neomorph98/literature_ai_system

literature_ai_system is a Python-based system that automates literature collection, reading, analysis, and synthesis. It fetches papers from academic sources (Google Scholar, PubMed, arXiv) and ingests local PDF files, then uses AI pipelines to summarize findings, extract consensus and points of disagreement, and generate reasoned viewpoints. Intended users - Researchers, graduate students, systematic reviewers, R&D engineers, clinicians, and policy analysts who need rapid literature synthesis and structured summaries. Key features - Multi-source ingestion: scrapers for Google Scholar, PubMed, arXiv plus local PDF import. - Text processing: PDF parsing, chunking, metadata extraction. - Semantic indexing and retrieval using LangChain / LlamaIndex. - LLM-based tasks: concise summaries, consensus extraction, disagreement/contradiction detection, argument and viewpoint generation. - Modular pipelines: configurable components and model backends. - Local deployment via Docker for private/offline use.

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