# 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" : 24576,
      "max_new_tokens" : 8192,
      "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" : "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" : "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" : "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": "mistralai/Mistral-7B-Instruct-v0.1",
      "displayName": "mistralai/Mistral-7B-Instruct-v0.1",
      "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-v0.1",
      "tokenizer": "mistralai/Mistral-7B-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": 0.1,
        "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?"
        }
      ],
      "unlisted": true
    },
        {
      "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?"
        }
      ]
    }
]`

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='mistralai/Mistral-7B-Instruct-v0.1'

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=1
PUBLIC_APP_DISCLAIMER=1

PUBLIC_GOOGLE_ANALYTICS_ID=G-8Q63TH4CSL
PUBLIC_PLAUSIBLE_SCRIPT_URL="/js/script.js"

# 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
EXPOSE_API=true

ALTERNATIVE_REDIRECT_URLS=`[
  huggingchat://login/callback
]`

WEBSEARCH_BLOCKLIST=`["youtube.com", "twitter.com"]`