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| # 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` | |