# Plan for Implementing High-Performance Batch Processing

This document outlines the necessary code modifications to implement a high-performance batch processing mode that can be toggled by the "Use VADER" checkbox in the GUI.

The goal is to create two distinct modes:
- **VADER On (Nuanced Mode):** Slower, processes chunks one-by-one with unique TTS parameters for nuanced delivery.
- **VADER Off (Batch Mode):** Significantly faster, processes chunks in batches with a single set of TTS parameters.

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## 1. File to Modify: `src/chatterbox/tts.py`

*   **Purpose:** To enable the core TTS model to handle batches of text.
*   **Changes Needed:**
    *   A new method, `generate_batch(self, texts: list, **tts_params)`, needs to be created within the `ChatterboxTTS` class.
    *   This method must perform the following steps:
        1.  Accept a list of text strings (`texts`).
        2.  Tokenize each text string in the list.
        3.  Pad the tokenized sequences to ensure they all have the same length, creating a single batch tensor. `torch.nn.utils.rnn.pad_sequence` is suitable for this.
        4.  Feed the complete batch tensor to the underlying model (`self.t3.inference` and `self.s3gen.inference`).
        5.  Return a list of the resulting audio waveforms.

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## 2. File to Modify: `modules/tts_engine.py`

*   **Purpose:** To orchestrate the new batching workflow and choose the processing mode.
*   **Changes Needed:**

    ### a. Create a New Worker Function
    *   Add a new function: `process_batch(batch_of_chunks, model, ...)`
    *   This function will:
        1.  Accept a list of chunk objects (e.g., a batch of 16).
        2.  Extract the text from each chunk into a simple list.
        3.  Call the new `model.generate_batch()` with the list of texts and the shared TTS parameters.
        4.  Receive a list of audio waveforms back.
        5.  Loop through the audio waves, apply the existing silence trimming and padding logic to each one, and save them to their respective `chunk_...wav` files.

    ### b. Modify the Main `process_book_folder` Function
    *   Locate the `use_vader` flag which is determined from the GUI options.
    *   Wrap the core processing loop in an `if/else` block based on this flag.
    *   **`if use_vader:` (Nuanced Mode):**
        *   Keep the existing code that iterates through chunks one-by-one and submits them to the `process_one_chunk` function.
    *   **`else:` (Batch Mode):**
        *   Add the new logic here.
        *   Group the `all_chunks` list into fixed-size batches based on `TTS_BATCH_SIZE` from the config.
        *   Use the existing `ThreadPoolExecutor` to submit these new **batches** to the new `process_batch` worker function.

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## 3. Files to Modify: `config/config.py` and `chatterbox_gui.py`

*   **Purpose:** To provide user control over the batch size for performance tuning.
*   **Changes Needed:**
    *   **In `config/config.py`:**
        *   Add a new configuration variable: `TTS_BATCH_SIZE = 16` (or another sensible default).
    *   **In `chatterbox_gui.py`:**
        *   On the "Config" tab, add a new `QSpinBox` (numeric input field) that is linked to the `TTS_BATCH_SIZE` variable. This will allow the user to change the batch size without editing code.