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Updated July 1, 2026

Start Mining: From Fork to Live

The hands-on path to mining Ditto SN118: fork the reference harness, practice off-chain against DittoBench with your own OpenRouter key, then submit on-chain when your score is strong.

Start Mining: From Fork to Live

This is the practical path from a fresh checkout to a live, scored submission. The golden rule: practice off-chain until your score is strong, then pay to submit on-chain. Practice is free and uses the exact same scoring loop, so there’s no reason to spend TAO on a harness you haven’t measured.

1. Start from the starter kit

Fork the dittobench-starter-kit — a complete, working Rust harness that depends on the ditto-harness crate. It already implements the contract validators score:

  • the memory tools: save_memory, search_memories, search_subjects, search_memories_in_subjects, fetch_memories
  • an importable agent loop that uses them
  • the full production retrieval stack, wired and active: vector candidate pool → composite ranking (multiple signals + a learned fusion-weight MLP) → cross-encoder rerank

src/baseline.rs is where you start — it’s the marked extension point that wires the DB, embedder, model, ranker, and reranker together. But you submit the whole crate, so nothing limits you to it: change reranker.rs, retrain or swap the ranking models in fixtures/models/, edit the tool catalog, add files — anything that raises recall and tool accuracy without blowing your latency budget.

2. Practice against DittoBench (off-chain, free)

The dittobench-starter-kit is the official practice bench. It runs the same generate → seed → run → score loop the on-chain validators use, but off-chain and with your own model key:

  • Bring your own key — supply an OpenRouter API key per run; nothing is stored.
  • Fresh dataset every run — tool cases are paraphrased and the memory “haystack” is reassembled with distractors and new timestamps each time, so there’s no static answer key to memorize.
  • Run sizes — small for fast iteration, up to full for a realistic pass.

You get back a composite score (plus tool accuracy, memory recall, and median latency). Drive that number up. There’s also a hosted DittoBench practice API so you can score a deployed harness over HTTP — the starter kit README has the current endpoint and usage.

Why practice matters: on-chain submission costs a fee and every scored run uses a brand-new dataset. Overfitting is impossible and re-submitting isn’t free — so the harness you submit should already be winning off-chain.

3. Register and fund your keys

To submit on-chain you need:

  • A hotkey registered on netuid 118 (finney). Registration is standard Bittensor — register your hotkey on the subnet.
  • A funded coldkey. The submission fee is a small transfer (~$5 in TAO, see Submitting) signed by the coldkey that owns your hotkey.

4. Package your harness

The starter kit packages the whole crate for you:

cargo run -- submit   # writes dittobench-submission.tgz (the whole crate)

The tarball is the entire crate (source, Cargo.toml/Cargo.lock, and the model fixtures), minus build artifacts — it must build and run inside an isolated Docker sandbox. The platform recomputes the tarball’s lowercase-hex SHA-256 on upload and checks it against the hash you sign, so the bytes you sign are the bytes that get scored.

Size: the platform accepts tarballs up to 5 MB — comfortably enough for the default submission, which is the whole crate plus the shipped ranking models (cross-encoder.onnx ~4.3 MB + mlp-weights.bin ~848 KB, ~4.6 MB total). If you vendor substantially larger weights, keep an eye on that budget.

5. Submit

When your off-chain score is where you want it, submit on-chain. The ditto miner CLI (rolling out with launch) automates the whole flow — quote the fee, pre-check, pay, upload, and poll:

# Shape of the miner CLI (rolling out for launch)
ditto upload --path ./my-harness.tar.gz --name "my-harness" \
  --wallet.name <coldkey> --wallet.hotkey <hotkey> --network finney
ditto status <agent_id>

Prefer to drive it yourself? The full HTTP flow — pricing, pre-check, on-chain payment, verified upload, and status polling — is documented step by step in Submitting to Subnet 118.

6. Watch it get scored

After a successful upload you get an agent_id. Poll its status as it moves uploaded → screening → evaluating → scored → live. Once it’s live, it’s competing for weight. See Scoring & Rewards for how the number is computed and how emissions are shared.