pharmaclaw-literature-agent

# Literature Agent v1.0.0 ## Overview Dual-source literature search combining PubMed (biomedical focus) and Semantic Scholar (broader CS/ML/AI coverage). Deduplicates across sources, enriches with citation metrics and TLDR summaries. **Key capabilities:** - PubMed search with MeSH terms, abstracts, publication types - Semantic Scholar search with citation counts, influential citations, TLDR - Paper lookup by DOI or PMID - Citation tracking (who cited this paper?) - Related paper discovery (what did this paper reference?) - Automatic query construction from compound/target/disease inputs - Cross-source deduplication and enrichment ## Quick Start ```bash # Search by topic python scripts/pubmed_search.py --query "KRAS G12C inhibitor" --max-results 5 # Search Semantic Scholar (includes ML/AI papers) python scripts/semantic_scholar.py --query "graph neural network drug discovery" # Full chain: compound + disease context python scripts/chain_entry.py --input-json '{"compound": "sotorasib", "disease": "lung cancer"}' # Look up a specific paper and find who cited it python scripts/semantic_scholar.py --paper-id "DOI:10.1038/s41586-021-03819-2" --citations # Recent papers only (last 3 years) python scripts/pubmed_search.py --query "organometallic catalyst drug synthesis" --years 3 ``` ## Scripts ### `scripts/pubmed_search.py` PubMed via NCBI E-utilities (public, no key required, rate limit: 3 req/sec). ``` --query <text> Required. Search query --max-results <N> 1-50 (default: 10) --sort <type> relevance | date (default: relevance) --years <N> Limit to last N years ``` Returns: PMID, title, authors, journal, year, DOI, abstract, MeSH terms, keywords, publication types. ### `scripts/semantic_scholar.py` Semantic Scholar API (public, no key required, rate limit: 100 req/5 min). ``` --query <text> Search query --paper-id <id> Paper ID (DOI:xxx, PMID:xxx, ArXiv:xxx) --related Get references of a paper (requires --paper-id) --citations Get papers citing a paper (requires --paper-id) --max-results <N> 1-50 (default: 10) --year-range <range> e.g., "2020-2026" or "2023-" ``` Returns: title, authors, year, abstract, TLDR, citation count, influential citations, DOI, ArXiv ID, open-access PDF URL. ### `scripts/chain_entry.py` Standard PharmaClaw chain interface. Searches both PubMed and Semantic Scholar, deduplicates, and sorts by citation impact. Input keys: `query`, `compound`/`name`, `target`, `disease`, `mechanism`, `reaction`, `topic`, `doi`, `pmid`, `max_results`, `years`, `context` Automatic query building: `{"compound": "aspirin", "disease": "colorectal cancer"}` → searches "aspirin colorectal cancer" ## Chaining | From | Input | To | |------|-------|----| | Chemistry Query | Compound name/SMILES | **Literature** → find published studies | | Catalyst Design | Reaction type | **Literature** → find catalyst optimization papers | | **Literature** | Key findings | Pharmacology → validate claims | | **Literature** | Synthesis references | Chemistry Query → retrosynthesis | | **Literature** | Patent mentions | IP Expansion → FTO analysis |