fix: Ollama base URL not read from per-purpose config keys in Docker + i18n for all locales

The admin form saves Ollama URLs as OLLAMA_BASE_URL_TAGS/EMBEDDING/CHAT,
but the factory only read OLLAMA_BASE_URL — causing 500 errors in Docker
where no localhost fallback exists.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

memento-note/app/(admin)/admin/settings/admin-settings-form.tsx

@@ -446,27 +446,21 @@ export function AdminSettingsForm({ config }: { config: Record<string, string> }
                     </div>
                   </div>
                   <div className="space-y-2">
-                    <Label htmlFor="AI_MODEL_TAGS_OLLAMA">{t('admin.ai.model')}</Label>
-                    <select
-                      id="AI_MODEL_TAGS_OLLAMA"
-                      name="AI_MODEL_TAGS_OLLAMA"
+                    <Label>{t('admin.ai.model')}</Label>
+                    <input type="hidden" name="AI_MODEL_TAGS_OLLAMA" value={selectedTagsModel} />
+                    <Combobox
+                      options={ollamaTagsModels.length > 0
+                        ? ollamaTagsModels.map((m) => ({ value: m, label: m }))
+                        : selectedTagsModel
+                          ? [{ value: selectedTagsModel, label: `${selectedTagsModel} (${t('admin.ai.saved')})` }]
+                          : []
+                      }
                       value={selectedTagsModel}
-                      onChange={(e) => setSelectedTagsModel(e.target.value)}
-                      className="flex h-10 w-full rounded-md border border-input bg-background px-3 py-2 text-sm ring-offset-background focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2"
-                    >
-                      {ollamaTagsModels.length > 0 ? (
-                        <>
-                          {!ollamaTagsModels.includes(selectedTagsModel) && selectedTagsModel && (
-                            <option value={selectedTagsModel}>{selectedTagsModel} ({t('admin.ai.configured')})</option>
-                          )}
-                          {ollamaTagsModels.map((model) => (
-                            <option key={model} value={model}>{model}</option>
-                          ))}
-                        </>
-                      ) : (
-                        <option value={selectedTagsModel || 'granite4:latest'}>{selectedTagsModel || 'granite4:latest'} {t('admin.ai.saved')}</option>
-                      )}
-                    </select>
+                      onChange={setSelectedTagsModel}
+                      placeholder={selectedTagsModel || t('admin.ai.clickToLoadModels')}
+                      searchPlaceholder={t('admin.ai.searchModel')}
+                      emptyMessage={t('admin.ai.noModels')}
+                    />
                     <p className="text-xs text-muted-foreground">
                       {isLoadingTagsModels ? t('admin.ai.fetchingModels') : t('admin.ai.selectOllamaModel')}
                     </p>
@@ -620,27 +614,21 @@ export function AdminSettingsForm({ config }: { config: Record<string, string> }
                     </div>
                   </div>
                   <div className="space-y-2">
-                    <Label htmlFor="AI_MODEL_EMBEDDING_OLLAMA">{t('admin.ai.model')}</Label>
-                    <select
-                      id="AI_MODEL_EMBEDDING_OLLAMA"
-                      name="AI_MODEL_EMBEDDING_OLLAMA"
+                    <Label>{t('admin.ai.model')}</Label>
+                    <input type="hidden" name="AI_MODEL_EMBEDDING_OLLAMA" value={selectedEmbeddingModel} />
+                    <Combobox
+                      options={ollamaEmbeddingsModels.length > 0
+                        ? ollamaEmbeddingsModels.map((m) => ({ value: m, label: m }))
+                        : selectedEmbeddingModel
+                          ? [{ value: selectedEmbeddingModel, label: `${selectedEmbeddingModel} (${t('admin.ai.saved')})` }]
+                          : []
+                      }
                       value={selectedEmbeddingModel}
-                      onChange={(e) => setSelectedEmbeddingModel(e.target.value)}
-                      className="flex h-10 w-full rounded-md border border-input bg-background px-3 py-2 text-sm ring-offset-background focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2"
-                    >
-                      {ollamaEmbeddingsModels.length > 0 ? (
-                        <>
-                          {!ollamaEmbeddingsModels.includes(selectedEmbeddingModel) && selectedEmbeddingModel && (
-                            <option value={selectedEmbeddingModel}>{selectedEmbeddingModel} ({t('admin.ai.configured')})</option>
-                          )}
-                          {ollamaEmbeddingsModels.map((model) => (
-                            <option key={model} value={model}>{model}</option>
-                          ))}
-                        </>
-                      ) : (
-                        <option value={selectedEmbeddingModel || 'embeddinggemma:latest'}>{selectedEmbeddingModel || 'embeddinggemma:latest'} {t('admin.ai.saved')}</option>
-                      )}
-                    </select>
+                      onChange={setSelectedEmbeddingModel}
+                      placeholder={selectedEmbeddingModel || t('admin.ai.clickToLoadModels')}
+                      searchPlaceholder={t('admin.ai.searchModel')}
+                      emptyMessage={t('admin.ai.noModels')}
+                    />
                     <p className="text-xs text-muted-foreground">
                       {isLoadingEmbeddingsModels ? t('admin.ai.fetchingModels') : t('admin.ai.selectEmbeddingModel')}
                     </p>
@@ -790,27 +778,21 @@ export function AdminSettingsForm({ config }: { config: Record<string, string> }
                     </div>
                   </div>
                   <div className="space-y-2">
-                    <Label htmlFor="AI_MODEL_CHAT_OLLAMA">{t('admin.ai.model')}</Label>
-                    <select
-                      id="AI_MODEL_CHAT_OLLAMA"
-                      name="AI_MODEL_CHAT_OLLAMA"
+                    <Label>{t('admin.ai.model')}</Label>
+                    <input type="hidden" name="AI_MODEL_CHAT_OLLAMA" value={selectedChatModel} />
+                    <Combobox
+                      options={ollamaChatModels.length > 0
+                        ? ollamaChatModels.map((m) => ({ value: m, label: m }))
+                        : selectedChatModel
+                          ? [{ value: selectedChatModel, label: `${selectedChatModel} (${t('admin.ai.saved')})` }]
+                          : []
+                      }
                       value={selectedChatModel}
-                      onChange={(e) => setSelectedChatModel(e.target.value)}
-                      className="flex h-10 w-full rounded-md border border-input bg-background px-3 py-2 text-sm ring-offset-background focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2"
-                    >
-                      {ollamaChatModels.length > 0 ? (
-                        <>
-                          {!ollamaChatModels.includes(selectedChatModel) && selectedChatModel && (
-                            <option value={selectedChatModel}>{selectedChatModel} ({t('admin.ai.configured')})</option>
-                          )}
-                          {ollamaChatModels.map((model) => (
-                            <option key={model} value={model}>{model}</option>
-                          ))}
-                        </>
-                      ) : (
-                        <option value={selectedChatModel || 'granite4:latest'}>{selectedChatModel || 'granite4:latest'} {t('admin.ai.saved')}</option>
-                      )}
-                    </select>
+                      onChange={setSelectedChatModel}
+                      placeholder={selectedChatModel || t('admin.ai.clickToLoadModels')}
+                      searchPlaceholder={t('admin.ai.searchModel')}
+                      emptyMessage={t('admin.ai.noModels')}
+                    />
                     <p className="text-xs text-muted-foreground">
                       {isLoadingChatModels ? t('admin.ai.fetchingModels') : t('admin.ai.selectOllamaModel')}
                     </p>

memento-note/app/api/chat/route.ts

@@ -99,40 +99,46 @@ export async function POST(req: Request) {
   // This ensures the AI always has access to the notebook content,
   // even for vague queries like "what's in this notebook?"
   let notebookContext = ''
-  if (notebookId) {
-    const notebookNotes = await prisma.note.findMany({
-      where: {
-        notebookId,
-        userId,
-        trashedAt: null,
-      },
-      orderBy: { updatedAt: 'desc' },
-      take: 20,
-      select: { id: true, title: true, content: true, updatedAt: true },
-    })
-    if (notebookNotes.length > 0) {
-      notebookContext = notebookNotes
-        .map(n => `NOTE [${n.title || untitledText}] (updated ${n.updatedAt.toLocaleDateString()}):\n${(n.content || '').substring(0, 1500)}`)
-        .join('\n\n---\n\n')
+  let searchNotes = ''
+
+  // When scope is "this note" (noteContext present), skip RAG retrieval entirely
+  // The note content is already injected as copilotContext below
+  if (!noteContext) {
+    if (notebookId) {
+      const notebookNotes = await prisma.note.findMany({
+        where: {
+          notebookId,
+          userId,
+          trashedAt: null,
+        },
+        orderBy: { updatedAt: 'desc' },
+        take: 20,
+        select: { id: true, title: true, content: true, updatedAt: true },
+      })
+      if (notebookNotes.length > 0) {
+        notebookContext = notebookNotes
+          .map(n => `NOTE [${n.title || untitledText}] (updated ${n.updatedAt.toLocaleDateString()}):\n${(n.content || '').substring(0, 1500)}`)
+          .join('\n\n---\n\n')
+      }
     }
-  }
 
-  // Also run semantic search for the specific query
-  let searchResults: any[] = []
-  try {
-    searchResults = await semanticSearchService.search(currentMessage, {
-      notebookId,
-      limit: notebookId ? 10 : 5,
-      threshold: notebookId ? 0.3 : 0.5,
-      defaultTitle: untitledText,
-    })
-  } catch {
-    // Search failure should not block chat
-  }
+    // Also run semantic search for the specific query
+    let searchResults: any[] = []
+    try {
+      searchResults = await semanticSearchService.search(currentMessage, {
+        notebookId,
+        limit: notebookId ? 10 : 5,
+        threshold: notebookId ? 0.3 : 0.5,
+        defaultTitle: untitledText,
+      })
+    } catch {
+      // Search failure should not block chat
+    }
 
-  const searchNotes = searchResults
-    .map((r) => `NOTE [${r.title || untitledText}]: ${r.content}`)
-    .join('\n\n---\n\n')
+    searchNotes = searchResults
+      .map((r) => `NOTE [${r.title || untitledText}]: ${r.content}`)
+      .join('\n\n---\n\n')
+  }
 
   // Combine: full notebook context + semantic search results (deduplicated)
   const contextNotes = [notebookContext, searchNotes].filter(Boolean).join('\n\n---\n\n')
@@ -354,7 +360,7 @@ ${noteContext.content || '(empty)'}
 ${imageContextParts.length > 0 ? `\nImages: ${imageContextParts.length} image(s) attached. When the user asks about images, describe what you see in them.` : ''}
 
 The user wants you to write in a **${noteContext.tone || 'professional'}** tone.
-Keep your suggestions tailored to this note and tone. You can suggest rewrites, answer questions about the note, or draft new sections.`
+IMPORTANT: Focus ONLY on this note. Do NOT reference other notes or external information unless the user explicitly asks. Your job is to help with this specific note — suggest rewrites, answer questions about it, or draft new sections.`
   }
 
   const systemPrompt = `${prompts.system}
@@ -413,7 +419,11 @@ Never switch to another language. Even if the user writes in a different languag
     webSearch: !!webSearch,
     config,
   }
-  const chatTools = toolRegistry.buildToolsForChat(chatToolContext)
+  // When scoped to "this note", only provide web tools — no note_search/note_read
+  // to prevent the AI from pulling information from other notes
+  const chatTools = noteContext
+    ? toolRegistry.buildToolsForChat({ ...chatToolContext, webOnly: true })
+    : toolRegistry.buildToolsForChat(chatToolContext)
 
   // 8. Save user message to DB before streaming
   if (isNewMessage && lastIncoming) {

memento-note/components/notes-tabs-view.tsx

@@ -613,31 +613,27 @@ export function NotesTabsView({
     setItems((prev) => {
       const prevIds = prev.map((n) => n.id).join(',')
       const incomingIds = notes.map((n) => n.id).join(',')
+      const merge = (fresh: Note, local: Note) => {
+        const labelsChanged = JSON.stringify(fresh.labels?.sort()) !== JSON.stringify(local.labels?.sort())
+        return {
+          ...fresh,
+          title: local.title || fresh.title,
+          content: local.content,
+          checkItems: local.checkItems,
+          labels: labelsChanged ? fresh.labels : local.labels
+        }
+      }
       if (prevIds === incomingIds) {
         return prev.map((p) => {
           const fresh = notes.find((n) => n.id === p.id)
           if (!fresh) return p
-          const labelsChanged = JSON.stringify(fresh.labels?.sort()) !== JSON.stringify(p.labels?.sort())
-          return {
-            ...fresh,
-            title: p.title,
-            content: p.content,
-            checkItems: p.checkItems,
-            labels: labelsChanged ? fresh.labels : p.labels
-          }
+          return merge(fresh, p)
         })
       }
       return notes.map((fresh) => {
         const local = prev.find((p) => p.id === fresh.id)
         if (!local) return fresh
-        const labelsChanged = JSON.stringify(fresh.labels?.sort()) !== JSON.stringify(local.labels?.sort())
-        return {
-          ...fresh,
-          title: local.title,
-          content: local.content,
-          checkItems: local.checkItems,
-          labels: labelsChanged ? fresh.labels : local.labels
-        }
+        return merge(fresh, local)
       })
     })
   }, [notes])

memento-note/lib/ai/factory.ts

@@ -5,8 +5,8 @@ import { AIProvider } from './types';
 
 type ProviderType = 'ollama' | 'openai' | 'custom' | 'deepseek' | 'openrouter';
 
-function createOllamaProvider(config: Record<string, string>, modelName: string, embeddingModelName: string): OllamaProvider {
-  let baseUrl = config?.OLLAMA_BASE_URL || process.env.OLLAMA_BASE_URL
+function createOllamaProvider(config: Record<string, string>, modelName: string, embeddingModelName: string, baseUrlOverride?: string): OllamaProvider {
+  let baseUrl = baseUrlOverride || config?.OLLAMA_BASE_URL || process.env.OLLAMA_BASE_URL
 
   // Only use localhost as fallback for local development (not in Docker)
   if (!baseUrl && process.env.NODE_ENV !== 'production') {
@@ -62,10 +62,10 @@ function createOpenRouterProvider(config: Record<string, string>, modelName: str
   return new CustomOpenAIProvider(apiKey, 'https://openrouter.ai/api/v1', modelName, embeddingModelName);
 }
 
-function getProviderInstance(providerType: ProviderType, config: Record<string, string>, modelName: string, embeddingModelName: string): AIProvider {
+function getProviderInstance(providerType: ProviderType, config: Record<string, string>, modelName: string, embeddingModelName: string, ollamaBaseUrl?: string): AIProvider {
   switch (providerType) {
     case 'ollama':
-      return createOllamaProvider(config, modelName, embeddingModelName);
+      return createOllamaProvider(config, modelName, embeddingModelName, ollamaBaseUrl);
     case 'openai':
       return createOpenAIProvider(config, modelName, embeddingModelName);
     case 'custom':
@@ -75,7 +75,7 @@ function getProviderInstance(providerType: ProviderType, config: Record<string,
     case 'openrouter':
       return createOpenRouterProvider(config, modelName, embeddingModelName);
     default:
-      return createOllamaProvider(config, modelName, embeddingModelName);
+      return createOllamaProvider(config, modelName, embeddingModelName, ollamaBaseUrl);
   }
 }
 
@@ -102,8 +102,9 @@ export function getTagsProvider(config?: Record<string, string>): AIProvider {
   const provider = providerType.toLowerCase() as ProviderType;
   const modelName = config?.AI_MODEL_TAGS || process.env.AI_MODEL_TAGS || 'granite4:latest';
   const embeddingModelName = config?.AI_MODEL_EMBEDDING || process.env.AI_MODEL_EMBEDDING || 'embeddinggemma:latest';
+  const ollamaBaseUrl = config?.OLLAMA_BASE_URL_TAGS || config?.OLLAMA_BASE_URL;
 
-  return getProviderInstance(provider, config || {}, modelName, embeddingModelName);
+  return getProviderInstance(provider, config || {}, modelName, embeddingModelName, ollamaBaseUrl);
 }
 
 export function getEmbeddingsProvider(config?: Record<string, string>): AIProvider {
@@ -129,8 +130,9 @@ export function getEmbeddingsProvider(config?: Record<string, string>): AIProvid
   const provider = providerType.toLowerCase() as ProviderType;
   const modelName = config?.AI_MODEL_TAGS || process.env.AI_MODEL_TAGS || 'granite4:latest';
   const embeddingModelName = config?.AI_MODEL_EMBEDDING || process.env.AI_MODEL_EMBEDDING || 'embeddinggemma:latest';
+  const ollamaBaseUrl = config?.OLLAMA_BASE_URL_EMBEDDING || config?.OLLAMA_BASE_URL;
 
-  return getProviderInstance(provider, config || {}, modelName, embeddingModelName);
+  return getProviderInstance(provider, config || {}, modelName, embeddingModelName, ollamaBaseUrl);
 }
 
 export function getAIProvider(config?: Record<string, string>): AIProvider {
@@ -167,6 +169,7 @@ export function getChatProvider(config?: Record<string, string>): AIProvider {
     'granite4:latest'
   );
   const embeddingModelName = config?.AI_MODEL_EMBEDDING || process.env.AI_MODEL_EMBEDDING || 'embeddinggemma:latest';
+  const ollamaBaseUrl = config?.OLLAMA_BASE_URL_CHAT || config?.OLLAMA_BASE_URL_TAGS || config?.OLLAMA_BASE_URL_EMBEDDING || config?.OLLAMA_BASE_URL;
 
-  return getProviderInstance(provider, config || {}, modelName, embeddingModelName);
+  return getProviderInstance(provider, config || {}, modelName, embeddingModelName, ollamaBaseUrl);
 }

memento-note/lib/ai/tools/registry.ts

@@ -49,9 +49,10 @@ class ToolRegistry {
   /**
    * Build tools for the chat endpoint.
    * Includes internal tools (note_search, note_read) and web tools when configured.
+   * When webOnly is true, only web tools are included (no note access).
    */
-  buildToolsForChat(ctx: ToolContext): Record<string, any> {
-    const toolNames: string[] = ['note_search', 'note_read']
+  buildToolsForChat(ctx: ToolContext & { webOnly?: boolean }): Record<string, any> {
+    const toolNames: string[] = ctx.webOnly ? [] : ['note_search', 'note_read']
 
     // Add web tools only when user toggled web search AND config is present
     if (ctx.webSearch) {