# YouTube Chat Webhook Listener (Version 2) - gRPC Implementation Plan

This document outlines the detailed plan for implementing a robust, quota-friendly, open-source, and Linux-compatible solution for monitoring YouTube Live Chat by leveraging the recommended `liveChatMessages.streamList` gRPC endpoint.

## Phase 1: gRPC Client Setup

1.  **Install Dependencies:**
    *   **Action:** Install `grpcio` and `grpcio-tools` Python packages.

2.  **Obtain `.proto` File:**
    *   **Action:** Locate and download the official Protocol Buffers (`.proto`) file that defines the `liveChatMessages.streamList` service.

3.  **Generate Python Client Code:**
    *   **Action:** Use `grpc_tools.protoc` to generate the Python client-side libraries from the `.proto` file.

4.  **Develop gRPC Client:**
    *   **Action:** Write a Python script to:
        *   Establish a secure gRPC channel to the YouTube API endpoint.
        *   Create a client stub for the `liveChatMessages.streamList` service.
        *   Initiate the `StreamList` request to begin receiving messages.
        *   Implement a loop to continuously process messages as they are pushed from the server.

## Phase 2: Integration and Enhancements

1.  **Integrate with Display Logic:**
    *   **Action:** Adapt the existing `rich` display logic from `main.py` to consume messages received from the gRPC client instead of the polling mechanism.

2.  **Error Handling & Resilience:**
    *   **Action:** Implement robust error handling for gRPC connections, including automatic reconnection logic.
    *   **Action:** Utilize `nextPageToken` (if provided by the gRPC stream) to resume receiving messages from where the connection was interrupted, preventing data loss.

3.  **Configuration:**
    *   **Action:** Externalize API keys, default video ID, and display preferences into a configuration file (e.g., `config.ini` or `config.json`).

4.  **Enhance Display Features:**
    *   **Action:** Implement a more sophisticated system to assign consistent, unique colors to each user.
    *   **Action:** Improve emote rendering and potentially integrate with external emote services (e.g., BTTV, FrankerFaceZ) if feasible and compliant.
    *   **Action:** Add options for message filtering (e.g., by user, keywords, message type).

## Phase 3: Testing and Documentation

1.  **Unit and Integration Tests:**
    *   **Action:** Write comprehensive unit tests for the gRPC client, message processing, and display logic.
    *   **Action:** Develop integration tests to ensure the end-to-end flow works correctly.

2.  **Update Documentation:**
    *   **Action:** Update the project's `README.md` with detailed usage instructions, setup guides, and explanations of the gRPC implementation.