Add installation scripts and update documentation for Phase 3 features

INSTALLATION.md

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+# Installation Guide for OBS Recording Transcriber
+
+This guide will help you install all the necessary dependencies for the OBS Recording Transcriber application, including the advanced features from Phase 3.
+
+## Prerequisites
+
+Before installing the Python packages, you need to set up some prerequisites:
+
+### 1. Python 3.8 or higher
+
+Make sure you have Python 3.8 or higher installed. You can download it from [python.org](https://www.python.org/downloads/).
+
+### 2. FFmpeg
+
+FFmpeg is required for audio processing:
+
+- **Windows**: 
+  - Download from [gyan.dev/ffmpeg/builds](https://www.gyan.dev/ffmpeg/builds/)
+  - Extract the ZIP file
+  - Add the `bin` folder to your system PATH
+
+- **macOS**:
+  ```bash
+  brew install ffmpeg
+  ```
+
+- **Linux**:
+  ```bash
+  sudo apt update
+  sudo apt install ffmpeg
+  ```
+
+### 3. Visual C++ Build Tools (Windows only)
+
+Some packages like `tokenizers` require C++ build tools:
+
+1. Download and install [Visual C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/)
+2. During installation, select "Desktop development with C++"
+
+## Installation Steps
+
+### 1. Create a Virtual Environment (Recommended)
+
+```bash
+# Create a virtual environment
+python -m venv venv
+
+# Activate the virtual environment
+# Windows
+venv\Scripts\activate
+# macOS/Linux
+source venv/bin/activate
+```
+
+### 2. Install PyTorch
+
+For better performance, install PyTorch with CUDA support if you have an NVIDIA GPU:
+
+```bash
+# Windows/Linux with CUDA
+pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
+
+# macOS or CPU-only
+pip install torch torchvision torchaudio
+```
+
+### 3. Install Dependencies
+
+```bash
+# Install all dependencies from requirements.txt
+pip install -r requirements.txt
+```
+
+### 4. Troubleshooting Common Issues
+
+#### Tokenizers Installation Issues
+
+If you encounter issues with `tokenizers` installation:
+
+1. Make sure you have Visual C++ Build Tools installed (Windows)
+2. Try installing Rust: [rustup.rs](https://rustup.rs/)
+3. Install tokenizers separately:
+   ```bash
+   pip install tokenizers --no-binary tokenizers
+   ```
+
+#### PyAnnote.Audio Access
+
+To use speaker diarization, you need a HuggingFace token with access to the pyannote models:
+
+1. Create an account on [HuggingFace](https://huggingface.co/)
+2. Generate an access token at [huggingface.co/settings/tokens](https://huggingface.co/settings/tokens)
+3. Request access to [pyannote/speaker-diarization-3.0](https://huggingface.co/pyannote/speaker-diarization-3.0)
+4. Set the token in the application when prompted or as an environment variable:
+   ```bash
+   # Windows
+   set HF_TOKEN=your_token_here
+   # macOS/Linux
+   export HF_TOKEN=your_token_here
+   ```
+
+#### Memory Issues with Large Files
+
+If you encounter memory issues with large files:
+
+1. Use a smaller Whisper model (e.g., "base" instead of "large")
+2. Reduce the GPU memory fraction in the application settings
+3. Increase your system's swap space/virtual memory
+
+## Running the Application
+
+After installation, run the application with:
+
+```bash
+streamlit run app.py
+```
+
+## Optional: Ollama Setup for Local Summarization
+
+To use Ollama for local summarization:
+
+1. Install Ollama from [ollama.ai](https://ollama.ai/)
+2. Pull a model:
+   ```bash
+   ollama pull llama3
+   ```
+3. Uncomment the Ollama line in requirements.txt and install:
+   ```bash
+   pip install ollama
+   ```
+
+## Verifying Installation
+
+To verify that all components are working correctly:
+
+1. Run the application
+2. Check that GPU acceleration is available (if applicable)
+3. Test a small video file with basic transcription
+4. Gradually enable advanced features like diarization and translation
+
+If you encounter any issues, check the application logs for specific error messages.