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# template used in production for HuggingChat.
MODELS=`[
{
"name" : "CohereForAI/c4ai-command-r-plus",
"tokenizer": "Xenova/c4ai-command-r-v01-tokenizer",
"description": "Command R+ is Cohere's latest LLM and is the first open weight model to beat GPT4 in the Chatbot Arena!",
"modelUrl": "https://huggingface.co/CohereForAI/c4ai-command-r-plus",
"websiteUrl": "https://docs.cohere.com/docs/command-r-plus",
"logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/cohere-logo.png",
"parameters": {
"stop": ["<|END_OF_TURN_TOKEN|>"],
"truncate" : 28672,
"max_new_tokens" : 4096,
"temperature" : 0.3
},
"promptExamples" : [
{
"title": "Write an email from bullet list",
"prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"
}, {
"title": "Code a snake game",
"prompt": "Code a basic snake game in python, give explanations for each step."
}, {
"title": "Assist in a task",
"prompt": "How do I make a delicious lemon cheesecake?"
}
]
},
{
"name" : "meta-llama/Meta-Llama-3-70B-Instruct",
"description": "Generation over generation, Meta Llama 3 demonstrates state-of-the-art performance on a wide range of industry benchmarks and offers new capabilities, including improved reasoning.",
"logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/meta-logo.png",
"modelUrl": "https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct",
"websiteUrl": "https://llama.meta.com/llama3/",
"tokenizer" : "philschmid/meta-llama-3-tokenizer",
"promptExamples" : [
{
"title": "Write an email from bullet list",
"prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"
}, {
"title": "Code a snake game",
"prompt": "Code a basic snake game in python, give explanations for each step."
}, {
"title": "Assist in a task",
"prompt": "How do I make a delicious lemon cheesecake?"
}
],
"parameters": {
"stop": ["<|eot_id|>"],
"truncate": 6144,
"max_new_tokens": 2047
}
},
{
"name" : "HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1",
"tokenizer": "HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1",
"description": "Zephyr 141B-A35B is a fine-tuned version of Mistral 8x22B, trained using ORPO, a novel alignment algorithm.",
"modelUrl": "https://huggingface.co/HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1",
"websiteUrl": "https://huggingface.co/HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1",
"logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/zephyr-logo.png",
"parameters": {
"truncate" : 24576,
"max_new_tokens" : 8192,
},
"preprompt" : "You are Zephyr, an assistant developed by KAIST AI, Argilla, and Hugging Face. You should give concise responses to very simple questions, but provide thorough responses to more complex and open-ended questions. You are happy to help with writing, analysis, question answering, math, coding, and all sorts of other tasks.",
"promptExamples" : [
{
"title": "Write a poem",
"prompt": "Write a poem to help me remember the first 10 elements on the periodic table, giving each element its own line."
}, {
"title": "Code a snake game",
"prompt": "Code a basic snake game in python, give explanations for each step."
}, {
"title": "Assist in a task",
"prompt": "How do I make a delicious lemon cheesecake?"
}
]
},
{
"name" : "mistralai/Mixtral-8x7B-Instruct-v0.1",
"description" : "The latest MoE model from Mistral AI! 8x7B and outperforms Llama 2 70B in most benchmarks.",
"logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/mistral-logo.png",
"websiteUrl" : "https://mistral.ai/news/mixtral-of-experts/",
"modelUrl": "https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1",
"tokenizer": "mistralai/Mixtral-8x7B-Instruct-v0.1",
"preprompt" : "",
"chatPromptTemplate": "<s> {{#each messages}}{{#ifUser}}[INST]{{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}} {{content}} [/INST]{{/ifUser}}{{#ifAssistant}} {{content}}</s> {{/ifAssistant}}{{/each}}",
"parameters" : {
"temperature" : 0.6,
"top_p" : 0.95,
"repetition_penalty" : 1.2,
"top_k" : 50,
"truncate" : 24576,
"max_new_tokens" : 8192,
"stop" : ["</s>"]
},
"promptExamples" : [
{
"title": "Write an email from bullet list",
"prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"
}, {
"title": "Code a snake game",
"prompt": "Code a basic snake game in python, give explanations for each step."
}, {
"title": "Assist in a task",
"prompt": "How do I make a delicious lemon cheesecake?"
}
]
},
{
"name" : "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
"description" : "Nous Hermes 2 Mixtral 8x7B DPO is the new flagship Nous Research model trained over the Mixtral 8x7B MoE LLM.",
"logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/nous-logo.png",
"websiteUrl" : "https://nousresearch.com/",
"modelUrl": "https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
"tokenizer": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
"chatPromptTemplate" : "{{#if @root.preprompt}}<|im_start|>system\n{{@root.preprompt}}<|im_end|>\n{{/if}}{{#each messages}}{{#ifUser}}<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n{{/ifUser}}{{#ifAssistant}}{{content}}<|im_end|>\n{{/ifAssistant}}{{/each}}",
"promptExamples": [
{
"title": "Write an email from bullet list",
"prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"
}, {
"title": "Code a snake game",
"prompt": "Code a basic snake game in python, give explanations for each step."
}, {
"title": "Assist in a task",
"prompt": "How do I make a delicious lemon cheesecake?"
}
],
"parameters": {
"temperature": 0.7,
"top_p": 0.95,
"repetition_penalty": 1,
"top_k": 50,
"truncate": 24576,
"max_new_tokens": 2048,
"stop": ["<|im_end|>"]
}
},
{
"name" : "google/gemma-1.1-7b-it",
"description": "Gemma 7B 1.1 is the latest release in the Gemma family of lightweight models built by Google, trained using a novel RLHF method.",
"websiteUrl" : "https://blog.google/technology/developers/gemma-open-models/",
"logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/google-logo.png",
"modelUrl": "https://huggingface.co/google/gemma-1.1-7b-it",
"preprompt": "",
"chatPromptTemplate" : "{{#each messages}}{{#ifUser}}<start_of_turn>user\n{{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}}{{content}}<end_of_turn>\n<start_of_turn>model\n{{/ifUser}}{{#ifAssistant}}{{content}}<end_of_turn>\n{{/ifAssistant}}{{/each}}",
"promptExamples": [
{
"title": "Write an email from bullet list",
"prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"
}, {
"title": "Code a snake game",
"prompt": "Code a basic snake game in python, give explanations for each step."
}, {
"title": "Assist in a task",
"prompt": "How do I make a delicious lemon cheesecake?"
}
],
"parameters": {
"do_sample": true,
"truncate": 7168,
"max_new_tokens": 1024,
"stop" : ["<end_of_turn>"]
}
},
{
"name": "mistralai/Mistral-7B-Instruct-v0.2",
"displayName": "mistralai/Mistral-7B-Instruct-v0.2",
"description": "Mistral 7B is a new Apache 2.0 model, released by Mistral AI that outperforms Llama2 13B in benchmarks.",
"logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/mistral-logo.png",
"websiteUrl": "https://mistral.ai/news/announcing-mistral-7b/",
"modelUrl": "https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2",
"tokenizer": "mistralai/Mistral-7B-Instruct-v0.2",
"preprompt": "",
"chatPromptTemplate" : "<s>{{#each messages}}{{#ifUser}}[INST] {{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}}{{content}} [/INST]{{/ifUser}}{{#ifAssistant}}{{content}}</s>{{/ifAssistant}}{{/each}}",
"parameters": {
"temperature": 0.3,
"top_p": 0.95,
"repetition_penalty": 1.2,
"top_k": 50,
"truncate": 3072,
"max_new_tokens": 1024,
"stop": ["</s>"]
},
"promptExamples": [
{
"title": "Write an email from bullet list",
"prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"
}, {
"title": "Code a snake game",
"prompt": "Code a basic snake game in python, give explanations for each step."
}, {
"title": "Assist in a task",
"prompt": "How do I make a delicious lemon cheesecake?"
}
]
},
{
"name": "microsoft/Phi-3-mini-4k-instruct",
"tokenizer": "microsoft/Phi-3-mini-4k-instruct",
"description" : "Phi-3 Mini-4K-Instruct is a 3.8B parameters, lightweight, state-of-the-art open model built upon datasets used for Phi-2.",
"logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/microsoft-logo.png",
"modelUrl": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct",
"websiteUrl": "https://azure.microsoft.com/en-us/blog/introducing-phi-3-redefining-whats-possible-with-slms/",
"preprompt": "",
"chatPromptTemplate": "{{preprompt}}{{#each messages}}{{#ifUser}}<|user|>\n{{content}}<|end|>\n<|assistant|>\n{{/ifUser}}{{#ifAssistant}}{{content}}<|end|>\n{{/ifAssistant}}{{/each}}",
"parameters": {
"stop": ["<|end|>", "<|endoftext|>", "<|assistant|>"],
"max_new_tokens": 1024,
"truncate": 3071
},
"promptExamples": [
{
"title": "Write an email from bullet list",
"prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"
}, {
"title": "Code a snake game",
"prompt": "Code a basic snake game in python, give explanations for each step."
}, {
"title": "Assist in a task",
"prompt": "How do I make a delicious lemon cheesecake?"
}
]
},
{
"name": "meta-llama/Meta-Llama-3-8B-Instruct",
"tokenizer" : "philschmid/meta-llama-3-tokenizer",
"parameters": {
"temperature": 0.1,
"stop": ["<|eot_id|>"],
},
"unlisted": true
}
]`
OLD_MODELS=`[
{"name":"bigcode/starcoder"},
{"name":"OpenAssistant/oasst-sft-6-llama-30b-xor"},
{"name":"HuggingFaceH4/zephyr-7b-alpha"},
{"name":"openchat/openchat_3.5"},
{"name":"openchat/openchat-3.5-1210"},
{"name": "tiiuae/falcon-180B-chat"},
{"name": "codellama/CodeLlama-34b-Instruct-hf"},
{"name": "google/gemma-7b-it"},
{"name": "meta-llama/Llama-2-70b-chat-hf"},
{"name": "codellama/CodeLlama-70b-Instruct-hf"},
{"name": "openchat/openchat-3.5-0106"}
]`
TASK_MODEL='meta-llama/Meta-Llama-3-8B-Instruct'
TEXT_EMBEDDING_MODELS = `[
{
"name": "bge-base-en-v1-5-sxa",
"displayName": "bge-base-en-v1-5-sxa",
"chunkCharLength": 512,
"endpoints": [
{ "type": "tei",
"url" : "https://huggingchat-tei.hf.space/"
}
]
}
]`
APP_BASE="/chat"
PUBLIC_ORIGIN=https://huggingface.co
PUBLIC_SHARE_PREFIX=https://hf.co/chat
PUBLIC_ANNOUNCEMENT_BANNERS=`[]`
PUBLIC_APP_NAME=HuggingChat
PUBLIC_APP_ASSETS=huggingchat
PUBLIC_APP_COLOR=yellow
PUBLIC_APP_DESCRIPTION="Making the community's best AI chat models available to everyone."
PUBLIC_APP_DISCLAIMER_MESSAGE="Disclaimer: AI is an area of active research with known problems such as biased generation and misinformation. Do not use this application for high-stakes decisions or advice."
PUBLIC_APP_DATA_SHARING=0
PUBLIC_APP_DISCLAIMER=1
PUBLIC_PLAUSIBLE_SCRIPT_URL="/js/script.js"
PUBLIC_APPLE_APP_ID=6476778843
# Not part of the .env but set as other variables in the space
# ADDRESS_HEADER=X-Forwarded-For
# XFF_DEPTH=2
ENABLE_ASSISTANTS=true
ENABLE_ASSISTANTS_RAG=true
REQUIRE_FEATURED_ASSISTANTS=true
EXPOSE_API=true
ALTERNATIVE_REDIRECT_URLS=`[
huggingchat://login/callback
]`
WEBSEARCH_BLOCKLIST=`["youtube.com", "twitter.com"]`
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