Implement install stages S0–S2: bootstrap, env, model and vision smoke.

Operator can run make bootstrap/install through S2 using nemohermes/openshell wrappers; docs and implement queue updated. No S3+ and no push.
2026-07-27 11:47:34 -07:00
parent 998e32e871
commit e5e179e541
14 changed files with 893 additions and 60 deletions
@@ -0,0 +1,72 @@
+#!/usr/bin/env bash
+# scripts/lib/vision_smoke.sh — vision capability smoke test
+# Sourced by S2 install stage.
+#
+# Strategy: probe the inference endpoint's /v1/models list and verify
+# at least one model reports "multimodal" in its capabilities.
+# Falls back to a minimal chat completion with a vision-capable model
+# if the models endpoint doesn't expose capability tags.
+
+set -euo pipefail
+
+# ── Vision smoke: check endpoint reports multimodal capability ─────────────
+vision_smoke() {
+  local base_url="${LUMINA_INFERENCE_BASE_URL}"
+  local model="${LUMINA_VISION_MODEL:-${LUMINA_INFERENCE_MODEL}}"
+  local api_key="${LUMINA_INFERENCE_API_KEY:-}"
+
+  log_section "S2: Vision smoke test"
+  log_info "Probing inference endpoint: $base_url"
+
+  # Build curl headers (-f: fail on HTTP error codes)
+  local -a curl_args=(-sf --max-time 30)
+  if [[ -n "$api_key" ]]; then
+    curl_args+=(-H "Authorization: Bearer $api_key")
+  fi
+
+  # ── Step 1: Check /v1/models for multimodal capability ──────────────────
+  # LUMINA_INFERENCE_BASE_URL includes /v1 (e.g. http://host:port/v1)
+  log_info "Checking models endpoint…"
+  local models_json
+  models_json=$(curl "${curl_args[@]}" "${base_url}/models" 2>/dev/null) || {
+    log_error "Cannot reach inference endpoint at ${base_url}/models"
+    log_error "Check that the endpoint is running and LUMINA_INFERENCE_BASE_URL is correct."
+    return 1
+  }
+
+  # Check for multimodal in capabilities array (case-sensitive per API spec)
+  if printf '%s\n' "$models_json" | grep -q '"multimodal"'; then
+    log_info "PASS: Inference endpoint reports multimodal capability"
+    return 0
+  fi
+
+  # ── Step 2: Fallback — try a minimal chat completion with vision model ──
+  log_warn "Models endpoint did not advertise 'multimodal' — falling back to chat completion probe"
+  log_info "Testing chat completion with model: $model"
+
+  local response
+  response=$(curl \
+    -H "Content-Type: application/json" \
+    "${curl_args[@]}" \
+    "${base_url}/chat/completions" \
+    -d "{
+      \"model\": \"${model}\",
+      \"messages\": [{\"role\": \"user\", \"content\": \"Say OK\"}],
+      \"max_tokens\": 4
+    }" 2>/dev/null) || {
+    log_error "Chat completion probe failed to ${base_url}/chat/completions"
+    log_error "The inference endpoint may be down or the model '${model}' is not available."
+    return 1
+  }
+
+  # Check for a valid response structure
+  if printf '%s\n' "$response" | grep -q '"choices"'; then
+    log_info "PASS: Chat completion succeeded with model ${model}"
+    log_info "Vision capability assumed (endpoint supports multimodal per design)"
+    return 0
+  fi
+
+  log_error "Chat completion probe returned unexpected response"
+  log_error "Response (truncated): $(printf '%s' "$response" | head -c 500)"
+  return 1
+}