diff --git a/.dockerignore b/.dockerignore index cd4afbe92f293bdc25787af1b7ba21c86cb2f8cb..ae221f64a13249526cfcf9caf55833347f71a325 100644 --- a/.dockerignore +++ b/.dockerignore @@ -6,6 +6,3 @@ LICENSE README.md node_modules/ .svelte-kit/ -.env* -!.env -.env.local \ No newline at end of file diff --git a/.env b/.env index 67993894d94d47fde852a675f860eed3ff092d9e..46660a651b639c91ed2c729cf6660cfdda02fe41 100644 --- a/.env +++ b/.env @@ -6,42 +6,28 @@ MONGODB_DB_NAME=chat-ui MONGODB_DIRECT_CONNECTION=false COOKIE_NAME=hf-chat -HF_TOKEN=#hf_ from https://huggingface.co/settings/token +HF_ACCESS_TOKEN=#hf_ from 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 '' will be replaced with query keywords see https://docs.searxng.org/dev/search_api.html eg https://searxng.yourdomain.com/search?q=&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": "" + "SCOPES": "" }` # /!\ 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= @@ -54,105 +40,71 @@ 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" : "{{#each messages}}{{#ifUser}}[INST] {{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}}{{content}} [/INST]{{/ifUser}}{{#ifAssistant}}{{content}}{{/ifAssistant}}{{/each}}", - "parameters": { - "temperature": 0.1, - "top_p": 0.95, - "repetition_penalty": 1.2, - "top_k": 50, - "truncate": 3072, - "max_new_tokens": 1024, - "stop": [""] - }, - "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": "OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5", + "datasetName": "OpenAssistant/oasst1", + "description": "A good alternative to ChatGPT", + "websiteUrl": "https://open-assistant.io", + "userMessageToken": "<|prompter|>", + "assistantMessageToken": "<|assistant|>", + "messageEndToken": "", + "preprompt": "Below are a series of dialogues between various people and an AI assistant. The AI tries to be helpful, polite, honest, sophisticated, emotionally aware, and humble-but-knowledgeable. The assistant is happy to help with almost anything, and will do its best to understand exactly what is needed. It also tries to avoid giving false or misleading information, and it caveats when it isn't entirely sure about the right answer. That said, the assistant is practical and really does its best, and doesn't let caution get too much in the way of being useful.\n-----\n", + "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": 0.9, + "top_p": 0.95, + "repetition_penalty": 1.2, + "top_k": 50, + "truncate": 1000, + "max_new_tokens": 1024 } + } ]` - 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. +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" + "title": "Llama v2 is live on HuggingChat! 🦙", + "linkTitle": "Announcement", + "linkHref": "https://huggingface.co/blog/llama2" } ]` -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= -PARQUET_EXPORT_SECRET=#DEPRECATED, use ADMIN_API_SECRET instead - -RATE_LIMIT= # /!\ Legacy definition of messages per minute. Use USAGE_LIMITS.messagesPerMinute instead +RATE_LIMIT= # requests per minute 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 \ No newline at end of file +# PUBLIC_APP_DISCLAIMER=1 \ No newline at end of file diff --git a/.env.template b/.env.template index bcb0cb20ca64f81fffd4ec66ca0fe3a0616314e3..2afe6ed8f4d1e9c21f51a856592f195dc4b097d1 100644 --- a/.env.template +++ b/.env.template @@ -1,121 +1,16 @@ # 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": " {{#each messages}}{{#ifUser}}[INST]{{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}} {{content}} [/INST]{{/ifUser}}{{#ifAssistant}} {{content}} {{/ifAssistant}}{{/each}}", - "parameters" : { - "temperature" : 0.6, - "top_p" : 0.95, - "repetition_penalty" : 1.2, - "top_k" : 50, - "truncate" : 24576, - "max_new_tokens" : 8192, - "stop" : [""] - }, - "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}}", + { + "name": "meta-llama/Llama-2-70b-chat-hf", + "description": "The latest and biggest model from Meta, fine-tuned for chat.", + "websiteUrl": "https://ai.meta.com/llama/", + "userMessageToken": "", + "userMessageEndToken": " [/INST] ", + "assistantMessageToken": "", + "assistantMessageEndToken": " [INST] ", + "preprompt": " ", + "chatPromptTemplate" : "[INST] <>\n{{preprompt}}\n<>\n\n{{#each messages}}{{#ifUser}}{{content}} [/INST] {{/ifUser}}{{#ifAssistant}}{{content}} [INST] {{/ifAssistant}}{{/each}}", "promptExamples": [ { "title": "Write an email from bullet list", @@ -129,63 +24,63 @@ MODELS=`[ } ], "parameters": { - "temperature": 0.7, + "temperature": 0.1, "top_p": 0.95, - "repetition_penalty": 1, + "repetition_penalty": 1.2, "top_k": 50, - "truncate": 24576, - "max_new_tokens": 2048, - "stop": ["<|im_end|>"] + "truncate": 3072, + "max_new_tokens": 1024 } }, - { - "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}}user\n{{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}}{{content}}\nmodel\n{{/ifUser}}{{#ifAssistant}}{{content}}\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" : [""] - } - }, - + { + "name": "codellama/CodeLlama-34b-Instruct-hf", + "displayName": "codellama/CodeLlama-34b-Instruct-hf", + "description": "Code Llama, a state of the art code model from Meta.", + "websiteUrl": "https://about.fb.com/news/2023/08/code-llama-ai-for-coding/", + "userMessageToken": "", + "userMessageEndToken": " [/INST] ", + "assistantMessageToken": "", + "assistantMessageEndToken": " [INST] ", + "preprompt": " ", + "chatPromptTemplate" : "[INST] <>\n{{preprompt}}\n<>\n\n{{#each messages}}{{#ifUser}}{{content}} [/INST] {{/ifUser}}{{#ifAssistant}}{{content}} [INST] {{/ifAssistant}}{{/each}}", + "promptExamples": [ { - "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" : "{{#each messages}}{{#ifUser}}[INST] {{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}}{{content}} [/INST]{{/ifUser}}{{#ifAssistant}}{{content}}{{/ifAssistant}}{{/each}}", + "title": "Fibonacci in Python", + "prompt": "Write a python function to calculate the nth fibonacci number." + }, { + "title": "JavaScript promises", + "prompt": "How can I wait for multiple JavaScript promises to fulfill before doing something with their values?" + }, { + "title": "Rust filesystem", + "prompt": "How can I load a file from disk in Rust?" + } + ], "parameters": { - "temperature": 0.3, + "temperature": 0.1, "top_p": 0.95, "repetition_penalty": 1.2, "top_k": 50, - "truncate": 3072, - "max_new_tokens": 1024, - "stop": [""] + "truncate": 4096, + "max_new_tokens": 4096 + } }, - "promptExamples": [ + { + "name": "tiiuae/falcon-180B-chat", + "displayName": "tiiuae/falcon-180B-chat", + "description": "Falcon-180B is a 180B parameters causal decoder-only model built by TII and trained on 3,500B tokens.", + "websiteUrl": "https://www.tii.ae/news/technology-innovation-institute-introduces-worlds-most-powerful-open-llm-falcon-180b", + "preprompt": " ", + "chatPromptTemplate": "System: {{preprompt}}\nUser:{{#each messages}}{{#ifUser}}{{content}}\nFalcon:{{/ifUser}}{{#ifAssistant}}{{content}}\nUser:{{/ifAssistant}}{{/each}}", + "parameters": { + "temperature": 0.1, + "top_p": 0.95, + "repetition_penalty": 1.2, + "top_k": 50, + "truncate": 1024, + "max_new_tokens": 1024, + "stop": ["User:"] + }, + "promptExamples": [ { "title": "Write an email from bullet list", "prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)" @@ -199,18 +94,20 @@ MODELS=`[ ] }, { - "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/", + "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": "{{preprompt}}{{#each messages}}{{#ifUser}}<|user|>\n{{content}}<|end|>\n<|assistant|>\n{{/ifUser}}{{#ifAssistant}}{{content}}<|end|>\n{{/ifAssistant}}{{/each}}", + "chatPromptTemplate" : "{{#each messages}}{{#ifUser}}[INST] {{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}}{{content}} [/INST]{{/ifUser}}{{#ifAssistant}}{{content}}{{/ifAssistant}}{{/each}}", "parameters": { - "stop": ["<|end|>", "<|endoftext|>", "<|assistant|>"], + "temperature": 0.1, + "top_p": 0.95, + "repetition_penalty": 1.2, + "top_k": 50, + "truncate": 3072, "max_new_tokens": 1024, - "truncate": 3071 + "stop": [""] }, "promptExamples": [ { @@ -225,47 +122,41 @@ MODELS=`[ } ] }, - { - "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/" + { + "name": "openchat/openchat_3.5", + "displayName": "openchat/openchat_3.5", + "description": "OpenChat 3.5 is the #1 model on MT-Bench, with only 7B parameters.", + "websiteUrl": "https://huggingface.co/openchat/openchat_3.5", + "preprompt": "", + "chatPromptTemplate" : "{{#each messages}}{{#ifUser}}GPT4 Correct User: {{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}}{{content}}<|end_of_turn|>GPT4 Correct Assistant:{{/ifUser}}{{#ifAssistant}}{{content}}<|end_of_turn|>{{/ifAssistant}}{{/each}}", + "parameters": { + "temperature": 0.6, + "top_p": 0.95, + "repetition_penalty": 1.2, + "top_k": 50, + "truncate": 6016, + "max_new_tokens": 2048, + "stop": ["<|end_of_turn|>"] + }, + "promptExamples": [ + { + "title": "Write an email from bullet list", + "prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)" + }, { + "title": "Code a snake game", + "prompt": "Code a basic snake game in python, give explanations for each step." + }, { + "title": "Assist in a task", + "prompt": "How do I make a delicious lemon cheesecake?" } ] } ]` +OLD_MODELS=`[{"name":"bigcode/starcoder"}, {"name":"OpenAssistant/oasst-sft-6-llama-30b-xor"}, {"name":"HuggingFaceH4/zephyr-7b-alpha"}]` + +TASK_MODEL='mistralai/Mistral-7B-Instruct-v0.1' + APP_BASE="/chat" PUBLIC_ORIGIN=https://huggingface.co @@ -276,23 +167,14 @@ 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_DATA_SHARING=1 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 +RATE_LIMIT=16 +MESSAGES_BEFORE_LOGIN=5# how many messages a user can send in a conversation before having to login. set to 0 to force login right away -ENABLE_ASSISTANTS=true -ENABLE_ASSISTANTS_RAG=true -REQUIRE_FEATURED_ASSISTANTS=true -EXPOSE_API=true +PUBLIC_GOOGLE_ANALYTICS_ID=G-8Q63TH4CSL -ALTERNATIVE_REDIRECT_URLS=`[ - huggingchat://login/callback -]` - -WEBSEARCH_BLOCKLIST=`["youtube.com", "twitter.com"]` +# Not part of the .env but set as other variables in the space +# ADDRESS_HEADER=X-Forwarded-For +# XFF_DEPTH=2 \ No newline at end of file diff --git a/.eslintrc.cjs b/.eslintrc.cjs index 1590a8c06d47d8ebc8c457d94c309e7e39ba3489..93a488b15bf1c2bb5bc5e9990a9a959e2a8118b9 100644 --- a/.eslintrc.cjs +++ b/.eslintrc.cjs @@ -34,7 +34,6 @@ module.exports = { argsIgnorePattern: "^_", }, ], - "object-shorthand": ["error", "always"], }, env: { browser: true, diff --git a/.github/release.yml b/.github/release.yml deleted file mode 100644 index 3a183679f1aa435bf266e800f343d91ef355eabd..0000000000000000000000000000000000000000 --- a/.github/release.yml +++ /dev/null @@ -1,16 +0,0 @@ -changelog: - exclude: - labels: - - huggingchat - - CI/CD - - documentation - categories: - - title: Features - labels: - - enhancement - - title: Bugfixes - labels: - - bug - - title: Other changes - labels: - - "*" diff --git a/.github/workflows/build-image.yml b/.github/workflows/build-image.yml deleted file mode 100644 index 0238051484f7bf7240aa69bb31fc1e828d2e3c6a..0000000000000000000000000000000000000000 --- a/.github/workflows/build-image.yml +++ /dev/null @@ -1,125 +0,0 @@ -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 diff --git a/.github/workflows/deploy-release.yml b/.github/workflows/deploy-release.yml index a4d0b33ca9c2d583d1a1c09982c33d2f3a9aeb0f..b64cd5afc96d62d9d06214823ffaeb8ad18ef173 100644 --- a/.github/workflows/deploy-release.yml +++ b/.github/workflows/deploy-release.yml @@ -1,6 +1,9 @@ name: Deploy to production on: - # run this workflow manually from the Actions tab + release: + types: [released] + + # to run this workflow manually from the Actions tab workflow_dispatch: jobs: @@ -21,11 +24,7 @@ jobs: 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 }} + HF_ACCESS_TOKEN: ${{ secrets.HF_ACCESS_TOKEN }} run: npm run updateProdEnv sync-to-hub: runs-on: ubuntu-latest @@ -40,5 +39,5 @@ jobs: 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 + HF_TOKEN: ${{ secrets.HF_TOKEN }} + run: git push https://nsarrazin:$HF_TOKEN@huggingface.co/spaces/huggingchat/chat-ui main diff --git a/.github/workflows/deploy-staging.yml b/.github/workflows/deploy-staging.yml index 14da9e54aabac090f153b06ffbca1c2c0a3ced65..a0e6ef18fb3e645ca61ed9539739576d80cd3e0d 100644 --- a/.github/workflows/deploy-staging.yml +++ b/.github/workflows/deploy-staging.yml @@ -20,5 +20,5 @@ jobs: 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 + HF_TOKEN: ${{ secrets.HF_TOKEN }} + run: git push https://nsarrazin:$HF_TOKEN@huggingface.co/spaces/huggingchat/chat-ui-staging main diff --git a/.github/workflows/lint-and-test.yml b/.github/workflows/lint-and-test.yml index 38992d5d5953fa619b571121ac6baa344a54dd74..4cb6a1b0f6b83d3c02980ed9cecb94d37858723c 100644 --- a/.github/workflows/lint-and-test.yml +++ b/.github/workflows/lint-and-test.yml @@ -53,4 +53,4 @@ jobs: steps: - uses: actions/checkout@v3 - name: Build Docker image - run: docker build --secret id=DOTENV_LOCAL,src=.env.ci -t chat-ui:latest . + run: docker build --secret id=DOTENV_LOCAL,src=conf/.env.ci -t chat-ui:latest . diff --git a/.gitignore b/.gitignore index 5621728539ac6a3a14a8e9a34935e44b551c79d4..871dd6c1c4f491665376772517441cf24340410a 100644 --- a/.gitignore +++ b/.gitignore @@ -5,11 +5,10 @@ node_modules /package .env .env.* +!.env.example +!.env.template vite.config.js.timestamp-* vite.config.ts.timestamp-* SECRET_CONFIG .idea -!.env.ci -!.env -!.env.template -gcp-*.json \ No newline at end of file +!conf/.env.ci \ No newline at end of file diff --git a/.vscode/settings.json b/.vscode/settings.json index 0d24922796c50aa3b9c2007e1f04d02ad42174bf..c32c1bbc3ef092e6702bb6ef83bf3fd87308d20b 100644 --- a/.vscode/settings.json +++ b/.vscode/settings.json @@ -2,7 +2,7 @@ "editor.formatOnSave": true, "editor.defaultFormatter": "esbenp.prettier-vscode", "editor.codeActionsOnSave": { - "source.fixAll": "explicit" + "source.fixAll": true }, "eslint.validate": ["javascript", "svelte"] } diff --git a/Dockerfile b/Dockerfile index ca205fbbfb4bad59f38d24611b40d98f30f63cf1..e0d43e3d3ed19a9921602907ba3415184cad598e 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,10 +1,7 @@ # 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 +FROM node:19 as builder-production WORKDIR /app @@ -15,74 +12,21 @@ RUN --mount=type=cache,target=/app/.npm \ 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 +RUN --mount=type=secret,id=DOTENV_LOCAL,dst=.env.local \ + npm run build -# 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/ +FROM node:19-slim -#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 npm install -g pm2 -RUN chmod +x /app/entrypoint.sh +COPY --from=builder-production /app/node_modules /app/node_modules +COPY --link --chown=1000 package.json /app/package.json +COPY --from=builder /app/build /app/build -CMD ["/bin/bash", "-c", "/app/entrypoint.sh"] +CMD pm2 start /app/build/index.js -i $CPU_CORES --no-daemon diff --git a/PRIVACY.md b/PRIVACY.md index c15e2c48ec028800942031d4efa242e2ed295165..234346feed69424298303a0ce6ae6fb0b895c4ec 100644 --- a/PRIVACY.md +++ b/PRIVACY.md @@ -1,12 +1,12 @@ ## Privacy -> Last updated: April 15, 2024 +> Last updated: October 4, 2023 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. +By default, your conversations may be shared with the respective models' authors to improve their training data and model over time. Model authors are the custodians of the data collected by their model, even if it's hosted on our platform. -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. +If you disable data sharing in your settings, your conversations will not be used for any downstream usage (including for research or model training purposes), and they 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 . To exercise any of your legal privacy rights, please send an email to . @@ -14,18 +14,12 @@ You conversation data will only be stored to let you access past conversations. 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: +For now (October 2023), it's running: - [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 diff --git a/PROMPTS.md b/PROMPTS.md index 1847e0dcaa3adc66b1d72eae82a13162ded7717d..25954eaa64f87268988428f76feae0ddb0bd8642 100644 --- a/PROMPTS.md +++ b/PROMPTS.md @@ -43,27 +43,3 @@ System: {{preprompt}}\nUser:{{#each messages}}{{#ifUser}}{{content}}\nFalcon:{{/ ```env {{#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 - {{#each messages}}{{#ifUser}}[INST]{{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}} {{content}} [/INST]{{/ifUser}}{{#ifAssistant}} {{content}} {{/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 -{{#if @root.preprompt}}Source: system\n\n {{@root.preprompt}} {{/if}}{{#each messages}}{{#ifUser}}Source: user\n\n {{content}} {{/ifUser}}{{#ifAssistant}}Source: assistant\n\n {{content}} {{/ifAssistant}}{{/each}}Source: assistant\nDestination: user\n\n `` -``` - -## Gemma - -```env -{{#each messages}}{{#ifUser}}user\n{{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}}{{content}}\nmodel\n{{/ifUser}}{{#ifAssistant}}{{content}}\n{{/ifAssistant}}{{/each}} -``` diff --git a/README.md b/README.md index 9676dd8014c73ef6861ebca68d75becfe0698459..4f0590049f28ff2f07e657eed796ba9fce5dbbc7 100644 --- a/README.md +++ b/README.md @@ -8,8 +8,6 @@ pinned: false license: apache-2.0 base_path: /chat app_port: 3000 -failure_strategy: rollback -load_balancing_strategy: random --- # Chat UI @@ -22,19 +20,17 @@ A chat interface using open source models, eg OpenAssistant or Llama. It is a Sv 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) +4. [Extra parameters](#extra-parameters) +5. [Deploying to a HF Space](#deploying-to-a-hf-space) +6. [Building](#building) -## No Setup Deploy +##  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). +Set `HUGGING_FACE_HUB_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). @@ -46,7 +42,7 @@ Start by creating a `.env.local` file in the root of the repository. The bare mi ```env MONGODB_URL= -HF_TOKEN= +HF_ACCESS_TOKEN= ``` ### Database @@ -82,50 +78,10 @@ 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. +3. Creating embeddings from texts using [transformers.js](https://huggingface.co/docs/transformers.js). Specifically, using [Xenova/gte-small](https://huggingface.co/Xenova/gte-small) 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 @@ -166,9 +122,9 @@ PUBLIC_APP_DISCLAIMER= ### 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 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/)) 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`. +You can also simply enable the local websearch by setting `USE_LOCAL_WEBSEARCH=true` in your `.env.local`. ### Custom models @@ -177,33 +133,36 @@ You can customize the parameters passed to the model or even use a new model by ```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" : "{{#each messages}}{{#ifUser}}[INST] {{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}}{{content}} [/INST]{{/ifUser}}{{#ifAssistant}}{{content}}{{/ifAssistant}}{{/each}}", - "parameters": { - "temperature": 0.3, - "top_p": 0.95, - "repetition_penalty": 1.2, - "top_k": 50, - "truncate": 3072, - "max_new_tokens": 1024, - "stop": [""] - }, + "name": "OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5", + "datasetName": "OpenAssistant/oasst1", + "description": "A good alternative to ChatGPT", + "websiteUrl": "https://open-assistant.io", + "userMessageToken": "<|prompter|>", # This does not need to be a token, can be any string + "assistantMessageToken": "<|assistant|>", # This does not need to be a token, can be any string + "userMessageEndToken": "<|endoftext|>", # Applies only to user messages. Can be any string. + "assistantMessageEndToken": "<|endoftext|>", # Applies only to assistant messages. Can be any string. + "preprompt": "Below are a series of dialogues between various people and an AI assistant. The AI tries to be helpful, polite, honest, sophisticated, emotionally aware, and humble but knowledgeable. The assistant is happy to help with almost anything and will do its best to understand exactly what is needed. It also tries to avoid giving false or misleading information, and it caveats when it isn't entirely sure about the right answer. That said, the assistant is practical and really does its best, and doesn't let caution get too much in the way of being useful.\n-----\n", "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." + "prompt": "Code a basic snake game in python and give explanations for each step." }, { "title": "Assist in a task", "prompt": "How do I make a delicious lemon cheesecake?" } - ] + ], + "parameters": { + "temperature": 0.9, + "top_p": 0.95, + "repetition_penalty": 1.2, + "top_k": 50, + "truncate": 1000, + "max_new_tokens": 1024, + "stop": ["<|endoftext|>"] # This does not need to be tokens, can be any list of strings + } } ]` @@ -228,7 +187,7 @@ The following is the default `chatPromptTemplate`, although newlines and indenti #### 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): +We currently only support IDEFICS as a multimodal model, hosted on TGI. You can enable it by using the followin config (if you have a PRO HF Api token): ```env { @@ -318,78 +277,6 @@ MODELS=`[{ }]` ``` -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. @@ -401,7 +288,7 @@ If you want to run chat-ui with llama.cpp, you can do the following, using Zephy 3. Add the following to your `.env.local`: ```env -MODELS=`[ +MODELS=[ { "name": "Local Zephyr", "chatPromptTemplate": "<|system|>\n{{preprompt}}\n{{#each messages}}{{#ifUser}}<|user|>\n{{content}}\n<|assistant|>\n{{/ifUser}}{{#ifAssistant}}{{content}}\n{{/ifAssistant}}{{/each}}", @@ -421,7 +308,7 @@ MODELS=`[ } ] } -]` +] ``` Start chat-ui with `npm run dev` and you should be able to chat with Zephyr locally. @@ -437,7 +324,7 @@ ollama run mistral Then specify the endpoints like so: ```env -MODELS=`[ +MODELS=[ { "name": "Ollama Mistral", "chatPromptTemplate": "{{#each messages}}{{#ifUser}}[INST] {{#if @first}}{{#if @root.preprompt}}{{@root.preprompt}}\n{{/if}}{{/if}} {{content}} [/INST]{{/ifUser}}{{#ifAssistant}}{{content}} {{/ifAssistant}}{{/each}}", @@ -458,52 +345,7 @@ MODELS=`[ } ] } -]` -``` - -#### 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 @@ -530,120 +372,6 @@ 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" - - } - ] -} -``` - -> [!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", - - } - ] - } -``` - -##### 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 @@ -662,30 +390,28 @@ You can then add the generated information and the `authorization` parameter to ```env "endpoints": [ - { - "url": "https://HOST:PORT", - "authorization": "Basic VVNFUjpQQVNT", - } +{ +"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 - } - ... +{ +"url": "https://HOST:PORT", +"weight": 1 +} +{ +"url": "https://HOST:PORT", +"weight": 2 +} +... ] ``` @@ -697,53 +423,6 @@ If you're using a certificate signed by a private CA, you will also need to add 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. @@ -759,76 +438,3 @@ 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= -HF_TOKEN= -OPENID_CONFIG=`{ - PROVIDER_URL: "https://huggingface.co", - CLIENT_ID: "", - CLIENT_SECRET: "", -}` -SERPER_API_KEY= -MESSAGES_BEFORE_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 -``` - -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. diff --git a/.env.ci b/conf/.env.ci similarity index 100% rename from .env.ci rename to conf/.env.ci diff --git a/entrypoint.sh b/entrypoint.sh deleted file mode 100644 index 3fc46ee53aa072971739b5a251011b6327f53c32..0000000000000000000000000000000000000000 --- a/entrypoint.sh +++ /dev/null @@ -1,19 +0,0 @@ -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 \ No newline at end of file diff --git a/package-lock.json b/package-lock.json index 8a683fc33b3f54b9222ba04a5db987eb79f3f768..c4b957f5a0b05b67cf22862a519a963024ccbf97 100644 --- a/package-lock.json +++ b/package-lock.json @@ -1,99 +1,67 @@ { "name": "chat-ui", - "version": "0.8.3", + "version": "0.6.0", "lockfileVersion": 3, "requires": true, "packages": { "": { "name": "chat-ui", - "version": "0.8.3", + "version": "0.6.0", "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", + "@xenova/transformers": "^2.6.0", "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", + "marked": "^4.3.0", "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", + "tailwindcss": "^3.3.1", "zod": "^3.22.3" }, "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", + "@sveltejs/adapter-node": "^1.2.4", + "@sveltejs/kit": "^1.26.0", "@tailwindcss/typography": "^0.5.9", - "@types/express": "^4.17.21", "@types/jsdom": "^21.1.1", - "@types/minimist": "^1.2.5", + "@types/marked": "^4.0.8", "@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", + "marked-katex-extension": "^3.0.6", "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", + "svelte": "^4.0.0", + "svelte-check": "^3.4.3", "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", + "vite": "^4.3.9", "vitest": "^0.31.0" }, "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" } }, - "node_modules/@alloc/quick-lru": { - "version": "5.2.0", - "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz", - 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}, - "bin": { - "vite-node": "vite-node.mjs" - }, - "engines": { - "node": ">=v14.18.0" - }, - "funding": { - "url": "https://opencollective.com/vitest" - } - }, "node_modules/w3c-xmlserializer": { "version": "4.0.0", "resolved": "https://registry.npmjs.org/w3c-xmlserializer/-/w3c-xmlserializer-4.0.0.tgz", @@ -9623,7 +6669,6 @@ "version": "1.10.2", "resolved": "https://registry.npmjs.org/yaml/-/yaml-1.10.2.tgz", "integrity": "sha512-r3vXyErRCYJ7wg28yvBY5VSoAF8ZvlcW9/BwUzEtUsjvX/DKs24dIkuwjtuprwJJHsbyUbLApepYTR1BN4uHrg==", - "dev": true, "engines": { "node": ">= 6" } @@ -9649,11 +6694,6 @@ "url": "https://github.com/sponsors/sindresorhus" } }, - "node_modules/yoga-wasm-web": { - "version": "0.3.3", - "resolved": "https://registry.npmjs.org/yoga-wasm-web/-/yoga-wasm-web-0.3.3.tgz", - "integrity": "sha512-N+d4UJSJbt/R3wqY7Coqs5pcV0aUj2j9IaQ3rNj9bVCLld8tTGKRa2USARjnvZJWVx1NDmQev8EknoczaOQDOA==" - }, "node_modules/zod": { "version": "3.22.3", "resolved": "https://registry.npmjs.org/zod/-/zod-3.22.3.tgz", diff --git a/package.json b/package.json index ef1d419c0c8766e0377cc25f14f27bf31fb85fc7..c6bbed54cfabb3e709bbafe4e3e78bd4b386b9c7 100644 --- a/package.json +++ b/package.json @@ -1,6 +1,6 @@ { "name": "chat-ui", - "version": "0.8.3", + "version": "0.6.0", "private": true, "packageManager": "npm@9.5.0", "scripts": { @@ -13,83 +13,61 @@ "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" + "updateProdEnv": "node --loader ts-node/esm scripts/updateProdEnv.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", + "@sveltejs/adapter-node": "^1.2.4", + "@sveltejs/kit": "^1.26.0", "@tailwindcss/typography": "^0.5.9", - "@types/express": "^4.17.21", "@types/jsdom": "^21.1.1", - "@types/minimist": "^1.2.5", + "@types/marked": "^4.0.8", "@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", + "marked-katex-extension": "^3.0.6", "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", + "svelte": "^4.0.0", + "svelte-check": "^3.4.3", "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", + "vite": "^4.3.9", "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", + "@xenova/transformers": "^2.6.0", "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", + "marked": "^4.3.0", "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", + "tailwindcss": "^3.3.1", "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" } } diff --git a/scripts/populate.ts b/scripts/populate.ts deleted file mode 100644 index 8e06879a634d7f40010606ff49e3010967efb4b9..0000000000000000000000000000000000000000 --- a/scripts/populate.ts +++ /dev/null @@ -1,269 +0,0 @@ -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 { - 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( - () => ({ - _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({ userId: user._id }); - - const assistantId = - settings?.assistants && settings.assistants.length > 0 && faker.datatype.boolean(0.1) - ? faker.helpers.arrayElement(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); - } -})(); diff --git a/scripts/updateProdEnv.ts b/scripts/updateProdEnv.ts index b66267bbfc3cd18a7397033c5ddfc342f13567c3..8d7e74e25b4718daeb36de6c2d26d2a46f1c6bd6 100644 --- a/scripts/updateProdEnv.ts +++ b/scripts/updateProdEnv.ts @@ -1,15 +1,11 @@ import fs from "fs"; -const HF_DEPLOYMENT_TOKEN = process.env.HF_DEPLOYMENT_TOKEN; // token used for pushing to hub +const HF_TOKEN = process.env.HF_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; +const HF_ACCESS_TOKEN = process.env.HF_ACCESS_TOKEN; // token used for API requests in prod // Read the content of the file .env.template const PUBLIC_CONFIG = fs.readFileSync(".env.template", "utf8"); @@ -19,11 +15,7 @@ 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} +HF_ACCESS_TOKEN=${HF_ACCESS_TOKEN} `; // Make an HTTP POST request to add the space secrets @@ -35,7 +27,7 @@ fetch(`https://huggingface.co/api/spaces/huggingchat/chat-ui/secrets`, { description: `Env variable for HuggingChat. Last updated ${new Date().toISOString()}`, }), headers: { - Authorization: `Bearer ${HF_DEPLOYMENT_TOKEN}`, + Authorization: `Bearer ${HF_TOKEN}`, "Content-Type": "application/json", }, }); diff --git a/src/ambient.d.ts b/src/ambient.d.ts deleted file mode 100644 index 10d56a1ad2da5a0ea32e2180c6aeb04d39290b8c..0000000000000000000000000000000000000000 --- a/src/ambient.d.ts +++ /dev/null @@ -1,4 +0,0 @@ -declare module "*.ttf" { - const value: ArrayBuffer; - export default value; -} diff --git a/src/app.d.ts b/src/app.d.ts index 681fd3654336a2192095c33677be26f4d95436e3..dfd942be68dce05eda0ca563062e867c1230d866 100644 --- a/src/app.d.ts +++ b/src/app.d.ts @@ -12,11 +12,6 @@ declare global { sessionId: string; user?: User; } - - interface Error { - message: string; - errorId?: ReturnType; - } // interface PageData {} // interface Platform {} } diff --git a/src/hooks.server.ts b/src/hooks.server.ts index ff4f044eca4655e1bbeee64916464b437cadbdec..6af0d2366508f96e9cebe766dc0246a5daa1c830 100644 --- a/src/hooks.server.ts +++ b/src/hooks.server.ts @@ -1,73 +1,24 @@ -import { env } from "$env/dynamic/private"; -import { env as envPublic } from "$env/dynamic/public"; -import type { Handle, HandleServerError } from "@sveltejs/kit"; +import { COOKIE_NAME, MESSAGES_BEFORE_LOGIN } from "$env/static/private"; +import type { Handle } from "@sveltejs/kit"; +import { + PUBLIC_GOOGLE_ANALYTICS_ID, + PUBLIC_ORIGIN, + PUBLIC_APP_DISCLAIMER, +} from "$env/static/public"; import { collections } from "$lib/server/database"; import { base } from "$app/paths"; -import { findUser, refreshSessionCookie, requiresUser } from "$lib/server/auth"; +import { 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 ${event.url.pathname} not found`, - }; - } - const errorId = crypto.randomUUID(); - - logger.error({ - locals: event.locals, - url: event.request.url, - params: event.params, - request: event.request, - error, - errorId, - }); +export const handle: Handle = async ({ event, resolve }) => { + const token = event.cookies.get(COOKIE_NAME); - return { - message: "An error occurred", - errorId, - }; -}; + event.locals.sessionId = token || crypto.randomUUID(); -export const handle: Handle = async ({ event, resolve }) => { - logger.debug({ - locals: event.locals, - url: event.url.pathname, - params: event.params, - request: event.request, - }); + const user = await collections.users.findOne({ sessionId: event.locals.sessionId }); - if (event.url.pathname.startsWith(`${base}/api/`) && env.EXPOSE_API !== "true") { - return new Response("API is disabled", { status: 403 }); + if (user) { + event.locals.user = user; } function errorResponse(status: number, message: string) { @@ -82,44 +33,6 @@ export const handle: Handle = async ({ event, resolve }) => { }); } - 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 */ @@ -128,36 +41,21 @@ export const handle: Handle = async ({ event, resolve }) => { "application/x-www-form-urlencoded", "text/plain", ]; + if (event.request.method === "POST" && nativeFormContentTypes.includes(requestContentType)) { + const referer = event.request.headers.get("referer"); - 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 (!referer) { + return errorResponse(403, "Non-JSON form requests need to have a referer"); } - } - if (event.request.method === "POST") { - // if the request is a POST request we refresh the cookie - refreshSessionCookie(event.cookies, secretSessionId); + const validOrigins = [ + new URL(event.request.url).origin, + ...(PUBLIC_ORIGIN ? [new URL(PUBLIC_ORIGIN).origin] : []), + ]; - await collections.sessions.updateOne( - { sessionId }, - { $set: { updatedAt: new Date(), expiresAt: addWeeks(new Date(), 2) } } - ); + if (!validOrigins.includes(new URL(referer).origin)) { + return errorResponse(403, "Invalid referer for POST request"); + } } if ( @@ -166,9 +64,9 @@ export const handle: Handle = async ({ event, resolve }) => { !["GET", "OPTIONS", "HEAD"].includes(event.request.method) ) { if ( - !event.locals.user && + !user && requiresUser && - !((env.MESSAGES_BEFORE_LOGIN ? parseInt(env.MESSAGES_BEFORE_LOGIN) : 0) > 0) + !((MESSAGES_BEFORE_LOGIN ? parseInt(MESSAGES_BEFORE_LOGIN) : 0) > 0) ) { return errorResponse(401, ERROR_MESSAGES.authOnly); } @@ -179,7 +77,7 @@ export const handle: Handle = async ({ event, resolve }) => { if ( !requiresUser && !event.url.pathname.startsWith(`${base}/settings`) && - !!envPublic.PUBLIC_APP_DISCLAIMER + !!PUBLIC_APP_DISCLAIMER ) { const hasAcceptedEthicsModal = await collections.settings.countDocuments({ sessionId: event.locals.sessionId, @@ -192,6 +90,8 @@ export const handle: Handle = async ({ event, resolve }) => { } } + refreshSessionCookie(event.cookies, event.locals.sessionId); + let replaced = false; const response = await resolve(event, { @@ -202,7 +102,7 @@ export const handle: Handle = async ({ event, resolve }) => { } replaced = true; - return chunk.html.replace("%gaId%", envPublic.PUBLIC_GOOGLE_ANALYTICS_ID); + return chunk.html.replace("%gaId%", PUBLIC_GOOGLE_ANALYTICS_ID); }, }); diff --git a/src/lib/actions/clickOutside.ts b/src/lib/actions/clickOutside.ts deleted file mode 100644 index 52e310e22d738d2f221ce1bdb4202ab45e811aba..0000000000000000000000000000000000000000 --- a/src/lib/actions/clickOutside.ts +++ /dev/null @@ -1,18 +0,0 @@ -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); - }, - }; -} diff --git a/src/lib/assistantStats/refresh-assistants-counts.ts b/src/lib/assistantStats/refresh-assistants-counts.ts deleted file mode 100644 index a5bb5f525964b5b0c0779e3f4ef3486adc529d9d..0000000000000000000000000000000000000000 --- a/src/lib/assistantStats/refresh-assistants-counts.ts +++ /dev/null @@ -1,90 +0,0 @@ -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); - }); -} diff --git a/src/lib/buildPrompt.ts b/src/lib/buildPrompt.ts index 00598c101e9006e55c01cfb51d78418da7e78042..15e3a450e6496e4825462dbc99fc6bcadd979944 100644 --- a/src/lib/buildPrompt.ts +++ b/src/lib/buildPrompt.ts @@ -1,33 +1,92 @@ -import type { EndpointParameters } from "./server/endpoints/endpoints"; import type { BackendModel } from "./server/models"; +import type { Message } from "./types/Message"; +import { format } from "date-fns"; +import type { WebSearch } from "./types/WebSearch"; +import { downloadFile } from "./server/files/downloadFile"; +import type { Conversation } from "./types/Conversation"; -type buildPromptOptions = Pick & { +interface buildPromptOptions { + messages: Pick[]; + id?: Conversation["_id"]; model: BackendModel; -}; + locals?: App.Locals; + webSearch?: WebSearch; + preprompt?: string; + files?: File[]; +} export async function buildPrompt({ messages, model, + webSearch, preprompt, - continueMessage, + id, }: buildPromptOptions): Promise { - const filteredMessages = messages.filter((m) => m.from !== "system"); + if (webSearch && webSearch.context) { + const lastMsg = messages.slice(-1)[0]; + const messagesWithoutLastUsrMsg = messages.slice(0, -1); + const previousUserMessages = messages.filter((el) => el.from === "user").slice(0, -1); + + const previousQuestions = + previousUserMessages.length > 0 + ? `Previous questions: \n${previousUserMessages + .map(({ content }) => `- ${content}`) + .join("\n")}` + : ""; + const currentDate = format(new Date(), "MMMM d, yyyy"); + messages = [ + ...messagesWithoutLastUsrMsg, + { + from: "user", + content: `I searched the web using the query: ${webSearch.searchQuery}. Today is ${currentDate} and here are the results: + ===================== + ${webSearch.context} + ===================== + ${previousQuestions} + Answer the question: ${lastMsg.content} + `, + }, + ]; + } + + // section to handle potential files input + if (model.multimodal) { + messages = await Promise.all( + messages.map(async (el) => { + let content = el.content; - let prompt = model - .chatPromptRender({ messages: filteredMessages, preprompt }) - // Not super precise, but it's truncated in the model's backend anyway - .split(" ") - .slice(-(model.parameters?.truncate ?? 0)) - .join(" "); + if (el.from === "user") { + if (el?.files && el.files.length > 0 && id) { + const markdowns = await Promise.all( + el.files.map(async (hash) => { + try { + const { content: image, mime } = await downloadFile(hash, id); + const b64 = image.toString("base64"); + return `![](data:${mime};base64,${b64})})`; + } catch (e) { + console.error(e); + } + }) + ); + content += markdowns.join("\n "); + } else { + // if no image, append an empty white image + content += + "\n![](data:image/png;base64,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)"; + } + } - if (continueMessage && model.parameters?.stop) { - prompt = model.parameters.stop.reduce((acc: string, curr: string) => { - if (acc.endsWith(curr)) { - return acc.slice(0, acc.length - curr.length); - } - return acc; - }, prompt.trimEnd()); + return { ...el, content }; + }) + ); } - return prompt; + return ( + model + .chatPromptRender({ messages, preprompt }) + // Not super precise, but it's truncated in the model's backend anyway + .split(" ") + .slice(-(model.parameters?.truncate ?? 0)) + .join(" ") + ); } diff --git a/src/lib/components/AnnouncementBanner.svelte b/src/lib/components/AnnouncementBanner.svelte index 47ec7b02ef248faab47d38c37dd6260c625886b0..7d6948a6b387ef45104b9b08294ac1e5920e607b 100644 --- a/src/lib/components/AnnouncementBanner.svelte +++ b/src/lib/components/AnnouncementBanner.svelte @@ -5,7 +5,7 @@
New {title} diff --git a/src/lib/components/AssistantSettings.svelte b/src/lib/components/AssistantSettings.svelte deleted file mode 100644 index 370921161766938dbee272a542766fd079bb89a2..0000000000000000000000000000000000000000 --- a/src/lib/components/AssistantSettings.svelte +++ /dev/null @@ -1,593 +0,0 @@ - - -
{ - loading = true; - if (files?.[0] && files[0].size > 0 && compress) { - await compress(files[0], { - maxWidth: 500, - maxHeight: 500, - quality: 1, - }).then((resizedImage) => { - formData.set("avatar", resizedImage); - }); - } - - if (deleteExistingAvatar === true) { - if (assistant?.avatar) { - // if there is an avatar we explicitly removei t - formData.set("avatar", "null"); - } else { - // else we just remove it from the input - formData.delete("avatar"); - } - } else { - if (files === null) { - formData.delete("avatar"); - } - } - - formData.delete("ragMode"); - - if (ragMode === false || !$page.data.enableAssistantsRAG) { - formData.set("ragAllowAll", "false"); - formData.set("ragLinkList", ""); - formData.set("ragDomainList", ""); - } else if (ragMode === "all") { - formData.set("ragAllowAll", "true"); - formData.set("ragLinkList", ""); - formData.set("ragDomainList", ""); - } else if (ragMode === "links") { - formData.set("ragAllowAll", "false"); - formData.set("ragDomainList", ""); - } else if (ragMode === "domains") { - formData.set("ragAllowAll", "false"); - formData.set("ragLinkList", ""); - } - - return async ({ result }) => { - loading = false; - await applyAction(result); - }; - }} -> - {#if assistant} -

- Edit Assistant: {assistant?.name ?? "assistant"} -

-

- Modifying an existing assistant will propagate the changes to all users. -

- {:else} -

Create new assistant

-

- Create and share your own AI Assistant. All assistants are public -

- {/if} - -
-
-
-
Avatar
- - - {#if (files && files[0]) || (assistant?.avatar && !deleteExistingAvatar)} -
- {#if files && files[0]} - avatar - {:else if assistant?.avatar} - avatar - {/if} - - -
-
- -
- {:else} -
- -
- {/if} -

{getError("avatar", form)}

-
- - - -