Dehug

Problem Statement

DeHug is a decentralized hub where developers and researchers can publish, version, discover, and monetize AI models and datasets. Creators upload model weights and metadata, mint a Model NFT on Base that proves authorship and license terms, and optionally shard large artifacts to decentralized storage (IPFS/Filecoin/Arweave). Consumers can run inference directly (via on-chain triggered jobs routed to decentralized compute) or pull models through the DeHug Python SDK and pay usage fees that automatically distribute royalties to creators and collaborators.Key featuresModel NFTs (ERC-721/1155 + ERC-2981): On-chain ownership, licensing, and royalty rules (default 5% creator royalty, configurable splits).Immutable storage & provenance: Content-addressed artifacts (IPFS CIDs), signed manifests, and optional EAS attestations for lineage.Usage-based monetization: Pay-per-inference or subscription; automatic revenue splits to contributors (core author, data curators, evaluators).Developer-first SDKs: Python SDK for training/inference pipelines (TensorFlow, PyTorch, Transformers) + REST/Graph endpoints.Discovery & gamification: Trending models, contributor leaderboards, badges, and seasonal model-upload challenges and hackathons.Enterprise mode: Private spaces, audit/compliance logs, SSO, policy-locked licenses, and analytics dashboards.Who it’s forOpen-source model authors who want fair, programmable payouts.Research labs/enterprises needing verifiable provenance, usage analytics, and compliant decentralized storage/compute.Builders who want a “Hugging Face-like” experience—but with on-chain ownership, royalties, and composability in the Base ecosystem.

Solution

Architecture at a glanceFrontend: Next.js (App Router) + React + TypeScript + Tailwind/shadcn for a clean, fast UI. Wagmi + Coinbase Wallet for wallet flows; SIWE for auth.Smart contracts (Base):ModelRegistry.sol (tracks model IDs, owners, license URIs, content hashes, versions).ModelNFT.sol (ERC-721/1155) with ERC-2981 royalties; integrates 0xSplits (or equivalent) for multi-party revenue sharing.UsageController.sol for metered access tokens/passes and pay-per-inference receipts.Indexing & query: Subgraph (The Graph) to power search, trending, creator stats, and royalty histories.Storage: IPFS/Filecoin (via web3.storage/NFT.storage) for weights, tokenizer, configs, and a signed model manifest (JSON) that pins:artifact CIDs, SHA-256/Merkle root, license, dependencies, eval scores, and optional EAS attestations.Compute layer:Decentralized compute integration (e.g., 0G/other networks) for queued inference/training jobs triggered by on-chain receipts.OR serverless GPU fallback for the demo to guarantee live inference during judging.Client fallback: ONNX Runtime Web/WASM for small models to prove end-to-end portability.Backend services: FastAPI (Python) microservice for inference orchestration, model validation, and eval job runners; Node/Express for webhook + payments glue.Data & telemetry: Postgres for off-chain analytics; Prometheus/Grafana for usage metrics; Log drains for audit trails.Marketplace compatibility: OpenSea/Magic Eden ready via ERC-2981; royalties honored on secondary trades.Partner tech & why it helpedBase: low fees, EVM tooling, strong ecosystem → cheap mints, frequent updates, easy composability with DeFi/NFT infra.IPFS/Filecoin/Arweave: durable, verifiable storage → reproducible science and auditability.0xSplits (or similar): instant multi-party payouts → reward data curators, evaluators, and collaborators fairly.The Graph: fast queries for trending/leaderboards → smooth UX without hammering RPCs.EAS (Ethereum Attestation Service): optional provenance attestations → trust signals for enterprises and researchers.Notable hacks we’re proud ofModel Manifest v0: a signed JSON schema that deterministically binds code, weights, license, evals, and dependencies; we compute a Merkle root over all files, store leaf hashes in IPFS DAGs, and stamp the root on-chain for tamper-evident provenance.Sharded weight uploads: chunked TARs with streaming pin + parallel verification to keep large models responsive in the browser.Usage-as-receipt flow: a tiny “inference pass” NFT minted/burned per job; acts as both a payment receipt and cache-key for replays.WASM fallback: for small models, we demo end-to-end inference fully in-browser with ONNX Runtime Web—no server, no GPU—just to prove portability.What’s working in the MVPUpload → pin → mint Model NFT on Base → run inference (decentralized or fallback) → auto-distribute creator royalty (default 5%) → list on marketplace.Python SDK: dehug login, dehug push, dehug pull, dehug infer with examples for PyTorch/Transformers.Discovery: basic search, tags, trending, and contributor badges seeded by hackathon challenge uploads.