[FEATURE] Signed Document Exporter (PDF + Metadata)

[erik-sv]

Problem Statement

Many organizations — especially in publishing, legal, HR, or academic settings — need to preserve and share AI-generated content in portable, non-editable formats like PDF. However, EncypherAI currently only supports plain text output, and there’s no way to retain or display the embedded metadata in shareable documents (unless content is copy-pasted or inserted directly)

Proposed Solution

• Add support for exporting AI-generated text + its metadata as a cryptographically signed PDF.
• Embed metadata visibly (e.g., footer, summary page, QR code) or invisibly (e.g., PDF metadata fields).
• Optionally include a hash-based signature to prove the PDF was not altered after export.
• Add a CLI command: encypher export --pdf

Alternative Solutions

• Share plain .txt and .json bundles, which are not user-friendly and often get separated.
• Manual copy-paste into third-party document tools, which may strip metadata.

Use Cases

1. An academic institution submits an AI-generated appendix or summary with full verifiable metadata in a publication-ready PDF.
2. An HR team archives candidate interviews or summaries generated by AI with built-in origin tracking.
3. A journalist attaches verifiable metadata to a submitted AI-assisted article before sending to editors.

Implementation Ideas

• Use Python libraries such as reportlab, PyMuPDF, or fpdf for PDF generation.
• Embed metadata in PDF properties (/Keywords, /Subject, custom fields) and optionally render visible text or QR with metadata summary.
• Support an optional signing step using SHA-256 hash or digital signature for tamper detection.
• Include a verification hash at the end of the document for offline validation.

Additional Context

This bridges the gap between machine-readable metadata and human-readable deliverables. It also helps institutions meet documentation, compliance, and audit requirements for responsible AI usage.

Future extension: add support for exporting to DOCX, HTML, or Markdown with embedded metadata.