document.md

# Student & Developer Documentation

## Overview
Welcome to the RemiAI Framework! This document is designed to help you understand how to customize, configure, and make this application your own. This framework is built to be "Plug-and-Play"—meaning you don't need to know Python or complex AI coding to use it. It includes **Text Generation** (chat with AI), **Text-to-Speech** (TTS — convert text to voice), and **Speech-to-Text** (STT — extract text from audio files), all running 100% offline.

## 🛠️ Setup & How to Customize

### 0. Quick Setup (Important!)
Before running the app, you **must** ensure the AI engine files are downloaded correctly. GitHub does not store large files directly, so we use **Git LFS**.

1.  **Install Git LFS**:
    *   Download and install from [git-lfs.com](https://git-lfs.com).
    *   Open a terminal and run: `git lfs install`
2.  **Pull Files**:
    *   Run: `git lfs pull` inside the project folder.
    *   *Why?* Without this, the app will say **"RemiAI Engine Missing"** or "Connection Refused".

### 1. Changing the AI Name
Want to name the AI "Jarvis" or "MyBot"?
1.  Open `index.html` in any text editor (VS Code, Notepad, etc.).
2.  Search for "RemiAI" or "Bujji".
3.  Replace the text with your desired name.
4.  Save the file.
5.  Restart the app (`npm start`), and your new name will appear!

### 2. Replacing the AI Models (LLM, TTS, STT)
This framework is a **Universal Wrapper**. You can swap out any of the three "brains" (Text, Speech, Hearing) to build your own dedicated application.

#### A. Changing the Chat Model (Text Generation)
1.  **Download**: Get a `.gguf` model from Hugging Face (e.g., `Llama-3-8B-GGUF`).
2.  **Rename**: Rename it to `model.gguf`.
3.  **Replace**: Overwrite the existing `model.gguf` in the root folder.
4.  **Restart**: Run `npm start`.

#### B. Changing the Text-to-Speech (TTS) Voice
The framework uses **Piper TTS**.
1.  **Download**: Get a voice model (`.onnx`) and its config (`.json`) from [Piper Voices](https://github.com/rhasspy/piper/blob/master/VOICES.md).
2.  **Place Files**: Put both files in `engine/piper/` (e.g., `my-voice.onnx` and `my-voice.onnx.json`).
3.  **Update Code**:
    *   Open `main.js`.
    *   Search for: `engine/piper/en_US-lessac-medium.onnx`
    *   Replace the filename with your new `.onnx` file name.
4.  **Restart**: Run `npm start`.

#### C. Changing the Speech-to-Text (STT) Engine
The framework uses **Whisper.cpp**.
1.  **Download**: Get a model in GGML/Binary format (`ggml-*.bin`) from [Hugging Face (ggerganov/whisper.cpp)](https://huggingface.co/ggerganov/whisper.cpp).
2.  **Place File**: Put the file in `engine/whisper/`.
3.  **Update Code**:
    *   Open `main.js`.
    *   Search for: `engine/whisper/ggml-base.en.bin`
    *   Replace the filename with your new `.bin` file name.
4.  **Restart**: Run `npm start`.

**Hardware Warning**:
*   **Good Configuration**: i3 (8GB RAM) for basic usage.
*   **Recommended**: i5 (16GB RAM) for larger models.
*   *Note: Using models larger than your RAM capacity will crash your computer. Stick to "Q4_K_M" quantizations for the best balance.*

### 3. Customizing the UI
All styles are in `styles.css` (or within `index.html`).
*   **Colors**: Change the background colors or chat bubble colors in the CSS.
*   **Icons**: Replace `remiai.ico` with your own `.ico` file to change the app icon.

### 4. Using Text-to-Speech (TTS)
The TTS feature converts typed text into natural-sounding English speech using the **Piper** engine.

**How to Use:**
1.  Click the **🔊 Speaker icon** in the sidebar.
2.  Type the text you want to hear in the text area.
3.  Click **"Speak"** — the audio will generate and play automatically.
4.  Click **"Download Audio"** to save the `.wav` file to your preferred location (a native Save dialog will appear).

**Customization:**
*   The TTS voice model is stored at `engine/piper/en_US-lessac-medium.onnx`.
*   You can replace it with other Piper ONNX voice models from [Piper Voices](https://github.com/rhasspy/piper/blob/master/VOICES.md).
*   Download a new `.onnx` model + its `.json` config file and place them in `engine/piper/`.

### 5. Using Speech-to-Text (STT)
The STT feature extracts text from audio files using the **Whisper** engine (runs as a local server).

**How to Use:**
1.  Click the **🎙️ Microphone icon** in the sidebar.
2.  Click **"Browse Audio File"** to select your audio file.
3.  Supported formats: `.wav`, `.mp3`, `.m4a`, `.ogg`, `.flac`.
4.  Click **"Transcribe"** — wait for processing (10-30 seconds depending on file length).
5.  The transcribed text will appear below. Click **"Copy"** to copy it to your clipboard.

**Requirements:**
*   `ffmpeg.exe` and `ffmpeg.dll` must be present in the `bin/` folder for audio format conversion.
*   If missing, download FFmpeg from [ffmpeg.org](https://ffmpeg.org/download.html) and place the files in `bin/`.

### 6. Dynamic Resource Management (New!)
To ensure the application runs smoothly even on lower-end devices, we implemented a dynamic resource management system.
*   **Behavior**: When you are in the **Chat** tab, the heavy AI model (Text Generation) is loaded into RAM.
*   **Optimization**: When you switch to **TTS**, **STT**, or **Web Browser** tabs, the main AI model is **automatically unloaded/stopped**. This frees up to 2GB+ of RAM and significant CPU usage, allowing the TTS/STT engines to run faster and the browser to be more responsive.
*   **Reloading**: When you switch back to the **Chat** tab, the model automatically restarts.
*   *Note: You might see "Connecting..." for a few seconds. If it stays stuck, click the "Refresh App" button.*

### 7. Offline Dependencies
All libraries are bundled locally — **no internet needed** after initial setup:
*   **Lucide Icons**: Loaded from `node_modules/lucide/` (not from CDN).
*   **Marked.js**: Loaded from `node_modules/marked/` (not from CDN).
*   If icons or markdown rendering is broken, simply run `npm install` to restore them.

## ❓ Frequently Asked Questions (FAQ)

**Q: Do I need Python?**
A: **No.** The application comes with a pre-compiled engine (`bujji_engine.exe` / `llama-server.exe`) that runs the model directly.

**Q: Why does it say "AVX2"?**
A: AVX2 is a feature in modern CPUs that makes the AI run faster. The app automatically detects if you have it. If not, it switches to a slower but compatible mode (AVX).

**Q: The app opens but doesn't reply / "RemiAI Engine Missing" Error.**
A: 
1.  **Git LFS Issue**: This usually means you downloaded "pointers" (tiny files) instead of the real engine. Open a terminal in the folder and run `git lfs pull`.
2.  **Model Issue**: Check if `model.gguf` exists in the `engine` folder.
3.  **Console Check**: Open Developer Tools (Ctrl+Shift+I) to see errors.

**Q: I see "Content Security Policy" warnings in the console.**
A: We have configured safeguards (`index.html` meta tags) to block malicious scripts. The CSP is set to only allow local resources (`'self'`) and the local API server (`127.0.0.1:5000`). All external CDN dependencies have been removed.

**Q: How do I build it into an .exe file?**
A: Run the command:
```bash
npm run dist
```
This will create an installer in the `release` folder that you can share with friends! 

`if you are facing errors while building open the power shell as an administrator and run the above command then it will works 100%`

**Q: TTS says "Piper TTS executable not found".**
A: Make sure `piper.exe` exists in `engine/cpu_avx2/` (or `engine/cpu_avx/`). Run `git lfs pull` to download all engine binaries.

**Q: STT says "Whisper server failed to start".**
A: 
1.  Check that `whisper.exe` exists in `engine/cpu_avx2/` (or `engine/cpu_avx/`).
2.  Check that `ffmpeg.exe` and `ffmpeg.dll` are present in the `bin/` folder. The Whisper server needs FFmpeg for audio conversion.
3.  Run `git lfs pull` to ensure all files are fully downloaded.

**Q: STT says "No speech detected".**
A: Make sure your audio file contains clear English speech. Background noise or non-English audio may cause transcription failures. Try with a clear `.wav` recording first.

**Q: Can I use TTS and STT together?**
A: Yes! You can generate speech with TTS, save the `.wav` file, then upload it to STT to verify the transcription. They work independently and can be used simultaneously.

**Q: Does the app need internet to work?**
A: **No.** After the initial `npm install` and `git lfs pull` setup, the app runs 100% offline. All models, engines, icons, and libraries are bundled locally.