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feat: first-run wizard + auto-detect inference — turn new users into inference buyers on Day 1

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Valutazione

Difficoltà
5/5
Tempo stimato
Più di una settimana
Idoneità per principianti
28/100
Tipo di issue
Funzionalità
Chiarezza
Abbastanza chiara
Stato di attività
Tranquilla
Stack tecnologico
go
Ambito
backend-api-design, blockchain, cli

Direzione di ricerca

Inizia con il flusso esistente di obol setup e l’implementazione di obol sell http da PR #288, quindi esamina l’interfaccia proposta discovery/public.go e le dipendenze da issue #300/PR #302. Usa il piano di test elencato per definire il completamento: rilevamento al primo avvio, individuazione dei modelli locali, ServiceOffers pubblici, obol buy http, proxy dei pagamenti e flusso dell’acquirente end-to-end.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Summary

Improve obol-stack onboarding by auto-detecting available inference endpoints and enabling new users to buy inference immediately — before they even set up their own node.

Inspired by hermes-agent PR NousResearch/hermes-agent#4194 which fixes first-run wizard triggering and adds model auto-detection for local endpoints.

Motivation

Current onboarding assumes the user wants to serve inference. But the fastest path to value is letting them buy inference first:

  1. User installs obol-stack
  2. Wizard detects no local GPU / no llama-server running
  3. Instead of stopping, it queries public ERC-8004 registry (via 8004scan.io API or BaseScan) for available inference ServiceOffers
  4. Shows a list: "These models are available on the network. Want to connect?"
  5. User picks one, pays via x402 per-request — they're using the network in 60 seconds
  6. Later, they add their own GPU and become a seller too

This is the DePIN flywheel: make it trivially easy to be a buyer first, then convert buyers into sellers.

Design

Phase 1: Local auto-detection (from hermes-agent #4194)

When obol setup runs:

  1. Probe local endpoints — scan localhost for common inference servers:

    • llama-server (port 8080)
    • ollama (port 11434)
    • vllm (port 8000)
    • litellm (port 4000)
    • Any custom endpoint the user provides

  2. Auto-detect models — if a server responds, hit /v1/models endpoint:

    • One model found → auto-select, confirm with user
    • Multiple models → numbered list, user picks
    • No server → skip to Phase 2

  3. Don't silently borrow credentials — if the user has never configured obol-stack, don't assume existing services are intended for obol. Always ask.

Phase 2: Network discovery — become a buyer

If no local inference is found (or user wants more options):

  1. Query public ERC-8004 registry for registered inference ServiceOffers:

    • Primary: 8004scan.io API (if available)
    • Fallback: BaseScan API for ERC-8004 token metadata
    • Filter by OASF skill: natural_language_processing/natural_language_generation/text_completion

  2. Display available services with pricing:

    Available inference on the network:

1. qwen3.5-27b-q6k @ node-xyz    — /usr/bin/bash.001/req — 15/15 ToolCall-15
2. llama-3-70b-q4   @ node-abc    — /usr/bin/bash.002/req — 14/15 ToolCall-15  
3. mistral-24b       @ node-def    — /usr/bin/bash.0008/req — 13/15 ToolCall-15

Connect to one? (payment via x402 USDC on Base)

  3. One-command connect:

    obol buy http --from node-xyz --model qwen3.5-27b

    This configures the local Hermes agent to route inference through the selected node, paying per-request via x402.

Phase 3: Buyer-to-seller conversion

Once a user is buying inference and sees the economics:

  • "You've spent $4.20 on inference this week. Your RTX 3090 could earn $12/week serving Qwen3.5-27B."
  • obol sell http --upstream llama-server --price 0.001 — one command to flip from buyer to seller

Implementation Notes

First-run guard (from hermes-agent #4194)

The key insight from the hermes-agent PR: check whether obol-stack itself has been configured before looking at what's running on the machine. If the config is empty or default, trigger the wizard regardless of what services are detected.

// Don't skip setup just because llama-server is running
if !config.IsConfigured() {
    runSetupWizard()  // always ask on first run
}
ERC-8004 public discovery

For Phase 2, we need a lightweight client that can query registered ServiceOffers without running the full reth-indexer:

// discovery/public.go
type PublicDiscovery interface {
    ListServiceOffers(skill string) ([]ServiceOffer, error)
}

// Implementations:
// - 8004ScanClient (preferred, purpose-built API)
// - BaseScanClient (fallback, reads ERC-8004 NFT metadata)
// - RethIndexerClient (if running locally)
obol buy http (new command)

Mirror of obol sell http but for the buyer side:

obol buy http \
  --from <node-address-or-erc8004-id> \
  --model <model-name> \
  --max-price 0.002 \       # won't pay more than this per request
  --configure-hermes         # auto-configure Hermes agent to use this endpoint

This generates the x402 payment headers for each request and proxies through to the seller's endpoint.

Dependency on existing PRs

  • PR #288: obol sell http command, ServiceOffer CRD, x402 payment parsing
  • Issue #300 / PR #302: inference lifecycle (model registry, hardware detection)
  • The reth-erc8004-indexer (optional, for self-hosted discovery)

Test Plan

  • First-run wizard triggers on fresh install even if llama-server is running
  • Local endpoint probe correctly identifies llama-server, ollama, vllm, litellm
  • Model auto-detection lists available models from /v1/models
  • Single model auto-selects with user confirmation
  • Public ERC-8004 query returns registered inference ServiceOffers
  • obol buy http configures x402 payment and proxies requests
  • Buyer-to-seller prompt triggers after N requests or $X spent
  • End-to-end: fresh install → buy inference → use via Hermes agent

Labels

component:onboarding component:inference component:erc8004 priority:high

Lingua principale
Go
Stelle
11
Fork
1
Merge medio
1h 20m
PR unite (30g)
39

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