.env.template

# template used in production for HuggingChat.

MODELS=`[
      {
      "name": "meta-llama/Llama-2-70b-chat-hf",
      "description": "The latest and biggest model from Meta, fine-tuned for chat.",
      "websiteUrl": "https://ai.meta.com/llama/",
      "userMessageToken": "",
      "userMessageEndToken": " [/INST] ",
      "assistantMessageToken": "",
      "assistantMessageEndToken": " </s><s>[INST] ",
      "preprompt": " ",
      "chatPromptTemplate" : "<s>[INST] <<SYS>>\n{{preprompt}}\n<</SYS>>\n\n{{#each messages}}{{#ifUser}}{{content}} [/INST] {{/ifUser}}{{#ifAssistant}}{{content}} </s><s>[INST] {{/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": 0.1,
        "top_p": 0.95,
        "repetition_penalty": 1.2,
        "top_k": 50,
        "truncate": 1000,
        "max_new_tokens": 1024
      }
        },
        {
      "name": "codellama/CodeLlama-34b-Instruct-hf",
      "displayName": "codellama/CodeLlama-34b-Instruct-hf",
      "description": "Code Llama, a state of the art code model from Meta.",
      "websiteUrl": "https://about.fb.com/news/2023/08/code-llama-ai-for-coding/",
      "userMessageToken": "",
      "userMessageEndToken": " [/INST] ",
      "assistantMessageToken": "",
      "assistantMessageEndToken": " </s><s>[INST] ",
      "preprompt": " ",
      "chatPromptTemplate" : "<s>[INST] <<SYS>>\n{{preprompt}}\n<</SYS>>\n\n{{#each messages}}{{#ifUser}}{{content}} [/INST] {{/ifUser}}{{#ifAssistant}}{{content}} </s><s>[INST] {{/ifAssistant}}{{/each}}",
      "promptExamples": [
        {
          "title": "Fibonacci in Python",
          "prompt": "Write a python function to calculate the nth fibonacci number."
        }, {
          "title": "JavaScript promises",
          "prompt": "How can I wait for multiple JavaScript promises to fulfill before doing something with their values?"
        }, {
          "title": "Rust filesystem",
          "prompt": "How can I load a file from disk in Rust?"
        }
      ],
      "parameters": {
        "temperature": 0.1,
        "top_p": 0.95,
        "repetition_penalty": 1.2,
        "top_k": 50,
        "truncate": 1000,
        "max_new_tokens": 2048
      }
      },
      {
        "name": "tiiuae/falcon-180B-chat",
        "displayName": "tiiuae/falcon-180B-chat",
        "description": "Falcon-180B is a 180B parameters causal decoder-only model built by TII and trained on 3,500B tokens.",
        "websiteUrl": "https://www.tii.ae/news/technology-innovation-institute-introduces-worlds-most-powerful-open-llm-falcon-180b",
        "preprompt": " ",
        "chatPromptTemplate": "System: {{preprompt}}\nUser:{{#each messages}}{{#ifUser}}{{content}}\nFalcon:{{/ifUser}}{{#ifAssistant}}{{content}}\nUser:{{/ifAssistant}}{{/each}}",
        "parameters": {
          "temperature": 0.1,
          "top_p": 0.95,
          "repetition_penalty": 1.2,
          "top_k": 50,
          "truncate": 1000,
          "max_new_tokens": 1024,
          "stop": ["User:"]
      },
          "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": "HuggingFaceH4/zephyr-7b-alpha",
      "displayName": "HuggingFaceH4/zephyr-7b-alpha",
      "description": "Zephyr 7B α is a fine-tune of Mistral 7B, released by the Hugging Face H4 RLHF team.",
      "websiteUrl": "https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha/",
      "preprompt": "",
      "chatPromptTemplate" : "<|system|>\n{{preprompt}}</s>\n{{#each messages}}{{#ifUser}}<|user|>\n{{content}}</s>\n<|assistant|>\n{{/ifUser}}{{#ifAssistant}}{{content}}</s>\n{{/ifAssistant}}{{/each}}",
      "parameters": {
        "temperature": 0.7,
        "top_p": 0.95,
        "repetition_penalty": 1.2,
        "top_k": 50,
        "truncate": 1000,
        "max_new_tokens": 2048,
        "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":"mistralai/Mistral-7B-Instruct-v0.1"}]`
TASK_MODEL='HuggingFaceH4/zephyr-7b-alpha'

APP_BASE="/chat"
PUBLIC_ORIGIN=https://huggingface.co
PUBLIC_SHARE_PREFIX=https://hf.co/chat
PUBLIC_ANNOUNCEMENT_BANNERS=`[
    {
    "title": "Websearch 2.0, now with RAG & sources",
    "linkTitle": "Discuss",
    "linkHref": "https://huggingface.co/spaces/huggingchat/chat-ui/discussions/254"
  }
]`

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_DATA_SHARING=1
PUBLIC_APP_DISCLAIMER=1

RATE_LIMIT=16
MESSAGES_BEFORE_LOGIN=1# how many messages a user can send in a conversation before having to login. set to 0 to force login right away

# Not part of the .env but set as other variables in the space
# ADDRESS_HEADER=X-Forwarded-For
# XFF_DEPTH=2