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scibudy-installer

v0.1.1

Published

Unified installer and bootstrap wrapper for Scibudy

Readme

Scibudy

CI Docs Release Check

Scibudy is a Codex-native scientific research expansion assistant for scholarly search, library management, full-text ingestion, and local semantic analysis.

Scibudy combines:

  • a local MCP server for Codex
  • a shell-first CLI
  • a browser management UI
  • a layered install system for CPU-first and GPU-extended deployments

中文简介:

Scibudy 是一个面向 Codex 的科研增强助手,提供学术检索、文献库管理、全文分析和本地高质量语义检索能力。它既可以作为 MCP 工具,也可以作为独立 CLI 和本地管理界面使用。

Status

  • License: Apache-2.0
  • Release posture: stable v0.x
  • Primary platforms: Linux and macOS
  • Full local GPU path: Linux + NVIDIA first

Quick links

Installation

Before you install

For most new users, the real prerequisites are only:

  • Node.js 18+
  • Python 3.10+

Read more:

Unified installer

npx scibudy-install --profile base

Profiles:

  • base: search, library management, UI, Codex config
  • analysis: base + analysis-oriented runtime conventions
  • gpu-local: local GPU model environment and warm flow
  • full: full bootstrap for a Linux GPU workstation

Source install

git clone [email protected]:ONEMULE/scibudy.git
cd scibudy
python3 -m venv .venv
. .venv/bin/activate
python -m pip install -e .[dev]
scibudy bootstrap --profile base --install-codex

Runtime commands

Primary command aliases:

  • scibudy
  • scibudy-mcp
  • compatibility aliases: research-cli, research-mcp

Examples:

scibudy search "simulation-based calibration" --mode general
scibudy collect "simulation-based calibration" --target-dir ~/Desktop/sbc-library
scibudy analysis-settings
scibudy ingest-library <library_id>
scibudy search-evidence <library_id> calibration
scibudy ui --open

For more examples and Codex prompt patterns:

Local model stack

The highest-quality local retrieval path currently uses:

  • Qwen/Qwen3-Embedding-4B
  • Qwen/Qwen3-Reranker-4B

Recommended workflow:

scibudy install-local-models
scibudy warm-local-models --background

See:

Repository layout

research_mcp/   Python runtime, MCP server, CLI, analysis engine
web/            UI source and built assets
bin/            npm/bootstrap entrypoints
docs/           Bilingual project documentation
examples/       Copyable usage examples
scripts/        Release and smoke-check helpers
.github/        CI, templates, automation

Open-source project standards

This repository is intentionally organized like a professional open-source library:

  • documented install profiles
  • release manifest and bootstrap state
  • contributor and support policies
  • issue/PR templates
  • CI and packaging checks
  • bilingual documentation for core user workflows

Development

Core local checks:

make test
make build-ui
make package-check
make release-check

For deeper guidance: