen-1.5-72b|Qwen|1+ Providers|[huggingface.co](https://huggingface.co/Qwen/Qwen1.5-72B)|
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|qwen-2-72b|Qwen|2+ Providers|[huggingface.co](https://huggingface.co/Qwen/Qwen2-72B)|
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|qwen-turbo|Qwen|1+ Providers|[qwenlm.github.io](https://qwenlm.github.io/blog/qwen2.5/)|
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@ -148,6 +152,8 @@
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|grok-2|x.ai|1+ Providers|[x.ai](https://x.ai/blog/grok-2)|
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|sonar-online|Perplexity AI|2+ Providers|[docs.perplexity.ai](https://docs.perplexity.ai/)|
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|sonar-chat|Perplexity AI|1+ Providers|[docs.perplexity.ai](https://docs.perplexity.ai/)|
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|mythomax-l2-13b|Gryphe|1+ Providers|[huggingface.co](https://huggingface.co/Gryphe/MythoMax-L2-13b)|
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|cosmosrp|Gryphe|1+ Providers|[huggingface.co](https://huggingface.co/PawanKrd/CosmosRP-8k)|
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---
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### ImageModel
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|Model|Base Provider|Provider|Website|
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@ -1,76 +1,199 @@
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from __future__ import annotations
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from aiohttp import ClientSession, ClientResponseError
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import random
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import json
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from aiohttp import ClientSession
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from ..typing import AsyncResult, Messages
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from ..image import ImageResponse
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from .helper import format_prompt
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from ..errors import ResponseStatusError
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def split_long_message(message: str, max_length: int = 4000) -> list[str]:
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return [message[i:i+max_length] for i in range(0, len(message), max_length)]
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class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://api.airforce"
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text_api_endpoint = "https://api.airforce/chat/completions"
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image_api_endpoint = "https://api.airforce/imagine2"
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text_api_endpoint = "https://api.airforce/chat/completions"
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working = True
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default_model = 'llama-3-70b-chat'
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supports_gpt_35_turbo = True
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supports_gpt_4 = True
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supports_stream = True
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supports_system_message = True
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supports_message_history = True
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default_model = 'llama-3-70b-chat'
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text_models = [
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# Open source models
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'llama-2-13b-chat',
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'llama-3-70b-chat',
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'llama-3-70b-chat-turbo',
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'llama-3-70b-chat-lite',
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'llama-3-8b-chat',
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'llama-3-8b-chat-turbo',
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'llama-3-8b-chat-lite',
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'llama-3.1-405b-turbo',
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'llama-3.1-70b-turbo',
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'llama-3.1-8b-turbo',
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'LlamaGuard-2-8b',
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'Llama-Guard-7b',
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'Meta-Llama-Guard-3-8B',
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'Mixtral-8x7B-Instruct-v0.1',
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||||
'Mixtral-8x22B-Instruct-v0.1',
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'Mistral-7B-Instruct-v0.1',
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'Mistral-7B-Instruct-v0.2',
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'Mistral-7B-Instruct-v0.3',
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'Qwen1.5-72B-Chat',
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'Qwen1.5-110B-Chat',
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'Qwen2-72B-Instruct',
|
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'gemma-2b-it',
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'gemma-2-9b-it',
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'gemma-2-27b-it',
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'dbrx-instruct',
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'deepseek-llm-67b-chat',
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'Nous-Hermes-2-Mixtral-8x7B-DPO',
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||||
'Nous-Hermes-2-Yi-34B',
|
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'WizardLM-2-8x22B',
|
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'SOLAR-10.7B-Instruct-v1.0',
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'StripedHyena-Nous-7B',
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'sparkdesk',
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|
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# Other models
|
||||
'chatgpt-4o-latest',
|
||||
'gpt-4',
|
||||
'gpt-4-turbo',
|
||||
'gpt-4o-mini-2024-07-18',
|
||||
'gpt-4o-mini',
|
||||
'gpt-4o',
|
||||
'gpt-3.5-turbo',
|
||||
'gpt-3.5-turbo-0125',
|
||||
'gpt-3.5-turbo-1106',
|
||||
'gpt-3.5-turbo-16k',
|
||||
'gpt-3.5-turbo-0613',
|
||||
'gpt-3.5-turbo-16k-0613',
|
||||
'gemini-1.5-flash',
|
||||
'gemini-1.5-pro',
|
||||
]
|
||||
|
||||
text_models = [
|
||||
# anthorpic
|
||||
'claude-3-haiku-20240307',
|
||||
'claude-3-sonnet-20240229',
|
||||
'claude-3-5-sonnet-20240620',
|
||||
'claude-3-opus-20240229',
|
||||
|
||||
# openai
|
||||
'chatgpt-4o-latest',
|
||||
'gpt-4',
|
||||
#'gpt-4-0613',
|
||||
'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',
|
||||
#'gpt-3.5-turbo-16k', # No response from the API.
|
||||
#'gpt-3.5-turbo-0613', # No response from the API.
|
||||
#'gpt-3.5-turbo-16k-0613', # No response from the API.
|
||||
'gpt-4o',
|
||||
#'o1-mini', # No response from the API.
|
||||
|
||||
# meta-llama
|
||||
'llama-3-70b-chat',
|
||||
'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-2-70b-chat', # Failed to load response after multiple retries.
|
||||
'llama-2-13b-chat',
|
||||
#'llama-2-7b-chat', # Failed to load response after multiple retries.
|
||||
'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',
|
||||
|
||||
# codellama
|
||||
#'CodeLlama-7b-Python-hf', # Failed to load response after multiple retries.
|
||||
#'CodeLlama-7b-Python',
|
||||
#'CodeLlama-13b-Python-hf', # Failed to load response after multiple retries.
|
||||
#'CodeLlama-34b-Python-hf', # Failed to load response after multiple retries.
|
||||
#'CodeLlama-70b-Python-hf', # Failed to load response after multiple retries.
|
||||
|
||||
# 01-ai
|
||||
#'Yi-34B-Chat', # Failed to load response after multiple retries.
|
||||
#'Yi-34B', # Failed to load response after multiple retries.
|
||||
#'Yi-6B', # Failed to load response after multiple retries.
|
||||
|
||||
# mistral-ai
|
||||
#'Mixtral-8x7B-v0.1',
|
||||
#'Mixtral-8x22B', # Failed to load response after multiple retries.
|
||||
'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',
|
||||
|
||||
# openchat
|
||||
#'openchat-3.5', # Failed to load response after multiple retries.
|
||||
|
||||
# wizardlm
|
||||
#'WizardLM-13B-V1.2', # Failed to load response after multiple retries.
|
||||
#'WizardCoder-Python-34B-V1.0', # Failed to load response after multiple retries.
|
||||
|
||||
# qwen
|
||||
#'Qwen1.5-0.5B-Chat', # Failed to load response after multiple retries.
|
||||
#'Qwen1.5-1.8B-Chat', # Failed to load response after multiple retries.
|
||||
#'Qwen1.5-4B-Chat', # Failed to load response after multiple retries.
|
||||
'Qwen1.5-7B-Chat',
|
||||
'Qwen1.5-14B-Chat',
|
||||
'Qwen1.5-72B-Chat',
|
||||
'Qwen1.5-110B-Chat',
|
||||
'Qwen2-72B-Instruct',
|
||||
|
||||
# google
|
||||
'gemma-2b-it',
|
||||
#'gemma-7b-it', # Failed to load response after multiple retries.
|
||||
#'gemma-2b', # Failed to load response after multiple retries.
|
||||
#'gemma-7b', # Failed to load response after multiple retries.
|
||||
'gemma-2-9b-it', # fix bug
|
||||
'gemma-2-27b-it',
|
||||
|
||||
# gemini
|
||||
'gemini-1.5-flash',
|
||||
'gemini-1.5-pro',
|
||||
|
||||
# databricks
|
||||
'dbrx-instruct',
|
||||
|
||||
# lmsys
|
||||
#'vicuna-7b-v1.5', # Failed to load response after multiple retries.
|
||||
#'vicuna-13b-v1.5', # Failed to load response after multiple retries.
|
||||
|
||||
# cognitivecomputations
|
||||
#'dolphin-2.5-mixtral-8x7b', # Failed to load response after multiple retries.
|
||||
|
||||
# deepseek-ai
|
||||
#'deepseek-coder-33b-instruct', # No response from the API.
|
||||
#'deepseek-coder-67b-instruct', # Failed to load response after multiple retries.
|
||||
'deepseek-llm-67b-chat',
|
||||
|
||||
# NousResearch
|
||||
#'Nous-Capybara-7B-V1p9', # Failed to load response after multiple retries.
|
||||
'Nous-Hermes-2-Mixtral-8x7B-DPO',
|
||||
#'Nous-Hermes-2-Mixtral-8x7B-SFT', # Failed to load response after multiple retries.
|
||||
#'Nous-Hermes-llama-2-7b', # Failed to load response after multiple retries.
|
||||
#'Nous-Hermes-Llama2-13b', # Failed to load response after multiple retries.
|
||||
'Nous-Hermes-2-Yi-34B',
|
||||
|
||||
# Open-Orca
|
||||
#'Mistral-7B-OpenOrca', # Failed to load response after multiple retries.
|
||||
|
||||
# togethercomputer
|
||||
#'alpaca-7b', # Failed to load response after multiple retries.
|
||||
|
||||
# teknium
|
||||
#'OpenHermes-2-Mistral-7B', # Failed to load response after multiple retries.
|
||||
#'OpenHermes-2.5-Mistral-7B', # Failed to load response after multiple retries.
|
||||
|
||||
# microsoft
|
||||
'WizardLM-2-8x22B',
|
||||
|
||||
# Nexusflow
|
||||
#'NexusRaven-V2-13B', # Failed to load response after multiple retries.
|
||||
|
||||
# Phind
|
||||
#'Phind-CodeLlama-34B-v2', # Failed to load response after multiple retries.
|
||||
|
||||
# Snoflake
|
||||
#'snowflake-arctic-instruct', # No response from the API.
|
||||
|
||||
# upstage
|
||||
'SOLAR-10.7B-Instruct-v1.0',
|
||||
|
||||
# togethercomputer
|
||||
#'StripedHyena-Hessian-7B', # Failed to load response after multiple retries.
|
||||
#'StripedHyena-Nous-7B', # Failed to load response after multiple retries.
|
||||
#'Llama-2-7B-32K-Instruct', # Failed to load response after multiple retries.
|
||||
#'CodeLlama-13b-Instruct', # No response from the API.
|
||||
#'evo-1-131k-base', # Failed to load response after multiple retries.
|
||||
#'OLMo-7B-Instruct', # Failed to load response after multiple retries.
|
||||
|
||||
# garage-bAInd
|
||||
#'Platypus2-70B-instruct', # Failed to load response after multiple retries.
|
||||
|
||||
# snorkelai
|
||||
#'Snorkel-Mistral-PairRM-DPO', # Failed to load response after multiple retries.
|
||||
|
||||
# Undi95
|
||||
#'ReMM-SLERP-L2-13B', # Failed to load response after multiple retries.
|
||||
|
||||
# Gryphe
|
||||
'MythoMax-L2-13b',
|
||||
|
||||
# Autism
|
||||
#'chronos-hermes-13b', # Failed to load response after multiple retries.
|
||||
|
||||
# Undi95
|
||||
#'Toppy-M-7B', # Failed to load response after multiple retries.
|
||||
|
||||
# iFlytek
|
||||
#'sparkdesk', # Failed to load response after multiple retries.
|
||||
|
||||
# pawan
|
||||
'cosmosrp',
|
||||
|
||||
]
|
||||
image_models = [
|
||||
'flux',
|
||||
'flux-realism',
|
||||
@ -85,158 +208,206 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
|
||||
models = [
|
||||
*text_models,
|
||||
*image_models
|
||||
*image_models,
|
||||
]
|
||||
model_aliases = {
|
||||
# Open source models
|
||||
"llama-2-13b": "llama-2-13b-chat",
|
||||
# anthorpic
|
||||
"claude-3-haiku": "claude-3-haiku-20240307",
|
||||
"claude-3-sonnet": "claude-3-sonnet-20240229",
|
||||
"claude-3-5-sonnet": "claude-3-5-sonnet-20240620",
|
||||
"claude-3-opus": "claude-3-opus-20240229",
|
||||
|
||||
# openai
|
||||
"gpt-4o": "chatgpt-4o-latest",
|
||||
"gpt-4o-mini": "gpt-4o-mini-2024-07-18",
|
||||
"gpt-3.5-turbo": "gpt-3.5-turbo-0125",
|
||||
"gpt-3.5-turbo": "gpt-3.5-turbo-1106",
|
||||
|
||||
# meta-llama
|
||||
"llama-3-70b": "llama-3-70b-chat",
|
||||
"llama-3-70b": "llama-3-70b-chat-turbo",
|
||||
"llama-3-70b": "llama-3-70b-chat-lite",
|
||||
"llama-3-8b": "llama-3-8b-chat",
|
||||
"llama-3-8b": "llama-3-8b-chat-turbo",
|
||||
"llama-3-70b": "llama-3-70b-chat-lite",
|
||||
"llama-3-8b": "llama-3-8b-chat-lite",
|
||||
"llama-2-13b": "llama-2-13b-chat",
|
||||
"llama-3.1-405b": "llama-3.1-405b-turbo",
|
||||
"llama-3.1-70b": "llama-3.1-70b-turbo",
|
||||
"llama-3.1-8b": "llama-3.1-8b-turbo",
|
||||
"llamaguard-2-8b": "LlamaGuard-2-8b",
|
||||
"llamaguard-7b": "Llama-Guard-7b",
|
||||
"llama-3.2-90b": "Llama-3.2-90B-Vision-Instruct-Turbo",
|
||||
|
||||
# mistral-ai
|
||||
"mixtral-8x7b": "Mixtral-8x7B-Instruct-v0.1",
|
||||
"mixtral-8x22b": "Mixtral-8x22B-Instruct-v0.1",
|
||||
"mistral-7b": "Mistral-7B-Instruct-v0.1",
|
||||
"mistral-7b": "Mistral-7B-Instruct-v0.2",
|
||||
"mistral-7b": "Mistral-7B-Instruct-v0.3",
|
||||
"mixtral-8x7b-dpo": "Nous-Hermes-2-Mixtral-8x7B-DPO",
|
||||
|
||||
# qwen
|
||||
"qwen-1.5-7b": "Qwen1.5-7B-Chat",
|
||||
"qwen-1.5-14b": "Qwen1.5-14B-Chat",
|
||||
"qwen-1.5-72b": "Qwen1.5-72B-Chat",
|
||||
"qwen-1.5-110b": "Qwen1.5-110B-Chat",
|
||||
"qwen-2-72b": "Qwen2-72B-Instruct",
|
||||
"gemma-2b": "gemma-2b-it",
|
||||
"gemma-2b-9b": "gemma-2-9b-it",
|
||||
"gemma-2b-27b": "gemma-2-27b-it",
|
||||
"deepseek": "deepseek-llm-67b-chat",
|
||||
"yi-34b": "Nous-Hermes-2-Yi-34B",
|
||||
"wizardlm-2-8x22b": "WizardLM-2-8x22B",
|
||||
"solar-10-7b": "SOLAR-10.7B-Instruct-v1.0",
|
||||
"sh-n-7b": "StripedHyena-Nous-7B",
|
||||
"sparkdesk-v1.1": "sparkdesk",
|
||||
|
||||
# Other models
|
||||
"gpt-4o": "chatgpt-4o-latest",
|
||||
"gpt-4o-mini": "gpt-4o-mini-2024-07-18",
|
||||
"gpt-3.5-turbo": "gpt-3.5-turbo-0125",
|
||||
"gpt-3.5-turbo": "gpt-3.5-turbo-1106",
|
||||
"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",
|
||||
# google
|
||||
"gemma-2b": "gemma-2b-it",
|
||||
"gemma-2-9b": "gemma-2-9b-it",
|
||||
"gemma-2-27b": "gemma-2-27b-it",
|
||||
|
||||
# gemini
|
||||
"gemini-flash": "gemini-1.5-flash",
|
||||
"gemini-pro": "gemini-1.5-pro",
|
||||
|
||||
# Image models
|
||||
"dalle-3": "dall-e-3",
|
||||
# deepseek-ai
|
||||
"deepseek": "deepseek-llm-67b-chat",
|
||||
|
||||
# NousResearch
|
||||
"mixtral-8x7b-dpo": "Nous-Hermes-2-Mixtral-8x7B-DPO",
|
||||
"yi-34b": "Nous-Hermes-2-Yi-34B",
|
||||
|
||||
# microsoft
|
||||
"wizardlm-2-8x22b": "WizardLM-2-8x22B",
|
||||
|
||||
# upstage
|
||||
"solar-10.7b": "SOLAR-10.7B-Instruct-v1.0",
|
||||
|
||||
# Gryphe
|
||||
"mythomax-l2-13b": "MythoMax-L2-13b",
|
||||
}
|
||||
|
||||
@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 the model is an image model, use the image API
|
||||
if model in cls.image_models:
|
||||
async for result in cls._generate_image(model, messages, proxy, seed, size):
|
||||
yield result
|
||||
# If the model is a text model, use the text API
|
||||
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",
|
||||
"content-type": "application/json",
|
||||
"origin": "https://api.airforce",
|
||||
"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36",
|
||||
"authorization": "Bearer null",
|
||||
"cache-control": "no-cache",
|
||||
"pragma": "no-cache",
|
||||
"priority": "u=1, i",
|
||||
"referer": "https://llmplayground.net/",
|
||||
"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": "cross-site",
|
||||
"origin": "https://llmplayground.net",
|
||||
"user-agent": "Mozilla/5.0"
|
||||
}
|
||||
|
||||
if model in cls.image_models:
|
||||
async for item in cls.generate_image(model, messages, headers, proxy, **kwargs):
|
||||
yield item
|
||||
else:
|
||||
async for item in cls.generate_text(model, messages, headers, proxy, **kwargs):
|
||||
yield item
|
||||
if seed is None:
|
||||
seed = random.randint(0, 100000)
|
||||
|
||||
@classmethod
|
||||
async def generate_text(cls, model: str, messages: Messages, headers: dict, proxy: str, **kwargs) -> AsyncResult:
|
||||
async with ClientSession() as session:
|
||||
data = {
|
||||
"messages": [{"role": "user", "content": message['content']} for message in messages],
|
||||
# Assume the first message is the prompt for the image
|
||||
prompt = messages[0]['content']
|
||||
|
||||
async with ClientSession(headers=headers) as session:
|
||||
params = {
|
||||
"model": model,
|
||||
"max_tokens": kwargs.get('max_tokens', 4096),
|
||||
"temperature": kwargs.get('temperature', 1),
|
||||
"top_p": kwargs.get('top_p', 1),
|
||||
"stream": True
|
||||
"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()
|
||||
|
||||
try:
|
||||
async with session.post(cls.text_api_endpoint, json=data, headers=headers, proxy=proxy) as response:
|
||||
response.raise_for_status()
|
||||
async for line in response.content:
|
||||
if line:
|
||||
line = line.decode('utf-8').strip()
|
||||
if line.startswith("data: "):
|
||||
if line == "data: [DONE]":
|
||||
break
|
||||
try:
|
||||
data = json.loads(line[6:])
|
||||
if 'choices' in data and len(data['choices']) > 0:
|
||||
delta = data['choices'][0].get('delta', {})
|
||||
if 'content' in delta:
|
||||
content = delta['content']
|
||||
if "One message exceeds the 1000chars per message limit" in content:
|
||||
raise ResponseStatusError(
|
||||
"Message too long",
|
||||
400,
|
||||
"Please try a shorter message."
|
||||
)
|
||||
yield content
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
except ResponseStatusError as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
raise ResponseStatusError(str(e), 500, "An unexpected error occurred")
|
||||
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_image(cls, model: str, messages: Messages, headers: dict, proxy: str, **kwargs) -> AsyncResult:
|
||||
prompt = messages[-1]['content'] if messages else ""
|
||||
params = {
|
||||
"prompt": prompt,
|
||||
"size": kwargs.get("size", "1:1"),
|
||||
"seed": kwargs.get("seed"),
|
||||
"model": model
|
||||
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"
|
||||
}
|
||||
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(cls.image_api_endpoint, params=params, proxy=proxy) as response:
|
||||
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()
|
||||
content = await response.read()
|
||||
|
||||
if response.content_type.startswith('image/'):
|
||||
image_url = str(response.url)
|
||||
yield ImageResponse(image_url, prompt)
|
||||
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:
|
||||
try:
|
||||
text = content.decode('utf-8', errors='ignore')
|
||||
raise ResponseStatusError("Image generation failed", response.status, text)
|
||||
except Exception as decode_error:
|
||||
raise ResponseStatusError("Decoding error", 500, str(decode_error))
|
||||
except ClientResponseError as e:
|
||||
raise ResponseStatusError(f"HTTP {e.status}", e.status, e.message)
|
||||
except Exception as e:
|
||||
raise ResponseStatusError("Unexpected error", 500, str(e))
|
||||
json_data = await response.json()
|
||||
content = json_data['choices'][0]['message']['content']
|
||||
part_response = content
|
||||
|
||||
full_response += part_response
|
||||
yield full_response
|
||||
|
||||
@classmethod
|
||||
def _format_messages(cls, messages: Messages) -> str:
|
||||
"""Formats messages for text generation."""
|
||||
return " ".join([msg['content'] for msg in messages])
|
||||
|
||||
@ -9,8 +9,8 @@ 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
|
||||
|
||||
@ -53,7 +53,7 @@ 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:
|
||||
|
||||
@ -1,94 +0,0 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from aiohttp import ClientSession
|
||||
import json
|
||||
import random
|
||||
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', '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
|
||||
def generate_fingerprint(cls) -> str:
|
||||
return str(random.randint(100000000, 999999999))
|
||||
|
||||
@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": cls.generate_fingerprint(),
|
||||
"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 ""
|
||||
@ -25,18 +25,10 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
'llama-3.1-70b',
|
||||
'llama-3.1-405b',
|
||||
'ImageGenerationLV45LJp',
|
||||
'GPT-4o',
|
||||
'Gemini-PRO',
|
||||
'Claude-Sonnet-3.5',
|
||||
'gpt-4o',
|
||||
'gemini-pro',
|
||||
'claude-sonnet-3.5',
|
||||
]
|
||||
|
||||
model_aliases = {
|
||||
"gemini-flash": "gemini-1.5-flash",
|
||||
"flux": "ImageGenerationLV45LJp",
|
||||
"gpt-4o": "GPT-4o",
|
||||
"gemini-pro": "Gemini-PRO",
|
||||
"claude-3.5-sonnet": "Claude-Sonnet-3.5",
|
||||
}
|
||||
|
||||
agentMode = {
|
||||
'ImageGenerationLV45LJp': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"},
|
||||
@ -51,9 +43,14 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
}
|
||||
|
||||
userSelectedModel = {
|
||||
"GPT-4o": "GPT-4o",
|
||||
"Gemini-PRO": "Gemini-PRO",
|
||||
'Claude-Sonnet-3.5': "Claude-Sonnet-3.5",
|
||||
"gpt-4o": "gpt-4o",
|
||||
"gemini-pro": "gemini-pro",
|
||||
'claude-sonnet-3.5': "claude-sonnet-3.5",
|
||||
}
|
||||
|
||||
model_aliases = {
|
||||
"gemini-flash": "gemini-1.5-flash",
|
||||
"flux": "ImageGenerationLV45LJp",
|
||||
}
|
||||
|
||||
@classmethod
|
||||
@ -119,8 +116,9 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
"agentMode": {},
|
||||
"trendingAgentMode": {},
|
||||
"userSelectedModel": None,
|
||||
"userSystemPrompt": None,
|
||||
"isMicMode": False,
|
||||
"maxTokens": 99999999,
|
||||
"maxTokens": 1024,
|
||||
"playgroundTopP": 0.9,
|
||||
"playgroundTemperature": 0.5,
|
||||
"isChromeExt": False,
|
||||
|
||||
@ -134,11 +134,21 @@ class ChatGpt(AbstractProvider, ProviderModelMixin):
|
||||
}
|
||||
|
||||
response = session.post('https://chatgpt.com/backend-anon/sentinel/chat-requirements',
|
||||
headers=headers, json={'p': pow_req}).json()
|
||||
headers=headers, json={'p': pow_req})
|
||||
|
||||
turnstile = response.get('turnstile', {})
|
||||
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.get('proofofwork', {})
|
||||
pow_conf = response_data.get('proofofwork', {})
|
||||
|
||||
if turnstile_required:
|
||||
turnstile_dx = turnstile.get('dx')
|
||||
@ -146,7 +156,7 @@ class ChatGpt(AbstractProvider, ProviderModelMixin):
|
||||
|
||||
headers = headers | {
|
||||
'openai-sentinel-turnstile-token' : turnstile_token,
|
||||
'openai-sentinel-chat-requirements-token': response.get('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
|
||||
)
|
||||
@ -187,20 +197,29 @@ class ChatGpt(AbstractProvider, ProviderModelMixin):
|
||||
'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:
|
||||
if 'DONE' in line.decode():
|
||||
break
|
||||
|
||||
data = json.loads(line.decode()[6:])
|
||||
if data.get('message').get('author').get('role') == 'assistant':
|
||||
tokens = (data.get('message').get('content').get('parts')[0])
|
||||
|
||||
yield tokens.replace(replace, '')
|
||||
|
||||
replace = tokens
|
||||
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
|
||||
|
||||
@ -17,6 +17,7 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
|
||||
'meta-llama/Meta-Llama-3.1-70B-Instruct',
|
||||
'CohereForAI/c4ai-command-r-plus-08-2024',
|
||||
'Qwen/Qwen2.5-72B-Instruct',
|
||||
'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',
|
||||
@ -26,6 +27,7 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
|
||||
"llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct",
|
||||
"command-r-plus": "CohereForAI/c4ai-command-r-plus-08-2024",
|
||||
"qwen-2-72b": "Qwen/Qwen2.5-72B-Instruct",
|
||||
"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",
|
||||
|
||||
@ -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",
|
||||
|
||||
@ -1,12 +1,11 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from aiohttp import ClientSession, ClientResponseError
|
||||
import base64
|
||||
import re
|
||||
from aiohttp import ClientSession, ClientResponseError
|
||||
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"
|
||||
@ -27,18 +26,20 @@ class LiteIcoding(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
}
|
||||
|
||||
bearer_tokens = [
|
||||
"aa3020ee873e40cb8b3f515a0708ebc4",
|
||||
"5d69cd271b144226ac1199b3c849a566",
|
||||
"62977f48a95844f8853a953679401850",
|
||||
"d815b091959e42dd8b7871dfaf879485"
|
||||
"NWQ2OWNkMjcxYjE0NDIyNmFjMTE5OWIzYzg0OWE1NjY=",
|
||||
"ZDgxNWIwOTU5NTk0ZTRkZDhiNzg3MWRmYWY4Nzk0ODU="
|
||||
]
|
||||
current_token_index = 0
|
||||
|
||||
@classmethod
|
||||
def decode_token(cls, encoded_token: str) -> str:
|
||||
return base64.b64decode(encoded_token).decode('utf-8')
|
||||
|
||||
@classmethod
|
||||
def get_next_bearer_token(cls):
|
||||
token = cls.bearer_tokens[cls.current_token_index]
|
||||
encoded_token = cls.bearer_tokens[cls.current_token_index]
|
||||
cls.current_token_index = (cls.current_token_index + 1) % len(cls.bearer_tokens)
|
||||
return token
|
||||
return cls.decode_token(encoded_token)
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
@ -95,9 +96,11 @@ class LiteIcoding(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
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()
|
||||
|
||||
@ -24,21 +24,18 @@ class MagickPen(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
|
||||
@classmethod
|
||||
async def fetch_api_credentials(cls) -> tuple:
|
||||
url = "https://magickpen.com/_nuxt/9e47cd7579e60a9d1f13.js"
|
||||
url = "https://magickpen.com/_nuxt/bf709a9ce19f14e18116.js"
|
||||
async with ClientSession() as session:
|
||||
async with session.get(url) as response:
|
||||
text = await response.text()
|
||||
|
||||
# Extract the necessary values from the file
|
||||
pattern = r'"X-API-Secret":"(\w+)"'
|
||||
match = re.search(pattern, text)
|
||||
X_API_SECRET = match.group(1) if match else None
|
||||
|
||||
# Generate timestamp and nonce
|
||||
timestamp = str(int(time.time() * 1000)) # in milliseconds
|
||||
timestamp = str(int(time.time() * 1000))
|
||||
nonce = str(random.random())
|
||||
|
||||
# Generate the signature
|
||||
s = ["TGDBU9zCgM", timestamp, nonce]
|
||||
s.sort()
|
||||
signature_string = ''.join(s)
|
||||
|
||||
@ -19,7 +19,6 @@ 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
|
||||
|
||||
@ -33,6 +33,12 @@ except NameError:
|
||||
except StopAsyncIteration:
|
||||
raise StopIteration
|
||||
|
||||
async def safe_aclose(generator):
|
||||
try:
|
||||
await generator.aclose()
|
||||
except Exception as e:
|
||||
logging.warning(f"Error while closing generator: {e}")
|
||||
|
||||
async def iter_response(
|
||||
response: AsyncIterator[str],
|
||||
stream: bool,
|
||||
@ -45,48 +51,56 @@ async def iter_response(
|
||||
completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28))
|
||||
idx = 0
|
||||
|
||||
async for chunk in response:
|
||||
if isinstance(chunk, FinishReason):
|
||||
finish_reason = chunk.reason
|
||||
break
|
||||
elif isinstance(chunk, BaseConversation):
|
||||
yield chunk
|
||||
continue
|
||||
try:
|
||||
async for chunk in response:
|
||||
if isinstance(chunk, FinishReason):
|
||||
finish_reason = chunk.reason
|
||||
break
|
||||
elif isinstance(chunk, BaseConversation):
|
||||
yield chunk
|
||||
continue
|
||||
|
||||
content += str(chunk)
|
||||
idx += 1
|
||||
content += str(chunk)
|
||||
idx += 1
|
||||
|
||||
if max_tokens is not None and idx >= max_tokens:
|
||||
finish_reason = "length"
|
||||
if max_tokens is not None and idx >= max_tokens:
|
||||
finish_reason = "length"
|
||||
|
||||
first, content, chunk = find_stop(stop, content, chunk if stream else None)
|
||||
first, content, chunk = find_stop(stop, content, chunk if stream else None)
|
||||
|
||||
if first != -1:
|
||||
finish_reason = "stop"
|
||||
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(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()))
|
||||
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()))
|
||||
finally:
|
||||
if hasattr(response, 'aclose'):
|
||||
await safe_aclose(response)
|
||||
|
||||
async def iter_append_model_and_provider(response: AsyncIterator) -> AsyncIterator:
|
||||
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
|
||||
try:
|
||||
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
|
||||
finally:
|
||||
if hasattr(response, 'aclose'):
|
||||
await safe_aclose(response)
|
||||
|
||||
class AsyncClient(BaseClient):
|
||||
def __init__(
|
||||
@ -158,8 +172,6 @@ class Completions:
|
||||
response = iter_append_model_and_provider(response)
|
||||
return response if stream else await anext(response)
|
||||
|
||||
|
||||
|
||||
class Chat:
|
||||
completions: Completions
|
||||
|
||||
@ -168,14 +180,18 @@ class Chat:
|
||||
|
||||
async def iter_image_response(response: AsyncIterator) -> Union[ImagesResponse, None]:
|
||||
logging.info("Starting iter_image_response")
|
||||
async for chunk in response:
|
||||
logging.info(f"Processing chunk: {chunk}")
|
||||
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
|
||||
try:
|
||||
async for chunk in response:
|
||||
logging.info(f"Processing chunk: {chunk}")
|
||||
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
|
||||
finally:
|
||||
if hasattr(response, 'aclose'):
|
||||
await safe_aclose(response)
|
||||
|
||||
async def create_image(client: AsyncClient, provider: ProviderType, prompt: str, model: str = "", **kwargs) -> AsyncIterator:
|
||||
logging.info(f"Creating image with provider: {provider}, model: {model}, prompt: {prompt}")
|
||||
@ -220,12 +236,25 @@ class Images:
|
||||
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)
|
||||
elif isinstance(response, str):
|
||||
image_response = ImageResponse([response], prompt)
|
||||
return self._process_image_response(image_response)
|
||||
generator = None
|
||||
try:
|
||||
generator = provider.create_async_generator(model, messages, **kwargs)
|
||||
async for response in generator:
|
||||
logging.debug(f"Received response: {type(response)}")
|
||||
if isinstance(response, ImageResponse):
|
||||
return self._process_image_response(response)
|
||||
elif isinstance(response, str):
|
||||
image_response = ImageResponse([response], prompt)
|
||||
return self._process_image_response(image_response)
|
||||
except RuntimeError as e:
|
||||
if "async generator ignored GeneratorExit" in str(e):
|
||||
logging.warning("Generator ignored GeneratorExit, handling gracefully")
|
||||
else:
|
||||
raise
|
||||
finally:
|
||||
if generator and hasattr(generator, 'aclose'):
|
||||
await safe_aclose(generator)
|
||||
logging.info("AsyncGeneratorProvider processing completed")
|
||||
elif hasattr(provider, 'create'):
|
||||
logging.info("Using provider's create method")
|
||||
async_create = asyncio.iscoroutinefunction(provider.create)
|
||||
@ -241,7 +270,7 @@ class Images:
|
||||
return self._process_image_response(image_response)
|
||||
elif hasattr(provider, 'create_completion'):
|
||||
logging.info("Using provider's create_completion method")
|
||||
response = await create_image(provider, prompt, model, **kwargs)
|
||||
response = await create_image(self.client, provider, prompt, model, **kwargs)
|
||||
async for chunk in response:
|
||||
if isinstance(chunk, ImageProviderResponse):
|
||||
logging.info("Found ImageProviderResponse")
|
||||
@ -277,12 +306,24 @@ class Images:
|
||||
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)
|
||||
generator = None
|
||||
try:
|
||||
generator = provider.create_async_generator(model, messages, image=image_data, **kwargs)
|
||||
async for response in generator:
|
||||
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)
|
||||
except RuntimeError as e:
|
||||
if "async generator ignored GeneratorExit" in str(e):
|
||||
logging.warning("Generator ignored GeneratorExit in create_variation, handling gracefully")
|
||||
else:
|
||||
raise
|
||||
finally:
|
||||
if generator and hasattr(generator, 'aclose'):
|
||||
await safe_aclose(generator)
|
||||
logging.info("AsyncGeneratorProvider processing completed in create_variation")
|
||||
elif hasattr(provider, 'create_variation'):
|
||||
if asyncio.iscoroutinefunction(provider.create_variation):
|
||||
response = await provider.create_variation(image, **kwargs)
|
||||
@ -296,5 +337,3 @@ class Images:
|
||||
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")
|
||||
|
||||
182
g4f/models.py
182
g4f/models.py
@ -9,10 +9,8 @@ from .Provider import (
|
||||
Allyfy,
|
||||
Bing,
|
||||
Binjie,
|
||||
Bixin123,
|
||||
Blackbox,
|
||||
ChatGpt,
|
||||
Chatgpt4o,
|
||||
Chatgpt4Online,
|
||||
ChatGptEs,
|
||||
ChatgptFree,
|
||||
@ -80,12 +78,16 @@ default = Model(
|
||||
ReplicateHome,
|
||||
Upstage,
|
||||
Blackbox,
|
||||
Bixin123,
|
||||
Binjie,
|
||||
Free2GPT,
|
||||
MagickPen,
|
||||
DeepInfraChat,
|
||||
LiteIcoding,
|
||||
Airforce,
|
||||
ChatHub,
|
||||
Nexra,
|
||||
ChatGptEs,
|
||||
ChatHub,
|
||||
])
|
||||
)
|
||||
|
||||
@ -106,7 +108,7 @@ gpt_35_turbo = Model(
|
||||
name = 'gpt-3.5-turbo',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = IterListProvider([
|
||||
Allyfy, Nexra, Bixin123, Airforce,
|
||||
Allyfy, Nexra, Airforce, Liaobots,
|
||||
])
|
||||
)
|
||||
|
||||
@ -115,7 +117,7 @@ gpt_4o = Model(
|
||||
name = 'gpt-4o',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = IterListProvider([
|
||||
Liaobots, Nexra, Airforce, Chatgpt4o, ChatGptEs,
|
||||
Liaobots, Nexra, ChatGptEs, Airforce,
|
||||
OpenaiChat
|
||||
])
|
||||
)
|
||||
@ -133,7 +135,7 @@ gpt_4_turbo = Model(
|
||||
name = 'gpt-4-turbo',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = IterListProvider([
|
||||
Nexra, Bixin123, Liaobots, Airforce, Bing
|
||||
Nexra, Liaobots, Airforce, Bing
|
||||
])
|
||||
)
|
||||
|
||||
@ -141,9 +143,8 @@ gpt_4 = Model(
|
||||
name = 'gpt-4',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = IterListProvider([
|
||||
Nexra, Binjie, Airforce,
|
||||
gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider,
|
||||
Chatgpt4Online, Bing, OpenaiChat,
|
||||
Nexra, Binjie, Airforce, Chatgpt4Online, Bing, OpenaiChat,
|
||||
gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider
|
||||
])
|
||||
)
|
||||
|
||||
@ -205,7 +206,7 @@ llama_3_1_70b = Model(
|
||||
llama_3_1_405b = Model(
|
||||
name = "llama-3.1-405b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = IterListProvider([Blackbox, DeepInfraChat, Airforce])
|
||||
best_provider = IterListProvider([DeepInfraChat, Blackbox, Airforce])
|
||||
)
|
||||
|
||||
llama_3_1 = Model(
|
||||
@ -214,12 +215,38 @@ llama_3_1 = Model(
|
||||
best_provider = IterListProvider([Nexra, llama_3_1_8b.best_provider, llama_3_1_70b.best_provider, llama_3_1_405b.best_provider,])
|
||||
)
|
||||
|
||||
# llama 3.2
|
||||
llama_3_2_11b = Model(
|
||||
name = "llama-3.2-11b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = IterListProvider([HuggingChat, HuggingFace])
|
||||
)
|
||||
|
||||
llama_3_2_90b = Model(
|
||||
name = "llama-3.2-90b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = IterListProvider([Airforce])
|
||||
)
|
||||
|
||||
# llamaguard
|
||||
llamaguard_7b = Model(
|
||||
name = "llamaguard-7b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = IterListProvider([Airforce])
|
||||
)
|
||||
|
||||
llamaguard_2_8b = Model(
|
||||
name = "llamaguard-2-8b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = IterListProvider([Airforce])
|
||||
)
|
||||
|
||||
|
||||
### Mistral ###
|
||||
mistral_7b = Model(
|
||||
name = "mistral-7b",
|
||||
base_provider = "Mistral",
|
||||
best_provider = IterListProvider([HuggingChat, DeepInfraChat, Airforce, HuggingFace, DeepInfra])
|
||||
best_provider = IterListProvider([DeepInfraChat, Airforce, HuggingFace, DeepInfra])
|
||||
)
|
||||
|
||||
mixtral_8x7b = Model(
|
||||
@ -245,7 +272,13 @@ mistral_nemo = Model(
|
||||
mixtral_8x7b_dpo = Model(
|
||||
name = "mixtral-8x7b-dpo",
|
||||
base_provider = "NousResearch",
|
||||
best_provider = Airforce
|
||||
best_provider = IterListProvider([Airforce])
|
||||
)
|
||||
|
||||
yi_34b = Model(
|
||||
name = "yi-34b",
|
||||
base_provider = "NousResearch",
|
||||
best_provider = IterListProvider([Airforce])
|
||||
)
|
||||
|
||||
hermes_3 = Model(
|
||||
@ -310,49 +343,56 @@ gemma_2b = Model(
|
||||
])
|
||||
)
|
||||
|
||||
# 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
|
||||
best_provider = IterListProvider([
|
||||
ChatHub,
|
||||
gemma_2_27b.best_provider,
|
||||
])
|
||||
)
|
||||
|
||||
|
||||
### Anthropic ###
|
||||
claude_2 = Model(
|
||||
name = 'claude-2',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = You
|
||||
)
|
||||
|
||||
claude_2_0 = Model(
|
||||
name = 'claude-2.0',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = Liaobots
|
||||
)
|
||||
|
||||
claude_2_1 = Model(
|
||||
name = 'claude-2.1',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = Liaobots
|
||||
)
|
||||
|
||||
claude_2 = Model(
|
||||
name = 'claude-2',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = IterListProvider([
|
||||
You,
|
||||
claude_2_1.best_provider,
|
||||
])
|
||||
)
|
||||
|
||||
# claude 3
|
||||
claude_3_opus = Model(
|
||||
name = 'claude-3-opus',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = Liaobots
|
||||
best_provider = IterListProvider([Airforce, Liaobots])
|
||||
)
|
||||
|
||||
claude_3_sonnet = Model(
|
||||
name = 'claude-3-sonnet',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = Liaobots
|
||||
best_provider = IterListProvider([Airforce, Liaobots])
|
||||
)
|
||||
|
||||
claude_3_haiku = Model(
|
||||
name = 'claude-3-haiku',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = IterListProvider([DDG, Liaobots])
|
||||
best_provider = IterListProvider([DDG, Airforce, Liaobots])
|
||||
)
|
||||
|
||||
claude_3 = Model(
|
||||
@ -367,7 +407,7 @@ claude_3 = Model(
|
||||
claude_3_5_sonnet = Model(
|
||||
name = 'claude-3.5-sonnet',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = IterListProvider([Blackbox, Liaobots])
|
||||
best_provider = IterListProvider([Blackbox, Airforce, Liaobots])
|
||||
)
|
||||
|
||||
claude_3_5 = Model(
|
||||
@ -417,15 +457,22 @@ command_r_plus = Model(
|
||||
sparkdesk_v1_1 = Model(
|
||||
name = 'sparkdesk-v1.1',
|
||||
base_provider = 'iFlytek',
|
||||
best_provider = IterListProvider([FreeChatgpt, Airforce])
|
||||
best_provider = IterListProvider([FreeChatgpt])
|
||||
)
|
||||
|
||||
|
||||
### Qwen ###
|
||||
# qwen 1
|
||||
qwen_1_5_7b = Model(
|
||||
name = 'qwen-1.5-7b',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
qwen_1_5_14b = Model(
|
||||
name = 'qwen-1.5-14b',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = FreeChatgpt
|
||||
best_provider = IterListProvider([FreeChatgpt, Airforce])
|
||||
)
|
||||
|
||||
qwen_1_5_72b = Model(
|
||||
@ -440,22 +487,17 @@ qwen_1_5_110b = Model(
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
# qwen 2
|
||||
qwen_2_72b = Model(
|
||||
name = 'qwen-2-72b',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = IterListProvider([DeepInfraChat, HuggingChat, Airforce, HuggingFace])
|
||||
)
|
||||
|
||||
qwen_turbo = Model(
|
||||
name = 'qwen-turbo',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = Bixin123
|
||||
)
|
||||
|
||||
qwen = Model(
|
||||
name = 'qwen',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = IterListProvider([Nexra, qwen_1_5_14b.best_provider, qwen_1_5_72b.best_provider, qwen_1_5_110b.best_provider, qwen_2_72b.best_provider, qwen_turbo.best_provider])
|
||||
best_provider = IterListProvider([Nexra, qwen_1_5_14b.best_provider, qwen_1_5_72b.best_provider, qwen_1_5_110b.best_provider, qwen_2_72b.best_provider])
|
||||
)
|
||||
|
||||
|
||||
@ -488,13 +530,6 @@ yi_1_5_9b = Model(
|
||||
best_provider = FreeChatgpt
|
||||
)
|
||||
|
||||
yi_34b = Model(
|
||||
name = 'yi-34b',
|
||||
base_provider = '01-ai',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
|
||||
### Upstage ###
|
||||
solar_1_mini = Model(
|
||||
name = 'solar-1-mini',
|
||||
@ -542,14 +577,6 @@ wizardlm_2_8x22b = Model(
|
||||
best_provider = IterListProvider([DeepInfraChat, Airforce])
|
||||
)
|
||||
|
||||
### Together ###
|
||||
sh_n_7b = Model(
|
||||
name = 'sh-n-7b',
|
||||
base_provider = 'Together',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
|
||||
### Yorickvp ###
|
||||
llava_13b = Model(
|
||||
name = 'llava-13b',
|
||||
@ -611,7 +638,8 @@ grok_2_mini = Model(
|
||||
best_provider = Liaobots
|
||||
)
|
||||
|
||||
# Perplexity AI
|
||||
|
||||
### Perplexity AI ###
|
||||
sonar_online = Model(
|
||||
name = 'sonar-online',
|
||||
base_provider = 'Perplexity AI',
|
||||
@ -625,6 +653,22 @@ sonar_chat = Model(
|
||||
)
|
||||
|
||||
|
||||
### Gryphe ###
|
||||
mythomax_l2_13b = Model(
|
||||
name = 'mythomax-l2-13b',
|
||||
base_provider = 'Gryphe',
|
||||
best_provider = IterListProvider([Airforce])
|
||||
)
|
||||
|
||||
|
||||
### Pawan ###
|
||||
cosmosrp = Model(
|
||||
name = 'cosmosrp',
|
||||
base_provider = 'Pawan',
|
||||
best_provider = IterListProvider([Airforce])
|
||||
)
|
||||
|
||||
|
||||
|
||||
#############
|
||||
### Image ###
|
||||
@ -654,6 +698,7 @@ playground_v2_5 = Model(
|
||||
|
||||
)
|
||||
|
||||
|
||||
### Flux AI ###
|
||||
flux = Model(
|
||||
name = 'flux',
|
||||
@ -805,6 +850,14 @@ 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-3.2-11b': llama_3_2_11b,
|
||||
'llama-3.2-90b': llama_3_2_90b,
|
||||
|
||||
# llamaguard
|
||||
'llamaguard-7b': llamaguard_7b,
|
||||
'llamaguard-2-8b': llamaguard_2_8b,
|
||||
|
||||
|
||||
### Mistral ###
|
||||
@ -835,12 +888,14 @@ class ModelUtils:
|
||||
'gemma-2b': gemma_2b,
|
||||
'gemma-2b-9b': gemma_2b_9b,
|
||||
'gemma-2b-27b': gemma_2b_27b,
|
||||
|
||||
# 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
|
||||
@ -880,11 +935,11 @@ class ModelUtils:
|
||||
|
||||
### Qwen ###
|
||||
'qwen': qwen,
|
||||
'qwen-1.5-7b': qwen_1_5_7b,
|
||||
'qwen-1.5-14b': qwen_1_5_14b,
|
||||
'qwen-1.5-72b': qwen_1_5_72b,
|
||||
'qwen-1.5-110b': qwen_1_5_110b,
|
||||
'qwen-2-72b': qwen_2_72b,
|
||||
'qwen-turbo': qwen_turbo,
|
||||
|
||||
|
||||
### Zhipu AI ###
|
||||
@ -908,11 +963,7 @@ class ModelUtils:
|
||||
|
||||
### DeepSeek ###
|
||||
'deepseek': deepseek,
|
||||
|
||||
|
||||
### Together ###
|
||||
'sh-n-7b': sh_n_7b,
|
||||
|
||||
|
||||
|
||||
### Yorickvp ###
|
||||
'llava-13b': llava_13b,
|
||||
@ -947,9 +998,18 @@ class ModelUtils:
|
||||
'grok-2': grok_2,
|
||||
'grok-2-mini': grok_2_mini,
|
||||
|
||||
|
||||
### Perplexity AI ###
|
||||
'sonar-online': sonar_online,
|
||||
'sonar-chat': sonar_chat,
|
||||
|
||||
|
||||
### Gryphe ###
|
||||
'mythomax-l2-13b': sonar_chat,
|
||||
|
||||
|
||||
### Pawan ###
|
||||
'cosmosrp': cosmosrp,
|
||||
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user