Qwen-Max: Journal Paper Generation from Title/Abstract Workflow Solution

Workflow overview

Why this workflow matters

Supports knowledge capture and document intelligence use cases.

Introduction Generates complete scientific papers from title and abstract using AI. Designed for researchers, automating literature search, content generation, and citation formatting. How It Works Extracts input, searches academic databases (CrossRef, Semantic Scholar, OpenAlex), merges sources, processes citations, generates AI sections (Introduction, Literature Review, Methodology, Results, Discussion, Conclusion), compiles document. Workflow Template Webhook → Extract Data → Search (CrossRef + Semantic Scholar + OpenAlex) → Merge Sources → Process References → Prepare Context → AI Generate (Introduction + Literature Review + Methodology + Results + Discussion + Conclusion via OpenAI) → Merge Sections → Compile Document Workflow Steps Input & Search: Webhook receives title/abstract; searches CrossRef, Semantic Scholar, OpenAlex; merges and processes references AI Generation: OpenAI generates six sections with in-text citations using retrieved references Assembly: Merges sections; compiles formatted document with reference list Setup Instructions Trigger & APIs: Configure webhook URL; add OpenAI API key; customize prompts Databases: Set up CrossRef, Semantic Scholar, OpenAlex API access; configure search parameters Prerequisites OpenAI API, CrossRef API, Semantic Scholar API, OpenAlex API, webhook platform, AlekSystem instance Customization Adjust reference limits, modify prompts for research fields, add citation styles (APA/IEEE), integrate databases (PubMed, arXiv), customize outputs (DOCX/LaTeX/PDF) Benefits Automates paper drafting, comprehensive literature integration, proper citations

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