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AI-powered research assistant for scientists — literature search, data analysis, academic writing, and project management

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    Readme

    Research Copilot

    An AI-powered desktop research assistant for scientists and academics. Literature search, data analysis, academic writing, cross-project paper memory, and project management — powered by your ChatGPT Pro / Claude Max subscription (or an API key), all in one desktop app.

    Built on pi-mono (agent runtime) + Electron + React.

    Main Interface


    Signing in (READ THIS FIRST)

    Research Copilot supports three auth methods and automatically prefers the cheapest working one. When multiple are configured, priority is:

    ChatGPT subscription → Claude subscription → OpenAI API key → Anthropic API key

    First-launch model selection follows this order; you can override it any time from the model selector.

    The fastest and most cost-predictable path. No API key needed, no metered billing surprises.

    • ChatGPT Pro / Plus — click the model selector, pick a GPT-5.4 (sub) entry, sign in via OAuth. Uses the official ChatGPT subscription endpoint.
    • Claude Pro / Max — click the model selector, pick a Claude … (sub) entry, sign in via OAuth. Uses the official Anthropic subscription endpoint. (Previously gated behind ENABLE_CLAUDE_SUB=1; enabled by default since 0235a3f.)

    Credentials are stored in the OS keychain via pi-ai's OAuth helper and refreshed automatically.

    Option 2 — Bring an API key

    Open the unified settings panel (Cmd+.) and paste a key, or set it in your shell profile:

    export OPENAI_API_KEY="sk-..."           # GPT-5.4, GPT-4o, o-series
    export ANTHROPIC_API_KEY="sk-ant-..."    # Claude Opus / Sonnet / Haiku

    Keys entered in the UI are saved to ~/.research-copilot/config.json.

    Optional supporting keys

    Key Enhances Without it
    BRAVE_API_KEY web_search tool — general web search via Brave Falls back gracefully to arXiv-only academic search
    OPENROUTER_API_KEY scientific-schematics skill — AI-generated diagrams The schematics skill fails when invoked; all other skills still work

    Semantic Scholar, arXiv, OpenAlex, DBLP: used for literature search and do not require API keys. They work out of the box.


    How is Research Copilot different from Claude Cowork?

    Claude Cowork is Anthropic's general-purpose autonomous agent for knowledge workers — it handles file organization, document drafting, and data extraction across everyday desktop tasks.

    Research Copilot is a vertical tool built specifically for academic research. The two differ in depth, not surface:

    Claude Cowork Research Copilot
    Scope Horizontal — any knowledge work Vertical — academic research lifecycle
    Literature No academic search Multi-source search (Semantic Scholar, arXiv, OpenAlex, DBLP) with relevance scoring, coverage tracking, and citation tracing
    Paper management Processes files you already have Structured artifact system with DOI, bibtex, citeKey, citation counts, and relevance metadata
    Academic writing Generic document drafting Venue-specific templates (NeurIPS, ICML, journals), IMRAD structure, LaTeX, citation verification (never hallucinated)
    Grant writing None Agency-specific guidance (NSF, NIH, DOE, DARPA, NSTC) with compliance checklists
    Data analysis Extracts data from documents LLM-generated Python scripts with statistical modeling, matplotlib/seaborn visualization, and output manifests
    Domain skills General capabilities 14 pluggable research skills (scientific writing, visualization, scholar evaluation, paper revision, slides, etc.) — extensible via Markdown
    Cross-project memory Per-conversation only Background Paper Wiki agent that indexes every paper you touch into a local, concept-organized knowledge base shared across all your projects
    Knowledge persistence Not specified Artifact store, session summaries, cross-session memory, @-mention references
    Auth Claude subscription only ChatGPT Pro / Claude Max via OAuth or OpenAI / Anthropic API keys — priority-ordered so subscriptions are preferred automatically
    Openness Closed-source commercial product Open source (MIT) — fully customizable

    In short: Claude Cowork is like a smart office assistant. Research Copilot is like a lab partner who knows how to search literature, run stats, write papers, and apply for grants.


    Features

    AI Chat with Coding & Writing Tools

    Converse with an AI research assistant that can read, write, and edit files in your workspace. It generates LaTeX manuscripts, creates publication-quality figures, runs Python analysis scripts, and manages your project files — all through natural language.

    Search across Semantic Scholar, arXiv, OpenAlex, and DBLP simultaneously. Papers are scored for relevance, deduplicated, and organized in a searchable table. Quick actions let you do deep searches, fill coverage gaps, or trace citation chains.

    Literature Management

    Cross-Project Paper Wiki

    A background agent that turns every paper you've ever opened into a local, concept-organized knowledge base shared across all your projects. Each paper gets a summarized wiki page; recurring concepts get their own pages with back-references to the papers that mention them. The wiki is searchable from any project via wiki_search / wiki_get / wiki_coverage tools, so the AI can recall and cite work from earlier projects without you re-feeding it context.

    The wiki runs offline and is disabled by default — it consumes LLM tokens (roughly 8K–25K input / 2K–4K output per paper), so you opt in from the Settings panel and pick a model you're comfortable paying for. Subscription-backed models are recommended; an "Auto" option follows the system-wide priority (sub before API key). Identity drift across DOI/arXiv/title lookups is reconciled automatically so papers don't get reprocessed.

    Extensible Skills System

    Skills are lazy-loaded knowledge modules that give the AI domain expertise. The app ships with 14 builtin skills covering academic writing (paper-writing, paper-revision, research-grants, rewrite-humanize, scientific-writing, scholar-evaluation), visualization (matplotlib, seaborn, scientific-schematics, scientific-visualization, marp-slides), research ideation (brainstorming, creative-thinking), and general coding. You can also add your own project-specific skills as plain Markdown files.

    File Attachments in Chat

    Attach files directly in the chat input via the paperclip button, drag & drop, or paste. Supported formats:

    Format How it's processed
    Images (PNG, JPEG, GIF, WebP) Sent as vision content — the LLM sees the image visually
    Text files (CSV, MD, TXT, JSON, XML, HTML) Read directly and injected as text into the message
    Documents (PDF, DOCX) Converted to text via markitdown CLI (with pypdf fallback for PDF), then injected into the message

    Note: Document conversion requires markitdown (pip install markitdown[all]) or pypdf (pip install pypdf) for PDF/DOCX files. Text-based formats work out of the box with no extra dependencies.

    Future plan: The underlying Anthropic API supports native PDF document blocks (preserving layout, tables, and embedded images). Once the pi-mono agent runtime adds DocumentContent support, PDF attachments will be upgraded to use native API handling instead of text extraction.

    More

    • Document conversion — PDF / DOCX / PPTX / XLSX → Markdown (via agent tools)
    • Python data analysis — LLM-generated analysis with matplotlib/seaborn visualization
    • Artifact management — notes, papers, data, web content with CRUD tools
    • @-mention system — reference entities inline in chat
    • Session continuity — automatic context compaction and session summaries
    • Integrated terminal — run commands without leaving the app
    • LLM providers — OpenAI and Anthropic, via ChatGPT Pro / Claude Max subscription OAuth or API keys, with automatic priority selection
    • Unified settings panelCmd+. opens a single pane for models, API keys, research presets, data-analysis timeouts, and the Paper Wiki agent

    Prerequisites

    • Node.js >= 18
    • npm >= 9
    • Python 3 (optional, for data analysis and figure generation)
    • macOS recommended (Linux/Windows: use the git clone method below, untested)

    Getting Started

    npm install -g research-copilot
    research-copilot

    Option B: Clone from source

    git clone https://github.com/daidong/PiPilot.git
    cd PiPilot
    npm install
    npm run dev

    Authentication

    On first launch, open the model selector (top of the chat pane) and either sign in with ChatGPT Pro / Claude Max via OAuth, or paste an OPENAI_API_KEY / ANTHROPIC_API_KEY into the unified settings panel (Cmd+.). Everything else is optional.

    See Signing in above for the full breakdown and optional supporting keys.

    Build for Production

    npm run build

    Project Structure

    app/                  # Electron desktop application
    ├── src/main/         # Main process (IPC handlers, app lifecycle)
    ├── src/preload/      # Context bridge (renderer ↔ main)
    └── src/renderer/     # React UI (components, Zustand stores)
    
    lib/                  # Research agent logic (framework-independent)
    ├── agents/           # Coordinator agent + prompt registry
    ├── commands/         # Artifact CRUD, search, enrichment
    ├── mentions/         # @-mention parsing and resolution
    ├── memory-v2/        # Artifact storage and session summaries
    ├── skills/           # Skills system (loader + builtin skills)
    └── tools/            # Research tools (web, literature, data, convert)
    
    shared-electron/      # Reusable Electron IPC utilities
    shared-ui/            # Shared React components and stores

    Adding Custom Skills

    Create a Markdown file at <your-workspace>/.pi/skills/<name>/SKILL.md:

    ---
    id: my-skill
    name: My Skill
    shortDescription: Brief description of what this skill does
    ---
    
    Summary loaded at startup.
    
    ## Procedures
    Detailed guidance loaded on demand when the skill is activated.

    Skills are auto-discovered from three locations (later overrides earlier):

    1. lib/skills/builtin/ — shipped with the app
    2. ~/.research-pilot/skills/ — user-global
    3. <workspace>/.pi/skills/ — project-specific

    Configuration

    Research Copilot stores its data in the workspace under .research-pilot/:

    .research-pilot/
    ├── artifacts/          # Notes, papers, data, web content
    │   ├── notes/
    │   ├── papers/
    │   ├── data/
    │   └── web-content/
    └── memory-v2/
        └── session-summaries/

    License

    MIT