RDLLM Project Attribution Map

RDLLM is an attribution system, so the project documentation must also be attributed. This page explains what the repository was built from, where each source class is recorded, how those sources shaped the system, and how a reader can verify the claims.

Short Version

What Was Built

RDLLM is a provider-neutral source-attribution, source-footer, and royalty-settlement reference implementation for AI outputs. It contains:

Source Classes

Source class Where it is attributed How it shaped RDLLM
Creator revenue and rights-management analogies docs/evidence.html, paper/references.bib Fixed creator-pool framing, payout/escrow language, rights-conflict handling, and registry-dispute handling.
Source attribution, citation, RAG, and claim-verification papers docs/recent_research.html, docs/references.html, paper/rdllm_white_paper.html, paper/references.bib Claim Evidence rows, citation-marker gates, answer-link gates, source-disagreement gates, source-footer verification, and answer-claim coverage.
Data valuation and influence research docs/evidence.html, paper/references.bib Training-value priors, residual attribution concepts, counterfactual checks, and model-signal boundaries.
Provenance, credentials, trace, and transparency standards docs/evidence.html, docs/references.html, docs/schemas Verifiable receipt formats, PROV-shaped exports, VC-shaped credentials, OpenTelemetry-style trace exchange, transparency-log language, and schema-first artifact design.
Rights, licensing, and machine-readable policy standards docs/evidence.html, docs/mechanism.html, docs/schemas ODRL/Croissant/SPDX-aligned rights metadata, source-access leases, creator license contracts, consent revocation, and escrow routing.
Production security and public-sector guidance docs/recent_research.html, docs/production_readiness.html, docs/operator_runbook.html NIST AI RMF, NIST SSDF, OWASP LLM Top 10, SLSA, launch gates, operator profiles, support bundles, and fail-closed production readiness.
Provider API and runtime documentation docs/provider_onboarding.html, docs/provider_compatibility_matrix.html Provider-family routing, usage-meter normalization, response-state normalization, streaming final-state requirements, and source annotation normalization.
Public documentation and discoverability guidance docs/recent_research.html, docs/github_start_here.html, docs/public_explainer.html GitHub start guide, public explainers, localized quickstarts, API examples, SEO/GEO notes, and docs-readiness audit.
Repository-authored code and tests src/rdllm, tools, tests Deterministic attribution engine, verifiers, service boundary, operator tooling, package smoke, and shipping gate.

How Sources Become Product Rules

RDLLM does not treat a paper, standard, or platform analogy as a feature by itself. A source becomes part of the system only when it is converted into an auditable rule:

  1. The source is recorded in docs/recent_research.html, docs/evidence.html, docs/references.html, or paper/references.bib.
  2. The rule is implemented in src/rdllm or tools.
  3. The runtime output or artifact shape is captured in docs/schemas.
  4. Tests or smoke scripts prove the behavior.
  5. User-facing docs show the exact field names that users will see.

Example: source-disagreement research becomes rdllm-visible-source-disagreement/v1, visible disagreement, agreements, and conflicts fields in Claim Evidence rows, verifier failures when visible sources plainly contradict claims, schema fields, tests, and README runtime examples.

Code Attribution

The repository code is authored for this project and distributed under the repository license. The Python package has no required runtime dependencies in pyproject.toml; development checks use optional tooling such as build and jsonschema.

Important code locations:

Paper And Research Attribution

The paper source is paper/royalty_driven_llm_paper.html. The public concept white paper is paper/rdllm_white_paper.html; it explains the state-of-the-art evidence base, runtime architecture, allocation mechanism, threat model, and public-readiness posture. The BibTeX bibliography is paper/references.bib. The public human-readable reference index is docs/references.html. Current implementation-facing research notes are in docs/recent_research.html.

When a new research source changes behavior, the repository should update:

Runtime Example Attribution

Runtime examples in public docs should be derived from commands, not invented:

PYTHONPATH=src python3 -m rdllm.cli answer "How should AI prove attribution?"
PYTHONPATH=src python3 tools/service_smoke.py
PYTHONPATH=src python3 tools/provider_live_smoke.py
PYTHONPATH=src python3 tools/package_smoke.py

These commands produce source rows, support scores, text-match values, Claim Evidence rows, payout fields, display hashes, and verifier statuses used in the README and example docs.

Public Artifact Attribution

Public artifacts are generated and verified through the repository gates. The canonical source files are in artifacts/. Hosted copies for static discovery are exported to docs/.well-known/rdllm/ and indexed by docs/.well-known/rdllm.json.

Verify hosted artifacts:

PYTHONPATH=src python3 tools/hosting_export.py --check
PYTHONPATH=src python3 tools/hosted_surface_audit.py
PYTHONPATH=src python3 tools/public_surface_privacy_audit.py

Documentation Attribution

Public-facing docs follow a layered model:

The public docs are checked by:

PYTHONPATH=src python3 tools/github_docs_readiness_audit.py
PYTHONPATH=src python3 tools/docs_link_audit.py

Verification Commands

Use these commands to audit the repository's public-facing claims:

PYTHONPATH=src python3 tools/github_docs_readiness_audit.py
PYTHONPATH=src python3 tools/docs_link_audit.py
PYTHONPATH=src python3 tools/ship_check.py --skip-tests --skip-regenerate
PYTHONPATH=src python3 -m unittest discover -s tests

If any command fails, the corresponding public claim should not be treated as ready.