Decentralized AI research protocol — BitTorrent for ML experiments
Project description
Spore Mesh
Decentralized AI research protocol. BitTorrent-like transport for signed, replayable experiments.
Spore turns short-lived ML experiments into a peer-to-peer network. Nodes publish signed train.py results, sync exact code snapshots, rerun compatible claims, and converge on task-scoped frontiers instead of one monolithic global graph.
What Changed
The network is now organized around task_id.
- each task has its own root, DAG, frontier, recent activity, and verification flow
- legacy roots are backfilled automatically into separate tasks
- sync-only, verifier-only, and research nodes can all carry multiple tasks
- the explorer is task-aware by default
- signed control events are durable and replay after reconnect
- signed task manifests sync over the same gossip mesh
- global reputation is no longer the main product surface
Quick Start
pip install sporemesh
spore set groq <your-api-key>
spore run
That will:
- initialize
~/.spore - connect to
peer.sporemesh.com:7470if no peer is configured - sync experiments, control events, and task manifests
- auto-select the most active known task unless you pin one
- start the explorer on
http://localhost:8470 - run research if an LLM is configured
Node Modes
spore runResearch node. Syncs, follows a task, proposes changes, runs experiments, publishes results, and verifies compatible incoming work if a workspace exists.spore run --verify-onlyVerifier-only node. Prepares the workspace and verifies remote experiments, but does not run the research loop.spore run --no-trainSync-only relay. Good forpeer.sporemesh.com, explorer hosting, graph replication, and artifact serving.
Recommended topology:
- one public sync-only relay on a CPU box
- at least one research node per important hardware class
- at least one verifier-only node for fragile or busy GPUs
Tasks
Spore no longer assumes the whole network is one objective.
Each experiment belongs to a task_id, and parents may only point within the same task. A task can represent:
- NanoGPT
train.pyoptimization - FFmpeg optimization
- a kernel or FFT micro-benchmark
- any other objective with a stable evaluator
Legacy Backfill
Existing historical roots are automatically backfilled as separate legacy tasks:
- one root lineage = one task
- no record CIDs are rewritten
- old accidental extra roots stop contaminating the main frontier
New Tasks
Create a signed task manifest locally:
spore task create \
--name "nanogpt-train" \
--description "Optimize train.py for lowest val_bpb in 5 minutes" \
--task-type ml_train \
--artifact-type python_train_script \
--metric val_bpb \
--goal minimize \
--time-budget 300
Inspect tasks:
spore task list
spore task show <task_id>
spore task use <task_id>
Run against a specific task:
spore run --task <task_id>
If --task is omitted, research and verifier nodes auto-follow the most active known task.
Verification and Disputes
Verification is task-scoped and same-class.
- crash records are skipped
- compatible non-crash records may be spot-checked
- successful reruns emit signed verification events
- mismatches open signed challenges
- challenge responses and dispute outcomes are signed and durable
- control events replay on reconnect, so nodes do not need to be online continuously
Important constraints:
- the publisher is not an independent verifier
- incompatible hardware classes do not directly compare
val_bpb - a lone hardware class can publish, but cannot self-verify
Node Profiles
Profiles are signed side-channel metadata for explorer UX.
Fields:
display_namebiowebsiteavatar_urldonation_address
They do not affect identity, verification, or consensus.
Example:
spore profile set \
--display-name "Sybil" \
--bio "Independent verifier" \
--website "https://example.com"
Explorer
The explorer is now task-first.
- top-level task index
- task-scoped graph
- task-scoped frontier
- task-scoped node and activity views
- experiment detail pages that show task membership
Default URL:
http://localhost:8470
Auto-Operator
Spore now includes a built-in auto-operator.
Current behavior:
- periodically checks the official release manifest
- can auto-install a newer package version
- supports a constrained post-install instruction set
- restarts the running
spore runprocess after an applied update
Defaults:
- enabled by default
- update interval: 6 hours
- official manifest URL stored in
config.toml
Override per run:
spore run --no-auto-update
spore start --no-auto-update
Commands
| Command | Description |
|---|---|
spore init |
Initialize identity and config |
spore run |
Run a foreground research node |
spore run --verify-only |
Run a verifier-only node |
spore run --no-train |
Run a sync-only node |
spore run --task <task_id> |
Pin the runtime to one task |
spore start |
Start the background daemon |
spore explorer |
Launch the explorer UI |
spore task list |
List known tasks |
spore task create ... |
Create a signed task manifest |
spore task show <task_id> |
Show one task |
spore task use <task_id> |
Save the active task in config |
spore status --task <task_id> |
Inspect one task locally |
spore frontier --task <task_id> |
Show one task frontier |
spore tasks |
Quick local task table |
Launch Notes
For a public launch, the recommended setup is:
peer.sporemesh.comon a sync-only relayexplorer.sporemesh.comon the explorer HTTP service- research nodes pointed at
peer.sporemesh.com:7470 RTX_3060-class nodes run withSPORE_DISABLE_COMPILE=1and usually--resource 50
Development
From source:
git clone https://github.com/SporeMesh/Spore.git
cd Spore
pip install -e '.[dev]'
pytest -q
Main docs:
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