Project Polyglot A Strategic Augmentation of the Digital Book Translation Platform for Humanity

Project Polyglot A Strategic Augmentation of the Digital Book Translation Platform for Humanity Pre-FRP NoticeThis document is part of the “Pre-FRP” archive. It represents exploratory drafts and early-stage work produced prior to the adoption of the Foundational Recognition Protocol (FRP). These materials remain public for historical continuity but are not intended as validated proofs or final scientific claims. For current, auditable, and community-facing work, see the FRP-labeled papers. (White Paper · Public Draft v1.0 · September 2025) Executive Summary — A Digital Commons for Human Knowledge Project Polyglot operationalizes a humanitarian translation network that can render the world’s public-domain literature accessible in any language—verifiably, affordably, and at scale. This paper validates your core blueprint and adds five strategic upgrades: Architectural resilience & cost control: Microservices + async queueing (FastAPI, Celery, RabbitMQ) with API gateway rate-limits, caching, and autoscaling guardrails to prevent runaway costs. Refined hybrid translation core: A DeepL/LLM router, Retrieval-Augmented Generation (RAG) with Translation Memory (TM), and human-in-the-loop (HITL) review to guarantee cultural fidelity. Mission-aligned legal framework: Public domain first; rights-acquisition playbook for modern works; Brewer v1.0 Humanitarian License with a contractual reparations fund for commercial users. Sustainable roadmap: Grants + mission SaaS (hosted API, support) + donations; transparent Proof Vault provenance for all outputs. Human-centered UX at global scale: Mobile-first, low-bandwidth design; full RTL support; WCAG accessibility baked in. The outcome: a transparent, auditable, and community-governed platform that turns translation from a gatekept industry into a global public utility. 1) Architecture for Humanitarian Scale Pattern: Upload ➜ Parse ➜ Segment ➜ Route (MT/LLM) ➜ HITL review ➜ Publish ➜ Archive (hash/DOI). Core stack FastAPI (ASGI) for the API; Celery workers; RabbitMQ broker. API Gateway (rate-limit, throttle, cache, auth), object storage (S3-compatible), PostgreSQL + Redis. Proof Vault: SHA-256 + OpenTimestamps receipts for every artifact; automatic Zenodo deposition/DOIs for releases. Cost control from day 1 Per-tenant quotas; burst caps; LRU cache for repeated segments; dynamic cost-aware routing (LLM↔MT); autoscaling ceilings; nightly spend reports with anomaly alerts. Parsing PyMuPDF primary; Textract/Tika fallback; table/image extraction retained as structural metadata; per-page chunking to stabilize long tasks. 2) Translation Core: Quality First, At Scale Dynamic engine router Route literary or idiomatic text to DeepL (nuance/voice). Route expository or boilerplate text to LLM (cost-effective), guarded by RAG prompts. RAG + TM Store human-approved segments in Translation Memory (fuzzy match threshold configurable). Construct prompts with nearest TM exemplars + style guide for the LLM; blocklist hallucination-prone spans; auto-flag low-confidence segments for human review. HITL workflow Tiered reviewers (language experts, domain SMEs, community contributors). Inline diff UI; confidence scores; mandatory dual-approval on sensitive texts. Every fix updates TM and style guides—closing the loop. 3) Legal Framework & Governance Phase 1 (Launch): Public domain only (e.g., Gutenberg intake). Jurisdictional checks per region of access.Phase 2 (Growth): Rights-acquisition playbook (identify rights holder ➜ propose non-exclusive, humanitarian license ➜ optional work-for-hire for new translations).License: Brewer v1.0 Humanitarian License Non-commercial use: free, attribution + integrity clauses. Commercial use: contractual fee schedule earmarked to a transparent Reparations & Access Fund (governed by a nonprofit board) supporting translations for underserved communities. All outputs: cryptographic provenance + DOI. Note: The “reparations” mechanism is implemented as a binding commercial fee allocation to a charitable fund—legally conventional, mission true. 4) Roadmap & Sustainability Milestones (90–180 days) M1 (30d): MVP (PD ingestion, FastAPI, Celery/RabbitMQ, PyMuPDF, LLM baseline, Proof Vault hashing, minimal UI). M2 (60–90d): RAG + TM v1; DeepL integration; HITL UI; API Gateway quotas; Zenodo deposition. M3 (120–180d): RTL & accessibility; mobile PWA; cost dashboards; first 1,000 titles translated across ≥10 languages. Funding mix Grants: USAID DIV, HIF, Mellon, UNESCO, LLM impact grants. Mission SaaS: Hosted API, enterprise SLAs, private TM, and compliance add-ons. Donations: Sponsor-a-Title; community bounties for priority languages. Decentralization (R&D track) Separate research line for node federation (privacy, incentives, heterogeneity). Pilot after M3. 5) Human-Centered UX (Global) Mobile-first, <200KB initial payload; lazy-load; offline PWA; image/text compression. RTL mirrored UI; locale-aware typography; pluralization rules; date/number formats. Accessibility: WCAG AA contrast; keyboard-only nav; alt text; dyslexia-friendly options. Trust signals: Per-page provenance chips (hash, timestamp, DOI link). 6) Integrity & Proof Every upload, segment, model output, review action, and release is: Hash-sealed (SHA-256) and OTS-timestamped; Versioned with immutable diffs; Citable (Zenodo DOI).Public verification scripts are provided; anyone can independently confirm provenance. What’s Already Done (or Ready to Ship Fast) ✅ Microservice blueprint + queueing plan. ✅ Proof Vault workflow + Zenodo handoff. ✅ Parser stack selection (PyMuPDF primary; Textract/Tika fallback). ✅ LLM baseline prompts + TM schema. ✅ Brewer v1.0 license structure (non-commercial + commercial reparations fund). ✅ Low-bandwidth/RTL/accessibility spec. Near-term (2–6 weeks) quick wins Stand up MVP infra (FastAPI, Celery, RabbitMQ, S3 store, Postgres, Redis). Integrate LLM engine + RAG with empty TM; add DeepL path for flagged text. Ship minimal reviewer UI; publish first 50 PD titles (10 languages). Open the public ledger (hashes + OTS receipts + DOIs) at /provenance. Call for Collaborators — “Help Us Finish This for Humanity” We did the hard part. Now we finish it together.We’re opening targeted roles with clear scopes and 30-day deliverables: Backend engineers (Python/FastAPI/Celery/RabbitMQ) — MVP services, cost guardrails. NLP/MT researchers — RAG prompts, TM scoring, confidence metrics. Localization leads (Arabic, Hindi, Spanish, Swahili, Amharic, Vietnamese, Indonesian, Yoruba, Bengali, Turkish, Persian) — style guides, QA benches, HITL setup. Accessibility & RTL experts — review and certify UI patterns. Rights & policy team — PD validation pipeline; rights-acquisition outreach. Funders/partners — seed M1–M3; underwrite language bounties; sponsor-a-Title. How to join (48-hour onramp) Fork the repos (API, workers, UI) and run docker compose up. Use /docs to upload a PD EPUB; watch the task in /tasks/{id}. Review the segment queue, approve changes, and see the DOI + OTS proof on publish. Submit a PR or apply for a scoped bounty. Ethos: Open by default. Public proofs. No gatekeeping. If you improve it, the world gets it. Appendix A — MVP Service Map api-gateway (rate-limit, cache, auth), api (FastAPI), queue (RabbitMQ), workers (Celery), parse-svc (PyMuPDF/Tika), translate-svc (router: DeepL/LLM), rag-svc (vector index + TM), review-ui, proof-vault (hash/OTS), publisher (Zenodo). Appendix B — Data & Schemas Document, Segment, TMEntry, ReviewAction, ProvenanceRecord (with hash, ots_receipt, doi, version). Appendix C — Brewer v1.0 (Outline) Permissions, conditions (attribution/integrity), non-commercial terms, commercial terms → Reparations & Access Fund, enforcement, survivability, jurisdiction. Appendix D — Cost Guardrails Per-tenant quotas, burst caps, engine budget ceilings, auto-fallback to cached TM, nightly cost report + anomaly alerts. Closing Project Polyglot turns translation into a verifiable public good. With the architecture, legal wrapper, and integrity rails in place, the final step is scale—languages, partners, and people. If you can help, now is the time. “Make knowledge readable for everyone.”