AIPOCH Open-Science v0.36.0

AIPOCH Open-Science v0.36.0

A trust-and-reach release: Notebook execution becomes reviewable with per-run risk screening, PDFs gain resumable shared full-document translation, and the connector catalog grows cancer proteomics discovery and population-specific linkage-disequilibrium queries.

AIPOCH Open-Science is an open-source, local-first, model-agnostic AI research workbench for scientists and researchers. It enables reproducible, inspectable research across models with scientific AI agents, Python and R execution, scientific data connectors, and cross-platform support for macOS, Windows, and Linux.

v0.36.0 makes Notebook execution reviewable and extends scientific reach. Every Notebook run is now screened for destructive or risky code before dispatch: ordinary reads and analysis run without repeated prompts, while risky executions surface a focused review card with source-line context and a durable receipt. PDF reading gains resumable full-document translation with original, translation, and side-by-side compare modes — one saved edition per managed PDF, shared across Literature, Reading, Inbox and Workspace entries. The connector catalog grows a PDC connector for cancer proteomics study, biospecimen and quantitative file discovery, and the Genomes connector gains population-specific Ensembl linkage-disequilibrium queries for comparing association signals and finding proxy variants. Claude Haiku 5.5 joins the bundled Anthropic catalog. Underneath, PDF structure extraction preserves native scientific layouts more faithfully, model catalogs shed context-size suffix aliases that broke selection on some engines, and find, file mentions, Remote Web marketplace browsing and composer chips are fixed.

✨ Highlights

• Reviewable Notebook execution. Every Notebook run is screened for destructive or risky code before it executes; risky runs surface a focused review card with source-line context and a durable receipt, while ordinary analysis runs without repeated prompts. (#3336)
• Resumable shared PDF translation. Translate a full PDF with paragraph-level checkpoints, switch between original, translation, and side-by-side compare reading modes, and resume across sessions — one saved edition per managed PDF, shared across all entries. (#3334)
• Connector reach. A new PDC connector brings cancer proteomics study, biospecimen and file discovery, and the Genomes connector gains population-specific linkage-disequilibrium queries. (#3335, #3337)
• Claude Haiku 5.5. The bundled Anthropic catalog adds Claude Haiku 5.5 with its 1M-token context window. (#3333)

🚀 New Features

• Reviewable Notebook execution with per-run risk analysis and durable review receipts (#3336)
• Resumable full-document PDF translation with original/translation/compare reading modes (#3334)
• PDC connector: search cancer proteomics studies, biospecimen associations and quantitative file metadata (#3335)
• Population-specific Ensembl linkage-disequilibrium queries: pairwise r²/D′ and proxy-variant lookup (#3337)
• Claude Haiku 5.5 in the Anthropic model catalog (#3333)
• Select all for the loaded page in Literature Library and Inbox batch toolbars (#3340)
• Drag a project file card or the open artifact into the composer to mention it (#3315)

🔧 Improvements

• Scientific dependency lineage is stronger for Python and R notebooks: more scientific readers, container transforms and callbacks are tracked, so dependency edges and file effects stay accurate (#3309, #3332)

🐛 Bug Fixes

• PDF structure extraction preserves native scientific layouts — complete tables, tiered headers, footers and multi-panel figures (#3320)
• The Files panel no longer blocks file mentions in a new conversation (#3338)
• Find (Ctrl/Cmd+F) works again in an empty workspace (#3316)
• The Specialist Marketplace opens in Remote Web (#3331)
• Compact mention chips in new-session composers render at their normal size again (#3341)
• Context-size suffix aliases are removed from official model catalogs, fixing model-selection failures with some engines (#3326)

📦 Install

Requirements: macOS 12+ (Apple Silicon or Intel), Linux x64 or ARM64, or Windows 10/11 x64. On first run, the onboarding wizard checks the environment and can install and configure an app-managed agent runtime. Once installed, the app can update itself in place.

Download the appropriate package from the Assets section below, or from the official download page:

Platform	Package
macOS (Apple Silicon)	DMG for ARM64
macOS (Intel)	DMG for x64
Linux	AppImage or Debian package for x64 / ARM64
Windows	Code-signed installer for x64

macOS — first launch. Official release builds are Developer ID signed and notarized by Apple, so they open like other trusted applications. A locally built copy is notarized differently and may require approval through macOS Privacy & Security.

Windows — first launch. Official release builds are code-signed; Windows recognizes the publisher and no SmartScreen warning appears. Verify that the package came from the official release page before continuing.

Build from source instead:

npm install
npm run build:mac   # or: build:linux / build:win

🧭 What's in this release (maturity)

• ✅ Implemented: everything shipping in v0.35.1, plus: reviewable Notebook execution with per-run risk review; resumable shared PDF translation; the PDC connector; population-specific Ensembl linkage-disequilibrium queries; Claude Haiku 5.5; and page-level select all in Literature batch toolbars.
• 🚧 Partial: provider choice remains constrained by the active framework's endpoint compatibility; remote compute covers direct SSH and Slurm (cloud-GPU submission is not built yet); WSL2 Bash remains an opt-in Windows x64 preview; the skills commons ships marketplace discovery but not cross-machine forking or user-facing version pinning; reproducibility ships replayable per-version verification, session replay, and RO-Crate packaging, while solver-exact equivalence remains open; conditional package restore is an exported script workflow; and review is opt-in and record-scoped.
• 🗺️ Roadmap: a unified model gateway, cross-machine skill forking and version pinning, cloud-GPU execution, stronger sandboxing and credential isolation, and collaborative research workflows.

🐢 Known Limitations

• Replay reproduces recorded steps, it does not re-execute them. Solver-exact equivalence guarantees remain open; replayable verification remains the deterministic check, and starting a check from the web client currently requires the desktop app.
• Sensitive package evidence is opt-in. Session diagnostics include sensitive package evidence only after explicit confirmation, and the export stays local until you share it.
• Imported .science sessions are read-only. They stay inspectable and referenceable, and forking them into a writable continuation remains available; execution and continuation remain disabled on the import itself.
• Bookmarks belong to a single session. They do not follow branch switches, join .science package exports, or sync across machines — forking copies them into the new session with fresh identities.
• PDF annotations are bound to the file version they annotate. Notes follow the file across projects and sessions where that version is shared, but they do not sync across machines.
• WSL2 Bash is a preview. It is opt-in on Windows x64 only; PowerShell remains the default shell runtime.
• Remote compute covers direct SSH and Slurm. Cloud-GPU submission is not built yet.
• Editable artifacts cover text formats. Binary formats stay read-only, and editing always publishes new versions.
• Network sandboxing covers the app's notebook and compute runtimes, not the whole system. On Windows, the boundary applies only after the sandbox's one-time administrator setup.
• Provider choice is per framework, not one unified gateway. The available protocol depends on the selected agent backend, and remote endpoints must use HTTPS.
• Code reconstruction is LLM-generated. It does not replace deterministic reproduction; replayable verification is the deterministic check.
• The reviewer is opt-in and record-scoped. It does not replace domain-specific validation of citations, units, statistics, or methods.
• No local GPU compute backend.
• No multi-user real-time collaboration.

🙏 Acknowledgements

Thanks to @ewen-poch, @nasus2002, @Korrz777, @justemu, and everyone in Discord, X, and Discussions.

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Full Changelog: https://github.com/aipoch/open-science/commits/v0.36.0