| image: |
| repository: huggingface |
| name: chat-ui |
|
|
| nodeSelector: |
| role-huggingchat: "true" |
|
|
| tolerations: |
| - key: "huggingface.co/huggingchat" |
| operator: "Equal" |
| value: "true" |
| effect: "NoSchedule" |
|
|
| serviceAccount: |
| enabled: true |
| create: true |
| name: huggingchat-prod |
|
|
| ingress: |
| path: "/chat" |
| annotations: |
| alb.ingress.kubernetes.io/healthcheck-path: "/healthcheck" |
| alb.ingress.kubernetes.io/listen-ports: "[{\"HTTP\": 80}, {\"HTTPS\": 443}]" |
| alb.ingress.kubernetes.io/group.name: "hub-prod" |
| alb.ingress.kubernetes.io/scheme: "internet-facing" |
| alb.ingress.kubernetes.io/ssl-redirect: "443" |
| alb.ingress.kubernetes.io/tags: "Env=prod,Project=hub,Terraform=true" |
| alb.ingress.kubernetes.io/target-node-labels: "role-hub-utils=true" |
| kubernetes.io/ingress.class: "alb" |
|
|
| ingressInternal: |
| enabled: true |
| path: "/chat" |
| annotations: |
| alb.ingress.kubernetes.io/group.name: hub-prod-internal-public |
| alb.ingress.kubernetes.io/healthcheck-path: "/healthcheck" |
| alb.ingress.kubernetes.io/listen-ports: "[{\"HTTP\": 80}, {\"HTTPS\": 443}]" |
| alb.ingress.kubernetes.io/load-balancer-name: hub-prod-internal-public |
| alb.ingress.kubernetes.io/target-group-attributes: deregistration_delay.timeout_seconds=30 |
| alb.ingress.kubernetes.io/target-node-labels: role-hub-lb=true |
| alb.ingress.kubernetes.io/target-type: ip |
| kubernetes.io/ingress.class: "alb" |
|
|
| envVars: |
| ADDRESS_HEADER: 'X-Forwarded-For' |
| ADMIN_CLI_LOGIN: "false" |
| ALTERNATIVE_REDIRECT_URLS: '["huggingchat://login/callback"]' |
| APP_BASE: "/chat" |
| ALLOW_IFRAME: "false" |
| COMMUNITY_TOOLS: "true" |
| COOKIE_SAMESITE: "lax" |
| COOKIE_SECURE: "true" |
| ENABLE_ASSISTANTS: "true" |
| ENABLE_ASSISTANTS_RAG: "true" |
| ENABLE_CONFIG_MANAGER: "false" |
| METRICS_PORT: 5565 |
| LOG_LEVEL: "debug" |
| METRICS_ENABLED: "true" |
| MODELS: > |
| [ |
| { |
| "name": "meta-llama/Llama-3.3-70B-Instruct", |
| "id": "meta-llama/Llama-3.3-70B-Instruct", |
| "description": "Ideal for everyday use. A fast and extremely capable model matching closed source models' capabilities. Now with the latest Llama 3.3 weights!", |
| "modelUrl": "https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct", |
| "websiteUrl": "https://llama.meta.com/", |
| "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/meta-logo.png", |
| "tools": true, |
| "preprompt": "", |
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| "endpoints": [{"type" : "inference-client"}], |
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| { |
| "title": "Write an email", |
| "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 game", |
| "prompt": "Code a basic snake game in python, give explanations for each step." |
| }, |
| { |
| "title": "Recipe help", |
| "prompt": "How do I make a delicious lemon cheesecake?" |
| } |
| ] |
| }, |
| { |
| "name": "Qwen/Qwen3-235B-A22B", |
| "description": "Qwen's flagship model featuring optional reasoning. Exceptional performance with benchmarks rivaling R1 and o1.", |
| "modelUrl": "https://huggingface.co/Qwen/Qwen3-235B-A22B", |
| "websiteUrl": "https://qwenlm.github.io/blog/qwen3/", |
| "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/qwen-logo.png", |
| "preprompt": "You are Qwen, created by Alibaba Cloud. You are a helpful assistant.", |
| "reasoning": { |
| "type": "tokens", |
| "beginToken": "<think>", |
| "endToken": "</think>" |
| }, |
| "parameters": { |
| "stop": ["<|endoftext|>", "<|im_end|>"], |
| "temperature": 0.6, |
| }, |
| "tools": true, |
| "promptExamples": [ |
| { |
| "title": "Write an email", |
| "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) /nothink" |
| }, |
| { |
| "title": "Build a website", |
| "prompt": "Generate a snazzy static landing page for a local coffee shop using HTML and CSS. You can use tailwind using <script src='https://cdn.tailwindcss.com'></script>." |
| }, |
| { |
| "title": "Larger number", |
| "prompt": "9.11 or 9.9 which number is larger?" |
| }, |
| ], |
| "endpoints": [ |
| { |
| "type": "inference-client", |
| "baseURL": "https://api-inference.endpoints.huggingface.tech/models/Qwen/Qwen3-235B-A22B/v1" |
| } |
| ] |
| }, |
| { |
| "name": "Qwen/Qwen2.5-72B-Instruct", |
| "description": "The latest Qwen open model with improved role-playing, long text generation and structured data understanding.", |
| "modelUrl": "https://huggingface.co/Qwen/Qwen2.5-72B-Instruct", |
| "websiteUrl": "https://qwenlm.github.io/blog/qwen2.5/", |
| "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/qwen-logo.png", |
| "preprompt": "You are Qwen, created by Alibaba Cloud. You are a helpful assistant.", |
| "parameters": { |
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| "temperature": 0.6, |
| "truncate": 28672, |
| "max_new_tokens": 3072 |
| }, |
| "tools": true, |
| "endpoints": [{"type" : "inference-client"}], |
| "promptExamples": [ |
| { |
| "title": "Write an email", |
| "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 game", |
| "prompt": "Code a basic snake game in python, give explanations for each step." |
| }, |
| { |
| "title": "Recipe help", |
| "prompt": "How do I make a delicious lemon cheesecake?" |
| } |
| ] |
| }, |
| { |
| "name": "CohereLabs/c4ai-command-r-plus-08-2024", |
| "description": "Cohere's largest language model, optimized for conversational interaction and tool use. Now with the 2024 update!", |
| "modelUrl": "https://huggingface.co/CohereLabs/c4ai-command-r-plus-08-2024", |
| "websiteUrl": "https://docs.cohere.com/docs/command-r-plus", |
| "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/cohere-logo.png", |
| "tools": true, |
| "systemRoleSupported": false, |
| "parameters": { |
| "stop": ["<|END_OF_TURN_TOKEN|>", "<|im_end|>"], |
| "truncate": 28672, |
| "max_new_tokens": 2048, |
| "temperature": 0.3 |
| }, |
| "endpoints": [{"type" : "inference-client"}], |
| "promptExamples": [ |
| { |
| "title": "Generate image", |
| "prompt": "Generate the portrait of a scientific mouse in its laboratory." |
| }, |
| { |
| "title": "Review code", |
| "prompt": "Review this pull request: https://github.com/huggingface/chat-ui/pull/1131/files" |
| }, |
| { |
| "title": "Code a game", |
| "prompt": "Code a basic snake game in python, give explanations for each step." |
| } |
| ] |
| }, |
| { |
| "name": "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B", |
| "modelUrl": "https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B", |
| "websiteUrl": "https://deepseek.com/", |
| "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/deepseek-logo.png", |
| "description": "The first reasoning model from DeepSeek, distilled into a 32B dense model. Outperforms o1-mini on multiple benchmarks.", |
| "reasoning": { |
| "type": "tokens", |
| "beginToken": "", |
| "endToken": "</think>" |
| }, |
| "tools": true, |
| "promptExamples": [ |
| { |
| "title": "Rs in strawberry", |
| "prompt": "how many R in strawberry?" |
| }, |
| { |
| "title": "Larger number", |
| "prompt": "9.11 or 9.9 which number is larger?" |
| }, |
| { |
| "title": "Measuring 6 liters", |
| "prompt": "I have a 6- and a 12-liter jug. I want to measure exactly 6 liters." |
| } |
| ], |
| "endpoints": [ |
| { |
| "type": "inference-client", |
| "baseURL": "https://b8xf586h164t4vk7.us-east-1.aws.endpoints.huggingface.cloud/v1" |
| } |
| ] |
| }, |
| { |
| "name": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF", |
| "modelUrl": "https://huggingface.co/nvidia/Llama-3.1-Nemotron-70B-Instruct-HF", |
| "websiteUrl": "https://www.nvidia.com/", |
| "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/nvidia-logo.png", |
| "description": "Nvidia's latest Llama fine-tune, topping alignment benchmarks and optimized for instruction following.", |
| "parameters": { |
| "stop": ["<|eot_id|>", "<|im_end|>"], |
| "temperature": 0.5, |
| "truncate": 28672, |
| "max_new_tokens": 2048 |
| }, |
| "promptExamples": [ |
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| "title": "Rs in strawberry", |
| "prompt": "how many R in strawberry?" |
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| "title": "Larger number", |
| "prompt": "9.11 or 9.9 which number is larger?" |
| }, |
| { |
| "title": "Measuring 6 liters", |
| "prompt": "I have a 6- and a 12-liter jug. I want to measure exactly 6 liters." |
| } |
| ], |
| "endpoints": [ |
| { |
| "type": "inference-client", |
| "baseURL": "https://api-inference.endpoints.huggingface.tech/models/nvidia/Llama-3.1-Nemotron-70B-Instruct-HF/v1" |
| } |
| ] |
| }, |
| { |
| "name": "Qwen/QwQ-32B", |
| "tools": true, |
| "preprompt": "You are a helpful and harmless assistant. You are Qwen developed by Alibaba. You should think step-by-step.", |
| "modelUrl": "https://huggingface.co/Qwen/QwQ-32B", |
| "websiteUrl": "https://qwenlm.github.io/blog/qwq-32b/", |
| "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/qwen-logo.png", |
| "description": "QwQ is the latest reasoning model released by the Qwen team, approaching the capabilities of R1 in benchmarks.", |
| "reasoning": { |
| "type": "tokens", |
| "beginToken": "", |
| "endToken": "</think>" |
| }, |
| "promptExamples": [ |
| { |
| "title": "Rs in strawberry", |
| "prompt": "how many R in strawberry?" |
| }, |
| { |
| "title": "Larger number", |
| "prompt": "9.11 or 9.9 which number is larger?" |
| }, |
| { |
| "title": "Measuring 6 liters", |
| "prompt": "I have a 6- and a 12-liter jug. I want to measure exactly 6 liters." |
| } |
| ], |
| "endpoints": [ |
| { |
| "type": "inference-client", |
| } |
| ] |
| }, |
| { |
| "name": "google/gemma-3-27b-it", |
| "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/google-logo.png", |
| "multimodal": true, |
| "tools": true, |
| "systemRoleSupported" : false, |
| "description": "Google's latest open model with great multilingual performance, supports image inputs natively.", |
| "websiteUrl": "https://blog.google/technology/developers/gemma-3/", |
| "promptExamples": [ |
| { |
| "title": "Write an email", |
| "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 game", |
| "prompt": "Code a basic snake game in python, give explanations for each step." |
| }, |
| { |
| "title": "Recipe help", |
| "prompt": "How do I make a delicious lemon cheesecake?" |
| } |
| ], |
| "endpoints": [ |
| { |
| "type": "inference-client", |
| "baseURL": "https://wp0d3hn6s3k8jk22.us-east-1.aws.endpoints.huggingface.cloud/v1", |
| "multimodal": { |
| "image": { |
| "maxSizeInMB": 10, |
| "maxWidth": 560, |
| "maxHeight": 560, |
| "supportedMimeTypes": ["image/jpeg", "image/png", "image/webp"], |
| "preferredMimeType": "image/webp" |
| } |
| } |
| } |
| ] |
| }, |
| { |
| "name": "mistralai/Mistral-Small-3.1-24B-Instruct-2503", |
| "tools": true, |
| "displayName": "mistralai/Mistral-Small-3.1-24B-Instruct-2503", |
| "description": "A small model with good capabilities in language understanding and commonsense reasoning.", |
| "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/mistral-logo.png", |
| "websiteUrl": "https://mistral.ai/news/mistral-nemo/", |
| "modelUrl": "https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503", |
| "preprompt": "", |
| "promptExamples": [ |
| { |
| "title": "Write an email", |
| "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 game", |
| "prompt": "Code a basic snake game in python, give explanations for each step." |
| }, |
| { |
| "title": "Recipe help", |
| "prompt": "How do I make a delicious lemon cheesecake?" |
| } |
| ], |
| |
| "endpoints": [ |
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| } |
| ] |
| }, |
| { |
| "name": "Qwen/Qwen2.5-VL-32B-Instruct", |
| "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/qwen-logo.png", |
| "description": "The latest multimodal model from Qwen! Supports image inputs natively.", |
| "websiteUrl": "https://qwenlm.github.io/blog/qwen2.5-vl/", |
| "modelUrl": "https://huggingface.co/Qwen/Qwen2.5-VL-32B-Instruct", |
| "multimodal": true, |
| "promptExamples": [ |
| { |
| "title": "Write an email", |
| "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 game", |
| "prompt": "Code a basic snake game in python, give explanations for each step." |
| }, |
| { |
| "title": "Recipe help", |
| "prompt": "How do I make a delicious lemon cheesecake?" |
| } |
| ], |
| "endpoints": [ |
| { |
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| "maxSizeInMB": 10, |
| "maxWidth": 1024, |
| "maxHeight": 1024, |
| "supportedMimeTypes": ["image/png", "image/jpeg", "image/webp"], |
| "preferredMimeType": "image/webp" |
| } |
| } |
| } |
| ] |
| }, |
| { |
| "name": "microsoft/Phi-4", |
| "tools": true, |
| "systemRoleSupported": false, |
| "description": "One of the best small models, super fast for simple tasks.", |
| "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/microsoft-logo.png", |
| "modelUrl": "https://huggingface.co/microsoft/Phi-4", |
| "websiteUrl": "https://techcommunity.microsoft.com/blog/aiplatformblog/introducing-phi-4-microsoft%E2%80%99s-newest-small-language-model-specializing-in-comple/4357090", |
| "preprompt": "", |
| "parameters": { |
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| "temperature": 0.6, |
| "truncate": 28672, |
| "max_new_tokens": 3072 |
| }, |
| "promptExamples": [ |
| { |
| "title": "Write an email", |
| "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 game", |
| "prompt": "Code a basic snake game in python, give explanations for each step." |
| }, |
| { |
| "title": "Recipe help", |
| "prompt": "How do I make a delicious lemon cheesecake?" |
| } |
| ], |
| "endpoints": [ |
| { |
| "type": "inference-client", |
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| } |
| ] |
| }, |
| { |
| "name": "NousResearch/Hermes-3-Llama-3.1-8B", |
| "description": "Nous Research's latest Hermes 3 release in 8B size. Follows instruction closely.", |
| "tools": true, |
| "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/nous-logo.png", |
| "websiteUrl": "https://nousresearch.com/", |
| "modelUrl": "https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B", |
| "promptExamples": [ |
| { |
| "title": "Write an email", |
| "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 game", |
| "prompt": "Code a basic snake game in python, give explanations for each step." |
| }, |
| { |
| "title": "Recipe help", |
| "prompt": "How do I make a delicious lemon cheesecake?" |
| } |
| ], |
| "parameters": { |
| "stop": ["<|im_end|>"], |
| "temperature": 0.6, |
| "truncate": 14336, |
| "max_new_tokens": 1536 |
| }, |
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| } |
| ] |
|
|
| NODE_ENV: "prod" |
| NODE_LOG_STRUCTURED_DATA: 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" }, |
| { "name": "meta-llama/Meta-Llama-3-70B-Instruct" }, |
| { "name": "meta-llama/Meta-Llama-3.1-405B-Instruct-FP8" }, |
| { |
| "name": "CohereForAI/c4ai-command-r-plus-08-2024", |
| "transferTo": "CohereLabs/c4ai-command-r-plus-08-2024" |
| }, |
| { |
| "name": "CohereForAI/c4ai-command-r-plus", |
| "transferTo": "CohereLabs/c4ai-command-r-plus-08-2024" |
| }, |
| { |
| "name": "01-ai/Yi-1.5-34B-Chat", |
| "transferTo": "CohereLabs/c4ai-command-r-plus-08-2024" |
| }, |
| { |
| "name": "mistralai/Mixtral-8x7B-Instruct-v0.1", |
| "transferTo": "mistralai/Mistral-Small-3.1-24B-Instruct-2503" |
| }, |
| { |
| "name": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", |
| "transferTo": "NousResearch/Hermes-3-Llama-3.1-8B" |
| }, |
| { |
| "name": "mistralai/Mistral-7B-Instruct-v0.3", |
| "transferTo": "mistralai/Mistral-Small-3.1-24B-Instruct-2503" |
| }, |
| { |
| "name": "microsoft/Phi-3-mini-4k-instruct", |
| "transferTo": "microsoft/Phi-4" |
| }, |
| { |
| "name": "meta-llama/Meta-Llama-3.1-70B-Instruct", |
| "transferTo": "meta-llama/Llama-3.3-70B-Instruct" |
| }, |
| { |
| "name": "Qwen/QwQ-32B-Preview", |
| "transferTo": "Qwen/QwQ-32B" |
| }, |
| { |
| "name": "mistralai/Mistral-Nemo-Instruct-2407", |
| "transferTo": "mistralai/Mistral-Small-3.1-24B-Instruct-2503" |
| }, |
| { |
| "name": "microsoft/Phi-3.5-mini-instruct", |
| "transferTo": "microsoft/Phi-4" |
| }, |
| { |
| "name": "Qwen/Qwen2.5-Coder-32B-Instruct", |
| "transferTo": "Qwen/QwQ-32B" |
| }, |
| { |
| "name": "meta-llama/Llama-3.2-11B-Vision-Instruct", |
| "transferTo" : "Qwen/Qwen2.5-VL-32B-Instruct" |
| } |
| ] |
| PUBLIC_ORIGIN: "https://huggingface.co" |
| PUBLIC_SHARE_PREFIX: "https://hf.co/chat" |
| PUBLIC_ANNOUNCEMENT_BANNERS: > |
| [ |
| { |
| "title": "Qwen 3 235B is available!", |
| "linkTitle": "Try it out!", |
| "linkHref": "https://huggingface.co/chat/models/Qwen/Qwen3-235B-A22B" |
| } |
| ] |
| 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_GUEST_MESSAGE: "Sign in with a free Hugging Face account to continue using HuggingChat." |
| PUBLIC_APP_DATA_SHARING: 0 |
| PUBLIC_APP_DISCLAIMER: 1 |
| PUBLIC_PLAUSIBLE_SCRIPT_URL: "/js/script.js" |
| REQUIRE_FEATURED_ASSISTANTS: "true" |
| TASK_MODEL: > |
| { |
| "name": "NousResearch/Hermes-3-Llama-3.1-8B", |
| "unlisted": true, |
| "endpoints": [{"type" : "inference-client"}], |
| "parameters": { |
| "temperature": 0.1, |
| "max_new_tokens": 256 |
| } |
| } |
| |
|
|
| 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/" |
| }] |
| }] |
| WEBSEARCH_BLOCKLIST: '["youtube.com", "twitter.com"]' |
| XFF_DEPTH: '2' |
| TOOLS: > |
| [ |
| { |
| "_id": "000000000000000000000001", |
| "displayName": "Image Generation", |
| "description": "Use this tool to generate images based on a prompt.", |
| "color": "yellow", |
| "icon": "camera", |
| "baseUrl": "black-forest-labs/FLUX.1-schnell", |
| "name": "image_generation", |
| "endpoint": "/infer", |
| "inputs": [ |
| { |
| "name": "prompt", |
| "description": "A prompt to generate an image from", |
| "paramType": "required", |
| "type": "str" |
| }, |
| { "name": "seed", "paramType": "fixed", "value": "0", "type": "float" }, |
| { |
| "name": "randomize_seed", |
| "paramType": "fixed", |
| "value": "true", |
| "type": "bool" |
| }, |
| { |
| "name": "width", |
| "description": "numeric value between 256 and 2048", |
| "paramType": "optional", |
| "default": 1024, |
| "type": "float" |
| }, |
| { |
| "name": "height", |
| "description": "numeric value between 256 and 2048", |
| "paramType": "optional", |
| "default": 1024, |
| "type": "float" |
| }, |
| { |
| "name": "num_inference_steps", |
| "paramType": "fixed", |
| "value": "4", |
| "type": "float" |
| } |
| ], |
| "outputComponent": "image", |
| "outputComponentIdx": 0, |
| "showOutput": true |
| }, |
| { |
| "_id": "000000000000000000000002", |
| "displayName": "Document Parser", |
| "description": "Use this tool to parse any document and get its content in markdown format.", |
| "color": "yellow", |
| "icon": "cloud", |
| "baseUrl": "huggingchat/document-parser", |
| "name": "document_parser", |
| "endpoint": "/predict", |
| "inputs": [ |
| { |
| "name": "document", |
| "description": "Filename of the document to parse", |
| "paramType": "required", |
| "type": "file", |
| "mimeTypes": 'application/*' |
| }, |
| { |
| "name": "filename", |
| "paramType": "fixed", |
| "value": "document.pdf", |
| "type": "str" |
| } |
| ], |
| "outputComponent": "textbox", |
| "outputComponentIdx": 0, |
| "showOutput": false, |
| "isHidden": true |
| }, |
| { |
| "_id": "000000000000000000000003", |
| "name": "edit_image", |
| "baseUrl": "multimodalart/cosxl", |
| "endpoint": "/run_edit", |
| "inputs": [ |
| { |
| "name": "image", |
| "description": "The image path to be edited", |
| "paramType": "required", |
| "type": "file", |
| "mimeTypes": 'image/*' |
| }, |
| { |
| "name": "prompt", |
| "description": "The prompt with which to edit the image", |
| "paramType": "required", |
| "type": "str" |
| }, |
| { |
| "name": "negative_prompt", |
| "paramType": "fixed", |
| "value": "", |
| "type": "str" |
| }, |
| { |
| "name": "guidance_scale", |
| "paramType": "fixed", |
| "value": 6.5, |
| "type": "float" |
| }, |
| { |
| "name": "steps", |
| "paramType": "fixed", |
| "value": 30, |
| "type": "float" |
| } |
| ], |
| "outputComponent": "image", |
| "showOutput": true, |
| "displayName": "Image Editor", |
| "color": "green", |
| "icon": "camera", |
| "description": "This tool lets you edit images", |
| "outputComponentIdx": 0 |
| } |
| ] |
| HF_ORG_ADMIN: '644171cfbd0c97265298aa99' |
| HF_ORG_EARLY_ACCESS: '5e67bd5b1009063689407478' |
| HF_API_ROOT: 'https://api-inference.endpoints.huggingface.tech/models' |
| infisical: |
| enabled: true |
| env: "prod-us-east-1" |
|
|
| autoscaling: |
| enabled: true |
| minReplicas: 12 |
| maxReplicas: 30 |
| targetMemoryUtilizationPercentage: "50" |
| targetCPUUtilizationPercentage: "50" |
|
|
| resources: |
| requests: |
| cpu: 2 |
| memory: 4Gi |
| limits: |
| cpu: 4 |
| memory: 8Gi |
|
|
| monitoring: |
| enabled: true |
|
|
