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Merge pull request #1 from HuaDongJian/package/scinet-client-cli
Package SciNet as pip-installable client CLI
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‎README.md‎

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‎README_zh.md‎

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‎docs/api/SCINET_API_DOC.html‎

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‎docs/api/SCINET_API_DOC_zh.html‎

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<!doctype html>
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<html lang="zh-CN">
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<head>
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<meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<title>SciNet API 文档站</title>
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<meta http-equiv="refresh" content="0; url=SCINET_API_DOC.html?lang=zh">
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<script>location.replace("SCINET_API_DOC.html?lang=zh");</script>
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</head>
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<body>
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<p>正在打开 <a href="SCINET_API_DOC.html?lang=zh">SciNet API 中文文档站</a>...</p>
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</body>
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</html>

‎docs/api/index.html‎

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<!doctype html>
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<html lang="en">
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<head>
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<meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<title>SciNet API Documentation</title>
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<meta http-equiv="refresh" content="0; url=SCINET_API_DOC.html">
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<script>location.replace("SCINET_API_DOC.html");</script>
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</head>
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<body>
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<p>Opening <a href="SCINET_API_DOC.html">SciNet API Documentation</a>...</p>
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</body>
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</html>

‎scinet/.env.example‎

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# SciNet public API configuration.
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SCINET_API_BASE_URL=http://scinet.openkg.cn
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SCINET_API_KEY=your-personal-scinet-token
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SCINET_TIMEOUT=900
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SCINET_RUNS_DIR=./runs

‎scinet/.gitignore‎

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.env
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.env.local
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token.env
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*.sqlite3
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.cache/
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runs/
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__pycache__/
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*.pyc
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dist/
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build/
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*.egg-info/
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.venv/
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.DS_Store

‎scinet/MANIFEST.in‎

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include README.md
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include .env.example
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recursive-include examples *.sh\ninclude src/scinet/builtin_skills.json\ninclude README_skills.md\n

‎scinet/README.md‎

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# SciNet Client
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A lightweight pip-installable client and CLI for the hosted SciNet / KG2API service.
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SciNet provides scientific knowledge-graph retrieval for paper search, related-author discovery, author-paper lookup, literature review, idea grounding/evaluation, idea generation, trend analysis, and researcher review.
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## Installation
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Install directly from GitHub:
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```bash
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pip install git+https://github.com/zjunlp/SciNet.git
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```
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For isolated CLI usage:
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```bash
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pipx install git+https://github.com/zjunlp/SciNet.git
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```
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After installation:
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```bash
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scinet -h
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```
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## Get an API Token
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Open:
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```text
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http://scinet.openkg.cn/register
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```
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Complete email verification and copy your personal token.
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Then configure:
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```bash
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export SCINET_API_BASE_URL="http://scinet.openkg.cn"
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export SCINET_API_KEY="your-personal-scinet-token"
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```
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You can also create a local `.env` from `.env.example`, although the CLI reads environment variables directly.
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## Quick Start
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```bash
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scinet health
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scinet config
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```
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Search papers:
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```bash
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scinet --timeout 900 search-papers \
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--query "open world agent" \
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--domain "artificial intelligence" \
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--time-range 2020-2024 \
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--keyword "high:open world agent" \
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--top-k 3 \
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--top-keywords 0 \
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--max-titles 0 \
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--max-refs 0 \
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--report-max-items 3
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```
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Literature review:
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```bash
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scinet --timeout 900 literature-review \
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--query "retrieval augmented generation" \
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--domain "artificial intelligence" \
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--time-range 2020-2025 \
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--keyword "high:retrieval augmented generation" \
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--top-k 5
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```
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Idea evaluation:
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```bash
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scinet --timeout 900 idea-evaluate \
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--idea "LLM-based multi-perspective evaluation for scientific research ideas" \
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--keyword "high:idea evaluation" \
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--top-k 3
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```
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Researcher review:
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```bash
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scinet --timeout 900 researcher-review \
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--author "Yoshua Bengio" \
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--limit 10 \
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--no-abstract
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```
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## Python SDK
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```python
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from scinet import SciNetClient
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client = SciNetClient()
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print(client.health())
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result = client.search_papers(
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query="open world agent",
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keywords=[{"text": "open world agent", "score": 10}],
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top_k=3,
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)
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print(result)
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```
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## Commands
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| Command | Purpose |
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|---|---|
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| `health` | Check backend health |
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| `config` | Show configuration |
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| `build-plan` | Build a structured plan without calling backend |
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| `search-papers` | Search related papers |
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| `related-authors` | Retrieve related authors |
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| `author-papers` | Query papers by author |
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| `support-papers` | Retrieve support papers |
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| `paper-search` | Lightweight low-level paper search |
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| `literature-review` | Review-oriented paper retrieval |
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| `idea-grounding` | Ground a research idea against literature |
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| `idea-evaluate` | Collect evidence for idea evaluation |
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| `idea-generate` | Discover idea seeds |
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| `trend-report` | Research trend analysis |
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| `researcher-review` | Researcher background review |
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| `make-report` | Regenerate Markdown report from saved artifacts |
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## Outputs
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Each run saves artifacts under:
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```text
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runs/<run_id>/
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plan.json
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request.json
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response.json
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summary.txt
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report.md
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metadata.json
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```
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## Development
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Install editable mode:
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```bash
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pip install -e .
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scinet -h
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```
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Build package:
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```bash
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python -m pip install build twine
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python -m build
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twine check dist/*
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```
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## Security
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Do not commit `.env`, API tokens, SMTP credentials, `.cache/`, or `runs/`.
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## License
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MIT.

‎scinet/README_skills.md‎

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# SciNet Skills
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SciNet skills are editable JSON presets for downstream research workflows.
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```bash
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scinet skill list
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scinet skill show literature-review
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scinet skill run literature-review --query "open world agent" --keyword "high:open world agent"
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scinet skill init my-review --from literature-review
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```
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User-defined skills are loaded from:
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1. `./skills/*.json`
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2. `~/.scinet/skills/*.json`
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3. paths in `SCINET_SKILLS_DIR`
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User skills override builtin skills with the same name.

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