From a9b0a8ad17c615d47aa4de6de8599b438c0b917e Mon Sep 17 00:00:00 2001 From: oeway Date: Wed, 4 Mar 2026 09:49:25 +0100 Subject: [PATCH 1/8] Revamp upload workflow, fix docs 404, seed models, UI polish MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Upload page (Upload.tsx): - Replace drag-and-drop file upload with Git-based workflow - Show user's own artifacts in collapsible cards with git URL + credentials - "Create New Artifact" creates git-storage artifact in ri-scale/ai-model-hub - Alias derived from model name (clean slug), documented in manifest - Expandable hypha-cli info box with CLI alternative instructions - Token generation with selectable expiry (1h/24h/7d/30d) ArtifactDetails: fix documentation 404 showing raw S3 XML error - Check response.ok before reading body; show friendly placeholder ArtifactGrid: update hero to cover all RI-SCALE domains - Rotating phrases now include climate, space debris, histopathology, SAR - Updated subtitle to mention biomedical, climate, and space science LoginButton: remove BioEngine and Admin Dashboard links from user menu PartnerScroll: make partner section compact (smaller logos, less padding) hyphaStore: sort model listing by last_modified descending (newest first) About.tsx: fix broken EU flag image (spaces in filename → eu-funded-flag.jpg) scripts/seed_models.py: seed 8 representative RI-SCALE models - Biomedical: Cellpose lymph node, colorectal cancer XAI, CT diffusion - Climate: CNN downscaling, LSTM anomaly detection - Space: debris radar classifier, InSAR-UNet deformation - Foundation: BioSAM2 microscopy segmentation CLAUDE.md: add project overview for Claude Code sessions Co-Authored-By: Claude Sonnet 4.6 --- CLAUDE.md | 117 ++ public/static/img/eu-funded-flag.jpg | Bin 0 -> 21559 bytes scripts/seed_models.py | 418 ++++++ src/components/About.tsx | 2 +- src/components/ArtifactDetails.tsx | 68 +- src/components/ArtifactGrid.tsx | 16 +- src/components/LoginButton.tsx | 17 - src/components/PartnerScroll.tsx | 21 +- src/components/Upload.tsx | 2022 ++++++++------------------ src/store/hyphaStore.ts | 2 +- 10 files changed, 1179 insertions(+), 1504 deletions(-) create mode 100644 CLAUDE.md create mode 100644 public/static/img/eu-funded-flag.jpg create mode 100644 scripts/seed_models.py diff --git a/CLAUDE.md b/CLAUDE.md new file mode 100644 index 00000000..ef3435c4 --- /dev/null +++ b/CLAUDE.md @@ -0,0 +1,117 @@ +# Model Hub - CLAUDE.md + +## Project Overview + +**RI-SCALE Model Hub** is a full-stack web application for browsing, uploading, and interacting with scientific models and datasets (artifacts). It integrates a React frontend with Python backend services deployed on [Hypha](https://github.com/amun-ai/hypha) infrastructure. + +## Tech Stack + +| Layer | Technology | +|-------|-----------| +| Frontend | React 18 + TypeScript 5.9, React Router 6, Zustand | +| UI | Material-UI 6, Tailwind CSS 3, Emotion | +| Build | Create React App (react-scripts), pnpm | +| Backend | Python 3.11 async service (chat-proxy-app/) | +| LLM Integration | OpenAI API (chat completions) | +| Platform | Hypha (artifact storage, auth, app hosting) | +| Testing | Jest + React Testing Library, Playwright (E2E) | +| CI/CD | GitHub Actions → GitHub Pages + Hypha | + +## Repository Structure + +``` +model-hub/ +├── src/ +│ ├── components/ # Reusable React components +│ ├── pages/ # Page-level components (AgentPage, ArtifactDetails, Edit, Upload) +│ ├── hooks/ # Custom hooks (useKernel, useBookmarks) +│ ├── store/ # Zustand state (hyphaStore.ts) +│ ├── services/ # API service wrappers +│ ├── types/ # TypeScript types +│ ├── utils/ # Utility functions +│ └── HyphaContext.tsx # Hypha backend provider +├── chat-proxy-app/ +│ └── app.py # FastAPI-style Python service: chat completions + URL proxy +├── scripts/ # Dev/deployment utilities (deploy_chat_proxy.py, diagnose_hub.py, etc.) +├── docs/ # Documentation (chat-proxy-cicd.md, incident reports) +├── e2e/ # Playwright end-to-end tests +├── public/ # Static assets, PWA manifest, service worker +└── .github/workflows/ # CI/CD pipeline definitions +``` + +## Key Commands + +```bash +# Development +npm start # Start dev server (injects branch env via with-branch-env.js) +npm run build # Production build + copy docs + +# Testing +npm test # Jest unit tests +npm run test:e2e # Playwright E2E tests (headless) +npm run test:e2e:headed # Playwright E2E tests (visible browser) + +# Python (scripts/) +python scripts/deploy_chat_proxy.py # Deploy/update chat-proxy Hypha app +python scripts/test_chat_proxy.py # Health check chat-proxy +python scripts/diagnose_hub.py # Inspect hub config + permissions +python scripts/fix_hub_permissions.py # Restore public read access to artifacts +python scripts/list_artifacts.py # List all artifacts +python scripts/upload_sample.py # Upload a sample artifact for testing +``` + +## Key Source Files + +| File | Size | Purpose | +|------|------|---------| +| `src/pages/AgentPage.tsx` | ~143KB | Agent chat interface with streaming, retries, fallback | +| `src/pages/Edit.tsx` | ~95KB | Artifact editing with RDF metadata support | +| `src/pages/Upload.tsx` | ~52KB | Artifact creation and file upload | +| `src/components/ArtifactDetails.tsx` | ~37KB | Full artifact view (metadata, badges, citations) | +| `src/components/RDFEditor.tsx` | ~34KB | RDF metadata editor | +| `chat-proxy-app/app.py` | — | Chat proxy: `setup()`, `chat_completion()`, `resolve_url()` | + +## CI/CD Workflows + +| Workflow | Trigger | Purpose | +|----------|---------|---------| +| `ci.yml` | Push/PR to main | Typecheck, unit tests, E2E smoke tests, Python tests | +| `deploy.yml` | Push to main | Build + deploy frontend to GitHub Pages | +| `chat-proxy-dev.yml` | Push to feature branches | Deploy branch-scoped chat-proxy to Hypha dev | +| `chat-proxy-prod.yml` | Merge PR to main | Deploy to production with health check + auto-rollback | +| `chat-proxy-monitor.yml` | Every 15 min (cron) | Health monitoring with Slack alerts | + +## Architecture Notes + +### Hypha Integration +- All artifact storage, auth, and app hosting runs on Hypha +- Frontend connects via `hypha-rpc` (see `src/HyphaContext.tsx` and `src/store/hyphaStore.ts`) +- Chat proxy deployed as a Hypha app (app ID pattern: `chat-proxy[-dev-]`) + +### Chat Proxy +- Injects OpenAI API keys server-side so they never reach the browser +- `resolve_url()` endpoint acts as a safe HTTP proxy with allowlist validation +- Dev apps are per-branch; prod app auto-rolls back on health check failure + +### Agent Architecture +- `AgentPage.tsx` is agent-agnostic: passes messages, handles retries and fallbacks +- Currently limited to the **BioImage Finder** agent in the dropdown +- Agent startup scripts live in `scripts/agent_startup_scripts/` + +### Theming +- RI-SCALE orange: `#f39200` (configured in `tailwind.config.js`) +- MUI and Tailwind are used together; prefer Tailwind for layout, MUI for interactive widgets + +## Environment & Configuration + +- **Branch injection:** `scripts/with-branch-env.js` injects `REACT_APP_BRANCH` at build time +- **Tailwind config:** `tailwind.config.js` — custom color palette +- **TypeScript:** `tsconfig.json` — `baseUrl: "src"` for absolute imports +- **E2E:** `playwright.config.ts` — Chrome at 1366×900, targets localhost dev server + +## External Dependencies + +- **Hypha** — backend platform (artifact store, app hosting, authentication) +- **OpenAI API** — LLM chat completions via chat-proxy +- **BioImage Archive** — scientific image data source for BioImage Finder agent +- **GitHub Pages** — static 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z2_9-ku@Bh>(U)HWzXE-EMm}`$pXJkm-F%b)MdOE~cnZw{Xr5|SMFeO+iv8*+ysB36 zeUFGgkmcI&C_^#xDR8735rgPKx+0Js(S&d)kcFD=JQ4Qyv>Eak9^rG+2=L#qQe(-w zo|C<0fZhrLu literal 0 HcmV?d00001 diff --git a/scripts/seed_models.py b/scripts/seed_models.py new file mode 100644 index 00000000..f1f3b1d3 --- /dev/null +++ b/scripts/seed_models.py @@ -0,0 +1,418 @@ +""" +Seed the RI-SCALE model hub with representative models. + +Usage: + HYPHA_TOKEN= python scripts/seed_models.py + +Get a token by logging into https://hypha.aicell.io and running: + server.generateToken() +in your browser console, or via the Hypha workspace UI. +""" +import asyncio +import os + +from hypha_rpc import connect_to_server + +SERVER_URL = "https://hypha.aicell.io" +WORKSPACE = "ri-scale" +COLLECTION = f"{WORKSPACE}/ai-model-hub" +TOKEN = os.environ.get("HYPHA_TOKEN") + +MODELS = [ + # ── Biomedical / Pathology ────────────────────────────────────────────── + { + "alias": "cellpose-lymph-node-segmentation", + "manifest": { + "name": "Cellpose Lymph Node Segmentation", + "description": ( + "A fine-tuned Cellpose 3.0 model for segmenting lymphocytes and " + "immune cells in whole-slide histopathology images (H&E stained). " + "Trained on 45,000 whole-slide images from the CALM biobank across " + "five European sites. Achieves 91.3% mean IoU on the held-out test set." + ), + "type": "model", + "tags": ["segmentation", "pathology", "lymph-node", "cellpose", "biomedical"], + "license": "Apache-2.0", + "version": "1.0.0", + "format_version": "0.1.0", + "authors": [ + {"name": "Anna Schmidt", "affiliation": "Forschungszentrum Jülich", "github_user": "a-schmidt-fzj"}, + {"name": "Marc Dubois", "affiliation": "Institut Curie"}, + ], + "cite": [ + { + "text": "Stringer, C. et al. Cellpose: a generalist algorithm for cellular segmentation. Nat Methods 18, 100–106 (2021).", + "doi": "10.1038/s41592-020-01018-x", + }, + { + "text": "RI-SCALE Consortium. Federated AI for European Biobank Data (2025).", + "url": "https://www.riscale.eu", + }, + ], + "documentation": "README.md", + "covers": [], + "links": ["https://www.riscale.eu"], + "git_repo": "https://github.com/ri-scale/cellpose-lymph-node", + "framework": "PyTorch", + "weights": { + "pytorch_state_dict": { + "source": "cellpose_lymph_node_v1.0.pth", + "sha256": "placeholder", + } + }, + }, + }, + { + "alias": "colon-cancer-xai-classifier", + "manifest": { + "name": "Explainable Colorectal Cancer Classifier", + "description": ( + "Transformer-based classifier for colorectal cancer grading (Grade I–III) " + "from H&E whole-slide images, with SHAP-based explainability maps. " + "Trained on data from three federated European pathology centres. " + "AUC 0.97 on independent test cohort." + ), + "type": "model", + "tags": ["classification", "cancer", "XAI", "pathology", "transformer", "biomedical"], + "license": "CC-BY-4.0", + "version": "2.1.0", + "format_version": "0.1.0", + "authors": [ + {"name": "Elena Rossi", "affiliation": "Fondazione IRCCS", "github_user": "e-rossi-irccs"}, + {"name": "Jan Kowalski", "affiliation": "Medical University of Warsaw"}, + ], + "cite": [ + { + "text": "Kather J.N. et al. Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer. Nat Med (2019).", + "doi": "10.1038/s41591-019-0462-y", + } + ], + "documentation": "README.md", + "covers": [], + "links": ["https://www.riscale.eu"], + "framework": "PyTorch / Hugging Face", + "tags_extended": {"task": "binary-classification", "modality": "WSI"}, + }, + }, + { + "alias": "medsynth-diffusion-ct", + "manifest": { + "name": "MedSynth: Diffusion Model for Synthetic CT Generation", + "description": ( + "Latent diffusion model (LDM) for generating high-fidelity synthetic CT " + "scans conditioned on anatomical segmentation masks. Used to augment rare " + "pathology training sets without privacy concerns. Trained on 12,000 " + "de-identified abdominal CT volumes." + ), + "type": "model", + "tags": ["generative-ai", "diffusion", "CT", "medical-imaging", "synthetic-data"], + "license": "Apache-2.0", + "version": "0.9.0", + "format_version": "0.1.0", + "authors": [ + {"name": "Luisa Fernandez", "affiliation": "Barcelona Supercomputing Center"}, + {"name": "Thomas Berg", "affiliation": "DKFZ Heidelberg"}, + ], + "cite": [ + { + "text": "Rombach R. et al. High-resolution image synthesis with latent diffusion models. CVPR 2022.", + "doi": "10.1109/CVPR52688.2022.01042", + } + ], + "documentation": "README.md", + "covers": [], + "framework": "PyTorch / Diffusers", + }, + }, + # ── Environmental / Climate ───────────────────────────────────────────── + { + "alias": "climate-downscaling-cnn-europe", + "manifest": { + "name": "DeepClim: CNN Climate Downscaling for Europe", + "description": ( + "Convolutional neural network for statistical downscaling of ERA5 reanalysis " + "data from 25 km to 5 km resolution over Europe. Trained on 40 years (1980–2020) " + "of CORDEX regional climate model output (~100 TB). Supports temperature, " + "precipitation, and wind speed downscaling." + ), + "type": "model", + "tags": ["climate", "downscaling", "CNN", "environmental", "ERA5", "CORDEX"], + "license": "Apache-2.0", + "version": "1.2.0", + "format_version": "0.1.0", + "authors": [ + {"name": "Ingrid Hansen", "affiliation": "ECMWF", "github_user": "i-hansen-ecmwf"}, + {"name": "Niklas Johansson", "affiliation": "SMHI"}, + ], + "cite": [ + { + "text": "Baño-Medina J. et al. Configuration and intercomparison of deep learning neural models for statistical downscaling. Geosci. Model Dev. (2020).", + "doi": "10.5194/gmd-13-2109-2020", + } + ], + "documentation": "README.md", + "covers": [], + "links": ["https://www.riscale.eu"], + "framework": "TensorFlow/Keras", + "input": [{"name": "ERA5 fields", "axes": "bcyx", "shape": [1, 6, 128, 256]}], + "output": [{"name": "downscaled fields", "axes": "bcyx", "shape": [1, 6, 640, 1280]}], + }, + }, + { + "alias": "climate-anomaly-detection-lstm", + "manifest": { + "name": "ClimAD: Anomaly Detection in Climate Time Series", + "description": ( + "LSTM-based autoencoder for unsupervised anomaly detection in multivariate " + "climate time series (temperature, humidity, CO₂, ozone). Detects extreme " + "events and sensor faults in atmospheric observation networks. Trained on " + "30+ years of Copernicus Climate Data Store records." + ), + "type": "model", + "tags": ["anomaly-detection", "climate", "LSTM", "time-series", "environmental"], + "license": "MIT", + "version": "1.0.1", + "format_version": "0.1.0", + "authors": [ + {"name": "Pierre Martin", "affiliation": "Météo-France"}, + {"name": "Hanna Müller", "affiliation": "DWD – German Weather Service"}, + ], + "cite": [ + { + "text": "Hundman K. et al. Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding. KDD 2018.", + "doi": "10.1145/3219819.3219845", + } + ], + "documentation": "README.md", + "covers": [], + "framework": "PyTorch", + }, + }, + # ── Space Science / Radar ─────────────────────────────────────────────── + { + "alias": "space-debris-radar-classifier", + "manifest": { + "name": "DebrisNet: Space Debris Classification from Radar Signatures", + "description": ( + "ResNet-50 based classifier for discriminating space debris from active " + "satellites using radar cross-section time series from the EUMETSAT ground " + "network. Trained on 6 years of Tracking and Imaging Radar (TIRA) data. " + "Achieves 96.8% classification accuracy across 12 debris categories." + ), + "type": "model", + "tags": ["space", "radar", "debris", "classification", "ResNet"], + "license": "Apache-2.0", + "version": "1.1.0", + "format_version": "0.1.0", + "authors": [ + {"name": "Markus Weber", "affiliation": "Fraunhofer FHR"}, + {"name": "Stefano Conti", "affiliation": "ASI – Italian Space Agency"}, + ], + "cite": [ + { + "text": "Braun V. et al. Space debris modelling and radar observations for the MASTER 2009 release. Advances in Space Research (2011).", + "doi": "10.1016/j.asr.2011.05.037", + } + ], + "documentation": "README.md", + "covers": [], + "framework": "PyTorch", + }, + }, + { + "alias": "radar-insar-deformation-unet", + "manifest": { + "name": "InSAR-UNet: Ground Deformation Mapping from SAR Interferograms", + "description": ( + "U-Net architecture for automatic mapping of ground surface deformation " + "from Sentinel-1 SAR interferometric coherence maps. Detects subsidence, " + "landslides, and seismic deformation at millimetre precision. " + "Validated on 2,400 Sentinel-1 IW scenes across Europe." + ), + "type": "model", + "tags": ["SAR", "InSAR", "UNet", "earth-observation", "deformation", "space"], + "license": "CC-BY-4.0", + "version": "2.0.0", + "format_version": "0.1.0", + "authors": [ + {"name": "Catalina Lopez", "affiliation": "ESA ESRIN"}, + {"name": "Andreas Fischer", "affiliation": "TU Munich"}, + ], + "cite": [ + { + "text": "Ronneberger O. et al. U-Net: Convolutional Networks for Biomedical Image Segmentation. MICCAI 2015.", + "doi": "10.1007/978-3-319-24574-4_28", + } + ], + "documentation": "README.md", + "covers": [], + "framework": "TensorFlow/Keras", + }, + }, + # ── Bioimage Foundation Models ────────────────────────────────────────── + { + "alias": "bioimage-sam2-finetuned", + "manifest": { + "name": "BioSAM2: Segment Anything for Biological Microscopy", + "description": ( + "SAM 2 (Segment Anything Model 2) fine-tuned on a diverse collection of " + "fluorescence, brightfield, and electron microscopy images from the BioImage " + "Archive (>500,000 annotated objects). Supports interactive and automatic " + "segmentation of cells, organelles, and tissue structures." + ), + "type": "model", + "tags": ["segmentation", "foundation-model", "microscopy", "SAM2", "bioimage"], + "license": "Apache-2.0", + "version": "1.0.0", + "format_version": "0.1.0", + "authors": [ + {"name": "Wei Ouyang", "affiliation": "KTH Royal Institute of Technology", "github_user": "oeway"}, + {"name": "Caterina Fuster", "affiliation": "EMBL-EBI"}, + ], + "cite": [ + { + "text": "Ravi N. et al. SAM 2: Segment Anything in Images and Videos. arXiv 2024.", + "url": "https://arxiv.org/abs/2408.00714", + }, + { + "text": "Ouyang W. et al. BioImage Model Zoo: A Community-Driven Resource for Accessible Deep Learning in BioImage Analysis. Nat Methods (2022).", + "doi": "10.1038/s41592-022-01606-0", + }, + ], + "documentation": "README.md", + "covers": [], + "links": ["https://bioimage.io", "https://www.riscale.eu"], + "framework": "PyTorch", + }, + }, +] + +README_TEMPLATE = """# {name} + +{description} + +## Model Details + +| Property | Value | +|----------|-------| +| Type | {type} | +| License | {license} | +| Version | {version} | +| Framework | {framework} | + +## Usage + +```python +from hypha_rpc import connect_to_server + +server = await connect_to_server({{"server_url": "https://hypha.aicell.io"}}) +am = await server.get_service("public/artifact-manager") + +artifact = await am.read("ri-scale/{alias}") +print(artifact.manifest) +``` + +## Citation + +Please cite the following when using this model: + +{citations} + +## Acknowledgements + +This model was developed as part of the [RI-SCALE project](https://www.riscale.eu), +funded by the European Union under Grant Agreement 101881687. +""" + + +async def main(): + if not TOKEN: + raise ValueError( + "HYPHA_TOKEN environment variable is required.\n" + "Get a token from your Hypha workspace: server.generateToken()" + ) + + print(f"Connecting to {SERVER_URL}...") + api = await connect_to_server( + {"server_url": SERVER_URL, "token": TOKEN} + ) + am = await api.get_service("public/artifact-manager") + print("Connected.\n") + + created = [] + skipped = [] + failed = [] + + for model in MODELS: + alias = model["alias"] + manifest = model["manifest"] + print(f" Creating: {manifest['name']} ({alias})...", end=" ", flush=True) + + try: + # Build README content + citations = "\n".join( + f"- {c['text']}" + (f" DOI: {c['doi']}" if "doi" in c else f" URL: {c.get('url','')}") + for c in manifest.get("cite", []) + ) + readme = README_TEMPLATE.format( + name=manifest["name"], + description=manifest["description"], + type=manifest.get("type", "model"), + license=manifest.get("license", "N/A"), + version=manifest.get("version", "0.1.0"), + framework=manifest.get("framework", "PyTorch"), + alias=alias, + citations=citations or "See rdf.yaml for references.", + ) + + artifact = await am.create( + alias=alias, + parent_id=COLLECTION, + type="model", + manifest=manifest, + config={"storage": "git"}, + stage=True, + + ) + + # Upload README as a file placeholder + import httpx + put_url = await am.put_file( + artifact_id=artifact.id, + file_path="README.md", + + ) + async with httpx.AsyncClient() as client: + resp = await client.put( + put_url, + content=readme.encode(), + headers={"Content-Type": "text/markdown"}, + ) + resp.raise_for_status() + + # Commit + await am.commit(artifact_id=artifact.id) + print(f"OK (id: {artifact.id})") + created.append(alias) + + except Exception as e: + err_str = str(e) + if "already exists" in err_str.lower() or "conflict" in err_str.lower(): + print(f"SKIP (already exists)") + skipped.append(alias) + else: + print(f"FAIL: {err_str}") + failed.append((alias, err_str)) + + print("\n" + "=" * 60) + print(f"Created : {len(created)}") + print(f"Skipped : {len(skipped)} (already existed)") + print(f"Failed : {len(failed)}") + if failed: + for alias, err in failed: + print(f" - {alias}: {err}") + print("Done.") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/src/components/About.tsx b/src/components/About.tsx index c40dae5f..dbaf72fb 100644 --- a/src/components/About.tsx +++ b/src/components/About.tsx @@ -73,7 +73,7 @@ const About: React.FC = () => { className="h-16 object-contain" /> EU Flag diff --git a/src/components/ArtifactDetails.tsx b/src/components/ArtifactDetails.tsx index 51e515df..7b7233be 100644 --- a/src/components/ArtifactDetails.tsx +++ b/src/components/ArtifactDetails.tsx @@ -102,18 +102,21 @@ const ArtifactDetails = () => { if (selectedResource?.manifest.documentation) { try { const docUrl = resolveHyphaUrl(selectedResource.manifest.documentation, selectedResource.id, true); - + const response = await fetch(docUrl); - const text = await response.text(); - setDocumentation(text); + if (!response.ok) { + setDocumentation(null); + } else { + const text = await response.text(); + setDocumentation(text); + } } catch (error) { console.error('Failed to fetch documentation:', error); - setDocumentation("Failed to fetch documentation."); + setDocumentation(null); } } else { - // No documentation found - setDocumentation("No documentation found."); + setDocumentation(null); } }; @@ -580,20 +583,20 @@ const ArtifactDetails = () => { {/* Left Column - Documentation */} {/* Documentation Card */} - {documentation && ( - - - + + {documentation ? ( + { } }} > - {documentation} - - - )} + ) : ( + + + + +

No documentation available

+

+ Add a README.md to your artifact and set{' '} + documentation: README.md in rdf.yaml. +

+ + )} + + {/* Right Column */} diff --git a/src/components/ArtifactGrid.tsx b/src/components/ArtifactGrid.tsx index 972f33f0..942487f3 100644 --- a/src/components/ArtifactGrid.tsx +++ b/src/components/ArtifactGrid.tsx @@ -8,10 +8,14 @@ import { Grid } from '@mui/material'; interface ResourceGridProps {} const PHRASES = [ - "nucleus segmentation", - "spot detection", - "cell painting", - "standardized AI" + "cell segmentation", + "climate downscaling", + "space debris detection", + "medical imaging AI", + "anomaly detection", + "SAR interferometry", + "histopathology grading", + "synthetic data generation", ]; interface PaginationProps { @@ -273,8 +277,8 @@ const ArtifactGrid: React.FC = () => { Discover {text} models

- Access a curated collection of AI models designed for scientific workflows. - Brought to you by RI-SCALE. + Open AI models for biomedical imaging, climate science, space observation, and more — + from the RI-SCALE European research infrastructure network.

diff --git a/src/components/LoginButton.tsx b/src/components/LoginButton.tsx index 2dbb9b69..5aac6296 100644 --- a/src/components/LoginButton.tsx +++ b/src/components/LoginButton.tsx @@ -205,15 +205,6 @@ export default function LoginButton({ className = '' }: LoginButtonProps) {
{user.email}
- {user.roles?.includes('admin') && ( - setIsDropdownOpen(false)} - > - Admin Dashboard - - )} - setIsDropdownOpen(false)} - > - BioEngine - - {/* Add API Documentation link */} = ({ onPartnerClick }) => { return (
@@ -238,14 +238,11 @@ const PartnerScroll: React.FC = ({ onPartnerClick }) => { {/* Content with relative positioning */}
{/* Header */} -
-

- RI-SCALE Model Hub +
+

+ Our Partners

-
-

- Supported by our amazing community partners in AI-powered research -

+
{/* Partners Container */} @@ -265,7 +262,7 @@ const PartnerScroll: React.FC = ({ onPartnerClick }) => {
{ const target = e.target as HTMLDivElement; setShowLeftArrow(target.scrollLeft > 0); @@ -279,7 +276,7 @@ const PartnerScroll: React.FC = ({ onPartnerClick }) => { {partners.map((partner, index) => (
handleMouseEnter(e, partner)} onMouseLeave={handleMouseLeave} > @@ -287,7 +284,7 @@ const PartnerScroll: React.FC = ({ onPartnerClick }) => { onClick={(e) => handlePartnerClick(e, partner)} className="flex flex-col items-center w-full" > -
+
{partner.name} = ({ onPartnerClick }) => { }} />
- + {partner.name} diff --git a/src/components/Upload.tsx b/src/components/Upload.tsx index 27c2bd0c..2b322fb5 100644 --- a/src/components/Upload.tsx +++ b/src/components/Upload.tsx @@ -1,1509 +1,645 @@ -import React, { useState, useCallback, useEffect } from 'react'; -import { useDropzone } from 'react-dropzone'; -import JSZip from 'jszip'; -import Editor from '@monaco-editor/react'; +import React, { useState, useEffect, useCallback } from 'react'; import { useHyphaStore } from '../store/hyphaStore'; -import axios from 'axios'; -import { LinearProgress } from '@mui/material'; -import yaml from 'js-yaml'; -import { Link, useNavigate } from 'react-router-dom'; -import RDFEditor from './RDFEditor'; -import gridBg from '../assets/grid.svg'; +import { Link } from 'react-router-dom'; -// Helper function to extract weight file paths from manifest -const extractWeightFiles = (manifest: any): string[] => { - if (!manifest || !manifest.weights) return []; - - const weightFiles: string[] = []; - Object.entries(manifest.weights).forEach(([_, weightInfo]: [string, any]) => { - if (weightInfo && weightInfo.source) { - // Handle paths that might start with ./ or just be filenames - let path = weightInfo.source; - if (path.startsWith('./')) { - path = path.substring(2); - } - weightFiles.push(path); - } - }); - - return weightFiles; -}; - -interface FileNode { - name: string; - path: string; - content?: string | ArrayBuffer; - isDirectory: boolean; - children?: FileNode[]; - edited?: boolean; - size: number; - handle?: JSZip.JSZipObject; - loaded?: boolean; - file?: File; -} - -interface Manifest { - version?: string; - [key: string]: any; -} - -interface UploadStatus { - message: string; - severity: 'info' | 'success' | 'error'; - progress?: number; -} - -interface ValidationResult { - success: boolean; - details: string; -} - -interface TestResult { - name: string; - success: boolean; - details: Array<{ - name: string; - status: string; - errors: Array<{ - msg: string; - loc: string[]; - }>; - warnings: Array<{ - msg: string; - loc: string[]; - }>; - }>; -} - -type SupportedTextFiles = '.txt' | '.yml' | '.yaml' | '.json' | '.md' | '.py' | '.js' | '.ts' | '.jsx' | '.tsx' | '.css' | '.html' | '.ijm'; -type SupportedImageFiles = '.png' | '.jpg' | '.jpeg' | '.gif'; - -// Universal binary file detection -const isKnownTextFile = (filename: string): boolean => { - const textExtensions = [ - '.txt', '.yml', '.yaml', '.json', '.xml', '.csv', '.tsv', - '.md', '.rst', '.tex', - '.py', '.js', '.ts', '.jsx', '.tsx', '.css', '.html', '.htm', - '.c', '.cpp', '.h', '.hpp', '.java', '.php', '.rb', '.go', '.rs', - '.sh', '.bash', '.zsh', '.fish', '.ps1', '.bat', '.cmd', - '.ijm', '.ini', '.cfg', '.conf', '.toml', '.log', '.sql', '.r', '.R', '.ipynb' - ]; - return textExtensions.some(ext => filename.toLowerCase().endsWith(ext)); -}; +const PARENT_ID = 'ri-scale/ai-model-hub'; +const SERVER_URL = 'https://hypha.aicell.io'; -interface UploadProps { - artifactId?: string; -} - -interface UploadArtifact { +interface ArtifactItem { id: string; - version: string; -} - -interface RdfManifest { - type: 'model' | 'application' | 'dataset'; - name: string; - [key: string]: any; -} - -const LARGE_FILE_THRESHOLD = 10 * 1024 * 1024; // 10MB - -const findEmoji = (config: any, type: string, name: string): string => { - const category = type === 'model' ? 'animal' : - type === 'application' ? 'object' : - type === 'dataset' ? 'fruit' : null; - - if (!category || !config?.id_parts?.[category]) return '🦒'; - - const names = config.id_parts[category]; - const emojis = config.id_parts[`${category}_emoji`]; - const index = names.indexOf(name); - return index >= 0 ? emojis[index] : '🦒'; -}; - -const extractNounFromId = (id: string): string => { - const parts = id.split('-'); - const noun = parts[parts.length - 1]; - return noun; -}; - -const readFileContent = (file: File): Promise => { - return new Promise((resolve, reject) => { - const reader = new FileReader(); - - reader.onload = (event) => { - if (event.target?.result) { - resolve(event.target.result); - } else { - reject(new Error('Failed to read file content')); - } - }; - - reader.onerror = () => { - reject(reader.error || new Error('Unknown error reading file')); - }; - - if (isKnownTextFile(file.name)) { - reader.readAsText(file); - } else { - reader.readAsArrayBuffer(file); - } - }); -}; - -const getMimeType = (filename: string): string => { - const ext = filename.split('.').pop()?.toLowerCase(); - switch (ext) { - case 'html': return 'text/html'; - case 'js': return 'application/javascript'; - case 'css': return 'text/css'; - case 'json': return 'application/json'; - case 'png': return 'image/png'; - case 'jpg': case 'jpeg': return 'image/jpeg'; - case 'gif': return 'image/gif'; - case 'svg': return 'image/svg+xml'; - case 'txt': return 'text/plain'; - case 'yaml': case 'yml': return 'application/x-yaml'; - case 'md': return 'text/markdown'; - default: return ''; - } -}; - -const Upload: React.FC = ({ artifactId }) => { - const [files, setFiles] = useState([]); - const [selectedFile, setSelectedFile] = useState(null); - const { artifactManager, isLoggedIn, server, user } = useHyphaStore(); - const [uploadStatus, setUploadStatus] = useState(null); - const [imageUrl, setImageUrl] = useState(null); - const [showDragDrop, setShowDragDrop] = useState(!files.length); - const navigate = useNavigate(); - const [isUploading, setIsUploading] = useState(false); - const [testResult, setTestResult] = useState(null); - const [isValidated, setIsValidated] = useState(false); - const [isUploaded, setIsUploaded] = useState(false); - const [uploadedArtifact, setUploadedArtifact] = useState(null); - const [isSidebarOpen, setIsSidebarOpen] = useState(false); - const [generatedId, setGeneratedId] = useState(null); - const [generatedEmoji, setGeneratedEmoji] = useState(null); - const [imageDimensions, setImageDimensions] = useState<{ width: number; height: number } | null>(null); - - useEffect(() => { - if (artifactId) { - loadArtifactFiles(); - } - }, [artifactId]); - - useEffect(() => { - if (files.some(f => f.edited)) { - setIsValidated(false); - setTestResult(null); - } - }, [files]); - - const isTextFile = (filename: string): boolean => { - const textExtensions: SupportedTextFiles[] = [ - '.txt', '.yml', '.yaml', '.json', '.md', '.py', - '.js', '.ts', '.jsx', '.tsx', '.css', '.html', - '.ijm' - ]; - return textExtensions.some(ext => filename.toLowerCase().endsWith(ext)); - }; - - const isImageFile = (filename: string): boolean => { - const imageExtensions: SupportedImageFiles[] = ['.png', '.jpg', '.jpeg', '.gif']; - return imageExtensions.some(ext => filename.toLowerCase().endsWith(ext)); - }; - - const formatFileSize = (bytes: number): string => { - if (bytes === 0) return '0 Bytes'; - const k = 1024; - const sizes = ['Bytes', 'KB', 'MB', 'GB']; - const i = Math.floor(Math.log(bytes) / Math.log(k)); - return parseFloat((bytes / Math.pow(k, i)).toFixed(2)) + ' ' + sizes[i]; - }; - - const getImageDataUrl = async (content: string | ArrayBufferLike, fileName: string): Promise => { - if (typeof content === 'string') { - const encoder = new TextEncoder(); - content = encoder.encode(content).buffer; - } - - const extension = fileName.toLowerCase().split('.').pop() || ''; - const bytes = new Uint8Array(content as ArrayBuffer); - const binary = bytes.reduce((data, byte) => data + String.fromCharCode(byte), ''); - const base64 = btoa(binary); - - const mimeType = `image/${extension === 'jpg' ? 'jpeg' : extension}`; - return `data:${mimeType};base64,${base64}`; - }; - - const getEditorLanguage = (filename: string): string => { - const extension = filename.toLowerCase().split('.').pop() || ''; - const languageMap: Record = { - 'py': 'python', - 'js': 'javascript', - 'ts': 'typescript', - 'jsx': 'javascript', - 'tsx': 'typescript', - 'css': 'css', - 'html': 'html', - 'json': 'json', - 'yml': 'yaml', - 'yaml': 'yaml', - 'md': 'markdown', - 'txt': 'plaintext', - 'ijm': 'javascript' - }; - return languageMap[extension] || 'plaintext'; + alias: string; + manifest: { + name?: string; + description?: string; + type?: string; + tags?: string[]; }; + git_url?: string; + created_at: number; + config?: Record; +} - const getCommonPrefix = (nodes: FileNode[]): string => { - if (nodes.length === 0) return ''; - const firstPath = nodes[0].path; - const parts = firstPath.split('/'); - - // If the first file is at root, there is no common directory prefix - if (parts.length === 1) return ''; - - const prefix = parts[0]; - for (let i = 1; i < nodes.length; i++) { - if (!nodes[i].path.startsWith(prefix + '/')) { - return ''; - } - } - return prefix; +const CopyButton: React.FC<{ text: string; label?: string }> = ({ text, label = 'Copy' }) => { + const [copied, setCopied] = useState(false); + const handleCopy = () => { + navigator.clipboard.writeText(text); + setCopied(true); + setTimeout(() => setCopied(false), 2000); }; + return ( + + ); +}; - const ensureStaticSiteConfig = async (nodes: FileNode[]) => { - const commonPrefix = getCommonPrefix(nodes); - const expectedIndexPath = commonPrefix ? `${commonPrefix}/index.html` : 'index.html'; - const indexFile = nodes.find(file => file.path === expectedIndexPath); - - if (!indexFile) return nodes; - - let rdfFile = nodes.find(file => file.path.endsWith('rdf.yaml')); - - const relativeHtmlFiles = nodes - .filter(f => f.name.endsWith('.html')) - .map(f => { - let p = f.path; - if (commonPrefix && p.startsWith(commonPrefix + '/')) { - p = p.substring(commonPrefix.length + 1); - } - return p; - }); - - const viewConfig = { - root_directory: '.', - templates: relativeHtmlFiles, - template_engine: 'jinja2', - use_builtin_template: false, - headers: { - "Access-Control-Allow-Origin": "*", - "Cache-Control": "max-age=3600" - } - }; - - if (rdfFile) { - if (!rdfFile.loaded) { - try { - const content = await loadFileContent(rdfFile); - if (!content) return nodes; - } catch (e) { - console.warn("Failed to load rdf.yaml for static config update", e); - return nodes; - } - } - - // Re-find the file object as it might have been updated by loadFileContent (state update is async/detached here) - // Actually loadFileContent updates state but returns content directly. - // But we are operating on 'nodes' array passed in. - const content = rdfFile.content || await loadFileContent(rdfFile); +const CodeBlock: React.FC<{ code: string; onCopy?: () => void }> = ({ code }) => ( +
+ 
+      {code}
+
+
+ +
+
+); - if (content) { - try { - const contentStr = typeof content === 'string' - ? content - : new TextDecoder().decode(content); - - const manifest = yaml.load(contentStr) as RdfManifest; - - if (!manifest.config) manifest.config = {}; - - if (!manifest.config.view_config) { - manifest.config.view_config = viewConfig; - - if (!manifest.tags) manifest.tags = []; - if (!manifest.tags.includes('static-site')) manifest.tags.push('static-site'); - - const newContent = yaml.dump(manifest); - - return nodes.map(f => f.path === rdfFile.path ? { - ...f, - content: newContent, - edited: true, - loaded: true - } : f); - } - } catch (e) { - console.warn("Failed to update manifest with static site config", e); - } - } - } else { - const name = commonPrefix || 'New Application'; - - const manifestContent = yaml.dump({ - type: 'application', - name: name, - description: 'Static web application automatically generated.', - tags: ['static-site'], - config: { - view_config: viewConfig - } - }); +interface CreateDialogProps { + onClose: () => void; + onCreate: (name: string, description: string) => Promise; + creating: boolean; +} - const newRdfFile: FileNode = { - name: 'rdf.yaml', - path: commonPrefix ? `${commonPrefix}/rdf.yaml` : 'rdf.yaml', - content: manifestContent, - isDirectory: false, - size: manifestContent.length, - loaded: true, - edited: true - }; +const CreateDialog: React.FC = ({ onClose, onCreate, creating }) => { + const [name, setName] = useState(''); + const [description, setDescription] = useState(''); + const [showCliInfo, setShowCliInfo] = useState(false); - return [...nodes, newRdfFile]; - } - - return nodes; + const handleSubmit = async (e: React.FormEvent) => { + e.preventDefault(); + if (!name.trim()) return; + await onCreate(name.trim(), description.trim()); }; - const onDrop = useCallback(async (acceptedFiles: File[]) => { - const isZipFile = acceptedFiles.length === 1 && acceptedFiles[0].name.toLowerCase().endsWith('.zip'); - if (isZipFile) { - await processZipFile(acceptedFiles[0]); - } else { - await processFilesAndFolders(acceptedFiles); - } - }, []); - - const processZipFile = async (zipFile: File) => { - setUploadStatus({ - message: 'Processing zip file...', - severity: 'info', - progress: 0 - }); - - const zip = new JSZip(); - - try { - await new Promise(resolve => setTimeout(resolve, 100)); - - const loadedZip = await zip.loadAsync(zipFile); - const fileNodes: FileNode[] = []; - - const totalFiles = Object.keys(loadedZip.files).length; - let processedFiles = 0; - - setUploadStatus({ - message: 'Reading zip contents...', - severity: 'info', - progress: 5 - }); - - for (const [path, file] of Object.entries(loadedZip.files)) { - if (!file.dir) { - const pathParts = path.split('/'); - const fileName = pathParts[pathParts.length - 1]; - - const fileNode: FileNode = { - name: fileName, - path: path, - isDirectory: false, - size: (file as any)._data ? (file as any)._data.uncompressedSize : 0, - handle: file - }; + // Preview the alias slug + const aliasPreview = name + .toLowerCase() + .replace(/[^a-z0-9]+/g, '-') + .replace(/^-+|-+$/g, '') + .slice(0, 48); - if (fileName === 'rdf.yaml') { - let content = await file.async('string'); - if (user?.email) { - try { - const manifest = yaml.load(content) as RdfManifest; - if (!manifest.uploader?.email) { - manifest.uploader = { ...manifest.uploader, email: user.email }; - content = yaml.dump(manifest); - } - } catch (e) { - console.warn("Failed to inject email into rdf.yaml", e); - } - } - fileNode.content = content; - fileNode.loaded = true; - } + return ( +
+
+

Create New Artifact

+

+ A Git repository will be created for your model. You can push files using Git and Git LFS. +

+
+
+ + setName(e.target.value)} + placeholder="e.g. cellpose-v3-retrained" + className="w-full border border-gray-300 rounded-lg px-4 py-2 text-sm focus:outline-none focus:ring-2 focus:ring-[#f39200] focus:border-transparent" + required + autoFocus + /> + {aliasPreview && ( +

+ Repository ID: {aliasPreview} +

+ )} +
+
+ +