SKILL: Bohrium Paper & Patent Search

Overview

Search academic papers and patents using the Bohrium RAG search engine. Combines keyword matching with semantic understanding, supporting natural language queries, date range filtering, JCR zone/database filtering, and AI reranking.

Supported Search Types:

Use cases: Literature review, technical survey, method comparison, trend analysis.

No CLI support — all operations use the HTTP API.

Authentication

ACCESS_KEY is read from the OpenClaw config ~/.openclaw/openclaw.json:

"bohrium-paper-search": {
  "enabled": true,
  "apiKey": "YOUR_ACCESS_KEY",
  "env": {
    "ACCESS_KEY": "YOUR_ACCESS_KEY"
  }
}

OpenClaw automatically injects env.ACCESS_KEY into the runtime.

Common Code Template

import os, requests

AK = os.environ.get("ACCESS_KEY", "")
BASE = "https://open.bohrium.com"
PAPER_BASE = f"{BASE}/openapi/v2/paper"
HEADERS_JSON = {"accessKey": AK, "Content-Type": "application/json"}

English Paper Search

Basic Search

r = requests.post(f"{PAPER_BASE}/rag/pass/keyword", headers=HEADERS_JSON, json={
    "words": ["deep learning", "molecular dynamics"],
    "question": "How to use deep learning for molecular dynamics simulation?",
    "startTime": "",
    "endTime": "",
    "pageSize": 10
})
data = r.json()
print(f"Found {len(data['data'])} papers")
for p in data["data"]:
    print(f"  [{p['doi']}] {p['enName']}")
    print(f"    Journal: {p.get('publicationEnName', '')}, IF: {p.get('impactFactor', 0)}")
    print(f"    Date: {p['coverDateStart']}, Citations: {p['citationNums']}")

Advanced Search (Date Range + JCR Zone + Database + Type)

r = requests.post(f"{PAPER_BASE}/rag/pass/keyword", headers=HEADERS_JSON, json={
    "words": ["deep learning", "protein structure"],
    "question": "deep learning protein structure prediction",
    "type": 5,                          # Search version (see below)
    "startTime": "2024-01-01",          # Start date YYYY-MM-DD
    "endTime": "2025-01-01",            # End date
    "jcrZones": ["Q1", "Q2"],           # JCR zone filter
    "includeDbs": ["SCI"],              # Database filter
    "areaIds": [],                      # Area IDs (optional)
    "publicationIds": [],               # Publication IDs (optional)
    "pageSize": 20
})

Request Parameters

Response Fields

Patent Search

r = requests.post(f"{PAPER_BASE}/rag/pass/patent", headers=HEADERS_JSON, json={
    "type": 3,
    "words": ["neural network"],
    "question": "neural network",
    "pageSize": 5
})
data = r.json()
for p in data:
    print(f"  Patent: {p}")

Note: Patent search type is capped at 3; English paper keyword search type is capped at 5.

Patent Request Parameters

Patent Response Fields

Returns array format with patent information objects.

Search Tips

Keyword Selection

# GOOD: 3-8 professional terms
words = ["molecular dynamics", "force field", "deep potential", "neural network"]

# BAD: Too generic
words = ["science", "research"]

Combine question for Better Relevance

words is for exact keyword matching, question is for semantic understanding. Best results come from combining both; this applies to English paper keyword search and patent search:

{
    "words": ["GNN", "molecular property", "prediction"],
    "question": "How do graph neural networks predict molecular properties?",
    "pageSize": 20
}

Filter for High-Quality Journals

{
    "words": ["..."],
    "question": "...",
    "jcrZones": ["Q1"],          # Q1 journals only
    "includeDbs": ["SCI"],       # SCI-indexed only
    "startTime": "2023-01-01",   # Recent 2 years
    "endTime": "2025-12-31"
}

curl Examples

AK="YOUR_ACCESS_KEY"
BASE="https://open.bohrium.com"
PAPER_BASE="$BASE/openapi/v2/paper"

# English paper search
curl -s -X POST "$PAPER_BASE/rag/pass/keyword" \
  -H "Content-Type: application/json" \
  -H "accessKey: $AK" \
  -d '{"words":["deep learning","protein"],"question":"deep learning protein structure prediction","type":5,"startTime":"2024-01-01","endTime":"2025-01-01","jcrZones":["Q1"],"pageSize":5}'

# Patent search
curl -s -X POST "$PAPER_BASE/rag/pass/patent" \
  -H "Content-Type: application/json" \
  -H "accessKey: $AK" \
  -d '{"type":3,"words":["neural network"],"question":"neural network","pageSize":5}'

Troubleshooting