AIPOCH Open Science

Open-source, local-first, model-agnostic AI research workbench for reproducible science.

Open Science is an open-source, local-first, model-agnostic AI research workbench developed by [AIPOCH](https://aipoch.com/open-science) for scientists and researchers. It enables reproducible, inspectable research with scientific AI agents, Python and R execution, scientific data connectors, and cross-platform support for macOS, Windows, and Linux. Create a project, describe your research goal in plain language, and let the agents read files, search the web, run code, query scientific data sources, and produce reports, tables, and figures with traceable provenance—all in one workspace. Open Science supports computational and data-intensive research across disciplines, including machine learning, statistics, life sciences, chemistry, materials science, physics and environmental science. It supports the research process from literature review and hypothesis development to code execution, data analysis, simulation, visualization, and the production of traceable research outputs. > 💡 **[Open Science v0.26.0 released](https://github.com/aipoch/open-science/releases/latest)** _(last updated September 2026)_. Open Science v0.26.0 brings HPC-class compute and a literature workspace: remote compute hosts gain a per-host Slurm execution mode alongside direct SSH, and a new reference library organizes references, PDFs, and citations with identifier-aware imports, duplicate merging, open-access full-text attachment, and citation formatting. Apodex joins the built-in providers alongside the latest OpenAI and Anthropic models, notebook tool calls become readable summary cards, and smoother streaming, quieter default permissions, and a broad set of fixes land throughout. See the [latest release notes](https://github.com/aipoch/open-science/releases/latest) for full details.

Open Science open-source AI research workbench desktop app workspace showing an agent session with generated artifacts

## 🚀 Quick Start Get Open Science running in three steps: download the installer for your platform, complete the guided first-run setup, and create a research project. ### 1. Download the app Open the [latest release](https://github.com/aipoch/open-science/releases/latest), expand **Assets**, and choose the installer for your computer: | Your computer | Choose | | ----------------------------------- | ---------------------------------------- | | macOS — Apple Silicon (M1 or newer) | The macOS DMG for Apple Silicon / ARM64 | | macOS — Intel | The macOS DMG for Intel / x64 | | Windows x64 | The Windows x64 installer | | Linux x64 | The Linux x64 AppImage or Debian package | Review the assets and verification information published on the release page. See [Verifying your download](SECURITY.md#verifying-your-download) before installation if you need to validate a package. > If macOS or Windows shows an unidentified-developer or unknown-publisher warning, verify that the package came from the official Releases page before continuing. ### 2. Complete first-time setup The first launch has five guided steps: 1. **Environment** checks compatibility, app storage, secure credential storage, and network access. 2. **Data location** chooses where large artifacts, notebooks, uploads, and environments are stored. 3. **Agent runtime** selects and prepares Claude Code, OpenCode, Codex, or CodeBuddy. App-managed runtimes can be installed without requiring Node.js, npm, or an administrator password. 4. **Model provider** connects and tests the model you want to use. Choose a built-in provider, a custom gateway, or an existing Claude or Codex subscription login. 5. **Notebook runtime** optionally prepares app-managed Python and R environments or enables detected and manually registered interpreters for either language.


_{Host compatibility, storage, and network checks}	_{Provider, API Key, endpoint, and model validation}

Notebook execution is optional. Every required environment and agent-runtime check must pass before `Continue` becomes available, and the model connection must pass before setup finishes. Notebook and data-location settings can keep their defaults and be changed later in Settings. While a kernel is running, a Variables view can inspect the live Python or R namespace — names, types, shapes, and previews — read-only, refreshed after each execution. ### 3. Start a research project 1. Click **New project** and give the project a stable research name and optional description. 2. Open a session and describe the goal, input data, constraints, desired outputs, and how the result should be checked. 3. Attach source files, select a verified model, and choose an approval mode. 4. Send the task. Inspect the agent's tool activity, approve sensitive actions, and open generated artifacts in the preview panel. 5. To explore a different direction, edit an earlier user message and resend it on a new branch; use the message revision controls to return to either path. 6. Open an artifact's **Provenance** view to inspect its versions and the available evidence behind the selected result. 7. Continue the work in later sessions. Use `@` to reference an existing project file and `/` to explicitly select an enabled skill. > Screenshots in this README illustrate the workflow. Labels, catalogs, and other interface details may differ from the version you install. ## Product Tour Open Science organizes research into projects and sessions so that every result can stay connected to the evidence that produced it. The sections below walk through the workspace, artifact provenance, previews, scientific skills, and data connectors. ### One workspace from task to traceable artifacts Projects keep related sessions, uploads, generated files, and preview state together. The conversation records the agent's answer and the commands, file reads, edits, searches, and connector calls that produced it. Each generated artifact is stored as an immutable, checksummed version. Its **Provenance** view exposes the evidence Open Science could verify at creation time: producer code and execution history, referenced inputs, an observed environment inventory, the producing conversation branch, and any version-scoped reviewer findings. Missing evidence is shown as unavailable instead of being guessed.


_{Uploads and generated files organized by project and session}	_{Native previews keep data and the research history side by side}

Generated reports, figures, and tables remain attached to the session and are also collected in the project file library. Preview tabs keep the active result visible as the panel changes size, and long names preserve their identifying suffix and extension. Open Science previews common scientific data, PDFs, Office documents (DOCX, XLSX, PPTX), images (with zoom and pan), source code with syntax highlighting, molecular structures and reactions, and Notebook history. Preview limits do not truncate the underlying file—the full artifact stays available to the agent and external tools. Use `Cmd/Ctrl+F` to search transcripts, Notebook output, and rendered pages across the workspace, or `Cmd/Ctrl+K` to open the project-scoped command palette. A dark mode rounds out the workspace: toggle the theme in **Settings → General** and the whole shell, transcript, and renderer palette switch without a flash. The interface is also available in German, Spanish, Chinese (Simplified and Traditional), Japanese, Korean, French, and Russian with a runtime language switcher in Settings. ### Branch a conversation without losing the original Edit a completed user message to resend a revised prompt from that point. Open Science creates a new message branch instead of deleting the turns that followed, and revision controls let you move between the original and alternative paths. Branch selection, tool activity, attachments, and generated artifacts persist across project switches and restarts. Provenance remains tied to the exact branch that produced each artifact version, so exploring a different hypothesis does not blur the record of the earlier result. ### Scientific skills and data connectors Open Science includes a growing catalog of **22 featured**, file-based research skills: AlphaFold2, Boltz, Borzoi, Chai-1, Customize, DiffDock, Environment & Packages, ESM-2, ESMFold2, Evo 2, Figure Composer, Figure Style, Indication Dossier, LigandMPNN, Literature Review, OpenFold3, Paper Narrative, ProteinMPNN, scGPT, scvi-tools, SolubleMPNN, and **Remote Compute (SSH)** for submitting and harvesting long-running jobs on remote HPC clusters. You can create personal skills, upload `SKILL.md`/ZIP/`.skill` packages, preview and import compatible skills from GitHub with optional authenticated access, or import skills already installed in your global agent directories. The agent can also request a package import from a session attachment or a public GitHub URL, with an app-owned preview and confirmation step before anything is written. Enabled skills can be selected directly in the composer with `/`. It also includes **24 built-in** research connectors: Literature Graph, PubMed, bioRxiv, Genes & Ontologies, Genomes, BioMart, Variants, Human Genetics, Clinical Genomics, Structures & Interactions, Protein Annotation, Expression, Omics Archives, CellGuide, Regulation, RNA, Chemistry, ChEMBL, ZINC, Molecule Viewer, Clinical Trials, Drug Regulatory, Cancer Models, and Research Resources. Built-in and custom connectors remain behind the permission system, with per-tool `Always allow`, `Ask each time`, and `Block` controls. The installed app shows the current skill, connector, and tool catalogs.


_{Readable, reusable research skills}	_{Scientific databases exposed as permissioned agent tools}

## Benchmark Performance ### 🏆 #1 on BiomniBench-DA Public 50 Open Science achieved the highest ranking score in the compiled BiomniBench-DA Public 50 comparison, earning **79.05** with **gpt-5.6-sol (xhigh)**. The result combines a Gemini 3.1 Pro judge score of **81.04** and a DeepSeek v4-pro judge score of **77.06** through an equal-weight mean, placing Open Science **#1** among the collected Public 50 results. Explore the [BiomniBench-DA dataset](https://huggingface.co/datasets/phylobio/BiomniBench-DA).

BiomniBench-DA Public 50 comparison showing AIPOCH Open Science ranked first with a score of 79.05

## Why Open Science Open Science brings research tasks, execution, files, and evidence into one local, inspectable desktop workspace. Research work is usually split across chat windows, notebooks, local scripts, scientific databases, file browsers, and reporting tools. Context is lost at every handoff, and the answer is often separated from the code and files that produced it. Open Science brings those pieces into one inspectable desktop workspace: - **Work that persists.** Projects, sessions, drafts, files, previews, and run history survive application restarts. - **Execution, not just suggestions.** The agent can run commands, Python, and R, edit files, search, call connectors, and generate artifacts with the user's approval. - **Alternative paths without lost work.** Revise an earlier prompt on a new message branch and switch between the resulting research directions. - **Traceable results.** Immutable artifact versions retain the production evidence Open Science can verify, and explicitly mark evidence it cannot. - **Multiple model choices.** Use a built-in cloud provider, a compatible custom gateway, or a Claude or Codex subscription; choose each Session's model and reasoning effort together in the composer. - **Local-first ownership.** The application and project state run on your computer; external calls happen through services you explicitly configure or approve. - **Inspectability.** The source code, skills, connector definitions, tool activity, generated files, and artifact provenance are available for review. - **Extensibility.** Add skills and MCP connectors instead of waiting for a closed plugin roadmap. - **No seat license.** Open Science is Apache-2.0 software. You pay only for the model or infrastructure you choose to use. Open Science is an independent product built from scratch. It is not a proxy, unofficial client, or reskin of another AI research application. ## Design Principles Open Science is built on seven design principles that govern how code, data, models, and human oversight fit together: open by default, explicit multi-provider compatibility, local-first data ownership, human-in-the-loop oversight, durable research records, composable capabilities, and honest scientific boundaries. - **Open by default.** Source code, formats, connectors, and skills should remain inspectable and forkable. - **Multi-provider with explicit compatibility.** The app validates provider configuration and makes endpoint requirements visible instead of treating every API protocol as interchangeable. - **Local-first and data-aware.** Keep project state local, surface external data flows, and make autonomy opt-in. - **Human-in-the-loop.** File edits, commands, network access, and connector calls are governed by explicit approval profiles. - **Durable research records.** Sessions, tool activity, Notebook history, and immutable artifact versions should remain reviewable after the run ends, with unavailable evidence stated plainly. - **Composable capabilities.** Skills, connectors, models, previews, and future compute backends should be replaceable parts rather than one black box. - **Honest scientific boundaries.** Generated output does not replace expert judgment, statistical review, or validation against primary evidence. ## Core Capabilities Open Science combines project management, multi-model agent execution, Python and R notebooks, scientific data connectors, immutable artifact versions with provenance, and permissioned human-in-the-loop control in one local workspace. The installed app and [latest release notes](https://github.com/aipoch/open-science/releases/latest) are the source of truth for changing catalogs, packaging details, and newly added options. | Area | Core capability | | ---------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Projects and sessions** | Create, rename, and delete projects; maintain multiple sessions with pinning; edit completed prompts into persistent, selectable message branches without deleting the original downstream path; persistent side conversations within a session; generated and editable session details (title and description); restore recent work, drafts, conversation history, and preview state. | | **Agent workflow** | Natural-language tasks, streamed responses, typed tool-activity cards grouped under declared purpose titles, compact summary cards for artifact writes and notebook controls in messages and approvals, a live context-usage indicator with category-level estimates, on-demand context compaction, and persistence across restarts, stop controls, approval pauses, a confirmation step (with a remembered preference) before closing or quitting during a running task, a composer message queue for staging follow-up messages during a running turn, unified draft undo and redo history, branching into a new session from completed agent messages, desktop notifications with attention reasons plus durable unread conversation badges and native attention on blocking approvals, a cross-surface notification message center with kind- and state-coded icons, durable read state, and retained deleted targets, structured agent clarification cards for multi-question requests with per-question answer review, text, image, and PDF annotations — selected text or regions with click-to-reveal in the source document — that send selected context into the conversation, timeline markers for agent configuration changes between turns, and expanded skill-load rows that show the loaded skill document, a session reading context that links up to three PDFs so the agent can read the current page, page through the full document, and search across them, persistent agent memory that recalls project-scoped knowledge across sessions, in-app sandboxed previews for source links in agent responses, live session status on the Home dashboard, message timing metadata with elapsed-time and usage popovers, per-turn token usage with per-model-call usage details and a per-call context-window chart, completed-turn agent framework and model identification, a project-scoped command palette, project-scoped frame reads, project actions and agent context, a project quick switcher in the workspace project menu that lists other active projects with title and description previews and fuzzy search once the list grows, refined session sidebar rows with hover previews of session title and description, session references (`#`) to other sessions in the composer with turn-scoped read access, side-chat advisories injected into a running main turn, session-number lookup in global search, review-gated session plans with durable execution contracts and CLI plan show, approve, and reject commands, smooth live response rendering, collapsible side panels, a new-conversation keyboard shortcut, and recovery of sessions interrupted by an application restart. | | **Subagent delegation** | Production subagent delegation with durable messaging and recovery, and a per-session delegation switch in the composer's agent controls that decides whether the agent may delegate work. | | **Models** | Built-in cloud providers including Apodex, NVIDIA Build with a curated agent-capable catalog, and the latest OpenAI and Anthropic model catalogs (GPT-6 Astra and Claude Fable 5.1), custom compatible gateways, Claude and Codex subscription logins, connection validation, per-model multimodal image input, a combined per-Session composer picker for model and model-supported reasoning effort, a consolidated Scenario models card covering the subagent, reviewer, and vision policies, Settings defaults for new Sessions, and a dedicated Vision model selector with a persistent image evidence relay for text-only backends. Available providers and API formats are validated against the selected agent backend. | | **Agent backend** | A selectable agent-framework backend — Claude Code, OpenCode, Codex, or a login-free CodeBuddy runtime — so the same workspace can run on more than one underlying agent implementation, with provider and model choices validated against the selected backend, app-managed backends installable, switchable, and removable from Settings, and agent-aware context replay that respects each framework's context path after switches or resumes. | | **Specialists** | Personal specialist agent profiles with scoped capabilities, immediate in-flight handoff from the main agent, conversational customization, package import/export, immutable invocation identities, generated name-based IDs with validated overrides, and a scoped Specialist marketplace with signed package verification, official and user-approved GitHub sources, CDN fallback, download progress, and skill-conflict resolution on import. The marketplace separates Installed and Marketplace views with a card-grid browse layout, filter chips, and a single primary browsing entry with an explicit return path, opens verified cached listings immediately with manual refresh, supports direct installation from details, and provides shared capability icons (64 built-in glyphs), quick appearance editing, and capability-row navigation. | | **Capability organization** | Cross-resource tags for skills, connectors, and runnable specialists, with a protected Favorites tag, assignment menus, badges, filters, a searchable Tags settings browser, and persistent pointer or keyboard drag ordering. | | **Execution** | Persistent Python, R, and REPL control-plane kernels with durable code/output history, plus stateless shell commands recorded in the same run history; outbound network access from notebook and compute runtimes limited to Open Science defaults and user-approved domains, with blocked destinations surfaced for in-conversation approval, and protection status surfaced in Settings → Runtimes; bounded REPL inference for agent-driven evaluation; app-managed environments with offline provisioning, safe managed-runtime reinstall from Settings, and a global toggle for whether the agent may create runtime environments; bring-your-own Python and R interpreters; remote compute hosts with key or password authentication (including Windows) and OS-encrypted stored credentials as additional execution targets, each with a per-host execution mode — direct SSH or Slurm — so notebook runs can submit as Slurm jobs on HPC-partitioned clusters, with a guided setup skill that hands the cluster's exact setup, repair, and removal steps to the user or administrator; a user terminal shared with the agent, with live variable-name suggestions from the running kernel while typing; a read-only installed-package inventory per runtime environment; a read-only live variable browser for running Python and R kernels; notebook artifact read access for agent-side file inspection; package-installation progress with elapsed time in the session activity; and progressive history loading for long-running notebooks. Package management for external R runtimes remains manual. | | **Inputs and files** | File attachments (up to 10 GB per file with streaming upload), a project-level library with indexed pagination, session grouping, source-scoped filename search, grid and list views, a large expand modal for large projects, split-view file preview beside the session, generated artifact cards, `@` references to existing uploads/outputs, `@path` mentions to grant local folder access with cross-drive browsing, an editable path bar, and a drive switcher, file download/export, selective session-artifact downloads, long plain-text pastes converted into attachments with exact restore, conversation export as Markdown or PDF, and session export as `.ipynb` (per-tab or download-all). | | **Literature** | A project-ready reference library: import references by identifier (DOI, PubMed ID, arXiv ID, and more) or from files, organize them into collections, link them to projects, and route downloaded PDFs through an Inbox with Trash recovery; find and attach full-text PDFs through public open-access sources (Europe PMC, PMC, OpenAlex, arXiv, and Unpaywall), looking up all applicable sources in parallel, with optional credentials; compare duplicate records side by side and bulk-merge them while preserving attachments and links; and format citations from stored metadata with artifact provenance. | | **Artifacts and provenance** | Immutable, session-scoped artifact versions with checksummed content and available producer code, execution history, exact input references, environment inventory, producing message-branch context, artifact lineage access, and version-scoped reviewer evidence, with version navigation and direct links between related evidence; allowlisted text artifacts and uploads (Markdown, plain text, scripts, and source code) are editable as raw text, where each save publishes a new version that preserves its source lineage and a Compare action shows the predecessor. | | **Preview formats** | Responsive multi-tab previews for common scientific data, PDFs with selectable text, area selection, outline and thumbnail navigation, document search, and page navigation, Office documents (DOCX, XLSX, PPTX), images (including TIFF, with zoom and pan), source code with syntax highlighting, molecular structures and reactions, and Notebook history, viewable inline or full-screen, with right-click tab actions (close, close others, download, copy path, save as artifact), right-click content menus that copy paths, download, or save local files as artifacts and inspect provenance or return to the originating context for managed artifacts, and view-in-context navigation back to the conversation that produced an artifact. | | **Local data management** | Local project and application data, configurable storage location that also carries notebook workload caches, guided migration, and global proxy settings with system, manual, and direct modes; a token usage dashboard with period summaries, a 30-day activity heatmap, daily input/cache/output charts, per-run usage attribution, and coverage of model calls outside the main conversation (side conversations, delegation, compaction). | | **Skills** | **22 featured** built-in skills; personal skills with immutable lowercase-hyphenated names; conversational skill creation from natural language inside a session; save-as-skill from a completed conversation turn; direct user skill folder support with out-of-band package validation; bulk enable/disable management with source, status, and text filters; package upload including large, asset-heavy bundles; authenticated GitHub preview/import; import of installed global skills with candidate preview; agent-requested package imports from session attachments or GitHub URLs; camelCase Host JavaScript APIs for skill scripting with structured validation; provenance-aware figure workflows with registered styling, composition, and paper-narrative helpers; enable/disable controls; and explicit `/` selection in a session. The redesigned Skills panel unifies main-agent and specialist filtering, shows actual-user avatar stacks with a bounded Used by popover, consolidates row actions, and supports confirmed bulk deletion while protecting built-in and specialist-linked skills. | | **Connectors** | **24 built-in** research connectors with runtime status and recovery surfaces, custom local/remote MCP connectors with immutable lowercase invocation names sepa > 内容过长，已截断。完整文档请查看仓库原文。