502 Bad Gateway

.dockerignore

@@ -0,0 +1,11 @@
+Dockerfile
+.vscode/
+.idea
+.gitignore
+LICENSE
+README.md
+node_modules/
+.svelte-kit/
+.env*
+!.env
+.env.local

.env

@@ -0,0 +1,158 @@
+# Use .env.local to change these variables
+# DO NOT EDIT THIS FILE WITH SENSITIVE DATA
+
+MONGODB_URL=#your mongodb URL here
+MONGODB_DB_NAME=chat-ui
+MONGODB_DIRECT_CONNECTION=false
+
+COOKIE_NAME=hf-chat
+HF_TOKEN=#hf_<token> from https://huggingface.co/settings/token
+HF_API_ROOT=https://api-inference.huggingface.co/models
+
+OPENAI_API_KEY=#your openai api key here
+ANTHROPIC_API_KEY=#your anthropic api key here
+CLOUDFLARE_ACCOUNT_ID=#your cloudflare account id here
+CLOUDFLARE_API_TOKEN=#your cloudflare api token here
+COHERE_API_TOKEN=#your cohere api token here
+
+HF_ACCESS_TOKEN=#LEGACY! Use HF_TOKEN instead
+
+# used to activate search with web functionality. disabled if none are defined. choose one of the following:
+YDC_API_KEY=#your docs.you.com api key here
+SERPER_API_KEY=#your serper.dev api key here
+SERPAPI_KEY=#your serpapi key here
+SERPSTACK_API_KEY=#your serpstack api key here
+USE_LOCAL_WEBSEARCH=#set to true to parse google results yourself, overrides other API keys
+SEARXNG_QUERY_URL=# where '<query>' will be replaced with query keywords see https://docs.searxng.org/dev/search_api.html eg https://searxng.yourdomain.com/search?q=<query>&engines=duckduckgo,google&format=json
+
+WEBSEARCH_ALLOWLIST=`[]` # if it's defined, allow websites from only this list.
+WEBSEARCH_BLOCKLIST=`[]` # if it's defined, block websites from this list.
+
+# Parameters to enable open id login
+OPENID_CONFIG=`{
+  "PROVIDER_URL": "",
+  "CLIENT_ID": "",
+  "CLIENT_SECRET": "",
+  "SCOPES": "",
+  "NAME_CLAIM": ""
+}`
+
+# /!\ legacy openid settings, prefer the config above
+OPENID_CLIENT_ID=
+OPENID_CLIENT_SECRET=
+OPENID_SCOPES="openid profile" # Add "email" for some providers like Google that do not provide preferred_username
+OPENID_NAME_CLAIM="name" # Change to "username" for some providers that do not provide name
+OPENID_PROVIDER_URL=https://huggingface.co # for Google, use https://accounts.google.com
+OPENID_TOLERANCE=
+OPENID_RESOURCE=
+
+# Parameters to enable a global mTLS context for client fetch requests
+USE_CLIENT_CERTIFICATE=false
+CERT_PATH=#
+KEY_PATH=#
+CA_PATH=#
+CLIENT_KEY_PASSWORD=#
+REJECT_UNAUTHORIZED=true
+
+TEXT_EMBEDDING_MODELS = `[
+  {
+    "name": "Xenova/gte-small",
+    "displayName": "Xenova/gte-small",
+    "description": "Local embedding model running on the server.",
+    "chunkCharLength": 512,
+    "endpoints": [
+      { "type": "transformersjs" }
+    ]
+  }
+]`
+
+# 'name', 'userMessageToken', 'assistantMessageToken' are required
+MODELS=`[
+    {
+      "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.",
+      "websiteUrl": "https://mistral.ai/news/announcing-mistral-7b/",
+      "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?"
+        }
+      ]
+    }
+]`
+
+OLD_MODELS=`[]`# any removed models, `{ name: string, displayName?: string, id?: string }`
+TASK_MODEL= # name of the model used for tasks such as summarizing title, creating query, etc.
+
+PUBLIC_ORIGIN=#https://huggingface.co
+PUBLIC_SHARE_PREFIX=#https://hf.co/chat
+PUBLIC_GOOGLE_ANALYTICS_ID=#G-XXXXXXXX / Leave empty to disable
+PUBLIC_PLAUSIBLE_SCRIPT_URL=#/js/script.js / Leave empty to disable
+PUBLIC_ANNOUNCEMENT_BANNERS=`[
+    {
+    "title": "Code Llama 70B is available! 🦙",
+    "linkTitle": "try it",
+    "linkHref": "https://huggingface.co/chat?model=codellama/CodeLlama-70b-Instruct-hf"
+  }
+]`
+
+PUBLIC_APPLE_APP_ID=#1234567890 / Leave empty to disable
+
+PARQUET_EXPORT_DATASET=
+PARQUET_EXPORT_HF_TOKEN=
+ADMIN_API_SECRET=# secret to admin API calls, like computing usage stats or exporting parquet data
+
+PARQUET_EXPORT_SECRET=#DEPRECATED, use ADMIN_API_SECRET instead
+
+RATE_LIMIT= # /!\ Legacy definition of messages per minute. Use USAGE_LIMITS.messagesPerMinute instead
+MESSAGES_BEFORE_LOGIN=# how many messages a user can send in a conversation before having to login. set to 0 to force login right away
+
+APP_BASE="" # base path of the app, e.g. /chat, left blank as default
+PUBLIC_APP_NAME=ChatUI # name used as title throughout the app
+PUBLIC_APP_ASSETS=chatui # used to find logos & favicons in static/$PUBLIC_APP_ASSETS
+PUBLIC_APP_COLOR=blue # can be any of tailwind colors: https://tailwindcss.com/docs/customizing-colors#default-color-palette
+PUBLIC_APP_DESCRIPTION=# description used throughout the app (if not set, a default one will be used)
+PUBLIC_APP_DATA_SHARING=#set to 1 to enable options & text regarding data sharing
+PUBLIC_APP_DISCLAIMER=#set to 1 to show a disclaimer on login page
+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. Do not insert your personal data, especially sensitive, like health data."
+LLM_SUMMERIZATION=true
+
+EXPOSE_API=true
+# 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
+
+ENABLE_ASSISTANTS=false #set to true to enable assistants feature
+ENABLE_ASSISTANTS_RAG=false # /!\ This will let users specify arbitrary URLs that the server will then request. Make sure you have the proper firewall rules in place. 
+REQUIRE_FEATURED_ASSISTANTS=false
+ENABLE_LOCAL_FETCH=false #set to true to disable the blocklist for local fetches. Only enable this if you have the proper firewall rules to prevent SSRF attacks and understand the implications.
+ALTERNATIVE_REDIRECT_URLS=`[]` #valide alternative redirect URL for OAuth
+WEBHOOK_URL_REPORT_ASSISTANT=#provide webhook url to get notified when an assistant gets reported
+
+ALLOWED_USER_EMAILS=`[]` # if it's defined, only these emails will be allowed to use the app
+
+USAGE_LIMITS=`{}`
+ALLOW_INSECURE_COOKIES=false # recommended to keep this to false but set to true if you need to run over http without tls
+METRICS_PORT=
+LOG_LEVEL=info

.env.ci

@@ -0,0 +1 @@
+MONGODB_URL=mongodb://localhost:27017/

.env.template

@@ -0,0 +1,298 @@
+# 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": "<s>{{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|>"],
+        "truncate": 1024,
+      },
+      "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"]`

.eslintignore

@@ -0,0 +1,13 @@
+.DS_Store
+node_modules
+/build
+/.svelte-kit
+/package
+.env
+.env.*
+!.env.example
+
+# Ignore files for PNPM, NPM and YARN
+pnpm-lock.yaml
+package-lock.json
+yarn.lock

.eslintrc.cjs

@@ -0,0 +1,44 @@
+module.exports = {
+	root: true,
+	parser: "@typescript-eslint/parser",
+	extends: [
+		"eslint:recommended",
+		"plugin:@typescript-eslint/recommended",
+		"plugin:svelte/recommended",
+		"prettier",
+	],
+	plugins: ["@typescript-eslint"],
+	ignorePatterns: ["*.cjs"],
+	overrides: [
+		{
+			files: ["*.svelte"],
+			parser: "svelte-eslint-parser",
+			parserOptions: {
+				parser: "@typescript-eslint/parser",
+			},
+		},
+	],
+	parserOptions: {
+		sourceType: "module",
+		ecmaVersion: 2020,
+		extraFileExtensions: [".svelte"],
+	},
+	rules: {
+		"no-shadow": ["error"],
+		"@typescript-eslint/no-explicit-any": "error",
+		"@typescript-eslint/no-non-null-assertion": "error",
+		"@typescript-eslint/no-unused-vars": [
+			// prevent variables with a _ prefix from being marked as unused
+			"error",
+			{
+				argsIgnorePattern: "^_",
+			},
+		],
+		"object-shorthand": ["error", "always"],
+	},
+	env: {
+		browser: true,
+		es2017: true,
+		node: true,
+	},
+};

.github/release.yml

@@ -0,0 +1,16 @@
+changelog:
+  exclude:
+    labels:
+      - huggingchat
+      - CI/CD
+      - documentation
+  categories:
+    - title: Features
+      labels:
+        - enhancement
+    - title: Bugfixes
+      labels:
+        - bug
+    - title: Other changes
+      labels:
+        - "*"

.github/workflows/build-image.yml

@@ -0,0 +1,125 @@
+name: Build and Publish Image
+
+on:
+  push:
+    branches:
+      - "main"
+  pull_request:
+    branches:
+      - "*"
+    paths:
+      - "Dockerfile"
+      - "entrypoint.sh"
+  workflow_dispatch:
+  release:
+    types: [published, edited]
+
+jobs:
+  build-and-publish-image-with-db:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Extract package version
+        id: package-version
+        run: |
+          VERSION=$(jq -r .version package.json)
+          echo "VERSION=$VERSION" >> $GITHUB_OUTPUT
+          MAJOR=$(echo $VERSION | cut -d '.' -f1)
+          echo "MAJOR=$MAJOR" >> $GITHUB_OUTPUT
+          MINOR=$(echo $VERSION | cut -d '.' -f1).$(echo $VERSION | cut -d '.' -f2)
+          echo "MINOR=$MINOR" >> $GITHUB_OUTPUT
+
+      - name: Docker metadata
+        id: meta
+        uses: docker/metadata-action@v5
+        with:
+          images: |
+            ghcr.io/huggingface/chat-ui-db
+          tags: |
+            type=raw,value=${{ steps.package-version.outputs.VERSION }},enable=${{github.event_name == 'release'}}
+            type=raw,value=${{ steps.package-version.outputs.MAJOR }},enable=${{github.event_name == 'release'}}
+            type=raw,value=${{ steps.package-version.outputs.MINOR }},enable=${{github.event_name == 'release'}}
+            type=raw,value=latest,enable={{is_default_branch}}
+            type=sha,enable={{is_default_branch}}
+
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v3
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Login to GitHub Container Registry
+        if: github.event_name != 'pull_request'
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.repository_owner }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Build and Publish Docker Image with DB
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          file: Dockerfile
+          push: ${{ github.event_name != 'pull_request' }}
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+          platforms: linux/amd64,linux/arm64
+          build-args: |
+            INCLUDE_DB=true
+  build-and-publish-image-nodb:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Extract package version
+        id: package-version
+        run: |
+          VERSION=$(jq -r .version package.json)
+          echo "VERSION=$VERSION" >> $GITHUB_OUTPUT
+          MAJOR=$(echo $VERSION | cut -d '.' -f1)
+          echo "MAJOR=$MAJOR" >> $GITHUB_OUTPUT
+          MINOR=$(echo $VERSION | cut -d '.' -f1).$(echo $VERSION | cut -d '.' -f2)
+          echo "MINOR=$MINOR" >> $GITHUB_OUTPUT
+
+      - name: Docker metadata
+        id: meta
+        uses: docker/metadata-action@v5
+        with:
+          images: |
+            ghcr.io/huggingface/chat-ui
+          tags: |
+            type=raw,value=${{ steps.package-version.outputs.VERSION }},enable=${{github.event_name == 'release'}}
+            type=raw,value=${{ steps.package-version.outputs.MAJOR }},enable=${{github.event_name == 'release'}}
+            type=raw,value=${{ steps.package-version.outputs.MINOR }},enable=${{github.event_name == 'release'}}
+            type=raw,value=latest,enable={{is_default_branch}}
+            type=sha,enable={{is_default_branch}}
+
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v3
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Login to GitHub Container Registry
+        if: github.event_name != 'pull_request'
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.repository_owner }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Build and Publish Docker Image without DB
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          file: Dockerfile
+          push: ${{ github.event_name != 'pull_request' }}
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+          platforms: linux/amd64,linux/arm64
+          build-args: |
+            INCLUDE_DB=false

.github/workflows/deploy-release.yml

@@ -0,0 +1,44 @@
+name: Deploy to production
+on:
+  # run this workflow manually from the Actions tab
+  workflow_dispatch:
+
+jobs:
+  update-env:
+    runs-on: ubuntu-latest
+    timeout-minutes: 10
+
+    steps:
+      - uses: actions/checkout@v3
+      - uses: actions/setup-node@v3
+        with:
+          node-version: "20"
+          cache: "npm"
+      - run: npm install ci
+      - name: "Update DOTENV_LOCAL in prod"
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          SERPER_API_KEY: ${{ secrets.SERPER_API_KEY }}
+          OPENID_CONFIG: ${{ secrets.OPENID_CONFIG }}
+          MONGODB_URL: ${{ secrets.MONGODB_URL }}
+          HF_DEPLOYMENT_TOKEN: ${{ secrets.HF_DEPLOYMENT_TOKEN }}
+          WEBHOOK_URL_REPORT_ASSISTANT: ${{ secrets.WEBHOOK_URL_REPORT_ASSISTANT }}
+          ADMIN_API_SECRET: ${{ secrets.ADMIN_API_SECRET }}
+          USAGE_LIMITS: ${{ secrets.USAGE_LIMITS }}
+          MESSAGES_BEFORE_LOGIN: ${{ secrets.MESSAGES_BEFORE_LOGIN }}
+        run: npm run updateProdEnv
+  sync-to-hub:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check large files
+        uses: ActionsDesk/lfs-warning@v2.0
+        with:
+          filesizelimit: 10485760 # this is 10MB so we can sync to HF Spaces
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+          lfs: true
+      - name: Push to hub
+        env:
+          HF_DEPLOYMENT_TOKEN: ${{ secrets.HF_DEPLOYMENT_TOKEN }}
+        run: git push https://nsarrazin:$HF_DEPLOYMENT_TOKEN@huggingface.co/spaces/huggingchat/chat-ui main

.github/workflows/deploy-staging.yml

@@ -0,0 +1,24 @@
+name: Deploy to staging environment
+on:
+  push:
+    branches: [main]
+
+  # to run this workflow manually from the Actions tab
+  workflow_dispatch:
+
+jobs:
+  sync-to-hub:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check large files
+        uses: ActionsDesk/lfs-warning@v2.0
+        with:
+          filesizelimit: 10485760 # this is 10MB so we can sync to HF Spaces
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+          lfs: true
+      - name: Push to hub
+        env:
+          HF_DEPLOYMENT_TOKEN: ${{ secrets.HF_DEPLOYMENT_TOKEN }}
+        run: git push https://nsarrazin:$HF_DEPLOYMENT_TOKEN@huggingface.co/spaces/huggingchat/chat-ui-staging main

.github/workflows/lint-and-test.yml

@@ -0,0 +1,56 @@
+name: Lint and test
+on:
+  pull_request:
+  push:
+    branches:
+      - main
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    timeout-minutes: 10
+
+    steps:
+      - uses: actions/checkout@v3
+
+      - uses: actions/setup-node@v3
+        with:
+          node-version: "20"
+          cache: "npm"
+      - run: |
+          npm install ci
+      - name: "Checking lint/format errors"
+        run: |
+          npm run lint
+      - name: "Checking type errors"
+        run: |
+          npm run check
+  test:
+    runs-on: ubuntu-latest
+    timeout-minutes: 10
+
+    services:
+      mongodb:
+        image: mongo:6.0.5
+        ports:
+          - 27017:27017
+
+    steps:
+      - uses: actions/checkout@v3
+
+      - uses: actions/setup-node@v3
+        with:
+          node-version: "20"
+          cache: "npm"
+      - run: |
+          npm ci
+      - name: "Tests"
+        run: |
+          npm run test
+  build-check:
+    runs-on: ubuntu-latest
+    timeout-minutes: 10
+    steps:
+      - uses: actions/checkout@v3
+      - name: Build Docker image
+        run: docker build --secret id=DOTENV_LOCAL,src=.env.ci -t chat-ui:latest .

.gitignore

@@ -0,0 +1,15 @@
+.DS_Store
+node_modules
+/build
+/.svelte-kit
+/package
+.env
+.env.*
+vite.config.js.timestamp-*
+vite.config.ts.timestamp-*
+SECRET_CONFIG
+.idea
+!.env.ci
+!.env
+!.env.template
+gcp-*.json

.npmrc

@@ -0,0 +1 @@
+engine-strict=true

.prettierignore

@@ -0,0 +1,13 @@
+.DS_Store
+node_modules
+/build
+/.svelte-kit
+/package
+.env
+.env.*
+!.env.example
+
+# Ignore files for PNPM, NPM and YARN
+pnpm-lock.yaml
+package-lock.json
+yarn.lock

.prettierrc

@@ -0,0 +1,8 @@
+{
+	"useTabs": true,
+	"trailingComma": "es5",
+	"printWidth": 100,
+	"plugins": ["prettier-plugin-svelte", "prettier-plugin-tailwindcss"],
+	"pluginSearchDirs": ["."],
+	"overrides": [{ "files": "*.svelte", "options": { "parser": "svelte" } }]
+}

.vscode/settings.json

@@ -0,0 +1,8 @@
+{
+	"editor.formatOnSave": true,
+	"editor.defaultFormatter": "esbenp.prettier-vscode",
+	"editor.codeActionsOnSave": {
+		"source.fixAll": "explicit"
+	},
+	"eslint.validate": ["javascript", "svelte"]
+}

Dockerfile

@@ -0,0 +1,88 @@
+# syntax=docker/dockerfile:1
+# read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+ARG INCLUDE_DB=false
+
+# stage that install the dependencies
+FROM node:20 as builder-production
+
+WORKDIR /app
+
+COPY --link --chown=1000 package-lock.json package.json ./
+RUN --mount=type=cache,target=/app/.npm \
+        npm set cache /app/.npm && \
+        npm ci --omit=dev
+
+FROM builder-production as builder
+
+ARG APP_BASE=
+ARG PUBLIC_APP_COLOR=blue
+
+RUN --mount=type=cache,target=/app/.npm \
+        npm set cache /app/.npm && \
+        npm ci
+
+COPY --link --chown=1000 . .
+
+RUN npm run build
+
+# mongo image
+FROM mongo:latest as mongo
+
+# image to be used if INCLUDE_DB is false
+FROM node:20-slim as local_db_false
+
+# image to be used if INCLUDE_DB is true
+FROM node:20-slim as local_db_true
+
+RUN apt-get update
+RUN apt-get install gnupg curl -y
+# copy mongo from the other stage
+COPY --from=mongo /usr/bin/mongo* /usr/bin/
+
+ENV MONGODB_URL=mongodb://localhost:27017
+RUN mkdir -p /data/db
+RUN chown -R 1000:1000 /data/db
+
+# final image
+FROM local_db_${INCLUDE_DB} as final
+
+# build arg to determine if the database should be included
+ARG INCLUDE_DB=false
+ENV INCLUDE_DB=${INCLUDE_DB}
+
+# svelte requires APP_BASE at build time so it must be passed as a build arg
+ARG APP_BASE=
+# tailwind requires the primary theme to be known at build time so it must be passed as a build arg
+ARG PUBLIC_APP_COLOR=blue
+
+
+# install dotenv-cli
+RUN npm install -g dotenv-cli
+
+# switch to a user that works for spaces
+RUN userdel -r node
+RUN useradd -m -u 1000 user
+USER user
+
+ENV HOME=/home/user \
+	PATH=/home/user/.local/bin:$PATH
+
+WORKDIR /app
+
+# add a .env.local if the user doesn't bind a volume to it
+RUN touch /app/.env.local
+
+# get the default config, the entrypoint script and the server script
+COPY --chown=1000 package.json /app/package.json
+COPY --chown=1000 .env /app/.env
+COPY --chown=1000 entrypoint.sh /app/entrypoint.sh
+COPY --chown=1000 gcp-*.json /app/
+
+#import the build & dependencies
+COPY --from=builder --chown=1000 /app/build /app/build
+COPY --from=builder --chown=1000 /app/node_modules /app/node_modules
+
+RUN chmod +x /app/entrypoint.sh
+
+CMD ["/bin/bash", "-c", "/app/entrypoint.sh"]

LICENSE

@@ -0,0 +1,203 @@
+Copyright 2018- The Hugging Face team. All rights reserved.
+
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
+      "You" (or "Your") shall mean an individual or Legal Entity
+      exercising permissions granted by this License.
+
+      "Source" form shall mean the preferred form for making modifications,
+      including but not limited to software source code, documentation
+      source, and configuration files.
+
+      "Object" form shall mean any form resulting from mechanical
+      transformation or translation of a Source form, including but
+      not limited to compiled object code, generated documentation,
+      and conversions to other media types.
+
+      "Work" shall mean the work of authorship, whether in Source or
+      Object form, made available under the License, as indicated by a
+      copyright notice that is included in or attached to the work
+      (an example is provided in the Appendix below).
+
+      "Derivative Works" shall mean any work, whether in Source or Object
+      form, that is based on (or derived from) the Work and for which the
+      editorial revisions, annotations, elaborations, or other modifications
+      represent, as a whole, an original work of authorship. For the purposes
+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
+      the Work and Derivative Works thereof.
+
+      "Contribution" shall mean any work of authorship, including
+      the original version of the Work and any modifications or additions
+      to that Work or Derivative Works thereof, that is intentionally
+      submitted to Licensor for inclusion in the Work by the copyright owner
+      or by an individual or Legal Entity authorized to submit on behalf of
+      the copyright owner. For the purposes of this definition, "submitted"
+      means any form of electronic, verbal, or written communication sent
+      to the Licensor or its representatives, including but not limited to
+      communication on electronic mailing lists, source code control systems,
+      and issue tracking systems that are managed by, or on behalf of, the
+      Licensor for the purpose of discussing and improving the Work, but
+      excluding communication that is conspicuously marked or otherwise
+      designated in writing by the copyright owner as "Not a Contribution."
+
+      "Contributor" shall mean Licensor and any individual or Legal Entity
+      on behalf of whom a Contribution has been received by Licensor and
+      subsequently incorporated within the Work.
+
+   2. Grant of Copyright License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      copyright license to reproduce, prepare Derivative Works of,
+      publicly display, publicly perform, sublicense, and distribute the
+      Work and such Derivative Works in Source or Object form.
+
+   3. Grant of Patent License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      (except as stated in this section) patent license to make, have made,
+      use, offer to sell, sell, import, and otherwise transfer the Work,
+      where such license applies only to those patent claims licensable
+      by such Contributor that are necessarily infringed by their
+      Contribution(s) alone or by combination of their Contribution(s)
+      with the Work to which such Contribution(s) was submitted. If You
+      institute patent litigation against any entity (including a
+      cross-claim or counterclaim in a lawsuit) alleging that the Work
+      or a Contribution incorporated within the Work constitutes direct
+      or contributory patent infringement, then any patent licenses
+      granted to You under this License for that Work shall terminate
+      as of the date such litigation is filed.
+
+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or
+          Derivative Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
+          that You distribute, all copyright, patent, trademark, and
+          attribution notices from the Source form of the Work,
+          excluding those notices that do not pertain to any part of
+          the Derivative Works; and
+
+      (d) If the Work includes a "NOTICE" text file as part of its
+          distribution, then any Derivative Works that You distribute must
+          include a readable copy of the attribution notices contained
+          within such NOTICE file, excluding those notices that do not
+          pertain to any part of the Derivative Works, in at least one
+          of the following places: within a NOTICE text file distributed
+          as part of the Derivative Works; within the Source form or
+          documentation, if provided along with the Derivative Works; or,
+          within a display generated by the Derivative Works, if and
+          wherever such third-party notices normally appear. The contents
+          of the NOTICE file are for informational purposes only and
+          do not modify the License. You may add Your own attribution
+          notices within Derivative Works that You distribute, alongside
+          or as an addendum to the NOTICE text from the Work, provided
+          that such additional attribution notices cannot be construed
+          as modifying the License.
+
+      You may add Your own copyright statement to Your modifications and
+      may provide additional or different license terms and conditions
+      for use, reproduction, or distribution of Your modifications, or
+      for any such Derivative Works as a whole, provided Your use,
+      reproduction, and distribution of the Work otherwise complies with
+      the conditions stated in this License.
+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+      implied, including, without limitation, any warranties or conditions
+      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+      PARTICULAR PURPOSE. You are solely responsible for determining the
+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
+      result of this License or out of the use or inability to use the
+      Work (including but not limited to damages for loss of goodwill,
+      work stoppage, computer failure or malfunction, or any and all
+      other commercial damages or losses), even if such Contributor
+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.

PRIVACY.md

@@ -0,0 +1,42 @@
+## Privacy
+
+> Last updated: April 15, 2024
+
+Users of HuggingChat are authenticated through their HF user account.
+
+We endorse Privacy by Design. As such, your conversations are private to you and will not be shared with anyone, including model authors, for any purpose, including for research or model training purposes.
+
+You conversation data will only be stored to let you access past conversations. You can click on the Delete icon to delete any past conversation at any moment.
+
+🗓 Please also consult huggingface.co's main privacy policy at <https://huggingface.co/privacy>. To exercise any of your legal privacy rights, please send an email to <privacy@huggingface.co>.
+
+## About available LLMs
+
+The goal of this app is to showcase that it is now possible to build an open source alternative to ChatGPT. 💪
+
+We aim to always provide a diverse set of state of the art open LLMs, hence we rotate the available models over time.
+
+Historically, HuggingChat has been running models such as:
+
+- [Llama 2 70B](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf)
+- [CodeLlama 35B](https://about.fb.com/news/2023/08/code-llama-ai-for-coding/)
+- [Falcon 180B](https://www.tii.ae/news/technology-innovation-institute-introduces-worlds-most-powerful-open-llm-falcon-180b)
+- [Mistral 7B](https://mistral.ai/news/announcing-mistral-7b/)
+- [Cohere Command R+](https://huggingface.co/chat/models/CohereForAI/c4ai-command-r-plus)
+- [Google Gemma 7B](https://huggingface.co/chat/models/google/gemma-1.1-7b-it)
+
+This is only a partial list. Check the [models](https://huggingface.co/chat/models/) page for up-to-date list of the best available LLMs.
+
+## Technical details
+
+This app is running in a [Space](https://huggingface.co/docs/hub/spaces-overview), which entails that the code for this UI is publicly visible [inside the Space repo](https://huggingface.co/spaces/huggingchat/chat-ui/tree/main).
+
+**Further development takes place on the [huggingface/chat-ui GitHub repo](https://github.com/huggingface/chat-ui).**
+
+The inference backend is running the optimized [text-generation-inference](https://github.com/huggingface/text-generation-inference) on HuggingFace's Inference API infrastructure.
+
+It is therefore possible to deploy a copy of this app to a Space and customize it (swap model, add some UI elements, or store user messages according to your own Terms and conditions). You can also 1-click deploy your own instance using the [Chat UI Spaces Docker template](https://huggingface.co/new-space?template=huggingchat/chat-ui-template).
+
+We welcome any feedback on this app: please participate to the public discussion at <https://huggingface.co/spaces/huggingchat/chat-ui/discussions>
+
+<a target="_blank" href="https://huggingface.co/spaces/huggingchat/chat-ui/discussions"><img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-a-discussion-xl.svg" title="open a discussion"></a>

PROMPTS.md

@@ -0,0 +1,69 @@
+# Prompt templates
+
+These are the templates used to format the conversation history for different models used in HuggingChat. Set them in your `.env.local` [like so](https://github.com/huggingface/chat-ui#chatprompttemplate).
+
+## Llama 2
+
+```env
+<s>[INST] <<SYS>>\n{{preprompt}}\n<</SYS>>\n\n{{#each messages}}{{#ifUser}}{{content}} [/INST] {{/ifUser}}{{#ifAssistant}}{{content}} </s><s>[INST] {{/ifAssistant}}{{/each}}
+```
+
+## CodeLlama
+
+```env
+<s>[INST] <<SYS>>\n{{preprompt}}\n<</SYS>>\n\n{{#each messages}}{{#ifUser}}{{content}} [/INST] {{/ifUser}}{{#ifAssistant}}{{content}} </s><s>[INST] {{/ifAssistant}}{{/each}}
+```
+
+## Falcon
+
+```env
+System: {{preprompt}}\nUser:{{#each messages}}{{#ifUser}}{{content}}\nFalcon:{{/ifUser}}{{#ifAssistant}}{{content}}\nUser:{{/ifAssistant}}{{/each}}
+```
+
+## Mistral
+
+```env
+<s>{{#each messages}}{{#ifUser}}[INST] {{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}} {{content}} [/INST]{{/ifUser}}{{#ifAssistant}}{{content}}</s> {{/ifAssistant}}{{/each}}
+```
+
+## Zephyr
+
+```env
+<|system|>\n{{preprompt}}</s>\n{{#each messages}}{{#ifUser}}<|user|>\n{{content}}</s>\n<|assistant|>\n{{/ifUser}}{{#ifAssistant}}{{content}}</s>\n{{/ifAssistant}}{{/each}}
+```
+
+## IDEFICS
+
+```env
+{{#each messages}}{{#ifUser}}User: {{content}}{{/ifUser}}<end_of_utterance>\nAssistant: {{#ifAssistant}}{{content}}\n{{/ifAssistant}}{{/each}}
+```
+
+## OpenChat
+
+```env
+<s>{{#each messages}}{{#ifUser}}GPT4 User: {{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}}{{content}}<|end_of_turn|>GPT4 Assistant: {{/ifUser}}{{#ifAssistant}}{{content}}<|end_of_turn|>{{/ifAssistant}}{{/each}}
+```
+
+## Mixtral
+
+```env
+<s> {{#each messages}}{{#ifUser}}[INST]{{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}} {{content}} [/INST]{{/ifUser}}{{#ifAssistant}} {{content}}</s> {{/ifAssistant}}{{/each}}
+```
+
+## ChatML
+
+```env
+{{#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}}
+```
+
+## CodeLlama 70B
+
+```env
+<s>{{#if @root.preprompt}}Source: system\n\n {{@root.preprompt}} <step> {{/if}}{{#each messages}}{{#ifUser}}Source: user\n\n {{content}} <step> {{/ifUser}}{{#ifAssistant}}Source: assistant\n\n {{content}} <step> {{/ifAssistant}}{{/each}}Source: assistant\nDestination: user\n\n ``
+```
+
+## Gemma
+
+```env
+{{#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}}
+```

README.md

@@ -3,5 +3,832 @@ title: chat-ui
 emoji: 🔥
 colorFrom: purple
 colorTo: purple
-sdk: static
+sdk: docker
+pinned: false
+license: apache-2.0
+base_path: /chat
+app_port: 3000
+failure_strategy: rollback
+load_balancing_strategy: random
 ---
+
+# Chat UI
+
+![Chat UI repository thumbnail](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/chatui-websearch.png)
+
+A chat interface using open source models, eg OpenAssistant or Llama. It is a SvelteKit app and it powers the [HuggingChat app on hf.co/chat](https://huggingface.co/chat).
+
+0. [No Setup Deploy](#no-setup-deploy)
+1. [Setup](#setup)
+2. [Launch](#launch)
+3. [Web Search](#web-search)
+4. [Text Embedding Models](#text-embedding-models)
+5. [Extra parameters](#extra-parameters)
+6. [Common issues](#common-issues)
+7. [Deploying to a HF Space](#deploying-to-a-hf-space)
+8. [Building](#building)
+
+## No Setup Deploy
+
+If you don't want to configure, setup, and launch your own Chat UI yourself, you can use this option as a fast deploy alternative.
+
+You can deploy your own customized Chat UI instance with any supported [LLM](https://huggingface.co/models?pipeline_tag=text-generation&sort=trending) of your choice on [Hugging Face Spaces](https://huggingface.co/spaces). To do so, use the chat-ui template [available here](https://huggingface.co/new-space?template=huggingchat/chat-ui-template).
+
+Set `HF_TOKEN` in [Space secrets](https://huggingface.co/docs/hub/spaces-overview#managing-secrets-and-environment-variables) to deploy a model with gated access or a model in a private repository. It's also compatible with [Inference for PROs](https://huggingface.co/blog/inference-pro) curated list of powerful models with higher rate limits. Make sure to create your personal token first in your [User Access Tokens settings](https://huggingface.co/settings/tokens).
+
+Read the full tutorial [here](https://huggingface.co/docs/hub/spaces-sdks-docker-chatui#chatui-on-spaces).
+
+## Setup
+
+The default config for Chat UI is stored in the `.env` file. You will need to override some values to get Chat UI to run locally. This is done in `.env.local`.
+
+Start by creating a `.env.local` file in the root of the repository. The bare minimum config you need to get Chat UI to run locally is the following:
+
+```env
+MONGODB_URL=<the URL to your MongoDB instance>
+HF_TOKEN=<your access token>
+```
+
+### Database
+
+The chat history is stored in a MongoDB instance, and having a DB instance available is needed for Chat UI to work.
+
+You can use a local MongoDB instance. The easiest way is to spin one up using docker:
+
+```bash
+docker run -d -p 27017:27017 --name mongo-chatui mongo:latest
+```
+
+In which case the url of your DB will be `MONGODB_URL=mongodb://localhost:27017`.
+
+Alternatively, you can use a [free MongoDB Atlas](https://www.mongodb.com/pricing) instance for this, Chat UI should fit comfortably within their free tier. After which you can set the `MONGODB_URL` variable in `.env.local` to match your instance.
+
+### Hugging Face Access Token
+
+If you use a remote inference endpoint, you will need a Hugging Face access token to run Chat UI locally. You can get one from [your Hugging Face profile](https://huggingface.co/settings/tokens).
+
+## Launch
+
+After you're done with the `.env.local` file you can run Chat UI locally with:
+
+```bash
+npm install
+npm run dev
+```
+
+## Web Search
+
+Chat UI features a powerful Web Search feature. It works by:
+
+1. Generating an appropriate search query from the user prompt.
+2. Performing web search and extracting content from webpages.
+3. Creating embeddings from texts using a text embedding model.
+4. From these embeddings, find the ones that are closest to the user query using a vector similarity search. Specifically, we use `inner product` distance.
+5. Get the corresponding texts to those closest embeddings and perform [Retrieval-Augmented Generation](https://huggingface.co/papers/2005.11401) (i.e. expand user prompt by adding those texts so that an LLM can use this information).
+
+## Text Embedding Models
+
+By default (for backward compatibility), when `TEXT_EMBEDDING_MODELS` environment variable is not defined, [transformers.js](https://huggingface.co/docs/transformers.js) embedding models will be used for embedding tasks, specifically, [Xenova/gte-small](https://huggingface.co/Xenova/gte-small) model.
+
+You can customize the embedding model by setting `TEXT_EMBEDDING_MODELS` in your `.env.local` file. For example:
+
+```env
+TEXT_EMBEDDING_MODELS = `[
+  {
+    "name": "Xenova/gte-small",
+    "displayName": "Xenova/gte-small",
+    "description": "locally running embedding",
+    "chunkCharLength": 512,
+    "endpoints": [
+      {"type": "transformersjs"}
+    ]
+  },
+  {
+    "name": "intfloat/e5-base-v2",
+    "displayName": "intfloat/e5-base-v2",
+    "description": "hosted embedding model",
+    "chunkCharLength": 768,
+    "preQuery": "query: ", # See https://huggingface.co/intfloat/e5-base-v2#faq
+    "prePassage": "passage: ", # See https://huggingface.co/intfloat/e5-base-v2#faq
+    "endpoints": [
+      {
+        "type": "tei",
+        "url": "http://127.0.0.1:8080/",
+        "authorization": "TOKEN_TYPE TOKEN" // optional authorization field. Example: "Basic VVNFUjpQQVNT"
+      }
+    ]
+  }
+]`
+```
+
+The required fields are `name`, `chunkCharLength` and `endpoints`.
+Supported text embedding backends are: [`transformers.js`](https://huggingface.co/docs/transformers.js), [`TEI`](https://github.com/huggingface/text-embeddings-inference) and [`OpenAI`](https://platform.openai.com/docs/guides/embeddings). `transformers.js` models run locally as part of `chat-ui`, whereas `TEI` models run in a different environment & accessed through an API endpoint. `openai` models are accessed through the [OpenAI API](https://platform.openai.com/docs/guides/embeddings).
+
+When more than one embedding models are supplied in `.env.local` file, the first will be used by default, and the others will only be used on LLM's which configured `embeddingModel` to the name of the model.
+
+## Extra parameters
+
+### OpenID connect
+
+The login feature is disabled by default and users are attributed a unique ID based on their browser. But if you want to use OpenID to authenticate your users, you can add the following to your `.env.local` file:
+
+```env
+OPENID_CONFIG=`{
+  PROVIDER_URL: "<your OIDC issuer>",
+  CLIENT_ID: "<your OIDC client ID>",
+  CLIENT_SECRET: "<your OIDC client secret>",
+  SCOPES: "openid profile",
+  TOLERANCE: // optional
+  RESOURCE: // optional
+}`
+```
+
+These variables will enable the openID sign-in modal for users.
+
+### Theming
+
+You can use a few environment variables to customize the look and feel of chat-ui. These are by default:
+
+```env
+PUBLIC_APP_NAME=ChatUI
+PUBLIC_APP_ASSETS=chatui
+PUBLIC_APP_COLOR=blue
+PUBLIC_APP_DESCRIPTION="Making the community's best AI chat models available to everyone."
+PUBLIC_APP_DATA_SHARING=
+PUBLIC_APP_DISCLAIMER=
+```
+
+- `PUBLIC_APP_NAME` The name used as a title throughout the app.
+- `PUBLIC_APP_ASSETS` Is used to find logos & favicons in `static/$PUBLIC_APP_ASSETS`, current options are `chatui` and `huggingchat`.
+- `PUBLIC_APP_COLOR` Can be any of the [tailwind colors](https://tailwindcss.com/docs/customizing-colors#default-color-palette).
+- `PUBLIC_APP_DATA_SHARING` Can be set to 1 to add a toggle in the user settings that lets your users opt-in to data sharing with models creator.
+- `PUBLIC_APP_DISCLAIMER` If set to 1, we show a disclaimer about generated outputs on login.
+
+### Web Search config
+
+You can enable the web search through an API by adding `YDC_API_KEY` ([docs.you.com](https://docs.you.com)) or `SERPER_API_KEY` ([serper.dev](https://serper.dev/)) or `SERPAPI_KEY` ([serpapi.com](https://serpapi.com/)) or `SERPSTACK_API_KEY` ([serpstack.com](https://serpstack.com/)) to your `.env.local`.
+
+You can also simply enable the local google websearch by setting `USE_LOCAL_WEBSEARCH=true` in your `.env.local` or specify a SearXNG instance by adding the query URL to `SEARXNG_QUERY_URL`.
+
+### Custom models
+
+You can customize the parameters passed to the model or even use a new model by updating the `MODELS` variable in your `.env.local`. The default one can be found in `.env` and looks like this :
+
+```env
+MODELS=`[
+  {
+    "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.",
+    "websiteUrl": "https://mistral.ai/news/announcing-mistral-7b/",
+    "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?"
+      }
+    ]
+  }
+]`
+
+```
+
+You can change things like the parameters, or customize the preprompt to better suit your needs. You can also add more models by adding more objects to the array, with different preprompts for example.
+
+#### chatPromptTemplate
+
+When querying the model for a chat response, the `chatPromptTemplate` template is used. `messages` is an array of chat messages, it has the format `[{ content: string }, ...]`. To identify if a message is a user message or an assistant message the `ifUser` and `ifAssistant` block helpers can be used.
+
+The following is the default `chatPromptTemplate`, although newlines and indentiation have been added for readability. You can find the prompts used in production for HuggingChat [here](https://github.com/huggingface/chat-ui/blob/main/PROMPTS.md).
+
+```prompt
+{{preprompt}}
+{{#each messages}}
+  {{#ifUser}}{{@root.userMessageToken}}{{content}}{{@root.userMessageEndToken}}{{/ifUser}}
+  {{#ifAssistant}}{{@root.assistantMessageToken}}{{content}}{{@root.assistantMessageEndToken}}{{/ifAssistant}}
+{{/each}}
+{{assistantMessageToken}}
+```
+
+#### Multi modal model
+
+We currently only support IDEFICS as a multimodal model, hosted on TGI. You can enable it by using the following config (if you have a PRO HF Api token):
+
+```env
+    {
+      "name": "HuggingFaceM4/idefics-80b-instruct",
+      "multimodal" : true,
+      "description": "IDEFICS is the new multimodal model by Hugging Face.",
+      "preprompt": "",
+      "chatPromptTemplate" : "{{#each messages}}{{#ifUser}}User: {{content}}{{/ifUser}}<end_of_utterance>\nAssistant: {{#ifAssistant}}{{content}}\n{{/ifAssistant}}{{/each}}",
+      "parameters": {
+        "temperature": 0.1,
+        "top_p": 0.95,
+        "repetition_penalty": 1.2,
+        "top_k": 12,
+        "truncate": 1000,
+        "max_new_tokens": 1024,
+        "stop": ["<end_of_utterance>", "User:", "\nUser:"]
+      }
+    }
+```
+
+#### Running your own models using a custom endpoint
+
+If you want to, instead of hitting models on the Hugging Face Inference API, you can run your own models locally.
+
+A good option is to hit a [text-generation-inference](https://github.com/huggingface/text-generation-inference) endpoint. This is what is done in the official [Chat UI Spaces Docker template](https://huggingface.co/new-space?template=huggingchat/chat-ui-template) for instance: both this app and a text-generation-inference server run inside the same container.
+
+To do this, you can add your own endpoints to the `MODELS` variable in `.env.local`, by adding an `"endpoints"` key for each model in `MODELS`.
+
+```env
+{
+// rest of the model config here
+"endpoints": [{
+  "type" : "tgi",
+  "url": "https://HOST:PORT",
+  }]
+}
+```
+
+If `endpoints` are left unspecified, ChatUI will look for the model on the hosted Hugging Face inference API using the model name.
+
+##### OpenAI API compatible models
+
+Chat UI can be used with any API server that supports OpenAI API compatibility, for example [text-generation-webui](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/openai), [LocalAI](https://github.com/go-skynet/LocalAI), [FastChat](https://github.com/lm-sys/FastChat/blob/main/docs/openai_api.md), [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), and [ialacol](https://github.com/chenhunghan/ialacol).
+
+The following example config makes Chat UI works with [text-generation-webui](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/openai), the `endpoint.baseUrl` is the url of the OpenAI API compatible server, this overrides the baseUrl to be used by OpenAI instance. The `endpoint.completion` determine which endpoint to be used, default is `chat_completions` which uses `v1/chat/completions`, change to `endpoint.completion` to `completions` to use the `v1/completions` endpoint.
+
+```
+MODELS=`[
+  {
+    "name": "text-generation-webui",
+    "id": "text-generation-webui",
+    "parameters": {
+      "temperature": 0.9,
+      "top_p": 0.95,
+      "repetition_penalty": 1.2,
+      "top_k": 50,
+      "truncate": 1000,
+      "max_new_tokens": 1024,
+      "stop": []
+    },
+    "endpoints": [{
+      "type" : "openai",
+      "baseURL": "http://localhost:8000/v1"
+    }]
+  }
+]`
+
+```
+
+The `openai` type includes official OpenAI models. You can add, for example, GPT4/GPT3.5 as a "openai" model:
+
+```
+OPENAI_API_KEY=#your openai api key here
+MODELS=`[{
+      "name": "gpt-4",
+      "displayName": "GPT 4",
+      "endpoints" : [{
+        "type": "openai"
+      }]
+},
+      {
+      "name": "gpt-3.5-turbo",
+      "displayName": "GPT 3.5 Turbo",
+      "endpoints" : [{
+        "type": "openai"
+      }]
+}]`
+```
+
+You may also consume any model provider that provides compatible OpenAI API endpoint. For example, you may self-host [Portkey](https://github.com/Portkey-AI/gateway) gateway and experiment with Claude or GPTs offered by Azure OpenAI. Example for Claude from Anthropic:
+
+```
+MODELS=`[{
+  "name": "claude-2.1",
+  "displayName": "Claude 2.1",
+  "description": "Anthropic has been founded by former OpenAI researchers...",
+  "parameters": {
+      "temperature": 0.5,
+      "max_new_tokens": 4096,
+  },
+  "endpoints": [
+      {
+          "type": "openai",
+          "baseURL": "https://gateway.example.com/v1",
+          "defaultHeaders": {
+              "x-portkey-config": '{"provider":"anthropic","api_key":"sk-ant-abc...xyz"}'
+          }
+      }
+  ]
+}]`
+```
+
+Example for GPT 4 deployed on Azure OpenAI:
+
+```
+MODELS=`[{
+  "id": "gpt-4-1106-preview",
+  "name": "gpt-4-1106-preview",
+  "displayName": "gpt-4-1106-preview",
+  "parameters": {
+      "temperature": 0.5,
+      "max_new_tokens": 4096,
+  },
+  "endpoints": [
+      {
+          "type": "openai",
+          "baseURL": "https://{resource-name}.openai.azure.com/openai/deployments/{deployment-id}",
+          "defaultHeaders": {
+              "api-key": "{api-key}"
+          },
+          "defaultQuery": {
+              "api-version": "2023-05-15"
+          }
+      }
+  ]
+}]`
+```
+
+Or try Mistral from [Deepinfra](https://deepinfra.com/mistralai/Mistral-7B-Instruct-v0.1/api?example=openai-http):
+
+> Note, apiKey can either be set custom per endpoint, or globally using `OPENAI_API_KEY` variable.
+
+```
+MODELS=`[{
+  "name": "mistral-7b",
+  "displayName": "Mistral 7B",
+  "description": "A 7B dense Transformer, fast-deployed and easily customisable. Small, yet powerful for a variety of use cases. Supports English and code, and a 8k context window.",
+  "parameters": {
+      "temperature": 0.5,
+      "max_new_tokens": 4096,
+  },
+  "endpoints": [
+      {
+          "type": "openai",
+          "baseURL": "https://api.deepinfra.com/v1/openai",
+          "apiKey": "abc...xyz"
+      }
+  ]
+}]`
+```
+
+##### Llama.cpp API server
+
+chat-ui also supports the llama.cpp API server directly without the need for an adapter. You can do this using the `llamacpp` endpoint type.
+
+If you want to run chat-ui with llama.cpp, you can do the following, using Zephyr as an example model:
+
+1. Get [the weights](https://huggingface.co/TheBloke/zephyr-7B-beta-GGUF/tree/main) from the hub
+2. Run the server with the following command: `./server -m models/zephyr-7b-beta.Q4_K_M.gguf -c 2048 -np 3`
+3. Add the following to your `.env.local`:
+
+```env
+MODELS=`[
+  {
+      "name": "Local Zephyr",
+      "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": 0.1,
+        "top_p": 0.95,
+        "repetition_penalty": 1.2,
+        "top_k": 50,
+        "truncate": 1000,
+        "max_new_tokens": 2048,
+        "stop": ["</s>"]
+      },
+      "endpoints": [
+        {
+         "url": "http://127.0.0.1:8080",
+         "type": "llamacpp"
+        }
+      ]
+  }
+]`
+```
+
+Start chat-ui with `npm run dev` and you should be able to chat with Zephyr locally.
+
+#### Ollama
+
+We also support the Ollama inference server. Spin up a model with
+
+```cli
+ollama run mistral
+```
+
+Then specify the endpoints like so:
+
+```env
+MODELS=`[
+  {
+      "name": "Ollama Mistral",
+      "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>"]
+      },
+      "endpoints": [
+        {
+         "type": "ollama",
+         "url" : "http://127.0.0.1:11434",
+         "ollamaName" : "mistral"
+        }
+      ]
+  }
+]`
+```
+
+#### Anthropic
+
+We also support Anthropic models through the official SDK. You may provide your API key via the `ANTHROPIC_API_KEY` env variable, or alternatively, through the `endpoints.apiKey` as per the following example.
+
+```
+MODELS=`[
+  {
+      "name": "claude-3-sonnet-20240229",
+      "displayName": "Claude 3 Sonnet",
+      "description": "Ideal balance of intelligence and speed",
+      "parameters": {
+        "max_new_tokens": 4096,
+      },
+      "endpoints": [
+        {
+          "type": "anthropic",
+          // optionals
+          "apiKey": "sk-ant-...",
+          "baseURL": "https://api.anthropic.com",
+          defaultHeaders: {},
+          defaultQuery: {}
+        }
+      ]
+  },
+  {
+      "name": "claude-3-opus-20240229",
+      "displayName": "Claude 3 Opus",
+      "description": "Most powerful model for highly complex tasks",
+      "parameters": {
+         "max_new_tokens": 4096
+      },
+      "endpoints": [
+        {
+          "type": "anthropic",
+          // optionals
+          "apiKey": "sk-ant-...",
+          "baseURL": "https://api.anthropic.com",
+          defaultHeaders: {},
+          defaultQuery: {}
+        }
+      ]
+  }
+]`
+```
+
+#### Amazon
+
+You can also specify your Amazon SageMaker instance as an endpoint for chat-ui. The config goes like this:
+
+```env
+"endpoints": [
+    {
+      "type" : "aws",
+      "service" : "sagemaker"
+      "url": "",
+      "accessKey": "",
+      "secretKey" : "",
+      "sessionToken": "",
+      "region": "",
+
+      "weight": 1
+    }
+]
+```
+
+You can also set `"service" : "lambda"` to use a lambda instance.
+
+You can get the `accessKey` and `secretKey` from your AWS user, under programmatic access.
+
+#### Cloudflare Workers AI
+
+You can also use Cloudflare Workers AI to run your own models with serverless inference.
+
+You will need to have a Cloudflare account, then get your [account ID](https://developers.cloudflare.com/fundamentals/setup/find-account-and-zone-ids/) as well as your [API token](https://developers.cloudflare.com/workers-ai/get-started/rest-api/#1-get-an-api-token) for Workers AI.
+
+You can either specify them directly in your `.env.local` using the `CLOUDFLARE_ACCOUNT_ID` and `CLOUDFLARE_API_TOKEN` variables, or you can set them directly in the endpoint config.
+
+You can find the list of models available on Cloudflare [here](https://developers.cloudflare.com/workers-ai/models/#text-generation).
+
+```env
+  {
+  "name" : "nousresearch/hermes-2-pro-mistral-7b",
+  "tokenizer": "nousresearch/hermes-2-pro-mistral-7b",
+  "parameters": {
+    "stop": ["<|im_end|>"]
+  },
+  "endpoints" : [
+    {
+      "type" : "cloudflare"
+      <!-- optionally specify these
+      "accountId": "your-account-id",
+      "authToken": "your-api-token"
+      -->
+    }
+  ]
+}
+```
+
+> [!NOTE]  
+> Cloudlare Workers AI currently do not support custom sampling parameters like temperature, top_p, etc.
+
+#### Cohere
+
+You can also use Cohere to run their models directly from chat-ui. You will need to have a Cohere account, then get your [API token](https://dashboard.cohere.com/api-keys). You can either specify it directly in your `.env.local` using the `COHERE_API_TOKEN` variable, or you can set it in the endpoint config.
+
+Here is an example of a Cohere model config. You can set which model you want to use by setting the `id` field to the model name.
+
+```env
+  {
+    "name" : "CohereForAI/c4ai-command-r-v01",
+    "id": "command-r",
+    "description": "C4AI Command-R is a research release of a 35 billion parameter highly performant generative model",
+    "endpoints": [
+      {
+        "type": "cohere",
+        <!-- optionally specify these, or use COHERE_API_TOKEN
+        "apiKey": "your-api-token"
+        -->
+      }
+    ]
+  }
+```
+
+##### Google Vertex models
+
+Chat UI can connect to the google Vertex API endpoints ([List of supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models)).
+
+To enable:
+
+1. [Select](https://console.cloud.google.com/project) or [create](https://cloud.google.com/resource-manager/docs/creating-managing-projects#creating_a_project) a Google Cloud project.
+1. [Enable billing for your project](https://cloud.google.com/billing/docs/how-to/modify-project).
+1. [Enable the Vertex AI API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com).
+1. [Set up authentication with a service account](https://cloud.google.com/docs/authentication/getting-started)
+   so you can access the API from your local workstation.
+
+The service account credentials file can be imported as an environmental variable:
+
+```env
+    GOOGLE_APPLICATION_CREDENTIALS = clientid.json
+```
+
+Make sure your docker container has access to the file and the variable is correctly set.
+Afterwards Google Vertex endpoints can be configured as following:
+
+```
+MODELS=`[
+//...
+    {
+       "name": "gemini-1.5-pro",
+       "displayName": "Vertex Gemini Pro 1.5",
+       "endpoints" : [{
+          "type": "vertex",
+          "project": "abc-xyz",
+          "location": "europe-west3",
+          "model": "gemini-1.5-pro-preview-0409", // model-name
+
+          // Optional
+          "safetyThreshold": "BLOCK_MEDIUM_AND_ABOVE",
+          "apiEndpoint": "", // alternative api endpoint url
+       }]
+     },
+]`
+
+```
+
+##### LangServe
+
+LangChain applications that are deployed using LangServe can be called with the following config:
+
+```
+MODELS=`[
+//...
+    {
+       "name": "summarization-chain", //model-name
+       "endpoints" : [{
+         "type": "langserve",
+         "url" : "http://127.0.0.1:8100",
+       }]
+     },
+]`
+
+```
+
+### Custom endpoint authorization
+
+#### Basic and Bearer
+
+Custom endpoints may require authorization, depending on how you configure them. Authentication will usually be set either with `Basic` or `Bearer`.
+
+For `Basic` we will need to generate a base64 encoding of the username and password.
+
+`echo -n "USER:PASS" | base64`
+
+> VVNFUjpQQVNT
+
+For `Bearer` you can use a token, which can be grabbed from [here](https://huggingface.co/settings/tokens).
+
+You can then add the generated information and the `authorization` parameter to your `.env.local`.
+
+```env
+"endpoints": [
+  {
+    "url": "https://HOST:PORT",
+    "authorization": "Basic VVNFUjpQQVNT",
+  }
+]
+```
+
+Please note that if `HF_TOKEN` is also set or not empty, it will take precedence.
+
+#### Models hosted on multiple custom endpoints
+
+If the model being hosted will be available on multiple servers/instances add the `weight` parameter to your `.env.local`. The `weight` will be used to determine the probability of requesting a particular endpoint.
+
+```env
+"endpoints": [
+  {
+    "url": "https://HOST:PORT",
+    "weight": 1
+  },
+  {
+    "url": "https://HOST:PORT",
+    "weight": 2
+  }
+  ...
+]
+```
+
+#### Client Certificate Authentication (mTLS)
+
+Custom endpoints may require client certificate authentication, depending on how you configure them. To enable mTLS between Chat UI and your custom endpoint, you will need to set the `USE_CLIENT_CERTIFICATE` to `true`, and add the `CERT_PATH` and `KEY_PATH` parameters to your `.env.local`. These parameters should point to the location of the certificate and key files on your local machine. The certificate and key files should be in PEM format. The key file can be encrypted with a passphrase, in which case you will also need to add the `CLIENT_KEY_PASSWORD` parameter to your `.env.local`.
+
+If you're using a certificate signed by a private CA, you will also need to add the `CA_PATH` parameter to your `.env.local`. This parameter should point to the location of the CA certificate file on your local machine.
+
+If you're using a self-signed certificate, e.g. for testing or development purposes, you can set the `REJECT_UNAUTHORIZED` parameter to `false` in your `.env.local`. This will disable certificate validation, and allow Chat UI to connect to your custom endpoint.
+
+#### Specific Embedding Model
+
+A model can use any of the embedding models defined in `.env.local`, (currently used when web searching),
+by default it will use the first embedding model, but it can be changed with the field `embeddingModel`:
+
+```env
+TEXT_EMBEDDING_MODELS = `[
+  {
+    "name": "Xenova/gte-small",
+    "chunkCharLength": 512,
+    "endpoints": [
+      {"type": "transformersjs"}
+    ]
+  },
+  {
+    "name": "intfloat/e5-base-v2",
+    "chunkCharLength": 768,
+    "endpoints": [
+      {"type": "tei", "url": "http://127.0.0.1:8080/", "authorization": "Basic VVNFUjpQQVNT"},
+      {"type": "tei", "url": "http://127.0.0.1:8081/"}
+    ]
+  }
+]`
+
+MODELS=`[
+  {
+      "name": "Ollama Mistral",
+      "chatPromptTemplate": "...",
+      "embeddingModel": "intfloat/e5-base-v2"
+      "parameters": {
+        ...
+      },
+      "endpoints": [
+        ...
+      ]
+  }
+]`
+```
+
+## Common issues
+
+### 403：You don't have access to this conversation
+
+Most likely you are running chat-ui over HTTP. The recommended option is to setup something like NGINX to handle HTTPS and proxy the requests to chat-ui. If you really need to run over HTTP you can add `ALLOW_INSECURE_COOKIES=true` to your `.env.local`.
+
+Make sure to set your `PUBLIC_ORIGIN` in your `.env.local` to the correct URL as well.
+
+## Deploying to a HF Space
+
+Create a `DOTENV_LOCAL` secret to your HF space with the content of your .env.local, and they will be picked up automatically when you run.
+
+## Building
+
+To create a production version of your app:
+
+```bash
+npm run build
+```
+
+You can preview the production build with `npm run preview`.
+
+> To deploy your app, you may need to install an [adapter](https://kit.svelte.dev/docs/adapters) for your target environment.
+
+## Config changes for HuggingChat
+
+The config file for HuggingChat is stored in the `.env.template` file at the root of the repository. It is the single source of truth that is used to generate the actual `.env.local` file using our CI/CD pipeline. See [updateProdEnv](https://github.com/huggingface/chat-ui/blob/cdb33a9583f5339ade724db615347393ef48f5cd/scripts/updateProdEnv.ts) for more details.
+
+> [!TIP]
+> If you want to make changes to the model config used in production for HuggingChat, you should do so against `.env.template`.
+
+We currently use the following secrets for deploying HuggingChat in addition to the `.env.template` above:
+
+- `MONGODB_URL`
+- `HF_TOKEN`
+- `OPENID_CONFIG`
+- `SERPER_API_KEY`
+
+### Running a copy of HuggingChat locally
+
+If you want to run an exact copy of HuggingChat locally, you will need to do the following first:
+
+1. Create an [OAuth App on the hub](https://huggingface.co/settings/applications/new) with `openid profile email` permissions. Make sure to set the callback URL to something like `http://localhost:5173/chat/login/callback` which matches the right path for your local instance.
+2. Create a [HF Token](https://huggingface.co/settings/tokens) with your Hugging Face account. You will need a Pro account to be able to access some of the larger models available through HuggingChat.
+3. Create a free account with [serper.dev](https://serper.dev/) (you will get 2500 free search queries)
+4. Run an instance of mongoDB, however you want. (Local or remote)
+
+You can then create a new `.env.SECRET_CONFIG` file with the following content
+
+```env
+MONGODB_URL=<link to your mongo DB from step 4>
+HF_TOKEN=<your HF token from step 2>
+OPENID_CONFIG=`{
+  PROVIDER_URL: "https://huggingface.co",
+  CLIENT_ID: "<your client ID from step 1>",
+  CLIENT_SECRET: "<your client secret from step 1>",
+}`
+SERPER_API_KEY=<your serper API key from step 3>
+MESSAGES_BEFORE_LOGIN=<can be any numerical value, or set to 0 to require login>
+```
+
+You can then run `npm run updateLocalEnv` in the root of chat-ui. This will create a `.env.local` file which combines the `.env.template` and the `.env.SECRET_CONFIG` file. You can then run `npm run dev` to start your local instance of HuggingChat.
+
+### Populate database
+
+> [!WARNING]
+> The `MONGODB_URL` used for this script will be fetched from `.env.local`. Make sure it's correct! The command runs directly on the database.
+
+You can populate the database using faker data using the `populate` script:
+
+```bash
+npm run populate <flags here>
+```
+
+At least one flag must be specified, the following flags are available:
+
+- `reset` - resets the database
+- `all` - populates all tables
+- `users` - populates the users table
+- `settings` - populates the settings table for existing users
+- `assistants` - populates the assistants table for existing users
+- `conversations` - populates the conversations table for existing users
+
+For example, you could use it like so:
+
+```bash
+npm run populate reset
+```
+
+to clear out the database. Then login in the app to create your user and run the following command:
+
+```bash
+npm run populate users settings assistants conversations
+```
+
+to populate the database with fake data, including fake conversations and assistants for your user.

_app/env.js

@@ -1 +0,0 @@
-export const env={}

_app/immutable/assets/0.DViICDYp.css

@@ -1 +0,0 @@
-*,:before,:after{box-sizing:border-box;border-width:0;border-style:solid;border-color:#e5e7eb}:before,:after{--tw-content: ""}html,:host{line-height:1.5;-webkit-text-size-adjust:100%;-moz-tab-size:4;-o-tab-size:4;tab-size:4;font-family:ui-sans-serif,system-ui,sans-serif,"Apple Color Emoji","Segoe UI Emoji",Segoe UI Symbol,"Noto Color Emoji";font-feature-settings:normal;font-variation-settings:normal;-webkit-tap-highlight-color:transparent}body{margin:0;line-height:inherit}hr{height:0;color:inherit;border-top-width:1px}abbr:where([title]){-webkit-text-decoration:underline dotted;text-decoration:underline dotted}h1,h2,h3,h4,h5,h6{font-size:inherit;font-weight:inherit}a{color:inherit;text-decoration:inherit}b,strong{font-weight:bolder}code,kbd,samp,pre{font-family:ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,Liberation Mono,Courier New,monospace;font-feature-settings:normal;font-variation-settings:normal;font-size:1em}small{font-size:80%}sub,sup{font-size:75%;line-height:0;position:relative;vertical-align:baseline}sub{bottom:-.25em}sup{top:-.5em}table{text-indent:0;border-color:inherit;border-collapse:collapse}button,input,optgroup,select,textarea{font-family:inherit;font-feature-settings:inherit;font-variation-settings:inherit;font-size:100%;font-weight:inherit;line-height:inherit;letter-spacing:inherit;color:inherit;margin:0;padding:0}button,select{text-transform:none}button,input:where([type=button]),input:where([type=reset]),input:where([type=submit]){-webkit-appearance:button;background-color:transparent;background-image:none}:-moz-focusring{outline:auto}:-moz-ui-invalid{box-shadow:none}progress{vertical-align:baseline}::-webkit-inner-spin-button,::-webkit-outer-spin-button{height:auto}[type=search]{-webkit-appearance:textfield;outline-offset:-2px}::-webkit-search-decoration{-webkit-appearance:none}::-webkit-file-upload-button{-webkit-appearance:button;font:inherit}summary{display:list-item}blockquote,dl,dd,h1,h2,h3,h4,h5,h6,hr,figure,p,pre{margin:0}fieldset{margin:0;padding:0}legend{padding:0}ol,ul,menu{list-style:none;margin:0;padding:0}dialog{padding:0}textarea{resize:vertical}input::-moz-placeholder,textarea::-moz-placeholder{opacity:1;color:#9ca3af}input::placeholder,textarea::placeholder{opacity:1;color:#9ca3af}button,[role=button]{cursor:pointer}:disabled{cursor:default}img,svg,video,canvas,audio,iframe,embed,object{display:block;vertical-align:middle}img,video{max-width:100%;height:auto}[hidden]{display:none}:root,[data-theme]{background-color:hsl(var(--b1) / var(--tw-bg-opacity, 1));color:hsl(var(--bc) / var(--tw-text-opacity, 1))}html{-webkit-tap-highlight-color:transparent}:root{color-scheme:light;--pf: 259 94% 44%;--sf: 314 100% 40%;--af: 174 75% 39%;--nf: 214 20% 14%;--in: 198 93% 60%;--su: 158 64% 52%;--wa: 43 96% 56%;--er: 0 91% 71%;--inc: 198 100% 12%;--suc: 158 100% 10%;--wac: 43 100% 11%;--erc: 0 100% 14%;--rounded-box: 1rem;--rounded-btn: .5rem;--rounded-badge: 1.9rem;--animation-btn: .25s;--animation-input: .2s;--btn-text-case: uppercase;--btn-focus-scale: .95;--border-btn: 1px;--tab-border: 1px;--tab-radius: .5rem;--p: 259 94% 51%;--pc: 259 96% 91%;--s: 314 100% 47%;--sc: 314 100% 91%;--a: 174 75% 46%;--ac: 174 75% 11%;--n: 214 20% 21%;--nc: 212 19% 87%;--b1: 0 0% 100%;--b2: 0 0% 95%;--b3: 180 2% 90%;--bc: 215 28% 17%}@media (prefers-color-scheme: dark){:root{color-scheme:dark;--pf: 262 80% 43%;--sf: 316 70% 43%;--af: 175 70% 34%;--in: 198 93% 60%;--su: 158 64% 52%;--wa: 43 96% 56%;--er: 0 91% 71%;--inc: 198 100% 12%;--suc: 158 100% 10%;--wac: 43 100% 11%;--erc: 0 100% 14%;--rounded-box: 1rem;--rounded-btn: .5rem;--rounded-badge: 1.9rem;--animation-btn: .25s;--animation-input: .2s;--btn-text-case: uppercase;--btn-focus-scale: .95;--border-btn: 1px;--tab-border: 1px;--tab-radius: .5rem;--p: 262 80% 50%;--pc: 0 0% 100%;--s: 316 70% 50%;--sc: 0 0% 100%;--a: 175 70% 41%;--ac: 0 0% 100%;--n: 213 18% 20%;--nf: 212 17% 17%;--nc: 220 13% 69%;--b1: 212 18% 14%;--b2: 213 18% 12%;--b3: 213 18% 10%;--bc: 220 13% 69%}}[data-theme=light]{color-scheme:light;--pf: 259 94% 44%;--sf: 314 100% 40%;--af: 174 75% 39%;--nf: 214 20% 14%;--in: 198 93% 60%;--su: 158 64% 52%;--wa: 43 96% 56%;--er: 0 91% 71%;--inc: 198 100% 12%;--suc: 158 100% 10%;--wac: 43 100% 11%;--erc: 0 100% 14%;--rounded-box: 1rem;--rounded-btn: .5rem;--rounded-badge: 1.9rem;--animation-btn: .25s;--animation-input: .2s;--btn-text-case: uppercase;--btn-focus-scale: .95;--border-btn: 1px;--tab-border: 1px;--tab-radius: .5rem;--p: 259 94% 51%;--pc: 259 96% 91%;--s: 314 100% 47%;--sc: 314 100% 91%;--a: 174 75% 46%;--ac: 174 75% 11%;--n: 214 20% 21%;--nc: 212 19% 87%;--b1: 0 0% 100%;--b2: 0 0% 95%;--b3: 180 2% 90%;--bc: 215 28% 17%}[data-theme=dark]{color-scheme:dark;--pf: 262 80% 43%;--sf: 316 70% 43%;--af: 175 70% 34%;--in: 198 93% 60%;--su: 158 64% 52%;--wa: 43 96% 56%;--er: 0 91% 71%;--inc: 198 100% 12%;--suc: 158 100% 10%;--wac: 43 100% 11%;--erc: 0 100% 14%;--rounded-box: 1rem;--rounded-btn: .5rem;--rounded-badge: 1.9rem;--animation-btn: .25s;--animation-input: .2s;--btn-text-case: uppercase;--btn-focus-scale: .95;--border-btn: 1px;--tab-border: 1px;--tab-radius: .5rem;--p: 262 80% 50%;--pc: 0 0% 100%;--s: 316 70% 50%;--sc: 0 0% 100%;--a: 175 70% 41%;--ac: 0 0% 100%;--n: 213 18% 20%;--nf: 212 17% 17%;--nc: 220 13% 69%;--b1: 212 18% 14%;--b2: 213 18% 12%;--b3: 213 18% 10%;--bc: 220 13% 69%}*,:before,:after{--tw-border-spacing-x: 0;--tw-border-spacing-y: 0;--tw-translate-x: 0;--tw-translate-y: 0;--tw-rotate: 0;--tw-skew-x: 0;--tw-skew-y: 0;--tw-scale-x: 1;--tw-scale-y: 1;--tw-pan-x: ;--tw-pan-y: ;--tw-pinch-zoom: ;--tw-scroll-snap-strictness: proximity;--tw-gradient-from-position: ;--tw-gradient-via-position: ;--tw-gradient-to-position: ;--tw-ordinal: ;--tw-slashed-zero: ;--tw-numeric-figure: ;--tw-numeric-spacing: ;--tw-numeric-fraction: ;--tw-ring-inset: ;--tw-ring-offset-width: 0px;--tw-ring-offset-color: #fff;--tw-ring-color: rgb(59 130 246 / .5);--tw-ring-offset-shadow: 0 0 #0000;--tw-ring-shadow: 0 0 #0000;--tw-shadow: 0 0 #0000;--tw-shadow-colored: 0 0 #0000;--tw-blur: ;--tw-brightness: ;--tw-contrast: ;--tw-grayscale: ;--tw-hue-rotate: ;--tw-invert: ;--tw-saturate: ;--tw-sepia: ;--tw-drop-shadow: ;--tw-backdrop-blur: ;--tw-backdrop-brightness: ;--tw-backdrop-contrast: ;--tw-backdrop-grayscale: ;--tw-backdrop-hue-rotate: ;--tw-backdrop-invert: ;--tw-backdrop-opacity: ;--tw-backdrop-saturate: ;--tw-backdrop-sepia: ;--tw-contain-size: ;--tw-contain-layout: ;--tw-contain-paint: ;--tw-contain-style: }::backdrop{--tw-border-spacing-x: 0;--tw-border-spacing-y: 0;--tw-translate-x: 0;--tw-translate-y: 0;--tw-rotate: 0;--tw-skew-x: 0;--tw-skew-y: 0;--tw-scale-x: 1;--tw-scale-y: 1;--tw-pan-x: ;--tw-pan-y: ;--tw-pinch-zoom: ;--tw-scroll-snap-strictness: proximity;--tw-gradient-from-position: ;--tw-gradient-via-position: ;--tw-gradient-to-position: ;--tw-ordinal: ;--tw-slashed-zero: ;--tw-numeric-figure: ;--tw-numeric-spacing: ;--tw-numeric-fraction: ;--tw-ring-inset: ;--tw-ring-offset-width: 0px;--tw-ring-offset-color: #fff;--tw-ring-color: rgb(59 130 246 / .5);--tw-ring-offset-shadow: 0 0 #0000;--tw-ring-shadow: 0 0 #0000;--tw-shadow: 0 0 #0000;--tw-shadow-colored: 0 0 #0000;--tw-blur: ;--tw-brightness: ;--tw-contrast: ;--tw-grayscale: ;--tw-hue-rotate: ;--tw-invert: ;--tw-saturate: ;--tw-sepia: ;--tw-drop-shadow: ;--tw-backdrop-blur: ;--tw-backdrop-brightness: ;--tw-backdrop-contrast: ;--tw-backdrop-grayscale: ;--tw-backdrop-hue-rotate: ;--tw-backdrop-invert: ;--tw-backdrop-opacity: ;--tw-backdrop-saturate: ;--tw-backdrop-sepia: ;--tw-contain-size: ;--tw-contain-layout: ;--tw-contain-paint: ;--tw-contain-style: }@media (hover:hover){.table tr.hover:hover,.table tr.hover:nth-child(2n):hover{--tw-bg-opacity: 1;background-color:hsl(var(--b2) / var(--tw-bg-opacity))}.table-zebra tr.hover:hover,.table-zebra tr.hover:nth-child(2n):hover{--tw-bg-opacity: 1;background-color:hsl(var(--b3) / var(--tw-bg-opacity))}}.link{cursor:pointer;text-decoration-line:underline}@keyframes button-pop{0%{transform:scale(var(--btn-focus-scale, .98))}40%{transform:scale(1.02)}to{transform:scale(1)}}@keyframes checkmark{0%{background-position-y:5px}50%{background-position-y:-2px}to{background-position-y:0}}.link:focus{outline:2px solid transparent;outline-offset:2px}.link:focus-visible{outline:2px solid currentColor;outline-offset:2px}.mockup-phone .display{overflow:hidden;border-radius:40px;margin-top:-25px}@keyframes modal-pop{0%{opacity:0}}@keyframes progress-loading{50%{background-position-x:-115%}}@keyframes radiomark{0%{box-shadow:0 0 0 12px hsl(var(--b1)) inset,0 0 0 12px hsl(var(--b1)) inset}50%{box-shadow:0 0 0 3px hsl(var(--b1)) inset,0 0 0 3px hsl(var(--b1)) inset}to{box-shadow:0 0 0 4px hsl(var(--b1)) inset,0 0 0 4px hsl(var(--b1)) inset}}@keyframes rating-pop{0%{transform:translateY(-.125em)}40%{transform:translateY(-.125em)}to{transform:translateY(0)}}@keyframes toast-pop{0%{transform:scale(.9);opacity:0}to{transform:scale(1);opacity:1}}.mx-4{margin-left:1rem;margin-right:1rem}.mx-auto{margin-left:auto;margin-right:auto}.mb-12{margin-bottom:3rem}.inline{display:inline}.flex{display:flex}.contents{display:contents}.w-10{width:2.5rem}.w-fit{width:-moz-fit-content;width:fit-content}.max-w-4xl{max-width:56rem}.items-center{align-items:center}.justify-center{justify-content:center}.gap-2{gap:.5rem}.rounded-lg{border-radius:.5rem}.border{border-width:1px}.border-gray-200{--tw-border-opacity: 1;border-color:rgb(229 231 235 / var(--tw-border-opacity))}.bg-gray-900{--tw-bg-opacity: 1;background-color:rgb(17 24 39 / var(--tw-bg-opacity))}.p-4{padding:1rem}.py-3{padding-top:.75rem;padding-bottom:.75rem}.pt-10{padding-top:2.5rem}.text-center{text-align:center}.text-3xl{font-size:1.875rem;line-height:2.25rem}.text-xl{font-size:1.25rem;line-height:1.75rem}.font-bold{font-weight:700}.leading-snug{line-height:1.375}.\!text-white{--tw-text-opacity: 1 !important;color:rgb(255 255 255 / var(--tw-text-opacity))!important}.text-gray-300{--tw-text-opacity: 1;color:rgb(209 213 219 / var(--tw-text-opacity))}.text-gray-400{--tw-text-opacity: 1;color:rgb(156 163 175 / var(--tw-text-opacity))}.transition-all{transition-property:all;transition-timing-function:cubic-bezier(.4,0,.2,1);transition-duration:.15s}.hover\:-translate-y-0\.5:hover{--tw-translate-y: -.125rem;transform:translate(var(--tw-translate-x),var(--tw-translate-y)) rotate(var(--tw-rotate)) skew(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y))}.hover\:border-gray-300:hover{--tw-border-opacity: 1;border-color:rgb(209 213 219 / var(--tw-border-opacity))}.hover\:bg-gray-800:hover{--tw-bg-opacity: 1;background-color:rgb(31 41 55 / var(--tw-bg-opacity))}

_app/immutable/assets/2.Dl1cvM0g.css

@@ -1 +0,0 @@
-.link.svelte-1hc9mw2{--tw-text-opacity:1;color:rgb(156 163 175 / var(--tw-text-opacity))}.link.svelte-1hc9mw2:hover{--tw-text-opacity:1;color:rgb(209 213 219 / var(--tw-text-opacity))}h3.svelte-1hc9mw2{text-align:center;font-size:1.875rem;line-height:2.25rem;font-weight:700;--tw-text-opacity:1;color:rgb(255 255 255 / var(--tw-text-opacity))}p.svelte-1hc9mw2{padding-top:.75rem;padding-bottom:.75rem;text-align:center;font-size:1.25rem;line-height:1.75rem;line-height:1.375;--tw-text-opacity:1;color:rgb(229 231 235 / var(--tw-text-opacity))}

_app/immutable/assets/_layout.DViICDYp.css

@@ -1 +0,0 @@
-*,:before,:after{box-sizing:border-box;border-width:0;border-style:solid;border-color:#e5e7eb}:before,:after{--tw-content: ""}html,:host{line-height:1.5;-webkit-text-size-adjust:100%;-moz-tab-size:4;-o-tab-size:4;tab-size:4;font-family:ui-sans-serif,system-ui,sans-serif,"Apple Color Emoji","Segoe UI Emoji",Segoe UI Symbol,"Noto Color Emoji";font-feature-settings:normal;font-variation-settings:normal;-webkit-tap-highlight-color:transparent}body{margin:0;line-height:inherit}hr{height:0;color:inherit;border-top-width:1px}abbr:where([title]){-webkit-text-decoration:underline dotted;text-decoration:underline dotted}h1,h2,h3,h4,h5,h6{font-size:inherit;font-weight:inherit}a{color:inherit;text-decoration:inherit}b,strong{font-weight:bolder}code,kbd,samp,pre{font-family:ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,Liberation Mono,Courier New,monospace;font-feature-settings:normal;font-variation-settings:normal;font-size:1em}small{font-size:80%}sub,sup{font-size:75%;line-height:0;position:relative;vertical-align:baseline}sub{bottom:-.25em}sup{top:-.5em}table{text-indent:0;border-color:inherit;border-collapse:collapse}button,input,optgroup,select,textarea{font-family:inherit;font-feature-settings:inherit;font-variation-settings:inherit;font-size:100%;font-weight:inherit;line-height:inherit;letter-spacing:inherit;color:inherit;margin:0;padding:0}button,select{text-transform:none}button,input:where([type=button]),input:where([type=reset]),input:where([type=submit]){-webkit-appearance:button;background-color:transparent;background-image:none}:-moz-focusring{outline:auto}:-moz-ui-invalid{box-shadow:none}progress{vertical-align:baseline}::-webkit-inner-spin-button,::-webkit-outer-spin-button{height:auto}[type=search]{-webkit-appearance:textfield;outline-offset:-2px}::-webkit-search-decoration{-webkit-appearance:none}::-webkit-file-upload-button{-webkit-appearance:button;font:inherit}summary{display:list-item}blockquote,dl,dd,h1,h2,h3,h4,h5,h6,hr,figure,p,pre{margin:0}fieldset{margin:0;padding:0}legend{padding:0}ol,ul,menu{list-style:none;margin:0;padding:0}dialog{padding:0}textarea{resize:vertical}input::-moz-placeholder,textarea::-moz-placeholder{opacity:1;color:#9ca3af}input::placeholder,textarea::placeholder{opacity:1;color:#9ca3af}button,[role=button]{cursor:pointer}:disabled{cursor:default}img,svg,video,canvas,audio,iframe,embed,object{display:block;vertical-align:middle}img,video{max-width:100%;height:auto}[hidden]{display:none}:root,[data-theme]{background-color:hsl(var(--b1) / var(--tw-bg-opacity, 1));color:hsl(var(--bc) / var(--tw-text-opacity, 1))}html{-webkit-tap-highlight-color:transparent}:root{color-scheme:light;--pf: 259 94% 44%;--sf: 314 100% 40%;--af: 174 75% 39%;--nf: 214 20% 14%;--in: 198 93% 60%;--su: 158 64% 52%;--wa: 43 96% 56%;--er: 0 91% 71%;--inc: 198 100% 12%;--suc: 158 100% 10%;--wac: 43 100% 11%;--erc: 0 100% 14%;--rounded-box: 1rem;--rounded-btn: .5rem;--rounded-badge: 1.9rem;--animation-btn: .25s;--animation-input: .2s;--btn-text-case: uppercase;--btn-focus-scale: .95;--border-btn: 1px;--tab-border: 1px;--tab-radius: .5rem;--p: 259 94% 51%;--pc: 259 96% 91%;--s: 314 100% 47%;--sc: 314 100% 91%;--a: 174 75% 46%;--ac: 174 75% 11%;--n: 214 20% 21%;--nc: 212 19% 87%;--b1: 0 0% 100%;--b2: 0 0% 95%;--b3: 180 2% 90%;--bc: 215 28% 17%}@media (prefers-color-scheme: dark){:root{color-scheme:dark;--pf: 262 80% 43%;--sf: 316 70% 43%;--af: 175 70% 34%;--in: 198 93% 60%;--su: 158 64% 52%;--wa: 43 96% 56%;--er: 0 91% 71%;--inc: 198 100% 12%;--suc: 158 100% 10%;--wac: 43 100% 11%;--erc: 0 100% 14%;--rounded-box: 1rem;--rounded-btn: .5rem;--rounded-badge: 1.9rem;--animation-btn: .25s;--animation-input: .2s;--btn-text-case: uppercase;--btn-focus-scale: .95;--border-btn: 1px;--tab-border: 1px;--tab-radius: .5rem;--p: 262 80% 50%;--pc: 0 0% 100%;--s: 316 70% 50%;--sc: 0 0% 100%;--a: 175 70% 41%;--ac: 0 0% 100%;--n: 213 18% 20%;--nf: 212 17% 17%;--nc: 220 13% 69%;--b1: 212 18% 14%;--b2: 213 18% 12%;--b3: 213 18% 10%;--bc: 220 13% 69%}}[data-theme=light]{color-scheme:light;--pf: 259 94% 44%;--sf: 314 100% 40%;--af: 174 75% 39%;--nf: 214 20% 14%;--in: 198 93% 60%;--su: 158 64% 52%;--wa: 43 96% 56%;--er: 0 91% 71%;--inc: 198 100% 12%;--suc: 158 100% 10%;--wac: 43 100% 11%;--erc: 0 100% 14%;--rounded-box: 1rem;--rounded-btn: .5rem;--rounded-badge: 1.9rem;--animation-btn: .25s;--animation-input: .2s;--btn-text-case: uppercase;--btn-focus-scale: .95;--border-btn: 1px;--tab-border: 1px;--tab-radius: .5rem;--p: 259 94% 51%;--pc: 259 96% 91%;--s: 314 100% 47%;--sc: 314 100% 91%;--a: 174 75% 46%;--ac: 174 75% 11%;--n: 214 20% 21%;--nc: 212 19% 87%;--b1: 0 0% 100%;--b2: 0 0% 95%;--b3: 180 2% 90%;--bc: 215 28% 17%}[data-theme=dark]{color-scheme:dark;--pf: 262 80% 43%;--sf: 316 70% 43%;--af: 175 70% 34%;--in: 198 93% 60%;--su: 158 64% 52%;--wa: 43 96% 56%;--er: 0 91% 71%;--inc: 198 100% 12%;--suc: 158 100% 10%;--wac: 43 100% 11%;--erc: 0 100% 14%;--rounded-box: 1rem;--rounded-btn: .5rem;--rounded-badge: 1.9rem;--animation-btn: .25s;--animation-input: .2s;--btn-text-case: uppercase;--btn-focus-scale: .95;--border-btn: 1px;--tab-border: 1px;--tab-radius: .5rem;--p: 262 80% 50%;--pc: 0 0% 100%;--s: 316 70% 50%;--sc: 0 0% 100%;--a: 175 70% 41%;--ac: 0 0% 100%;--n: 213 18% 20%;--nf: 212 17% 17%;--nc: 220 13% 69%;--b1: 212 18% 14%;--b2: 213 18% 12%;--b3: 213 18% 10%;--bc: 220 13% 69%}*,:before,:after{--tw-border-spacing-x: 0;--tw-border-spacing-y: 0;--tw-translate-x: 0;--tw-translate-y: 0;--tw-rotate: 0;--tw-skew-x: 0;--tw-skew-y: 0;--tw-scale-x: 1;--tw-scale-y: 1;--tw-pan-x: ;--tw-pan-y: ;--tw-pinch-zoom: ;--tw-scroll-snap-strictness: proximity;--tw-gradient-from-position: ;--tw-gradient-via-position: ;--tw-gradient-to-position: ;--tw-ordinal: ;--tw-slashed-zero: ;--tw-numeric-figure: ;--tw-numeric-spacing: ;--tw-numeric-fraction: ;--tw-ring-inset: ;--tw-ring-offset-width: 0px;--tw-ring-offset-color: #fff;--tw-ring-color: rgb(59 130 246 / .5);--tw-ring-offset-shadow: 0 0 #0000;--tw-ring-shadow: 0 0 #0000;--tw-shadow: 0 0 #0000;--tw-shadow-colored: 0 0 #0000;--tw-blur: ;--tw-brightness: ;--tw-contrast: ;--tw-grayscale: ;--tw-hue-rotate: ;--tw-invert: ;--tw-saturate: ;--tw-sepia: ;--tw-drop-shadow: ;--tw-backdrop-blur: ;--tw-backdrop-brightness: ;--tw-backdrop-contrast: ;--tw-backdrop-grayscale: ;--tw-backdrop-hue-rotate: ;--tw-backdrop-invert: ;--tw-backdrop-opacity: ;--tw-backdrop-saturate: ;--tw-backdrop-sepia: ;--tw-contain-size: ;--tw-contain-layout: ;--tw-contain-paint: ;--tw-contain-style: }::backdrop{--tw-border-spacing-x: 0;--tw-border-spacing-y: 0;--tw-translate-x: 0;--tw-translate-y: 0;--tw-rotate: 0;--tw-skew-x: 0;--tw-skew-y: 0;--tw-scale-x: 1;--tw-scale-y: 1;--tw-pan-x: ;--tw-pan-y: ;--tw-pinch-zoom: ;--tw-scroll-snap-strictness: proximity;--tw-gradient-from-position: ;--tw-gradient-via-position: ;--tw-gradient-to-position: ;--tw-ordinal: ;--tw-slashed-zero: ;--tw-numeric-figure: ;--tw-numeric-spacing: ;--tw-numeric-fraction: ;--tw-ring-inset: ;--tw-ring-offset-width: 0px;--tw-ring-offset-color: #fff;--tw-ring-color: rgb(59 130 246 / .5);--tw-ring-offset-shadow: 0 0 #0000;--tw-ring-shadow: 0 0 #0000;--tw-shadow: 0 0 #0000;--tw-shadow-colored: 0 0 #0000;--tw-blur: ;--tw-brightness: ;--tw-contrast: ;--tw-grayscale: ;--tw-hue-rotate: ;--tw-invert: ;--tw-saturate: ;--tw-sepia: ;--tw-drop-shadow: ;--tw-backdrop-blur: ;--tw-backdrop-brightness: ;--tw-backdrop-contrast: ;--tw-backdrop-grayscale: ;--tw-backdrop-hue-rotate: ;--tw-backdrop-invert: ;--tw-backdrop-opacity: ;--tw-backdrop-saturate: ;--tw-backdrop-sepia: ;--tw-contain-size: ;--tw-contain-layout: ;--tw-contain-paint: ;--tw-contain-style: }@media (hover:hover){.table tr.hover:hover,.table tr.hover:nth-child(2n):hover{--tw-bg-opacity: 1;background-color:hsl(var(--b2) / var(--tw-bg-opacity))}.table-zebra tr.hover:hover,.table-zebra tr.hover:nth-child(2n):hover{--tw-bg-opacity: 1;background-color:hsl(var(--b3) / var(--tw-bg-opacity))}}.link{cursor:pointer;text-decoration-line:underline}@keyframes button-pop{0%{transform:scale(var(--btn-focus-scale, .98))}40%{transform:scale(1.02)}to{transform:scale(1)}}@keyframes checkmark{0%{background-position-y:5px}50%{background-position-y:-2px}to{background-position-y:0}}.link:focus{outline:2px solid transparent;outline-offset:2px}.link:focus-visible{outline:2px solid currentColor;outline-offset:2px}.mockup-phone .display{overflow:hidden;border-radius:40px;margin-top:-25px}@keyframes modal-pop{0%{opacity:0}}@keyframes progress-loading{50%{background-position-x:-115%}}@keyframes radiomark{0%{box-shadow:0 0 0 12px hsl(var(--b1)) inset,0 0 0 12px hsl(var(--b1)) inset}50%{box-shadow:0 0 0 3px hsl(var(--b1)) inset,0 0 0 3px hsl(var(--b1)) inset}to{box-shadow:0 0 0 4px hsl(var(--b1)) inset,0 0 0 4px hsl(var(--b1)) inset}}@keyframes rating-pop{0%{transform:translateY(-.125em)}40%{transform:translateY(-.125em)}to{transform:translateY(0)}}@keyframes toast-pop{0%{transform:scale(.9);opacity:0}to{transform:scale(1);opacity:1}}.mx-4{margin-left:1rem;margin-right:1rem}.mx-auto{margin-left:auto;margin-right:auto}.mb-12{margin-bottom:3rem}.inline{display:inline}.flex{display:flex}.contents{display:contents}.w-10{width:2.5rem}.w-fit{width:-moz-fit-content;width:fit-content}.max-w-4xl{max-width:56rem}.items-center{align-items:center}.justify-center{justify-content:center}.gap-2{gap:.5rem}.rounded-lg{border-radius:.5rem}.border{border-width:1px}.border-gray-200{--tw-border-opacity: 1;border-color:rgb(229 231 235 / var(--tw-border-opacity))}.bg-gray-900{--tw-bg-opacity: 1;background-color:rgb(17 24 39 / var(--tw-bg-opacity))}.p-4{padding:1rem}.py-3{padding-top:.75rem;padding-bottom:.75rem}.pt-10{padding-top:2.5rem}.text-center{text-align:center}.text-3xl{font-size:1.875rem;line-height:2.25rem}.text-xl{font-size:1.25rem;line-height:1.75rem}.font-bold{font-weight:700}.leading-snug{line-height:1.375}.\!text-white{--tw-text-opacity: 1 !important;color:rgb(255 255 255 / var(--tw-text-opacity))!important}.text-gray-300{--tw-text-opacity: 1;color:rgb(209 213 219 / var(--tw-text-opacity))}.text-gray-400{--tw-text-opacity: 1;color:rgb(156 163 175 / var(--tw-text-opacity))}.transition-all{transition-property:all;transition-timing-function:cubic-bezier(.4,0,.2,1);transition-duration:.15s}.hover\:-translate-y-0\.5:hover{--tw-translate-y: -.125rem;transform:translate(var(--tw-translate-x),var(--tw-translate-y)) rotate(var(--tw-rotate)) skew(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y))}.hover\:border-gray-300:hover{--tw-border-opacity: 1;border-color:rgb(209 213 219 / var(--tw-border-opacity))}.hover\:bg-gray-800:hover{--tw-bg-opacity: 1;background-color:rgb(31 41 55 / var(--tw-bg-opacity))}

_app/immutable/assets/_page.Dl1cvM0g.css

@@ -1 +0,0 @@
-.link.svelte-1hc9mw2{--tw-text-opacity:1;color:rgb(156 163 175 / var(--tw-text-opacity))}.link.svelte-1hc9mw2:hover{--tw-text-opacity:1;color:rgb(209 213 219 / var(--tw-text-opacity))}h3.svelte-1hc9mw2{text-align:center;font-size:1.875rem;line-height:2.25rem;font-weight:700;--tw-text-opacity:1;color:rgb(255 255 255 / var(--tw-text-opacity))}p.svelte-1hc9mw2{padding-top:.75rem;padding-bottom:.75rem;text-align:center;font-size:1.25rem;line-height:1.75rem;line-height:1.375;--tw-text-opacity:1;color:rgb(229 231 235 / var(--tw-text-opacity))}

_app/immutable/chunks/entry.CsquK5o6.js

@@ -1,3 +0,0 @@
-import{n as lt,s as le,t as fe}from"./scheduler.CtbWrGNo.js";new URL("sveltekit-internal://");function ue(t,n){return t==="/"||n==="ignore"?t:n==="never"?t.endsWith("/")?t.slice(0,-1):t:n==="always"&&!t.endsWith("/")?t+"/":t}function de(t){return t.split("%25").map(decodeURI).join("%25")}function he(t){for(const n in t)t[n]=decodeURIComponent(t[n]);return t}function ft({href:t}){return t.split("#")[0]}const pe=["href","pathname","search","toString","toJSON"];function ge(t,n,e){const r=new URL(t);Object.defineProperty(r,"searchParams",{value:new Proxy(r.searchParams,{get(a,o){if(o==="get"||o==="getAll"||o==="has")return s=>(e(s),a[o](s));n();const i=Reflect.get(a,o);return typeof i=="function"?i.bind(a):i}}),enumerable:!0,configurable:!0});for(const a of pe)Object.defineProperty(r,a,{get(){return n(),t[a]},enumerable:!0,configurable:!0});return r}const me="/__data.json",_e=".html__data.json";function ye(t){return t.endsWith(".html")?t.replace(/\.html$/,_e):t.replace(/\/$/,"")+me}function we(...t){let n=5381;for(const e of t)if(typeof e=="string"){let r=e.length;for(;r;)n=n*33^e.charCodeAt(--r)}else if(ArrayBuffer.isView(e)){const r=new Uint8Array(e.buffer,e.byteOffset,e.byteLength);let a=r.length;for(;a;)n=n*33^r[--a]}else throw new TypeError("value must be a string or TypedArray");return(n>>>0).toString(36)}function ve(t){const n=atob(t),e=new Uint8Array(n.length);for(let r=0;r<n.length;r++)e[r]=n.charCodeAt(r);return e.buffer}const Vt=window.fetch;window.fetch=(t,n)=>((t instanceof Request?t.method:(n==null?void 0:n.method)||"GET")!=="GET"&&G.delete(mt(t)),Vt(t,n));const G=new Map;function be(t,n){const e=mt(t,n),r=document.querySelector(e);if(r!=null&&r.textContent){let{body:a,...o}=JSON.parse(r.textContent);const i=r.getAttribute("data-ttl");return i&&G.set(e,{body:a,init:o,ttl:1e3*Number(i)}),r.getAttribute("data-b64")!==null&&(a=ve(a)),Promise.resolve(new Response(a,o))}return window.fetch(t,n)}function ke(t,n,e){if(G.size>0){const r=mt(t,e),a=G.get(r);if(a){if(performance.now()<a.ttl&&["default","force-cache","only-if-cached",void 0].includes(e==null?void 0:e.cache))return new Response(a.body,a.init);G.delete(r)}}return window.fetch(n,e)}function mt(t,n){let r=`script[data-sveltekit-fetched][data-url=${JSON.stringify(t instanceof Request?t.url:t)}]`;if(n!=null&&n.headers||n!=null&&n.body){const a=[];n.headers&&a.push([...new Headers(n.headers)].join(",")),n.body&&(typeof n.body=="string"||ArrayBuffer.isView(n.body))&&a.push(n.body),r+=`[data-hash="${we(...a)}"]`}return r}const Ee=/^(\[)?(\.\.\.)?(\w+)(?:=(\w+))?(\])?$/;function Se(t){const n=[];return{pattern:t==="/"?/^\/$/:new RegExp(`^${Re(t).map(r=>{const a=/^\[\.\.\.(\w+)(?:=(\w+))?\]$/.exec(r);if(a)return n.push({name:a[1],matcher:a[2],optional:!1,rest:!0,chained:!0}),"(?:/(.*))?";const o=/^\[\[(\w+)(?:=(\w+))?\]\]$/.exec(r);if(o)return n.push({name:o[1],matcher:o[2],optional:!0,rest:!1,chained:!0}),"(?:/([^/]+))?";if(!r)return;const i=r.split(/\[(.+?)\](?!\])/);return"/"+i.map((c,l)=>{if(l%2){if(c.startsWith("x+"))return ut(String.fromCharCode(parseInt(c.slice(2),16)));if(c.startsWith("u+"))return ut(String.fromCharCode(...c.slice(2).split("-").map(f=>parseInt(f,16))));const u=Ee.exec(c),[,h,g,d,_]=u;return n.push({name:d,matcher:_,optional:!!h,rest:!!g,chained:g?l===1&&i[0]==="":!1}),g?"(.*?)":h?"([^/]*)?":"([^/]+?)"}return ut(c)}).join("")}).join("")}/?$`),params:n}}function Ae(t){return!/^\([^)]+\)$/.test(t)}function Re(t){return t.slice(1).split("/").filter(Ae)}function Ie(t,n,e){const r={},a=t.slice(1),o=a.filter(s=>s!==void 0);let i=0;for(let s=0;s<n.length;s+=1){const c=n[s];let l=a[s-i];if(c.chained&&c.rest&&i&&(l=a.slice(s-i,s+1).filter(u=>u).join("/"),i=0),l===void 0){c.rest&&(r[c.name]="");continue}if(!c.matcher||e[c.matcher](l)){r[c.name]=l;const u=n[s+1],h=a[s+1];u&&!u.rest&&u.optional&&h&&c.chained&&(i=0),!u&&!h&&Object.keys(r).length===o.length&&(i=0);continue}if(c.optional&&c.chained){i++;continue}return}if(!i)return r}function ut(t){return t.normalize().replace(/[[\]]/g,"\\$&").replace(/%/g,"%25").replace(/\//g,"%2[Ff]").replace(/\?/g,"%3[Ff]").replace(/#/g,"%23").replace(/[.*+?^${}()|\\]/g,"\\$&")}function Le({nodes:t,server_loads:n,dictionary:e,matchers:r}){const a=new Set(n);return Object.entries(e).map(([s,[c,l,u]])=>{const{pattern:h,params:g}=Se(s),d={id:s,exec:_=>{const f=h.exec(_);if(f)return Ie(f,g,r)},errors:[1,...u||[]].map(_=>t[_]),layouts:[0,...l||[]].map(i),leaf:o(c)};return d.errors.length=d.layouts.length=Math.max(d.errors.length,d.layouts.length),d});function o(s){const c=s<0;return c&&(s=~s),[c,t[s]]}function i(s){return s===void 0?s:[a.has(s),t[s]]}}function Ft(t,n=JSON.parse){try{return n(sessionStorage[t])}catch{}}function Pt(t,n,e=JSON.stringify){const r=e(n);try{sessionStorage[t]=r}catch{}}const O=[];function _t(t,n=lt){let e;const r=new Set;function a(s){if(le(t,s)&&(t=s,e)){const c=!O.length;for(const l of r)l[1](),O.push(l,t);if(c){for(let l=0;l<O.length;l+=2)O[l][0](O[l+1]);O.length=0}}}function o(s){a(s(t))}function i(s,c=lt){const l=[s,c];return r.add(l),r.size===1&&(e=n(a,o)||lt),s(t),()=>{r.delete(l),r.size===0&&e&&(e(),e=null)}}return{set:a,update:o,subscribe:i}}var Dt;const P=((Dt=globalThis.__sveltekit_1klgtbu)==null?void 0:Dt.base)??"";var Ct;const Pe=((Ct=globalThis.__sveltekit_1klgtbu)==null?void 0:Ct.assets)??P,Te="1722243467595",qt="sveltekit:snapshot",Gt="sveltekit:scroll",Mt="sveltekit:states",Ue="sveltekit:pageurl",D="sveltekit:history",H="sveltekit:navigation",J={tap:1,hover:2,viewport:3,eager:4,off:-1,false:-1},z=location.origin;function Ht(t){if(t instanceof URL)return t;let n=document.baseURI;if(!n){const e=document.getElementsByTagName("base");n=e.length?e[0].href:document.URL}return new URL(t,n)}function yt(){return{x:pageXOffset,y:pageYOffset}}function j(t,n){return t.getAttribute(`data-sveltekit-${n}`)}const Tt={...J,"":J.hover};function Bt(t){let n=t.assignedSlot??t.parentNode;return(n==null?void 0:n.nodeType)===11&&(n=n.host),n}function Kt(t,n){for(;t&&t!==n;){if(t.nodeName.toUpperCase()==="A"&&t.hasAttribute("href"))return t;t=Bt(t)}}function ht(t,n){let e;try{e=new URL(t instanceof SVGAElement?t.href.baseVal:t.href,document.baseURI)}catch{}const r=t instanceof SVGAElement?t.target.baseVal:t.target,a=!e||!!r||rt(e,n)||(t.getAttribute("rel")||"").split(/\s+/).includes("external"),o=(e==null?void 0:e.origin)===z&&t.hasAttribute("download");return{url:e,external:a,target:r,download:o}}function W(t){let n=null,e=null,r=null,a=null,o=null,i=null,s=t;for(;s&&s!==document.documentElement;)r===null&&(r=j(s,"preload-code")),a===null&&(a=j(s,"preload-data")),n===null&&(n=j(s,"keepfocus")),e===null&&(e=j(s,"noscroll")),o===null&&(o=j(s,"reload")),i===null&&(i=j(s,"replacestate")),s=Bt(s);function c(l){switch(l){case"":case"true":return!0;case"off":case"false":return!1;default:return}}return{preload_code:Tt[r??"off"],preload_data:Tt[a??"off"],keepfocus:c(n),noscroll:c(e),reload:c(o),replace_state:c(i)}}function Ut(t){const n=_t(t);let e=!0;function r(){e=!0,n.update(i=>i)}function a(i){e=!1,n.set(i)}function o(i){let s;return n.subscribe(c=>{(s===void 0||e&&c!==s)&&i(s=c)})}return{notify:r,set:a,subscribe:o}}function xe(){const{set:t,subscribe:n}=_t(!1);let e;async function r(){clearTimeout(e);try{const a=await fetch(`${Pe}/_app/version.json`,{headers:{pragma:"no-cache","cache-control":"no-cache"}});if(!a.ok)return!1;const i=(await a.json()).version!==Te;return i&&(t(!0),clearTimeout(e)),i}catch{return!1}}return{subscribe:n,check:r}}function rt(t,n){return t.origin!==z||!t.pathname.startsWith(n)}const Ne=-1,Oe=-2,je=-3,$e=-4,De=-5,Ce=-6;function Ve(t,n){if(typeof t=="number")return a(t,!0);if(!Array.isArray(t)||t.length===0)throw new Error("Invalid input");const e=t,r=Array(e.length);function a(o,i=!1){if(o===Ne)return;if(o===je)return NaN;if(o===$e)return 1/0;if(o===De)return-1/0;if(o===Ce)return-0;if(i)throw new Error("Invalid input");if(o in r)return r[o];const s=e[o];if(!s||typeof s!="object")r[o]=s;else if(Array.isArray(s))if(typeof s[0]=="string"){const c=s[0],l=n==null?void 0:n[c];if(l)return r[o]=l(a(s[1]));switch(c){case"Date":r[o]=new Date(s[1]);break;case"Set":const u=new Set;r[o]=u;for(let d=1;d<s.length;d+=1)u.add(a(s[d]));break;case"Map":const h=new Map;r[o]=h;for(let d=1;d<s.length;d+=2)h.set(a(s[d]),a(s[d+1]));break;case"RegExp":r[o]=new RegExp(s[1],s[2]);break;case"Object":r[o]=Object(s[1]);break;case"BigInt":r[o]=BigInt(s[1]);break;case"null":const g=Object.create(null);r[o]=g;for(let d=1;d<s.length;d+=2)g[s[d]]=a(s[d+1]);break;default:throw new Error(`Unknown type ${c}`)}}else{const c=new Array(s.length);r[o]=c;for(let l=0;l<s.length;l+=1){const u=s[l];u!==Oe&&(c[l]=a(u))}}else{const c={};r[o]=c;for(const l in s){const u=s[l];c[l]=a(u)}}return r[o]}return a(0)}const zt=new Set(["load","prerender","csr","ssr","trailingSlash","config"]);[...zt];const Fe=new Set([...zt]);[...Fe];function qe(t){return t.filter(n=>n!=null)}class at{constructor(n,e){this.status=n,typeof e=="string"?this.body={message:e}:e?this.body=e:this.body={message:`Error: ${n}`}}toString(){return JSON.stringify(this.body)}}class Yt{constructor(n,e){this.status=n,this.location=e}}class wt extends Error{constructor(n,e,r){super(r),this.status=n,this.text=e}}const Ge="x-sveltekit-invalidated",Me="x-sveltekit-trailing-slash";function X(t){return t instanceof at||t instanceof wt?t.status:500}function He(t){return t instanceof wt?t.text:"Internal Error"}const N=Ft(Gt)??{},B=Ft(qt)??{},U={url:Ut({}),page:Ut({}),navigating:_t(null),updated:xe()};function vt(t){N[t]=yt()}function Be(t,n){let e=t+1;for(;N[e];)delete N[e],e+=1;for(e=n+1;B[e];)delete B[e],e+=1}function V(t){return location.href=t.href,new Promise(()=>{})}function xt(){}let ot,pt,Z,T,gt,F;const Jt=[],Q=[];let R=null;const Wt=[],Ke=[];let $=[],y={branch:[],error:null,url:null},bt=!1,tt=!1,Nt=!0,K=!1,q=!1,Xt=!1,kt=!1,Et,S,L,I,et;const M=new Set;async function rn(t,n,e){var a,o;document.URL!==location.href&&(location.href=location.href),F=t,ot=Le(t),T=document.documentElement,gt=n,pt=t.nodes[0],Z=t.nodes[1],pt(),Z(),S=(a=history.state)==null?void 0:a[D],L=(o=history.state)==null?void 0:o[H],S||(S=L=Date.now(),history.replaceState({...history.state,[D]:S,[H]:L},""));const r=N[S];r&&(history.scrollRestoration="manual",scrollTo(r.x,r.y)),e?await tn(gt,e):Ze(location.href,{replaceState:!0}),Qe()}function ze(){Jt.length=0,kt=!1}function Zt(t){Q.some(n=>n==null?void 0:n.snapshot)&&(B[t]=Q.map(n=>{var e;return(e=n==null?void 0:n.snapshot)==null?void 0:e.capture()}))}function Qt(t){var n;(n=B[t])==null||n.forEach((e,r)=>{var a,o;(o=(a=Q[r])==null?void 0:a.snapshot)==null||o.restore(e)})}function Ot(){vt(S),Pt(Gt,N),Zt(L),Pt(qt,B)}async function te(t,n,e,r){return Y({type:"goto",url:Ht(t),keepfocus:n.keepFocus,noscroll:n.noScroll,replace_state:n.replaceState,state:n.state,redirect_count:e,nav_token:r,accept:()=>{n.invalidateAll&&(kt=!0)}})}async function Ye(t){if(t.id!==(R==null?void 0:R.id)){const n={};M.add(n),R={id:t.id,token:n,promise:ne({...t,preload:n}).then(e=>(M.delete(n),e.type==="loaded"&&e.state.error&&(R=null),e))}}return R.promise}async function dt(t){const n=ot.find(e=>e.exec(re(t)));n&&await Promise.all([...n.layouts,n.leaf].map(e=>e==null?void 0:e[1]()))}function ee(t,n,e){var o;y=t.state;const r=document.querySelector("style[data-sveltekit]");r&&r.remove(),I=t.props.page,Et=new F.root({target:n,props:{...t.props,stores:U,components:Q},hydrate:e}),Qt(L);const a={from:null,to:{params:y.params,route:{id:((o=y.route)==null?void 0:o.id)??null},url:new URL(location.href)},willUnload:!1,type:"enter",complete:Promise.resolve()};$.forEach(i=>i(a)),tt=!0}function nt({url:t,params:n,branch:e,status:r,error:a,route:o,form:i}){let s="never";if(P&&(t.pathname===P||t.pathname===P+"/"))s="always";else for(const d of e)(d==null?void 0:d.slash)!==void 0&&(s=d.slash);t.pathname=ue(t.pathname,s),t.search=t.search;const c={type:"loaded",state:{url:t,params:n,branch:e,error:a,route:o},props:{constructors:qe(e).map(d=>d.node.component),page:I}};i!==void 0&&(c.props.form=i);let l={},u=!I,h=0;for(let d=0;d<Math.max(e.length,y.branch.length);d+=1){const _=e[d],f=y.branch[d];(_==null?void 0:_.data)!==(f==null?void 0:f.data)&&(u=!0),_&&(l={...l,..._.data},u&&(c.props[`data_${h}`]=l),h+=1)}return(!y.url||t.href!==y.url.href||y.error!==a||i!==void 0&&i!==I.form||u)&&(c.props.page={error:a,params:n,route:{id:(o==null?void 0:o.id)??null},state:{},status:r,url:new URL(t),form:i??null,data:u?l:I.data}),c}async function St({loader:t,parent:n,url:e,params:r,route:a,server_data_node:o}){var u,h,g;let i=null,s=!0;const c={dependencies:new Set,params:new Set,parent:!1,route:!1,url:!1,search_params:new Set},l=await t();if((u=l.universal)!=null&&u.load){let d=function(...f){for(const m of f){const{href:b}=new URL(m,e);c.dependencies.add(b)}};const _={route:new Proxy(a,{get:(f,m)=>(s&&(c.route=!0),f[m])}),params:new Proxy(r,{get:(f,m)=>(s&&c.params.add(m),f[m])}),data:(o==null?void 0:o.data)??null,url:ge(e,()=>{s&&(c.url=!0)},f=>{s&&c.search_params.add(f)}),async fetch(f,m){let b;f instanceof Request?(b=f.url,m={body:f.method==="GET"||f.method==="HEAD"?void 0:await f.blob(),cache:f.cache,credentials:f.credentials,headers:f.headers,integrity:f.integrity,keepalive:f.keepalive,method:f.method,mode:f.mode,redirect:f.redirect,referrer:f.referrer,referrerPolicy:f.referrerPolicy,signal:f.signal,...m}):b=f;const A=new URL(b,e);return s&&d(A.href),A.origin===e.origin&&(b=A.href.slice(e.origin.length)),tt?ke(b,A.href,m):be(b,m)},setHeaders:()=>{},depends:d,parent(){return s&&(c.parent=!0),n()},untrack(f){s=!1;try{return f()}finally{s=!0}}};i=await l.universal.load.call(null,_)??null}return{node:l,loader:t,server:o,universal:(h=l.universal)!=null&&h.load?{type:"data",data:i,uses:c}:null,data:i??(o==null?void 0:o.data)??null,slash:((g=l.universal)==null?void 0:g.trailingSlash)??(o==null?void 0:o.slash)}}function jt(t,n,e,r,a,o){if(kt)return!0;if(!a)return!1;if(a.parent&&t||a.route&&n||a.url&&e)return!0;for(const i of a.search_params)if(r.has(i))return!0;for(const i of a.params)if(o[i]!==y.params[i])return!0;for(const i of a.dependencies)if(Jt.some(s=>s(new URL(i))))return!0;return!1}function At(t,n){return(t==null?void 0:t.type)==="data"?t:(t==null?void 0:t.type)==="skip"?n??null:null}function Je(t,n){if(!t)return new Set(n.searchParams.keys());const e=new Set([...t.searchParams.keys(),...n.searchParams.keys()]);for(const r of e){const a=t.searchParams.getAll(r),o=n.searchParams.getAll(r);a.every(i=>o.includes(i))&&o.every(i=>a.includes(i))&&e.delete(r)}return e}function $t({error:t,url:n,route:e,params:r}){return{type:"loaded",state:{error:t,url:n,route:e,params:r,branch:[]},props:{page:I,constructors:[]}}}async function ne({id:t,invalidating:n,url:e,params:r,route:a,preload:o}){if((R==null?void 0:R.id)===t)return M.delete(R.token),R.promise;const{errors:i,layouts:s,leaf:c}=a,l=[...s,c];i.forEach(p=>p==null?void 0:p().catch(()=>{})),l.forEach(p=>p==null?void 0:p[1]().catch(()=>{}));let u=null;const h=y.url?t!==y.url.pathname+y.url.search:!1,g=y.route?a.id!==y.route.id:!1,d=Je(y.url,e);let _=!1;const f=l.map((p,v)=>{var x;const k=y.branch[v],E=!!(p!=null&&p[0])&&((k==null?void 0:k.loader)!==p[1]||jt(_,g,h,d,(x=k.server)==null?void 0:x.uses,r));return E&&(_=!0),E});if(f.some(Boolean)){try{u=await se(e,f)}catch(p){const v=await C(p,{url:e,params:r,route:{id:t}});return M.has(o)?$t({error:v,url:e,params:r,route:a}):st({status:X(p),error:v,url:e,route:a})}if(u.type==="redirect")return u}const m=u==null?void 0:u.nodes;let b=!1;const A=l.map(async(p,v)=>{var it;if(!p)return;const k=y.branch[v],E=m==null?void 0:m[v];if((!E||E.type==="skip")&&p[1]===(k==null?void 0:k.loader)&&!jt(b,g,h,d,(it=k.universal)==null?void 0:it.uses,r))return k;if(b=!0,(E==null?void 0:E.type)==="error")throw E;return St({loader:p[1],url:e,params:r,route:a,parent:async()=>{var Lt;const It={};for(let ct=0;ct<v;ct+=1)Object.assign(It,(Lt=await A[ct])==null?void 0:Lt.data);return It},server_data_node:At(E===void 0&&p[0]?{type:"skip"}:E??null,p[0]?k==null?void 0:k.server:void 0)})});for(const p of A)p.catch(()=>{});const w=[];for(let p=0;p<l.length;p+=1)if(l[p])try{w.push(await A[p])}catch(v){if(v instanceof Yt)return{type:"redirect",location:v.location};if(M.has(o))return $t({error:await C(v,{params:r,url:e,route:{id:a.id}}),url:e,params:r,route:a});let k=X(v),E;if(m!=null&&m.includes(v))k=v.status??k,E=v.error;else if(v instanceof at)E=v.body;else{if(await U.updated.check())return await V(e);E=await C(v,{params:r,url:e,route:{id:a.id}})}const x=await We(p,w,i);return x?nt({url:e,params:r,branch:w.slice(0,x.idx).concat(x.node),status:k,error:E,route:a}):await oe(e,{id:a.id},E,k)}else w.push(void 0);return nt({url:e,params:r,branch:w,status:200,error:null,route:a,form:n?void 0:null})}async function We(t,n,e){for(;t--;)if(e[t]){let r=t;for(;!n[r];)r-=1;try{return{idx:r+1,node:{node:await e[t](),loader:e[t],data:{},server:null,universal:null}}}catch{continue}}}async function st({status:t,error:n,url:e,route:r}){const a={};let o=null;if(F.server_loads[0]===0)try{const l=await se(e,[!0]);if(l.type!=="data"||l.nodes[0]&&l.nodes[0].type!=="data")throw 0;o=l.nodes[0]??null}catch{(e.origin!==z||e.pathname!==location.pathname||bt)&&await V(e)}const s=await St({loader:pt,url:e,params:a,route:r,parent:()=>Promise.resolve({}),server_data_node:At(o)}),c={node:await Z(),loader:Z,universal:null,server:null,data:null};return nt({url:e,params:a,branch:[s,c],status:t,error:n,route:null})}function Rt(t,n){if(!t||rt(t,P))return;let e;try{e=F.hooks.reroute({url:new URL(t)})??t.pathname}catch{return}const r=re(e);for(const a of ot){const o=a.exec(r);if(o)return{id:t.pathname+t.search,invalidating:n,route:a,params:he(o),url:t}}}function re(t){return de(t.slice(P.length)||"/")}function ae({url:t,type:n,intent:e,delta:r}){let a=!1;const o=ce(y,e,t,n);r!==void 0&&(o.navigation.delta=r);const i={...o.navigation,cancel:()=>{a=!0,o.reject(new Error("navigation cancelled"))}};return K||Wt.forEach(s=>s(i)),a?null:o}async function Y({type:t,url:n,popped:e,keepfocus:r,noscroll:a,replace_state:o,state:i={},redirect_count:s=0,nav_token:c={},accept:l=xt,block:u=xt}){const h=Rt(n,!1),g=ae({url:n,type:t,delta:e==null?void 0:e.delta,intent:h});if(!g){u();return}const d=S,_=L;l(),K=!0,tt&&U.navigating.set(g.navigation),et=c;let f=h&&await ne(h);if(!f){if(rt(n,P))return await V(n);f=await oe(n,{id:null},await C(new wt(404,"Not Found",`Not found: ${n.pathname}`),{url:n,params:{},route:{id:null}}),404)}if(n=(h==null?void 0:h.url)||n,et!==c)return g.reject(new Error("navigation aborted")),!1;if(f.type==="redirect")if(s>=20)f=await st({status:500,error:await C(new Error("Redirect loop"),{url:n,params:{},route:{id:null}}),url:n,route:{id:null}});else return te(new URL(f.location,n).href,{},s+1,c),!1;else f.props.page.status>=400&&await U.updated.check()&&await V(n);if(ze(),vt(d),Zt(_),f.props.page.url.pathname!==n.pathname&&(n.pathname=f.props.page.url.pathname),i=e?e.state:i,!e){const w=o?0:1,p={[D]:S+=w,[H]:L+=w,[Mt]:i};(o?history.replaceState:history.pushState).call(history,p,"",n),o||Be(S,L)}if(R=null,f.props.page.state=i,tt){y=f.state,f.props.page&&(f.props.page.url=n);const w=(await Promise.all(Ke.map(p=>p(g.navigation)))).filter(p=>typeof p=="function");if(w.length>0){let p=function(){$=$.filter(v=>!w.includes(v))};w.push(p),$.push(...w)}Et.$set(f.props),Xt=!0}else ee(f,gt,!1);const{activeElement:m}=document;await fe();const b=e?e.scroll:a?yt():null;if(Nt){const w=n.hash&&document.getElementById(decodeURIComponent(n.hash.slice(1)));b?scrollTo(b.x,b.y):w?w.scrollIntoView():scrollTo(0,0)}const A=document.activeElement!==m&&document.activeElement!==document.body;!r&&!A&&en(),Nt=!0,f.props.page&&(I=f.props.page),K=!1,t==="popstate"&&Qt(L),g.fulfil(void 0),$.forEach(w=>w(g.navigation)),U.navigating.set(null)}async function oe(t,n,e,r){return t.origin===z&&t.pathname===location.pathname&&!bt?await st({status:r,error:e,url:t,route:n}):await V(t)}function Xe(){let t;T.addEventListener("mousemove",o=>{const i=o.target;clearTimeout(t),t=setTimeout(()=>{r(i,2)},20)});function n(o){r(o.composedPath()[0],1)}T.addEventListener("mousedown",n),T.addEventListener("touchstart",n,{passive:!0});const e=new IntersectionObserver(o=>{for(const i of o)i.isIntersecting&&(dt(i.target.href),e.unobserve(i.target))},{threshold:0});function r(o,i){const s=Kt(o,T);if(!s)return;const{url:c,external:l,download:u}=ht(s,P);if(l||u)return;const h=W(s);if(!h.reload)if(i<=h.preload_data){const g=Rt(c,!1);g&&Ye(g)}else i<=h.preload_code&&dt(c.pathname)}function a(){e.disconnect();for(const o of T.querySelectorAll("a")){const{url:i,external:s,download:c}=ht(o,P);if(s||c)continue;const l=W(o);l.reload||(l.preload_code===J.viewport&&e.observe(o),l.preload_code===J.eager&&dt(i.pathname))}}$.push(a),a()}function C(t,n){if(t instanceof at)return t.body;const e=X(t),r=He(t);return F.hooks.handleError({error:t,event:n,status:e,message:r})??{message:r}}function Ze(t,n={}){return t=Ht(t),t.origin!==z?Promise.reject(new Error("goto: invalid URL")):te(t,n,0)}function Qe(){var n;history.scrollRestoration="manual",addEventListener("beforeunload",e=>{let r=!1;if(Ot(),!K){const a=ce(y,void 0,null,"leave"),o={...a.navigation,cancel:()=>{r=!0,a.reject(new Error("navigation cancelled"))}};Wt.forEach(i=>i(o))}r?(e.preventDefault(),e.returnValue=""):history.scrollRestoration="auto"}),addEventListener("visibilitychange",()=>{document.visibilityState==="hidden"&&Ot()}),(n=navigator.connection)!=null&&n.saveData||Xe(),T.addEventListener("click",async e=>{var g;if(e.button||e.which!==1||e.metaKey||e.ctrlKey||e.shiftKey||e.altKey||e.defaultPrevented)return;const r=Kt(e.composedPath()[0],T);if(!r)return;const{url:a,external:o,target:i,download:s}=ht(r,P);if(!a)return;if(i==="_parent"||i==="_top"){if(window.parent!==window)return}else if(i&&i!=="_self")return;const c=W(r);if(!(r instanceof SVGAElement)&&a.protocol!==location.protocol&&!(a.protocol==="https:"||a.protocol==="http:")||s)return;if(o||c.reload){ae({url:a,type:"link"})?K=!0:e.preventDefault();return}const[u,h]=a.href.split("#");if(h!==void 0&&u===ft(location)){const[,d]=y.url.href.split("#");if(d===h){e.preventDefault(),h===""||h==="top"&&r.ownerDocument.getElementById("top")===null?window.scrollTo({top:0}):(g=r.ownerDocument.getElementById(h))==null||g.scrollIntoView();return}if(q=!0,vt(S),t(a),!c.replace_state)return;q=!1}e.preventDefault(),await new Promise(d=>{requestAnimationFrame(()=>{setTimeout(d,0)}),setTimeout(d,100)}),Y({type:"link",url:a,keepfocus:c.keepfocus,noscroll:c.noscroll,replace_state:c.replace_state??a.href===location.href})}),T.addEventListener("submit",e=>{if(e.defaultPrevented)return;const r=HTMLFormElement.prototype.cloneNode.call(e.target),a=e.submitter;if(((a==null?void 0:a.formMethod)||r.method)!=="get")return;const i=new URL((a==null?void 0:a.hasAttribute("formaction"))&&(a==null?void 0:a.formAction)||r.action);if(rt(i,P))return;const s=e.target,c=W(s);if(c.reload)return;e.preventDefault(),e.stopPropagation();const l=new FormData(s),u=a==null?void 0:a.getAttribute("name");u&&l.append(u,(a==null?void 0:a.getAttribute("value"))??""),i.search=new URLSearchParams(l).toString(),Y({type:"form",url:i,keepfocus:c.keepfocus,noscroll:c.noscroll,replace_state:c.replace_state??i.href===location.href})}),addEventListener("popstate",async e=>{var r;if((r=e.state)!=null&&r[D]){const a=e.state[D];if(et={},a===S)return;const o=N[a],i=e.state[Mt]??{},s=new URL(e.state[Ue]??location.href),c=e.state[H],l=ft(location)===ft(y.url);if(c===L&&(Xt||l)){t(s),N[S]=yt(),o&&scrollTo(o.x,o.y),i!==I.state&&(I={...I,state:i},Et.$set({page:I})),S=a;return}const h=a-S;await Y({type:"popstate",url:s,popped:{state:i,scroll:o,delta:h},accept:()=>{S=a,L=c},block:()=>{history.go(-h)},nav_token:et})}else if(!q){const a=new URL(location.href);t(a)}}),addEventListener("hashchange",()=>{q&&(q=!1,history.replaceState({...history.state,[D]:++S,[H]:L},"",location.href))});for(const e of document.querySelectorAll("link"))e.rel==="icon"&&(e.href=e.href);addEventListener("pageshow",e=>{e.persisted&&U.navigating.set(null)});function t(e){y.url=e,U.page.set({...I,url:e}),U.page.notify()}}async function tn(t,{status:n=200,error:e,node_ids:r,params:a,route:o,data:i,form:s}){bt=!0;const c=new URL(location.href);({params:a={},route:o={id:null}}=Rt(c,!1)||{});let l;try{const u=r.map(async(d,_)=>{const f=i[_];return f!=null&&f.uses&&(f.uses=ie(f.uses)),St({loader:F.nodes[d],url:c,params:a,route:o,parent:async()=>{const m={};for(let b=0;b<_;b+=1)Object.assign(m,(await u[b]).data);return m},server_data_node:At(f)})}),h=await Promise.all(u),g=ot.find(({id:d})=>d===o.id);if(g){const d=g.layouts;for(let _=0;_<d.length;_++)d[_]||h.splice(_,0,void 0)}l=nt({url:c,params:a,branch:h,status:n,error:e,form:s,route:g??null})}catch(u){if(u instanceof Yt){await V(new URL(u.location,location.href));return}l=await st({status:X(u),error:await C(u,{url:c,params:a,route:o}),url:c,route:o})}l.props.page&&(l.props.page.state={}),ee(l,t,!0)}async function se(t,n){var a;const e=new URL(t);e.pathname=ye(t.pathname),t.pathname.endsWith("/")&&e.searchParams.append(Me,"1"),e.searchParams.append(Ge,n.map(o=>o?"1":"0").join(""));const r=await Vt(e.href);if(!r.ok){let o;throw(a=r.headers.get("content-type"))!=null&&a.includes("application/json")?o=await r.json():r.status===404?o="Not Found":r.status===500&&(o="Internal Error"),new at(r.status,o)}return new Promise(async o=>{var h;const i=new Map,s=r.body.getReader(),c=new TextDecoder;function l(g){return Ve(g,{Promise:d=>new Promise((_,f)=>{i.set(d,{fulfil:_,reject:f})})})}let u="";for(;;){const{done:g,value:d}=await s.read();if(g&&!u)break;for(u+=!d&&u?`
-`:c.decode(d,{stream:!0});;){const _=u.indexOf(`
-`);if(_===-1)break;const f=JSON.parse(u.slice(0,_));if(u=u.slice(_+1),f.type==="redirect")return o(f);if(f.type==="data")(h=f.nodes)==null||h.forEach(m=>{(m==null?void 0:m.type)==="data"&&(m.uses=ie(m.uses),m.data=l(m.data))}),o(f);else if(f.type==="chunk"){const{id:m,data:b,error:A}=f,w=i.get(m);i.delete(m),A?w.reject(l(A)):w.fulfil(l(b))}}}})}function ie(t){return{dependencies:new Set((t==null?void 0:t.dependencies)??[]),params:new Set((t==null?void 0:t.params)??[]),parent:!!(t!=null&&t.parent),route:!!(t!=null&&t.route),url:!!(t!=null&&t.url),search_params:new Set((t==null?void 0:t.search_params)??[])}}function en(){const t=document.querySelector("[autofocus]");if(t)t.focus();else{const n=document.body,e=n.getAttribute("tabindex");n.tabIndex=-1,n.focus({preventScroll:!0,focusVisible:!1}),e!==null?n.setAttribute("tabindex",e):n.removeAttribute("tabindex");const r=getSelection();if(r&&r.type!=="None"){const a=[];for(let o=0;o<r.rangeCount;o+=1)a.push(r.getRangeAt(o));setTimeout(()=>{if(r.rangeCount===a.length){for(let o=0;o<r.rangeCount;o+=1){const i=a[o],s=r.getRangeAt(o);if(i.commonAncestorContainer!==s.commonAncestorContainer||i.startContainer!==s.startContainer||i.endContainer!==s.endContainer||i.startOffset!==s.startOffset||i.endOffset!==s.endOffset)return}r.removeAllRanges()}})}}}function ce(t,n,e,r){var c,l;let a,o;const i=new Promise((u,h)=>{a=u,o=h});return i.catch(()=>{}),{navigation:{from:{params:t.params,route:{id:((c=t.route)==null?void 0:c.id)??null},url:t.url},to:e&&{params:(n==null?void 0:n.params)??null,route:{id:((l=n==null?void 0:n.route)==null?void 0:l.id)??null},url:e},willUnload:!n,type:r,complete:i},fulfil:a,reject:o}}export{rn as a,U as s};

_app/immutable/chunks/index.C4D7lu78.js

@@ -1 +0,0 @@
-var E=Object.defineProperty;var j=(e,t,n)=>t in e?E(e,t,{enumerable:!0,configurable:!0,writable:!0,value:n}):e[t]=n;var p=(e,t,n)=>j(e,typeof t!="symbol"?t+"":t,n);import{r as h,n as y,f as w,h as C,i as S,j as B,k as b,l as I,m as P,p as N,q as T,v as q,w as H}from"./scheduler.CtbWrGNo.js";let $=!1;function M(){$=!0}function O(){$=!1}function D(e,t,n,a){for(;e<t;){const s=e+(t-e>>1);n(s)<=a?e=s+1:t=s}return e}function L(e){if(e.hydrate_init)return;e.hydrate_init=!0;let t=e.childNodes;if(e.nodeName==="HEAD"){const i=[];for(let r=0;r<t.length;r++){const o=t[r];o.claim_order!==void 0&&i.push(o)}t=i}const n=new Int32Array(t.length+1),a=new Int32Array(t.length);n[0]=-1;let s=0;for(let i=0;i<t.length;i++){const r=t[i].claim_order,o=(s>0&&t[n[s]].claim_order<=r?s+1:D(1,s,_=>t[n[_]].claim_order,r))-1;a[i]=n[o]+1;const u=o+1;n[u]=i,s=Math.max(u,s)}const c=[],l=[];let f=t.length-1;for(let i=n[s]+1;i!=0;i=a[i-1]){for(c.push(t[i-1]);f>=i;f--)l.push(t[f]);f--}for(;f>=0;f--)l.push(t[f]);c.reverse(),l.sort((i,r)=>i.claim_order-r.claim_order);for(let i=0,r=0;i<l.length;i++){for(;r<c.length&&l[i].claim_order>=c[r].claim_order;)r++;const o=r<c.length?c[r]:null;e.insertBefore(l[i],o)}}function R(e,t){if($){for(L(e),(e.actual_end_child===void 0||e.actual_end_child!==null&&e.actual_end_child.parentNode!==e)&&(e.actual_end_child=e.firstChild);e.actual_end_child!==null&&e.actual_end_child.claim_order===void 0;)e.actual_end_child=e.actual_end_child.nextSibling;t!==e.actual_end_child?(t.claim_order!==void 0||t.parentNode!==e)&&e.insertBefore(t,e.actual_end_child):e.actual_end_child=t.nextSibling}else(t.parentNode!==e||t.nextSibling!==null)&&e.appendChild(t)}function ee(e,t,n){$&&!n?R(e,t):(t.parentNode!==e||t.nextSibling!=n)&&e.insertBefore(t,n||null)}function U(e){e.parentNode&&e.parentNode.removeChild(e)}function V(e){return document.createElement(e)}function x(e){return document.createTextNode(e)}function te(){return x(" ")}function ne(){return x("")}function ie(e,t,n){n==null?e.removeAttribute(t):e.getAttribute(t)!==n&&e.setAttribute(t,n)}function re(e){return e.dataset.svelteH}function W(e){return Array.from(e.childNodes)}function z(e){e.claim_info===void 0&&(e.claim_info={last_index:0,total_claimed:0})}function A(e,t,n,a,s=!1){z(e);const c=(()=>{for(let l=e.claim_info.last_index;l<e.length;l++){const f=e[l];if(t(f)){const i=n(f);return i===void 0?e.splice(l,1):e[l]=i,s||(e.claim_info.last_index=l),f}}for(let l=e.claim_info.last_index-1;l>=0;l--){const f=e[l];if(t(f)){const i=n(f);return i===void 0?e.splice(l,1):e[l]=i,s?i===void 0&&e.claim_info.last_index--:e.claim_info.last_index=l,f}}return a()})();return c.claim_order=e.claim_info.total_claimed,e.claim_info.total_claimed+=1,c}function F(e,t,n,a){return A(e,s=>s.nodeName===t,s=>{const c=[];for(let l=0;l<s.attributes.length;l++){const f=s.attributes[l];n[f.name]||c.push(f.name)}c.forEach(l=>s.removeAttribute(l))},()=>a(t))}function ae(e,t,n){return F(e,t,n,V)}function G(e,t){return A(e,n=>n.nodeType===3,n=>{const a=""+t;if(n.data.startsWith(a)){if(n.data.length!==a.length)return n.splitText(a.length)}else n.data=a},()=>x(t),!0)}function le(e){return G(e," ")}function se(e,t){t=""+t,e.data!==t&&(e.data=t)}function fe(e,t,n,a){n==null?e.style.removeProperty(t):e.style.setProperty(t,n,"")}function ce(e,t){return new e(t)}const m=new Set;let d;function ue(){d={r:0,c:[],p:d}}function oe(){d.r||h(d.c),d=d.p}function J(e,t){e&&e.i&&(m.delete(e),e.i(t))}function de(e,t,n,a){if(e&&e.o){if(m.has(e))return;m.add(e),d.c.push(()=>{m.delete(e),a&&(n&&e.d(1),a())}),e.o(t)}else a&&a()}function _e(e){e&&e.c()}function me(e,t){e&&e.l(t)}function K(e,t,n){const{fragment:a,after_update:s}=e.$$;a&&a.m(t,n),b(()=>{const c=e.$$.on_mount.map(T).filter(S);e.$$.on_destroy?e.$$.on_destroy.push(...c):h(c),e.$$.on_mount=[]}),s.forEach(b)}function Q(e,t){const n=e.$$;n.fragment!==null&&(I(n.after_update),h(n.on_destroy),n.fragment&&n.fragment.d(t),n.on_destroy=n.fragment=null,n.ctx=[])}function X(e,t){e.$$.dirty[0]===-1&&(q.push(e),H(),e.$$.dirty.fill(0)),e.$$.dirty[t/31|0]|=1<<t%31}function he(e,t,n,a,s,c,l=null,f=[-1]){const i=P;N(e);const r=e.$$={fragment:null,ctx:[],props:c,update:y,not_equal:s,bound:w(),on_mount:[],on_destroy:[],on_disconnect:[],before_update:[],after_update:[],context:new Map(t.context||(i?i.$$.context:[])),callbacks:w(),dirty:f,skip_bound:!1,root:t.target||i.$$.root};l&&l(r.root);let o=!1;if(r.ctx=n?n(e,t.props||{},(u,_,...g)=>{const v=g.length?g[0]:_;return r.ctx&&s(r.ctx[u],r.ctx[u]=v)&&(!r.skip_bound&&r.bound[u]&&r.bound[u](v),o&&X(e,u)),_}):[],r.update(),o=!0,h(r.before_update),r.fragment=a?a(r.ctx):!1,t.target){if(t.hydrate){M();const u=W(t.target);r.fragment&&r.fragment.l(u),u.forEach(U)}else r.fragment&&r.fragment.c();t.intro&&J(e.$$.fragment),K(e,t.target,t.anchor),O(),C()}N(i)}class $e{constructor(){p(this,"$$");p(this,"$$set")}$destroy(){Q(this,1),this.$destroy=y}$on(t,n){if(!S(n))return y;const a=this.$$.callbacks[t]||(this.$$.callbacks[t]=[]);return a.push(n),()=>{const s=a.indexOf(n);s!==-1&&a.splice(s,1)}}$set(t){this.$$set&&!B(t)&&(this.$$.skip_bound=!0,this.$$set(t),this.$$.skip_bound=!1)}}const Y="4";typeof window<"u"&&(window.__svelte||(window.__svelte={v:new Set})).v.add(Y);export{$e as S,W as a,G as b,ae as c,U as d,V as e,le as f,ee as g,R as h,he as i,se as j,re as k,ie as l,J as m,de as n,ne as o,oe as p,fe as q,ue as r,te as s,x as t,ce as u,_e as v,me as w,K as x,Q as y};

_app/immutable/chunks/scheduler.CtbWrGNo.js

@@ -1 +0,0 @@
-function k(){}function x(t,n){for(const e in n)t[e]=n[e];return t}function w(t){return t()}function z(){return Object.create(null)}function j(t){t.forEach(w)}function F(t){return typeof t=="function"}function P(t,n){return t!=t?n==n:t!==n||t&&typeof t=="object"||typeof t=="function"}function S(t){return Object.keys(t).length===0}function E(t,...n){if(t==null){for(const o of n)o(void 0);return k}const e=t.subscribe(...n);return e.unsubscribe?()=>e.unsubscribe():e}function U(t,n,e){t.$$.on_destroy.push(E(n,e))}function A(t,n,e,o){if(t){const r=g(t,n,e,o);return t[0](r)}}function g(t,n,e,o){return t[1]&&o?x(e.ctx.slice(),t[1](o(n))):e.ctx}function B(t,n,e,o){if(t[2]&&o){const r=t[2](o(e));if(n.dirty===void 0)return r;if(typeof r=="object"){const a=[],f=Math.max(n.dirty.length,r.length);for(let s=0;s<f;s+=1)a[s]=n.dirty[s]|r[s];return a}return n.dirty|r}return n.dirty}function C(t,n,e,o,r,a){if(r){const f=g(n,e,o,a);t.p(f,r)}}function D(t){if(t.ctx.length>32){const n=[],e=t.ctx.length/32;for(let o=0;o<e;o++)n[o]=-1;return n}return-1}let i;function d(t){i=t}function m(){if(!i)throw new Error("Function called outside component initialization");return i}function G(t){m().$$.on_mount.push(t)}function H(t){m().$$.after_update.push(t)}const l=[],p=[];let u=[];const b=[],y=Promise.resolve();let h=!1;function v(){h||(h=!0,y.then(q))}function I(){return v(),y}function O(t){u.push(t)}const _=new Set;let c=0;function q(){if(c!==0)return;const t=i;do{try{for(;c<l.length;){const n=l[c];c++,d(n),M(n.$$)}}catch(n){throw l.length=0,c=0,n}for(d(null),l.length=0,c=0;p.length;)p.pop()();for(let n=0;n<u.length;n+=1){const e=u[n];_.has(e)||(_.add(e),e())}u.length=0}while(l.length);for(;b.length;)b.pop()();h=!1,_.clear(),d(t)}function M(t){if(t.fragment!==null){t.update(),j(t.before_update);const n=t.dirty;t.dirty=[-1],t.fragment&&t.fragment.p(t.ctx,n),t.after_update.forEach(O)}}function J(t){const n=[],e=[];u.forEach(o=>t.indexOf(o)===-1?n.push(o):e.push(o)),e.forEach(o=>o()),u=n}export{A as a,B as b,U as c,H as d,p as e,z as f,D as g,q as h,F as i,S as j,O as k,J as l,i as m,k as n,G as o,d as p,w as q,j as r,P as s,I as t,C as u,l as v,v as w};

_app/immutable/entry/app.Bje1ZUR5.js

@@ -1,2 +0,0 @@
-const __vite__mapDeps=(i,m=__vite__mapDeps,d=(m.f||(m.f=["../nodes/0.dPy0WIMN.js","../chunks/scheduler.CtbWrGNo.js","../chunks/index.C4D7lu78.js","../assets/0.DViICDYp.css","../nodes/1.BADQ-P6Z.js","../chunks/entry.CsquK5o6.js","../nodes/2.C-zSEB19.js","../assets/2.Dl1cvM0g.css"])))=>i.map(i=>d[i]);
-import{s as V,d as B,o as U,e as A,t as j}from"../chunks/scheduler.CtbWrGNo.js";import{S as W,i as z,s as F,o as h,f as G,g as k,n as p,p as L,m as g,d as w,e as H,c as J,a as K,l as q,q as d,t as Q,b as X,j as Y,r as S,u as E,v as y,w as D,x as R,y as P}from"../chunks/index.C4D7lu78.js";const Z="modulepreload",M=function(a,e){return new URL(a,e).href},I={},C=function(e,n,i){let s=Promise.resolve();if(n&&n.length>0){const u=document.getElementsByTagName("link"),t=document.querySelector("meta[property=csp-nonce]"),r=(t==null?void 0:t.nonce)||(t==null?void 0:t.getAttribute("nonce"));s=Promise.all(n.map(o=>{if(o=M(o,i),o in I)return;I[o]=!0;const f=o.endsWith(".css"),l=f?'[rel="stylesheet"]':"";if(!!i)for(let b=u.length-1;b>=0;b--){const v=u[b];if(v.href===o&&(!f||v.rel==="stylesheet"))return}else if(document.querySelector(`link[href="${o}"]${l}`))return;const _=document.createElement("link");if(_.rel=f?"stylesheet":Z,f||(_.as="script",_.crossOrigin=""),_.href=o,r&&_.setAttribute("nonce",r),document.head.appendChild(_),f)return new Promise((b,v)=>{_.addEventListener("load",b),_.addEventListener("error",()=>v(new Error(`Unable to preload CSS for ${o}`)))})}))}return s.then(()=>e()).catch(u=>{const t=new Event("vite:preloadError",{cancelable:!0});if(t.payload=u,window.dispatchEvent(t),!t.defaultPrevented)throw u})},re={};function $(a){let e,n,i;var s=a[1][0];function u(t,r){return{props:{data:t[3],form:t[2]}}}return s&&(e=E(s,u(a)),a[12](e)),{c(){e&&y(e.$$.fragment),n=h()},l(t){e&&D(e.$$.fragment,t),n=h()},m(t,r){e&&R(e,t,r),k(t,n,r),i=!0},p(t,r){if(r&2&&s!==(s=t[1][0])){if(e){S();const o=e;p(o.$$.fragment,1,0,()=>{P(o,1)}),L()}s?(e=E(s,u(t)),t[12](e),y(e.$$.fragment),g(e.$$.fragment,1),R(e,n.parentNode,n)):e=null}else if(s){const o={};r&8&&(o.data=t[3]),r&4&&(o.form=t[2]),e.$set(o)}},i(t){i||(e&&g(e.$$.fragment,t),i=!0)},o(t){e&&p(e.$$.fragment,t),i=!1},d(t){t&&w(n),a[12](null),e&&P(e,t)}}}function x(a){let e,n,i;var s=a[1][0];function u(t,r){return{props:{data:t[3],$$slots:{default:[ee]},$$scope:{ctx:t}}}}return s&&(e=E(s,u(a)),a[11](e)),{c(){e&&y(e.$$.fragment),n=h()},l(t){e&&D(e.$$.fragment,t),n=h()},m(t,r){e&&R(e,t,r),k(t,n,r),i=!0},p(t,r){if(r&2&&s!==(s=t[1][0])){if(e){S();const o=e;p(o.$$.fragment,1,0,()=>{P(o,1)}),L()}s?(e=E(s,u(t)),t[11](e),y(e.$$.fragment),g(e.$$.fragment,1),R(e,n.parentNode,n)):e=null}else if(s){const o={};r&8&&(o.data=t[3]),r&8215&&(o.$$scope={dirty:r,ctx:t}),e.$set(o)}},i(t){i||(e&&g(e.$$.fragment,t),i=!0)},o(t){e&&p(e.$$.fragment,t),i=!1},d(t){t&&w(n),a[11](null),e&&P(e,t)}}}function ee(a){let e,n,i;var s=a[1][1];function u(t,r){return{props:{data:t[4],form:t[2]}}}return s&&(e=E(s,u(a)),a[10](e)),{c(){e&&y(e.$$.fragment),n=h()},l(t){e&&D(e.$$.fragment,t),n=h()},m(t,r){e&&R(e,t,r),k(t,n,r),i=!0},p(t,r){if(r&2&&s!==(s=t[1][1])){if(e){S();const o=e;p(o.$$.fragment,1,0,()=>{P(o,1)}),L()}s?(e=E(s,u(t)),t[10](e),y(e.$$.fragment),g(e.$$.fragment,1),R(e,n.parentNode,n)):e=null}else if(s){const o={};r&16&&(o.data=t[4]),r&4&&(o.form=t[2]),e.$set(o)}},i(t){i||(e&&g(e.$$.fragment,t),i=!0)},o(t){e&&p(e.$$.fragment,t),i=!1},d(t){t&&w(n),a[10](null),e&&P(e,t)}}}function N(a){let e,n=a[6]&&O(a);return{c(){e=H("div"),n&&n.c(),this.h()},l(i){e=J(i,"DIV",{id:!0,"aria-live":!0,"aria-atomic":!0,style:!0});var s=K(e);n&&n.l(s),s.forEach(w),this.h()},h(){q(e,"id","svelte-announcer"),q(e,"aria-live","assertive"),q(e,"aria-atomic","true"),d(e,"position","absolute"),d(e,"left","0"),d(e,"top","0"),d(e,"clip","rect(0 0 0 0)"),d(e,"clip-path","inset(50%)"),d(e,"overflow","hidden"),d(e,"white-space","nowrap"),d(e,"width","1px"),d(e,"height","1px")},m(i,s){k(i,e,s),n&&n.m(e,null)},p(i,s){i[6]?n?n.p(i,s):(n=O(i),n.c(),n.m(e,null)):n&&(n.d(1),n=null)},d(i){i&&w(e),n&&n.d()}}}function O(a){let e;return{c(){e=Q(a[7])},l(n){e=X(n,a[7])},m(n,i){k(n,e,i)},p(n,i){i&128&&Y(e,n[7])},d(n){n&&w(e)}}}function te(a){let e,n,i,s,u;const t=[x,$],r=[];function o(l,m){return l[1][1]?0:1}e=o(a),n=r[e]=t[e](a);let f=a[5]&&N(a);return{c(){n.c(),i=F(),f&&f.c(),s=h()},l(l){n.l(l),i=G(l),f&&f.l(l),s=h()},m(l,m){r[e].m(l,m),k(l,i,m),f&&f.m(l,m),k(l,s,m),u=!0},p(l,[m]){let _=e;e=o(l),e===_?r[e].p(l,m):(S(),p(r[_],1,1,()=>{r[_]=null}),L(),n=r[e],n?n.p(l,m):(n=r[e]=t[e](l),n.c()),g(n,1),n.m(i.parentNode,i)),l[5]?f?f.p(l,m):(f=N(l),f.c(),f.m(s.parentNode,s)):f&&(f.d(1),f=null)},i(l){u||(g(n),u=!0)},o(l){p(n),u=!1},d(l){l&&(w(i),w(s)),r[e].d(l),f&&f.d(l)}}}function ne(a,e,n){let{stores:i}=e,{page:s}=e,{constructors:u}=e,{components:t=[]}=e,{form:r}=e,{data_0:o=null}=e,{data_1:f=null}=e;B(i.page.notify);let l=!1,m=!1,_=null;U(()=>{const c=i.page.subscribe(()=>{l&&(n(6,m=!0),j().then(()=>{n(7,_=document.title||"untitled page")}))});return n(5,l=!0),c});function b(c){A[c?"unshift":"push"](()=>{t[1]=c,n(0,t)})}function v(c){A[c?"unshift":"push"](()=>{t[0]=c,n(0,t)})}function T(c){A[c?"unshift":"push"](()=>{t[0]=c,n(0,t)})}return a.$$set=c=>{"stores"in c&&n(8,i=c.stores),"page"in c&&n(9,s=c.page),"constructors"in c&&n(1,u=c.constructors),"components"in c&&n(0,t=c.components),"form"in c&&n(2,r=c.form),"data_0"in c&&n(3,o=c.data_0),"data_1"in c&&n(4,f=c.data_1)},a.$$.update=()=>{a.$$.dirty&768&&i.page.set(s)},[t,u,r,o,f,l,m,_,i,s,b,v,T]}class oe extends W{constructor(e){super(),z(this,e,ne,te,V,{stores:8,page:9,constructors:1,components:0,form:2,data_0:3,data_1:4})}}const ae=[()=>C(()=>import("../nodes/0.dPy0WIMN.js"),__vite__mapDeps([0,1,2,3]),import.meta.url),()=>C(()=>import("../nodes/1.BADQ-P6Z.js"),__vite__mapDeps([4,1,2,5]),import.meta.url),()=>C(()=>import("../nodes/2.C-zSEB19.js"),__vite__mapDeps([6,1,2,7]),import.meta.url)],le=[],fe={"/":[2]},ce={handleError:({error:a})=>{console.error(a)},reroute:()=>{}};export{fe as dictionary,ce as hooks,re as matchers,ae as nodes,oe as root,le as server_loads};

_app/immutable/entry/start.BZni4wHA.js

@@ -1 +0,0 @@
-import{a as t}from"../chunks/entry.CsquK5o6.js";export{t as start};

_app/immutable/nodes/0.dPy0WIMN.js

@@ -1 +0,0 @@
-import{s as l,a as r,u as i,g as u,b as _}from"../chunks/scheduler.CtbWrGNo.js";import{S as f,i as c,m as p,n as m}from"../chunks/index.C4D7lu78.js";const d=!0,S=Object.freeze(Object.defineProperty({__proto__:null,prerender:d},Symbol.toStringTag,{value:"Module"}));function $(n){let s;const a=n[1].default,t=r(a,n,n[0],null);return{c(){t&&t.c()},l(e){t&&t.l(e)},m(e,o){t&&t.m(e,o),s=!0},p(e,[o]){t&&t.p&&(!s||o&1)&&i(t,a,e,e[0],s?_(a,e[0],o,null):u(e[0]),null)},i(e){s||(p(t,e),s=!0)},o(e){m(t,e),s=!1},d(e){t&&t.d(e)}}}function g(n,s,a){let{$$slots:t={},$$scope:e}=s;return n.$$set=o=>{"$$scope"in o&&a(0,e=o.$$scope)},[e,t]}class v extends f{constructor(s){super(),c(this,s,g,$,l,{})}}export{v as component,S as universal};

_app/immutable/nodes/1.BADQ-P6Z.js

@@ -1 +0,0 @@
-import{s as S,n as _,c as x}from"../chunks/scheduler.CtbWrGNo.js";import{S as j,i as q,e as f,t as d,s as y,c as g,a as h,b as v,d as u,f as C,g as m,h as $,j as E}from"../chunks/index.C4D7lu78.js";import{s as H}from"../chunks/entry.CsquK5o6.js";const P=()=>{const s=H;return{page:{subscribe:s.page.subscribe},navigating:{subscribe:s.navigating.subscribe},updated:s.updated}},k={subscribe(s){return P().page.subscribe(s)}};function w(s){var b;let t,r=s[0].status+"",o,n,i,c=((b=s[0].error)==null?void 0:b.message)+"",l;return{c(){t=f("h1"),o=d(r),n=y(),i=f("p"),l=d(c)},l(e){t=g(e,"H1",{});var a=h(t);o=v(a,r),a.forEach(u),n=C(e),i=g(e,"P",{});var p=h(i);l=v(p,c),p.forEach(u)},m(e,a){m(e,t,a),$(t,o),m(e,n,a),m(e,i,a),$(i,l)},p(e,[a]){var p;a&1&&r!==(r=e[0].status+"")&&E(o,r),a&1&&c!==(c=((p=e[0].error)==null?void 0:p.message)+"")&&E(l,c)},i:_,o:_,d(e){e&&(u(t),u(n),u(i))}}}function z(s,t,r){let o;return x(s,k,n=>r(0,o=n)),[o]}let F=class extends j{constructor(t){super(),q(this,t,z,w,S,{})}};export{F as component};

_app/immutable/nodes/2.C-zSEB19.js

@@ -1,3 +0,0 @@
-import{s as l,n as a}from"../chunks/scheduler.CtbWrGNo.js";import{S as i,i as c,e as o,c as h,k as g,l as m,g as u,d as f}from"../chunks/index.C4D7lu78.js";function d(r){let e,s=`<article class="mx-4 max-w-4xl text-gray-300"><a href="https://huggingface.co/chat" target="_blank" rel="noreferrer" class="mx-auto mb-12 flex w-fit items-center justify-center gap-2 rounded-lg border border-gray-200 p-4 text-xl font-bold !text-white transition-all hover:-translate-y-0.5 hover:border-gray-300 hover:bg-gray-800">Try
-			<h3 class="svelte-1hc9mw2"><img src="/logo.svg" alt="HuggingChat" class="inline w-10"/>
-				HuggingChat</h3></a> <p class="svelte-1hc9mw2">HuggingChat is now available at <a class="link svelte-1hc9mw2" href="https://huggingface.co/chat" target="_blank" rel="noreferrer">hf.co/chat</a> and is no longer hosted as a space.</p> <p class="svelte-1hc9mw2">You can still interact with the community and give feedback in the <a class="link svelte-1hc9mw2" href="https://huggingface.co/spaces/huggingchat/chat-ui/discussions" target="_blank" rel="noreferrer">space&#39;s discussions</a>.</p></article>`;return{c(){e=o("div"),e.innerHTML=s,this.h()},l(t){e=h(t,"DIV",{class:!0,"data-svelte-h":!0}),g(e)!=="svelte-hljhww"&&(e.innerHTML=s),this.h()},h(){m(e,"class","mx-auto w-fit pt-10")},m(t,n){u(t,e,n)},p:a,i:a,o:a,d(t){t&&f(e)}}}class w extends i{constructor(e){super(),c(this,e,null,d,l,{})}}export{w as component};

_app/version.json

@@ -1 +0,0 @@
-{"version":"1722243467595"}

entrypoint.sh

@@ -0,0 +1,19 @@
+ENV_LOCAL_PATH=/app/.env.local
+
+if test -z "${DOTENV_LOCAL}" ; then
+    if ! test -f "${ENV_LOCAL_PATH}" ; then
+        echo "DOTENV_LOCAL was not found in the ENV variables and .env.local is not set using a bind volume. Make sure to set environment variables properly. "
+    fi;
+else
+    echo "DOTENV_LOCAL was found in the ENV variables. Creating .env.local file."
+    cat <<< "$DOTENV_LOCAL" > ${ENV_LOCAL_PATH}
+fi;
+
+if [ "$INCLUDE_DB" = "true" ] ; then
+    echo "Starting local MongoDB instance"
+    nohup mongod &
+fi;
+
+export PUBLIC_VERSION=$(node -p "require('./package.json').version")
+
+dotenv -e /app/.env -c -- node /app/build/index.js -- --host 0.0.0.0 --port 3000

index.html

@@ -1,48 +0,0 @@
-<!DOCTYPE html>
-<html lang="en" class="bg-gray-900">
-	<head>
-		<meta charset="utf-8" />
-		<link rel="icon" href="./favicon.svg" />
-		<meta name="viewport" content="width=device-width" />
-		
-		<link href="./_app/immutable/assets/0.DViICDYp.css" rel="stylesheet">
-		<link href="./_app/immutable/assets/2.Dl1cvM0g.css" rel="stylesheet">
-		<link rel="modulepreload" href="./_app/immutable/entry/start.BZni4wHA.js">
-		<link rel="modulepreload" href="./_app/immutable/chunks/entry.CsquK5o6.js">
-		<link rel="modulepreload" href="./_app/immutable/chunks/scheduler.CtbWrGNo.js">
-		<link rel="modulepreload" href="./_app/immutable/entry/app.Bje1ZUR5.js">
-		<link rel="modulepreload" href="./_app/immutable/chunks/index.C4D7lu78.js">
-		<link rel="modulepreload" href="./_app/immutable/nodes/0.dPy0WIMN.js">
-		<link rel="modulepreload" href="./_app/immutable/nodes/2.C-zSEB19.js">
-	</head>
-	<body data-sveltekit-preload-data="hover">
-		<div style="display: contents">  <div class="mx-auto w-fit pt-10" data-svelte-h="svelte-hljhww"><article class="mx-4 max-w-4xl text-gray-300"><a href="https://huggingface.co/chat" target="_blank" rel="noreferrer" class="mx-auto mb-12 flex w-fit items-center justify-center gap-2 rounded-lg border border-gray-200 p-4 text-xl font-bold !text-white transition-all hover:-translate-y-0.5 hover:border-gray-300 hover:bg-gray-800">Try
-			<h3 class="svelte-1hc9mw2"><img src="/logo.svg" alt="HuggingChat" class="inline w-10">
-				HuggingChat</h3></a> <p class="svelte-1hc9mw2">HuggingChat is now available at <a class="link svelte-1hc9mw2" href="https://huggingface.co/chat" target="_blank" rel="noreferrer">hf.co/chat</a> and is no longer hosted as a space.</p> <p class="svelte-1hc9mw2">You can still interact with the community and give feedback in the <a class="link svelte-1hc9mw2" href="https://huggingface.co/spaces/huggingchat/chat-ui/discussions" target="_blank" rel="noreferrer">space&#39;s discussions</a>.</p></article> </div> 
-			
-			<script>
-				{
-					__sveltekit_1klgtbu = {
-						base: new URL(".", location).pathname.slice(0, -1)
-					};
-
-					const element = document.currentScript.parentElement;
-
-					const data = [null,null];
-
-					Promise.all([
-						import("./_app/immutable/entry/start.BZni4wHA.js"),
-						import("./_app/immutable/entry/app.Bje1ZUR5.js")
-					]).then(([kit, app]) => {
-						kit.start(app, element, {
-							node_ids: [0, 2],
-							data,
-							form: null,
-							error: null
-						});
-					});
-				}
-			</script>
-		</div>
-	</body>
-</html>

package.json

@@ -0,0 +1,95 @@
+{
+	"name": "chat-ui",
+	"version": "0.8.3",
+	"private": true,
+	"packageManager": "npm@9.5.0",
+	"scripts": {
+		"dev": "vite dev",
+		"build": "vite build",
+		"preview": "vite preview",
+		"check": "svelte-kit sync && svelte-check --tsconfig ./tsconfig.json",
+		"check:watch": "svelte-kit sync && svelte-check --tsconfig ./tsconfig.json --watch",
+		"lint": "prettier --plugin-search-dir . --check . && eslint .",
+		"format": "prettier --plugin-search-dir . --write .",
+		"test": "MONGODB_URL=mongodb://127.0.0.1:27017/ vitest",
+		"updateLocalEnv": "node --loader ts-node/esm scripts/updateLocalEnv.ts",
+		"updateProdEnv": "node --loader ts-node/esm scripts/updateProdEnv.ts",
+		"populate": "vite-node --options.transformMode.ssr='/.*/' scripts/populate.ts"
+	},
+	"devDependencies": {
+		"@faker-js/faker": "^8.4.1",
+		"@iconify-json/carbon": "^1.1.16",
+		"@iconify-json/eos-icons": "^1.1.6",
+		"@sveltejs/adapter-node": "^1.3.1",
+		"@sveltejs/kit": "^1.30.4",
+		"@tailwindcss/typography": "^0.5.9",
+		"@types/express": "^4.17.21",
+		"@types/jsdom": "^21.1.1",
+		"@types/minimist": "^1.2.5",
+		"@types/parquetjs": "^0.10.3",
+		"@types/uuid": "^9.0.8",
+		"@typescript-eslint/eslint-plugin": "^6.x",
+		"@typescript-eslint/parser": "^6.x",
+		"eslint": "^8.28.0",
+		"eslint-config-prettier": "^8.5.0",
+		"eslint-plugin-svelte": "^2.30.0",
+		"minimist": "^1.2.8",
+		"prettier": "^2.8.0",
+		"prettier-plugin-svelte": "^2.10.1",
+		"prettier-plugin-tailwindcss": "^0.2.7",
+		"prom-client": "^15.1.2",
+		"svelte": "^4.2.8",
+		"svelte-check": "^3.6.2",
+		"ts-node": "^10.9.1",
+		"tslib": "^2.4.1",
+		"typescript": "^5.0.0",
+		"unplugin-icons": "^0.16.1",
+		"vite": "^4.5.3",
+		"vite-node": "^1.3.1",
+		"vitest": "^0.31.0"
+	},
+	"type": "module",
+	"dependencies": {
+		"@huggingface/hub": "^0.5.1",
+		"@huggingface/inference": "^2.6.3",
+		"@iconify-json/bi": "^1.1.21",
+		"@resvg/resvg-js": "^2.6.0",
+		"@xenova/transformers": "^2.16.1",
+		"autoprefixer": "^10.4.14",
+		"browser-image-resizer": "^2.4.1",
+		"date-fns": "^2.29.3",
+		"dotenv": "^16.0.3",
+		"express": "^4.19.2",
+		"handlebars": "^4.7.8",
+		"highlight.js": "^11.7.0",
+		"image-size": "^1.0.2",
+		"ip-address": "^9.0.5",
+		"jsdom": "^22.0.0",
+		"json5": "^2.2.3",
+		"marked": "^12.0.1",
+		"marked-katex-extension": "^5.0.1",
+		"mongodb": "^5.8.0",
+		"nanoid": "^4.0.2",
+		"openid-client": "^5.4.2",
+		"parquetjs": "^0.11.2",
+		"pino": "^9.0.0",
+		"pino-pretty": "^11.0.0",
+		"postcss": "^8.4.31",
+		"saslprep": "^1.0.3",
+		"satori": "^0.10.11",
+		"satori-html": "^0.3.2",
+		"serpapi": "^1.1.1",
+		"sharp": "^0.33.2",
+		"tailwind-scrollbar": "^3.0.0",
+		"tailwindcss": "^3.4.0",
+		"uuid": "^9.0.1",
+		"zod": "^3.22.3"
+	},
+	"optionalDependencies": {
+		"@anthropic-ai/sdk": "^0.17.1",
+		"@google-cloud/vertexai": "^1.1.0",
+		"aws4fetch": "^1.0.17",
+		"cohere-ai": "^7.9.0",
+		"openai": "^4.14.2"
+	}
+}

postcss.config.js

@@ -0,0 +1,6 @@
+export default {
+	plugins: {
+		tailwindcss: {},
+		autoprefixer: {},
+	},
+};

scripts/populate.ts

@@ -0,0 +1,269 @@
+import readline from "readline";
+import minimist from "minimist";
+
+// @ts-expect-error: vite-node makes the var available but the typescript compiler doesn't see them
+import { env } from "$env/dynamic/private";
+
+import { faker } from "@faker-js/faker";
+import { ObjectId } from "mongodb";
+
+// @ts-expect-error: vite-node makes the var available but the typescript compiler doesn't see them
+import { collections } from "$lib/server/database";
+import { models } from "../src/lib/server/models.ts";
+import type { User } from "../src/lib/types/User";
+import type { Assistant } from "../src/lib/types/Assistant";
+import type { Conversation } from "../src/lib/types/Conversation";
+import type { Settings } from "../src/lib/types/Settings";
+import { defaultEmbeddingModel } from "../src/lib/server/embeddingModels.ts";
+import { Message } from "../src/lib/types/Message.ts";
+
+import { addChildren } from "../src/lib/utils/tree/addChildren.ts";
+import { generateSearchTokens } from "../src/lib/utils/searchTokens.ts";
+
+const rl = readline.createInterface({
+	input: process.stdin,
+	output: process.stdout,
+});
+
+rl.on("close", function () {
+	process.exit(0);
+});
+
+const possibleFlags = ["reset", "all", "users", "settings", "assistants", "conversations"];
+const argv = minimist(process.argv.slice(2));
+const flags = argv["_"].filter((flag) => possibleFlags.includes(flag));
+
+async function generateMessages(preprompt?: string): Promise<Message[]> {
+	const isLinear = faker.datatype.boolean(0.5);
+	const isInterrupted = faker.datatype.boolean(0.05);
+
+	const messages: Message[] = [];
+
+	messages.push({
+		id: crypto.randomUUID(),
+		from: "system",
+		content: preprompt ?? "",
+		createdAt: faker.date.recent({ days: 30 }),
+		updatedAt: faker.date.recent({ days: 30 }),
+	});
+
+	let isUser = true;
+	let lastId = messages[0].id;
+	if (isLinear) {
+		const convLength = faker.number.int({ min: 1, max: 25 }) * 2; // must always be even
+
+		for (let i = 0; i < convLength; i++) {
+			lastId = addChildren(
+				{
+					messages,
+					rootMessageId: messages[0].id,
+				},
+				{
+					from: isUser ? "user" : "assistant",
+					content: faker.lorem.sentence({
+						min: 10,
+						max: isUser ? 50 : 200,
+					}),
+					createdAt: faker.date.recent({ days: 30 }),
+					updatedAt: faker.date.recent({ days: 30 }),
+					interrupted: i === convLength - 1 && isInterrupted,
+				},
+				lastId
+			);
+			isUser = !isUser;
+		}
+	} else {
+		const convLength = faker.number.int({ min: 2, max: 200 });
+
+		for (let i = 0; i < convLength; i++) {
+			addChildren(
+				{
+					messages,
+					rootMessageId: messages[0].id,
+				},
+				{
+					from: isUser ? "user" : "assistant",
+					content: faker.lorem.sentence({
+						min: 10,
+						max: isUser ? 50 : 200,
+					}),
+					createdAt: faker.date.recent({ days: 30 }),
+					updatedAt: faker.date.recent({ days: 30 }),
+					interrupted: i === convLength - 1 && isInterrupted,
+				},
+				faker.helpers.arrayElement([
+					messages[0].id,
+					...messages.filter((m) => m.from === (isUser ? "assistant" : "user")).map((m) => m.id),
+				])
+			);
+
+			isUser = !isUser;
+		}
+	}
+	return messages;
+}
+
+async function seed() {
+	console.log("Seeding...");
+	const modelIds = models.map((model) => model.id);
+
+	if (flags.includes("reset")) {
+		console.log("Starting reset of DB");
+		await collections.users.deleteMany({});
+		await collections.settings.deleteMany({});
+		await collections.assistants.deleteMany({});
+		await collections.conversations.deleteMany({});
+		console.log("Reset done");
+	}
+
+	if (flags.includes("users") || flags.includes("all")) {
+		console.log("Creating 100 new users");
+		const newUsers: User[] = Array.from({ length: 100 }, () => ({
+			_id: new ObjectId(),
+			createdAt: faker.date.recent({ days: 30 }),
+			updatedAt: faker.date.recent({ days: 30 }),
+			username: faker.internet.userName(),
+			name: faker.person.fullName(),
+			hfUserId: faker.string.alphanumeric(24),
+			avatarUrl: faker.image.avatar(),
+		}));
+
+		await collections.users.insertMany(newUsers);
+		console.log("Done creating users.");
+	}
+
+	const users = await collections.users.find().toArray();
+	if (flags.includes("settings") || flags.includes("all")) {
+		console.log("Updating settings for all users");
+		users.forEach(async (user) => {
+			const settings: Settings = {
+				userId: user._id,
+				shareConversationsWithModelAuthors: faker.datatype.boolean(0.25),
+				hideEmojiOnSidebar: faker.datatype.boolean(0.25),
+				ethicsModalAcceptedAt: faker.date.recent({ days: 30 }),
+				activeModel: faker.helpers.arrayElement(modelIds),
+				createdAt: faker.date.recent({ days: 30 }),
+				updatedAt: faker.date.recent({ days: 30 }),
+				customPrompts: {},
+				assistants: [],
+			};
+			await collections.settings.updateOne(
+				{ userId: user._id },
+				{ $set: { ...settings } },
+				{ upsert: true }
+			);
+		});
+		console.log("Done updating settings.");
+	}
+
+	if (flags.includes("assistants") || flags.includes("all")) {
+		console.log("Creating assistants for all users");
+		await Promise.all(
+			users.map(async (user) => {
+				const name = faker.animal.insect();
+				const assistants = faker.helpers.multiple<Assistant>(
+					() => ({
+						_id: new ObjectId(),
+						name,
+						createdById: user._id,
+						createdByName: user.username,
+						createdAt: faker.date.recent({ days: 30 }),
+						updatedAt: faker.date.recent({ days: 30 }),
+						userCount: faker.number.int({ min: 1, max: 100000 }),
+						featured: faker.datatype.boolean(0.25),
+						modelId: faker.helpers.arrayElement(modelIds),
+						description: faker.lorem.sentence(),
+						preprompt: faker.hacker.phrase(),
+						exampleInputs: faker.helpers.multiple(() => faker.lorem.sentence(), {
+							count: faker.number.int({ min: 0, max: 4 }),
+						}),
+						searchTokens: generateSearchTokens(name),
+						last24HoursCount: faker.number.int({ min: 0, max: 1000 }),
+					}),
+					{ count: faker.number.int({ min: 3, max: 10 }) }
+				);
+				await collections.assistants.insertMany(assistants);
+				await collections.settings.updateOne(
+					{ userId: user._id },
+					{ $set: { assistants: assistants.map((a) => a._id.toString()) } },
+					{ upsert: true }
+				);
+			})
+		);
+		console.log("Done creating assistants.");
+	}
+
+	if (flags.includes("conversations") || flags.includes("all")) {
+		console.log("Creating conversations for all users");
+		await Promise.all(
+			users.map(async (user) => {
+				const conversations = faker.helpers.multiple(
+					async () => {
+						const settings = await collections.settings.findOne<Settings>({ userId: user._id });
+
+						const assistantId =
+							settings?.assistants && settings.assistants.length > 0 && faker.datatype.boolean(0.1)
+								? faker.helpers.arrayElement<ObjectId>(settings.assistants)
+								: undefined;
+
+						const preprompt =
+							(assistantId
+								? await collections.assistants
+										.findOne({ _id: assistantId })
+										.then((assistant: Assistant) => assistant?.preprompt ?? "")
+								: faker.helpers.maybe(() => faker.hacker.phrase(), { probability: 0.5 })) ?? "";
+
+						const messages = await generateMessages(preprompt);
+
+						const conv = {
+							_id: new ObjectId(),
+							userId: user._id,
+							assistantId,
+							preprompt,
+							createdAt: faker.date.recent({ days: 145 }),
+							updatedAt: faker.date.recent({ days: 145 }),
+							model: faker.helpers.arrayElement(modelIds),
+							title: faker.internet.emoji() + " " + faker.hacker.phrase(),
+							embeddingModel: defaultEmbeddingModel.id,
+							messages,
+							rootMessageId: messages[0].id,
+						} satisfies Conversation;
+
+						return conv;
+					},
+					{ count: faker.number.int({ min: 10, max: 200 }) }
+				);
+
+				await collections.conversations.insertMany(await Promise.all(conversations));
+			})
+		);
+		console.log("Done creating conversations.");
+	}
+}
+
+// run seed
+(async () => {
+	try {
+		rl.question(
+			"You're about to run a seeding script on the following MONGODB_URL: \x1b[31m" +
+				env.MONGODB_URL +
+				"\x1b[0m\n\n With the following flags: \x1b[31m" +
+				flags.join("\x1b[0m , \x1b[31m") +
+				"\x1b[0m\n \n\n Are you sure you want to continue? (yes/no): ",
+			async (confirm) => {
+				if (confirm !== "yes") {
+					console.log("Not 'yes', exiting.");
+					rl.close();
+					process.exit(0);
+				}
+				console.log("Starting seeding...");
+				await seed();
+				console.log("Seeding done.");
+				rl.close();
+			}
+		);
+	} catch (e) {
+		console.error(e);
+		process.exit(1);
+	}
+})();

scripts/updateLocalEnv.ts

@@ -0,0 +1,20 @@
+import fs from "fs";
+
+const SECRET_CONFIG = fs.existsSync(".env.SECRET_CONFIG")
+	? fs.readFileSync(".env.SECRET_CONFIG", "utf8")
+	: process.env.SECRET_CONFIG;
+
+if (!SECRET_CONFIG) {
+	throw new Error(
+		"SECRET_CONFIG is not defined. Please provide it either in a file or as an environment variable."
+	);
+}
+
+// Read the content of the file .env.template
+const PUBLIC_CONFIG = fs.readFileSync(".env.template", "utf8");
+
+// Prepend the content of the env variable SECRET_CONFIG
+const full_config = `${PUBLIC_CONFIG}\n${SECRET_CONFIG}`;
+
+// Write full_config to .env.local
+fs.writeFileSync(".env.local", full_config);

scripts/updateProdEnv.ts

@@ -0,0 +1,41 @@
+import fs from "fs";
+
+const HF_DEPLOYMENT_TOKEN = process.env.HF_DEPLOYMENT_TOKEN; // token used for pushing to hub
+
+const SERPER_API_KEY = process.env.SERPER_API_KEY;
+const OPENID_CONFIG = process.env.OPENID_CONFIG;
+const MONGODB_URL = process.env.MONGODB_URL;
+const HF_TOKEN = process.env.HF_TOKEN ?? process.env.HF_ACCESS_TOKEN; // token used for API requests in prod
+const WEBHOOK_URL_REPORT_ASSISTANT = process.env.WEBHOOK_URL_REPORT_ASSISTANT; // slack webhook url used to get "report assistant" events
+const ADMIN_API_SECRET = process.env.ADMIN_API_SECRET;
+const USAGE_LIMITS = process.env.USAGE_LIMITS;
+const MESSAGES_BEFORE_LOGIN = process.env.MESSAGES_BEFORE_LOGIN;
+
+// Read the content of the file .env.template
+const PUBLIC_CONFIG = fs.readFileSync(".env.template", "utf8");
+
+// Prepend the content of the env variable SECRET_CONFIG
+const full_config = `${PUBLIC_CONFIG}
+MONGODB_URL=${MONGODB_URL}
+OPENID_CONFIG=${OPENID_CONFIG}
+SERPER_API_KEY=${SERPER_API_KEY}
+HF_TOKEN=${HF_TOKEN}
+WEBHOOK_URL_REPORT_ASSISTANT=${WEBHOOK_URL_REPORT_ASSISTANT}
+ADMIN_API_SECRET=${ADMIN_API_SECRET}
+USAGE_LIMITS=${USAGE_LIMITS}
+MESSAGES_BEFORE_LOGIN=${MESSAGES_BEFORE_LOGIN}
+`;
+
+// Make an HTTP POST request to add the space secrets
+fetch(`https://huggingface.co/api/spaces/huggingchat/chat-ui/secrets`, {
+	method: "POST",
+	body: JSON.stringify({
+		key: "DOTENV_LOCAL",
+		value: full_config,
+		description: `Env variable for HuggingChat. Last updated ${new Date().toISOString()}`,
+	}),
+	headers: {
+		Authorization: `Bearer ${HF_DEPLOYMENT_TOKEN}`,
+		"Content-Type": "application/json",
+	},
+});

src/ambient.d.ts

@@ -0,0 +1,4 @@
+declare module "*.ttf" {
+	const value: ArrayBuffer;
+	export default value;
+}

src/app.d.ts

@@ -0,0 +1,25 @@
+/// <reference types="@sveltejs/kit" />
+/// <reference types="unplugin-icons/types/svelte" />
+
+import type { User } from "$lib/types/User";
+
+// See https://kit.svelte.dev/docs/types#app
+// for information about these interfaces
+declare global {
+	namespace App {
+		// interface Error {}
+		interface Locals {
+			sessionId: string;
+			user?: User;
+		}
+
+		interface Error {
+			message: string;
+			errorId?: ReturnType<typeof crypto.randomUUID>;
+		}
+		// interface PageData {}
+		// interface Platform {}
+	}
+}
+
+export {};

src/app.html

@@ -0,0 +1,47 @@
+<!DOCTYPE html>
+<html lang="en" class="h-full">
+	<head>
+		<meta charset="utf-8" />
+		<meta name="viewport" content="width=device-width, initial-scale=1, user-scalable=no" />
+		<meta name="theme-color" content="rgb(249, 250, 251)" />
+		<script>
+			if (
+				localStorage.theme === "dark" ||
+				(!("theme" in localStorage) && window.matchMedia("(prefers-color-scheme: dark)").matches)
+			) {
+				document.documentElement.classList.add("dark");
+				document
+					.querySelector('meta[name="theme-color"]')
+					.setAttribute("content", "rgb(26, 36, 50)");
+			}
+
+			// For some reason, Sveltekit doesn't let us load env variables from .env here, so we load it from hooks.server.ts
+			window.gaId = "%gaId%";
+		</script>
+		%sveltekit.head%
+	</head>
+	<body data-sveltekit-preload-data="hover" class="h-full dark:bg-gray-900">
+		<div id="app" class="contents h-full">%sveltekit.body%</div>
+
+		<!-- Google Tag Manager -->
+		<script>
+			if (window.gaId) {
+				const script = document.createElement("script");
+				script.src = "https://www.googletagmanager.com/gtag/js?id=" + window.gaId;
+				script.async = true;
+				document.head.appendChild(script);
+
+				window.dataLayer = window.dataLayer || [];
+				function gtag() {
+					dataLayer.push(arguments);
+				}
+				gtag("js", new Date());
+				/// ^ See https://developers.google.com/tag-platform/gtagjs/install
+				gtag("config", window.gaId);
+				gtag("consent", "default", { ad_storage: "denied", analytics_storage: "denied" });
+				/// ^ See https://developers.google.com/tag-platform/gtagjs/reference#consent
+				/// TODO: ask the user for their consent and update this with gtag('consent', 'update')
+			}
+		</script>
+	</body>
+</html>

src/hooks.server.ts

@@ -0,0 +1,210 @@
+import { env } from "$env/dynamic/private";
+import { env as envPublic } from "$env/dynamic/public";
+import type { Handle, HandleServerError } from "@sveltejs/kit";
+import { collections } from "$lib/server/database";
+import { base } from "$app/paths";
+import { findUser, refreshSessionCookie, requiresUser } from "$lib/server/auth";
+import { ERROR_MESSAGES } from "$lib/stores/errors";
+import { sha256 } from "$lib/utils/sha256";
+import { addWeeks } from "date-fns";
+import { checkAndRunMigrations } from "$lib/migrations/migrations";
+import { building } from "$app/environment";
+import { refreshAssistantsCounts } from "$lib/assistantStats/refresh-assistants-counts";
+import { logger } from "$lib/server/logger";
+import { AbortedGenerations } from "$lib/server/abortedGenerations";
+import { MetricsServer } from "$lib/server/metrics";
+
+// TODO: move this code on a started server hook, instead of using a "building" flag
+if (!building) {
+	await checkAndRunMigrations();
+	if (env.ENABLE_ASSISTANTS) {
+		refreshAssistantsCounts();
+	}
+
+	// Init metrics server
+	MetricsServer.getInstance();
+
+	// Init AbortedGenerations refresh process
+	AbortedGenerations.getInstance();
+}
+
+export const handleError: HandleServerError = async ({ error, event }) => {
+	// handle 404
+
+	if (building) {
+		throw error;
+	}
+
+	if (event.route.id === null) {
+		return {
+			message: `Page ${event.url.pathname} not found`,
+		};
+	}
+
+	const errorId = crypto.randomUUID();
+
+	logger.error({
+		locals: event.locals,
+		url: event.request.url,
+		params: event.params,
+		request: event.request,
+		error,
+		errorId,
+	});
+
+	return {
+		message: "An error occurred",
+		errorId,
+	};
+};
+
+export const handle: Handle = async ({ event, resolve }) => {
+	logger.debug({
+		locals: event.locals,
+		url: event.url.pathname,
+		params: event.params,
+		request: event.request,
+	});
+
+	if (event.url.pathname.startsWith(`${base}/api/`) && env.EXPOSE_API !== "true") {
+		return new Response("API is disabled", { status: 403 });
+	}
+
+	function errorResponse(status: number, message: string) {
+		const sendJson =
+			event.request.headers.get("accept")?.includes("application/json") ||
+			event.request.headers.get("content-type")?.includes("application/json");
+		return new Response(sendJson ? JSON.stringify({ error: message }) : message, {
+			status,
+			headers: {
+				"content-type": sendJson ? "application/json" : "text/plain",
+			},
+		});
+	}
+
+	if (event.url.pathname.startsWith(`${base}/admin/`) || event.url.pathname === `${base}/admin`) {
+		const ADMIN_SECRET = env.ADMIN_API_SECRET || env.PARQUET_EXPORT_SECRET;
+
+		if (!ADMIN_SECRET) {
+			return errorResponse(500, "Admin API is not configured");
+		}
+
+		if (event.request.headers.get("Authorization") !== `Bearer ${ADMIN_SECRET}`) {
+			return errorResponse(401, "Unauthorized");
+		}
+	}
+
+	const token = event.cookies.get(env.COOKIE_NAME);
+
+	let secretSessionId: string;
+	let sessionId: string;
+
+	if (token) {
+		secretSessionId = token;
+		sessionId = await sha256(token);
+
+		const user = await findUser(sessionId);
+
+		if (user) {
+			event.locals.user = user;
+		}
+	} else {
+		// if the user doesn't have any cookie, we generate one for him
+		secretSessionId = crypto.randomUUID();
+		sessionId = await sha256(secretSessionId);
+
+		if (await collections.sessions.findOne({ sessionId })) {
+			return errorResponse(500, "Session ID collision");
+		}
+	}
+
+	event.locals.sessionId = sessionId;
+
+	// CSRF protection
+	const requestContentType = event.request.headers.get("content-type")?.split(";")[0] ?? "";
+	/** https://developer.mozilla.org/en-US/docs/Web/HTML/Element/form#attr-enctype */
+	const nativeFormContentTypes = [
+		"multipart/form-data",
+		"application/x-www-form-urlencoded",
+		"text/plain",
+	];
+
+	if (event.request.method === "POST") {
+		refreshSessionCookie(event.cookies, event.locals.sessionId);
+
+		if (nativeFormContentTypes.includes(requestContentType)) {
+			const origin = event.request.headers.get("origin");
+
+			if (!origin) {
+				return errorResponse(403, "Non-JSON form requests need to have an origin");
+			}
+
+			const validOrigins = [
+				new URL(event.request.url).host,
+				...(envPublic.PUBLIC_ORIGIN ? [new URL(envPublic.PUBLIC_ORIGIN).host] : []),
+			];
+
+			if (!validOrigins.includes(new URL(origin).host)) {
+				return errorResponse(403, "Invalid referer for POST request");
+			}
+		}
+	}
+
+	if (event.request.method === "POST") {
+		// if the request is a POST request we refresh the cookie
+		refreshSessionCookie(event.cookies, secretSessionId);
+
+		await collections.sessions.updateOne(
+			{ sessionId },
+			{ $set: { updatedAt: new Date(), expiresAt: addWeeks(new Date(), 2) } }
+		);
+	}
+
+	if (
+		!event.url.pathname.startsWith(`${base}/login`) &&
+		!event.url.pathname.startsWith(`${base}/admin`) &&
+		!["GET", "OPTIONS", "HEAD"].includes(event.request.method)
+	) {
+		if (
+			!event.locals.user &&
+			requiresUser &&
+			!((env.MESSAGES_BEFORE_LOGIN ? parseInt(env.MESSAGES_BEFORE_LOGIN) : 0) > 0)
+		) {
+			return errorResponse(401, ERROR_MESSAGES.authOnly);
+		}
+
+		// if login is not required and the call is not from /settings and we display the ethics modal with PUBLIC_APP_DISCLAIMER
+		//  we check if the user has accepted the ethics modal first.
+		// If login is required, `ethicsModalAcceptedAt` is already true at this point, so do not pass this condition. This saves a DB call.
+		if (
+			!requiresUser &&
+			!event.url.pathname.startsWith(`${base}/settings`) &&
+			!!envPublic.PUBLIC_APP_DISCLAIMER
+		) {
+			const hasAcceptedEthicsModal = await collections.settings.countDocuments({
+				sessionId: event.locals.sessionId,
+				ethicsModalAcceptedAt: { $exists: true },
+			});
+
+			if (!hasAcceptedEthicsModal) {
+				return errorResponse(405, "You need to accept the welcome modal first");
+			}
+		}
+	}
+
+	let replaced = false;
+
+	const response = await resolve(event, {
+		transformPageChunk: (chunk) => {
+			// For some reason, Sveltekit doesn't let us load env variables from .env in the app.html template
+			if (replaced || !chunk.html.includes("%gaId%")) {
+				return chunk.html;
+			}
+			replaced = true;
+
+			return chunk.html.replace("%gaId%", envPublic.PUBLIC_GOOGLE_ANALYTICS_ID);
+		},
+	});
+
+	return response;
+};

src/lib/actions/clickOutside.ts

@@ -0,0 +1,18 @@
+export function clickOutside(element: HTMLDialogElement, callbackFunction: () => void) {
+	function onClick(event: MouseEvent) {
+		if (!element.contains(event.target as Node)) {
+			callbackFunction();
+		}
+	}
+
+	document.body.addEventListener("click", onClick);
+
+	return {
+		update(newCallbackFunction: () => void) {
+			callbackFunction = newCallbackFunction;
+		},
+		destroy() {
+			document.body.removeEventListener("click", onClick);
+		},
+	};
+}

src/lib/actions/snapScrollToBottom.ts

@@ -0,0 +1,54 @@
+import { navigating } from "$app/stores";
+import { tick } from "svelte";
+import { get } from "svelte/store";
+
+const detachedOffset = 10;
+
+/**
+ * @param node element to snap scroll to bottom
+ * @param dependency pass in a dependency to update scroll on changes.
+ */
+export const snapScrollToBottom = (node: HTMLElement, dependency: unknown) => {
+	let prevScrollValue = node.scrollTop;
+	let isDetached = false;
+
+	const handleScroll = () => {
+		// if user scrolled up, we detach
+		if (node.scrollTop < prevScrollValue) {
+			isDetached = true;
+		}
+
+		// if user scrolled back to within 10px of bottom, we reattach
+		if (node.scrollTop - (node.scrollHeight - node.clientHeight) >= -detachedOffset) {
+			isDetached = false;
+		}
+
+		prevScrollValue = node.scrollTop;
+	};
+
+	const updateScroll = async (_options: { force?: boolean } = {}) => {
+		const defaultOptions = { force: false };
+		const options = { ...defaultOptions, ..._options };
+		const { force } = options;
+
+		if (!force && isDetached && !get(navigating)) return;
+
+		// wait for next tick to ensure that the DOM is updated
+		await tick();
+
+		node.scrollTo({ top: node.scrollHeight });
+	};
+
+	node.addEventListener("scroll", handleScroll);
+
+	if (dependency) {
+		updateScroll({ force: true });
+	}
+
+	return {
+		update: updateScroll,
+		destroy: () => {
+			node.removeEventListener("scroll", handleScroll);
+		},
+	};
+};

src/lib/assistantStats/refresh-assistants-counts.ts

@@ -0,0 +1,90 @@
+import { Database } from "$lib/server/database";
+import { acquireLock, refreshLock } from "$lib/migrations/lock";
+import type { ObjectId } from "mongodb";
+import { subDays } from "date-fns";
+import { logger } from "$lib/server/logger";
+
+const LOCK_KEY = "assistants.count";
+
+let hasLock = false;
+let lockId: ObjectId | null = null;
+
+async function refreshAssistantsCountsHelper() {
+	if (!hasLock) {
+		return;
+	}
+
+	try {
+		await Database.getInstance()
+			.getClient()
+			.withSession((session) =>
+				session.withTransaction(async () => {
+					await Database.getInstance()
+						.getCollections()
+						.assistants.aggregate([
+							{ $project: { _id: 1 } },
+							{ $set: { last24HoursCount: 0 } },
+							{
+								$unionWith: {
+									coll: "assistants.stats",
+									pipeline: [
+										{
+											$match: { "date.at": { $gte: subDays(new Date(), 1) }, "date.span": "hour" },
+										},
+										{
+											$group: {
+												_id: "$assistantId",
+												last24HoursCount: { $sum: "$count" },
+											},
+										},
+									],
+								},
+							},
+							{
+								$group: {
+									_id: "$_id",
+									last24HoursCount: { $sum: "$last24HoursCount" },
+								},
+							},
+							{
+								$merge: {
+									into: "assistants",
+									on: "_id",
+									whenMatched: "merge",
+									whenNotMatched: "discard",
+								},
+							},
+						])
+						.next();
+				})
+			);
+	} catch (e) {
+		logger.error("Refresh assistants counter failed!");
+		logger.error(e);
+	}
+}
+
+async function maintainLock() {
+	if (hasLock && lockId) {
+		hasLock = await refreshLock(LOCK_KEY, lockId);
+
+		if (!hasLock) {
+			lockId = null;
+		}
+	} else if (!hasLock) {
+		lockId = (await acquireLock(LOCK_KEY)) || null;
+		hasLock = !!lockId;
+	}
+
+	setTimeout(maintainLock, 10_000);
+}
+
+export function refreshAssistantsCounts() {
+	const ONE_HOUR_MS = 3_600_000;
+
+	maintainLock().then(() => {
+		refreshAssistantsCountsHelper();
+
+		setInterval(refreshAssistantsCountsHelper, ONE_HOUR_MS);
+	});
+}