docs/data-models.md

Data Models: ResearchLink AI

All data models are Pydantic v2 BaseModel subclasses.

IngestionInput (schemas/inputs.py)

User-provided inputs. Requires at least one source.

Key fields: paper_pdf_path, paper_pdf_url, paper_url, github_url, bibtex, author_notes, target_output_dir, force_overwrite

ResolvedSources (schemas/inputs.py)

After source resolution. Tracks what's available.

Key fields: local_pdf_path, pdf_available, paper_url_reachable, github_url_reachable

PaperExtraction (schemas/paper.py)

Raw text and structure from PDF.

Key fields: full_text, title_candidates, abstract, section_headings, references_raw, extraction_complete, confidence

PaperMetadata (schemas/paper.py)

Structured paper metadata.

Key fields: id, title, year, status, venue, authors_provisional, areas, tags, slug, verification, confidence

CitationEntry + CitationReport (schemas/citations.py)

Per-reference and aggregate citation analysis.

Key enum: CitationStatus — verified, needs-verification, placeholder, incomplete, conflict

RepoAnalysis (schemas/repository.py)

GitHub repository inspection results.

Key fields: owner, repo_name, readme_content, detected_language, detected_frameworks, setup_commands, is_likely_official_impl

GenerationReport (schemas/outputs.py)

Final pipeline summary.

Key fields: slug, output_dir, files_generated, errors, warnings, quality_flags, success, duration_seconds