pysyrev — Python Systematic Review

pysyrev is an automated, LLM-assisted PRISMA workflow for systematic literature reviews. It covers the full pipeline — from raw bibliographic records to screened, deduplicated, and thematically structured corpora — and produces a PDF report at the end.

Features

• Multi-source ingestion — Web of Science (file or REST API), OpenAlex (file or REST API), Scopus, PubMed

• Automatic deduplication — fuzzy title matching across sources

• LLM-based screening — multi-reviewer workflows with majority or mean voting, powered by any provider supported by LiteLLM (Anthropic, OpenAI, Ollama, LiteLLM proxy…)

• Bibliographic network analysis — bibliographic coupling and co-citation graphs exported as GraphML

• Topic modelling — BERTopic-based clustering with UMAP + HDBSCAN grid search, ranked by coherence scores

• PDF report generation — declarative, theme-aware PDF engine built on ReportLab

Pipeline stages

Stage	Key	Description
Bibliography	bib	Fetch, clean, filter, deduplicate, and optionally resolve references
LLM review	review	Screen documents against inclusion/exclusion criteria with one or more LLM reviewers
Bibliographic network	bib-network	Build coupling and co-citation networks from the included corpus
Topic modelling	topic-model	Cluster documents into topics using BERTopic; rank configurations by coherence
Report	topic-report	Generate a PDF report from the selected topic model run

All sections are optional — only the stages declared in the config file are executed. Each stage auto-detects the most recent output of the previous one when run standalone.

Contents

• Installation
  • Prerequisites
  • From source
  • Optional extras
  • API keys
• Quick start
  • CLI
  • Python API
  • Report-only run
  • Auto-detection between stages
• Configuration reference
  • Root level
  • bib — bibliography collection
  • review — LLM-based title/abstract screening
  • bib_network — bibliographic networks
  • topic_model — BERTopic clustering
  • topic_report — PDF report generation
  • llm — topic label generation
  • report — PDF layout
• API reference
  • Pipeline
  • Bibliographic sources
  • Bibliographic network
  • LLM review
  • Topic model
  • Configuration classes