docs: rewrite README with verified setup, web deploy and limitations
Documents only what was executed on Linux (Node 24, npm): install, tsc, expo lint, web export and a headless-browser E2E against a mock of the LM Studio /v1 API. Also fixes the clone URL, which pointed at the old LocalAiApp repository name.
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# LocalMind
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# LocalMind
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**Chat client for local LLMs served by LM Studio. React Native + Expo app (Android, iOS and web) where every message stays on your own network: no cloud, no API key, no telemetry.**
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> A fully local, privacy-first AI companion app built with React Native and Expo. Your data never leaves your device.
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This application connects directly to your own local AI models, completely offline. Currently in alpha, it pairs flawlessly with the [LMStudio](https://lmstudio.ai) local inference API. We developed and tested it against **Qwen3.5 (without thinking)** to guarantee a smooth, zero-latency experience.
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## About
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*Roadmap: Future updates will introduce direct in-app model downloads and support for external APIs.*
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Running a model locally in LM Studio is easy; having a decent chat UI for it on the phone is not. LocalMind is that client: it talks straight to the LM Studio local server (the OpenAI-compatible `/v1` endpoints) over your LAN or `localhost`, streams the answer token by token, keeps chat sessions on the device and renders Markdown with code blocks.
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---
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It is an alpha project. There is no backend, no account and no server to deploy: the app is only the client, and the model runs on your machine.
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## Features
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## How it works
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- **100% Offline Inference:** Complete privacy. Zero cloud dependency.
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```
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- **Plug & Play LMStudio:** Instantly detects and fetches active models from your local server.
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Expo app (Android / iOS / web)
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- **Persistent Sessions:** Chat histories and settings are saved locally using Zustand and `AsyncStorage`.
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app/chat, app/settings ......... screens (expo-router, file based)
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- **Developer-Friendly UI:** Real-time markdown rendering with syntax highlighting and 1-click code copying.
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hooks/useLMStudio .............. sendMessage / regenerate / stop, stream callbacks
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- **Minimalist Dark Mode:** High-contrast, distraction-free interface built on NativeWind principles.
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services/lmStudioApi ........... HTTP + SSE client
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store/useAppStore .............. Zustand + AsyncStorage (sessions, settings, theme)
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| GET /v1/models
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| POST /v1/chat/completions (stream: true -> SSE)
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v
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LM Studio local server (default http://localhost:1234)
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```
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---
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- The connection settings (host, port, optional API key) live in the Zustand store and are persisted with `AsyncStorage`.
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- `services/lmStudioApi.ts` builds the base URL as `http(s)://<host>:<port>/v1` and streams the response: `XMLHttpRequest` progress events on native platforms, `fetch` + `ReadableStream` on web.
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- Each request carries a fixed system prompt (`constants/SystemPrompt.ts`); `temperature` is `0.7` and `max_tokens` is `2048`.
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- Every finished exchange is saved as a chat session (title taken from the first user message), so History can reload it later.
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## Quick Start
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## Stack
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To run this application, you will need both the frontend development environment and a local AI engine running.
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| Layer | Choice |
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| Runtime | Expo SDK 54, React Native 0.81.5, React 19.1 |
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| Routing | expo-router 6 (typed routes experiment on, React Compiler experiment on) |
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| State | Zustand 5 with `persist` + `@react-native-async-storage/async-storage` |
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| Animation / gestures | react-native-reanimated 4, react-native-gesture-handler |
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| Icons | lucide-react-native |
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| Markdown | `@ronradtke/react-native-markdown-display` |
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| Streaming | XMLHttpRequest (native) / fetch ReadableStream (web) |
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| Tooling | TypeScript 5.9 (`strict`), ESLint 9 flat config (`eslint-config-expo`) |
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| Model server | LM Studio local server, OpenAI-compatible `/v1` API |
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### 1. Model Server (LMStudio)
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## Requirements
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1. Extract and open [LMStudio](https://lmstudio.ai/).
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- Node.js `>= 20.19.4` (required by React Native 0.81.5; verified here on Node 24.20.0)
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2. Download a compatible model (e.g., Llama 3, Qwen2.5, Mistral).
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- npm (or pnpm) to install dependencies
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3. Open the **Local Server** tab (`<->`).
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- [LM Studio](https://lmstudio.ai) with a model downloaded, the local server started and **CORS enabled** (Local Server tab, default port `1234`)
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4. Enable **CORS** and set the port (default: `1234`).
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- To run the app: [Expo Go](https://expo.dev/go) on a physical device, an Android/iOS emulator, or a browser for the web target
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5. Click **Start Server**.
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> **Note:** If testing on a physical mobile device, locate your machine's local IPv4 address (e.g., `192.168.1.X`).
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## Quick start
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### 2. Mobile Client (App)
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Ensure you have [Node.js](https://nodejs.org/) (v18+) and the [Expo Go](https://expo.dev/go) app installed.
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```bash
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```bash
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git clone https://github.com/evandrodevbr/LocalAiApp.git
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git clone https://github.com/evandrodevbr/LocalMind.git
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cd LocalAiApp
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cd LocalMind
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npm install
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npm install
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npx expo start
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npx expo start
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```
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```
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Scan the QR code with Expo Go, or type `i`/`a` to launch a simulator.
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Then pick a target from the Expo CLI: `w` for web, `a` for Android, `i` for iOS, or scan the QR code with Expo Go.
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### 3. Connection
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Start the model side first:
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1. Open the app and tap the **Settings** icon.
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1. Open LM Studio, download a model and go to the **Local Server** tab (the `<->` icon).
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2. Enter your LMStudio server IP and Port (e.g., `192.168.1.X:1234`).
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2. Enable **CORS** and keep the port at `1234` (or note whatever you change it to).
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3. Tap **Test Connection**.
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3. Click **Start Server**.
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Once connected, your available models will load automatically.
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Finally, in the app:
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---
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1. Open **Settings** (gear icon in the chat header).
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2. Fill **Host IP / Address** and **Port Number**. On a physical device this must be your machine's LAN address (`192.168.x.x`), not `localhost`.
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3. Tap **Test Connection**. The badge turns to *Connected* and the model list becomes available in the chat header selector.
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## Bug Reports & Contributing
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## Usage
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Found an issue or have a suggestion? We welcome community involvement!
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| Screen | What it does |
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| Chat (`/chat`) | Conversation list with Markdown rendering, streaming answers, copy code blocks, edit / delete / regenerate a message, stop generation while it streams, model selector in the header, "new chat" button. |
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| History (`/chat/history`) | Saved sessions, most recent first, with message count and date; tap to reload, trash icon to delete. |
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| Settings (`/settings`) | Host, port and optional API key, connection test and status badge, light/dark toggle, app info. |
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👉 **[Report an Issue or Request a Feature](https://github.com/evandrodevbr/LocalAiApp/issues)**
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## API
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When creating an issue, please include:
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The app is a client of the LM Studio OpenAI-compatible API. Endpoints actually used:
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- A clear description of the bug.
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| Call | Where | Notes |
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- Steps to reproduce.
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- Relevant screenshots or environment details.
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| `GET /v1/models` | `testConnection()`, `getModels()` | The connection test aborts after 5 s; the model list feeds the header selector. |
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| `POST /v1/chat/completions` | `chatCompletion()`, `chatCompletionStream()` | Streaming (`stream: true`) is the path used by the chat; SSE lines with `choices[0].delta.content` are appended to the last message. |
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---
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- Base URL: `http://<host>:<port>/v1` (`http://` is prepended when the host has no scheme).
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- An `Authorization: Bearer <apiKey>` header is sent only when an API key is filled in.
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- `GET /v1/models` responds with the OpenAI shape `{ "data": [ { "id": ... } ] }`.
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## Acknowledgments
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## Web target
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Thank you for exploring this project! Our mission is to share knowledge and foster an open-source collaborative ecosystem around offline AI solutions. All feedback, testing, and code contributions are highly appreciated.
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The same codebase exports a static web build:
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<br>
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```bash
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<br>
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npx expo export --platform web # writes dist/
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npx serve dist # or any static server that maps /chat -> chat/index.html
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```
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The export generates `/`, `/chat`, `/chat/history`, `/settings`, `/_sitemap` and `/+not-found`. Use a static server that resolves extension-less URLs (`npx serve`, nginx `try_files $uri $uri.html $uri/ =404`); point unknown paths at `+not-found.html` for the app's 404 screen.
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## Project structure
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```
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app/
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├── _layout.tsx root stack, theme provider, splash screen
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├── index.tsx redirects to /chat
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├── +not-found.tsx 404 screen
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├── chat/
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│ ├── _layout.tsx chat header (model selector, history, new chat, settings)
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│ ├── index.tsx conversation screen, prompt suggestions, edit/regenerate
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│ └── history.tsx saved sessions
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└── settings/index.tsx server connection, appearance, about
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components/
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├── chat/ ChatInput, MessageBubble, MessageActions, ModelSelector, TypingIndicator
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└── ui/ Button, GlassCard, ConnectionBadge, ScreenWrapper, icons
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constants/ Colors, theme, SystemPrompt (system prompt sent to the model)
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hooks/ useLMStudio (chat flow), useThemeColor, useColorScheme
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services/ lmStudioApi (HTTP/SSE), types
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store/ useAppStore (Zustand + AsyncStorage)
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docs/ LM Studio API notes and design reference
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.agent/ AI development tooling (agents, skills, rules), not app code
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```
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## Verification
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There is no automated test suite in this repository. What exists and was actually run on Linux (Node 24.20.0, npm 11.19.0):
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| Command | Result |
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| `npm install` | exit 0 |
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| `npx tsc --noEmit` | exit 0, no type errors |
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| `npx expo lint` | exit 0, 0 errors and 3 warnings (`no-require-imports` twice and one `exhaustive-deps` in `app/chat/index.tsx`) |
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| `npx expo export --platform web` | exit 0, 6 static routes in `dist/` |
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| `npx expo start --web` | dev server serves the app on `http://localhost:8083`, no browser errors |
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End-to-end run of the exported web build in headless Chromium, against a local mock of the LM Studio `/v1` API:
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- `GET /v1/models` and `POST /v1/chat/completions` (SSE) reached the app: Test Connection returned *Connection successful*, and the header listed the mock model;
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- a message sent from the chat was answered by the mock and rendered incrementally: `Ola! Sou um modelo local rodando via mock do LM Studio. Teste E2E concluido com sucesso.`;
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- the session was persisted (`localStorage` key `localaiapp-storage`) and showed up in History with `2 msgs`;
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- zero uncaught page errors after the `import.meta` fix described below.
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Not verified in this environment: Android and iOS builds (no emulator or device available), and therefore the native streaming path via `XMLHttpRequest`.
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## Current state and limitations
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- Alpha. It was built against models served by LM Studio and has no fallback to any cloud API.
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- No auto-connect on launch: the app only checks the server from Settings or when the model selector is refreshed. Until then the chat shows *Server offline*.
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- `activeModelId` and `availableModels` are not persisted, so after restarting the app you have to select a model again.
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- `constants/Models.ts` (a Qwen model catalog) is not referenced anywhere in the app.
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- `react-native-sse` is declared in `package.json` but no code imports it.
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- Both `package-lock.json` and `pnpm-lock.yaml` are committed.
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- `app.json` still carries the previous project name (`LocalAiApp` / slug `localaiapp`) and the persisted storage key is `localaiapp-storage`.
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- No CI, no tests, no license file.
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## Documentation
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| Document | Content |
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| [`docs/Documentação de Implementaçoes Futuras.md`](docs/Documenta%C3%A7%C3%A3o%20de%20Implementa%C3%A7oes%20Futuras.md) | Notes on the LM Studio API (`/api/v0`, `/v1`, SDKs, CLI) and roadmap ideas (in Portuguese) |
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| [`docs/evandro-design-system.html`](docs/evandro-design-system.html) | Visual reference of the design system used in the UI |
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## License
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No license file is present in this repository. Without an explicit license the code is "all rights reserved" by default, so adding one (MIT, for example) is a pending decision of the project owner.
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Block a user