-
-
- {t("community:title", { defaultValue: "Built and extended by the community" })}
+
- {t("community:title", { defaultValue: "Built and extended by the community" })}
+
+ {/* Head */}
+
+
+
+
+ [ 05 ] {lang === "es" ? "Comunidad" : "Community"}
+
+
+
+
+ {lang === "es"
+ ? <>Construyamos esto juntos.
+ : <>Let's build this together.}
-
- {t("community:description", {
- defaultValue:
- "DashAI's plugin architecture enables anyone to contribute new capabilities. Build plugins, improve the core, and shape the future of open source AI tools.",
- })}
+
+ {lang === "es"
+ ? "dashAI es código abierto y comunidad abierta. Únete a la conversación, propone componentes, comparte experimentos."
+ : "dashAI is open source and open community. Join the conversation, propose components, share experiments."}
+
-
- {communityLinks.map((item, index) => {
- const Icon = item.icon
- const title = t(`community:cards.${item.key}.title`, {
- defaultValue: item.defaultTitle,
- })
- const description = t(`community:cards.${item.key}.description`, {
- defaultValue: item.defaultDescription,
- })
- return (
- window.open(item.link, "_blank", "noopener,noreferrer")}
- >
-
-
- {title}
- {description}
- {item.stats}
-
-
- )
- })}
+ {/* Cards */}
+
+ {/* Contact */}
+
+
+
+
+
+ {lang === "es" ? "Contacto" : "Contact"}
+
+
+ {lang === "es" ? "Escribinos directamente." : "Reach out directly."}
+
+
+ {lang === "es"
+ ? "Consultas, colaboraciones, integraciones institucionales o simplemente para contar qué estás construyendo con dashAI."
+ : "Questions, collaborations, institutional integrations, or just to share what you're building with dashAI."}
+
+
+ dashai.nocode@gmail.com →
+
- {/*
-
- {"Ready to build your first plugin?"}
-
- {
- "Our comprehensive documentation guides you through creating plugins and contributing to the core platform"
- }
-
-
-
-
+ {/* Discord */}
+
+
+
+
+
+ Discord
+
+
+ {lang === "es" ? "Súmate al servidor de Discord." : "Join the Discord server."}
+
+
+ {lang === "es"
+ ? "Soporte en vivo, anuncios de release, hilos por módulo (Datasets, Modelos, Generativo, Plugins) y el canal #show-and-tell para que compartas tus experimentos."
+ : "Live support, release announcements, threads per module (Datasets, Models, Generative, Plugins) and a #show-and-tell channel to share your experiments."}
+
+ { (e.currentTarget as HTMLElement).style.opacity = "0.85" }}
+ onMouseLeave={e => { (e.currentTarget as HTMLElement).style.opacity = "1" }}
+ >
+ {lang === "es" ? "Unirme al Discord" : "Join Discord"} →
+
+
+
+ {/* Newsletter */}
+
+
+
+
+
+ Newsletter
+
+
+ {lang === "es" ? "Una actualización mensual." : "One monthly digest."}
+
+
+ {lang === "es"
+ ? "Nuevas features, modelos agregados al catálogo, plugins de la comunidad, papers relevantes. Sin spam, sin promos — solo lo que importa para tu workflow."
+ : "New features, models added to the catalog, community plugins, relevant papers. No spam, no promos — just what matters for your workflow."}
+
+ {subscribed ? (
+
+ ✓ {lang === "es" ? "¡Suscripto!" : "Subscribed!"}
-
- */}
+ ) : (
+
+ )}
+
+ {lang === "es"
+ ? "· Cancela cuando quieras · 0 emails comerciales"
+ : "· Unsubscribe anytime · 0 commercial emails"}
+
+
)
diff --git a/components/download-section.tsx b/components/download-section.tsx
index 5f9127c..020f36c 100644
--- a/components/download-section.tsx
+++ b/components/download-section.tsx
@@ -1,178 +1,230 @@
"use client"
-import { Button } from "@/components/ui/button"
-import { Card, CardContent } from "@/components/ui/card"
-import { Download, Package } from "lucide-react"
import { useEffect, useState } from "react"
import { useTranslation } from "react-i18next"
import { findAsset, formatBytes, getLatestRelease } from "@/lib/github"
+import { siteConfig } from "@/lib/config"
const SOURCEFORGE_URL = "https://sourceforge.net/projects/dashai/files/latest/download"
+const TRACKER_URL = process.env.NEXT_PUBLIC_TRACKER_URL
-type DownloadEntry = {
- id: "mac_intel" | "mac_arm" | "windows"
- icon: typeof Package
- key: string
- defaultPlatform: string
- version: string
- size: string
- defaultFormat: string
- link: string
+async function trackClick(buttonId: string) {
+ if (!TRACKER_URL) return
+ try { await fetch(`${TRACKER_URL}/click/${buttonId}`, { method: "POST" }) } catch {}
}
-const FALLBACK_DOWNLOADS: DownloadEntry[] = [
- {
- id: "mac_intel",
- icon: Package,
- key: "macIntel",
- defaultPlatform: "macOS Intel processors",
- version: "",
- size: "",
- defaultFormat: ".dmg",
- link: SOURCEFORGE_URL,
- },
- {
- id: "mac_arm",
- icon: Package,
- key: "macArm",
- defaultPlatform: "macOS ARM processors",
- version: "",
- size: "",
- defaultFormat: ".dmg",
- link: SOURCEFORGE_URL,
- },
- {
- id: "windows",
- icon: Package,
- key: "windows",
- defaultPlatform: "Windows",
- version: "",
- size: "",
- defaultFormat: ".exe",
- link: SOURCEFORGE_URL,
- },
-]
+type ExeEntry = { id: "mac_intel" | "mac_arm" | "windows"; os: string; ext: string; link: string; version: string; size: string }
-const TRACKER_URL = process.env.NEXT_PUBLIC_TRACKER_URL
+const FALLBACK: ExeEntry[] = [
+ { id: "windows", os: "Windows", ext: ".exe", link: SOURCEFORGE_URL, version: "", size: "" },
+ { id: "mac_arm", os: "macOS (ARM)", ext: ".dmg", link: SOURCEFORGE_URL, version: "", size: "" },
+ { id: "mac_intel",os: "macOS (Intel)", ext: ".dmg",link: SOURCEFORGE_URL, version: "", size: "" },
+]
-async function trackClick(buttonId: string) {
- if (!TRACKER_URL) return
- try {
- await fetch(`${TRACKER_URL}/click/${buttonId}`, {
- method: "POST",
- })
- } catch {
- // non-blocking — don't let tracking errors affect the download
+function CopyButton({ text }: { text: string }) {
+ const [copied, setCopied] = useState(false)
+ const copy = () => {
+ navigator.clipboard.writeText(text).catch(() => {})
+ setCopied(true)
+ setTimeout(() => setCopied(false), 1400)
}
+ return (
+
+ )
}
export function DownloadSection() {
- const { t } = useTranslation()
- const [downloads, setDownloads] = useState(FALLBACK_DOWNLOADS)
+ const { i18n } = useTranslation()
+ const lang = i18n.language?.startsWith("es") ? "es" : "en"
+ const [exes, setExes] = useState(FALLBACK)
+ const [releaseTag, setReleaseTag] = useState("v0.9.3-alpha")
useEffect(() => {
- getLatestRelease().then((release) => {
+ getLatestRelease().then(release => {
if (!release) return
- setDownloads(
- FALLBACK_DOWNLOADS.map((entry) => {
- const asset = findAsset(release.assets, entry.id)
- if (!asset) return entry
- return {
- ...entry,
- version: release.tag_name,
- size: formatBytes(asset.size),
- link: asset.browser_download_url,
- }
- })
- )
+ setReleaseTag(release.tag_name)
+ setExes(FALLBACK.map(entry => {
+ const asset = findAsset(release.assets, entry.id)
+ if (!asset) return entry
+ return { ...entry, version: release.tag_name, size: formatBytes(asset.size), link: asset.browser_download_url }
+ }))
})
}, [])
+ const pipCmd = "pip install dashai\ndashai"
+
return (
-
-
-
-
- {t("download:title", { defaultValue: "Download DashAI" })}
+
+ {/* Horizontal line pattern */}
+
+
+ {/* Head */}
+
+
+
+
+ [ 04 ] {lang === "es" ? "Descarga" : "Download"}
+
+
+
+
+ {lang === "es" ? <>Descargá dashAI. : <>Download dashAI.}
-
- {t("download:badge", { defaultValue: "Beta Version" })}
-
-
- {t("download:description", {
- defaultValue:
- "This early version lets you explore DashAI's main features. We appreciate your feedback to help us improve before the official release.",
- })}
+
+ {releaseTag}
+ ·MIT License
+ ·Linux · macOS · Windows
+ ·{lang === "es" ? "Mayo 2026" : "May 2026"}
+
+
+
+
+ {/* 3-col grid */}
+
+ {/* Card 1 — executables */}
+
+
+ 01
+ {lang === "es" ? "Ejecutables (recomendado)" : "Executables (recommended)"}
+
+ {lang === "es" ? "Instalador nativo" : "Native installer"}
+
+ {lang === "es"
+ ? "Sin Python ni configuración. Descargá el ejecutable de tu sistema operativo desde GitHub Releases."
+ : "No Python, no setup. Download the executable for your OS from GitHub Releases."}
+
+
+
+ {lang === "es" ? "Ver releases" : "View releases"} →
+
+
+
+ {/* Card 2 — pip */}
+
+
+ 02
+ PyPI
+
+ {lang === "es" ? "Instalación con pip" : "Install with pip"}
+
+ {lang === "es"
+ ? <>dashai levanta el servidor y abre el navegador en localhost:8000.
+ : <>dashai starts the server and opens the browser at localhost:8000.}
+
+
-
-
- {platform}
-
- {download.version && (
-
- {download.version} • {download.size}
-
- )}
- {format}
-
-
-
-
- )
- })}
+ {/* Card 3 — requirements */}
+
+
+ ⊳
+ {lang === "es" ? "Requisitos" : "Requirements"}
+ {lang === "es" ? "Lo que necesitás" : "What you need"}
+
+ {[
+ { k: "Python", v: "≥ 3.10", note: lang === "es" ? "Solo para instalación pip" : "Only for pip install" },
+ { k: "RAM", v: "8 GB", note: lang === "es" ? "16 GB para LLMs locales" : "16 GB for local LLMs" },
+ { k: "OS", v: "Linux · macOS · Windows", note: lang === "es" ? "Ejecutables nativos disponibles" : "Native executables available" },
+ ].map(r => (
+ -
+ {r.k}
+
+ {r.v}
+ {r.note}
+
+
+ ))}
+
+
+
-
-
-
-
-
- {t("download:pip.title", { defaultValue: "Install via pip" })}
-
-
- {t("download:pip.subtitle", {
- defaultValue: "For developers who prefer command-line installation",
- })}
-
-
-
-
-
- {t("download:pip.command", { defaultValue: "pip install dashai" })}
-
-
-
-
-
-
+ {/* Footer row */}
+
+
+ {lang === "es" ? "¿Querés modificar el núcleo? Cloná el repo:" : "Want to modify the core? Clone the repo:"}
+
+ git clone github.com/DashAISoftware/DashAI
+
+
+
diff --git a/components/extensible-section.tsx b/components/extensible-section.tsx
new file mode 100644
index 0000000..a2b948b
--- /dev/null
+++ b/components/extensible-section.tsx
@@ -0,0 +1,181 @@
+"use client"
+
+import { useTranslation } from "react-i18next"
+
+const PAPER = "#FEFEFF"
+const PAPER_LINE = "#E3E2DF"
+const ON_LIGHT = "#191817"
+const ON_LIGHT_MUTE = "#4A4744"
+const ON_LIGHT_FAINT = "#6C685F"
+const PLUGINS_COLOR = "#1E63D8"
+const BRAND_ON_LIGHT = "#1E63D8"
+const CODE_BG = "#131211"
+const CODE_HEADER_BG = "#191817"
+const CODE_BORDER = "#2E2C29"
+
+const MODULES = [
+ { num: "01", name: "BaseTask", role: { es: "Tarea", en: "Task" }, desc: { es: "Paradigmas extensibles: clasificación, regresión, NLP, traducción, generación.", en: "Extensible paradigms: classification, regression, NLP, translation, generation." } },
+ { num: "02", name: "BaseModel", role: { es: "Modelo predictivo", en: "Predictive model"}, desc: { es: "Random Forest a transformers. Subclase + schema, listo para HPO.", en: "Random Forest to transformers. Subclass + schema, ready for HPO." } },
+ { num: "03", name: "BaseGenerativeModel", role: { es: "Modelo generativo", en: "Generative model"}, desc: { es: "LLMs e imagen como ciudadanos de primera clase.", en: "LLMs and image as first-class citizens." } },
+ { num: "04", name: "BaseMetric", role: { es: "Métrica", en: "Metric" }, desc: { es: "Classification, Regression, Translation. Aparece sola en la UI.", en: "Classification, Regression, Translation. Auto-appears in UI." } },
+ { num: "05", name: "BaseOptimizer", role: { es: "Optimización HPO", en: "HPO optimizer" }, desc: { es: "Optuna + HyperOpt. Estrategias bayesianas, evolutivas, QMC.", en: "Optuna + HyperOpt. Bayesian, evolutionary, QMC strategies." } },
+ { num: "06", name: "BaseDataLoader", role: { es: "Carga de datos", en: "Data loader" }, desc: { es: "CSV, JSON, imágenes, audio. Cada loader declara su formato.", en: "CSV, JSON, images, audio. Each loader declares its format." } },
+ { num: "07", name: "BaseExplorer", role: { es: "EDA / exploración", en: "EDA / exploration"}, desc: { es: "Visualizaciones, perfilado, distribuciones — tipado.", en: "Visualizations, profiling, distributions — typed." } },
+ { num: "08", name: "BaseConverter", role: { es: "Conversor", en: "Converter" }, desc: { es: "Transformaciones tipadas entre formatos y representaciones.", en: "Typed transformations between formats and representations." } },
+ { num: "09", name: "BaseGlobalExplainer", role: { es: "XAI global", en: "Global XAI" }, desc: { es: "Permutation importance, surrogate, partial dependence.", en: "Permutation importance, surrogate, partial dependence." } },
+ { num: "10", name: "BaseLocalExplainer", role: { es: "XAI local", en: "Local XAI" }, desc: { es: "SHAP, LIME, counterfactuals con abstracción dedicada.", en: "SHAP, LIME, counterfactuals with dedicated abstraction." } },
+ { num: "11", name: "BaseJob", role: { es: "Orquestación", en: "Orchestration" }, desc: { es: "Train, predict, explain, explore, convert, generate, evaluate, optimize.", en: "Train, predict, explain, explore, convert, generate, evaluate, optimize." } },
+ { num: "12", name: "BaseGenerativeTask", role: { es: "Tarea generativa", en: "Generative task" }, desc: { es: "Generación condicional, text-to-image, seq-to-seq.", en: "Conditional generation, text-to-image, seq-to-seq." } },
+]
+
+export function ExtensibleSection() {
+ const { i18n } = useTranslation()
+ const lang = i18n.language?.startsWith("es") ? "es" : "en"
+
+ return (
+
+ {/* Section head */}
+
+
+
+
+ [ 03 ] {lang === "es" ? "Extensibilidad" : "Extensibility"}
+
+
+
+
+ {"{ II }"}
+
+ {lang === "es" ? "Doce abstracciones" : "Twelve abstractions"}
+
+
+ Full Extensible.
+
+
+ {lang === "es"
+ ? "Cada rol funcional tiene su clase base. Veinte a cuarenta líneas para un componente nuevo. La UI emerge del schema, no se programa."
+ : "Each functional role has its base class. Twenty to forty lines for a new component. The UI emerges from the schema — it isn't programmed."}
+
+
+
+
+ {/* 12 Modules grid */}
+
+ {MODULES.map(m => (
+ (e.currentTarget.style.background = "#F4F4F2")}
+ onMouseLeave={e => (e.currentTarget.style.background = "")}
+ >
+ {m.num}
+ {m.name}
+ {lang === "es" ? m.role.es : m.role.en}
+ {lang === "es" ? m.desc.es : m.desc.en}
+
+ {[14, 22, 14].map((w, i) => )}
+
+
+ ))}
+
+
+ {/* Arch grid */}
+
+ {/* Arch points */}
+
+ {[
+ { ico: "⬡", title: "Schema-driven UI", body: { es: "El servidor expone el schema Pydantic; el frontend React renderiza el formulario sin conocerlo previamente.", en: "The server exposes the Pydantic schema; the React frontend renders the form without prior knowledge." } },
+ { ico: "↻", title: lang === "es" ? "Hot-install desde la UI" : "Hot-install from the UI", body: { es: "Un click instala una extensión desde PyPI. Sin reiniciar, sin shell externa.", en: "One click installs an extension from PyPI. No restart, no external shell." } },
+ { ico: "▶", title: lang === "es" ? "API HTTP pública" : "Public HTTP API", body: { es: <>Cualquier cliente HTTP — Python, Jupyter, CLI — consulta componentes y lanza jobs. GET /component/, POST /job/., en: <>Any HTTP client — Python, Jupyter, CLI — queries components and launches jobs. GET /component/, POST /job/. } },
+ { ico: "⚡", title: "FastAPI + React, not desktop", body: { es: "El servidor corre en cualquier máquina, accesible desde el navegador — local, red o remoto.", en: "The server runs anywhere, reachable from any browser — local, network or remote." } },
+ ].map(p => (
+
+
+ {p.ico}
+
+
+ {p.title}
+ {lang === "es" ? p.body.es : p.body.en}
+
+
+ ))}
+
+
+ {/* Code block */}
+
+
+
+
+
+
+
+ my_classifier.py
+
+
+ {`\
+`}# {lang === "es" ? "Un clasificador completo en dashAI" : "A complete classifier in dashAI"}{`
+`}from{` dashai.base `}import{` `}BaseModel{`
+`}from{` dashai.core.schema_fields `}import{` schema_field, optimizer_int_field
+`}from{` sklearn.ensemble `}import{` RandomForestClassifier
+
+`}class{` `}MyForestSchema{`(BaseSchema):
+ n_estimators: `}schema_field{`(
+ `}optimizer_int_field{`(ge=`}1{`),
+ placeholder={
+ `}"optimize"{`: `}False{`, `}"fixed_value"{`: `}100{`,
+ `}"lower_bound"{`: `}50{`, `}"upper_bound"{`: `}200{`,
+ },
+ description=`}"{lang === "es" ? "Número de árboles" : "Number of trees"}"{`,
+ )
+ max_depth: `}schema_field{`(
+ `}optimizer_int_field{`(ge=`}1{`),
+ placeholder={
+ `}"optimize"{`: `}False{`, `}"fixed_value"{`: `}2{`,
+ `}"lower_bound"{`: `}2{`, `}"upper_bound"{`: `}10{`,
+ },
+ description=`}"{lang === "es" ? "Profundidad máxima" : "Maximum depth"}"{`,
+ )
+
+`}class{` `}MyForest{`(`}BaseModel{`):
+ SCHEMA = MyForestSchema
+
+ `}def{` `}train{`(`}self{`, X, y):
+ `}self{`.model = RandomForestClassifier(
+ **`}self{`.params
+ ).fit(X, y)
+
+ `}def{` `}predict{`(`}self{`, X):
+ `}return{` `}self{`.model.predict(X)`}
+
+
+ {lang === "es" ? "33 líneas · UI auto-generada" : "33 lines · UI auto-generated"}
+ python ≥ 3.10
+
+
+
+
+ )
+}
diff --git a/components/features-section.tsx b/components/features-section.tsx
index 2036451..372ba86 100644
--- a/components/features-section.tsx
+++ b/components/features-section.tsx
@@ -1,141 +1,182 @@
"use client"
-import { useEffect, useRef, useState } from "react"
-import { Trans, useTranslation } from "react-i18next"
+import { useTranslation } from "react-i18next"
-const featureItems = [
- {
- id: 1,
- key: "dataExplorer",
- image: "features/eda_module.png",
- defaultTitle: "Data Explorer",
- defaultDescription:
- "Explore, clean, and prepare your data in an intuitive visual environment: perform dynamic, visual, and guided exploratory data analyses (EDA) directly within DashAI.",
- },
- {
- id: 2,
- key: "mlExperimentation",
- image: "features/ml_experimentation.png",
- defaultTitle: "ML Experimentation",
- defaultDescription:
- "Set up and manage your ML experiments with an intuitive interface. Select models, configure its hyperparameters, and define evaluation metrics without writing a single line of code.",
- },
- {
- id: 3,
- key: "resultsVisualization",
- image: "features/results.png",
- defaultTitle: "Results Visualization",
- defaultDescription:
- "Compare model performance across multiple experiments. Interactive dashboards help you identify the best performing models and understand their behavior through comprehensive metrics and visualizations.",
- },
- {
- id: 4,
- key: "modelExplainability",
- image: "features/explainability_module.png",
- defaultTitle: "Model Explainability",
- defaultDescription:
- "Understand how your models make decisions. Generate feature importance plots, SHAP values, and interpretable visualizations that help you trust and debug your AI models.",
- },
- {
- id: 5,
- key: "generativeModule",
- image: "features/generative_module.png",
- defaultTitle: "Generative Module",
- defaultDescription:
- "Experiment with generative AI models seamlessly. Generate text, images, and other content while visualizing the generation process and fine-tuning parameters in real-time.",
- },
-]
+const PAPER = "#FEFEFF"
+const PAPER_LINE = "#E3E2DF"
+const ON_LIGHT = "#191817"
+const ON_LIGHT_MUTE = "#4A4744"
+const ON_LIGHT_FAINT = "#6C685F"
+const BRAND_ON_LIGHT = "#1E63D8"
export function FeaturesSection() {
- const { t } = useTranslation()
- const [visibleFeatures, setVisibleFeatures] = useState>(new Set())
- const featureRefs = useRef<(HTMLDivElement | null)[]>([])
-
- useEffect(() => {
- const observers = featureRefs.current.map((ref, index) => {
- if (!ref) return null
-
- const observer = new IntersectionObserver(
- (entries) => {
- entries.forEach((entry) => {
- if (entry.isIntersecting) {
- setVisibleFeatures((prev) => new Set(prev).add(index))
- }
- })
- },
- { threshold: 0.2 }
- )
-
- observer.observe(ref)
- return observer
- })
-
- return () => {
- observers.forEach((observer) => observer?.disconnect())
- }
- }, [])
+ const { i18n } = useTranslation()
+ const lang = i18n.language?.startsWith("es") ? "es" : "en"
return (
-
-
-
-
-
- Powerful Features
-
-
-
- {t("features:description", {
- defaultValue:
- "Discover the powerful features that make DashAI the ultimate platform for AI experimentation",
- })}
+
+ {/* Section head */}
+
+
+
+
+ [ 01 ] {lang === "es" ? "Apertura" : "Openness"}
+
+
+
+
+ {"{ I }"}
+
+ {lang === "es" ? "Cuatro pruebas" : "Four proofs"}
+
+
+ Full Open.
+
+
+ {lang === "es"
+ ? "La apertura no es una declaración de licencia: es una propiedad medible del sistema."
+ : "Openness isn't a license statement: it's a measurable property of the system."}
+
-
- {featureItems.map((feature, index) => {
- const isEven = index % 2 === 0
- const isVisible = visibleFeatures.has(index)
- const title = t(`features:items.${feature.key}.title`, {
- defaultValue: feature.defaultTitle,
- })
- const description = t(`features:items.${feature.key}.description`, {
- defaultValue: feature.defaultDescription,
- })
+ {/* 4 Proofs */}
+
+ {[
+ {
+ num: "01", sub: lang === "es" ? "Licencia" : "License",
+ title: lang === "es" ? <>Licencia MIT, sin copyleft. : <>MIT licensed, no copyleft.,
+ body: lang === "es"
+ ? "Integrable en sistemas institucionales y productos comerciales. Sin obligación de liberar lo que construís encima."
+ : "Integrable into institutional systems and commercial products. No obligation to release what you build on top.",
+ },
+ {
+ num: "02", sub: lang === "es" ? "Núcleo" : "Core",
+ title: lang === "es" ? <>Sin paywall productivo. : <>No productive paywall.,
+ body: lang === "es"
+ ? "Scheduling, deployment, RBAC y gobernanza viven en el núcleo. El proyecto que clonás hoy es el que llega a producción."
+ : "Scheduling, deployment, RBAC and governance live in the core. The project you clone today is what reaches production.",
+ },
+ {
+ num: "03", sub: lang === "es" ? "Ecosistema" : "Ecosystem",
+ title: lang === "es" ? <>Sin componentes cerrados. : <>No closed components.,
+ body: lang === "es"
+ ? "Toda extensión oficial comparte la licencia del núcleo. Auditable, modificable, forkeable bajo los mismos términos."
+ : "Every official extension shares the core license. Auditable, modifiable, forkable under the same terms.",
+ },
+ {
+ num: "04", sub: lang === "es" ? "Ejecución" : "Execution",
+ title: lang === "es" ? <>Sin claves API externas requeridas. : <>No external API keys required.,
+ body: lang === "es"
+ ? "Los modelos del núcleo corren con pesos abiertos. El sistema de plugins te permite agregar cualquier modelo —local o vía API— pero el núcleo nunca exige dependencias externas."
+ : "Core models run entirely on open weights. The plugin system lets you add any model — local or API-backed — but nothing external is ever required.",
+ },
+ ].map(p => (
+
+
+ {p.num} / {p.sub}
+
+
+ {p.title}
+
+ {p.body}
+
+ ))}
+
- return (
- {
- featureRefs.current[index] = el
- }}
- className={`flex flex-col ${
- isEven ? "lg:flex-row" : "lg:flex-row-reverse"
- } gap-12 items-center transition-all duration-1000 ${
- isVisible ? "opacity-100 translate-y-0" : "opacity-0 translate-y-12"
- }`}
- >
-
- {title}
-
- {description}
-
-
+ {/* Catalog header */}
+
+
+ {lang === "es" ? "Cobertura nativa, ejecución local." : "Native coverage, local execution."}
+
+
+ {lang === "es" ? "⊳ La apertura puesta a prueba" : "⊳ Openness, in practice"}
+
+
-
-
- 
-
-
-
-
- )
- })}
-
+ {/* Catalog grid */}
+
+ {[
+ {
+ kind: lang === "es" ? "Tabular" : "Tabular",
+ swatchColor: BRAND_ON_LIGHT,
+ title: lang === "es" ? "Clasificación & regresión" : "Classification & regression",
+ count: "15 + 15",
+ body: lang === "es"
+ ? <>Treinta modelos sobre scikit-learn y boosting. Cada uno como subclase de BaseModel.
+ : <>Thirty models over scikit-learn and boosting. Each one as a subclass of BaseModel.,
+ tags: ["RandomForest","XGBoost","LightGBM","SVM","MLP","+25"],
+ countColor: BRAND_ON_LIGHT,
+ },
+ {
+ kind: lang === "es" ? "NLP + Traducción" : "NLP + Translation",
+ swatchColor: BRAND_ON_LIGHT,
+ title: lang === "es" ? "Transformers y seq-to-seq" : "Transformers & seq-to-seq",
+ count: "15 + 9",
+ body: lang === "es"
+ ? <>Clasificadores y modelos de traducción neural con métricas BLEU · ChrF · TER nativas.
+ : <>Classifiers and neural translation models with native BLEU · ChrF · TER metrics.,
+ tags: ["DistilBERT","DeBERTa-v3","ModernBERT","NLLB","OpusMT","+19"],
+ countColor: BRAND_ON_LIGHT,
+ },
+ {
+ kind: lang === "es" ? "Modelos generativos" : "Generative models",
+ swatchColor: BRAND_ON_LIGHT,
+ title: lang === "es" ? "LLMs locales" : "Local LLMs",
+ count: "5",
+ body: lang === "es"
+ ? "Llama, Mistral, Mixtral, Qwen y SmolLM con pesos abiertos. Generación como tarea nativa."
+ : "Llama, Mistral, Mixtral, Qwen and SmolLM on open weights. Generation as a native task.",
+ tags: ["Llama","Mistral","Mixtral","Qwen","SmolLM"],
+ countColor: BRAND_ON_LIGHT,
+ },
+ {
+ kind: lang === "es" ? "Visión generativa" : "Generative vision",
+ swatchColor: BRAND_ON_LIGHT,
+ title: lang === "es" ? "Texto a imagen" : "Text to image",
+ count: "11",
+ body: lang === "es"
+ ? "PixArt-Sigma, SDXL, Stable Diffusion y variantes ControlNet. Detección automática de CUDA."
+ : "PixArt-Sigma, SDXL, Stable Diffusion and ControlNet variants. Automatic CUDA detection.",
+ tags: ["PixArt-Sigma","SDXL","SD v3","SD v2","ControlNet","+6"],
+ countColor: BRAND_ON_LIGHT,
+ },
+ ].map(c => (
+
+
+
+ {c.kind}
+
+ {c.title}
+ {c.count}
+ {c.body}
+
+ {c.tags.map(tag => (
+ -
+ {tag}
+
+ ))}
+
+
+ ))}
)
diff --git a/components/footer.tsx b/components/footer.tsx
index 63de12f..fe56d1b 100644
--- a/components/footer.tsx
+++ b/components/footer.tsx
@@ -1,138 +1,144 @@
"use client"
-import { Github, Twitter, Linkedin } from "lucide-react"
-import { siteConfig } from "@/lib/config"
import { useTranslation } from "react-i18next"
-
-const productLinks = [
- {
- href: "#features",
- defaultLabel: "Features",
- key: "features",
- external: false,
- },
- {
- href: siteConfig.resources.changelog,
- defaultLabel: "Changelog",
- key: "changelog",
- external: true,
- },
-]
-
-const resourceLinks = [
- {
- href: siteConfig.docs.url,
- defaultLabel: "Documentation",
- key: "documentation",
- external: true,
- },
-]
-
-const communityLinks = [
- {
- href: siteConfig.github.url,
- defaultLabel: "GitHub",
- key: "github",
- external: true,
- },
- {
- href: siteConfig.github.contribute,
- defaultLabel: "Contribute",
- key: "contribute",
- external: true,
- },
-]
+import { siteConfig } from "@/lib/config"
export function Footer() {
- const { t } = useTranslation()
+ const { i18n } = useTranslation()
+ const lang = i18n.language?.startsWith("es") ? "es" : "en"
+
return (
-
+
-
+
+
+
+ [ 05 ] {lang === "es" ? "Comunidad" : "Community"}
+
+
+
+ + {lang === "es" + ? <>Construyamos esto juntos. + : <>Let's build this together.}
-- {t("community:description", { - defaultValue: - "DashAI's plugin architecture enables anyone to contribute new capabilities. Build plugins, improve the core, and shape the future of open source AI tools.", - })} +
+ {lang === "es" + ? "dashAI es código abierto y comunidad abierta. Únete a la conversación, propone componentes, comparte experimentos." + : "dashAI is open source and open community. Join the conversation, propose components, share experiments."}
- {communityLinks.map((item, index) => {
- const Icon = item.icon
- const title = t(`community:cards.${item.key}.title`, {
- defaultValue: item.defaultTitle,
- })
- const description = t(`community:cards.${item.key}.description`, {
- defaultValue: item.defaultDescription,
- })
- return (
- window.open(item.link, "_blank", "noopener,noreferrer")}
- >
-
-
-
- )
- })}
+ {/* Cards */}
+
-
- {title}
-{description}
- {item.stats} -
+ {/* Contact */}
+
-
- (FALLBACK_DOWNLOADS)
+ const { i18n } = useTranslation()
+ const lang = i18n.language?.startsWith("es") ? "es" : "en"
+ const [exes, setExes] = useState(FALLBACK)
+ const [releaseTag, setReleaseTag] = useState("v0.9.3-alpha")
useEffect(() => {
- getLatestRelease().then((release) => {
+ getLatestRelease().then(release => {
if (!release) return
- setDownloads(
- FALLBACK_DOWNLOADS.map((entry) => {
- const asset = findAsset(release.assets, entry.id)
- if (!asset) return entry
- return {
- ...entry,
- version: release.tag_name,
- size: formatBytes(asset.size),
- link: asset.browser_download_url,
- }
- })
- )
+ setReleaseTag(release.tag_name)
+ setExes(FALLBACK.map(entry => {
+ const asset = findAsset(release.assets, entry.id)
+ if (!asset) return entry
+ return { ...entry, version: release.tag_name, size: formatBytes(asset.size), link: asset.browser_download_url }
+ }))
})
}, [])
+ const pipCmd = "pip install dashai\ndashai"
+
return (
-
-
+
- {/*
+
+
+
+ {lang === "es" ? "Contacto" : "Contact"}
+
+ + {lang === "es" ? "Escribinos directamente." : "Reach out directly."} +
++ {lang === "es" + ? "Consultas, colaboraciones, integraciones institucionales o simplemente para contar qué estás construyendo con dashAI." + : "Questions, collaborations, institutional integrations, or just to share what you're building with dashAI."} +
+ + dashai.nocode@gmail.com → +{"Ready to build your first plugin?"}
-- { - "Our comprehensive documentation guides you through creating plugins and contributing to the core platform" - } -
-
-
-
+ {/* Discord */}
+
)
diff --git a/components/download-section.tsx b/components/download-section.tsx
index 5f9127c..020f36c 100644
--- a/components/download-section.tsx
+++ b/components/download-section.tsx
@@ -1,178 +1,230 @@
"use client"
-import { Button } from "@/components/ui/button"
-import { Card, CardContent } from "@/components/ui/card"
-import { Download, Package } from "lucide-react"
import { useEffect, useState } from "react"
import { useTranslation } from "react-i18next"
import { findAsset, formatBytes, getLatestRelease } from "@/lib/github"
+import { siteConfig } from "@/lib/config"
const SOURCEFORGE_URL = "https://sourceforge.net/projects/dashai/files/latest/download"
+const TRACKER_URL = process.env.NEXT_PUBLIC_TRACKER_URL
-type DownloadEntry = {
- id: "mac_intel" | "mac_arm" | "windows"
- icon: typeof Package
- key: string
- defaultPlatform: string
- version: string
- size: string
- defaultFormat: string
- link: string
+async function trackClick(buttonId: string) {
+ if (!TRACKER_URL) return
+ try { await fetch(`${TRACKER_URL}/click/${buttonId}`, { method: "POST" }) } catch {}
}
-const FALLBACK_DOWNLOADS: DownloadEntry[] = [
- {
- id: "mac_intel",
- icon: Package,
- key: "macIntel",
- defaultPlatform: "macOS Intel processors",
- version: "",
- size: "",
- defaultFormat: ".dmg",
- link: SOURCEFORGE_URL,
- },
- {
- id: "mac_arm",
- icon: Package,
- key: "macArm",
- defaultPlatform: "macOS ARM processors",
- version: "",
- size: "",
- defaultFormat: ".dmg",
- link: SOURCEFORGE_URL,
- },
- {
- id: "windows",
- icon: Package,
- key: "windows",
- defaultPlatform: "Windows",
- version: "",
- size: "",
- defaultFormat: ".exe",
- link: SOURCEFORGE_URL,
- },
-]
+type ExeEntry = { id: "mac_intel" | "mac_arm" | "windows"; os: string; ext: string; link: string; version: string; size: string }
-const TRACKER_URL = process.env.NEXT_PUBLIC_TRACKER_URL
+const FALLBACK: ExeEntry[] = [
+ { id: "windows", os: "Windows", ext: ".exe", link: SOURCEFORGE_URL, version: "", size: "" },
+ { id: "mac_arm", os: "macOS (ARM)", ext: ".dmg", link: SOURCEFORGE_URL, version: "", size: "" },
+ { id: "mac_intel",os: "macOS (Intel)", ext: ".dmg",link: SOURCEFORGE_URL, version: "", size: "" },
+]
-async function trackClick(buttonId: string) {
- if (!TRACKER_URL) return
- try {
- await fetch(`${TRACKER_URL}/click/${buttonId}`, {
- method: "POST",
- })
- } catch {
- // non-blocking — don't let tracking errors affect the download
+function CopyButton({ text }: { text: string }) {
+ const [copied, setCopied] = useState(false)
+ const copy = () => {
+ navigator.clipboard.writeText(text).catch(() => {})
+ setCopied(true)
+ setTimeout(() => setCopied(false), 1400)
}
+ return (
+
+ )
}
export function DownloadSection() {
- const { t } = useTranslation()
- const [downloads, setDownloads] = useState
+
+
+ {/* Newsletter */}
+
+
+
+
+ Discord
+
+ + {lang === "es" ? "Súmate al servidor de Discord." : "Join the Discord server."} +
++ {lang === "es" + ? "Soporte en vivo, anuncios de release, hilos por módulo (Datasets, Modelos, Generativo, Plugins) y el canal #show-and-tell para que compartas tus experimentos." + : "Live support, release announcements, threads per module (Datasets, Models, Generative, Plugins) and a #show-and-tell channel to share your experiments."} +
+ { (e.currentTarget as HTMLElement).style.opacity = "0.85" }} + onMouseLeave={e => { (e.currentTarget as HTMLElement).style.opacity = "1" }} + > + {lang === "es" ? "Unirme al Discord" : "Join Discord"} → + +
+
+
+
+
+ Newsletter
+
+ + {lang === "es" ? "Una actualización mensual." : "One monthly digest."} +
++ {lang === "es" + ? "Nuevas features, modelos agregados al catálogo, plugins de la comunidad, papers relevantes. Sin spam, sin promos — solo lo que importa para tu workflow." + : "New features, models added to the catalog, community plugins, relevant papers. No spam, no promos — just what matters for your workflow."} +
+ {subscribed ? ( +
+ ✓ {lang === "es" ? "¡Suscripto!" : "Subscribed!"}
-
- */}
+ ) : (
+
+ )}
+ + {lang === "es" + ? "· Cancela cuando quieras · 0 emails comerciales" + : "· Unsubscribe anytime · 0 commercial emails"} +
+
-
-
- {t("download:title", { defaultValue: "Download DashAI" })}
+
- {t("download:title", { defaultValue: "Download DashAI" })}
+
+ {/* Horizontal line pattern */}
+
+
+ {/* Head */}
+
+
+
+
+ [ 04 ] {lang === "es" ? "Descarga" : "Download"}
+
+
+
+
+ {lang === "es" ? <>Descargá dashAI. : <>Download dashAI.}
-
- {t("download:badge", { defaultValue: "Beta Version" })}
-
-
- {t("download:description", {
- defaultValue:
- "This early version lets you explore DashAI's main features. We appreciate your feedback to help us improve before the official release.",
- })}
+
+ {releaseTag}
+ ·MIT License
+ ·Linux · macOS · Windows
+ ·{lang === "es" ? "Mayo 2026" : "May 2026"}
+
+
+
+
+ {/* 3-col grid */}
+
+ {/* Card 1 — executables */}
+
+
+ 01
+ {lang === "es" ? "Ejecutables (recomendado)" : "Executables (recommended)"}
+
+ {lang === "es" ? "Instalador nativo" : "Native installer"}
+
+ {lang === "es"
+ ? "Sin Python ni configuración. Descargá el ejecutable de tu sistema operativo desde GitHub Releases."
+ : "No Python, no setup. Download the executable for your OS from GitHub Releases."}
+
+
+
+ {lang === "es" ? "Ver releases" : "View releases"} →
+
+
+
+ {/* Card 2 — pip */}
+
+
+ 02
+ PyPI
+
+ {lang === "es" ? "Instalación con pip" : "Install with pip"}
+
+ {lang === "es"
+ ? <>dashai levanta el servidor y abre el navegador en localhost:8000.
+ : <>dashai starts the server and opens the browser at localhost:8000.}
+
+
-
-
- {platform}
-
- {download.version && (
-
- {download.version} • {download.size}
-
- )}
- {format}
-
-
-
-
- )
- })}
+ {/* Card 3 — requirements */}
+
+
+ ⊳
+ {lang === "es" ? "Requisitos" : "Requirements"}
+ {lang === "es" ? "Lo que necesitás" : "What you need"}
+
+ {[
+ { k: "Python", v: "≥ 3.10", note: lang === "es" ? "Solo para instalación pip" : "Only for pip install" },
+ { k: "RAM", v: "8 GB", note: lang === "es" ? "16 GB para LLMs locales" : "16 GB for local LLMs" },
+ { k: "OS", v: "Linux · macOS · Windows", note: lang === "es" ? "Ejecutables nativos disponibles" : "Native executables available" },
+ ].map(r => (
+ -
+ {r.k}
+
+ {r.v}
+ {r.note}
+
+
+ ))}
+
+
+
-
-
-
-
-
- {t("download:pip.title", { defaultValue: "Install via pip" })}
-
-
- {t("download:pip.subtitle", {
- defaultValue: "For developers who prefer command-line installation",
- })}
-
-
-
-
-
- {t("download:pip.command", { defaultValue: "pip install dashai" })}
-
-
-
-
-
-
+ {/* Footer row */}
+
+
+ {lang === "es" ? "¿Querés modificar el núcleo? Cloná el repo:" : "Want to modify the core? Clone the repo:"}
+
+ git clone github.com/DashAISoftware/DashAI
+
+
+
diff --git a/components/extensible-section.tsx b/components/extensible-section.tsx
new file mode 100644
index 0000000..a2b948b
--- /dev/null
+++ b/components/extensible-section.tsx
@@ -0,0 +1,181 @@
+"use client"
+
+import { useTranslation } from "react-i18next"
+
+const PAPER = "#FEFEFF"
+const PAPER_LINE = "#E3E2DF"
+const ON_LIGHT = "#191817"
+const ON_LIGHT_MUTE = "#4A4744"
+const ON_LIGHT_FAINT = "#6C685F"
+const PLUGINS_COLOR = "#1E63D8"
+const BRAND_ON_LIGHT = "#1E63D8"
+const CODE_BG = "#131211"
+const CODE_HEADER_BG = "#191817"
+const CODE_BORDER = "#2E2C29"
+
+const MODULES = [
+ { num: "01", name: "BaseTask", role: { es: "Tarea", en: "Task" }, desc: { es: "Paradigmas extensibles: clasificación, regresión, NLP, traducción, generación.", en: "Extensible paradigms: classification, regression, NLP, translation, generation." } },
+ { num: "02", name: "BaseModel", role: { es: "Modelo predictivo", en: "Predictive model"}, desc: { es: "Random Forest a transformers. Subclase + schema, listo para HPO.", en: "Random Forest to transformers. Subclass + schema, ready for HPO." } },
+ { num: "03", name: "BaseGenerativeModel", role: { es: "Modelo generativo", en: "Generative model"}, desc: { es: "LLMs e imagen como ciudadanos de primera clase.", en: "LLMs and image as first-class citizens." } },
+ { num: "04", name: "BaseMetric", role: { es: "Métrica", en: "Metric" }, desc: { es: "Classification, Regression, Translation. Aparece sola en la UI.", en: "Classification, Regression, Translation. Auto-appears in UI." } },
+ { num: "05", name: "BaseOptimizer", role: { es: "Optimización HPO", en: "HPO optimizer" }, desc: { es: "Optuna + HyperOpt. Estrategias bayesianas, evolutivas, QMC.", en: "Optuna + HyperOpt. Bayesian, evolutionary, QMC strategies." } },
+ { num: "06", name: "BaseDataLoader", role: { es: "Carga de datos", en: "Data loader" }, desc: { es: "CSV, JSON, imágenes, audio. Cada loader declara su formato.", en: "CSV, JSON, images, audio. Each loader declares its format." } },
+ { num: "07", name: "BaseExplorer", role: { es: "EDA / exploración", en: "EDA / exploration"}, desc: { es: "Visualizaciones, perfilado, distribuciones — tipado.", en: "Visualizations, profiling, distributions — typed." } },
+ { num: "08", name: "BaseConverter", role: { es: "Conversor", en: "Converter" }, desc: { es: "Transformaciones tipadas entre formatos y representaciones.", en: "Typed transformations between formats and representations." } },
+ { num: "09", name: "BaseGlobalExplainer", role: { es: "XAI global", en: "Global XAI" }, desc: { es: "Permutation importance, surrogate, partial dependence.", en: "Permutation importance, surrogate, partial dependence." } },
+ { num: "10", name: "BaseLocalExplainer", role: { es: "XAI local", en: "Local XAI" }, desc: { es: "SHAP, LIME, counterfactuals con abstracción dedicada.", en: "SHAP, LIME, counterfactuals with dedicated abstraction." } },
+ { num: "11", name: "BaseJob", role: { es: "Orquestación", en: "Orchestration" }, desc: { es: "Train, predict, explain, explore, convert, generate, evaluate, optimize.", en: "Train, predict, explain, explore, convert, generate, evaluate, optimize." } },
+ { num: "12", name: "BaseGenerativeTask", role: { es: "Tarea generativa", en: "Generative task" }, desc: { es: "Generación condicional, text-to-image, seq-to-seq.", en: "Conditional generation, text-to-image, seq-to-seq." } },
+]
+
+export function ExtensibleSection() {
+ const { i18n } = useTranslation()
+ const lang = i18n.language?.startsWith("es") ? "es" : "en"
+
+ return (
+
+ {/* Section head */}
+
+
+
+
+ [ 03 ] {lang === "es" ? "Extensibilidad" : "Extensibility"}
+
+
+
+
+ {"{ II }"}
+
+ {lang === "es" ? "Doce abstracciones" : "Twelve abstractions"}
+
+
+ Full Extensible.
+
+
+ {lang === "es"
+ ? "Cada rol funcional tiene su clase base. Veinte a cuarenta líneas para un componente nuevo. La UI emerge del schema, no se programa."
+ : "Each functional role has its base class. Twenty to forty lines for a new component. The UI emerges from the schema — it isn't programmed."}
+
+
+
+
+ {/* 12 Modules grid */}
+
+ {MODULES.map(m => (
+ (e.currentTarget.style.background = "#F4F4F2")}
+ onMouseLeave={e => (e.currentTarget.style.background = "")}
+ >
+ {m.num}
+ {m.name}
+ {lang === "es" ? m.role.es : m.role.en}
+ {lang === "es" ? m.desc.es : m.desc.en}
+
+ {[14, 22, 14].map((w, i) => )}
+
+
+ ))}
+
+
+ {/* Arch grid */}
+
+ {/* Arch points */}
+
+ {[
+ { ico: "⬡", title: "Schema-driven UI", body: { es: "El servidor expone el schema Pydantic; el frontend React renderiza el formulario sin conocerlo previamente.", en: "The server exposes the Pydantic schema; the React frontend renders the form without prior knowledge." } },
+ { ico: "↻", title: lang === "es" ? "Hot-install desde la UI" : "Hot-install from the UI", body: { es: "Un click instala una extensión desde PyPI. Sin reiniciar, sin shell externa.", en: "One click installs an extension from PyPI. No restart, no external shell." } },
+ { ico: "▶", title: lang === "es" ? "API HTTP pública" : "Public HTTP API", body: { es: <>Cualquier cliente HTTP — Python, Jupyter, CLI — consulta componentes y lanza jobs. GET /component/, POST /job/., en: <>Any HTTP client — Python, Jupyter, CLI — queries components and launches jobs. GET /component/, POST /job/. } },
+ { ico: "⚡", title: "FastAPI + React, not desktop", body: { es: "El servidor corre en cualquier máquina, accesible desde el navegador — local, red o remoto.", en: "The server runs anywhere, reachable from any browser — local, network or remote." } },
+ ].map(p => (
+
+
+ {p.ico}
+
+
+ {p.title}
+ {lang === "es" ? p.body.es : p.body.en}
+
+
+ ))}
+
+
+ {/* Code block */}
+
+
+
+
+
+
+
+ my_classifier.py
+
+
+ {`\
+`}# {lang === "es" ? "Un clasificador completo en dashAI" : "A complete classifier in dashAI"}{`
+`}from{` dashai.base `}import{` `}BaseModel{`
+`}from{` dashai.core.schema_fields `}import{` schema_field, optimizer_int_field
+`}from{` sklearn.ensemble `}import{` RandomForestClassifier
+
+`}class{` `}MyForestSchema{`(BaseSchema):
+ n_estimators: `}schema_field{`(
+ `}optimizer_int_field{`(ge=`}1{`),
+ placeholder={
+ `}"optimize"{`: `}False{`, `}"fixed_value"{`: `}100{`,
+ `}"lower_bound"{`: `}50{`, `}"upper_bound"{`: `}200{`,
+ },
+ description=`}"{lang === "es" ? "Número de árboles" : "Number of trees"}"{`,
+ )
+ max_depth: `}schema_field{`(
+ `}optimizer_int_field{`(ge=`}1{`),
+ placeholder={
+ `}"optimize"{`: `}False{`, `}"fixed_value"{`: `}2{`,
+ `}"lower_bound"{`: `}2{`, `}"upper_bound"{`: `}10{`,
+ },
+ description=`}"{lang === "es" ? "Profundidad máxima" : "Maximum depth"}"{`,
+ )
+
+`}class{` `}MyForest{`(`}BaseModel{`):
+ SCHEMA = MyForestSchema
+
+ `}def{` `}train{`(`}self{`, X, y):
+ `}self{`.model = RandomForestClassifier(
+ **`}self{`.params
+ ).fit(X, y)
+
+ `}def{` `}predict{`(`}self{`, X):
+ `}return{` `}self{`.model.predict(X)`}
+
+
+ {lang === "es" ? "33 líneas · UI auto-generada" : "33 lines · UI auto-generated"}
+ python ≥ 3.10
+
+
+
+
+ )
+}
diff --git a/components/features-section.tsx b/components/features-section.tsx
index 2036451..372ba86 100644
--- a/components/features-section.tsx
+++ b/components/features-section.tsx
@@ -1,141 +1,182 @@
"use client"
-import { useEffect, useRef, useState } from "react"
-import { Trans, useTranslation } from "react-i18next"
+import { useTranslation } from "react-i18next"
-const featureItems = [
- {
- id: 1,
- key: "dataExplorer",
- image: "features/eda_module.png",
- defaultTitle: "Data Explorer",
- defaultDescription:
- "Explore, clean, and prepare your data in an intuitive visual environment: perform dynamic, visual, and guided exploratory data analyses (EDA) directly within DashAI.",
- },
- {
- id: 2,
- key: "mlExperimentation",
- image: "features/ml_experimentation.png",
- defaultTitle: "ML Experimentation",
- defaultDescription:
- "Set up and manage your ML experiments with an intuitive interface. Select models, configure its hyperparameters, and define evaluation metrics without writing a single line of code.",
- },
- {
- id: 3,
- key: "resultsVisualization",
- image: "features/results.png",
- defaultTitle: "Results Visualization",
- defaultDescription:
- "Compare model performance across multiple experiments. Interactive dashboards help you identify the best performing models and understand their behavior through comprehensive metrics and visualizations.",
- },
- {
- id: 4,
- key: "modelExplainability",
- image: "features/explainability_module.png",
- defaultTitle: "Model Explainability",
- defaultDescription:
- "Understand how your models make decisions. Generate feature importance plots, SHAP values, and interpretable visualizations that help you trust and debug your AI models.",
- },
- {
- id: 5,
- key: "generativeModule",
- image: "features/generative_module.png",
- defaultTitle: "Generative Module",
- defaultDescription:
- "Experiment with generative AI models seamlessly. Generate text, images, and other content while visualizing the generation process and fine-tuning parameters in real-time.",
- },
-]
+const PAPER = "#FEFEFF"
+const PAPER_LINE = "#E3E2DF"
+const ON_LIGHT = "#191817"
+const ON_LIGHT_MUTE = "#4A4744"
+const ON_LIGHT_FAINT = "#6C685F"
+const BRAND_ON_LIGHT = "#1E63D8"
export function FeaturesSection() {
- const { t } = useTranslation()
- const [visibleFeatures, setVisibleFeatures] = useState>(new Set())
- const featureRefs = useRef<(HTMLDivElement | null)[]>([])
-
- useEffect(() => {
- const observers = featureRefs.current.map((ref, index) => {
- if (!ref) return null
-
- const observer = new IntersectionObserver(
- (entries) => {
- entries.forEach((entry) => {
- if (entry.isIntersecting) {
- setVisibleFeatures((prev) => new Set(prev).add(index))
- }
- })
- },
- { threshold: 0.2 }
- )
-
- observer.observe(ref)
- return observer
- })
-
- return () => {
- observers.forEach((observer) => observer?.disconnect())
- }
- }, [])
+ const { i18n } = useTranslation()
+ const lang = i18n.language?.startsWith("es") ? "es" : "en"
return (
-
-
-
-
-
- Powerful Features
-
-
-
- {t("features:description", {
- defaultValue:
- "Discover the powerful features that make DashAI the ultimate platform for AI experimentation",
- })}
+
+ {/* Section head */}
+
+
+
+
+ [ 01 ] {lang === "es" ? "Apertura" : "Openness"}
+
+
+
+
+ {"{ I }"}
+
+ {lang === "es" ? "Cuatro pruebas" : "Four proofs"}
+
+
+ Full Open.
+
+
+ {lang === "es"
+ ? "La apertura no es una declaración de licencia: es una propiedad medible del sistema."
+ : "Openness isn't a license statement: it's a measurable property of the system."}
+
-
- {featureItems.map((feature, index) => {
- const isEven = index % 2 === 0
- const isVisible = visibleFeatures.has(index)
- const title = t(`features:items.${feature.key}.title`, {
- defaultValue: feature.defaultTitle,
- })
- const description = t(`features:items.${feature.key}.description`, {
- defaultValue: feature.defaultDescription,
- })
+ {/* 4 Proofs */}
+
+ {[
+ {
+ num: "01", sub: lang === "es" ? "Licencia" : "License",
+ title: lang === "es" ? <>Licencia MIT, sin copyleft. : <>MIT licensed, no copyleft.,
+ body: lang === "es"
+ ? "Integrable en sistemas institucionales y productos comerciales. Sin obligación de liberar lo que construís encima."
+ : "Integrable into institutional systems and commercial products. No obligation to release what you build on top.",
+ },
+ {
+ num: "02", sub: lang === "es" ? "Núcleo" : "Core",
+ title: lang === "es" ? <>Sin paywall productivo. : <>No productive paywall.,
+ body: lang === "es"
+ ? "Scheduling, deployment, RBAC y gobernanza viven en el núcleo. El proyecto que clonás hoy es el que llega a producción."
+ : "Scheduling, deployment, RBAC and governance live in the core. The project you clone today is what reaches production.",
+ },
+ {
+ num: "03", sub: lang === "es" ? "Ecosistema" : "Ecosystem",
+ title: lang === "es" ? <>Sin componentes cerrados. : <>No closed components.,
+ body: lang === "es"
+ ? "Toda extensión oficial comparte la licencia del núcleo. Auditable, modificable, forkeable bajo los mismos términos."
+ : "Every official extension shares the core license. Auditable, modifiable, forkable under the same terms.",
+ },
+ {
+ num: "04", sub: lang === "es" ? "Ejecución" : "Execution",
+ title: lang === "es" ? <>Sin claves API externas requeridas. : <>No external API keys required.,
+ body: lang === "es"
+ ? "Los modelos del núcleo corren con pesos abiertos. El sistema de plugins te permite agregar cualquier modelo —local o vía API— pero el núcleo nunca exige dependencias externas."
+ : "Core models run entirely on open weights. The plugin system lets you add any model — local or API-backed — but nothing external is ever required.",
+ },
+ ].map(p => (
+
+
+ {p.num} / {p.sub}
+
+
+ {p.title}
+
+ {p.body}
+
+ ))}
+
- return (
- {
- featureRefs.current[index] = el
- }}
- className={`flex flex-col ${
- isEven ? "lg:flex-row" : "lg:flex-row-reverse"
- } gap-12 items-center transition-all duration-1000 ${
- isVisible ? "opacity-100 translate-y-0" : "opacity-0 translate-y-12"
- }`}
- >
-
- {title}
-
- {description}
-
-
+ {/* Catalog header */}
+
+
+ {lang === "es" ? "Cobertura nativa, ejecución local." : "Native coverage, local execution."}
+
+
+ {lang === "es" ? "⊳ La apertura puesta a prueba" : "⊳ Openness, in practice"}
+
+
-
-
-
-
-
-
-
- )
- })}
-
+ {/* Catalog grid */}
+
+ {[
+ {
+ kind: lang === "es" ? "Tabular" : "Tabular",
+ swatchColor: BRAND_ON_LIGHT,
+ title: lang === "es" ? "Clasificación & regresión" : "Classification & regression",
+ count: "15 + 15",
+ body: lang === "es"
+ ? <>Treinta modelos sobre scikit-learn y boosting. Cada uno como subclase de BaseModel.
+ : <>Thirty models over scikit-learn and boosting. Each one as a subclass of BaseModel.,
+ tags: ["RandomForest","XGBoost","LightGBM","SVM","MLP","+25"],
+ countColor: BRAND_ON_LIGHT,
+ },
+ {
+ kind: lang === "es" ? "NLP + Traducción" : "NLP + Translation",
+ swatchColor: BRAND_ON_LIGHT,
+ title: lang === "es" ? "Transformers y seq-to-seq" : "Transformers & seq-to-seq",
+ count: "15 + 9",
+ body: lang === "es"
+ ? <>Clasificadores y modelos de traducción neural con métricas BLEU · ChrF · TER nativas.
+ : <>Classifiers and neural translation models with native BLEU · ChrF · TER metrics.,
+ tags: ["DistilBERT","DeBERTa-v3","ModernBERT","NLLB","OpusMT","+19"],
+ countColor: BRAND_ON_LIGHT,
+ },
+ {
+ kind: lang === "es" ? "Modelos generativos" : "Generative models",
+ swatchColor: BRAND_ON_LIGHT,
+ title: lang === "es" ? "LLMs locales" : "Local LLMs",
+ count: "5",
+ body: lang === "es"
+ ? "Llama, Mistral, Mixtral, Qwen y SmolLM con pesos abiertos. Generación como tarea nativa."
+ : "Llama, Mistral, Mixtral, Qwen and SmolLM on open weights. Generation as a native task.",
+ tags: ["Llama","Mistral","Mixtral","Qwen","SmolLM"],
+ countColor: BRAND_ON_LIGHT,
+ },
+ {
+ kind: lang === "es" ? "Visión generativa" : "Generative vision",
+ swatchColor: BRAND_ON_LIGHT,
+ title: lang === "es" ? "Texto a imagen" : "Text to image",
+ count: "11",
+ body: lang === "es"
+ ? "PixArt-Sigma, SDXL, Stable Diffusion y variantes ControlNet. Detección automática de CUDA."
+ : "PixArt-Sigma, SDXL, Stable Diffusion and ControlNet variants. Automatic CUDA detection.",
+ tags: ["PixArt-Sigma","SDXL","SD v3","SD v2","ControlNet","+6"],
+ countColor: BRAND_ON_LIGHT,
+ },
+ ].map(c => (
+
+
+
+ {c.kind}
+
+ {c.title}
+ {c.count}
+ {c.body}
+
+ {c.tags.map(tag => (
+ -
+ {tag}
+
+ ))}
+
+
+ ))}
)
diff --git a/components/footer.tsx b/components/footer.tsx
index 63de12f..fe56d1b 100644
--- a/components/footer.tsx
+++ b/components/footer.tsx
@@ -1,138 +1,144 @@
"use client"
-import { Github, Twitter, Linkedin } from "lucide-react"
-import { siteConfig } from "@/lib/config"
import { useTranslation } from "react-i18next"
-
-const productLinks = [
- {
- href: "#features",
- defaultLabel: "Features",
- key: "features",
- external: false,
- },
- {
- href: siteConfig.resources.changelog,
- defaultLabel: "Changelog",
- key: "changelog",
- external: true,
- },
-]
-
-const resourceLinks = [
- {
- href: siteConfig.docs.url,
- defaultLabel: "Documentation",
- key: "documentation",
- external: true,
- },
-]
-
-const communityLinks = [
- {
- href: siteConfig.github.url,
- defaultLabel: "GitHub",
- key: "github",
- external: true,
- },
- {
- href: siteConfig.github.contribute,
- defaultLabel: "Contribute",
- key: "contribute",
- external: true,
- },
-]
+import { siteConfig } from "@/lib/config"
export function Footer() {
- const { t } = useTranslation()
+ const { i18n } = useTranslation()
+ const lang = i18n.language?.startsWith("es") ? "es" : "en"
+
return (
-
+
+
+ {/* 3-col grid */}
+
+
+
+
+ [ 04 ] {lang === "es" ? "Descarga" : "Download"}
+
+
+
+ + {lang === "es" ? <>Descargá dashAI. : <>Download dashAI.}
- - {t("download:badge", { defaultValue: "Beta Version" })} - -- {t("download:description", { - defaultValue: - "This early version lets you explore DashAI's main features. We appreciate your feedback to help us improve before the official release.", - })} +
+ {releaseTag}
+ ·MIT License
+ ·Linux · macOS · Windows
+ ·{lang === "es" ? "Mayo 2026" : "May 2026"}
+
+
+ {/* Card 1 — executables */}
+
+
+
+ {/* Card 2 — pip */}
+
+ 01
+ {lang === "es" ? "Ejecutables (recomendado)" : "Executables (recommended)"}
+
+ {lang === "es" ? "Instalador nativo" : "Native installer"}
++ {lang === "es" + ? "Sin Python ni configuración. Descargá el ejecutable de tu sistema operativo desde GitHub Releases." + : "No Python, no setup. Download the executable for your OS from GitHub Releases."} +
+ + + {lang === "es" ? "Ver releases" : "View releases"} → + +
+
-
+ 02
+ PyPI
+
+ {lang === "es" ? "Instalación con pip" : "Install with pip"}
+
+ {lang === "es"
+ ? <>dashai levanta el servidor y abre el navegador en localhost:8000.
+ : <>dashai starts the server and opens the browser at localhost:8000.}
+
+
+ {lang === "es" ? "Ver en PyPI" : "View on PyPI"} →
+
$ pip install dashai
+ $ dashai
+
+ # {lang === "es" ? "http://localhost:8000/ — El navegador abre solo." : "http://localhost:8000/ — Browser opens on its own."}
+
+
-
-
-
-
+ {/* Footer row */}
+
+ {/* Section head */}
+
+ )
+}
diff --git a/components/features-section.tsx b/components/features-section.tsx
index 2036451..372ba86 100644
--- a/components/features-section.tsx
+++ b/components/features-section.tsx
@@ -1,141 +1,182 @@
"use client"
-import { useEffect, useRef, useState } from "react"
-import { Trans, useTranslation } from "react-i18next"
+import { useTranslation } from "react-i18next"
-const featureItems = [
- {
- id: 1,
- key: "dataExplorer",
- image: "features/eda_module.png",
- defaultTitle: "Data Explorer",
- defaultDescription:
- "Explore, clean, and prepare your data in an intuitive visual environment: perform dynamic, visual, and guided exploratory data analyses (EDA) directly within DashAI.",
- },
- {
- id: 2,
- key: "mlExperimentation",
- image: "features/ml_experimentation.png",
- defaultTitle: "ML Experimentation",
- defaultDescription:
- "Set up and manage your ML experiments with an intuitive interface. Select models, configure its hyperparameters, and define evaluation metrics without writing a single line of code.",
- },
- {
- id: 3,
- key: "resultsVisualization",
- image: "features/results.png",
- defaultTitle: "Results Visualization",
- defaultDescription:
- "Compare model performance across multiple experiments. Interactive dashboards help you identify the best performing models and understand their behavior through comprehensive metrics and visualizations.",
- },
- {
- id: 4,
- key: "modelExplainability",
- image: "features/explainability_module.png",
- defaultTitle: "Model Explainability",
- defaultDescription:
- "Understand how your models make decisions. Generate feature importance plots, SHAP values, and interpretable visualizations that help you trust and debug your AI models.",
- },
- {
- id: 5,
- key: "generativeModule",
- image: "features/generative_module.png",
- defaultTitle: "Generative Module",
- defaultDescription:
- "Experiment with generative AI models seamlessly. Generate text, images, and other content while visualizing the generation process and fine-tuning parameters in real-time.",
- },
-]
+const PAPER = "#FEFEFF"
+const PAPER_LINE = "#E3E2DF"
+const ON_LIGHT = "#191817"
+const ON_LIGHT_MUTE = "#4A4744"
+const ON_LIGHT_FAINT = "#6C685F"
+const BRAND_ON_LIGHT = "#1E63D8"
export function FeaturesSection() {
- const { t } = useTranslation()
- const [visibleFeatures, setVisibleFeatures] = useState>(new Set())
- const featureRefs = useRef<(HTMLDivElement | null)[]>([])
-
- useEffect(() => {
- const observers = featureRefs.current.map((ref, index) => {
- if (!ref) return null
-
- const observer = new IntersectionObserver(
- (entries) => {
- entries.forEach((entry) => {
- if (entry.isIntersecting) {
- setVisibleFeatures((prev) => new Set(prev).add(index))
- }
- })
- },
- { threshold: 0.2 }
- )
-
- observer.observe(ref)
- return observer
- })
-
- return () => {
- observers.forEach((observer) => observer?.disconnect())
- }
- }, [])
+ const { i18n } = useTranslation()
+ const lang = i18n.language?.startsWith("es") ? "es" : "en"
return (
-
-
- {downloads.map((download) => {
- const Icon = download.icon
- const platform = t(`download:cards.${download.key}.platform`, {
- defaultValue: download.defaultPlatform,
- })
- const format = t(`download:cards.${download.key}.format`, {
- defaultValue: download.defaultFormat,
- })
- return (
-
-
-
-
- )
- })}
+ {/* Card 3 — requirements */}
+
-
-
- {platform}
-
- {download.version && (
-
-
- - {download.version} • {download.size} -
- )} -{format}
-
+
+
+ ⊳
+ {lang === "es" ? "Requisitos" : "Requirements"}
+ {lang === "es" ? "Lo que necesitás" : "What you need"}
+-
+ {[
+ { k: "Python", v: "≥ 3.10", note: lang === "es" ? "Solo para instalación pip" : "Only for pip install" },
+ { k: "RAM", v: "8 GB", note: lang === "es" ? "16 GB para LLMs locales" : "16 GB for local LLMs" },
+ { k: "OS", v: "Linux · macOS · Windows", note: lang === "es" ? "Ejecutables nativos disponibles" : "Native executables available" },
+ ].map(r => (
+
- + {r.k} + + {r.v} + {r.note} + + + ))} +
-
-
-
- - {t("download:pip.title", { defaultValue: "Install via pip" })} -
-- {t("download:pip.subtitle", { - defaultValue: "For developers who prefer command-line installation", - })} -
-
-
-
-
-
- {t("download:pip.command", { defaultValue: "pip install dashai" })}
-
-
+
diff --git a/components/extensible-section.tsx b/components/extensible-section.tsx
new file mode 100644
index 0000000..a2b948b
--- /dev/null
+++ b/components/extensible-section.tsx
@@ -0,0 +1,181 @@
+"use client"
+
+import { useTranslation } from "react-i18next"
+
+const PAPER = "#FEFEFF"
+const PAPER_LINE = "#E3E2DF"
+const ON_LIGHT = "#191817"
+const ON_LIGHT_MUTE = "#4A4744"
+const ON_LIGHT_FAINT = "#6C685F"
+const PLUGINS_COLOR = "#1E63D8"
+const BRAND_ON_LIGHT = "#1E63D8"
+const CODE_BG = "#131211"
+const CODE_HEADER_BG = "#191817"
+const CODE_BORDER = "#2E2C29"
+
+const MODULES = [
+ { num: "01", name: "BaseTask", role: { es: "Tarea", en: "Task" }, desc: { es: "Paradigmas extensibles: clasificación, regresión, NLP, traducción, generación.", en: "Extensible paradigms: classification, regression, NLP, translation, generation." } },
+ { num: "02", name: "BaseModel", role: { es: "Modelo predictivo", en: "Predictive model"}, desc: { es: "Random Forest a transformers. Subclase + schema, listo para HPO.", en: "Random Forest to transformers. Subclass + schema, ready for HPO." } },
+ { num: "03", name: "BaseGenerativeModel", role: { es: "Modelo generativo", en: "Generative model"}, desc: { es: "LLMs e imagen como ciudadanos de primera clase.", en: "LLMs and image as first-class citizens." } },
+ { num: "04", name: "BaseMetric", role: { es: "Métrica", en: "Metric" }, desc: { es: "Classification, Regression, Translation. Aparece sola en la UI.", en: "Classification, Regression, Translation. Auto-appears in UI." } },
+ { num: "05", name: "BaseOptimizer", role: { es: "Optimización HPO", en: "HPO optimizer" }, desc: { es: "Optuna + HyperOpt. Estrategias bayesianas, evolutivas, QMC.", en: "Optuna + HyperOpt. Bayesian, evolutionary, QMC strategies." } },
+ { num: "06", name: "BaseDataLoader", role: { es: "Carga de datos", en: "Data loader" }, desc: { es: "CSV, JSON, imágenes, audio. Cada loader declara su formato.", en: "CSV, JSON, images, audio. Each loader declares its format." } },
+ { num: "07", name: "BaseExplorer", role: { es: "EDA / exploración", en: "EDA / exploration"}, desc: { es: "Visualizaciones, perfilado, distribuciones — tipado.", en: "Visualizations, profiling, distributions — typed." } },
+ { num: "08", name: "BaseConverter", role: { es: "Conversor", en: "Converter" }, desc: { es: "Transformaciones tipadas entre formatos y representaciones.", en: "Typed transformations between formats and representations." } },
+ { num: "09", name: "BaseGlobalExplainer", role: { es: "XAI global", en: "Global XAI" }, desc: { es: "Permutation importance, surrogate, partial dependence.", en: "Permutation importance, surrogate, partial dependence." } },
+ { num: "10", name: "BaseLocalExplainer", role: { es: "XAI local", en: "Local XAI" }, desc: { es: "SHAP, LIME, counterfactuals con abstracción dedicada.", en: "SHAP, LIME, counterfactuals with dedicated abstraction." } },
+ { num: "11", name: "BaseJob", role: { es: "Orquestación", en: "Orchestration" }, desc: { es: "Train, predict, explain, explore, convert, generate, evaluate, optimize.", en: "Train, predict, explain, explore, convert, generate, evaluate, optimize." } },
+ { num: "12", name: "BaseGenerativeTask", role: { es: "Tarea generativa", en: "Generative task" }, desc: { es: "Generación condicional, text-to-image, seq-to-seq.", en: "Conditional generation, text-to-image, seq-to-seq." } },
+]
+
+export function ExtensibleSection() {
+ const { i18n } = useTranslation()
+ const lang = i18n.language?.startsWith("es") ? "es" : "en"
+
+ return (
+
+ {lang === "es" ? "¿Querés modificar el núcleo? Cloná el repo:" : "Want to modify the core? Clone the repo:"}
+
+
+ git clone github.com/DashAISoftware/DashAI
+
+
+
+
+ {/* 12 Modules grid */}
+
+
+
+
+ [ 03 ] {lang === "es" ? "Extensibilidad" : "Extensibility"}
+
+
+
+
+ {"{ II }"}
+
+ {lang === "es" ? "Doce abstracciones" : "Twelve abstractions"}
+
+ + Full Extensible. +
++ {lang === "es" + ? "Cada rol funcional tiene su clase base. Veinte a cuarenta líneas para un componente nuevo. La UI emerge del schema, no se programa." + : "Each functional role has its base class. Twenty to forty lines for a new component. The UI emerges from the schema — it isn't programmed."} +
+
+ {MODULES.map(m => (
+
+
+ {/* Arch grid */}
+ (e.currentTarget.style.background = "#F4F4F2")}
+ onMouseLeave={e => (e.currentTarget.style.background = "")}
+ >
+
+ ))}
+ {m.num}
+ {m.name}
+ {lang === "es" ? m.role.es : m.role.en}
+ {lang === "es" ? m.desc.es : m.desc.en}
+
+ {[14, 22, 14].map((w, i) => )}
+
+
+ {/* Arch points */}
+
+
+ {[
+ { ico: "⬡", title: "Schema-driven UI", body: { es: "El servidor expone el schema Pydantic; el frontend React renderiza el formulario sin conocerlo previamente.", en: "The server exposes the Pydantic schema; the React frontend renders the form without prior knowledge." } },
+ { ico: "↻", title: lang === "es" ? "Hot-install desde la UI" : "Hot-install from the UI", body: { es: "Un click instala una extensión desde PyPI. Sin reiniciar, sin shell externa.", en: "One click installs an extension from PyPI. No restart, no external shell." } },
+ { ico: "▶", title: lang === "es" ? "API HTTP pública" : "Public HTTP API", body: { es: <>Cualquier cliente HTTP — Python, Jupyter, CLI — consulta componentes y lanza jobs.
+
+ {/* Code block */}
+ GET /component/, POST /job/., en: <>Any HTTP client — Python, Jupyter, CLI — queries components and launches jobs. GET /component/, POST /job/. } },
+ { ico: "⚡", title: "FastAPI + React, not desktop", body: { es: "El servidor corre en cualquier máquina, accesible desde el navegador — local, red o remoto.", en: "The server runs anywhere, reachable from any browser — local, network or remote." } },
+ ].map(p => (
+
+
+ ))}
+
+ {p.ico}
+
+
+
+ {p.title}
+{lang === "es" ? p.body.es : p.body.en}
+
+
+
+
+
+
+
+
+
+ my_classifier.py
+
+ {`\
+`}# {lang === "es" ? "Un clasificador completo en dashAI" : "A complete classifier in dashAI"}{`
+`}from{` dashai.base `}import{` `}BaseModel{`
+`}from{` dashai.core.schema_fields `}import{` schema_field, optimizer_int_field
+`}from{` sklearn.ensemble `}import{` RandomForestClassifier
+
+`}class{` `}MyForestSchema{`(BaseSchema):
+ n_estimators: `}schema_field{`(
+ `}optimizer_int_field{`(ge=`}1{`),
+ placeholder={
+ `}"optimize"{`: `}False{`, `}"fixed_value"{`: `}100{`,
+ `}"lower_bound"{`: `}50{`, `}"upper_bound"{`: `}200{`,
+ },
+ description=`}"{lang === "es" ? "Número de árboles" : "Number of trees"}"{`,
+ )
+ max_depth: `}schema_field{`(
+ `}optimizer_int_field{`(ge=`}1{`),
+ placeholder={
+ `}"optimize"{`: `}False{`, `}"fixed_value"{`: `}2{`,
+ `}"lower_bound"{`: `}2{`, `}"upper_bound"{`: `}10{`,
+ },
+ description=`}"{lang === "es" ? "Profundidad máxima" : "Maximum depth"}"{`,
+ )
+
+`}class{` `}MyForest{`(`}BaseModel{`):
+ SCHEMA = MyForestSchema
+
+ `}def{` `}train{`(`}self{`, X, y):
+ `}self{`.model = RandomForestClassifier(
+ **`}self{`.params
+ ).fit(X, y)
+
+ `}def{` `}predict{`(`}self{`, X):
+ `}return{` `}self{`.model.predict(X)`}
+
+
+ {lang === "es" ? "33 líneas · UI auto-generada" : "33 lines · UI auto-generated"}
+ python ≥ 3.10
+
+
-
-
-
-
- Powerful Features -
-
- {t("features:description", {
- defaultValue:
- "Discover the powerful features that make DashAI the ultimate platform for AI experimentation",
- })}
+
+ {lang === "es"
+ ? "La apertura no es una declaración de licencia: es una propiedad medible del sistema."
+ : "Openness isn't a license statement: it's a measurable property of the system."}
{p.body}
- {description}
- {c.body}
+
-
+
+
+
+ [ 01 ] {lang === "es" ? "Apertura" : "Openness"}
+
+
+
+
+ {"{ I }"}
+
+ {lang === "es" ? "Cuatro pruebas" : "Four proofs"}
+
+
+ Full Open.
+
+
- {featureItems.map((feature, index) => {
- const isEven = index % 2 === 0
- const isVisible = visibleFeatures.has(index)
- const title = t(`features:items.${feature.key}.title`, {
- defaultValue: feature.defaultTitle,
- })
- const description = t(`features:items.${feature.key}.description`, {
- defaultValue: feature.defaultDescription,
- })
+ {/* 4 Proofs */}
+
+ {/* Catalog grid */}
+
+ {[
+ {
+ num: "01", sub: lang === "es" ? "Licencia" : "License",
+ title: lang === "es" ? <>Licencia MIT, sin copyleft. : <>MIT licensed, no copyleft.,
+ body: lang === "es"
+ ? "Integrable en sistemas institucionales y productos comerciales. Sin obligación de liberar lo que construís encima."
+ : "Integrable into institutional systems and commercial products. No obligation to release what you build on top.",
+ },
+ {
+ num: "02", sub: lang === "es" ? "Núcleo" : "Core",
+ title: lang === "es" ? <>Sin paywall productivo. : <>No productive paywall.,
+ body: lang === "es"
+ ? "Scheduling, deployment, RBAC y gobernanza viven en el núcleo. El proyecto que clonás hoy es el que llega a producción."
+ : "Scheduling, deployment, RBAC and governance live in the core. The project you clone today is what reaches production.",
+ },
+ {
+ num: "03", sub: lang === "es" ? "Ecosistema" : "Ecosystem",
+ title: lang === "es" ? <>Sin componentes cerrados. : <>No closed components.,
+ body: lang === "es"
+ ? "Toda extensión oficial comparte la licencia del núcleo. Auditable, modificable, forkeable bajo los mismos términos."
+ : "Every official extension shares the core license. Auditable, modifiable, forkable under the same terms.",
+ },
+ {
+ num: "04", sub: lang === "es" ? "Ejecución" : "Execution",
+ title: lang === "es" ? <>Sin claves API externas requeridas. : <>No external API keys required.,
+ body: lang === "es"
+ ? "Los modelos del núcleo corren con pesos abiertos. El sistema de plugins te permite agregar cualquier modelo —local o vía API— pero el núcleo nunca exige dependencias externas."
+ : "Core models run entirely on open weights. The plugin system lets you add any model — local or API-backed — but nothing external is ever required.",
+ },
+ ].map(p => (
+
- return (
-
+
+ ))}
+
+ {p.num} / {p.sub}
+
+
+ {p.title}
+
+ {
- featureRefs.current[index] = el
- }}
- className={`flex flex-col ${
- isEven ? "lg:flex-row" : "lg:flex-row-reverse"
- } gap-12 items-center transition-all duration-1000 ${
- isVisible ? "opacity-100 translate-y-0" : "opacity-0 translate-y-12"
- }`}
- >
-
- )
- })}
-
-
+ {/* Catalog header */}
+ {title}
-
+
-
+ {lang === "es" ? "Cobertura nativa, ejecución local." : "Native coverage, local execution."}
+
+
+ {lang === "es" ? "⊳ La apertura puesta a prueba" : "⊳ Openness, in practice"}
+
+
-
-
-
-
-
-
+ {[
+ {
+ kind: lang === "es" ? "Tabular" : "Tabular",
+ swatchColor: BRAND_ON_LIGHT,
+ title: lang === "es" ? "Clasificación & regresión" : "Classification & regression",
+ count: "15 + 15",
+ body: lang === "es"
+ ? <>Treinta modelos sobre scikit-learn y boosting. Cada uno como subclase de
BaseModel.
+ : <>Thirty models over scikit-learn and boosting. Each one as a subclass of BaseModel.,
+ tags: ["RandomForest","XGBoost","LightGBM","SVM","MLP","+25"],
+ countColor: BRAND_ON_LIGHT,
+ },
+ {
+ kind: lang === "es" ? "NLP + Traducción" : "NLP + Translation",
+ swatchColor: BRAND_ON_LIGHT,
+ title: lang === "es" ? "Transformers y seq-to-seq" : "Transformers & seq-to-seq",
+ count: "15 + 9",
+ body: lang === "es"
+ ? <>Clasificadores y modelos de traducción neural con métricas BLEU · ChrF · TER nativas.
+ : <>Classifiers and neural translation models with native BLEU · ChrF · TER metrics.,
+ tags: ["DistilBERT","DeBERTa-v3","ModernBERT","NLLB","OpusMT","+19"],
+ countColor: BRAND_ON_LIGHT,
+ },
+ {
+ kind: lang === "es" ? "Modelos generativos" : "Generative models",
+ swatchColor: BRAND_ON_LIGHT,
+ title: lang === "es" ? "LLMs locales" : "Local LLMs",
+ count: "5",
+ body: lang === "es"
+ ? "Llama, Mistral, Mixtral, Qwen y SmolLM con pesos abiertos. Generación como tarea nativa."
+ : "Llama, Mistral, Mixtral, Qwen and SmolLM on open weights. Generation as a native task.",
+ tags: ["Llama","Mistral","Mixtral","Qwen","SmolLM"],
+ countColor: BRAND_ON_LIGHT,
+ },
+ {
+ kind: lang === "es" ? "Visión generativa" : "Generative vision",
+ swatchColor: BRAND_ON_LIGHT,
+ title: lang === "es" ? "Texto a imagen" : "Text to image",
+ count: "11",
+ body: lang === "es"
+ ? "PixArt-Sigma, SDXL, Stable Diffusion y variantes ControlNet. Detección automática de CUDA."
+ : "PixArt-Sigma, SDXL, Stable Diffusion and ControlNet variants. Automatic CUDA detection.",
+ tags: ["PixArt-Sigma","SDXL","SD v3","SD v2","ControlNet","+6"],
+ countColor: BRAND_ON_LIGHT,
+ },
+ ].map(c => (
+
+
+ ))}
+
+ {c.kind}
+
+ {c.title}
+ {c.count}
+
+ {c.tags.map(tag => (
+
+