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<ahref="http://scinet.openkg.cn/register">🔑 Get API Token</a>
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<ahref="http://scinet.openkg.cn/healthz">🩺 API Health</a>
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## 馃搼 Table of Contents
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-[鉁?Overview](#-overview)
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-[馃殌 Quick Start](#-quick-start)
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-[馃攽 API Token](#-api-token)
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-[馃 What SciNet Does](#-what-scinet-does)
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-[馃З Supported Tasks](#-supported-tasks)
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-[馃洜锔?CLI-First Workflow](#锔?cli-first-workflow)
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-[馃О Editable Skills](#-editable-skills)
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-[馃悕 Python SDK](#-python-sdk)
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-[鈿欙笍 Configuration](#锔?configuration)
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-[馃И Examples](#-examples)
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-[馃摝 Outputs and Artifacts](#-outputs-and-artifacts)
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-[馃洜锔?GROBID for PDF Workflows](#锔?grobid-for-pdf-workflows)
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-[馃搨 Repository Layout](#-repository-layout)
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-[馃Н Troubleshooting](#-troubleshooting)
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-[馃椇锔?Roadmap](#锔?roadmap)
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-[鉁嶏笍 Citation](#锔?citation)
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-[馃搫 License](#-license)
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## ✨ Overview
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---
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SciNet is a research map you can use from the command line. Give it a topic, an idea, an author, or a paper trail, and it helps you look up literature, gather graph-backed evidence, and turn the result into readable reports and reusable JSON artifacts.
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Behind that simple workflow is a large scientific knowledge graph. SciNet connects papers, authors, institutions, venues, keywords, citations, and a four-level research taxonomy from domains down to topics. That means a search is not limited to matching words: it can follow how research areas, people, concepts, and papers relate to one another.
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This repository packages that capability as a lightweight **SciNet client**. New users can install it with `pip`, register an API token, and start running literature-grounded research tasks without setting up Neo4j, maintaining graph data, or touching backend infrastructure.
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<imgsrc="imgs/field_distribution_pie.png"alt="SciNet field distribution across research areas"width="92%">
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<em>SciNet spans a broad research landscape, from medicine and social sciences to engineering, computer science, materials science, mathematics, and more.</em>
SciNet is a large-scale, multi-disciplinary, heterogeneous academic resource knowledge graph designed as a panoramic scientific evolution network. By integrating papers, authors, keywords, citations, disciplines, and other academic entities, SciNet provides a structured topological substrate for scientific discovery agents and research-assistance workflows.
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<em>The graph links papers with authors, institutions, sources, keywords, citations, related work, and the domain-field-subfield-topic hierarchy.</em>
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</p>
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This repository provides a lightweight, user-facing **client package** for running literature-grounded research tasks on top of the hosted SciNet / KG2API backend.
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With the client, you can:
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The client is responsible for:
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- search for papers with keyword, semantic, title, reference, and graph-aware retrieval;
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- run research workflows such as literature review, idea grounding, idea evaluation, idea generation, trend analysis, related-author retrieval, and researcher profiling;
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- save reproducible outputs such as `request.json`, `response.json`, `summary.txt`, and `report.md`;
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- customize downstream workflows through editable CLI **skills**.
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- building structured retrieval requests;
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- calling the hosted SciNet API;
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- formatting concise terminal outputs;
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- saving reproducible artifacts such as `request.json`, `response.json`, and `report.md`;
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- exposing downstream research workflows as editable CLI **skills**.
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---
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Users do **not** need to connect to Neo4j, graph databases, or backend infrastructure directly.
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## 📑 Table of Contents
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-[✨ Overview](#-overview)
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-[🚀 Quick Start](#-quick-start)
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-[🔑 API Token](#-api-token)
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-[🧠 What SciNet Does](#-what-scinet-does)
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-[🧩 Supported Tasks](#-supported-tasks)
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-[🛠️ CLI-First Workflow](#-cli-first-workflow)
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-[🧰 Editable Skills](#-editable-skills)
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-[🐍 Python SDK](#-python-sdk)
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-[⚙️ Configuration](#-configuration)
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-[🧪 Examples](#-examples)
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-[📦 Outputs and Artifacts](#-outputs-and-artifacts)
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-[🛠️ GROBID for PDF Workflows](#-grobid-for-pdf-workflows)
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-[📂 Repository Layout](#-repository-layout)
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-[🧯 Troubleshooting](#-troubleshooting)
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-[🗺️ Roadmap](#-roadmap)
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-[✍️ Citation](#-citation)
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-[📄 License](#-license)
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---
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## 馃殌 Quick Start
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## 🚀 Quick Start
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### 1. Install
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## 馃攽 API Token
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## 🔑 API Token
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SciNet uses personal API tokens for public access.
SciNet is built for research workflows rather than plain keyword search.
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## 馃З Supported Tasks
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## 🧩 Supported Tasks
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| Command | Scenario | Main Output |
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## 馃洜锔?CLI-First Workflow
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## 🛠️ CLI-First Workflow
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SciNet is CLI-first. The CLI is the primary interface for both users and AI agents.
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## 馃О Editable Skills
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## 🧰 Editable Skills
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SciNet skills are JSON presets for downstream research workflows. They make complex workflows easier to inspect, reuse, and customize.
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## 馃悕 Python SDK
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## 🐍 Python SDK
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SciNet also provides a lightweight Python client.
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## 鈿欙笍 Configuration
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## ⚙️ Configuration
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```env
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SCINET_API_BASE_URL=http://scinet.openkg.cn
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## 馃И Examples
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## 🧪 Examples
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### Literature Review
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## 馃摝 Outputs and Artifacts
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## 📦 Outputs and Artifacts
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Terminal output is concise and table-based. Full outputs are saved under:
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## 馃洜锔?GROBID for PDF Workflows
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## 🛠️ GROBID for PDF Workflows
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GROBID extracts structured metadata from scientific PDFs, including titles, authors, abstracts, and references. It is only needed for PDF-based workflows.
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