feat(supplier): HuggingFace Inference Providers router backend preset

OpenAI-compatible compute-backend preset (config only, reuses LLM_BACKEND=openai) for pointing a supplier node at the HuggingFace Inference Providers router. Adds a boot guard that rejects the OpenRouter-only reasoning param against the HF router, unit tests, and an operator runbook.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

supplier/.env.huggingface-chat.example

@@ -0,0 +1,114 @@
+# supplier/.env.huggingface-chat.example
+#
+# Preset for a chat supplier that uses the HuggingFace Inference Providers router
+# (https://router.huggingface.co) as its COMPUTE BACKEND to fulfil bonded
+# inference work commissioned on Vector. It is the OpenAI-compatible on-ramp:
+# the router is OpenAI-compatible, so this reuses the existing LLM_BACKEND=openai
+# path with NO code changes — it is config only.
+#
+# Copy to supplier/.env on the host (chmod 600) and fill in real values.
+# .env is gitignored — NEVER commit a populated copy.
+#
+# Runbook: docs/HUGGINGFACE_ROUTER_SETUP.md
+#
+# To generate a fresh Ed25519 wallet seed:  openssl rand -hex 32
+# Lines marked SECRET must never be shared, logged, or committed.
+
+# ─── Required ─────────────────────────────────────────────────────────────
+
+# 64-char hex Ed25519 private key seed for this supplier's wallet. SECRET.
+SUPPLIER_PRIV_KEY_HEX=PASTE_64_HEX_CHARS_HERE
+
+# Ogmios WebSocket URL. Testnet shown; use the mainnet URL for NETWORK_ID=1:
+#   testnet: wss://ogmios.vector.testnet.apexfusion.org
+#   mainnet: wss://ogmios.vector.mainnet.apexfusion.org
+OGMIOS_URL=wss://ogmios.vector.testnet.apexfusion.org
+
+# OutputReference of this supplier's on-chain advertisement UTxO.
+# Format "<64-hex-tx-hash>#<int>". Post it first (see tx:post-advert below),
+# then paste the printed "<txHash>#0" here.
+ADVERT_REF=PASTE_TXHASH_HERE#0
+
+# Cardano network ID. "0" = testnet, "1" = mainnet. Keep "0" until you have
+# validated the setup end-to-end on testnet.
+NETWORK_ID=0
+
+# ─── Backend: HuggingFace router (OpenAI-compatible) ──────────────────────
+# Route the chat job runner at the HF Inference Providers router instead of a
+# local Ollama. The supplier POSTs to ${OPENAI_BASE_URL}/v1/chat/completions.
+LLM_BACKEND=openai
+
+# HF router base URL. The supplier appends /v1/chat/completions itself, so do
+# NOT include the /v1 suffix here.
+OPENAI_BASE_URL=https://router.huggingface.co
+
+# HuggingFace access token (starts with "hf_"). Create one at
+# https://huggingface.co/settings/tokens with "Make calls to Inference
+# Providers" permission. Forwarded as `Authorization: Bearer <token>`. SECRET.
+OPENAI_API_KEY=PASTE_HF_TOKEN_HERE
+
+# First-token latency across hosted providers can exceed local Ollama — keep a
+# generous request timeout.
+OPENAI_TIMEOUT_MS=180000
+
+# ─── IMPORTANT: do NOT set OPENAI_REASONING here ──────────────────────────
+# `reasoning:{enabled:false}` is an OpenRouter-only param. The HF router
+# rejects it with HTTP 400 on every request. The supplier refuses to boot if
+# OPENAI_REASONING is disabled while OPENAI_BASE_URL points at the HF router.
+# (This is the #1 footgun when copying an OpenRouter env — leave it unset.)
+# OPENAI_REASONING=
+
+# Optional hard ceiling forwarded as `max_tokens`. Unset = provider grants the
+# max available (context − prompt). Keep below the model's context window.
+# OPENAI_MAX_TOKENS=
+
+# ─── Enable real chain submissions ────────────────────────────────────────
+# LIVE_CHAIN: only the literal "1" opts in to real Claim/Submit txs. Leave
+# unset for a dry run (read-only, no chain writes) while testing.
+LIVE_CHAIN=
+
+# HTTP listen port inside the container. Compose maps this to the host.
+PORT=8080
+
+# ─── tx:post-advert — run once before first deploy ────────────────────────
+# Execute (from repo root):
+#   pnpm --filter @marketplace/supplier tx:post-advert \
+#     --capability-id llm.text.generate.v1 \
+#     --model deepseek-ai/DeepSeek-V3:fastest \
+#     --max-output-tokens 512 \
+#     --max-processing-ms 60000 \
+#     --price-lovelace 2000000 \
+#     --endpoint-url https://mp-supplier.vector.testnet.apexfusion.org
+# Copy the printed "<txHash>#0" into ADVERT_REF above.
+#
+# NOTE on --model: HF uses PROVIDER-QUALIFIED model names. The bare id picks a
+# default provider; a ":<hint>" suffix pins routing:
+#   deepseek-ai/DeepSeek-V3:fastest    # cheapest/fastest provider for the model
+#   deepseek-ai/DeepSeek-V3:together   # pin a specific provider
+#   openai/gpt-oss-120b                # open-weight, HF-hosted
+# Browse models + providers at https://huggingface.co/models?inference_provider=all
+# The value lives on-chain in AdvertDatum.model — it is data, not code, so you
+# can advertise any router-supported model without touching the supplier.
+ADVERT_CAPABILITY_ID=llm.text.generate.v1
+ADVERT_MODEL=deepseek-ai/DeepSeek-V3:fastest
+ADVERT_MAX_OUTPUT_TOKENS=512
+ADVERT_MAX_PROCESSING_MS=60000
+
+# Flat AP3X amount committed in escrow per job (1 AP3X = 1_000_000 lovelace).
+# The HF backend meters PER TOKEN while this committed amount is fixed per job,
+# so size it for your worst-case prompt length and cap output tightly via
+# ADVERT_MAX_OUTPUT_TOKENS. See docs/HUGGINGFACE_ROUTER_SETUP.md §4.
+ADVERT_PRICE_LOVELACE=2000000
+ADVERT_SUPPLIER_BOND_LOVELACE=1000000
+ADVERT_BUYER_BOND_LOVELACE=1000000
+
+# HTTPS endpoint buyers will call (must be publicly reachable).
+ADVERT_ENDPOINT_URL=https://mp-supplier.vector.testnet.apexfusion.org
+
+# Optional off-chain detail pointer + its sha256 (leave empty for v1).
+ADVERT_DETAIL_URI=
+ADVERT_DETAIL_HASH=
+
+# ─── Optional: CIP-33 reference scripts (recommended on mainnet) ──────────
+# ESCROW_REF_UTXO=<txhash>#0
+# ADVERT_REF_UTXO=<txhash>#1

supplier/src/config.ts

@@ -15,7 +15,10 @@
  *
  * Required for CAPABILITY_KIND="chat" + LLM_BACKEND="openai":
  *   OPENAI_BASE_URL        — http(s):// URL for an OpenAI-compatible /v1/chat/completions
- *                            host (e.g. ChatMock localhost proxy backed by Codex OAuth).
+ *                            host. Examples: ChatMock localhost proxy (Codex OAuth),
+ *                            OpenRouter (https://openrouter.ai/api), or the HuggingFace
+ *                            Inference Providers router (https://router.huggingface.co).
+ *                            See docs/HUGGINGFACE_ROUTER_SETUP.md for the HF preset.
  *
  * Required for CAPABILITY_KIND="tts":
  *   PIPER_URL              — http(s):// URL for the openedai-speech-min PiperTTS host
@@ -51,6 +54,15 @@ const TX_HASH_RE = /^[0-9a-fA-F]{64}$/;
 const NON_NEG_INT_RE = /^(?:0|[1-9]\d*)$/;
 const POS_INT_RE = /^[1-9]\d*$/;
 
+/** Lowercased hostname of a URL, or "" if it doesn't parse. */
+function hostnameOf(url: string): string {
+  try {
+    return new URL(url).hostname.toLowerCase();
+  } catch {
+    return "";
+  }
+}
+
 export interface AdvertRef {
   txHash: string;
   index: number;
@@ -269,6 +281,24 @@ export function loadConfig(env: Record<string, string | undefined>): SupplierCon
     reasoningRaw === "0" ||
     reasoningRaw === "no";
 
+  // HuggingFace router guard. The `reasoning:{enabled:false}` param is
+  // OpenRouter-specific; the HF Inference Providers router
+  // (router.huggingface.co) rejects it with HTTP 400 on EVERY request. This is
+  // the easy footgun when copying an OpenRouter env to the HF preset, so fail
+  // fast at boot with a clear message instead of 400-ing every job.
+  // See docs/HUGGINGFACE_ROUTER_SETUP.md.
+  if (
+    llmBackend === "openai" &&
+    openaiReasoningDisabled &&
+    hostnameOf(openaiBaseUrl) === "router.huggingface.co"
+  ) {
+    throw new Error(
+      "loadConfig: OPENAI_REASONING must be unset for the HuggingFace router " +
+        "(OPENAI_BASE_URL=https://router.huggingface.co) — it rejects " +
+        "reasoning:{enabled:false} with HTTP 400. Remove OPENAI_REASONING.",
+    );
+  }
+
   // OPENAI_MAX_TOKENS — optional hard ceiling forwarded as `max_tokens`. Unset
   // or non-positive omits it (provider grants max available = context − prompt).
   // Keep it below the model context (kimi 262144) or the provider 400s when