# Project N.O.M.A.D.
+
### Node for Offline Media, Archives, and Data
**Knowledge That Never Goes Offline**
@@ -17,11 +18,13 @@
Project N.O.M.A.D. is a self-contained, offline-first knowledge and education server packed with critical tools, knowledge, and AI to keep you informed and empowered—anytime, anywhere.
## Installation & Quickstart
+
Project N.O.M.A.D. can be installed on any Debian-based operating system (we recommend Ubuntu). Installation is completely terminal-based, and all tools and resources are designed to be accessed through the browser, so there's no need for a desktop environment if you'd rather setup N.O.M.A.D. as a "server" and access it through other clients.
-*Note: sudo/root privileges are required to run the install script*
+_Note: sudo/root privileges are required to run the install script_
### Quick Install (Debian-based OS Only)
+
```bash
sudo apt-get update && \
sudo apt-get install -y curl && \
@@ -32,17 +35,33 @@ sudo bash install_nomad.sh
Project N.O.M.A.D. is now installed on your device! Open a browser and navigate to `http://localhost:8080` (or `http://DEVICE_IP:8080`) to start exploring!
+### macOS Apple Silicon Install
+
+N.O.M.A.D. can also run on Apple Silicon Macs with Docker Desktop or Colima for the core services and a native launchd-managed Mac AI worker for MLX/Core ML inference. The macOS path stores data under your home directory and keeps MLX/Core ML execution on the host so it can use Metal/Core ML acceleration.
+
+```bash
+curl -fsSL https://raw.githubusercontent.com/Crosstalk-Solutions/project-nomad/refs/heads/main/install/macos/install_macos_nomad.sh \
+ -o install_macos_nomad.sh && \
+bash install_macos_nomad.sh
+```
+
+After installation, open `http://localhost:8080`, go to AI Assistant settings, choose **Native MLX** or **Native Core ML**, and place compatible model folders/packages in `~/.project-nomad/mac-ai/models`.
+
For a complete step-by-step walkthrough (including Ubuntu installation), see the [Installation Guide](https://www.projectnomad.us/install). For Windows users, see the [WSL2 install guide](https://www.projectnomad.us/install/wsl2) — community-supported path covering native Docker and Docker Desktop install routes.
### Advanced Installation
+
For more control over the installation process, copy and paste the [Docker Compose template](https://raw.githubusercontent.com/Crosstalk-Solutions/project-nomad/refs/heads/main/install/management_compose.yaml) into a `docker-compose.yml` file and customize it to your liking (be sure to replace any placeholders with your actual values). Then, run `docker compose up -d` to start the Command Center and its dependencies. Note: this method is recommended for advanced users only, as it requires familiarity with Docker and manual configuration before starting.
## How It Works
+
N.O.M.A.D. is a management UI ("Command Center") and API that orchestrates a collection of containerized tools and resources via [Docker](https://www.docker.com/). It handles installation, configuration, and updates for everything — so you don't have to.
**Built-in capabilities include:**
+
- **AI Chat with Knowledge Base** — local AI chat powered by [Ollama](https://ollama.com/) or you can use OpenAI API compatible software such as LM Studio or llama.cpp, with document upload and semantic search (RAG via [Qdrant](https://qdrant.tech/))
- **Information Library** — offline Wikipedia, medical references, ebooks, and more via [Kiwix](https://kiwix.org/)
+- **Local Library** — in-app viewing for your own PDFs and local documents, with optional Knowledge Base indexing
- **Education Platform** — Khan Academy courses with progress tracking via [Kolibri](https://learningequality.org/kolibri/)
- **Offline Maps** — downloadable regional maps via [ProtoMaps](https://protomaps.com)
- **Data Tools** — encryption, encoding, and analysis via [CyberChef](https://gchq.github.io/CyberChef/)
@@ -54,25 +73,27 @@ N.O.M.A.D. also includes built-in tools like a Wikipedia content selector, ZIM l
## What's Included
-| Capability | Powered By | What You Get |
-|-----------|-----------|-------------|
-| Information Library | Kiwix | Offline Wikipedia, medical references, survival guides, ebooks |
-| AI Assistant | Ollama + Qdrant | Built-in chat with document upload and semantic search |
-| Education Platform | Kolibri | Khan Academy courses, progress tracking, multi-user support |
-| Offline Maps | ProtoMaps | Downloadable regional maps with search and navigation |
-| Data Tools | CyberChef | Encryption, encoding, hashing, and data analysis |
-| Notes | FlatNotes | Local note-taking with markdown support |
-| System Benchmark | Built-in | Hardware scoring, Builder Tags, and community leaderboard |
+| Capability | Powered By | What You Get |
+| ------------------- | --------------- | -------------------------------------------------------------- |
+| Information Library | Kiwix | Offline Wikipedia, medical references, survival guides, ebooks |
+| AI Assistant | Ollama + Qdrant | Built-in chat with document upload and semantic search |
+| Education Platform | Kolibri | Khan Academy courses, progress tracking, multi-user support |
+| Offline Maps | ProtoMaps | Downloadable regional maps with search and navigation |
+| Data Tools | CyberChef | Encryption, encoding, hashing, and data analysis |
+| Notes | FlatNotes | Local note-taking with markdown support |
+| System Benchmark | Built-in | Hardware scoring, Builder Tags, and community leaderboard |
## Device Requirements
+
While many similar offline survival computers are designed to be run on bare-minimum, lightweight hardware, Project N.O.M.A.D. is quite the opposite. To install and run the
available AI tools, we highly encourage the use of a beefy, GPU-backed device to make the most of your install.
At it's core, however, N.O.M.A.D. is still very lightweight. For a barebones installation of the management application itself, the following minimal specs are required:
-*Note: Project N.O.M.A.D. is not sponsored by any hardware manufacturer and is designed to be as hardware-agnostic as possible. The harware listed below is for example/comparison use only*
+_Note: Project N.O.M.A.D. is not sponsored by any hardware manufacturer and is designed to be as hardware-agnostic as possible. The harware listed below is for example/comparison use only_
#### Minimum Specs
+
- Processor: 2 GHz dual-core processor or better
- RAM: 4GB system memory
- Storage: At least 5 GB free disk space
@@ -82,6 +103,7 @@ At it's core, however, N.O.M.A.D. is still very lightweight. For a barebones ins
To run LLM's and other included AI tools:
#### Optimal Specs
+
- Processor: AMD Ryzen 7 or Intel Core i7 or better
- RAM: 32 GB system memory
- Graphics: NVIDIA RTX 3060 or AMD equivalent or better (more VRAM = run larger models)
@@ -94,20 +116,24 @@ To run LLM's and other included AI tools:
Again, Project N.O.M.A.D. itself is quite lightweight - it's the tools and resources you choose to install with N.O.M.A.D. that will determine the specs required for your unique deployment
#### Running AI models on a different host
+
By default, N.O.M.A.D.'s installer will attempt to setup Ollama on the host when the AI Assistant is installed. However, if you would like to run the AI model on a different host, you can go to the settings of of the AI assistant and input a URL for either an ollama or OpenAI-compatible API server (such as LM Studio).
Note that if you use Ollama on a different host, you must start the server with this option `OLLAMA_HOST=0.0.0.0`.
Ollama is the preferred way to use the AI assistant as it has features such as model download that OpenAI API does not support. So when using LM Studio for example, you will have to use LM Studio to download models.
You are responsible for the setup of Ollama/OpenAI server on the other host.
## Frequently Asked Questions (FAQ)
+
For answers to common questions about Project N.O.M.A.D., please see our [FAQ](FAQ.md) page.
## About Internet Usage & Privacy
+
Project N.O.M.A.D. is designed for offline usage. An internet connection is only required during the initial installation (to download dependencies) and if you (the user) decide to download additional tools and resources at a later time. Otherwise, N.O.M.A.D. does not require an internet connection and has ZERO built-in telemetry.
To test internet connectivity, N.O.M.A.D. attempts to make a request to Cloudflare's utility endpoint, `https://1.1.1.1/cdn-cgi/trace` and checks for a successful response.
## About Security
+
By design, Project N.O.M.A.D. is intended to be open and available without hurdles - it includes no authentication. If you decide to connect your device to a local network after install (e.g. for allowing other devices to access it's resources), you can block/open ports to control which services are exposed.
**Will authentication be added in the future?** Maybe. It's not currently a priority, but if there's enough demand for it, we may consider building in an optional authentication layer in a future release to support uses cases where multiple users need access to the same instance but with different permission levels (e.g. family use with parental controls, classroom use with teacher/admin accounts, etc.). We have a suggestion for this on our public roadmap, so if this is something you'd like to see, please upvote it here: https://roadmap.projectnomad.us/posts/1/user-authentication-please-build-in-user-auth-with-admin-user-roles
@@ -115,6 +141,7 @@ By design, Project N.O.M.A.D. is intended to be open and available without hurdl
For now, we recommend using network-level controls to manage access if you're planning to expose your N.O.M.A.D. instance to other devices on a local network. N.O.M.A.D. is not designed to be exposed directly to the internet, and we strongly advise against doing so unless you really know what you're doing, have taken appropriate security measures, and understand the risks involved.
## Contributing
+
Contributions are welcome and appreciated! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines on how to contribute to the project.
## Community & Resources
@@ -131,28 +158,35 @@ Contributions are welcome and appreciated! Please see [CONTRIBUTING.md](CONTRIBU
Project N.O.M.A.D. is licensed under the [Apache License 2.0](LICENSE).
## Helper Scripts
+
Once installed, Project N.O.M.A.D. has a few helper scripts should you ever need to troubleshoot issues or perform maintenance that can't be done through the Command Center. All of these scripts are found in Project N.O.M.A.D.'s install directory, `/opt/project-nomad`
###
###### Start Script - Starts all installed project containers
+
```bash
sudo bash /opt/project-nomad/start_nomad.sh
```
+
###
###### Stop Script - Stops all installed project containers
+
```bash
sudo bash /opt/project-nomad/stop_nomad.sh
```
+
###
-###### Update Script - Attempts to pull the latest images for the Command Center and its dependencies (i.e. mysql) and recreate the containers. Note: this *only* updates the Command Center containers. It does not update the installable application containers - that should be done through the Command Center UI
+###### Update Script - Attempts to pull the latest images for the Command Center and its dependencies (i.e. mysql) and recreate the containers. Note: this _only_ updates the Command Center containers. It does not update the installable application containers - that should be done through the Command Center UI
+
```bash
sudo bash /opt/project-nomad/update_nomad.sh
```
###### Uninstall Script - Need to start fresh? Use the uninstall script to make your life easy. Note: this cannot be undone!
+
```bash
curl -fsSL https://raw.githubusercontent.com/Crosstalk-Solutions/project-nomad/refs/heads/main/install/uninstall_nomad.sh -o uninstall_nomad.sh && sudo bash uninstall_nomad.sh
```
diff --git a/admin/app/controllers/local_library_controller.ts b/admin/app/controllers/local_library_controller.ts
new file mode 100644
index 0000000..aa26dd9
--- /dev/null
+++ b/admin/app/controllers/local_library_controller.ts
@@ -0,0 +1,150 @@
+import { EmbedFileJob } from '#jobs/embed_file_job'
+import { LocalLibraryService } from '#services/local_library_service'
+import {
+ localLibraryFilenameValidator,
+ localLibraryRenameValidator,
+} from '#validators/local_library'
+import { inject } from '@adonisjs/core'
+import type { HttpContext } from '@adonisjs/core/http'
+
+@inject()
+export default class LocalLibraryController {
+ constructor(private localLibraryService: LocalLibraryService) {}
+
+ async page({ inertia }: HttpContext) {
+ return inertia.render('local-library')
+ }
+
+ async list({ response }: HttpContext) {
+ return response.status(200).json({ files: await this.localLibraryService.list() })
+ }
+
+ async upload({ request, response }: HttpContext) {
+ const uploadedFile = request.file('file')
+ if (!uploadedFile) return response.status(400).json({ message: 'No file uploaded' })
+
+ try {
+ await this.localLibraryService.ensureStorage()
+ const name = this.localLibraryService.sanitizeUploadName(uploadedFile.clientName)
+ await uploadedFile.move(this.localLibraryService.getStoragePath(), { name, overwrite: true })
+ return response
+ .status(201)
+ .json({ message: 'File uploaded', files: await this.localLibraryService.list() })
+ } catch (error: any) {
+ if (error.message === 'unsupported_file_type') {
+ return response.status(400).json({ message: 'Unsupported library file type' })
+ }
+ if (error.message === 'invalid_filename') {
+ return response.status(400).json({ message: 'Invalid filename' })
+ }
+ throw error
+ }
+ }
+
+ async view({ request, response }: HttpContext) {
+ const payload = await request.validateUsing(localLibraryFilenameValidator)
+ try {
+ const file = await this.localLibraryService.stream(payload.params.filename)
+ response.header('Content-Type', file.contentType)
+ response.header('Content-Length', String(file.size))
+ response.header(
+ 'Content-Disposition',
+ `inline; filename="${encodeURIComponent(file.filename)}"`
+ )
+ return response.stream(file.stream)
+ } catch (error: any) {
+ if (['not_found', 'invalid_filename'].includes(error.message)) {
+ return response.status(404).json({ message: 'File not found' })
+ }
+ throw error
+ }
+ }
+
+ async download({ request, response }: HttpContext) {
+ const payload = await request.validateUsing(localLibraryFilenameValidator)
+ try {
+ const file = await this.localLibraryService.stream(payload.params.filename)
+ response.header('Content-Type', file.contentType)
+ response.header('Content-Length', String(file.size))
+ response.header(
+ 'Content-Disposition',
+ `attachment; filename="${encodeURIComponent(file.filename)}"`
+ )
+ return response.stream(file.stream)
+ } catch (error: any) {
+ if (['not_found', 'invalid_filename'].includes(error.message)) {
+ return response.status(404).json({ message: 'File not found' })
+ }
+ throw error
+ }
+ }
+
+ async preview({ request, response }: HttpContext) {
+ const payload = await request.validateUsing(localLibraryFilenameValidator)
+ try {
+ return response
+ .status(200)
+ .json(await this.localLibraryService.preview(payload.params.filename))
+ } catch (error: any) {
+ if (error.message === 'preview_unsupported') {
+ return response.status(415).json({ message: 'Preview is not supported for this file type' })
+ }
+ if (['not_found', 'invalid_filename'].includes(error.message)) {
+ return response.status(404).json({ message: 'File not found' })
+ }
+ throw error
+ }
+ }
+
+ async rename({ request, response }: HttpContext) {
+ const payload = await request.validateUsing(localLibraryRenameValidator)
+ try {
+ return response.status(200).json({
+ file: await this.localLibraryService.rename(payload.params.filename, payload.name),
+ })
+ } catch (error: any) {
+ if (['not_found', 'invalid_filename'].includes(error.message)) {
+ return response.status(404).json({ message: 'File not found' })
+ }
+ if (error.message === 'unsupported_file_type') {
+ return response.status(400).json({ message: 'Unsupported library file type' })
+ }
+ throw error
+ }
+ }
+
+ async delete({ request, response }: HttpContext) {
+ const payload = await request.validateUsing(localLibraryFilenameValidator)
+ try {
+ await this.localLibraryService.remove(payload.params.filename)
+ return response.status(200).json({ message: 'File deleted' })
+ } catch (error: any) {
+ if (['not_found', 'invalid_filename'].includes(error.message) || error.code === 'ENOENT') {
+ return response.status(404).json({ message: 'File not found' })
+ }
+ throw error
+ }
+ }
+
+ async index({ request, response }: HttpContext) {
+ const payload = await request.validateUsing(localLibraryFilenameValidator)
+ try {
+ const file = await this.localLibraryService.stream(payload.params.filename)
+ const result = await EmbedFileJob.dispatch({
+ filePath: file.fullPath,
+ fileName: file.filename,
+ fileSize: file.size,
+ })
+ return response.status(202).json({
+ message: result.message,
+ jobId: result.jobId,
+ alreadyProcessing: !result.created,
+ })
+ } catch (error: any) {
+ if (['not_found', 'invalid_filename'].includes(error.message)) {
+ return response.status(404).json({ message: 'File not found' })
+ }
+ throw error
+ }
+ }
+}
diff --git a/admin/app/controllers/mac_ai_controller.ts b/admin/app/controllers/mac_ai_controller.ts
new file mode 100644
index 0000000..51e7a46
--- /dev/null
+++ b/admin/app/controllers/mac_ai_controller.ts
@@ -0,0 +1,62 @@
+import { MacAiService } from '#services/mac_ai_service'
+import { RagService } from '#services/rag_service'
+import { assertNotCloudMetadataUrl } from '#validators/common'
+import { inject } from '@adonisjs/core'
+import type { HttpContext } from '@adonisjs/core/http'
+import type { MacAiProvider } from '../../types/mac_ai.js'
+import Service from '#models/service'
+import KVStore from '#models/kv_store'
+import { SERVICE_NAMES } from '../../constants/service_names.js'
+import logger from '@adonisjs/core/services/logger'
+
+@inject()
+export default class MacAiController {
+ constructor(
+ private macAiService: MacAiService,
+ private ragService: RagService
+ ) {}
+
+ async status({ response }: HttpContext) {
+ return response.status(200).json(await this.macAiService.status())
+ }
+
+ async configure({ request, response }: HttpContext) {
+ const provider = request.input('provider', 'ollama') as MacAiProvider
+ if (!['ollama', 'remote', 'native_mlx', 'native_coreml'].includes(provider)) {
+ return response.status(400).json({ success: false, message: 'Unsupported AI provider.' })
+ }
+
+ const workerUrl = request.input('workerUrl', undefined) as string | null | undefined
+ if (workerUrl && workerUrl.trim()) {
+ try {
+ assertNotCloudMetadataUrl(workerUrl)
+ } catch (error) {
+ return response.status(400).json({
+ success: false,
+ message: error instanceof Error ? error.message : 'Invalid native worker URL.',
+ })
+ }
+ }
+
+ const result = await this.macAiService.configure({
+ provider,
+ workerUrl,
+ modelRoot: request.input('modelRoot', undefined),
+ })
+
+ if (provider === 'native_mlx' || provider === 'native_coreml' || provider === 'remote') {
+ const aiService = await Service.query().where('service_name', SERVICE_NAMES.OLLAMA).first()
+ if (aiService) {
+ aiService.installed = true
+ aiService.installation_status = 'idle'
+ await aiService.save()
+ }
+ await KVStore.setValue('chat.suggestionsEnabled', false)
+ this.ragService.discoverNomadDocs().catch((error) => {
+ logger.error('[MacAiController] Failed to discover Nomad docs:', error)
+ })
+ }
+
+ return response.status(200).json(result)
+ }
+}
diff --git a/admin/app/controllers/ollama_controller.ts b/admin/app/controllers/ollama_controller.ts
index 3bf9e73..9067a16 100644
--- a/admin/app/controllers/ollama_controller.ts
+++ b/admin/app/controllers/ollama_controller.ts
@@ -21,7 +21,7 @@ export default class OllamaController {
private dockerService: DockerService,
private ollamaService: OllamaService,
private ragService: RagService
- ) { }
+ ) {}
async availableModels({ request }: HttpContext) {
const reqData = await request.validateUsing(getAvailableModelsSchema)
@@ -83,7 +83,9 @@ export default class OllamaController {
0.3 // Minimum similarity score of 0.3
)
- logger.debug(`[RAG] Retrieved ${relevantDocs.length} relevant documents for query: "${rewrittenQuery}"`)
+ logger.debug(
+ `[RAG] Retrieved ${relevantDocs.length} relevant documents for query: "${rewrittenQuery}"`
+ )
// If relevant context is found, inject as a system message with adaptive limits
if (relevantDocs.length > 0) {
@@ -107,7 +109,10 @@ export default class OllamaController {
)
const contextText = trimmedDocs
- .map((doc, idx) => `[Context ${idx + 1}] (Relevance: ${(doc.score * 100).toFixed(1)}%)\n${doc.text}`)
+ .map(
+ (doc, idx) =>
+ `[Context ${idx + 1}] (Relevance: ${(doc.score * 100).toFixed(1)}%)\n${doc.text}`
+ )
.join('\n\n')
const systemMessage = {
@@ -132,13 +137,19 @@ export default class OllamaController {
if (estimatedSystemTokens > 3000) {
const needed = estimatedSystemTokens + 2048 // leave room for conversation + response
numCtx = [8192, 16384, 32768, 65536].find((n) => n >= needed) ?? 65536
- logger.debug(`[OllamaController] Large system prompt (~${estimatedSystemTokens} tokens), requesting num_ctx: ${numCtx}`)
+ logger.debug(
+ `[OllamaController] Large system prompt (~${estimatedSystemTokens} tokens), requesting num_ctx: ${numCtx}`
+ )
}
// Check if the model supports "thinking" capability for enhanced response generation
// If gpt-oss model, it requires a text param for "think" https://docs.ollama.com/api/chat
const thinkingCapability = await this.ollamaService.checkModelHasThinking(reqData.model)
- const think: boolean | 'medium' = thinkingCapability ? (reqData.model.startsWith('gpt-oss') ? 'medium' : true) : false
+ const think: boolean | 'medium' = thinkingCapability
+ ? reqData.model.startsWith('gpt-oss')
+ ? 'medium'
+ : true
+ : false
// Separate sessionId from the Ollama request payload — Ollama rejects unknown fields
const { sessionId, ...ollamaRequest } = reqData
@@ -154,7 +165,9 @@ export default class OllamaController {
}
if (reqData.stream) {
- logger.debug(`[OllamaController] Initiating streaming response for model: "${reqData.model}" with think: ${think}`)
+ logger.debug(
+ `[OllamaController] Initiating streaming response for model: "${reqData.model}" with think: ${think}`
+ )
// Headers already flushed above
const stream = await this.ollamaService.chatStream({ ...ollamaRequest, think, numCtx })
let fullContent = ''
@@ -171,9 +184,13 @@ export default class OllamaController {
await this.chatService.addMessage(sessionId, 'assistant', fullContent)
const messageCount = await this.chatService.getMessageCount(sessionId)
if (messageCount <= 2 && userContent) {
- this.chatService.generateTitle(sessionId, userContent, fullContent, reqData.model).catch((err) => {
- logger.error(`[OllamaController] Title generation failed: ${err instanceof Error ? err.message : err}`)
- })
+ this.chatService
+ .generateTitle(sessionId, userContent, fullContent, reqData.model)
+ .catch((err) => {
+ logger.error(
+ `[OllamaController] Title generation failed: ${err instanceof Error ? err.message : err}`
+ )
+ })
}
}
return
@@ -186,9 +203,13 @@ export default class OllamaController {
await this.chatService.addMessage(sessionId, 'assistant', result.message.content)
const messageCount = await this.chatService.getMessageCount(sessionId)
if (messageCount <= 2 && userContent) {
- this.chatService.generateTitle(sessionId, userContent, result.message.content, reqData.model).catch((err) => {
- logger.error(`[OllamaController] Title generation failed: ${err instanceof Error ? err.message : err}`)
- })
+ this.chatService
+ .generateTitle(sessionId, userContent, result.message.content, reqData.model)
+ .catch((err) => {
+ logger.error(
+ `[OllamaController] Title generation failed: ${err instanceof Error ? err.message : err}`
+ )
+ })
}
}
@@ -223,7 +244,9 @@ export default class OllamaController {
const ollamaService = await Service.query().where('service_name', SERVICE_NAMES.OLLAMA).first()
if (!ollamaService) {
- return response.status(404).send({ success: false, message: 'Ollama service record not found.' })
+ return response
+ .status(404)
+ .send({ success: false, message: 'Ollama service record not found.' })
}
// Clear path: null or empty URL removes remote config. If a local nomad_ollama container
@@ -231,6 +254,7 @@ export default class OllamaController {
// the service marked installed. Otherwise fall back to uninstalled.
if (!remoteUrl || remoteUrl.trim() === '') {
await KVStore.clearValue('ai.remoteOllamaUrl')
+ await KVStore.setValue('ai.provider', 'ollama')
const hasLocalContainer = await this._startLocalOllamaContainerIfExists()
ollamaService.installed = hasLocalContainer
ollamaService.installation_status = 'idle'
@@ -272,6 +296,7 @@ export default class OllamaController {
// Save remote URL and mark service as installed
await KVStore.setValue('ai.remoteOllamaUrl', remoteUrl.trim())
+ await KVStore.setValue('ai.provider', 'remote')
ollamaService.installed = true
ollamaService.installation_status = 'idle'
await ollamaService.save()
@@ -300,9 +325,7 @@ export default class OllamaController {
private async _stopLocalOllamaContainer(): PromiseLoading preview...
+ ) : ( +
+ {preview?.text || 'No readable text preview was found.'}
+
+ )}
+
+
+ ) : (
+ <>
+
+
+ Choose a file
++ PDFs open here without leaving Command Center. +
+
+
+
+
+
+ + {selected.displayName} +
++ {selected.type.toUpperCase()} • {formatBytes(selected.size)} +
+
+ {selected.canIndex && (
+ indexFile(selected)}
+ >
+ Index for AI
+
+ )}
+
+
+
+
+ deleteFile(selected)}
+ >
+ Delete
+
+
+
+ {selected.type === 'pdf' && selected.viewUrl ? (
+
+ ) : selected.type === 'epub' || selected.type === 'text' ? (
+
+ {previewLoading ? (
+
+ ) : (
+
+
+ )}
+
+
+ )}
+
+
+ + This file is stored locally and can be downloaded, but preview is not + available. +
+