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# 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.

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To build a Python application that leverages the `liveChatMessages.streamList` gRPC endpoint to receive real-time YouTube Live Chat messages, process them, and display them in the terminal with rich formatting. This will ensure a highly efficient and compliant method for sustained live stream monitoring. To build a Python application that leverages the `liveChatMessages.streamList` gRPC endpoint to receive real-time YouTube Live Chat messages, process them, and display them in the terminal with rich formatting. This will ensure a highly efficient and compliant method for sustained live stream monitoring.
## Implementation Plan: gRPC Client ## Detailed Implementation Plan
### Phase 1: gRPC Client Setup For a detailed breakdown of the implementation steps, please refer to the [DEVELOPMENT_PLAN.md](DEVELOPMENT_PLAN.md) file.
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.
## Dependencies ## Dependencies
@@ -64,4 +22,4 @@ To build a Python application that leverages the `liveChatMessages.streamList` g
* Interactive message sending via gRPC (if supported by the API). * Interactive message sending via gRPC (if supported by the API).
* More advanced terminal UI (e.g., `prompt_toolkit` for input). * More advanced terminal UI (e.g., `prompt_toolkit` for input).
* Web overlay integration. * Web overlay integration.