Merge branch 'RooCodeInc:main' into main

2026-09-06 08:18:39 +00:00 · 2025-07-08 12:46:31 -03:00 · 2025-07-08 12:46:31 -03:00 · 00a0b631f7
commit 00a0b631f7
parent 39c5cf773a 6ab57fae43
61 changed files with 3351 additions and 330 deletions
--- a/src/core/environment/tests/getEnvironmentDetails.spec.ts
+++ b/src/core/environment/tests/getEnvironmentDetails.spec.ts
@ -313,25 +313,6 @@ describe("getEnvironmentDetails", () => {
 		expect(mockInactiveTerminal.getCurrentWorkingDirectory).toHaveBeenCalled()
 	})

-	it("should include warning when file writing is not allowed", async () => {
-		;(isToolAllowedForMode as Mock).mockReturnValue(false)
-		;(getModeBySlug as Mock).mockImplementation((slug: string) => {
-			if (slug === "code") {
-				return { name: "💻 Code" }
-			}
-
-			if (slug === defaultModeSlug) {
-				return { name: "Default Mode" }
-			}
-
-			return null
-		})
-
-		const result = await getEnvironmentDetails(mockCline as Task)
-
-		expect(result).toContain("NOTE: You are currently in '💻 Code' mode, which does not allow write operations")
-	})
-
 	it("should include experiment-specific details when Power Steering is enabled", async () => {
 		mockState.experiments = { [EXPERIMENT_IDS.POWER_STEERING]: true }
 		;(experiments.isEnabled as Mock).mockReturnValue(true)
--- a/src/core/environment/getEnvironmentDetails.ts
+++ b/src/core/environment/getEnvironmentDetails.ts
@ -233,16 +233,6 @@ export async function getEnvironmentDetails(cline: Task, includeFileDetails: boo
 		}
 	}

-	// Add warning if not in code mode.
-	if (
-		!isToolAllowedForMode("write_to_file", currentMode, customModes ?? [], { apply_diff: cline.diffEnabled }) &&
-		!isToolAllowedForMode("apply_diff", currentMode, customModes ?? [], { apply_diff: cline.diffEnabled })
-	) {
-		const currentModeName = getModeBySlug(currentMode, customModes)?.name ?? currentMode
-		const defaultModeName = getModeBySlug(defaultModeSlug, customModes)?.name ?? defaultModeSlug
-		details += `\n\nNOTE: You are currently in '${currentModeName}' mode, which does not allow write operations. To write files, the user will need to switch to a mode that supports file writing, such as '${defaultModeName}' mode.`
-	}
-
 	if (includeFileDetails) {
 		details += `\n\n# Current Workspace Directory (${cline.cwd.toPosix()}) Files\n`
 		const isDesktop = arePathsEqual(cline.cwd, path.join(os.homedir(), "Desktop"))
--- a/src/core/webview/tests/ClineProvider.spec.ts
+++ b/src/core/webview/tests/ClineProvider.spec.ts
--- a/src/core/webview/webviewMessageHandler.ts
+++ b/src/core/webview/webviewMessageHandler.ts
@ -6,9 +6,16 @@ import pWaitFor from "p-wait-for"
 import * as vscode from "vscode"
 import * as yaml from "yaml"

-import { type Language, type ProviderSettings, type GlobalState, TelemetryEventName } from "@roo-code/types"
+import {
+	type Language,
+	type ProviderSettings,
+	type GlobalState,
+	type ClineMessage,
+	TelemetryEventName,
+} from "@roo-code/types"
 import { CloudService } from "@roo-code/cloud"
 import { TelemetryService } from "@roo-code/telemetry"
+import { type ApiMessage } from "../task-persistence/apiMessages"

 import { ClineProvider } from "./ClineProvider"
 import { changeLanguage, t } from "../../i18n"
@ -58,6 +65,200 @@ export const webviewMessageHandler = async (
 	const updateGlobalState = async <K extends keyof GlobalState>(key: K, value: GlobalState[K]) =>
 		await provider.contextProxy.setValue(key, value)

+	/**
+	 * Shared utility to find message indices based on timestamp
+	 */
+	const findMessageIndices = (messageTs: number, currentCline: any) => {
+		const timeCutoff = messageTs - 1000 // 1 second buffer before the message
+		const messageIndex = currentCline.clineMessages.findIndex((msg: ClineMessage) => msg.ts && msg.ts >= timeCutoff)
+		const apiConversationHistoryIndex = currentCline.apiConversationHistory.findIndex(
+			(msg: ApiMessage) => msg.ts && msg.ts >= timeCutoff,
+		)
+		return { messageIndex, apiConversationHistoryIndex }
+	}
+
+	/**
+	 * Removes just the target message, preserving messages after the next user message
+	 */
+	const removeMessagesJustThis = async (
+		currentCline: any,
+		messageIndex: number,
+		apiConversationHistoryIndex: number,
+	) => {
+		// Find the next user message first
+		const nextUserMessage = currentCline.clineMessages
+			.slice(messageIndex + 1)
+			.find((msg: ClineMessage) => msg.type === "say" && msg.say === "user_feedback")
+
+		// Handle UI messages
+		if (nextUserMessage) {
+			// Find absolute index of next user message
+			const nextUserMessageIndex = currentCline.clineMessages.findIndex(
+				(msg: ClineMessage) => msg === nextUserMessage,
+			)
+
+			// Keep messages before current message and after next user message
+			await currentCline.overwriteClineMessages([
+				...currentCline.clineMessages.slice(0, messageIndex),
+				...currentCline.clineMessages.slice(nextUserMessageIndex),
+			])
+		} else {
+			// If no next user message, keep only messages before current message
+			await currentCline.overwriteClineMessages(currentCline.clineMessages.slice(0, messageIndex))
+		}
+
+		// Handle API messages
+		if (apiConversationHistoryIndex !== -1) {
+			if (nextUserMessage && nextUserMessage.ts) {
+				// Keep messages before current API message and after next user message
+				await currentCline.overwriteApiConversationHistory([
+					...currentCline.apiConversationHistory.slice(0, apiConversationHistoryIndex),
+					...currentCline.apiConversationHistory.filter(
+						(msg: ApiMessage) => msg.ts && msg.ts >= nextUserMessage.ts,
+					),
+				])
+			} else {
+				// If no next user message, keep only messages before current API message
+				await currentCline.overwriteApiConversationHistory(
+					currentCline.apiConversationHistory.slice(0, apiConversationHistoryIndex),
+				)
+			}
+		}
+	}
+
+	/**
+	 * Removes the target message and all subsequent messages
+	 */
+	const removeMessagesThisAndSubsequent = async (
+		currentCline: any,
+		messageIndex: number,
+		apiConversationHistoryIndex: number,
+	) => {
+		// Delete this message and all that follow
+		await currentCline.overwriteClineMessages(currentCline.clineMessages.slice(0, messageIndex))
+
+		if (apiConversationHistoryIndex !== -1) {
+			await currentCline.overwriteApiConversationHistory(
+				currentCline.apiConversationHistory.slice(0, apiConversationHistoryIndex),
+			)
+		}
+	}
+
+	/**
+	 * Handles message deletion operations with user confirmation
+	 */
+	const handleDeleteOperation = async (messageTs: number): Promise<void> => {
+		const options = [
+			t("common:confirmation.delete_just_this_message"),
+			t("common:confirmation.delete_this_and_subsequent"),
+		]
+
+		const answer = await vscode.window.showInformationMessage(
+			t("common:confirmation.delete_message"),
+			{ modal: true },
+			...options,
+		)
+
+		// Only proceed if user selected one of the options and we have a current cline
+		if (answer && options.includes(answer) && provider.getCurrentCline()) {
+			const currentCline = provider.getCurrentCline()!
+			const { messageIndex, apiConversationHistoryIndex } = findMessageIndices(messageTs, currentCline)
+
+			if (messageIndex !== -1) {
+				try {
+					const { historyItem } = await provider.getTaskWithId(currentCline.taskId)
+
+					// Check which option the user selected
+					if (answer === options[0]) {
+						// Delete just this message
+						await removeMessagesJustThis(currentCline, messageIndex, apiConversationHistoryIndex)
+					} else if (answer === options[1]) {
+						// Delete this message and all subsequent
+						await removeMessagesThisAndSubsequent(currentCline, messageIndex, apiConversationHistoryIndex)
+					}
+
+					// Initialize with history item after deletion
+					await provider.initClineWithHistoryItem(historyItem)
+				} catch (error) {
+					console.error("Error in delete message:", error)
+					vscode.window.showErrorMessage(
+						`Error deleting message: ${error instanceof Error ? error.message : String(error)}`,
+					)
+				}
+			}
+		}
+	}
+
+	/**
+	 * Handles message editing operations with user confirmation
+	 */
+	const handleEditOperation = async (messageTs: number, editedContent: string): Promise<void> => {
+		const options = [
+			t("common:confirmation.edit_this_and_delete_subsequent"),
+			t("common:confirmation.edit_just_this_message"),
+		]
+
+		const answer = await vscode.window.showInformationMessage(
+			t("common:confirmation.edit_message"),
+			{ modal: true },
+			...options,
+		)
+
+		// Only proceed if user selected one of the options and we have a current cline
+		if (answer && options.includes(answer) && provider.getCurrentCline()) {
+			const currentCline = provider.getCurrentCline()!
+			const { messageIndex, apiConversationHistoryIndex } = findMessageIndices(messageTs, currentCline)
+
+			if (messageIndex !== -1) {
+				try {
+					// Check which option the user selected
+					if (answer === options[0]) {
+						// Edit this message and delete subsequent
+						await removeMessagesThisAndSubsequent(currentCline, messageIndex, apiConversationHistoryIndex)
+					} else if (answer === options[1]) {
+						// Edit just this message
+						await removeMessagesJustThis(currentCline, messageIndex, apiConversationHistoryIndex)
+					}
+
+					// Process the edited message as a regular user message
+					// This will add it to the conversation and trigger an AI response
+					webviewMessageHandler(provider, {
+						type: "askResponse",
+						askResponse: "messageResponse",
+						text: editedContent,
+					})
+
+					// Don't initialize with history item for edit operations
+					// The webviewMessageHandler will handle the conversation state
+				} catch (error) {
+					console.error("Error in edit message:", error)
+					vscode.window.showErrorMessage(
+						`Error editing message: ${error instanceof Error ? error.message : String(error)}`,
+					)
+				}
+			}
+		}
+	}
+
+	/**
+	 * Handles message modification operations (delete or edit) with confirmation dialog
+	 * @param messageTs Timestamp of the message to operate on
+	 * @param operation Type of operation ('delete' or 'edit')
+	 * @param editedContent New content for edit operations
+	 * @returns Promise<void>
+	 */
+	const handleMessageModificationsOperation = async (
+		messageTs: number,
+		operation: "delete" | "edit",
+		editedContent?: string,
+	): Promise<void> => {
+		if (operation === "delete") {
+			await handleDeleteOperation(messageTs)
+		} else if (operation === "edit" && editedContent) {
+			await handleEditOperation(messageTs, editedContent)
+		}
+	}
+
 	switch (message.type) {
 		case "webviewDidLaunch":
 			// Load custom modes first
@ -989,108 +1190,19 @@ export const webviewMessageHandler = async (
 			}
 			break
 		case "deleteMessage": {
-			const answer = await vscode.window.showInformationMessage(
-				t("common:confirmation.delete_message"),
-				{ modal: true },
-				t("common:confirmation.just_this_message"),
-				t("common:confirmation.this_and_subsequent"),
-			)
-
+			if (provider.getCurrentCline() && typeof message.value === "number" && message.value) {
+				await handleMessageModificationsOperation(message.value, "delete")
+			}
+			break
+		}
+		case "submitEditedMessage": {
 			if (
-				(answer === t("common:confirmation.just_this_message") ||
-					answer === t("common:confirmation.this_and_subsequent")) &&
 				provider.getCurrentCline() &&
 				typeof message.value === "number" &&
-				message.value
+				message.value &&
+				message.editedMessageContent
 			) {
-				const timeCutoff = message.value - 1000 // 1 second buffer before the message to delete
-
-				const messageIndex = provider
-					.getCurrentCline()!
-					.clineMessages.findIndex((msg) => msg.ts && msg.ts >= timeCutoff)
-
-				const apiConversationHistoryIndex = provider
-					.getCurrentCline()
-					?.apiConversationHistory.findIndex((msg) => msg.ts && msg.ts >= timeCutoff)
-
-				if (messageIndex !== -1) {
-					const { historyItem } = await provider.getTaskWithId(provider.getCurrentCline()!.taskId)
-
-					if (answer === t("common:confirmation.just_this_message")) {
-						// Find the next user message first
-						const nextUserMessage = provider
-							.getCurrentCline()!
-							.clineMessages.slice(messageIndex + 1)
-							.find((msg) => msg.type === "say" && msg.say === "user_feedback")
-
-						// Handle UI messages
-						if (nextUserMessage) {
-							// Find absolute index of next user message
-							const nextUserMessageIndex = provider
-								.getCurrentCline()!
-								.clineMessages.findIndex((msg) => msg === nextUserMessage)
-
-							// Keep messages before current message and after next user message
-							await provider
-								.getCurrentCline()!
-								.overwriteClineMessages([
-									...provider.getCurrentCline()!.clineMessages.slice(0, messageIndex),
-									...provider.getCurrentCline()!.clineMessages.slice(nextUserMessageIndex),
-								])
-						} else {
-							// If no next user message, keep only messages before current message
-							await provider
-								.getCurrentCline()!
-								.overwriteClineMessages(
-									provider.getCurrentCline()!.clineMessages.slice(0, messageIndex),
-								)
-						}
-
-						// Handle API messages
-						if (apiConversationHistoryIndex !== -1) {
-							if (nextUserMessage && nextUserMessage.ts) {
-								// Keep messages before current API message and after next user message
-								await provider
-									.getCurrentCline()!
-									.overwriteApiConversationHistory([
-										...provider
-											.getCurrentCline()!
-											.apiConversationHistory.slice(0, apiConversationHistoryIndex),
-										...provider
-											.getCurrentCline()!
-											.apiConversationHistory.filter(
-												(msg) => msg.ts && msg.ts >= nextUserMessage.ts,
-											),
-									])
-							} else {
-								// If no next user message, keep only messages before current API message
-								await provider
-									.getCurrentCline()!
-									.overwriteApiConversationHistory(
-										provider
-											.getCurrentCline()!
-											.apiConversationHistory.slice(0, apiConversationHistoryIndex),
-									)
-							}
-						}
-					} else if (answer === t("common:confirmation.this_and_subsequent")) {
-						// Delete this message and all that follow
-						await provider
-							.getCurrentCline()!
-							.overwriteClineMessages(provider.getCurrentCline()!.clineMessages.slice(0, messageIndex))
-						if (apiConversationHistoryIndex !== -1) {
-							await provider
-								.getCurrentCline()!
-								.overwriteApiConversationHistory(
-									provider
-										.getCurrentCline()!
-										.apiConversationHistory.slice(0, apiConversationHistoryIndex),
-								)
-						}
-					}
-
-					await provider.initClineWithHistoryItem(historyItem)
-				}
+				await handleMessageModificationsOperation(message.value, "edit", message.editedMessageContent)
 			}
 			break
 		}
@ -1843,8 +1955,12 @@ export const webviewMessageHandler = async (
 			const settings = message.codeIndexSettings

 			try {
-				// Save global state settings atomically (without codebaseIndexEnabled which is now in global settings)
+				// Check if embedder provider has changed
 				const currentConfig = getGlobalState("codebaseIndexConfig") || {}
+				const embedderProviderChanged =
+					currentConfig.codebaseIndexEmbedderProvider !== settings.codebaseIndexEmbedderProvider
+
+				// Save global state settings atomically (without codebaseIndexEnabled which is now in global settings)
 				const globalStateConfig = {
 					...currentConfig,
 					codebaseIndexQdrantUrl: settings.codebaseIndexQdrantUrl,
@ -1880,23 +1996,7 @@ export const webviewMessageHandler = async (
 					)
 				}

-				// Verify secrets are actually stored
-				const storedOpenAiKey = provider.contextProxy.getSecret("codeIndexOpenAiKey")
-
-				// Notify code index manager of changes
-				if (provider.codeIndexManager) {
-					await provider.codeIndexManager.handleSettingsChange()
-
-					// Auto-start indexing if now enabled and configured
-					if (provider.codeIndexManager.isFeatureEnabled && provider.codeIndexManager.isFeatureConfigured) {
-						if (!provider.codeIndexManager.isInitialized) {
-							await provider.codeIndexManager.initialize(provider.contextProxy)
-						}
-						provider.codeIndexManager.startIndexing()
-					}
-				}
-
-				// Send success response
+				// Send success response first - settings are saved regardless of validation
 				await provider.postMessageToWebview({
 					type: "codeIndexSettingsSaved",
 					success: true,
@ -1905,6 +2005,61 @@ export const webviewMessageHandler = async (

 				// Update webview state
 				await provider.postStateToWebview()
+
+				// Then handle validation and initialization
+				if (provider.codeIndexManager) {
+					// If embedder provider changed, perform proactive validation
+					if (embedderProviderChanged) {
+						try {
+							// Force handleSettingsChange which will trigger validation
+							await provider.codeIndexManager.handleSettingsChange()
+						} catch (error) {
+							// Validation failed - the error state is already set by handleSettingsChange
+							provider.log(
+								`Embedder validation failed after provider change: ${error instanceof Error ? error.message : String(error)}`,
+							)
+							// Send validation error to webview
+							await provider.postMessageToWebview({
+								type: "indexingStatusUpdate",
+								values: provider.codeIndexManager.getCurrentStatus(),
+							})
+							// Exit early - don't try to start indexing with invalid configuration
+							break
+						}
+					} else {
+						// No provider change, just handle settings normally
+						try {
+							await provider.codeIndexManager.handleSettingsChange()
+						} catch (error) {
+							// Log but don't fail - settings are saved
+							provider.log(
+								`Settings change handling error: ${error instanceof Error ? error.message : String(error)}`,
+							)
+						}
+					}
+
+					// Wait a bit more to ensure everything is ready
+					await new Promise((resolve) => setTimeout(resolve, 200))
+
+					// Auto-start indexing if now enabled and configured
+					if (provider.codeIndexManager.isFeatureEnabled && provider.codeIndexManager.isFeatureConfigured) {
+						if (!provider.codeIndexManager.isInitialized) {
+							try {
+								await provider.codeIndexManager.initialize(provider.contextProxy)
+								provider.log(`Code index manager initialized after settings save`)
+							} catch (error) {
+								provider.log(
+									`Code index initialization failed: ${error instanceof Error ? error.message : String(error)}`,
+								)
+								// Send error status to webview
+								await provider.postMessageToWebview({
+									type: "indexingStatusUpdate",
+									values: provider.codeIndexManager.getCurrentStatus(),
+								})
+							}
+						}
+					}
+				}
 			} catch (error) {
 				provider.log(`Error saving code index settings: ${error.message || error}`)
 				await provider.postMessageToWebview({
--- a/src/i18n/locales/ca/common.json
+++ b/src/i18n/locales/ca/common.json
@ -23,8 +23,11 @@
 		"delete_config_profile": "Estàs segur que vols eliminar aquest perfil de configuració?",
 		"delete_custom_mode_with_rules": "Esteu segur que voleu suprimir aquest mode {scope}?\n\nAixò també suprimirà la carpeta de regles associada a:\n{rulesFolderPath}",
 		"delete_message": "Què vols eliminar?",
-		"just_this_message": "Només aquest missatge",
-		"this_and_subsequent": "Aquest i tots els missatges posteriors"
+		"edit_message": "Eliminar tots els missatges després d'aquest?",
+		"delete_just_this_message": "Només aquest missatge",
+		"edit_just_this_message": "No, només editar aquest",
+		"delete_this_and_subsequent": "Aquest i tots els missatges posteriors",
+		"edit_this_and_delete_subsequent": "Sí"
 	},
 	"errors": {
 		"invalid_data_uri": "Format d'URI de dades no vàlid",
@ -112,6 +115,11 @@
 		"remove": "Eliminar",
 		"keep": "Mantenir"
 	},
+	"buttons": {
+		"save": "Desar",
+		"cancel": "Cancel·lar",
+		"edit": "Editar"
+	},
 	"tasks": {
 		"canceled": "Error de tasca: Ha estat aturada i cancel·lada per l'usuari.",
 		"deleted": "Fallada de tasca: Ha estat aturada i eliminada per l'usuari.",
--- a/src/i18n/locales/ca/embeddings.json
+++ b/src/i18n/locales/ca/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "No s'ha pogut llegir el cos de l'error",
 		"requestFailed": "La sol·licitud de l'API d'Ollama ha fallat amb l'estat {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Estructura de resposta no vàlida de l'API d'Ollama: no s'ha trobat la matriu \"embeddings\" o no és una matriu.",
-		"embeddingFailed": "La incrustació d'Ollama ha fallat: {{message}}"
+		"embeddingFailed": "La incrustació d'Ollama ha fallat: {{message}}",
+		"serviceNotRunning": "El servei d'Ollama no s'està executant a {{baseUrl}}",
+		"serviceUnavailable": "El servei d'Ollama no està disponible (estat: {{status}})",
+		"modelNotFound": "No s'ha trobat el model d'Ollama: {{modelId}}",
+		"modelNotEmbeddingCapable": "El model d'Ollama no és capaç de fer incrustacions: {{modelId}}",
+		"hostNotFound": "No s'ha trobat l'amfitrió d'Ollama: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "Error desconegut en processar el fitxer {{filePath}}",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "No s'ha pogut connectar a la base de dades vectorial Qdrant. Assegura't que Qdrant estigui funcionant i sigui accessible a {{qdrantUrl}}. Error: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Ha fallat l'autenticació. Comproveu la vostra clau d'API a la configuració.",
+		"connectionFailed": "No s'ha pogut connectar al servei d'incrustació. Comproveu la vostra configuració de connexió i assegureu-vos que el servei estigui funcionant.",
+		"modelNotAvailable": "El model especificat no està disponible. Comproveu la vostra configuració de model.",
+		"configurationError": "Configuració d'incrustació no vàlida. Reviseu la vostra configuració.",
+		"serviceUnavailable": "El servei d'incrustació no està disponible. Assegureu-vos que estigui funcionant i sigui accessible.",
+		"invalidEndpoint": "Punt final d'API no vàlid. Comproveu la vostra configuració d'URL.",
+		"invalidEmbedderConfig": "Configuració d'incrustació no vàlida. Comproveu la vostra configuració.",
+		"invalidApiKey": "Clau d'API no vàlida. Comproveu la vostra configuració de clau d'API.",
+		"invalidBaseUrl": "URL base no vàlida. Comproveu la vostra configuració d'URL.",
+		"invalidModel": "Model no vàlid. Comproveu la vostra configuració de model.",
+		"invalidResponse": "Resposta no vàlida del servei d'incrustació. Comproveu la vostra configuració."
 	}
 }
--- a/src/i18n/locales/de/common.json
+++ b/src/i18n/locales/de/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "Möchtest du dieses Konfigurationsprofil wirklich löschen?",
 		"delete_custom_mode_with_rules": "Bist du sicher, dass du diesen {scope}-Modus löschen möchtest?\n\nDadurch wird auch der zugehörige Regelordner unter folgender Adresse gelöscht:\n{rulesFolderPath}",
 		"delete_message": "Was möchtest du löschen?",
-		"just_this_message": "Nur diese Nachricht",
-		"this_and_subsequent": "Diese und alle nachfolgenden Nachrichten"
+		"edit_message": "Alle Nachrichten nach dieser löschen?",
+		"delete_just_this_message": "Nur diese Nachricht",
+		"edit_just_this_message": "Nein, nur diese bearbeiten",
+		"delete_this_and_subsequent": "Diese und alle nachfolgenden Nachrichten",
+		"edit_this_and_delete_subsequent": "Ja"
 	},
 	"errors": {
 		"invalid_data_uri": "Ungültiges Daten-URI-Format",
@ -108,6 +111,11 @@
 		"remove": "Entfernen",
 		"keep": "Behalten"
 	},
+	"buttons": {
+		"save": "Speichern",
+		"cancel": "Abbrechen",
+		"edit": "Bearbeiten"
+	},
 	"tasks": {
 		"canceled": "Aufgabenfehler: Die Aufgabe wurde vom Benutzer gestoppt und abgebrochen.",
 		"deleted": "Aufgabenfehler: Die Aufgabe wurde vom Benutzer gestoppt und gelöscht.",
--- a/src/i18n/locales/de/embeddings.json
+++ b/src/i18n/locales/de/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "Fehlerinhalt konnte nicht gelesen werden",
 		"requestFailed": "Ollama API-Anfrage fehlgeschlagen mit Status {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Ungültige Antwortstruktur von Ollama API: \"embeddings\" Array nicht gefunden oder kein Array.",
-		"embeddingFailed": "Ollama Einbettung fehlgeschlagen: {{message}}"
+		"embeddingFailed": "Ollama Einbettung fehlgeschlagen: {{message}}",
+		"serviceNotRunning": "Ollama-Dienst wird unter {{baseUrl}} nicht ausgeführt",
+		"serviceUnavailable": "Ollama-Dienst ist nicht verfügbar (Status: {{status}})",
+		"modelNotFound": "Ollama-Modell nicht gefunden: {{modelId}}",
+		"modelNotEmbeddingCapable": "Ollama-Modell ist nicht für Einbettungen geeignet: {{modelId}}",
+		"hostNotFound": "Ollama-Host nicht gefunden: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "Unbekannter Fehler beim Verarbeiten der Datei {{filePath}}",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Verbindung zur Qdrant-Vektordatenbank fehlgeschlagen. Stelle sicher, dass Qdrant läuft und unter {{qdrantUrl}} erreichbar ist. Fehler: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Authentifizierung fehlgeschlagen. Bitte überprüfe deinen API-Schlüssel in den Einstellungen.",
+		"connectionFailed": "Verbindung zum Embedder-Dienst fehlgeschlagen. Bitte überprüfe deine Verbindungseinstellungen und stelle sicher, dass der Dienst läuft.",
+		"modelNotAvailable": "Das angegebene Modell ist nicht verfügbar. Bitte überprüfe deine Modellkonfiguration.",
+		"configurationError": "Ungültige Embedder-Konfiguration. Bitte überprüfe deine Einstellungen.",
+		"serviceUnavailable": "Der Embedder-Dienst ist nicht verfügbar. Bitte stelle sicher, dass er läuft und erreichbar ist.",
+		"invalidEndpoint": "Ungültiger API-Endpunkt. Bitte überprüfe deine URL-Konfiguration.",
+		"invalidEmbedderConfig": "Ungültige Embedder-Konfiguration. Bitte überprüfe deine Einstellungen.",
+		"invalidApiKey": "Ungültiger API-Schlüssel. Bitte überprüfe deine API-Schlüssel-Konfiguration.",
+		"invalidBaseUrl": "Ungültige Basis-URL. Bitte überprüfe deine URL-Konfiguration.",
+		"invalidModel": "Ungültiges Modell. Bitte überprüfe deine Modellkonfiguration.",
+		"invalidResponse": "Ungültige Antwort vom Embedder-Dienst. Bitte überprüfe deine Konfiguration."
 	}
 }
--- a/src/i18n/locales/en/common.json
+++ b/src/i18n/locales/en/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "Are you sure you want to delete this configuration profile?",
 		"delete_custom_mode_with_rules": "Are you sure you want to delete this {scope} mode?\n\nThis will also delete the associated rules folder at:\n{rulesFolderPath}",
 		"delete_message": "What would you like to delete?",
-		"just_this_message": "Just this message",
-		"this_and_subsequent": "This and all subsequent messages"
+		"edit_message": "Delete all messages after this one?",
+		"delete_just_this_message": "Just this message",
+		"edit_just_this_message": "No, just edit this one",
+		"delete_this_and_subsequent": "This and all subsequent messages",
+		"edit_this_and_delete_subsequent": "Yes"
 	},
 	"errors": {
 		"invalid_data_uri": "Invalid data URI format",
@ -108,6 +111,11 @@
 		"remove": "Remove",
 		"keep": "Keep"
 	},
+	"buttons": {
+		"save": "Save",
+		"cancel": "Cancel",
+		"edit": "Edit"
+	},
 	"tasks": {
 		"canceled": "Task error: It was stopped and canceled by the user.",
 		"deleted": "Task failure: It was stopped and deleted by the user.",
--- a/src/i18n/locales/en/embeddings.json
+++ b/src/i18n/locales/en/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "Could not read error body",
 		"requestFailed": "Ollama API request failed with status {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Invalid response structure from Ollama API: \"embeddings\" array not found or not an array.",
-		"embeddingFailed": "Ollama embedding failed: {{message}}"
+		"embeddingFailed": "Ollama embedding failed: {{message}}",
+		"serviceNotRunning": "Ollama service is not running at {{baseUrl}}",
+		"serviceUnavailable": "Ollama service is unavailable (status: {{status}})",
+		"modelNotFound": "Ollama model not found: {{modelId}}",
+		"modelNotEmbeddingCapable": "Ollama model is not embedding capable: {{modelId}}",
+		"hostNotFound": "Ollama host not found: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "Unknown error processing file {{filePath}}",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Failed to connect to Qdrant vector database. Please ensure Qdrant is running and accessible at {{qdrantUrl}}. Error: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Authentication failed. Please check your API key in the settings.",
+		"connectionFailed": "Failed to connect to the embedder service. Please check your connection settings and ensure the service is running.",
+		"modelNotAvailable": "The specified model is not available. Please check your model configuration.",
+		"configurationError": "Invalid embedder configuration. Please review your settings.",
+		"serviceUnavailable": "The embedder service is not available. Please ensure it is running and accessible.",
+		"invalidEndpoint": "Invalid API endpoint. Please check your URL configuration.",
+		"invalidEmbedderConfig": "Invalid embedder configuration. Please check your settings.",
+		"invalidApiKey": "Invalid API key. Please check your API key configuration.",
+		"invalidBaseUrl": "Invalid base URL. Please check your URL configuration.",
+		"invalidModel": "Invalid model. Please check your model configuration.",
+		"invalidResponse": "Invalid response from embedder service. Please check your configuration."
 	}
 }
--- a/src/i18n/locales/es/common.json
+++ b/src/i18n/locales/es/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "¿Estás seguro de que deseas eliminar este perfil de configuración?",
 		"delete_custom_mode_with_rules": "¿Estás seguro de que quieres eliminar este modo {scope}?\n\nEsto también eliminará la carpeta de reglas asociada en:\n{rulesFolderPath}",
 		"delete_message": "¿Qué deseas eliminar?",
-		"just_this_message": "Solo este mensaje",
-		"this_and_subsequent": "Este y todos los mensajes posteriores"
+		"edit_message": "¿Eliminar todos los mensajes posteriores a este?",
+		"delete_just_this_message": "Solo este mensaje",
+		"edit_just_this_message": "No, solo editar este",
+		"delete_this_and_subsequent": "Este y todos los mensajes posteriores",
+		"edit_this_and_delete_subsequent": "Sí"
 	},
 	"errors": {
 		"invalid_data_uri": "Formato de URI de datos no válido",
@ -108,6 +111,11 @@
 		"remove": "Eliminar",
 		"keep": "Mantener"
 	},
+	"buttons": {
+		"save": "Guardar",
+		"cancel": "Cancelar",
+		"edit": "Editar"
+	},
 	"tasks": {
 		"canceled": "Error de tarea: Fue detenida y cancelada por el usuario.",
 		"deleted": "Fallo de tarea: Fue detenida y eliminada por el usuario.",
--- a/src/i18n/locales/es/embeddings.json
+++ b/src/i18n/locales/es/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "No se pudo leer el cuerpo del error",
 		"requestFailed": "La solicitud de la API de Ollama falló con estado {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Estructura de respuesta inválida de la API de Ollama: array \"embeddings\" no encontrado o no es un array.",
-		"embeddingFailed": "Incrustación de Ollama falló: {{message}}"
+		"embeddingFailed": "Incrustación de Ollama falló: {{message}}",
+		"serviceNotRunning": "El servicio Ollama no se está ejecutando en {{baseUrl}}",
+		"serviceUnavailable": "El servicio Ollama no está disponible (estado: {{status}})",
+		"modelNotFound": "No se encuentra el modelo Ollama: {{modelId}}",
+		"modelNotEmbeddingCapable": "El modelo Ollama no es capaz de realizar incrustaciones: {{modelId}}",
+		"hostNotFound": "No se encuentra el host de Ollama: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "Error desconocido procesando archivo {{filePath}}",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Error al conectar con la base de datos vectorial Qdrant. Asegúrate de que Qdrant esté funcionando y sea accesible en {{qdrantUrl}}. Error: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Error de autenticación. Comprueba tu clave de API en los ajustes.",
+		"connectionFailed": "Error al conectar con el servicio de embedder. Comprueba los ajustes de conexión y asegúrate de que el servicio esté funcionando.",
+		"modelNotAvailable": "El modelo especificado no está disponible. Comprueba la configuración de tu modelo.",
+		"configurationError": "Configuración de embedder no válida. Revisa tus ajustes.",
+		"serviceUnavailable": "El servicio de embedder no está disponible. Asegúrate de que esté funcionando y sea accesible.",
+		"invalidEndpoint": "Punto de conexión de API no válido. Comprueba la configuración de tu URL.",
+		"invalidEmbedderConfig": "Configuración de embedder no válida. Comprueba tus ajustes.",
+		"invalidApiKey": "Clave de API no válida. Comprueba la configuración de tu clave de API.",
+		"invalidBaseUrl": "URL base no válida. Comprueba la configuración de tu URL.",
+		"invalidModel": "Modelo no válido. Comprueba la configuración de tu modelo.",
+		"invalidResponse": "Respuesta no válida del servicio de embedder. Comprueba tu configuración."
 	}
 }
--- a/src/i18n/locales/fr/common.json
+++ b/src/i18n/locales/fr/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "Êtes-vous sûr de vouloir supprimer ce profil de configuration ?",
 		"delete_custom_mode_with_rules": "Êtes-vous sûr de vouloir supprimer ce mode {scope} ?\n\nCela supprimera également le dossier de règles associé à l'adresse :\n{rulesFolderPath}",
 		"delete_message": "Que souhaitez-vous supprimer ?",
-		"just_this_message": "Uniquement ce message",
-		"this_and_subsequent": "Ce message et tous les messages suivants"
+		"edit_message": "Supprimer tous les messages après celui-ci ?",
+		"delete_just_this_message": "Uniquement ce message",
+		"edit_just_this_message": "Non, modifier uniquement celui-ci",
+		"delete_this_and_subsequent": "Ce message et tous les messages suivants",
+		"edit_this_and_delete_subsequent": "Oui"
 	},
 	"errors": {
 		"invalid_data_uri": "Format d'URI de données invalide",
@ -108,6 +111,11 @@
 		"remove": "Supprimer",
 		"keep": "Conserver"
 	},
+	"buttons": {
+		"save": "Enregistrer",
+		"cancel": "Annuler",
+		"edit": "Modifier"
+	},
 	"tasks": {
 		"canceled": "Erreur de tâche : Elle a été arrêtée et annulée par l'utilisateur.",
 		"deleted": "Échec de la tâche : Elle a été arrêtée et supprimée par l'utilisateur.",
--- a/src/i18n/locales/fr/embeddings.json
+++ b/src/i18n/locales/fr/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "Impossible de lire le corps de l'erreur",
 		"requestFailed": "Échec de la requête API Ollama avec le statut {{status}} {{statusText}} : {{errorBody}}",
 		"invalidResponseStructure": "Structure de réponse invalide de l'API Ollama : tableau \"embeddings\" non trouvé ou n'est pas un tableau.",
-		"embeddingFailed": "Échec de l'embedding Ollama : {{message}}"
+		"embeddingFailed": "Échec de l'embedding Ollama : {{message}}",
+		"serviceNotRunning": "Le service Ollama n'est pas en cours d'exécution sur {{baseUrl}}",
+		"serviceUnavailable": "Le service Ollama est indisponible (statut : {{status}})",
+		"modelNotFound": "Modèle Ollama introuvable : {{modelId}}",
+		"modelNotEmbeddingCapable": "Le modèle Ollama n'est pas capable d'intégrer : {{modelId}}",
+		"hostNotFound": "Hôte Ollama introuvable : {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "Erreur inconnue lors du traitement du fichier {{filePath}}",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Échec de la connexion à la base de données vectorielle Qdrant. Veuillez vous assurer que Qdrant fonctionne et est accessible à {{qdrantUrl}}. Erreur : {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Échec de l'authentification. Veuillez vérifier votre clé API dans les paramètres.",
+		"connectionFailed": "Échec de la connexion au service d'embedding. Veuillez vérifier vos paramètres de connexion et vous assurer que le service est en cours d'exécution.",
+		"modelNotAvailable": "Le modèle spécifié n'est pas disponible. Veuillez vérifier la configuration de votre modèle.",
+		"configurationError": "Configuration de l'embedder invalide. Veuillez vérifier vos paramètres.",
+		"serviceUnavailable": "Le service d'embedding n'est pas disponible. Veuillez vous assurer qu'il est en cours d'exécution et accessible.",
+		"invalidEndpoint": "Point de terminaison d'API invalide. Veuillez vérifier votre configuration d'URL.",
+		"invalidEmbedderConfig": "Configuration de l'embedder invalide. Veuillez vérifier vos paramètres.",
+		"invalidApiKey": "Clé API invalide. Veuillez vérifier votre configuration de clé API.",
+		"invalidBaseUrl": "URL de base invalide. Veuillez vérifier votre configuration d'URL.",
+		"invalidModel": "Modèle invalide. Veuillez vérifier votre configuration de modèle.",
+		"invalidResponse": "Réponse invalide du service d'embedder. Veuillez vérifier votre configuration."
 	}
 }
--- a/src/i18n/locales/hi/common.json
+++ b/src/i18n/locales/hi/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "क्या आप वाकई इस कॉन्फ़िगरेशन प्रोफ़ाइल को हटाना चाहते हैं?",
 		"delete_custom_mode_with_rules": "क्या आप वाकई इस {scope} मोड को हटाना चाहते हैं?\n\nयह संबंधित नियम फ़ोल्डर को भी यहाँ हटा देगा:\n{rulesFolderPath}",
 		"delete_message": "आप क्या हटाना चाहते हैं?",
-		"just_this_message": "सिर्फ यह संदेश",
-		"this_and_subsequent": "यह और सभी बाद के संदेश"
+		"edit_message": "इसके बाद के सभी संदेशों को हटाएं?",
+		"delete_just_this_message": "सिर्फ यह संदेश",
+		"edit_just_this_message": "नहीं, केवल इसे संपादित करें",
+		"delete_this_and_subsequent": "यह और सभी बाद के संदेश",
+		"edit_this_and_delete_subsequent": "हां"
 	},
 	"errors": {
 		"invalid_data_uri": "अमान्य डेटा URI फॉर्मेट",
@ -108,6 +111,11 @@
 		"remove": "हटाएं",
 		"keep": "रखें"
 	},
+	"buttons": {
+		"save": "सहेजें",
+		"cancel": "रद्द करें",
+		"edit": "संपादित करें"
+	},
 	"tasks": {
 		"canceled": "टास्क त्रुटि: इसे उपयोगकर्ता द्वारा रोका और रद्द किया गया था।",
 		"deleted": "टास्क विफलता: इसे उपयोगकर्ता द्वारा रोका और हटाया गया था।",
--- a/src/i18n/locales/hi/embeddings.json
+++ b/src/i18n/locales/hi/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "त्रुटि सामग्री पढ़ नहीं सका",
 		"requestFailed": "Ollama API अनुरोध स्थिति {{status}} {{statusText}} के साथ विफल: {{errorBody}}",
 		"invalidResponseStructure": "Ollama API से अमान्य प्रतिक्रिया संरचना: \"embeddings\" सरणी नहीं मिली या सरणी नहीं है।",
-		"embeddingFailed": "Ollama एम्बेडिंग विफल: {{message}}"
+		"embeddingFailed": "Ollama एम्बेडिंग विफल: {{message}}",
+		"serviceNotRunning": "ओलामा सेवा {{baseUrl}} पर नहीं चल रही है",
+		"serviceUnavailable": "ओलामा सेवा अनुपलब्ध है (स्थिति: {{status}})",
+		"modelNotFound": "ओलामा मॉडल नहीं मिला: {{modelId}}",
+		"modelNotEmbeddingCapable": "ओलामा मॉडल एम्बेडिंग में सक्षम नहीं है: {{modelId}}",
+		"hostNotFound": "ओलामा होस्ट नहीं मिला: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "फ़ाइल {{filePath}} प्रसंस्करण में अज्ञात त्रुटि",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Qdrant वेक्टर डेटाबेस से कनेक्ट करने में विफल। कृपया सुनिश्चित करें कि Qdrant चल रहा है और {{qdrantUrl}} पर पहुंच योग्य है। त्रुटि: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "प्रमाणीकरण विफल। कृपया सेटिंग्स में अपनी एपीआई कुंजी जांचें।",
+		"connectionFailed": "एम्बेडर सेवा से कनेक्ट करने में विफल। कृपया अपनी कनेक्शन सेटिंग्स जांचें और सुनिश्चित करें कि सेवा चल रही है।",
+		"modelNotAvailable": "निर्दिष्ट मॉडल उपलब्ध नहीं है। कृपया अपनी मॉडल कॉन्फ़िगरेशन जांचें।",
+		"configurationError": "अमान्य एम्बेडर कॉन्फ़िगरेशन। कृपया अपनी सेटिंग्स की समीक्षा करें।",
+		"serviceUnavailable": "एम्बेडर सेवा उपलब्ध नहीं है। कृपया सुनिश्चित करें कि यह चल रहा है और पहुंच योग्य है।",
+		"invalidEndpoint": "अमान्य एपीआई एंडपॉइंट। कृपया अपनी यूआरएल कॉन्फ़िगरेशन जांचें।",
+		"invalidEmbedderConfig": "अमान्य एम्बेडर कॉन्फ़िगरेशन। कृपया अपनी सेटिंग्स जांचें।",
+		"invalidApiKey": "अमान्य एपीआई कुंजी। कृपया अपनी एपीआई कुंजी कॉन्फ़िगरेशन जांचें।",
+		"invalidBaseUrl": "अमान्य बेस यूआरएल। कृपया अपनी यूआरएल कॉन्फ़िगरेशन जांचें।",
+		"invalidModel": "अमान्य मॉडल। कृपया अपनी मॉडल कॉन्फ़िगरेशन जांचें।",
+		"invalidResponse": "एम्बेडर सेवा से अमान्य प्रतिक्रिया। कृपया अपनी कॉन्फ़िगरेशन जांचें।"
 	}
 }
--- a/src/i18n/locales/id/common.json
+++ b/src/i18n/locales/id/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "Apakah kamu yakin ingin menghapus profil konfigurasi ini?",
 		"delete_custom_mode_with_rules": "Anda yakin ingin menghapus mode {scope} ini?\n\nIni juga akan menghapus folder aturan terkait di:\n{rulesFolderPath}",
 		"delete_message": "Apa yang ingin kamu hapus?",
-		"just_this_message": "Hanya pesan ini",
-		"this_and_subsequent": "Ini dan semua pesan selanjutnya"
+		"edit_message": "Hapus semua pesan setelah ini?",
+		"delete_just_this_message": "Hanya pesan ini",
+		"edit_just_this_message": "Tidak, hanya edit yang ini",
+		"delete_this_and_subsequent": "Ini dan semua pesan selanjutnya",
+		"edit_this_and_delete_subsequent": "Ya"
 	},
 	"errors": {
 		"invalid_data_uri": "Format data URI tidak valid",
@ -108,6 +111,11 @@
 		"remove": "Hapus",
 		"keep": "Simpan"
 	},
+	"buttons": {
+		"save": "Simpan",
+		"cancel": "Batal",
+		"edit": "Edit"
+	},
 	"tasks": {
 		"canceled": "Error tugas: Dihentikan dan dibatalkan oleh pengguna.",
 		"deleted": "Kegagalan tugas: Dihentikan dan dihapus oleh pengguna.",
--- a/src/i18n/locales/id/embeddings.json
+++ b/src/i18n/locales/id/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "Tidak dapat membaca body error",
 		"requestFailed": "Permintaan API Ollama gagal dengan status {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Struktur respons tidak valid dari API Ollama: array \"embeddings\" tidak ditemukan atau bukan array.",
-		"embeddingFailed": "Embedding Ollama gagal: {{message}}"
+		"embeddingFailed": "Embedding Ollama gagal: {{message}}",
+		"serviceNotRunning": "Layanan Ollama tidak berjalan di {{baseUrl}}",
+		"serviceUnavailable": "Layanan Ollama tidak tersedia (status: {{status}})",
+		"modelNotFound": "Model Ollama tidak ditemukan: {{modelId}}",
+		"modelNotEmbeddingCapable": "Model Ollama tidak mampu melakukan embedding: {{modelId}}",
+		"hostNotFound": "Host Ollama tidak ditemukan: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "Error tidak dikenal saat memproses file {{filePath}}",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Gagal terhubung ke database vektor Qdrant. Pastikan Qdrant berjalan dan dapat diakses di {{qdrantUrl}}. Error: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Autentikasi gagal. Silakan periksa kunci API Anda di pengaturan.",
+		"connectionFailed": "Gagal terhubung ke layanan embedder. Silakan periksa pengaturan koneksi Anda dan pastikan layanan berjalan.",
+		"modelNotAvailable": "Model yang ditentukan tidak tersedia. Silakan periksa konfigurasi model Anda.",
+		"configurationError": "Konfigurasi embedder tidak valid. Harap tinjau pengaturan Anda.",
+		"serviceUnavailable": "Layanan embedder tidak tersedia. Pastikan layanan tersebut berjalan dan dapat diakses.",
+		"invalidEndpoint": "Endpoint API tidak valid. Silakan periksa konfigurasi URL Anda.",
+		"invalidEmbedderConfig": "Konfigurasi embedder tidak valid. Silakan periksa pengaturan Anda.",
+		"invalidApiKey": "Kunci API tidak valid. Silakan periksa konfigurasi kunci API Anda.",
+		"invalidBaseUrl": "URL dasar tidak valid. Silakan periksa konfigurasi URL Anda.",
+		"invalidModel": "Model tidak valid. Silakan periksa konfigurasi model Anda.",
+		"invalidResponse": "Respons tidak valid dari layanan embedder. Silakan periksa konfigurasi Anda."
 	}
 }
--- a/src/i18n/locales/it/common.json
+++ b/src/i18n/locales/it/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "Sei sicuro di voler eliminare questo profilo di configurazione?",
 		"delete_custom_mode_with_rules": "Sei sicuro di voler eliminare questa modalità {scope}?\n\nQuesto eliminerà anche la cartella delle regole associata in:\n{rulesFolderPath}",
 		"delete_message": "Cosa desideri eliminare?",
-		"just_this_message": "Solo questo messaggio",
-		"this_and_subsequent": "Questo e tutti i messaggi successivi"
+		"edit_message": "Eliminare tutti i messaggi dopo questo?",
+		"delete_just_this_message": "Solo questo messaggio",
+		"edit_just_this_message": "No, modifica solo questo",
+		"delete_this_and_subsequent": "Questo e tutti i messaggi successivi",
+		"edit_this_and_delete_subsequent": "Sì"
 	},
 	"errors": {
 		"invalid_data_uri": "Formato URI dati non valido",
@ -108,6 +111,11 @@
 		"remove": "Rimuovi",
 		"keep": "Mantieni"
 	},
+	"buttons": {
+		"save": "Salva",
+		"cancel": "Annulla",
+		"edit": "Modifica"
+	},
 	"tasks": {
 		"canceled": "Errore attività: È stata interrotta e annullata dall'utente.",
 		"deleted": "Fallimento attività: È stata interrotta ed eliminata dall'utente.",
--- a/src/i18n/locales/it/embeddings.json
+++ b/src/i18n/locales/it/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "Impossibile leggere il corpo dell'errore",
 		"requestFailed": "Richiesta API Ollama fallita con stato {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Struttura di risposta non valida dall'API Ollama: array \"embeddings\" non trovato o non è un array.",
-		"embeddingFailed": "Embedding Ollama fallito: {{message}}"
+		"embeddingFailed": "Embedding Ollama fallito: {{message}}",
+		"serviceNotRunning": "Il servizio Ollama non è in esecuzione su {{baseUrl}}",
+		"serviceUnavailable": "Il servizio Ollama non è disponibile (stato: {{status}})",
+		"modelNotFound": "Modello Ollama non trovato: {{modelId}}",
+		"modelNotEmbeddingCapable": "Il modello Ollama non è in grado di eseguire l'embedding: {{modelId}}",
+		"hostNotFound": "Host Ollama non trovato: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "Errore sconosciuto nell'elaborazione del file {{filePath}}",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Impossibile connettersi al database vettoriale Qdrant. Assicurati che Qdrant sia in esecuzione e accessibile su {{qdrantUrl}}. Errore: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Autenticazione fallita. Controlla la tua chiave API nelle impostazioni.",
+		"connectionFailed": "Connessione al servizio di embedder fallita. Controlla le impostazioni di connessione e assicurati che il servizio sia in esecuzione.",
+		"modelNotAvailable": "Il modello specificato non è disponibile. Controlla la configurazione del tuo modello.",
+		"configurationError": "Configurazione dell'embedder non valida. Rivedi le tue impostazioni.",
+		"serviceUnavailable": "Il servizio di embedder non è disponibile. Assicurati che sia in esecuzione e accessibile.",
+		"invalidEndpoint": "Endpoint API non valido. Controlla la configurazione del tuo URL.",
+		"invalidEmbedderConfig": "Configurazione dell'embedder non valida. Controlla le tue impostazioni.",
+		"invalidApiKey": "Chiave API non valida. Controlla la configurazione della tua chiave API.",
+		"invalidBaseUrl": "URL di base non valido. Controlla la configurazione del tuo URL.",
+		"invalidModel": "Modello non valido. Controlla la configurazione del tuo modello.",
+		"invalidResponse": "Risposta non valida dal servizio embedder. Controlla la tua configurazione."
 	}
 }
--- a/src/i18n/locales/ja/common.json
+++ b/src/i18n/locales/ja/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "この設定プロファイルを削除してもよろしいですか？",
 		"delete_custom_mode_with_rules": "この{scope}モードを削除してもよろしいですか？\n\nこれにより、関連するルールフォルダも次の場所で削除されます:\n{rulesFolderPath}",
 		"delete_message": "何を削除しますか？",
-		"just_this_message": "このメッセージのみ",
-		"this_and_subsequent": "これ以降のすべてのメッセージ"
+		"edit_message": "これ以降のメッセージをすべて削除しますか？",
+		"delete_just_this_message": "このメッセージのみ",
+		"edit_just_this_message": "いいえ、これだけを編集",
+		"delete_this_and_subsequent": "これ以降のすべてのメッセージ",
+		"edit_this_and_delete_subsequent": "はい"
 	},
 	"errors": {
 		"invalid_data_uri": "データURIフォーマットが無効です",
@ -108,6 +111,11 @@
 		"remove": "削除",
 		"keep": "保持"
 	},
+	"buttons": {
+		"save": "保存",
+		"cancel": "キャンセル",
+		"edit": "編集"
+	},
 	"tasks": {
 		"canceled": "タスクエラー：ユーザーによって停止およびキャンセルされました。",
 		"deleted": "タスク失敗：ユーザーによって停止および削除されました。",
--- a/src/i18n/locales/ja/embeddings.json
+++ b/src/i18n/locales/ja/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "エラー本文を読み取れませんでした",
 		"requestFailed": "Ollama APIリクエストが失敗しました。ステータス {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Ollama APIからの無効な応答構造：\"embeddings\"配列が見つからないか、配列ではありません。",
-		"embeddingFailed": "Ollama埋め込みが失敗しました：{{message}}"
+		"embeddingFailed": "Ollama埋め込みが失敗しました：{{message}}",
+		"serviceNotRunning": "Ollamaサービスは{{baseUrl}}で実行されていません",
+		"serviceUnavailable": "Ollamaサービスは利用できません（ステータス：{{status}}）",
+		"modelNotFound": "Ollamaモデルが見つかりません：{{modelId}}",
+		"modelNotEmbeddingCapable": "Ollamaモデルは埋め込みに対応していません：{{modelId}}",
+		"hostNotFound": "Ollamaホストが見つかりません：{{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "ファイル{{filePath}}の処理中に不明なエラーが発生しました",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Qdrantベクターデータベースへの接続に失敗しました。Qdrantが実行中で{{qdrantUrl}}でアクセス可能であることを確認してください。エラー：{{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "認証に失敗しました。設定でAPIキーを確認してください。",
+		"connectionFailed": "エンベッダーサービスへの接続に失敗しました。接続設定を確認し、サービスが実行されていることを確認してください。",
+		"modelNotAvailable": "指定されたモデルは利用できません。モデル構成を確認してください。",
+		"configurationError": "無効なエンベッダー構成です。設定を確認してください。",
+		"serviceUnavailable": "エンベッダーサービスは利用できません。実行中でアクセス可能であることを確認してください。",
+		"invalidEndpoint": "無効なAPIエンドポイントです。URL構成を確認してください。",
+		"invalidEmbedderConfig": "無効なエンベッダー構成です。設定を確認してください。",
+		"invalidApiKey": "無効なAPIキーです。APIキー構成を確認してください。",
+		"invalidBaseUrl": "無効なベースURLです。URL構成を確認してください。",
+		"invalidModel": "無効なモデルです。モデル構成を確認してください。",
+		"invalidResponse": "エンベッダーサービスからの無効な応答です。設定を確認してください。"
 	}
 }
--- a/src/i18n/locales/ko/common.json
+++ b/src/i18n/locales/ko/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "이 구성 프로필을 삭제하시겠습니까?",
 		"delete_custom_mode_with_rules": "이 {scope} 모드를 삭제하시겠습니까?\n\n이렇게 하면 연결된 규칙 폴더도 다음 위치에서 삭제됩니다:\n{rulesFolderPath}",
 		"delete_message": "무엇을 삭제하시겠습니까?",
-		"just_this_message": "이 메시지만",
-		"this_and_subsequent": "이 메시지와 모든 후속 메시지"
+		"edit_message": "이 메시지 이후의 모든 메시지를 삭제하시겠습니까?",
+		"delete_just_this_message": "이 메시지만",
+		"edit_just_this_message": "아니요, 이것만 편집",
+		"delete_this_and_subsequent": "이 메시지와 모든 후속 메시지",
+		"edit_this_and_delete_subsequent": "예"
 	},
 	"errors": {
 		"invalid_data_uri": "잘못된 데이터 URI 형식",
@ -108,6 +111,11 @@
 		"remove": "제거",
 		"keep": "유지"
 	},
+	"buttons": {
+		"save": "저장",
+		"cancel": "취소",
+		"edit": "편집"
+	},
 	"tasks": {
 		"canceled": "작업 오류: 사용자에 의해 중지 및 취소되었습니다.",
 		"deleted": "작업 실패: 사용자에 의해 중지 및 삭제되었습니다.",
--- a/src/i18n/locales/ko/embeddings.json
+++ b/src/i18n/locales/ko/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "오류 본문을 읽을 수 없습니다",
 		"requestFailed": "Ollama API 요청이 실패했습니다. 상태 {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Ollama API에서 잘못된 응답 구조: \"embeddings\" 배열을 찾을 수 없거나 배열이 아닙니다.",
-		"embeddingFailed": "Ollama 임베딩 실패: {{message}}"
+		"embeddingFailed": "Ollama 임베딩 실패: {{message}}",
+		"serviceNotRunning": "Ollama 서비스가 {{baseUrl}}에서 실행되고 있지 않습니다",
+		"serviceUnavailable": "Ollama 서비스를 사용할 수 없습니다 (상태: {{status}})",
+		"modelNotFound": "Ollama 모델을 찾을 수 없습니다: {{modelId}}",
+		"modelNotEmbeddingCapable": "Ollama 모델은 임베딩이 불가능합니다: {{modelId}}",
+		"hostNotFound": "Ollama 호스트를 찾을 수 없습니다: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "파일 {{filePath}} 처리 중 알 수 없는 오류",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Qdrant 벡터 데이터베이스에 연결하지 못했습니다. Qdrant가 실행 중이고 {{qdrantUrl}}에서 접근 가능한지 확인하세요. 오류: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "인증에 실패했습니다. 설정에서 API 키를 확인하세요.",
+		"connectionFailed": "임베더 서비스에 연결하지 못했습니다. 연결 설정을 확인하고 서비스가 실행 중인지 확인하세요.",
+		"modelNotAvailable": "지정된 모델을 사용할 수 없습니다. 모델 구성을 확인하세요.",
+		"configurationError": "잘못된 임베더 구성입니다. 설정을 검토하세요.",
+		"serviceUnavailable": "임베더 서비스를 사용할 수 없습니다. 실행 중이고 액세스 가능한지 확인하세요.",
+		"invalidEndpoint": "잘못된 API 엔드포인트입니다. URL 구성을 확인하세요.",
+		"invalidEmbedderConfig": "잘못된 임베더 구성입니다. 설정을 확인하세요.",
+		"invalidApiKey": "잘못된 API 키입니다. API 키 구성을 확인하세요.",
+		"invalidBaseUrl": "잘못된 기본 URL입니다. URL 구성을 확인하세요.",
+		"invalidModel": "잘못된 모델입니다. 모델 구성을 확인하세요.",
+		"invalidResponse": "임베더 서비스에서 잘못된 응답이 왔습니다. 구성을 확인하세요."
 	}
 }
--- a/src/i18n/locales/nl/common.json
+++ b/src/i18n/locales/nl/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "Weet je zeker dat je dit configuratieprofiel wilt verwijderen?",
 		"delete_custom_mode_with_rules": "Weet je zeker dat je deze {scope}-modus wilt verwijderen?\n\nDit verwijdert ook de bijbehorende regelsmap op:\n{rulesFolderPath}",
 		"delete_message": "Wat wil je verwijderen?",
-		"just_this_message": "Alleen dit bericht",
-		"this_and_subsequent": "Dit en alle volgende berichten"
+		"delete_just_this_message": "Alleen dit bericht",
+		"delete_this_and_subsequent": "Dit en alle volgende berichten",
+		"edit_message": "Alle berichten na dit bericht verwijderen?",
+		"edit_just_this_message": "Nee, alleen dit bericht bewerken",
+		"edit_this_and_delete_subsequent": "Ja"
 	},
 	"errors": {
 		"invalid_data_uri": "Ongeldig data-URI-formaat",
@ -108,6 +111,11 @@
 		"remove": "Verwijderen",
 		"keep": "Behouden"
 	},
+	"buttons": {
+		"save": "Opslaan",
+		"cancel": "Annuleren",
+		"edit": "Bewerken"
+	},
 	"tasks": {
 		"canceled": "Taakfout: gestopt en geannuleerd door gebruiker.",
 		"deleted": "Taakfout: gestopt en verwijderd door gebruiker.",
--- a/src/i18n/locales/nl/embeddings.json
+++ b/src/i18n/locales/nl/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "Kon foutinhoud niet lezen",
 		"requestFailed": "Ollama API-verzoek mislukt met status {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Ongeldige responsstructuur van Ollama API: \"embeddings\" array niet gevonden of is geen array.",
-		"embeddingFailed": "Ollama insluiting mislukt: {{message}}"
+		"embeddingFailed": "Ollama insluiting mislukt: {{message}}",
+		"serviceNotRunning": "Ollama-service draait niet op {{baseUrl}}",
+		"serviceUnavailable": "Ollama-service is niet beschikbaar (status: {{status}})",
+		"modelNotFound": "Ollama-model niet gevonden: {{modelId}}",
+		"modelNotEmbeddingCapable": "Ollama-model is niet in staat tot insluiten: {{modelId}}",
+		"hostNotFound": "Ollama-host niet gevonden: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "Onbekende fout bij verwerken van bestand {{filePath}}",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Kan geen verbinding maken met Qdrant vectordatabase. Zorg ervoor dat Qdrant draait en toegankelijk is op {{qdrantUrl}}. Fout: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Authenticatie mislukt. Controleer je API-sleutel in de instellingen.",
+		"connectionFailed": "Verbinding met de embedder-service mislukt. Controleer je verbindingsinstellingen en zorg ervoor dat de service draait.",
+		"modelNotAvailable": "Het opgegeven model is niet beschikbaar. Controleer je modelconfiguratie.",
+		"configurationError": "Ongeldige embedder-configuratie. Controleer je instellingen.",
+		"serviceUnavailable": "De embedder-service is niet beschikbaar. Zorg ervoor dat deze draait en toegankelijk is.",
+		"invalidEndpoint": "Ongeldig API-eindpunt. Controleer je URL-configuratie.",
+		"invalidEmbedderConfig": "Ongeldige embedder-configuratie. Controleer je instellingen.",
+		"invalidApiKey": "Ongeldige API-sleutel. Controleer je API-sleutelconfiguratie.",
+		"invalidBaseUrl": "Ongeldige basis-URL. Controleer je URL-configuratie.",
+		"invalidModel": "Ongeldig model. Controleer je modelconfiguratie.",
+		"invalidResponse": "Ongeldige reactie van embedder-service. Controleer je configuratie."
 	}
 }
--- a/src/i18n/locales/pl/common.json
+++ b/src/i18n/locales/pl/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "Czy na pewno chcesz usunąć ten profil konfiguracyjny?",
 		"delete_custom_mode_with_rules": "Czy na pewno chcesz usunąć ten tryb {scope}?\n\nSpowoduje to również usunięcie powiązanego folderu reguł pod adresem:\n{rulesFolderPath}",
 		"delete_message": "Co chcesz usunąć?",
-		"just_this_message": "Tylko tę wiadomość",
-		"this_and_subsequent": "Tę i wszystkie kolejne wiadomości"
+		"delete_just_this_message": "Tylko tę wiadomość",
+		"delete_this_and_subsequent": "Tę i wszystkie kolejne wiadomości",
+		"edit_message": "Usunąć wszystkie wiadomości po tej?",
+		"edit_just_this_message": "Nie, tylko edytuj tę wiadomość",
+		"edit_this_and_delete_subsequent": "Tak"
 	},
 	"errors": {
 		"invalid_data_uri": "Nieprawidłowy format URI danych",
@ -108,6 +111,11 @@
 		"remove": "Usuń",
 		"keep": "Zachowaj"
 	},
+	"buttons": {
+		"save": "Zapisz",
+		"cancel": "Anuluj",
+		"edit": "Edytuj"
+	},
 	"tasks": {
 		"canceled": "Błąd zadania: Zostało zatrzymane i anulowane przez użytkownika.",
 		"deleted": "Niepowodzenie zadania: Zostało zatrzymane i usunięte przez użytkownika.",
--- a/src/i18n/locales/pl/embeddings.json
+++ b/src/i18n/locales/pl/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "Nie można odczytać treści błędu",
 		"requestFailed": "Żądanie API Ollama nie powiodło się ze statusem {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Nieprawidłowa struktura odpowiedzi z API Ollama: tablica \"embeddings\" nie została znaleziona lub nie jest tablicą.",
-		"embeddingFailed": "Osadzenie Ollama nie powiodło się: {{message}}"
+		"embeddingFailed": "Osadzenie Ollama nie powiodło się: {{message}}",
+		"serviceNotRunning": "Usługa Ollama nie jest uruchomiona pod adresem {{baseUrl}}",
+		"serviceUnavailable": "Usługa Ollama jest niedostępna (status: {{status}})",
+		"modelNotFound": "Nie znaleziono modelu Ollama: {{modelId}}",
+		"modelNotEmbeddingCapable": "Model Ollama nie jest zdolny do osadzania: {{modelId}}",
+		"hostNotFound": "Nie znaleziono hosta Ollama: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "Nieznany błąd podczas przetwarzania pliku {{filePath}}",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Nie udało się połączyć z bazą danych wektorowych Qdrant. Upewnij się, że Qdrant jest uruchomiony i dostępny pod adresem {{qdrantUrl}}. Błąd: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Uwierzytelnianie nie powiodło się. Sprawdź swój klucz API w ustawieniach.",
+		"connectionFailed": "Nie udało się połączyć z usługą embeddera. Sprawdź ustawienia połączenia i upewnij się, że usługa jest uruchomiona.",
+		"modelNotAvailable": "Określony model jest niedostępny. Sprawdź konfigurację modelu.",
+		"configurationError": "Nieprawidłowa konfiguracja embeddera. Sprawdź swoje ustawienia.",
+		"serviceUnavailable": "Usługa embeddera jest niedostępna. Upewnij się, że jest uruchomiona i dostępna.",
+		"invalidEndpoint": "Nieprawidłowy punkt końcowy API. Sprawdź konfigurację adresu URL.",
+		"invalidEmbedderConfig": "Nieprawidłowa konfiguracja embeddera. Sprawdź swoje ustawienia.",
+		"invalidApiKey": "Nieprawidłowy klucz API. Sprawdź konfigurację klucza API.",
+		"invalidBaseUrl": "Nieprawidłowy podstawowy adres URL. Sprawdź konfigurację adresu URL.",
+		"invalidModel": "Nieprawidłowy model. Sprawdź konfigurację modelu.",
+		"invalidResponse": "Nieprawidłowa odpowiedź z usługi embedder. Sprawdź swoją konfigurację."
 	}
 }
--- a/src/i18n/locales/pt-BR/common.json
+++ b/src/i18n/locales/pt-BR/common.json
@ -23,8 +23,11 @@
 		"delete_config_profile": "Tem certeza de que deseja excluir este perfil de configuração?",
 		"delete_custom_mode_with_rules": "Tem certeza de que deseja excluir este modo {scope}?\n\nIsso também excluirá a pasta de regras associada em:\n{rulesFolderPath}",
 		"delete_message": "O que você gostaria de excluir?",
-		"just_this_message": "Apenas esta mensagem",
-		"this_and_subsequent": "Esta e todas as mensagens subsequentes"
+		"delete_just_this_message": "Apenas esta mensagem",
+		"delete_this_and_subsequent": "Esta e todas as mensagens subsequentes",
+		"edit_message": "Excluir todas as mensagens após esta?",
+		"edit_just_this_message": "Não, apenas editar esta",
+		"edit_this_and_delete_subsequent": "Sim"
 	},
 	"errors": {
 		"invalid_data_uri": "Formato de URI de dados inválido",
@ -112,6 +115,11 @@
 		"remove": "Remover",
 		"keep": "Manter"
 	},
+	"buttons": {
+		"save": "Salvar",
+		"cancel": "Cancelar",
+		"edit": "Editar"
+	},
 	"tasks": {
 		"canceled": "Erro na tarefa: Foi interrompida e cancelada pelo usuário.",
 		"deleted": "Falha na tarefa: Foi interrompida e excluída pelo usuário.",
--- a/src/i18n/locales/pt-BR/embeddings.json
+++ b/src/i18n/locales/pt-BR/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "Não foi possível ler o corpo do erro",
 		"requestFailed": "Solicitação da API Ollama falhou com status {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Estrutura de resposta inválida da API Ollama: array \"embeddings\" não encontrado ou não é um array.",
-		"embeddingFailed": "Embedding Ollama falhou: {{message}}"
+		"embeddingFailed": "Embedding Ollama falhou: {{message}}",
+		"serviceNotRunning": "O serviço Ollama não está em execução em {{baseUrl}}",
+		"serviceUnavailable": "O serviço Ollama não está disponível (status: {{status}})",
+		"modelNotFound": "Modelo Ollama não encontrado: {{modelId}}",
+		"modelNotEmbeddingCapable": "O modelo Ollama não é capaz de embedding: {{modelId}}",
+		"hostNotFound": "Host Ollama não encontrado: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "Erro desconhecido ao processar arquivo {{filePath}}",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Falha ao conectar com o banco de dados vetorial Qdrant. Certifique-se de que o Qdrant esteja rodando e acessível em {{qdrantUrl}}. Erro: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Falha na autenticação. Verifique sua chave de API nas configurações.",
+		"connectionFailed": "Falha ao conectar ao serviço do embedder. Verifique suas configurações de conexão e garanta que o serviço esteja em execução.",
+		"modelNotAvailable": "O modelo especificado não está disponível. Verifique a configuração do seu modelo.",
+		"configurationError": "Configuração do embedder inválida. Revise suas configurações.",
+		"serviceUnavailable": "O serviço do embedder não está disponível. Garanta que ele esteja em execução e acessível.",
+		"invalidEndpoint": "Endpoint de API inválido. Verifique sua configuração de URL.",
+		"invalidEmbedderConfig": "Configuração do embedder inválida. Verifique suas configurações.",
+		"invalidApiKey": "Chave de API inválida. Verifique sua configuração de chave de API.",
+		"invalidBaseUrl": "URL base inválida. Verifique sua configuração de URL.",
+		"invalidModel": "Modelo inválido. Verifique a configuração do seu modelo.",
+		"invalidResponse": "Resposta inválida do serviço de embedder. Verifique sua configuração."
 	}
 }
--- a/src/i18n/locales/ru/common.json
+++ b/src/i18n/locales/ru/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "Вы уверены, что хотите удалить этот профиль конфигурации?",
 		"delete_custom_mode_with_rules": "Вы уверены, что хотите удалить этот режим {scope}?\n\nЭто также приведет к удалению соответствующей папки правил по адресу:\n{rulesFolderPath}",
 		"delete_message": "Что вы хотите удалить?",
-		"just_this_message": "Только это сообщение",
-		"this_and_subsequent": "Это и все последующие сообщения"
+		"delete_just_this_message": "Только это сообщение",
+		"delete_this_and_subsequent": "Это и все последующие сообщения",
+		"edit_message": "Удалить все сообщения после этого?",
+		"edit_just_this_message": "Нет, только редактировать это",
+		"edit_this_and_delete_subsequent": "Да"
 	},
 	"errors": {
 		"invalid_data_uri": "Неверный формат URI данных",
@ -108,6 +111,11 @@
 		"remove": "Удалить",
 		"keep": "Оставить"
 	},
+	"buttons": {
+		"save": "Сохранить",
+		"cancel": "Отмена",
+		"edit": "Редактировать"
+	},
 	"tasks": {
 		"canceled": "Ошибка задачи: Она была остановлена и отменена пользователем.",
 		"deleted": "Сбой задачи: Она была остановлена и удалена пользователем.",
--- a/src/i18n/locales/ru/embeddings.json
+++ b/src/i18n/locales/ru/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "Не удалось прочитать тело ошибки",
 		"requestFailed": "Запрос к API Ollama не удался со статусом {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Неверная структура ответа от API Ollama: массив \"embeddings\" не найден или не является массивом.",
-		"embeddingFailed": "Вложение Ollama не удалось: {{message}}"
+		"embeddingFailed": "Вложение Ollama не удалось: {{message}}",
+		"serviceNotRunning": "Сервис Ollama не запущен по адресу {{baseUrl}}",
+		"serviceUnavailable": "Сервис Ollama недоступен (статус: {{status}})",
+		"modelNotFound": "Модель Ollama не найдена: {{modelId}}",
+		"modelNotEmbeddingCapable": "Модель Ollama не способна к вложению: {{modelId}}",
+		"hostNotFound": "Хост Ollama не найден: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "Неизвестная ошибка при обработке файла {{filePath}}",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Не удалось подключиться к векторной базе данных Qdrant. Убедитесь, что Qdrant запущен и доступен по адресу {{qdrantUrl}}. Ошибка: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Ошибка аутентификации. Проверьте свой ключ API в настройках.",
+		"connectionFailed": "Не удалось подключиться к службе эмбеддера. Проверьте настройки подключения и убедитесь, что служба запущена.",
+		"modelNotAvailable": "Указанная модель недоступна. Проверьте конфигурацию модели.",
+		"configurationError": "Неверная конфигурация эмбеддера. Проверьте свои настройки.",
+		"serviceUnavailable": "Служба эмбеддера недоступна. Убедитесь, что она запущена и доступна.",
+		"invalidEndpoint": "Неверная конечная точка API. Проверьте конфигурацию URL.",
+		"invalidEmbedderConfig": "Неверная конфигурация эмбеддера. Проверьте свои настройки.",
+		"invalidApiKey": "Неверный ключ API. Проверьте конфигурацию ключа API.",
+		"invalidBaseUrl": "Неверный базовый URL. Проверьте конфигурацию URL.",
+		"invalidModel": "Неверная модель. Проверьте конфигурацию модели.",
+		"invalidResponse": "Неверный ответ от службы embedder. Проверьте вашу конфигурацию."
 	}
 }
--- a/src/i18n/locales/tr/common.json
+++ b/src/i18n/locales/tr/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "Bu yapılandırma profilini silmek istediğinizden emin misiniz?",
 		"delete_custom_mode_with_rules": "Bu {scope} modunu silmek istediğinizden emin misiniz?\n\nBu işlem, ilişkili kurallar klasörünü de şu konumdan silecektir:\n{rulesFolderPath}",
 		"delete_message": "Neyi silmek istersiniz?",
-		"just_this_message": "Sadece bu mesajı",
-		"this_and_subsequent": "Bu ve sonraki tüm mesajları"
+		"delete_just_this_message": "Sadece bu mesajı",
+		"delete_this_and_subsequent": "Bu ve sonraki tüm mesajları",
+		"edit_message": "Bu mesajdan sonraki tüm mesajlar silinsin mi?",
+		"edit_just_this_message": "Hayır, sadece bunu düzenle",
+		"edit_this_and_delete_subsequent": "Evet"
 	},
 	"errors": {
 		"invalid_data_uri": "Geçersiz veri URI formatı",
@ -108,6 +111,11 @@
 		"remove": "Kaldır",
 		"keep": "Koru"
 	},
+	"buttons": {
+		"save": "Kaydet",
+		"cancel": "İptal",
+		"edit": "Düzenle"
+	},
 	"tasks": {
 		"canceled": "Görev hatası: Kullanıcı tarafından durduruldu ve iptal edildi.",
 		"deleted": "Görev başarısız: Kullanıcı tarafından durduruldu ve silindi.",
--- a/src/i18n/locales/tr/embeddings.json
+++ b/src/i18n/locales/tr/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "Hata gövdesi okunamadı",
 		"requestFailed": "Ollama API isteği {{status}} {{statusText}} durumuyla başarısız oldu: {{errorBody}}",
 		"invalidResponseStructure": "Ollama API'den geçersiz yanıt yapısı: \"embeddings\" dizisi bulunamadı veya dizi değil.",
-		"embeddingFailed": "Ollama gömülmesi başarısız oldu: {{message}}"
+		"embeddingFailed": "Ollama gömülmesi başarısız oldu: {{message}}",
+		"serviceNotRunning": "Ollama hizmeti {{baseUrl}} adresinde çalışmıyor",
+		"serviceUnavailable": "Ollama hizmeti kullanılamıyor (durum: {{status}})",
+		"modelNotFound": "Ollama modeli bulunamadı: {{modelId}}",
+		"modelNotEmbeddingCapable": "Ollama modeli gömme yeteneğine sahip değil: {{modelId}}",
+		"hostNotFound": "Ollama ana bilgisayarı bulunamadı: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "{{filePath}} dosyası işlenirken bilinmeyen hata",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Qdrant vektör veritabanına bağlanılamadı. Qdrant'ın çalıştığından ve {{qdrantUrl}} adresinde erişilebilir olduğundan emin olun. Hata: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Kimlik doğrulama başarısız oldu. Lütfen ayarlardan API anahtarınızı kontrol edin.",
+		"connectionFailed": "Gömücü hizmetine bağlanılamadı. Lütfen bağlantı ayarlarınızı kontrol edin ve hizmetin çalıştığından emin olun.",
+		"modelNotAvailable": "Belirtilen model mevcut değil. Lütfen model yapılandırmanızı kontrol edin.",
+		"configurationError": "Geçersiz gömücü yapılandırması. Lütfen ayarlarınızı gözden geçirin.",
+		"serviceUnavailable": "Gömücü hizmeti mevcut değil. Lütfen çalıştığından ve erişilebilir olduğundan emin olun.",
+		"invalidEndpoint": "Geçersiz API uç noktası. Lütfen URL yapılandırmanızı kontrol edin.",
+		"invalidEmbedderConfig": "Geçersiz gömücü yapılandırması. Lütfen ayarlarınızı kontrol edin.",
+		"invalidApiKey": "Geçersiz API anahtarı. Lütfen API anahtarı yapılandırmanızı kontrol edin.",
+		"invalidBaseUrl": "Geçersiz temel URL. Lütfen URL yapılandırmanızı kontrol edin.",
+		"invalidModel": "Geçersiz model. Lütfen model yapılandırmanızı kontrol edin.",
+		"invalidResponse": "Embedder hizmetinden geçersiz yanıt. Lütfen yapılandırmanızı kontrol edin."
 	}
 }
--- a/src/i18n/locales/vi/common.json
+++ b/src/i18n/locales/vi/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "Bạn có chắc chắn muốn xóa hồ sơ cấu hình này không?",
 		"delete_custom_mode_with_rules": "Bạn có chắc chắn muốn xóa chế độ {scope} này không?\n\nThao tác này cũng sẽ xóa thư mục quy tắc liên quan tại:\n{rulesFolderPath}",
 		"delete_message": "Bạn muốn xóa gì?",
-		"just_this_message": "Chỉ tin nhắn này",
-		"this_and_subsequent": "Tin nhắn này và tất cả tin nhắn tiếp theo"
+		"delete_just_this_message": "Chỉ tin nhắn này",
+		"delete_this_and_subsequent": "Tin nhắn này và tất cả tin nhắn tiếp theo",
+		"edit_message": "Xóa tất cả tin nhắn sau tin nhắn này?",
+		"edit_just_this_message": "Không, chỉ chỉnh sửa tin nhắn này",
+		"edit_this_and_delete_subsequent": "Có"
 	},
 	"errors": {
 		"invalid_data_uri": "Định dạng URI dữ liệu không hợp lệ",
@ -108,6 +111,11 @@
 		"remove": "Xóa",
 		"keep": "Giữ"
 	},
+	"buttons": {
+		"save": "Lưu",
+		"cancel": "Hủy",
+		"edit": "Chỉnh sửa"
+	},
 	"tasks": {
 		"canceled": "Lỗi nhiệm vụ: Nó đã bị dừng và hủy bởi người dùng.",
 		"deleted": "Nhiệm vụ thất bại: Nó đã bị dừng và xóa bởi người dùng.",
--- a/src/i18n/locales/vi/embeddings.json
+++ b/src/i18n/locales/vi/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "Không thể đọc nội dung lỗi",
 		"requestFailed": "Yêu cầu API Ollama thất bại với trạng thái {{status}} {{statusText}}: {{errorBody}}",
 		"invalidResponseStructure": "Cấu trúc phản hồi không hợp lệ từ API Ollama: không tìm thấy mảng \"embeddings\" hoặc không phải là mảng.",
-		"embeddingFailed": "Nhúng Ollama thất bại: {{message}}"
+		"embeddingFailed": "Nhúng Ollama thất bại: {{message}}",
+		"serviceNotRunning": "Dịch vụ Ollama không chạy tại {{baseUrl}}",
+		"serviceUnavailable": "Dịch vụ Ollama không khả dụng (trạng thái: {{status}})",
+		"modelNotFound": "Không tìm thấy mô hình Ollama: {{modelId}}",
+		"modelNotEmbeddingCapable": "Mô hình Ollama không có khả năng nhúng: {{modelId}}",
+		"hostNotFound": "Không tìm thấy máy chủ Ollama: {{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "Lỗi không xác định khi xử lý tệp {{filePath}}",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "Không thể kết nối với cơ sở dữ liệu vector Qdrant. Vui lòng đảm bảo Qdrant đang chạy và có thể truy cập tại {{qdrantUrl}}. Lỗi: {{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "Xác thực không thành công. Vui lòng kiểm tra khóa API của bạn trong cài đặt.",
+		"connectionFailed": "Không thể kết nối với dịch vụ nhúng. Vui lòng kiểm tra cài đặt kết nối của bạn và đảm bảo dịch vụ đang chạy.",
+		"modelNotAvailable": "Mô hình được chỉ định không có sẵn. Vui lòng kiểm tra cấu hình mô hình của bạn.",
+		"configurationError": "Cấu hình nhúng không hợp lệ. Vui lòng xem lại cài đặt của bạn.",
+		"serviceUnavailable": "Dịch vụ nhúng không có sẵn. Vui lòng đảm bảo nó đang chạy và có thể truy cập được.",
+		"invalidEndpoint": "Điểm cuối API không hợp lệ. Vui lòng kiểm tra cấu hình URL của bạn.",
+		"invalidEmbedderConfig": "Cấu hình nhúng không hợp lệ. Vui lòng kiểm tra cài đặt của bạn.",
+		"invalidApiKey": "Khóa API không hợp lệ. Vui lòng kiểm tra cấu hình khóa API của bạn.",
+		"invalidBaseUrl": "URL cơ sở không hợp lệ. Vui lòng kiểm tra cấu hình URL của bạn.",
+		"invalidModel": "Mô hình không hợp lệ. Vui lòng kiểm tra cấu hình mô hình của bạn.",
+		"invalidResponse": "Phản hồi không hợp lệ từ dịch vụ embedder. Vui lòng kiểm tra cấu hình của bạn."
 	}
 }
--- a/src/i18n/locales/zh-CN/common.json
+++ b/src/i18n/locales/zh-CN/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "您确定要删除此配置文件吗？",
 		"delete_custom_mode_with_rules": "您确定要删除此 {scope} 模式吗？\n\n这也将删除位于以下位置的关联规则文件夹：\n{rulesFolderPath}",
 		"delete_message": "您想删除什么？",
-		"just_this_message": "仅此消息",
-		"this_and_subsequent": "此消息及所有后续消息"
+		"edit_message": "删除此消息后的所有消息？",
+		"delete_just_this_message": "仅此消息",
+		"edit_just_this_message": "不，仅编辑此消息",
+		"delete_this_and_subsequent": "此消息及所有后续消息",
+		"edit_this_and_delete_subsequent": "是"
 	},
 	"errors": {
 		"invalid_mcp_config": "项目MCP配置格式无效",
@ -113,6 +116,11 @@
 		"remove": "删除",
 		"keep": "保留"
 	},
+	"buttons": {
+		"save": "保存",
+		"cancel": "取消",
+		"edit": "编辑"
+	},
 	"tasks": {
 		"canceled": "任务错误：它已被用户停止并取消。",
 		"deleted": "任务失败：它已被用户停止并删除。",
--- a/src/i18n/locales/zh-CN/embeddings.json
+++ b/src/i18n/locales/zh-CN/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "无法读取错误内容",
 		"requestFailed": "Ollama API 请求失败，状态码 {{status}} {{statusText}}：{{errorBody}}",
 		"invalidResponseStructure": "Ollama API 响应结构无效：未找到 \"embeddings\" 数组或不是数组。",
-		"embeddingFailed": "Ollama 嵌入失败：{{message}}"
+		"embeddingFailed": "Ollama 嵌入失败：{{message}}",
+		"serviceNotRunning": "Ollama 服务未在 {{baseUrl}} 运行",
+		"serviceUnavailable": "Ollama 服务不可用（状态：{{status}}）",
+		"modelNotFound": "未找到 Ollama 模型：{{modelId}}",
+		"modelNotEmbeddingCapable": "Ollama 模型不具备嵌入能力：{{modelId}}",
+		"hostNotFound": "未找到 Ollama 主机：{{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "处理文件 {{filePath}} 时出现未知错误",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "连接 Qdrant 向量数据库失败。请确保 Qdrant 正在运行并可在 {{qdrantUrl}} 访问。错误：{{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "身份验证失败。请在设置中检查您的 API 密钥。",
+		"connectionFailed": "连接嵌入器服务失败。请检查您的连接设置并确保服务正在运行。",
+		"modelNotAvailable": "指定的模型不可用。请检查您的模型配置。",
+		"configurationError": "嵌入器配置无效。请查看您的设置。",
+		"serviceUnavailable": "嵌入器服务不可用。请确保它正在运行且可访问。",
+		"invalidEndpoint": "API 端点无效。请检查您的 URL 配置。",
+		"invalidEmbedderConfig": "嵌入器配置无效。请检查您的设置。",
+		"invalidApiKey": "API 密钥无效。请检查您的 API 密钥配置。",
+		"invalidBaseUrl": "基础 URL 无效。请检查您的 URL 配置。",
+		"invalidModel": "模型无效。请检查您的模型配置。",
+		"invalidResponse": "嵌入服务响应无效。请检查您的配置。"
 	}
 }
--- a/src/i18n/locales/zh-TW/common.json
+++ b/src/i18n/locales/zh-TW/common.json
@ -19,8 +19,11 @@
 		"delete_config_profile": "您確定要刪除此設定檔案嗎？",
 		"delete_custom_mode_with_rules": "您確定要刪除此 {scope} 模式嗎？\n\n這也將刪除位於以下位置的關聯規則資料夾：\n{rulesFolderPath}",
 		"delete_message": "您想刪除哪些內容？",
-		"just_this_message": "僅這則訊息",
-		"this_and_subsequent": "這則訊息及所有後續訊息"
+		"edit_message": "刪除此訊息後的所有訊息？",
+		"delete_just_this_message": "僅這則訊息",
+		"edit_just_this_message": "否，僅編輯此訊息",
+		"delete_this_and_subsequent": "這則訊息及所有後續訊息",
+		"edit_this_and_delete_subsequent": "是"
 	},
 	"errors": {
 		"invalid_data_uri": "資料 URI 格式無效",
@ -108,6 +111,11 @@
 		"remove": "刪除",
 		"keep": "保留"
 	},
+	"buttons": {
+		"save": "儲存",
+		"cancel": "取消",
+		"edit": "編輯"
+	},
 	"tasks": {
 		"canceled": "工作錯誤：它已被使用者停止並取消。",
 		"deleted": "工作失敗：它已被使用者停止並刪除。",
--- a/src/i18n/locales/zh-TW/embeddings.json
+++ b/src/i18n/locales/zh-TW/embeddings.json
@ -10,7 +10,12 @@
 		"couldNotReadErrorBody": "無法讀取錯誤內容",
 		"requestFailed": "Ollama API 請求失敗，狀態碼 {{status}} {{statusText}}：{{errorBody}}",
 		"invalidResponseStructure": "Ollama API 回應結構無效：未找到 \"embeddings\" 陣列或不是陣列。",
-		"embeddingFailed": "Ollama 內嵌失敗：{{message}}"
+		"embeddingFailed": "Ollama 內嵌失敗：{{message}}",
+		"serviceNotRunning": "Ollama 服務未在 {{baseUrl}} 執行",
+		"serviceUnavailable": "Ollama 服務不可用（狀態：{{status}}）",
+		"modelNotFound": "找不到 Ollama 模型：{{modelId}}",
+		"modelNotEmbeddingCapable": "Ollama 模型不具備內嵌能力：{{modelId}}",
+		"hostNotFound": "找不到 Ollama 主機：{{baseUrl}}"
 	},
 	"scanner": {
 		"unknownErrorProcessingFile": "處理檔案 {{filePath}} 時發生未知錯誤",
@ -19,5 +24,18 @@
 	},
 	"vectorStore": {
 		"qdrantConnectionFailed": "連接 Qdrant 向量資料庫失敗。請確保 Qdrant 正在執行並可在 {{qdrantUrl}} 存取。錯誤：{{errorMessage}}"
+	},
+	"validation": {
+		"authenticationFailed": "驗證失敗。請在設定中檢查您的 API 金鑰。",
+		"connectionFailed": "連線至內嵌服務失敗。請檢查您的連線設定並確保服務正在執行。",
+		"modelNotAvailable": "指定的模型不可用。請檢查您的模型組態。",
+		"configurationError": "無效的內嵌程式組態。請檢閱您的設定。",
+		"serviceUnavailable": "內嵌服務不可用。請確保它正在執行且可存取。",
+		"invalidEndpoint": "無效的 API 端點。請檢查您的 URL 組態。",
+		"invalidEmbedderConfig": "無效的內嵌程式組態。請檢查您的設定。",
+		"invalidApiKey": "無效的 API 金鑰。請檢查您的 API 金鑰組態。",
+		"invalidBaseUrl": "無效的基礎 URL。請檢查您的 URL 組態。",
+		"invalidModel": "無效的模型。請檢查您的模型組態。",
+		"invalidResponse": "內嵌服務回應無效。請檢查您的組態。"
 	}
 }
--- a/src/package.json
+++ b/src/package.json
@ -353,7 +353,7 @@
 		"vsix": "mkdirp ../bin && vsce package --no-dependencies --out ../bin",
 		"publish:marketplace": "vsce publish --no-dependencies && ovsx publish --no-dependencies",
 		"watch:bundle": "pnpm bundle --watch",
-		"watch:tsc": "tsc --noEmit --watch --project tsconfig.json",
+		"watch:tsc": "cd .. && tsc --noEmit --watch --project src/tsconfig.json",
 		"clean": "rimraf README.md CHANGELOG.md LICENSE dist mock .turbo"
 	},
 	"dependencies": {
--- a/src/services/code-index/tests/manager.spec.ts
+++ b/src/services/code-index/tests/manager.spec.ts
@ -1,3 +1,7 @@
+import { CodeIndexManager } from "../manager"
+import { CodeIndexServiceFactory } from "../service-factory"
+import type { MockedClass } from "vitest"
+
 // Mock vscode module
 vi.mock("vscode", () => ({
 	workspace: {
@ -21,10 +25,12 @@ vi.mock("../state-manager", () => ({
 		onProgressUpdate: vi.fn(),
 		getCurrentStatus: vi.fn(),
 		dispose: vi.fn(),
+		setSystemState: vi.fn(),
 	})),
 }))

-import { CodeIndexManager } from "../manager"
+vi.mock("../service-factory")
+const MockedCodeIndexServiceFactory = CodeIndexServiceFactory as MockedClass<typeof CodeIndexServiceFactory>

 describe("CodeIndexManager - handleSettingsChange regression", () => {
 	let mockContext: any
@ -72,13 +78,63 @@ describe("CodeIndexManager - handleSettingsChange regression", () => {
 			// Mock a minimal config manager that simulates first-time configuration
 			const mockConfigManager = {
 				loadConfiguration: vi.fn().mockResolvedValue({ requiresRestart: true }),
+				isFeatureConfigured: true,
+				isFeatureEnabled: true,
+				getConfig: vi.fn().mockReturnValue({
+					isEnabled: true,
+					isConfigured: true,
+					embedderProvider: "openai",
+					modelId: "text-embedding-3-small",
+					openAiOptions: { openAiNativeApiKey: "test-key" },
+					qdrantUrl: "http://localhost:6333",
+					qdrantApiKey: "test-key",
+					searchMinScore: 0.4,
+				}),
 			}
 			;(manager as any)._configManager = mockConfigManager

+			// Mock cache manager
+			const mockCacheManager = {
+				initialize: vi.fn(),
+				clearCacheFile: vi.fn(),
+			}
+			;(manager as any)._cacheManager = mockCacheManager
+
 			// Mock the feature state to simulate valid configuration that would normally trigger restart
 			vi.spyOn(manager, "isFeatureEnabled", "get").mockReturnValue(true)
 			vi.spyOn(manager, "isFeatureConfigured", "get").mockReturnValue(true)

+			// Mock service factory to handle _recreateServices call
+			const mockServiceFactoryInstance = {
+				configManager: mockConfigManager,
+				workspacePath: "/test/workspace",
+				cacheManager: mockCacheManager,
+				createEmbedder: vi.fn().mockReturnValue({ embedderInfo: { name: "openai" } }),
+				createVectorStore: vi.fn().mockReturnValue({}),
+				createDirectoryScanner: vi.fn().mockReturnValue({}),
+				createFileWatcher: vi.fn().mockReturnValue({
+					onDidStartBatchProcessing: vi.fn(),
+					onBatchProgressUpdate: vi.fn(),
+					watch: vi.fn(),
+					stopWatcher: vi.fn(),
+					dispose: vi.fn(),
+				}),
+				createServices: vi.fn().mockReturnValue({
+					embedder: { embedderInfo: { name: "openai" } },
+					vectorStore: {},
+					scanner: {},
+					fileWatcher: {
+						onDidStartBatchProcessing: vi.fn(),
+						onBatchProgressUpdate: vi.fn(),
+						watch: vi.fn(),
+						stopWatcher: vi.fn(),
+						dispose: vi.fn(),
+					},
+				}),
+				validateEmbedder: vi.fn().mockResolvedValue({ valid: true }),
+			}
+			MockedCodeIndexServiceFactory.mockImplementation(() => mockServiceFactoryInstance as any)
+
 			// The key test: this should NOT throw "CodeIndexManager not initialized" error
 			await expect(manager.handleSettingsChange()).resolves.not.toThrow()

@ -105,29 +161,65 @@ describe("CodeIndexManager - handleSettingsChange regression", () => {
 			}
 			;(manager as any)._configManager = mockConfigManager

+			// Mock cache manager
+			const mockCacheManager = {
+				initialize: vi.fn(),
+				clearCacheFile: vi.fn(),
+			}
+			;(manager as any)._cacheManager = mockCacheManager
+
 			// Simulate an initialized manager by setting the required properties
 			;(manager as any)._orchestrator = { stopWatcher: vi.fn() }
 			;(manager as any)._searchService = {}
-			;(manager as any)._cacheManager = {}

 			// Verify manager is considered initialized
 			expect(manager.isInitialized).toBe(true)

-			// Mock the methods that would be called during restart
-			const recreateServicesSpy = vi.spyOn(manager as any, "_recreateServices").mockImplementation(() => {})
-			const startIndexingSpy = vi.spyOn(manager, "startIndexing").mockResolvedValue()
-
 			// Mock the feature state
 			vi.spyOn(manager, "isFeatureEnabled", "get").mockReturnValue(true)
 			vi.spyOn(manager, "isFeatureConfigured", "get").mockReturnValue(true)

+			// Mock service factory to handle _recreateServices call
+			const mockServiceFactoryInstance = {
+				configManager: mockConfigManager,
+				workspacePath: "/test/workspace",
+				cacheManager: mockCacheManager,
+				createEmbedder: vi.fn().mockReturnValue({ embedderInfo: { name: "openai" } }),
+				createVectorStore: vi.fn().mockReturnValue({}),
+				createDirectoryScanner: vi.fn().mockReturnValue({}),
+				createFileWatcher: vi.fn().mockReturnValue({
+					onDidStartBatchProcessing: vi.fn(),
+					onBatchProgressUpdate: vi.fn(),
+					watch: vi.fn(),
+					stopWatcher: vi.fn(),
+					dispose: vi.fn(),
+				}),
+				createServices: vi.fn().mockReturnValue({
+					embedder: { embedderInfo: { name: "openai" } },
+					vectorStore: {},
+					scanner: {},
+					fileWatcher: {
+						onDidStartBatchProcessing: vi.fn(),
+						onBatchProgressUpdate: vi.fn(),
+						watch: vi.fn(),
+						stopWatcher: vi.fn(),
+						dispose: vi.fn(),
+					},
+				}),
+				validateEmbedder: vi.fn().mockResolvedValue({ valid: true }),
+			}
+			MockedCodeIndexServiceFactory.mockImplementation(() => mockServiceFactoryInstance as any)
+
+			// Mock the methods that would be called during restart
+			const recreateServicesSpy = vi.spyOn(manager as any, "_recreateServices")
+
 			await manager.handleSettingsChange()

 			// Verify that the restart sequence was called
 			expect(mockConfigManager.loadConfiguration).toHaveBeenCalled()
-			// stopWatcher is called inside _recreateServices, which we mocked
+			// _recreateServices should be called when requiresRestart is true
 			expect(recreateServicesSpy).toHaveBeenCalled()
-			expect(startIndexingSpy).toHaveBeenCalled()
+			// Note: startIndexing is NOT called by handleSettingsChange - it's only called by initialize()
 		})

 		it("should handle case when config manager is not set", async () => {
@ -138,4 +230,135 @@ describe("CodeIndexManager - handleSettingsChange regression", () => {
 			await expect(manager.handleSettingsChange()).resolves.not.toThrow()
 		})
 	})
+
+	describe("embedder validation integration", () => {
+		let mockServiceFactoryInstance: any
+		let mockStateManager: any
+		let mockEmbedder: any
+		let mockVectorStore: any
+		let mockScanner: any
+		let mockFileWatcher: any
+
+		beforeEach(() => {
+			// Mock service factory objects
+			mockEmbedder = { embedderInfo: { name: "openai" } }
+			mockVectorStore = {}
+			mockScanner = {}
+			mockFileWatcher = {
+				onDidStartBatchProcessing: vi.fn(),
+				onBatchProgressUpdate: vi.fn(),
+				watch: vi.fn(),
+				stopWatcher: vi.fn(),
+				dispose: vi.fn(),
+			}
+
+			// Mock service factory instance
+			mockServiceFactoryInstance = {
+				createServices: vi.fn().mockReturnValue({
+					embedder: mockEmbedder,
+					vectorStore: mockVectorStore,
+					scanner: mockScanner,
+					fileWatcher: mockFileWatcher,
+				}),
+				validateEmbedder: vi.fn(),
+			}
+
+			// Mock the ServiceFactory constructor
+			MockedCodeIndexServiceFactory.mockImplementation(() => mockServiceFactoryInstance)
+
+			// Mock state manager methods directly on the existing instance
+			mockStateManager = (manager as any)._stateManager
+			mockStateManager.setSystemState = vi.fn()
+
+			// Mock config manager
+			const mockConfigManager = {
+				loadConfiguration: vitest.fn().mockResolvedValue({ requiresRestart: false }),
+				isFeatureConfigured: true,
+				isFeatureEnabled: true,
+				getConfig: vitest.fn().mockReturnValue({
+					isEnabled: true,
+					isConfigured: true,
+					embedderProvider: "openai",
+					modelId: "text-embedding-3-small",
+					openAiOptions: { openAiNativeApiKey: "test-key" },
+					qdrantUrl: "http://localhost:6333",
+					qdrantApiKey: "test-key",
+					searchMinScore: 0.4,
+				}),
+			}
+			;(manager as any)._configManager = mockConfigManager
+		})
+
+		it("should validate embedder during _recreateServices when validation succeeds", async () => {
+			// Arrange
+			mockServiceFactoryInstance.validateEmbedder.mockResolvedValue({ valid: true })
+
+			// Act - directly call the private method for testing
+			await (manager as any)._recreateServices()
+
+			// Assert
+			expect(mockServiceFactoryInstance.createServices).toHaveBeenCalled()
+			const createdEmbedder = mockServiceFactoryInstance.createServices.mock.results[0].value.embedder
+			expect(mockServiceFactoryInstance.validateEmbedder).toHaveBeenCalledWith(createdEmbedder)
+			expect(mockStateManager.setSystemState).not.toHaveBeenCalledWith("Error", expect.any(String))
+		})
+
+		it("should set error state when embedder validation fails", async () => {
+			// Arrange
+			mockServiceFactoryInstance.validateEmbedder.mockResolvedValue({
+				valid: false,
+				error: "embeddings:validation.authenticationFailed",
+			})
+
+			// Act & Assert
+			await expect((manager as any)._recreateServices()).rejects.toThrow(
+				"embeddings:validation.authenticationFailed",
+			)
+
+			// Assert other expectations
+			expect(mockServiceFactoryInstance.createServices).toHaveBeenCalled()
+			const createdEmbedder = mockServiceFactoryInstance.createServices.mock.results[0].value.embedder
+			expect(mockServiceFactoryInstance.validateEmbedder).toHaveBeenCalledWith(createdEmbedder)
+			expect(mockStateManager.setSystemState).toHaveBeenCalledWith(
+				"Error",
+				"embeddings:validation.authenticationFailed",
+			)
+		})
+
+		it("should set generic error state when embedder validation throws", async () => {
+			// Arrange
+			// Since the real service factory catches exceptions, we should mock it to resolve with an error
+			mockServiceFactoryInstance.validateEmbedder.mockResolvedValue({
+				valid: false,
+				error: "embeddings:validation.configurationError",
+			})
+
+			// Act & Assert
+			await expect((manager as any)._recreateServices()).rejects.toThrow(
+				"embeddings:validation.configurationError",
+			)
+
+			// Assert other expectations
+			expect(mockServiceFactoryInstance.createServices).toHaveBeenCalled()
+			const createdEmbedder = mockServiceFactoryInstance.createServices.mock.results[0].value.embedder
+			expect(mockServiceFactoryInstance.validateEmbedder).toHaveBeenCalledWith(createdEmbedder)
+			expect(mockStateManager.setSystemState).toHaveBeenCalledWith(
+				"Error",
+				"embeddings:validation.configurationError",
+			)
+		})
+
+		it("should handle embedder creation failure", async () => {
+			// Arrange
+			mockServiceFactoryInstance.createServices.mockImplementation(() => {
+				throw new Error("Invalid configuration")
+			})
+
+			// Act & Assert - should throw the error
+			await expect((manager as any)._recreateServices()).rejects.toThrow("Invalid configuration")
+
+			// Should not attempt validation if embedder creation fails
+			expect(mockServiceFactoryInstance.validateEmbedder).not.toHaveBeenCalled()
+		})
+	})
 })
--- a/src/services/code-index/tests/service-factory.spec.ts
+++ b/src/services/code-index/tests/service-factory.spec.ts
@ -580,4 +580,187 @@ describe("CodeIndexServiceFactory", () => {
 			expect(() => factory.createVectorStore()).toThrow("Qdrant URL missing for vector store creation")
 		})
 	})
+
+	describe("validateEmbedder", () => {
+		let mockEmbedderInstance: any
+
+		beforeEach(() => {
+			mockEmbedderInstance = {
+				validateConfiguration: vitest.fn(),
+			}
+		})
+
+		it("should validate OpenAI embedder successfully", async () => {
+			// Arrange
+			const testConfig = {
+				embedderProvider: "openai",
+				modelId: "text-embedding-3-small",
+				openAiOptions: {
+					openAiNativeApiKey: "test-api-key",
+				},
+			}
+			mockConfigManager.getConfig.mockReturnValue(testConfig as any)
+			MockedOpenAiEmbedder.mockImplementation(() => mockEmbedderInstance)
+			mockEmbedderInstance.validateConfiguration.mockResolvedValue({ valid: true })
+
+			// Act
+			const embedder = factory.createEmbedder()
+			const result = await factory.validateEmbedder(embedder)
+
+			// Assert
+			expect(result).toEqual({ valid: true })
+			expect(mockEmbedderInstance.validateConfiguration).toHaveBeenCalled()
+		})
+
+		it("should return validation error from OpenAI embedder", async () => {
+			// Arrange
+			const testConfig = {
+				embedderProvider: "openai",
+				modelId: "text-embedding-3-small",
+				openAiOptions: {
+					openAiNativeApiKey: "invalid-key",
+				},
+			}
+			mockConfigManager.getConfig.mockReturnValue(testConfig as any)
+			MockedOpenAiEmbedder.mockImplementation(() => mockEmbedderInstance)
+			mockEmbedderInstance.validateConfiguration.mockResolvedValue({
+				valid: false,
+				error: "embeddings:validation.authenticationFailed",
+			})
+
+			// Act
+			const embedder = factory.createEmbedder()
+			const result = await factory.validateEmbedder(embedder)
+
+			// Assert
+			expect(result).toEqual({
+				valid: false,
+				error: "embeddings:validation.authenticationFailed",
+			})
+		})
+
+		it("should validate Ollama embedder successfully", async () => {
+			// Arrange
+			const testConfig = {
+				embedderProvider: "ollama",
+				modelId: "nomic-embed-text",
+				ollamaOptions: {
+					ollamaBaseUrl: "http://localhost:11434",
+				},
+			}
+			mockConfigManager.getConfig.mockReturnValue(testConfig as any)
+			MockedCodeIndexOllamaEmbedder.mockImplementation(() => mockEmbedderInstance)
+			mockEmbedderInstance.validateConfiguration.mockResolvedValue({ valid: true })
+
+			// Act
+			const embedder = factory.createEmbedder()
+			const result = await factory.validateEmbedder(embedder)
+
+			// Assert
+			expect(result).toEqual({ valid: true })
+			expect(mockEmbedderInstance.validateConfiguration).toHaveBeenCalled()
+		})
+
+		it("should validate OpenAI Compatible embedder successfully", async () => {
+			// Arrange
+			const testConfig = {
+				embedderProvider: "openai-compatible",
+				modelId: "custom-model",
+				openAiCompatibleOptions: {
+					baseUrl: "https://api.example.com/v1",
+					apiKey: "test-api-key",
+				},
+			}
+			mockConfigManager.getConfig.mockReturnValue(testConfig as any)
+			MockedOpenAICompatibleEmbedder.mockImplementation(() => mockEmbedderInstance)
+			mockEmbedderInstance.validateConfiguration.mockResolvedValue({ valid: true })
+
+			// Act
+			const embedder = factory.createEmbedder()
+			const result = await factory.validateEmbedder(embedder)
+
+			// Assert
+			expect(result).toEqual({ valid: true })
+			expect(mockEmbedderInstance.validateConfiguration).toHaveBeenCalled()
+		})
+
+		it("should validate Gemini embedder successfully", async () => {
+			// Arrange
+			const testConfig = {
+				embedderProvider: "gemini",
+				geminiOptions: {
+					apiKey: "test-gemini-api-key",
+				},
+			}
+			mockConfigManager.getConfig.mockReturnValue(testConfig as any)
+			MockedGeminiEmbedder.mockImplementation(() => mockEmbedderInstance)
+			mockEmbedderInstance.validateConfiguration.mockResolvedValue({ valid: true })
+
+			// Act
+			const embedder = factory.createEmbedder()
+			const result = await factory.validateEmbedder(embedder)
+
+			// Assert
+			expect(result).toEqual({ valid: true })
+			expect(mockEmbedderInstance.validateConfiguration).toHaveBeenCalled()
+		})
+
+		it("should handle validation exceptions", async () => {
+			// Arrange
+			const testConfig = {
+				embedderProvider: "openai",
+				modelId: "text-embedding-3-small",
+				openAiOptions: {
+					openAiNativeApiKey: "test-api-key",
+				},
+			}
+			mockConfigManager.getConfig.mockReturnValue(testConfig as any)
+			MockedOpenAiEmbedder.mockImplementation(() => mockEmbedderInstance)
+			const networkError = new Error("Network error")
+			mockEmbedderInstance.validateConfiguration.mockRejectedValue(networkError)
+
+			// Act
+			const embedder = factory.createEmbedder()
+			const result = await factory.validateEmbedder(embedder)
+
+			// Assert
+			expect(result).toEqual({
+				valid: false,
+				error: "Network error",
+			})
+			expect(mockEmbedderInstance.validateConfiguration).toHaveBeenCalled()
+		})
+
+		it("should return error for invalid embedder configuration", async () => {
+			// Arrange
+			const testConfig = {
+				embedderProvider: "openai",
+				modelId: "text-embedding-3-small",
+				openAiOptions: {
+					openAiNativeApiKey: undefined, // Missing API key
+				},
+			}
+			mockConfigManager.getConfig.mockReturnValue(testConfig as any)
+
+			// Act & Assert
+			// This should throw when trying to create the embedder
+			await expect(async () => {
+				const embedder = factory.createEmbedder()
+				await factory.validateEmbedder(embedder)
+			}).rejects.toThrow("OpenAI configuration missing for embedder creation")
+		})
+
+		it("should return error for unknown embedder provider", async () => {
+			// Arrange
+			const testConfig = {
+				embedderProvider: "unknown-provider",
+				modelId: "some-model",
+			}
+			mockConfigManager.getConfig.mockReturnValue(testConfig as any)
+
+			// Act & Assert
+			// This should throw when trying to create the embedder
+			expect(() => factory.createEmbedder()).toThrow("Invalid embedder type configured: unknown-provider")
+		})
+	})
 })
--- a/src/services/code-index/embedders/tests/gemini.spec.ts
+++ b/src/services/code-index/embedders/tests/gemini.spec.ts
@ -55,4 +55,54 @@ describe("GeminiEmbedder", () => {
 			expect(GeminiEmbedder.dimension).toBe(768)
 		})
 	})
+
+	describe("validateConfiguration", () => {
+		let mockValidateConfiguration: any
+
+		beforeEach(() => {
+			mockValidateConfiguration = vitest.fn()
+			MockedOpenAICompatibleEmbedder.prototype.validateConfiguration = mockValidateConfiguration
+		})
+
+		it("should delegate validation to OpenAICompatibleEmbedder", async () => {
+			// Arrange
+			embedder = new GeminiEmbedder("test-api-key")
+			mockValidateConfiguration.mockResolvedValue({ valid: true })
+
+			// Act
+			const result = await embedder.validateConfiguration()
+
+			// Assert
+			expect(mockValidateConfiguration).toHaveBeenCalled()
+			expect(result).toEqual({ valid: true })
+		})
+
+		it("should pass through validation errors from OpenAICompatibleEmbedder", async () => {
+			// Arrange
+			embedder = new GeminiEmbedder("test-api-key")
+			mockValidateConfiguration.mockResolvedValue({
+				valid: false,
+				error: "embeddings:validation.authenticationFailed",
+			})
+
+			// Act
+			const result = await embedder.validateConfiguration()
+
+			// Assert
+			expect(mockValidateConfiguration).toHaveBeenCalled()
+			expect(result).toEqual({
+				valid: false,
+				error: "embeddings:validation.authenticationFailed",
+			})
+		})
+
+		it("should handle validation exceptions", async () => {
+			// Arrange
+			embedder = new GeminiEmbedder("test-api-key")
+			mockValidateConfiguration.mockRejectedValue(new Error("Validation failed"))
+
+			// Act & Assert
+			await expect(embedder.validateConfiguration()).rejects.toThrow("Validation failed")
+		})
+	})
 })
--- a/src/services/code-index/embedders/tests/ollama.spec.ts
+++ b/src/services/code-index/embedders/tests/ollama.spec.ts
@ -0,0 +1,238 @@
+import { vitest, describe, it, expect, beforeEach, afterEach } from "vitest"
+import type { MockedFunction } from "vitest"
+import { CodeIndexOllamaEmbedder } from "../ollama"
+
+// Mock fetch
+global.fetch = vitest.fn() as MockedFunction<typeof fetch>
+
+// Mock i18n
+vitest.mock("../../../../i18n", () => ({
+	t: (key: string, params?: Record<string, any>) => {
+		const translations: Record<string, string> = {
+			"embeddings:validation.serviceUnavailable":
+				"The embedder service is not available. Please ensure it is running and accessible.",
+			"embeddings:validation.modelNotAvailable":
+				"The specified model is not available. Please check your model configuration.",
+			"embeddings:validation.connectionFailed":
+				"Failed to connect to the embedder service. Please check your connection settings and ensure the service is running.",
+			"embeddings:validation.configurationError": "Invalid embedder configuration. Please review your settings.",
+			"embeddings:errors.ollama.serviceNotRunning":
+				"Ollama service is not running at {{baseUrl}}. Please start Ollama first.",
+			"embeddings:errors.ollama.serviceUnavailable":
+				"Ollama service is unavailable at {{baseUrl}}. HTTP status: {{status}}",
+			"embeddings:errors.ollama.modelNotFound":
+				"Model '{{model}}' not found. Available models: {{availableModels}}",
+			"embeddings:errors.ollama.modelNotEmbedding": "Model '{{model}}' is not embedding capable",
+			"embeddings:errors.ollama.hostNotFound": "Ollama host not found: {{baseUrl}}",
+			"embeddings:errors.ollama.connectionTimeout": "Connection to Ollama timed out at {{baseUrl}}",
+		}
+		// Handle parameter substitution
+		let result = translations[key] || key
+		if (params) {
+			Object.entries(params).forEach(([param, value]) => {
+				result = result.replace(new RegExp(`{{${param}}}`, "g"), String(value))
+			})
+		}
+		return result
+	},
+}))
+
+// Mock console methods
+const consoleMocks = {
+	error: vitest.spyOn(console, "error").mockImplementation(() => {}),
+}
+
+describe("CodeIndexOllamaEmbedder", () => {
+	let embedder: CodeIndexOllamaEmbedder
+	let mockFetch: MockedFunction<typeof fetch>
+
+	beforeEach(() => {
+		vitest.clearAllMocks()
+		consoleMocks.error.mockClear()
+
+		mockFetch = global.fetch as MockedFunction<typeof fetch>
+
+		embedder = new CodeIndexOllamaEmbedder({
+			ollamaModelId: "nomic-embed-text",
+			ollamaBaseUrl: "http://localhost:11434",
+		})
+	})
+
+	afterEach(() => {
+		vitest.clearAllMocks()
+	})
+
+	describe("constructor", () => {
+		it("should initialize with provided options", () => {
+			expect(embedder.embedderInfo.name).toBe("ollama")
+		})
+
+		it("should use default values when not provided", () => {
+			const embedderWithDefaults = new CodeIndexOllamaEmbedder({})
+			expect(embedderWithDefaults.embedderInfo.name).toBe("ollama")
+		})
+	})
+
+	describe("validateConfiguration", () => {
+		it("should validate successfully when service is available and model exists", async () => {
+			// Mock successful /api/tags call
+			mockFetch.mockImplementationOnce(() =>
+				Promise.resolve({
+					ok: true,
+					status: 200,
+					json: () =>
+						Promise.resolve({
+							models: [{ name: "nomic-embed-text:latest" }, { name: "llama2:latest" }],
+						}),
+				} as Response),
+			)
+
+			// Mock successful /api/embed test call
+			mockFetch.mockImplementationOnce(() =>
+				Promise.resolve({
+					ok: true,
+					status: 200,
+					json: () =>
+						Promise.resolve({
+							embeddings: [[0.1, 0.2, 0.3]],
+						}),
+				} as Response),
+			)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(true)
+			expect(result.error).toBeUndefined()
+			expect(mockFetch).toHaveBeenCalledTimes(2)
+
+			// Check first call (GET /api/tags)
+			const firstCall = mockFetch.mock.calls[0]
+			expect(firstCall[0]).toBe("http://localhost:11434/api/tags")
+			expect(firstCall[1]?.method).toBe("GET")
+			expect(firstCall[1]?.headers).toEqual({ "Content-Type": "application/json" })
+			expect(firstCall[1]?.signal).toBeDefined() // AbortSignal for timeout
+
+			// Check second call (POST /api/embed)
+			const secondCall = mockFetch.mock.calls[1]
+			expect(secondCall[0]).toBe("http://localhost:11434/api/embed")
+			expect(secondCall[1]?.method).toBe("POST")
+			expect(secondCall[1]?.headers).toEqual({ "Content-Type": "application/json" })
+			expect(secondCall[1]?.body).toBe(JSON.stringify({ model: "nomic-embed-text", input: ["test"] }))
+			expect(secondCall[1]?.signal).toBeDefined() // AbortSignal for timeout
+		})
+
+		it("should fail validation when service is not available", async () => {
+			mockFetch.mockRejectedValueOnce(new Error("ECONNREFUSED"))
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("Connection to Ollama timed out at http://localhost:11434")
+		})
+
+		it("should fail validation when tags endpoint returns 404", async () => {
+			mockFetch.mockImplementationOnce(() =>
+				Promise.resolve({
+					ok: false,
+					status: 404,
+				} as Response),
+			)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe(
+				"Ollama service is not running at http://localhost:11434. Please start Ollama first.",
+			)
+		})
+
+		it("should fail validation when tags endpoint returns other error", async () => {
+			mockFetch.mockImplementationOnce(() =>
+				Promise.resolve({
+					ok: false,
+					status: 500,
+				} as Response),
+			)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("Ollama service is unavailable at http://localhost:11434. HTTP status: 500")
+		})
+
+		it("should fail validation when model does not exist", async () => {
+			// Mock successful /api/tags call with different models
+			mockFetch.mockImplementationOnce(() =>
+				Promise.resolve({
+					ok: true,
+					status: 200,
+					json: () =>
+						Promise.resolve({
+							models: [{ name: "llama2:latest" }, { name: "mistral:latest" }],
+						}),
+				} as Response),
+			)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe(
+				"Model 'nomic-embed-text' not found. Available models: llama2:latest, mistral:latest",
+			)
+		})
+
+		it("should fail validation when model exists but doesn't support embeddings", async () => {
+			// Mock successful /api/tags call
+			mockFetch.mockImplementationOnce(() =>
+				Promise.resolve({
+					ok: true,
+					status: 200,
+					json: () =>
+						Promise.resolve({
+							models: [{ name: "nomic-embed-text" }],
+						}),
+				} as Response),
+			)
+
+			// Mock failed /api/embed test call
+			mockFetch.mockImplementationOnce(() =>
+				Promise.resolve({
+					ok: false,
+					status: 400,
+				} as Response),
+			)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("Model 'nomic-embed-text' is not embedding capable")
+		})
+
+		it("should handle ECONNREFUSED errors", async () => {
+			mockFetch.mockRejectedValueOnce(new Error("ECONNREFUSED"))
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("Connection to Ollama timed out at http://localhost:11434")
+		})
+
+		it("should handle ENOTFOUND errors", async () => {
+			mockFetch.mockRejectedValueOnce(new Error("ENOTFOUND"))
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("Ollama host not found: http://localhost:11434")
+		})
+
+		it("should handle generic network errors", async () => {
+			mockFetch.mockRejectedValueOnce(new Error("Network timeout"))
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("Network timeout")
+		})
+	})
+})
--- a/src/services/code-index/embedders/tests/openai-compatible.spec.ts
+++ b/src/services/code-index/embedders/tests/openai-compatible.spec.ts
@ -882,4 +882,133 @@ describe("OpenAICompatibleEmbedder", () => {
 			expect(mockCreate).toHaveBeenCalled()
 		})
 	})
+
+	describe("validateConfiguration", () => {
+		let embedder: OpenAICompatibleEmbedder
+		let mockFetch: MockedFunction<typeof fetch>
+
+		beforeEach(() => {
+			vitest.clearAllMocks()
+			// Reset and re-assign the global fetch mock
+			global.fetch = vitest.fn()
+			mockFetch = global.fetch as MockedFunction<typeof fetch>
+		})
+
+		it("should validate successfully with valid configuration and base URL", async () => {
+			embedder = new OpenAICompatibleEmbedder(testBaseUrl, testApiKey, testModelId)
+
+			const mockResponse = {
+				data: [{ embedding: [0.1, 0.2, 0.3] }],
+				usage: { prompt_tokens: 2, total_tokens: 2 },
+			}
+			mockEmbeddingsCreate.mockResolvedValue(mockResponse)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(true)
+			expect(result.error).toBeUndefined()
+			expect(mockEmbeddingsCreate).toHaveBeenCalledWith({
+				input: ["test"],
+				model: testModelId,
+				encoding_format: "base64",
+			})
+		})
+
+		it("should validate successfully with full endpoint URL", async () => {
+			const fullUrl = "https://api.example.com/v1/embeddings"
+			embedder = new OpenAICompatibleEmbedder(fullUrl, testApiKey, testModelId)
+
+			mockFetch.mockResolvedValueOnce({
+				ok: true,
+				status: 200,
+				json: async () => ({
+					data: [{ embedding: [0.1, 0.2, 0.3] }],
+					usage: { prompt_tokens: 2, total_tokens: 2 },
+				}),
+				text: async () => "",
+			} as any)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(true)
+			expect(result.error).toBeUndefined()
+			expect(mockFetch).toHaveBeenCalledWith(
+				fullUrl,
+				expect.objectContaining({
+					method: "POST",
+					headers: expect.objectContaining({
+						Authorization: `Bearer ${testApiKey}`,
+					}),
+				}),
+			)
+		})
+
+		it("should fail validation with authentication error", async () => {
+			embedder = new OpenAICompatibleEmbedder(testBaseUrl, testApiKey, testModelId)
+
+			const authError = new Error("Invalid API key")
+			;(authError as any).status = 401
+			mockEmbeddingsCreate.mockRejectedValue(authError)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("embeddings:validation.authenticationFailed")
+		})
+
+		it("should fail validation with connection error", async () => {
+			embedder = new OpenAICompatibleEmbedder(testBaseUrl, testApiKey, testModelId)
+
+			const connectionError = new Error("ECONNREFUSED")
+			mockEmbeddingsCreate.mockRejectedValue(connectionError)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("embeddings:validation.connectionFailed")
+		})
+
+		it("should fail validation with invalid endpoint for full URL", async () => {
+			const fullUrl = "https://api.example.com/v1/embeddings"
+			embedder = new OpenAICompatibleEmbedder(fullUrl, testApiKey, testModelId)
+
+			mockFetch.mockResolvedValueOnce({
+				ok: false,
+				status: 404,
+				json: async () => ({ error: "Not found" }),
+				text: async () => "Not found",
+			} as any)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("embeddings:validation.invalidEndpoint")
+		})
+
+		it("should fail validation with rate limit error", async () => {
+			embedder = new OpenAICompatibleEmbedder(testBaseUrl, testApiKey, testModelId)
+
+			const rateLimitError = new Error("Rate limit exceeded")
+			;(rateLimitError as any).status = 429
+			mockEmbeddingsCreate.mockRejectedValue(rateLimitError)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("embeddings:validation.serviceUnavailable")
+		})
+
+		it("should fail validation with generic error", async () => {
+			embedder = new OpenAICompatibleEmbedder(testBaseUrl, testApiKey, testModelId)
+
+			const genericError = new Error("Unknown error")
+			;(genericError as any).status = 500
+			mockEmbeddingsCreate.mockRejectedValue(genericError)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("embeddings:validation.configurationError")
+		})
+	})
 })
--- a/src/services/code-index/embedders/tests/openai.spec.ts
+++ b/src/services/code-index/embedders/tests/openai.spec.ts
@ -464,4 +464,66 @@ describe("OpenAiEmbedder", () => {
 			})
 		})
 	})
+
+	describe("validateConfiguration", () => {
+		it("should validate successfully with valid configuration", async () => {
+			const mockResponse = {
+				data: [{ embedding: [0.1, 0.2, 0.3] }],
+				usage: { prompt_tokens: 2, total_tokens: 2 },
+			}
+			mockEmbeddingsCreate.mockResolvedValue(mockResponse)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(true)
+			expect(result.error).toBeUndefined()
+			expect(mockEmbeddingsCreate).toHaveBeenCalledWith({
+				input: ["test"],
+				model: "text-embedding-3-small",
+			})
+		})
+
+		it("should fail validation with authentication error", async () => {
+			const authError = new Error("Invalid API key")
+			;(authError as any).status = 401
+			mockEmbeddingsCreate.mockRejectedValue(authError)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("embeddings:validation.authenticationFailed")
+		})
+
+		it("should fail validation with rate limit error", async () => {
+			const rateLimitError = new Error("Rate limit exceeded")
+			;(rateLimitError as any).status = 429
+			mockEmbeddingsCreate.mockRejectedValue(rateLimitError)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("embeddings:validation.serviceUnavailable")
+		})
+
+		it("should fail validation with connection error", async () => {
+			const connectionError = new Error("ECONNREFUSED")
+			mockEmbeddingsCreate.mockRejectedValue(connectionError)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("embeddings:validation.connectionFailed")
+		})
+
+		it("should fail validation with generic error", async () => {
+			const genericError = new Error("Unknown error")
+			;(genericError as any).status = 500
+			mockEmbeddingsCreate.mockRejectedValue(genericError)
+
+			const result = await embedder.validateConfiguration()
+
+			expect(result.valid).toBe(false)
+			expect(result.error).toBe("embeddings:validation.configurationError")
+		})
+	})
 })
--- a/src/services/code-index/embedders/gemini.ts
+++ b/src/services/code-index/embedders/gemini.ts
@ -46,6 +46,16 @@ export class GeminiEmbedder implements IEmbedder {
 		return this.openAICompatibleEmbedder.createEmbeddings(texts, GeminiEmbedder.GEMINI_MODEL)
 	}

+	/**
+	 * Validates the Gemini embedder configuration by delegating to the underlying OpenAI-compatible embedder
+	 * @returns Promise resolving to validation result with success status and optional error message
+	 */
+	async validateConfiguration(): Promise<{ valid: boolean; error?: string }> {
+		// Delegate validation to the OpenAI-compatible embedder
+		// The error messages will be specific to Gemini since we're using Gemini's base URL
+		return this.openAICompatibleEmbedder.validateConfiguration()
+	}
+
 	/**
 	 * Returns information about this embedder
 	 */
--- a/src/services/code-index/embedders/ollama.ts
+++ b/src/services/code-index/embedders/ollama.ts
@ -3,6 +3,7 @@ import { EmbedderInfo, EmbeddingResponse, IEmbedder } from "../interfaces"
 import { getModelQueryPrefix } from "../../../shared/embeddingModels"
 import { MAX_ITEM_TOKENS } from "../constants"
 import { t } from "../../../i18n"
+import { withValidationErrorHandling } from "../shared/validation-helpers"

 /**
 * Implements the IEmbedder interface using a local Ollama instance.
@ -101,6 +102,127 @@ export class CodeIndexOllamaEmbedder implements IEmbedder {
 		}
 	}

+	/**
+	 * Validates the Ollama embedder configuration by checking service availability and model existence
+	 * @returns Promise resolving to validation result with success status and optional error message
+	 */
+	async validateConfiguration(): Promise<{ valid: boolean; error?: string }> {
+		return withValidationErrorHandling(
+			async () => {
+				// First check if Ollama service is running by trying to list models
+				const modelsUrl = `${this.baseUrl}/api/tags`
+
+				// Add timeout to prevent indefinite hanging
+				const controller = new AbortController()
+				const timeoutId = setTimeout(() => controller.abort(), 5000) // 5 second timeout
+
+				const modelsResponse = await fetch(modelsUrl, {
+					method: "GET",
+					headers: {
+						"Content-Type": "application/json",
+					},
+					signal: controller.signal,
+				})
+				clearTimeout(timeoutId)
+
+				if (!modelsResponse.ok) {
+					if (modelsResponse.status === 404) {
+						return {
+							valid: false,
+							error: t("embeddings:errors.ollama.serviceNotRunning", { baseUrl: this.baseUrl }),
+						}
+					}
+					return {
+						valid: false,
+						error: t("embeddings:errors.ollama.serviceUnavailable", {
+							baseUrl: this.baseUrl,
+							status: modelsResponse.status,
+						}),
+					}
+				}
+
+				// Check if the specific model exists
+				const modelsData = await modelsResponse.json()
+				const models = modelsData.models || []
+
+				// Check both with and without :latest suffix
+				const modelExists = models.some((m: any) => {
+					const modelName = m.name || ""
+					return (
+						modelName === this.defaultModelId ||
+						modelName === `${this.defaultModelId}:latest` ||
+						modelName === this.defaultModelId.replace(":latest", "")
+					)
+				})
+
+				if (!modelExists) {
+					const availableModels = models.map((m: any) => m.name).join(", ")
+					return {
+						valid: false,
+						error: t("embeddings:errors.ollama.modelNotFound", {
+							model: this.defaultModelId,
+							availableModels,
+						}),
+					}
+				}
+
+				// Try a test embedding to ensure the model works for embeddings
+				const testUrl = `${this.baseUrl}/api/embed`
+
+				// Add timeout for test request too
+				const testController = new AbortController()
+				const testTimeoutId = setTimeout(() => testController.abort(), 5000)
+
+				const testResponse = await fetch(testUrl, {
+					method: "POST",
+					headers: {
+						"Content-Type": "application/json",
+					},
+					body: JSON.stringify({
+						model: this.defaultModelId,
+						input: ["test"],
+					}),
+					signal: testController.signal,
+				})
+				clearTimeout(testTimeoutId)
+
+				if (!testResponse.ok) {
+					return {
+						valid: false,
+						error: t("embeddings:errors.ollama.modelNotEmbedding", { model: this.defaultModelId }),
+					}
+				}
+
+				return { valid: true }
+			},
+			"ollama",
+			{
+				beforeStandardHandling: (error: any) => {
+					// Handle Ollama-specific connection errors
+					if (error?.message === "ECONNREFUSED") {
+						return {
+							valid: false,
+							error: t("embeddings:errors.ollama.connectionTimeout", { baseUrl: this.baseUrl }),
+						}
+					} else if (error?.message === "ENOTFOUND") {
+						return {
+							valid: false,
+							error: t("embeddings:errors.ollama.hostNotFound", { baseUrl: this.baseUrl }),
+						}
+					} else if (error?.name === "AbortError") {
+						// Handle timeout
+						return {
+							valid: false,
+							error: t("embeddings:errors.ollama.connectionTimeout", { baseUrl: this.baseUrl }),
+						}
+					}
+					// Let standard handling take over
+					return undefined
+				},
+			},
+		)
+	}
+
 	get embedderInfo(): EmbedderInfo {
 		return {
 			name: "ollama",
--- a/src/services/code-index/embedders/openai-compatible.ts
+++ b/src/services/code-index/embedders/openai-compatible.ts
@ -8,6 +8,7 @@ import {
 } from "../constants"
 import { getDefaultModelId, getModelQueryPrefix } from "../../../shared/embeddingModels"
 import { t } from "../../../i18n"
+import { withValidationErrorHandling, HttpError, formatEmbeddingError } from "../shared/validation-helpers"

 interface EmbeddingItem {
 	embedding: string | number[]
@ -26,12 +27,6 @@ interface OpenAIEmbeddingResponse {
 * OpenAI Compatible implementation of the embedder interface with batching and rate limiting.
 * This embedder allows using any OpenAI-compatible API endpoint by specifying a custom baseURL.
 */
-interface HttpError extends Error {
-	status?: number
-	response?: {
-		status?: number
-	}
-}

 export class OpenAICompatibleEmbedder implements IEmbedder {
 	private embeddingsClient: OpenAI
@ -201,14 +196,31 @@ export class OpenAICompatibleEmbedder implements IEmbedder {
 			}),
 		})

-		if (!response.ok) {
-			const errorText = await response.text()
-			const error = new Error(`HTTP ${response.status}: ${errorText}`) as HttpError
-			error.status = response.status
+		if (!response || !response.ok) {
+			const status = response?.status || 0
+			let errorText = "No response"
+			try {
+				if (response && typeof response.text === "function") {
+					errorText = await response.text()
+				} else if (response) {
+					errorText = `Error ${status}`
+				}
+			} catch {
+				// Ignore text parsing errors
+				errorText = `Error ${status}`
+			}
+			const error = new Error(`HTTP ${status}: ${errorText}`) as HttpError
+			error.status = status || response?.status || 0
 			throw error
 		}

-		return await response.json()
+		try {
+			return await response.json()
+		} catch (e) {
+			const error = new Error(`Failed to parse response JSON`) as HttpError
+			error.status = response.status
+			throw error
+		}
 	}

 	/**
@ -272,11 +284,11 @@ export class OpenAICompatibleEmbedder implements IEmbedder {
 					},
 				}
 			} catch (error) {
-				const httpError = error as HttpError
-				const isRateLimitError = httpError?.status === 429
 				const hasMoreAttempts = attempts < MAX_RETRIES - 1

-				if (isRateLimitError && hasMoreAttempts) {
+				// Check if it's a rate limit error
+				const httpError = error as HttpError
+				if (httpError?.status === 429 && hasMoreAttempts) {
 					const delayMs = INITIAL_DELAY_MS * Math.pow(2, attempts)
 					console.warn(
 						t("embeddings:rateLimitRetry", {
@ -292,37 +304,50 @@ export class OpenAICompatibleEmbedder implements IEmbedder {
 				// Log the error for debugging
 				console.error(`OpenAI Compatible embedder error (attempt ${attempts + 1}/${MAX_RETRIES}):`, error)

-				// Provide more context in the error message using robust error extraction
-				let errorMessage = t("embeddings:unknownError")
-				if (httpError?.message) {
-					errorMessage = httpError.message
-				} else if (typeof error === "string") {
-					errorMessage = error
-				} else if (error && typeof error === "object" && "toString" in error) {
-					try {
-						errorMessage = String(error)
-					} catch {
-						errorMessage = t("embeddings:unknownError")
-					}
-				}
-
-				const statusCode = httpError?.status || httpError?.response?.status
-
-				if (statusCode === 401) {
-					throw new Error(t("embeddings:authenticationFailed"))
-				} else if (statusCode) {
-					throw new Error(
-						t("embeddings:failedWithStatus", { attempts: MAX_RETRIES, statusCode, errorMessage }),
-					)
-				} else {
-					throw new Error(t("embeddings:failedWithError", { attempts: MAX_RETRIES, errorMessage }))
-				}
+				// Format and throw the error
+				throw formatEmbeddingError(error, MAX_RETRIES)
 			}
 		}

 		throw new Error(t("embeddings:failedMaxAttempts", { attempts: MAX_RETRIES }))
 	}

+	/**
+	 * Validates the OpenAI-compatible embedder configuration by testing endpoint connectivity and API key
+	 * @returns Promise resolving to validation result with success status and optional error message
+	 */
+	async validateConfiguration(): Promise<{ valid: boolean; error?: string }> {
+		return withValidationErrorHandling(async () => {
+			// Test with a minimal embedding request
+			const testTexts = ["test"]
+			const modelToUse = this.defaultModelId
+
+			let response: OpenAIEmbeddingResponse
+
+			if (this.isFullUrl) {
+				// Test direct HTTP request for full endpoint URLs
+				response = await this.makeDirectEmbeddingRequest(this.baseUrl, testTexts, modelToUse)
+			} else {
+				// Test using OpenAI SDK for base URLs
+				response = (await this.embeddingsClient.embeddings.create({
+					input: testTexts,
+					model: modelToUse,
+					encoding_format: "base64",
+				})) as OpenAIEmbeddingResponse
+			}
+
+			// Check if we got a valid response
+			if (!response?.data || response.data.length === 0) {
+				return {
+					valid: false,
+					error: "embeddings:validation.invalidResponse",
+				}
+			}
+
+			return { valid: true }
+		}, "openai-compatible")
+	}
+
 	/**
 	 * Returns information about this embedder
 	 */
--- a/src/services/code-index/embedders/openai.ts
+++ b/src/services/code-index/embedders/openai.ts
@ -10,6 +10,7 @@ import {
 } from "../constants"
 import { getModelQueryPrefix } from "../../../shared/embeddingModels"
 import { t } from "../../../i18n"
+import { withValidationErrorHandling, formatEmbeddingError, HttpError } from "../shared/validation-helpers"

 /**
 * OpenAI implementation of the embedder interface with batching and rate limiting
@ -138,10 +139,11 @@ export class OpenAiEmbedder extends OpenAiNativeHandler implements IEmbedder {
 					},
 				}
 			} catch (error: any) {
-				const isRateLimitError = error?.status === 429
 				const hasMoreAttempts = attempts < MAX_RETRIES - 1

-				if (isRateLimitError && hasMoreAttempts) {
+				// Check if it's a rate limit error
+				const httpError = error as HttpError
+				if (httpError?.status === 429 && hasMoreAttempts) {
 					const delayMs = INITIAL_DELAY_MS * Math.pow(2, attempts)
 					console.warn(
 						t("embeddings:rateLimitRetry", {
@ -157,37 +159,38 @@ export class OpenAiEmbedder extends OpenAiNativeHandler implements IEmbedder {
 				// Log the error for debugging
 				console.error(`OpenAI embedder error (attempt ${attempts + 1}/${MAX_RETRIES}):`, error)

-				// Provide more context in the error message using robust error extraction
-				let errorMessage = "Unknown error"
-				if (error?.message) {
-					errorMessage = error.message
-				} else if (typeof error === "string") {
-					errorMessage = error
-				} else if (error && typeof error.toString === "function") {
-					try {
-						errorMessage = error.toString()
-					} catch {
-						errorMessage = "Unknown error"
-					}
-				}
-
-				const statusCode = error?.status || error?.response?.status
-
-				if (statusCode === 401) {
-					throw new Error(t("embeddings:authenticationFailed"))
-				} else if (statusCode) {
-					throw new Error(
-						t("embeddings:failedWithStatus", { attempts: MAX_RETRIES, statusCode, errorMessage }),
-					)
-				} else {
-					throw new Error(t("embeddings:failedWithError", { attempts: MAX_RETRIES, errorMessage }))
-				}
+				// Format and throw the error
+				throw formatEmbeddingError(error, MAX_RETRIES)
 			}
 		}

 		throw new Error(t("embeddings:failedMaxAttempts", { attempts: MAX_RETRIES }))
 	}

+	/**
+	 * Validates the OpenAI embedder configuration by attempting a minimal embedding request
+	 * @returns Promise resolving to validation result with success status and optional error message
+	 */
+	async validateConfiguration(): Promise<{ valid: boolean; error?: string }> {
+		return withValidationErrorHandling(async () => {
+			// Test with a minimal embedding request
+			const response = await this.embeddingsClient.embeddings.create({
+				input: ["test"],
+				model: this.defaultModelId,
+			})
+
+			// Check if we got a valid response
+			if (!response.data || response.data.length === 0) {
+				return {
+					valid: false,
+					error: t("embeddings:openai.invalidResponseFormat"),
+				}
+			}
+
+			return { valid: true }
+		}, "openai")
+	}
+
 	get embedderInfo(): EmbedderInfo {
 		return {
 			name: "openai",
--- a/src/services/code-index/interfaces/embedder.ts
+++ b/src/services/code-index/interfaces/embedder.ts
@ -10,6 +10,13 @@ export interface IEmbedder {
 	 * @returns Promise resolving to an EmbeddingResponse
 	 */
 	createEmbeddings(texts: string[], model?: string): Promise<EmbeddingResponse>
+
+	/**
+	 * Validates the embedder configuration by testing connectivity and credentials.
+	 * @returns Promise resolving to validation result with success status and optional error message
+	 */
+	validateConfiguration(): Promise<{ valid: boolean; error?: string }>
+
 	get embedderInfo(): EmbedderInfo
 }

--- a/src/services/code-index/manager.ts
+++ b/src/services/code-index/manager.ts
@ -118,7 +118,14 @@ export class CodeIndexManager {
 			return { requiresRestart }
 		}

-		// 3. CacheManager Initialization
+		// 3. Check if workspace is available
+		const workspacePath = getWorkspacePath()
+		if (!workspacePath) {
+			this._stateManager.setSystemState("Standby", "No workspace folder open")
+			return { requiresRestart }
+		}
+
+		// 4. CacheManager Initialization
 		if (!this._cacheManager) {
 			this._cacheManager = new CacheManager(this.context, this.workspacePath)
 			await this._cacheManager.initialize()
@ -215,6 +222,9 @@ export class CodeIndexManager {
 		if (this._orchestrator) {
 			this.stopWatcher()
 		}
+		// Clear existing services to ensure clean state
+		this._orchestrator = undefined
+		this._searchService = undefined

 		// (Re)Initialize service factory
 		this._serviceFactory = new CodeIndexServiceFactory(
@ -224,7 +234,14 @@ export class CodeIndexManager {
 		)

 		const ignoreInstance = ignore()
-		const ignorePath = path.join(getWorkspacePath(), ".gitignore")
+		const workspacePath = getWorkspacePath()
+
+		if (!workspacePath) {
+			this._stateManager.setSystemState("Standby", "")
+			return
+		}
+
+		const ignorePath = path.join(workspacePath, ".gitignore")
 		try {
 			const content = await fs.readFile(ignorePath, "utf8")
 			ignoreInstance.add(content)
@ -241,6 +258,17 @@ export class CodeIndexManager {
 			ignoreInstance,
 		)

+		// Validate embedder configuration before proceeding
+		const validationResult = await this._serviceFactory.validateEmbedder(embedder)
+		if (!validationResult.valid) {
+			// Set error state with clear message
+			this._stateManager.setSystemState(
+				"Error",
+				validationResult.error || "Embedder configuration validation failed",
+			)
+			throw new Error(validationResult.error || "Invalid embedder configuration")
+		}
+
 		// (Re)Initialize orchestrator
 		this._orchestrator = new CodeIndexOrchestrator(
 			this._configManager!,
@ -259,6 +287,9 @@ export class CodeIndexManager {
 			embedder,
 			vectorStore,
 		)
+
+		// Clear any error state after successful recreation
+		this._stateManager.setSystemState("Standby", "")
 	}

 	/**
@ -274,13 +305,16 @@ export class CodeIndexManager {
 			const isFeatureEnabled = this.isFeatureEnabled
 			const isFeatureConfigured = this.isFeatureConfigured

-			// If configuration changes require a restart and the manager is initialized, restart the service
-			if (requiresRestart && isFeatureEnabled && isFeatureConfigured && this.isInitialized) {
-				// Recreate services with new configuration
-				await this._recreateServices()
-
-				// Start indexing with new services
-				this.startIndexing()
+			if (requiresRestart && isFeatureEnabled && isFeatureConfigured) {
+				try {
+					// Recreate services with new configuration
+					await this._recreateServices()
+				} catch (error) {
+					// Error state already set in _recreateServices
+					console.error("Failed to recreate services:", error)
+					// Re-throw the error so the caller knows validation failed
+					throw error
+				}
 			}
 		}
 	}
--- a/src/services/code-index/orchestrator.ts
+++ b/src/services/code-index/orchestrator.ts
@ -164,6 +164,31 @@ export class CodeIndexOrchestrator {
 				}
 			}

+			// Check for partial failures - if a significant portion of blocks failed
+			const failureRate = (cumulativeBlocksFoundSoFar - cumulativeBlocksIndexed) / cumulativeBlocksFoundSoFar
+			if (batchErrors.length > 0 && failureRate > 0.1) {
+				// More than 10% of blocks failed to index
+				const firstError = batchErrors[0]
+				throw new Error(
+					`Indexing partially failed: Only ${cumulativeBlocksIndexed} of ${cumulativeBlocksFoundSoFar} blocks were indexed. ${firstError.message}`,
+				)
+			}
+
+			// CRITICAL: If there were ANY batch errors and NO blocks were successfully indexed,
+			// this is a complete failure regardless of the failure rate calculation
+			if (batchErrors.length > 0 && cumulativeBlocksIndexed === 0) {
+				const firstError = batchErrors[0]
+				throw new Error(`Indexing failed completely: ${firstError.message}`)
+			}
+
+			// Final sanity check: If we found blocks but indexed none and somehow no errors were reported,
+			// this is still a failure
+			if (cumulativeBlocksFoundSoFar > 0 && cumulativeBlocksIndexed === 0) {
+				throw new Error(
+					"Indexing failed: No code blocks were successfully indexed despite finding files to process. This indicates a critical embedder failure.",
+				)
+			}
+
 			await this._startWatcher()

 			this.stateManager.setSystemState("Indexed", "File watcher started.")
--- a/src/services/code-index/service-factory.ts
+++ b/src/services/code-index/service-factory.ts
@ -66,6 +66,23 @@ export class CodeIndexServiceFactory {
 		throw new Error(`Invalid embedder type configured: ${config.embedderProvider}`)
 	}

+	/**
+	 * Validates an embedder instance to ensure it's properly configured.
+	 * @param embedder The embedder instance to validate
+	 * @returns Promise resolving to validation result
+	 */
+	public async validateEmbedder(embedder: IEmbedder): Promise<{ valid: boolean; error?: string }> {
+		try {
+			return await embedder.validateConfiguration()
+		} catch (error) {
+			// If validation throws an exception, preserve the original error message
+			return {
+				valid: false,
+				error: error instanceof Error ? error.message : "embeddings:validation.configurationError",
+			}
+		}
+	}
+
 	/**
 	 * Creates a vector store instance using the current configuration.
 	 */
--- a/src/services/code-index/shared/validation-helpers.ts
+++ b/src/services/code-index/shared/validation-helpers.ts
@ -0,0 +1,187 @@
+import { t } from "../../../i18n"
+import { serializeError } from "serialize-error"
+
+/**
+ * HTTP error interface for embedder errors
+ */
+export interface HttpError extends Error {
+	status?: number
+	response?: {
+		status?: number
+	}
+}
+
+/**
+ * Common error types that can occur during embedder validation
+ */
+export interface ValidationError {
+	status?: number
+	message?: string
+	name?: string
+	code?: string
+}
+
+/**
+ * Maps HTTP status codes to appropriate error messages
+ */
+export function getErrorMessageForStatus(status: number | undefined, embedderType: string): string | undefined {
+	switch (status) {
+		case 401:
+		case 403:
+			return "embeddings:validation.authenticationFailed"
+		case 404:
+			return embedderType === "openai"
+				? "embeddings:validation.modelNotAvailable"
+				: "embeddings:validation.invalidEndpoint"
+		case 429:
+			return "embeddings:validation.serviceUnavailable"
+		default:
+			if (status && status >= 400 && status < 600) {
+				return "embeddings:validation.configurationError"
+			}
+			return undefined
+	}
+}
+
+/**
+ * Extracts status code from various error formats
+ */
+export function extractStatusCode(error: any): number | undefined {
+	// Direct status property
+	if (error?.status) return error.status
+
+	// Response status property
+	if (error?.response?.status) return error.response.status
+
+	// Extract from error message (e.g., "HTTP 404: Not Found")
+	if (error?.message) {
+		const match = error.message.match(/HTTP (\d+):/)
+		if (match) {
+			return parseInt(match[1], 10)
+		}
+	}
+
+	// Use serialize-error as fallback for complex objects
+	const serialized = serializeError(error)
+	if (serialized?.status) return serialized.status
+	if (serialized?.response?.status) return serialized.response.status
+
+	return undefined
+}
+
+/**
+ * Extracts error message from various error formats
+ */
+export function extractErrorMessage(error: any): string {
+	if (error?.message) {
+		return error.message
+	}
+
+	if (typeof error === "string") {
+		return error
+	}
+
+	if (error && typeof error === "object" && "toString" in error) {
+		try {
+			return String(error)
+		} catch {
+			return "Unknown error"
+		}
+	}
+
+	// Use serialize-error as fallback for complex objects
+	const serialized = serializeError(error)
+	if (serialized?.message) {
+		return serialized.message
+	}
+
+	return "Unknown error"
+}
+
+/**
+ * Standard validation error handler for embedder configuration validation
+ * Returns a consistent error response based on the error type
+ */
+export function handleValidationError(
+	error: any,
+	embedderType: string,
+	customHandlers?: {
+		beforeStandardHandling?: (error: any) => { valid: boolean; error: string } | undefined
+	},
+): { valid: boolean; error: string } {
+	// Serialize the error to ensure we have access to all properties
+	const serializedError = serializeError(error)
+
+	// Allow custom handling first (pass original error for backward compatibility)
+	if (customHandlers?.beforeStandardHandling) {
+		const customResult = customHandlers.beforeStandardHandling(error)
+		if (customResult) return customResult
+	}
+
+	// Extract status code and error message from serialized error
+	const statusCode = extractStatusCode(serializedError)
+	const errorMessage = extractErrorMessage(serializedError)
+
+	// Check for status-based errors first
+	const statusError = getErrorMessageForStatus(statusCode, embedderType)
+	if (statusError) {
+		return { valid: false, error: statusError }
+	}
+
+	// Check for connection errors
+	if (errorMessage) {
+		if (
+			errorMessage.includes("ENOTFOUND") ||
+			errorMessage.includes("ECONNREFUSED") ||
+			errorMessage.includes("ETIMEDOUT") ||
+			errorMessage === "AbortError" ||
+			errorMessage.includes("HTTP 0:") ||
+			errorMessage === "No response"
+		) {
+			return { valid: false, error: "embeddings:validation.connectionFailed" }
+		}
+
+		if (errorMessage.includes("Failed to parse response JSON")) {
+			return { valid: false, error: "embeddings:validation.invalidResponse" }
+		}
+	}
+
+	// For generic errors, preserve the original error message if it's not a standard one
+	if (errorMessage && errorMessage !== "Unknown error") {
+		return { valid: false, error: errorMessage }
+	}
+
+	// Fallback to generic error
+	return { valid: false, error: "embeddings:validation.configurationError" }
+}
+
+/**
+ * Wraps an async validation function with standard error handling
+ */
+export async function withValidationErrorHandling<T extends { valid: boolean; error?: string }>(
+	validationFn: () => Promise<T>,
+	embedderType: string,
+	customHandlers?: Parameters<typeof handleValidationError>[2],
+): Promise<{ valid: boolean; error?: string }> {
+	try {
+		return await validationFn()
+	} catch (error) {
+		return handleValidationError(error, embedderType, customHandlers)
+	}
+}
+
+/**
+ * Formats an embedding error message based on the error type and context
+ */
+export function formatEmbeddingError(error: any, maxRetries: number): Error {
+	const errorMessage = extractErrorMessage(error)
+	const statusCode = extractStatusCode(error)
+
+	if (statusCode === 401) {
+		return new Error(t("embeddings:authenticationFailed"))
+	} else if (statusCode) {
+		return new Error(t("embeddings:failedWithStatus", { attempts: maxRetries, statusCode, errorMessage }))
+	} else {
+		return new Error(t("embeddings:failedWithError", { attempts: maxRetries, errorMessage }))
+	}
+}
--- a/src/shared/WebviewMessage.ts
+++ b/src/shared/WebviewMessage.ts
@ -110,6 +110,7 @@ export interface WebviewMessage {
 		| "enhancedPrompt"
 		| "draggedImages"
 		| "deleteMessage"
+		| "submitEditedMessage"
 		| "terminalOutputLineLimit"
 		| "terminalShellIntegrationTimeout"
 		| "terminalShellIntegrationDisabled"
@ -193,6 +194,7 @@ export interface WebviewMessage {
 		| "saveCodeIndexSettingsAtomic"
 		| "requestCodeIndexSecretStatus"
 	text?: string
+	editedMessageContent?: string
 	tab?: "settings" | "history" | "mcp" | "modes" | "chat" | "marketplace" | "account"
 	disabled?: boolean
 	dataUri?: string
--- a/src/tsconfig.json
+++ b/src/tsconfig.json
@ -13,7 +13,6 @@
 		"noImplicitReturns": true,
 		"noUnusedLocals": false,
 		"resolveJsonModule": true,
-		"rootDir": ".",
 		"skipLibCheck": true,
 		"sourceMap": true,
 		"strict": true,
--- a/webview-ui/src/components/chat/ChatRow.tsx
+++ b/webview-ui/src/components/chat/ChatRow.tsx
@ -111,6 +111,8 @@ export const ChatRowContent = ({
 	const [reasoningCollapsed, setReasoningCollapsed] = useState(true)
 	const [isDiffErrorExpanded, setIsDiffErrorExpanded] = useState(false)
 	const [showCopySuccess, setShowCopySuccess] = useState(false)
+	const [isEditing, setIsEditing] = useState(false)
+	const [editedContent, setEditedContent] = useState("")
 	const { copyWithFeedback } = useCopyToClipboard()

 	// Memoized callback to prevent re-renders caused by inline arrow functions
@ -118,6 +120,31 @@ export const ChatRowContent = ({
 		onToggleExpand(message.ts)
 	}, [onToggleExpand, message.ts])

+	// Handle edit button click
+	const handleEditClick = useCallback(() => {
+		setIsEditing(true)
+		setEditedContent(message.text || "")
+		// Edit mode is now handled entirely in the frontend
+		// No need to notify the backend
+	}, [message.text])
+
+	// Handle cancel edit
+	const handleCancelEdit = useCallback(() => {
+		setIsEditing(false)
+		setEditedContent(message.text || "")
+	}, [message.text])
+
+	// Handle save edit
+	const handleSaveEdit = useCallback(() => {
+		setIsEditing(false)
+		// Send edited message to backend
+		vscode.postMessage({
+			type: "submitEditedMessage",
+			value: message.ts,
+			editedMessageContent: editedContent,
+		})
+	}, [message.ts, editedContent])
+
 	const [cost, apiReqCancelReason, apiReqStreamingFailedMessage] = useMemo(() => {
 		if (message.text !== null && message.text !== undefined && message.say === "api_req_started") {
 			const info = safeJsonParse<ClineApiReqInfo>(message.text)
@ -1001,23 +1028,56 @@ export const ChatRowContent = ({
 				case "user_feedback":
 					return (
 						<div className="bg-vscode-editor-background border rounded-xs p-1 overflow-hidden whitespace-pre-wrap">
-							<div className="flex justify-between">
-								<div className="flex-grow px-2 py-1 wrap-anywhere">
-									<Mention text={message.text} withShadow />
+							{isEditing ? (
+								<div className="flex flex-col gap-2 p-2">
+									<textarea
+										className="w-full p-2 bg-vscode-input-background text-vscode-input-foreground border border-vscode-input-border rounded-xs"
+										value={editedContent}
+										onChange={(e) => setEditedContent(e.target.value)}
+										rows={5}
+										autoFocus
+									/>
+									<div className="flex justify-end gap-2">
+										<Button variant="secondary" size="sm" onClick={handleCancelEdit}>
+											{t("chat:cancel.title")}
+										</Button>
+										<Button variant="default" size="sm" onClick={handleSaveEdit}>
+											{t("chat:save.title")}
+										</Button>
+									</div>
 								</div>
-								<Button
-									variant="ghost"
-									size="icon"
-									className="shrink-0"
-									disabled={isStreaming}
-									onClick={(e) => {
-										e.stopPropagation()
-										vscode.postMessage({ type: "deleteMessage", value: message.ts })
-									}}>
-									<span className="codicon codicon-trash" />
-								</Button>
-							</div>
-							{message.images && message.images.length > 0 && (
+							) : (
+								<div className="flex justify-between">
+									<div className="flex-grow px-2 py-1 wrap-anywhere">
+										<Mention text={message.text} withShadow />
+									</div>
+									<div className="flex">
+										<Button
+											variant="ghost"
+											size="icon"
+											className="shrink-0"
+											disabled={isStreaming}
+											onClick={(e) => {
+												e.stopPropagation()
+												handleEditClick()
+											}}>
+											<span className="codicon codicon-edit" />
+										</Button>
+										<Button
+											variant="ghost"
+											size="icon"
+											className="shrink-0"
+											disabled={isStreaming}
+											onClick={(e) => {
+												e.stopPropagation()
+												vscode.postMessage({ type: "deleteMessage", value: message.ts })
+											}}>
+											<span className="codicon codicon-trash" />
+										</Button>
+									</div>
+								</div>
+							)}
+							{!isEditing && message.images && message.images.length > 0 && (
 								<Thumbnails images={message.images} style={{ marginTop: "8px" }} />
 							)}
 						</div>
--- a/webview-ui/src/components/chat/tests/ChatTextArea.spec.tsx
+++ b/webview-ui/src/components/chat/tests/ChatTextArea.spec.tsx
@ -445,13 +445,15 @@ describe("ChatTextArea", () => {
 				})
 			})

-			it("should navigate to previous prompt on arrow up", () => {
+			it("should navigate to previous prompt on arrow up when cursor is at beginning", () => {
 				const setInputValue = vi.fn()
 				const { container } = render(
 					<ChatTextArea {...defaultProps} setInputValue={setInputValue} inputValue="" />,
 				)

 				const textarea = container.querySelector("textarea")!
+				// Ensure cursor is at the beginning
+				textarea.setSelectionRange(0, 0)

 				// Simulate arrow up key press
 				fireEvent.keyDown(textarea, { key: "ArrowUp" })
@ -755,6 +757,86 @@ describe("ChatTextArea", () => {
 				fireEvent.keyDown(textarea, { key: "ArrowUp" })
 				expect(setInputValue).toHaveBeenCalledWith("Message 2")
 			})
+
+			it("should not navigate history with arrow up when cursor is not at beginning", () => {
+				const setInputValue = vi.fn()
+				const { container } = render(
+					<ChatTextArea {...defaultProps} setInputValue={setInputValue} inputValue="Some text here" />,
+				)
+
+				const textarea = container.querySelector("textarea")!
+				// Set cursor to middle of text (not at beginning)
+				textarea.setSelectionRange(5, 5)
+
+				// Clear any calls from initial render
+				setInputValue.mockClear()
+
+				// Simulate arrow up key press
+				fireEvent.keyDown(textarea, { key: "ArrowUp" })
+
+				// Should not navigate history, allowing default behavior (move cursor to start)
+				expect(setInputValue).not.toHaveBeenCalled()
+			})
+
+			it("should navigate history with arrow up when cursor is at beginning", () => {
+				const setInputValue = vi.fn()
+				const { container } = render(
+					<ChatTextArea {...defaultProps} setInputValue={setInputValue} inputValue="Some text here" />,
+				)
+
+				const textarea = container.querySelector("textarea")!
+				// Set cursor to beginning of text
+				textarea.setSelectionRange(0, 0)
+
+				// Clear any calls from initial render
+				setInputValue.mockClear()
+
+				// Simulate arrow up key press
+				fireEvent.keyDown(textarea, { key: "ArrowUp" })
+
+				// Should navigate to history since cursor is at beginning
+				expect(setInputValue).toHaveBeenCalledWith("Third prompt")
+			})
+
+			it("should navigate history with Command+Up when cursor is at beginning", () => {
+				const setInputValue = vi.fn()
+				const { container } = render(
+					<ChatTextArea {...defaultProps} setInputValue={setInputValue} inputValue="Some text here" />,
+				)
+
+				const textarea = container.querySelector("textarea")!
+				// Set cursor to beginning of text
+				textarea.setSelectionRange(0, 0)
+
+				// Clear any calls from initial render
+				setInputValue.mockClear()
+
+				// Simulate Command+Up key press
+				fireEvent.keyDown(textarea, { key: "ArrowUp", metaKey: true })
+
+				// Should navigate to history since cursor is at beginning (same as regular Up)
+				expect(setInputValue).toHaveBeenCalledWith("Third prompt")
+			})
+
+			it("should not navigate history with Command+Up when cursor is not at beginning", () => {
+				const setInputValue = vi.fn()
+				const { container } = render(
+					<ChatTextArea {...defaultProps} setInputValue={setInputValue} inputValue="Some text here" />,
+				)
+
+				const textarea = container.querySelector("textarea")!
+				// Set cursor to middle of text (not at beginning)
+				textarea.setSelectionRange(5, 5)
+
+				// Clear any calls from initial render
+				setInputValue.mockClear()
+
+				// Simulate Command+Up key press
+				fireEvent.keyDown(textarea, { key: "ArrowUp", metaKey: true })
+
+				// Should not navigate history, allowing default behavior (same as regular Up)
+				expect(setInputValue).not.toHaveBeenCalled()
+			})
 		})
 	})

--- a/webview-ui/src/components/chat/hooks/usePromptHistory.ts
+++ b/webview-ui/src/components/chat/hooks/usePromptHistory.ts
@ -139,32 +139,8 @@ export const usePromptHistory = ({
 				const isAtBeginning = selectionStart === 0 && selectionEnd === 0
 				const isAtEnd = selectionStart === value.length && selectionEnd === value.length

-				// Check for modifier keys (Alt or Cmd/Ctrl)
-				const hasModifier = event.altKey || event.metaKey || event.ctrlKey
-
-				// Handle explicit history navigation with Alt+Up/Down
-				if (hasModifier && (event.key === "ArrowUp" || event.key === "ArrowDown")) {
-					event.preventDefault()
-
-					if (event.key === "ArrowUp") {
-						// Save current input if starting navigation
-						if (historyIndex === -1) {
-							setTempInput(inputValue)
-						}
-						return navigateToHistory(historyIndex + 1, textarea, "start")
-					} else {
-						// ArrowDown
-						if (historyIndex > 0) {
-							return navigateToHistory(historyIndex - 1, textarea, "end")
-						} else if (historyIndex === 0) {
-							returnToCurrentInput(textarea, "end")
-							return true
-						}
-					}
-				}
-
-				// Handle smart navigation without modifiers
-				if (!hasSelection && !hasModifier) {
+				// Handle smart navigation
+				if (!hasSelection) {
 					// Only navigate history with UP if cursor is at the very beginning
 					if (event.key === "ArrowUp" && isAtBeginning) {
 						event.preventDefault()