fix: normalize base URL in LM Studio embedder and improve error logging

Author: daniel-lxs

src/services/code-index/embedders/lmstudio.ts

@@ -23,9 +23,16 @@ export class CodeIndexLmStudioEmbedder implements IEmbedder {
 	 */
 	constructor(options: ApiHandlerOptions & { embeddingModelId?: string }) {
 		this.options = options
+
+		// Normalize base URL to prevent duplicate /v1 if user already provided it
+		let baseUrl = this.options.lmStudioBaseUrl || "http://localhost:1234"
+		if (!baseUrl.endsWith("/v1")) {
+			baseUrl = baseUrl + "/v1"
+		}
+
 		this.embeddingsClient = new OpenAI({
-			baseURL: (this.options.lmStudioBaseUrl || "http://localhost:1234") + "/v1",
-			apiKey: "noop", // LM Studio doesn't require a real API key
+			baseURL: baseUrl,
+			apiKey: "noop", // API key is intentionally hardcoded to "noop" because LM Studio does not require authentication
 		})
 		this.defaultModelId = options.embeddingModelId || "text-embedding-nomic-embed-text-v1.5@f16"
 	}
@@ -81,8 +88,11 @@ export class CodeIndexLmStudioEmbedder implements IEmbedder {
 					usage.promptTokens += batchResult.usage.promptTokens
 					usage.totalTokens += batchResult.usage.totalTokens
 				} catch (error) {
-					console.error("Failed to process batch:", error)
-					throw new Error("Failed to create embeddings: batch processing error")
+					const batchInfo = `batch of ${currentBatch.length} documents (indices: ${processedIndices.join(", ")})`
+					console.error(`Failed to process ${batchInfo}:`, error)
+					throw new Error(
+						`Failed to create embeddings for ${batchInfo}: ${error instanceof Error ? error.message : "batch processing error"}`,
+					)
 				}
 			}
 		}

webview-ui/src/components/settings/providers/LMStudio.tsx

@@ -56,47 +56,38 @@ export const LMStudio = ({ apiConfiguration, setApiConfigurationField }: LMStudi
 		vscode.postMessage({ type: "requestLmStudioModels" })
 	}, [])
 
+	// Reusable function to check if a model is available
+	const checkModelAvailability = useCallback(
+		(modelId: string | undefined): boolean => {
+			if (!modelId) return false
+
+			// Check if model exists in local LM Studio models
+			if (lmStudioModels.length > 0 && lmStudioModels.includes(modelId)) {
+				return false // Model is available locally
+			}
+
+			// If we have router models data for LM Studio
+			if (routerModels.data?.lmstudio) {
+				const availableModels = Object.keys(routerModels.data.lmstudio)
+				// Show warning if model is not in the list (regardless of how many models there are)
+				return !availableModels.includes(modelId)
+			}
+
+			// If neither source has loaded yet, don't show warning
+			return false
+		},
+		[lmStudioModels, routerModels.data],
+	)
+
 	// Check if the selected model exists in the fetched models
 	const modelNotAvailable = useMemo(() => {
-		const selectedModel = apiConfiguration?.lmStudioModelId
-		if (!selectedModel) return false
-
-		// Check if model exists in local LM Studio models
-		if (lmStudioModels.length > 0 && lmStudioModels.includes(selectedModel)) {
-			return false // Model is available locally
-		}
-
-		// If we have router models data for LM Studio
-		if (routerModels.data?.lmstudio) {
-			const availableModels = Object.keys(routerModels.data.lmstudio)
-			// Show warning if model is not in the list (regardless of how many models there are)
-			return !availableModels.includes(selectedModel)
-		}
-
-		// If neither source has loaded yet, don't show warning
-		return false
-	}, [apiConfiguration?.lmStudioModelId, routerModels.data, lmStudioModels])
+		return checkModelAvailability(apiConfiguration?.lmStudioModelId)
+	}, [apiConfiguration?.lmStudioModelId, checkModelAvailability])
 
 	// Check if the draft model exists
 	const draftModelNotAvailable = useMemo(() => {
-		const draftModel = apiConfiguration?.lmStudioDraftModelId
-		if (!draftModel) return false
-
-		// Check if model exists in local LM Studio models
-		if (lmStudioModels.length > 0 && lmStudioModels.includes(draftModel)) {
-			return false // Model is available locally
-		}
-
-		// If we have router models data for LM Studio
-		if (routerModels.data?.lmstudio) {
-			const availableModels = Object.keys(routerModels.data.lmstudio)
-			// Show warning if model is not in the list (regardless of how many models there are)
-			return !availableModels.includes(draftModel)
-		}
-
-		// If neither source has loaded yet, don't show warning
-		return false
-	}, [apiConfiguration?.lmStudioDraftModelId, routerModels.data, lmStudioModels])
+		return checkModelAvailability(apiConfiguration?.lmStudioDraftModelId)
+	}, [apiConfiguration?.lmStudioDraftModelId, checkModelAvailability])
 
 	return (
 		<>