Add local model asset catalog

frontend/src/App.tsx

@@ -222,10 +222,13 @@ function App(): JSX.Element {
   })
   const {
     detectionModels,
+    modelAssets,
     loadingDetectionModels,
     detectionModelError,
+    modelAssetError,
     selectedDetectionDatasetId,
     selectedDetectionModelId,
+    selectedModelAssetId,
     detectionTileManifestPath,
     detectionConfidenceThreshold,
     runningDetection,
@@ -254,6 +257,7 @@ function App(): JSX.Element {
     resetDetectionForProject,
     setSelectedDetectionDatasetId,
     setSelectedDetectionModelId,
+    setSelectedModelAssetId,
     setDetectionTileManifestPath,
     setDetectionConfidenceThreshold,
     setSelectedDetectionRunId,
@@ -930,10 +934,13 @@ function App(): JSX.Element {
             <div className="workspace-grid workspace-grid-ai">
               <DetectionLab
                 detectionModels={detectionModels}
+                modelAssets={modelAssets}
                 loadingDetectionModels={loadingDetectionModels}
                 detectionModelError={detectionModelError}
+                modelAssetError={modelAssetError}
                 selectedDetectionDatasetId={selectedDetectionDatasetId}
                 selectedDetectionModelId={selectedDetectionModelId}
+                selectedModelAssetId={selectedModelAssetId}
                 detectionTileManifestPath={detectionTileManifestPath}
                 detectionConfidenceThreshold={detectionConfidenceThreshold}
                 runningDetection={runningDetection}
@@ -959,6 +966,7 @@ function App(): JSX.Element {
                 onRefreshYoloPreflight={() => loadYoloPreflight()}
                 onSelectDataset={setSelectedDetectionDatasetId}
                 onSelectModel={setSelectedDetectionModelId}
+                onSelectModelAsset={setSelectedModelAssetId}
                 onSetConfidenceThreshold={setDetectionConfidenceThreshold}
                 onSetTileManifestPath={setDetectionTileManifestPath}
                 onRunDetection={runDetection}

frontend/src/components/detection/DetectionLab.tsx

@@ -5,15 +5,19 @@ import type {
   DetectionRead,
   DetectionRunRead,
   DetectionRunResponse,
+  ModelAssetRead,
   YoloPreflightResponse,
 } from '../../types'
 
 interface DetectionLabProps {
   detectionModels: DetectionModelCapability[]
+  modelAssets: ModelAssetRead[]
   loadingDetectionModels: boolean
   detectionModelError: string | null
+  modelAssetError: string | null
   selectedDetectionDatasetId: string
   selectedDetectionModelId: string
+  selectedModelAssetId: string
   detectionTileManifestPath: string
   detectionConfidenceThreshold: number
   runningDetection: boolean
@@ -39,6 +43,7 @@ interface DetectionLabProps {
   onRefreshYoloPreflight: () => void
   onSelectDataset: (datasetId: string) => void
   onSelectModel: (modelId: string) => void
+  onSelectModelAsset: (modelAssetId: string) => void
   onSetConfidenceThreshold: (value: number) => void
   onSetTileManifestPath: (value: string) => void
   onRunDetection: () => void
@@ -53,10 +58,13 @@ interface DetectionLabProps {
 
 export function DetectionLab({
   detectionModels,
+  modelAssets,
   loadingDetectionModels,
   detectionModelError,
+  modelAssetError,
   selectedDetectionDatasetId,
   selectedDetectionModelId,
+  selectedModelAssetId,
   detectionTileManifestPath,
   detectionConfidenceThreshold,
   runningDetection,
@@ -82,6 +90,7 @@ export function DetectionLab({
   onRefreshYoloPreflight,
   onSelectDataset,
   onSelectModel,
+  onSelectModelAsset,
   onSetConfidenceThreshold,
   onSetTileManifestPath,
   onRunDetection,
@@ -94,6 +103,7 @@ export function DetectionLab({
   onRunQa,
 }: DetectionLabProps): JSX.Element {
   const selectedDetectionModel = detectionModels.find((model) => model.model_id === selectedDetectionModelId) ?? null
+  const selectedModelAsset = modelAssets.find((asset) => asset.model_asset_id === selectedModelAssetId) ?? null
   const detectionRequiresTileManifest = selectedDetectionModelId === 'yolo-configured'
   const detectionHasDataset = selectedDetectionDatasetId.length > 0
   const detectionHasModel = selectedDetectionModel !== null
@@ -149,6 +159,12 @@ export function DetectionLab({
               <p>{detectionModelError}</p>
             </div>
           ) : null}
+          {modelAssetError ? (
+            <div className="result-state result-state-error">
+              <strong>Local model assets unavailable.</strong>
+              <p>{modelAssetError}</p>
+            </div>
+          ) : null}
           {detectionModels.length === 0 && !loadingDetectionModels ? (
             <div className="result-state result-state-empty">
               <strong>No detection models reported by backend.</strong>
@@ -173,6 +189,47 @@ export function DetectionLab({
         </ul>
       </div>
 
+      {selectedDetectionModelId === 'yolo-configured' ? (
+        <div className="ai-lab-model-surface" aria-label="Local model asset selection">
+          <div className="ai-lab-section-header">
+            <div>
+              <h3>Local model assets</h3>
+              <p>Select an existing model file mounted into the backend runtime. GeoIntel does not download model weights.</p>
+            </div>
+            <span className={selectedModelAsset ? 'status-badge status-badge-ready' : 'status-badge'}>
+              {selectedModelAsset ? 'asset selected' : 'using configured path'}
+            </span>
+          </div>
+          <label>
+            Local model file
+            <select value={selectedModelAssetId} onChange={(event) => onSelectModelAsset(event.target.value)}>
+              <option value="">Use configured YOLO_MODEL_PATH</option>
+              {modelAssets.map((asset) => (
+                <option key={asset.model_asset_id} value={asset.model_asset_id}>
+                  {asset.display_name} {asset.active ? '(active)' : ''}
+                </option>
+              ))}
+            </select>
+          </label>
+          {modelAssets.length === 0 && !loadingDetectionModels ? (
+            <div className="result-state result-state-empty">
+              <strong>No local model assets found.</strong>
+              <p>Mount model files into the backend model directory or continue with the configured YOLO_MODEL_PATH.</p>
+            </div>
+          ) : null}
+          {selectedModelAsset ? (
+            <div className="result-summary-card">
+              <p>File: {selectedModelAsset.filename}</p>
+              <p>Status: {selectedModelAsset.status}</p>
+              <p>Size: {formatModelAssetSize(selectedModelAsset.size_bytes)}</p>
+              <p>SHA-256: {selectedModelAsset.sha256.slice(0, 12)}</p>
+              <p>Path: {selectedModelAsset.model_path}</p>
+              <p>{selectedModelAsset.limitation_message}</p>
+            </div>
+          ) : null}
+        </div>
+      ) : null}
+
       <div className="ai-lab-model-surface" aria-label="YOLO runtime preflight">
         <div className="ai-lab-section-header">
           <div>
@@ -238,6 +295,7 @@ export function DetectionLab({
               <span>cuda_available: {String(yoloPreflight.runtime.cuda_available ?? 'unknown')}</span>
               <span>YOLO_CONFIG_DIR: {yoloPreflight.runtime.yolo_config_dir ?? 'n/a'}</span>
               <span>model directory: {yoloPreflight.runtime.model_directory ?? 'n/a'}</span>
+              <span>model_asset_id: {yoloPreflight.model_asset_id ?? 'n/a'}</span>
             </div>
           </div>
         ) : null}
@@ -486,3 +544,13 @@ export function DetectionLab({
     </section>
   )
 }
+
+function formatModelAssetSize(sizeBytes: number): string {
+  if (sizeBytes >= 1024 * 1024) {
+    return `${(sizeBytes / (1024 * 1024)).toFixed(1)} MB`
+  }
+  if (sizeBytes >= 1024) {
+    return `${(sizeBytes / 1024).toFixed(1)} KB`
+  }
+  return `${sizeBytes} B`
+}

frontend/src/components/providers/ProviderPanel.tsx

@@ -48,6 +48,12 @@ export function ProviderPanel({
         </div>
 
         <div className="system-provider-capability-surface" aria-label="Provider capability registry">
+          <div className="provider-detail-stack">
+            <strong>Official reference sources</strong>
+            <div>
+              GRB and OSM are reference-data provider capabilities, not AI model choices. Manual upload is the configured path for real reference datasets today; fixtures remain test/demo only.
+            </div>
+          </div>
           <ul className="system-provider-list">
             {providers.map((provider) => (
               <li className="system-provider-card" key={provider.provider_name}>

frontend/src/hooks/useDetectionWorkflow.ts

@@ -7,6 +7,7 @@ import type {
   DetectionRead,
   DetectionRunRead,
   DetectionRunResponse,
+  ModelAssetRead,
   QualityCheckRead,
   YoloPreflightResponse,
 } from '../types'
@@ -28,10 +29,13 @@ export function useDetectionWorkflow({
   loadQualityChecks,
 }: DetectionWorkflowOptions) {
   const [detectionModels, setDetectionModels] = useState<DetectionModelCapability[]>([])
+  const [modelAssets, setModelAssets] = useState<ModelAssetRead[]>([])
   const [loadingDetectionModels, setLoadingDetectionModels] = useState(false)
   const [detectionModelError, setDetectionModelError] = useState<string | null>(null)
+  const [modelAssetError, setModelAssetError] = useState<string | null>(null)
   const [selectedDetectionDatasetId, setSelectedDetectionDatasetId] = useState('')
   const [selectedDetectionModelId, setSelectedDetectionModelId] = useState('yolo-placeholder')
+  const [selectedModelAssetId, setSelectedModelAssetId] = useState('')
   const [detectionTileManifestPath, setDetectionTileManifestPath] = useState('')
   const [detectionConfidenceThreshold, setDetectionConfidenceThreshold] = useState(0.5)
   const [runningDetection, setRunningDetection] = useState(false)
@@ -55,6 +59,7 @@ export function useDetectionWorkflow({
   const loadDetectionModels = async () => {
     setLoadingDetectionModels(true)
     setDetectionModelError(null)
+    setModelAssetError(null)
     try {
       const response = await detectionApi.listModels()
       setDetectionModels(response.models)
@@ -63,6 +68,17 @@ export function useDetectionWorkflow({
       }
     } catch (error) {
       setDetectionModelError(formatError(error, 'Failed to load detection models'))
+    }
+    try {
+      const assetResponse = await detectionApi.listModelAssets()
+      setModelAssets(assetResponse.items)
+      const activeAsset = assetResponse.items.find((asset) => asset.active) ?? assetResponse.items[0] ?? null
+      if (!assetResponse.items.some((asset) => asset.model_asset_id === selectedModelAssetId)) {
+        setSelectedModelAssetId(activeAsset?.model_asset_id ?? '')
+      }
+    } catch (error) {
+      setModelAssets([])
+      setModelAssetError(formatError(error, 'Failed to load local model assets'))
     } finally {
       setLoadingDetectionModels(false)
     }
@@ -74,6 +90,7 @@ export function useDetectionWorkflow({
     try {
       const response = await detectionApi.getYoloPreflight({
         tile_manifest_path: tileManifestPath.trim() || null,
+        model_asset_id: selectedModelAssetId || null,
       })
       setYoloPreflight(response)
     } catch (error) {
@@ -143,6 +160,7 @@ export function useDetectionWorkflow({
         project_id: selectedProjectId,
         dataset_id: datasetId,
         model_id: selectedDetectionModelId,
+        model_asset_id: selectedModelAssetId || null,
         confidence_threshold: detectionConfidenceThreshold,
         tile_manifest_path: detectionTileManifestPath.trim() || null,
         parameters_json: {},
@@ -198,10 +216,13 @@ export function useDetectionWorkflow({
 
   return {
     detectionModels,
+    modelAssets,
     loadingDetectionModels,
     detectionModelError,
+    modelAssetError,
     selectedDetectionDatasetId,
     selectedDetectionModelId,
+    selectedModelAssetId,
     detectionTileManifestPath,
     detectionConfidenceThreshold,
     runningDetection,
@@ -230,6 +251,7 @@ export function useDetectionWorkflow({
     resetDetectionForProject,
     setSelectedDetectionDatasetId,
     setSelectedDetectionModelId,
+    setSelectedModelAssetId,
     setDetectionTileManifestPath,
     setDetectionConfidenceThreshold,
     setSelectedDetectionRunId,

frontend/src/services/api/detection.ts

@@ -8,6 +8,7 @@ import type {
   DetectionRunRead,
   DetectionRunRequest,
   DetectionRunResponse,
+  ModelAssetListResponse,
   YoloPreflightResponse,
 } from '../../types'
 
@@ -24,7 +25,8 @@ function queryString(params: Record<string, string | number | boolean | null | u
 
 export const detectionApi = {
   listModels: (): Promise<DetectionModelsResponse> => apiGet<DetectionModelsResponse>('/api/v1/detection/models'),
-  getYoloPreflight: (params: { tile_manifest_path?: string | null; check_model_load?: boolean | null } = {}): Promise<YoloPreflightResponse> =>
+  listModelAssets: (): Promise<ModelAssetListResponse> => apiGet<ModelAssetListResponse>('/api/v1/detection/model-assets'),
+  getYoloPreflight: (params: { tile_manifest_path?: string | null; check_model_load?: boolean | null; model_asset_id?: string | null } = {}): Promise<YoloPreflightResponse> =>
     apiGet<YoloPreflightResponse>(`/api/v1/detection/yolo/preflight${queryString(params)}`),
   run: (payload: DetectionRunRequest): Promise<DetectionRunResponse> =>
     apiPost<DetectionRunResponse>('/api/v1/detection/run', payload),

frontend/src/types.ts

@@ -404,6 +404,28 @@ export interface DetectionModelsResponse {
   models: DetectionModelCapability[]
 }
 
+export interface ModelAssetRead {
+  model_asset_id: string
+  filename: string
+  display_name: string
+  model_path: string
+  suffix: string
+  framework: string
+  task_type: string
+  size_bytes: number
+  sha256: string
+  active: boolean
+  status: string
+  limitation_message: string
+  will_download_models: boolean
+}
+
+export interface ModelAssetListResponse {
+  items: ModelAssetRead[]
+  total: number
+  model_directory: string
+}
+
 export interface YoloPreflightChecks {
   enabled: boolean
   dependencies_available?: boolean | null
@@ -428,6 +450,7 @@ export interface YoloPreflightRuntime {
 
 export interface YoloPreflightResponse {
   model_id: string
+  model_asset_id?: string | null
   model_path?: string | null
   tile_manifest_path?: string | null
   status: string
@@ -445,6 +468,7 @@ export interface DetectionRunRequest {
   project_id: string
   dataset_id: string
   model_id: string
+  model_asset_id?: string | null
   confidence_threshold: number
   class_filter?: string[] | null
   tile_manifest_path?: string | null