# How to develop a Matrix Bridge in Python Creating a Matrix bridge involves connecting the Matrix ecosystem with another chat service, enabling users to communicate across different platforms. In this guide, we'll develop a simple Matrix bridge using Python 3.12 and the Matrix Application Service (AppService) API with Synapse. - [How to develop a Matrix Bridge in Python](#how-to-develop-a-matrix-bridge-in-python) - [Prerequisites](#prerequisites) - [Setting Up Your Development Environment](#setting-up-your-development-environment) - [Understanding the Matrix Application Service API](#understanding-the-matrix-application-service-api) - [Registering Your AppService with Synapse](#registering-your-appservice-with-synapse) - [Creating the Registration File](#creating-the-registration-file) - [Generating Secure Tokens](#generating-secure-tokens) - [Registering with Synapse](#registering-with-synapse) - [Verifying Registration](#verifying-registration) - [Writing the Bridge](#writing-the-bridge) - [Setting Up the Bridge Script](#setting-up-the-bridge-script) - [Defining the Bridge Class](#defining-the-bridge-class) - [Handling Incoming Matrix Messages](#handling-incoming-matrix-messages) - [Sending Messages to Matrix Rooms](#sending-messages-to-matrix-rooms) - [Running the Bridge](#running-the-bridge) - [Testing the Bridge](#testing-the-bridge) - [Implementing Two-Way Communication](#implementing-two-way-communication) - [Integrating the External Chat Service API](#integrating-the-external-chat-service-api) - [Sending Messages from Matrix to the External Service](#sending-messages-from-matrix-to-the-external-service) - [Running the Bridge with External Service Integration](#running-the-bridge-with-external-service-integration) - [Replicating Users Over The Bridge](#replicating-users-over-the-bridge) - [Creating Virtual Matrix Users](#creating-virtual-matrix-users) - [Handling Messages from External Users](#handling-messages-from-external-users) - [Bridging User Profiles](#bridging-user-profiles) - [Handling State and Metadata](#handling-state-and-metadata) - [Tracking Room State](#tracking-room-state) - [Managing Metadata](#managing-metadata) - [Synchronising Custom Data](#synchronising-custom-data) - [Deploying the Bridge](#deploying-the-bridge) - [Containerisation with Docker](#containerisation-with-docker) - [Systemd Service](#systemd-service) - [Monitoring and Maintenance](#monitoring-and-maintenance) - [Implementing Logging](#implementing-logging) - [Error Handling](#error-handling) - [Health Checks](#health-checks) - [Regular Maintenance](#regular-maintenance) - [Monitoring Tools](#monitoring-tools) - [Conclusion](#conclusion) - [Next Steps](#next-steps) ## Prerequisites Before diving into the development of a Matrix bridge, you'll need to ensure that you have the following prerequisites in place: - **A running Matrix server**: You'll need access to a Matrix homeserver, and Synapse is the reference homeserver implementation for Matrix. If you don't have it set up yet, follow the [installation instructions](https://github.com/matrix-org/synapse) provided by the Matrix.org team. - **Python**: Ensure that you have Python installed on your system. You can download it from the [official Python website](https://www.python.org/downloads/), and for the purpose of this guide I am using Python 3.12. - **Familiarity with async/await**: A good understanding of Python's asynchronous programming features, specifically `async` and `await`, is required as we'll be dealing with asynchronous APIs. - **Basic understanding of the Matrix protocol**: Familiarise yourself with the basics of the Matrix protocol, which is the underlying technology for real-time communication. ### Setting Up Your Development Environment To get started, you'll need to set up a dedicated project directory and a virtual environment for your bridge. Follow these steps: ```bash # Create a project directory for your Matrix bridge mkdir my-matrix-bridge cd my-matrix-bridge # Create a virtual environment using Python 3.12 python3.12 -m venv venv # Activate the virtual environment source venv/bin/activate ``` Once your virtual environment is activated, you'll want to install the necessary Python packages. For Matrix communication, we'll use `matrix-nio`, which is a Python Matrix client library that supports AsyncIO. ```bash # Install matrix-nio with end-to-end encryption support pip install "matrix-nio[e2e]" ``` With the virtual environment set up and the necessary packages installed, you're ready to begin developing your Matrix bridge. ### Understanding the Matrix Application Service API The Matrix Application Service API is a powerful interface that allows third-party services (like the bridge you're about to build) to integrate with Matrix homeservers. It's important to understand how this API works and the concepts of "virtual users" and "namespaces" that you'll be using to map users and rooms between Matrix and the external chat service. Take some time to read through the [Application Service API specification](https://spec.matrix.org/v1.9/application-service-api/) to familiarise yourself with its capabilities and requirements. ## Registering Your AppService with Synapse To have your bridge communicate with the Matrix homeserver, you must first register it as an Application Service (AppService). This section guides you through creating a registration file for Synapse, which includes necessary details about your bridge and its permissions. ### Creating the Registration File The registration file is a YAML document that Synapse uses to recognise and interact with your AppService. Create a file named `bridge-registration.yaml` with the following structure: ```yaml # bridge-registration.yaml id: "example-bridge" url: "http://localhost:5000" as_token: "YOUR_AS_TOKEN" hs_token: "YOUR_HS_TOKEN" sender_localpart: "example-bridge-bot" namespaces: users: - exclusive: true regex: "@example-bridge_.*:your-homeserver.com" aliases: - exclusive: true regex: "#example-bridge_.*:your-homeserver.com" rooms: [] ``` Replace `your-homeserver.com` with your Matrix homeserver's domain to ensure the namespaces match correctly. Here's a breakdown of the keys: - `id`: A unique identifier for your AppService. - `url`: The callback URL where Synapse will send incoming events. - `as_token`: A token for the AppService to authenticate with Synapse. - `hs_token`: A token for Synapse to authenticate with the AppService. - `sender_localpart`: The localpart for the user ID that the bridge will use to send messages. - `namespaces`: Defines the users, aliases, and rooms that your bridge will manage. ### Generating Secure Tokens You'll need to generate secure tokens for `YOUR_AS_TOKEN` and `YOUR_HS_TOKEN`. These should be unique, random strings. You can use `openssl` to generate them: ```bash # Generate the AS token openssl rand -base64 32 # Generate the HS token openssl rand -base64 32 ``` Run the command twice and replace `YOUR_AS_TOKEN` and `YOUR_HS_TOKEN` in the `bridge-registration.yaml` with the generated strings. ### Registering with Synapse Copy the `bridge-registration.yaml` to Synapse's application services directory. The default location is `/etc/matrix-synapse/appservices`, but this may vary: ```bash # Copy the registration file to the Synapse directory sudo cp bridge-registration.yaml /etc/matrix-synapse/appservices/ ``` ### Verifying Registration After placing the registration file in the correct directory, restart Synapse to apply the changes - this could be via `sudo systemctl restart matrix-synapse` or another method like Docker, depending on how you've set up your homeserver. Check the Synapse logs to ensure that your AppService has been successfully registered. If there are no errors related to the AppService in the logs, your bridge should now be recognised by Synapse and ready to receive events. With the AppService registered, you can proceed to write the bridge code that will handle the incoming events and establish communication between the Matrix homeserver and your external chat service. ## Writing the Bridge Writing the bridge is a pivotal step in your project. It involves creating the Python script that will act as the intermediary, processing events from the Matrix homeserver and translating them into actions on the external chat service, and vice versa. Let's delve into the details of how to set up your bridge script. ### Setting Up the Bridge Script Begin by creating a new Python file named `bridge.py`. This file will house the core logic of your bridge. Start with the necessary imports and initialise the `AsyncClient` from `matrix-nio`, which will handle the communication with the Matrix homeserver: ```python # bridge.py import asyncio from nio import AsyncClient, RoomMessageText, MatrixRoom, LoginResponse # Configuration details - replace these with your actual details HOMESERVER_URL = "https://your-homeserver.com" BRIDGE_USER_ID = "@example-bridge-bot:your-homeserver.com" BRIDGE_AS_TOKEN = "YOUR_AS_TOKEN" # Initialise the AsyncClient for the bridge client = AsyncClient(HOMESERVER_URL, BRIDGE_USER_ID) ``` ### Defining the Bridge Class Now, let's encapsulate the bridge's functionality within a class called `MatrixBridge`: ```python class MatrixBridge: def __init__(self, client): self.client = client async def start(self): # Use the AS token to log in to the homeserver response = await self.client.login(token=BRIDGE_AS_TOKEN) if isinstance(response, LoginResponse): print("Successfully logged into the homeserver!") else: print(f"Login failed: {response}") return # Register a callback for RoomMessageText events self.client.add_event_callback(self.on_message, RoomMessageText) # Keep the client syncing with the homeserver await self.client.sync_forever(timeout=30000) ``` ### Handling Incoming Matrix Messages We need to define how the bridge will handle incoming messages from Matrix rooms. This is where you'll eventually add the logic to relay messages to the external chat service: ```python async def on_message(self, room: MatrixRoom, event: RoomMessageText): # Prevent the bridge from responding to its own messages if event.sender == BRIDGE_USER_ID: return print(f"Received message from {event.sender} in {room.room_id}: {event.body}") # Placeholder for relaying messages to the external service # For now, we'll send a confirmation message back to the Matrix room await self.send_message_to_matrix(room.room_id, "Message received and acknowledged!") ``` ### Sending Messages to Matrix Rooms We also need a method to send messages to Matrix rooms, which will be used to relay messages from the external chat service back to Matrix: ```python async def send_message_to_matrix(self, room_id: str, message: str): # Send a text message to the specified Matrix room await self.client.room_send( room_id=room_id, message_type="m.room.message", content={ "msgtype": "m.text", "body": message, } ) ``` ### Running the Bridge To run the bridge, we'll define an asynchronous `main` function that creates an instance of `MatrixBridge` and starts the syncing process: ```python async def main(): bridge = MatrixBridge(client) await bridge.start() if __name__ == "__main__": asyncio.run(main()) ``` This setup will log the bridge into the Matrix server and listen for messages in the rooms it's participating in. When a message is received, it prints the message to the console and sends a confirmation message back to the room. ### Testing the Bridge Run your bridge with the following command: ```bash python bridge.py ``` Join a Matrix room with your bridge bot and send a message. The bridge should print the message to the console and send a confirmation message back to the room. ## Implementing Two-Way Communication To achieve two-way communication between the Matrix ecosystem and an external chat service, you'll need to integrate both systems' APIs. This integration will allow messages to flow from Matrix to the external service and back again. Below, we'll walk through the process of setting up this communication using a hypothetical external chat service API. ### Integrating the External Chat Service API First, let's assume that the external chat service provides a Python SDK that we'll refer to as `external_chat_sdk`. You'll need to install this SDK in your virtual environment: ```bash # Install the external chat service SDK pip install external_chat_sdk ``` Now, we'll extend our `MatrixBridge` class to include the setup and event handling for the external chat service: ```python # bridge.py # Import the external chat service SDK from external_chat_sdk import ExternalChatClient, ExternalMessageEvent class MatrixBridge: def __init__(self, client, external_api_key): self.client = client self.external_client = ExternalChatClient(api_key=external_api_key) # Register event callback for incoming messages from the external service self.external_client.on_message(self.on_external_message) async def on_external_message(self, event: ExternalMessageEvent): # Convert the external message to a Matrix message format matrix_room_id = self.map_external_room_to_matrix(event.room_id) await self.send_message_to_matrix(matrix_room_id, event.sender, event.text) def map_external_room_to_matrix(self, external_room_id): # Implement your logic to map the external room ID to a Matrix room ID # This could involve a lookup in a database or a predefined mapping return f"!mapped_room_id:your-homeserver.com" # ... (rest of the existing MatrixBridge methods) ``` In the `__init__` method, we initialise the external chat client and set up an event callback for incoming messages. The `on_external_message` method is responsible for handling these messages and sending them to the appropriate Matrix room. ### Sending Messages from Matrix to the External Service Next, we'll handle messages coming from Matrix and relay them to the external chat service. We'll modify the `on_message` method within the `MatrixBridge` class: ```python class MatrixBridge: # ... (existing methods) async def on_message(self, room: MatrixRoom, event: RoomMessageText): # Prevent the bridge from responding to its own messages if event.sender == self.client.user_id: return # Map the Matrix room ID to the external room ID external_room_id = self.map_matrix_room_to_external(room.room_id) # Send the message to the external chat service await self.external_client.send_message(external_room_id, event.body) def map_matrix_room_to_external(self, matrix_room_id): # Implement your logic to map the Matrix room ID to an external room ID # This could involve a lookup in a database or a predefined mapping return "mapped_external_room_id" # ... (rest of the existing MatrixBridge methods) ``` In the modified `on_message` method, we map the Matrix room ID to the corresponding external room ID and send the message through the external chat client. ### Running the Bridge with External Service Integration Finally, we'll need to ensure that both the Matrix client and the external chat client are running. We'll modify the `main` function to start both services: ```python async def main(): bridge = MatrixBridge(client, "your_external_api_key") # Start the Matrix client matrix_client_task = asyncio.create_task(bridge.start()) # Start the external chat client external_client_task = asyncio.create_task(bridge.external_client.connect()) # Run both clients concurrently await asyncio.gather(matrix_client_task, external_client_task) if __name__ == "__main__": asyncio.run(main()) ``` With these changes, your bridge will now be able to handle two-way communication between Matrix and the external chat service. Messages sent in a Matrix room will be relayed to the corresponding room in the external service, and vice versa. ## Replicating Users Over The Bridge Replicating users over the bridge is a crucial step in ensuring that conversations flow naturally between the Matrix ecosystem and the external chat service. This involves creating "virtual" Matrix users that represent users from the external service within Matrix. Here's how you can implement user replication in your bridge. ### Creating Virtual Matrix Users First, we need to define a method to register virtual users with the Matrix homeserver. These virtual users will correspond to the users on the external chat service. ```python # bridge.py # ... (previous code) class MatrixBridge: # ... async def register_virtual_user(self, external_username): # Generate a Matrix user ID for the external user matrix_user_id = f"@{external_username}:your-homeserver.com" # Check if the virtual user already exists on the homeserver response = await self.client.register( username=external_username, password=None, # No password needed as these are virtual users admin=False, # Virtual users should not have admin rights kind="user" # This is a regular user account ) if isinstance(response, LoginResponse): print(f"Virtual user {matrix_user_id} registered successfully.") else: print(f"Failed to register virtual user {matrix_user_id}: {response}") return matrix_user_id # ... # ... (rest of the code) ``` In the `register_virtual_user` method, we're using the `register` coroutine of the `AsyncClient` to create a new user on the Matrix homeserver. We're assuming that the external service provides a unique username for each user, which we use to create the Matrix user ID. ### Handling Messages from External Users Next, we need to handle incoming messages from the external chat service and send them as the virtual Matrix users we've registered. ```python # bridge.py # ... (previous code) class MatrixBridge: # ... async def on_external_message(self, event): # Map the external username to a Matrix user ID matrix_user_id = await self.register_virtual_user(event.sender_username) # Find or create a Matrix room to send the message to room_id = await self.get_or_create_matrix_room(event.chat_room_id) # Send the message as the virtual Matrix user await self.send_message_as_user(room_id, matrix_user_id, event.text) async def send_message_as_user(self, room_id, user_id, text): # Impersonate the virtual user await self.client.impersonate_user(user_id) # Send the message await self.client.room_send( room_id=room_id, message_type="m.room.message", content={ "msgtype": "m.text", "body": text, } ) # Stop impersonating the user await self.client.impersonate_user(None) # ... # ... (rest of the code) ``` In the `on_external_message` method, we're calling `register_virtual_user` to ensure that a corresponding Matrix user exists for the external user sending the message. We then call `send_message_as_user` to send the message to the appropriate Matrix room as the virtual user. ### Bridging User Profiles Optionally, you might want to replicate user profile information, such as display names and avatars, from the external service to Matrix. Here's an example of how you might set a virtual user's display name: ```python # bridge.py # ... (previous code) class MatrixBridge: # ... async def set_virtual_user_profile(self, user_id, display_name, avatar_url=None): # Impersonate the virtual user await self.client.impersonate_user(user_id) # Set the user's display name await self.client.set_displayname(display_name) # Optionally, set the user's avatar if an URL is provided if avatar_url: await self.client.set_avatar_url(avatar_url) # Stop impersonating the user await self.client.impersonate_user(None) # ... # ... (rest of the code) ``` In the `set_virtual_user_profile` method, we're using the `set_displayname` and `set_avatar_url` coroutines of the `AsyncClient` to set the virtual user's profile information. ## Handling State and Metadata When building a Matrix bridge, managing the state and metadata is vital for ensuring a smooth and consistent experience across both the Matrix ecosystem and the external chat service. This includes tracking user presence, room membership, and any custom data that needs to be synchronised between the two platforms. ### Tracking Room State To keep the bridge aware of the room state, you need to handle state events such as room membership changes. Here's an example of how you might track room members: ```python # bridge.py # ... (previous code) class MatrixBridge: # ... async def on_room_member(self, room: MatrixRoom, event): # This event is triggered whenever a room member's state changes if event.membership == "join": print(f"{event.state_key} joined {room.room_id}") # Add user to the room's state self.add_user_to_room_state(room.room_id, event.state_key) elif event.membership == "leave": print(f"{event.state_key} left {room.room_id}") # Remove user from the room's state self.remove_user_from_room_state(room.room_id, event.state_key) def add_user_to_room_state(self, room_id, user_id): # Implement logic to add a user to the room's state # This could involve updating an in-memory structure or a database entry pass def remove_user_from_room_state(self, room_id, user_id): # Implement logic to remove a user from the room's state # This could involve updating an in-memory structure or a database entry pass # ... # ... (rest of the code) ``` In this example, we handle `on_room_member` events to track when users join or leave rooms. The methods `add_user_to_room_state` and `remove_user_from_room_state` would contain the logic to update the state accordingly. ### Managing Metadata Metadata can include any additional information that needs to be tracked, such as room aliases, user profiles, or custom data related to the external chat service. Here's an example of managing room aliases: ```python # bridge.py # ... (previous code) class MatrixBridge: # ... async def on_room_alias(self, room: MatrixRoom, event): # This event is triggered when a room alias is added or removed if event.alias: print(f"Alias {event.alias} added to {room.room_id}") # Store the new alias self.add_room_alias(room.room_id, event.alias) else: print(f"Alias for {room.room_id} removed") # Remove the alias self.remove_room_alias(room.room_id) def add_room_alias(self, room_id, alias): # Implement logic to store a new room alias # This could involve a database entry or an in-memory data structure pass def remove_room_alias(self, room_id): # Implement logic to remove a room alias # This could involve a database entry or an in-memory data structure pass # ... # ... (rest of the code) ``` Here, the `on_room_alias` event handler is used to manage room aliases. When an alias is added or removed, we update our metadata storage using `add_room_alias` and `remove_room_alias`. ### Synchronising Custom Data If your bridge requires custom data to be synchronised between Matrix and the external chat service, you should implement methods to handle this. For example, you might need to keep track of message edits or reactions: ```python # bridge.py # ... (previous code) class MatrixBridge: # ... async def on_message_edit(self, room: MatrixRoom, event): # This event is triggered when a message is edited original_event_id = event.replaces_event new_message_body = event.new_content['body'] print(f"Message {original_event_id} in {room.room_id} edited to: {new_message_body}") # Update the message in your storage self.update_message(original_event_id, new_message_body) def update_message(self, original_event_id, new_message_body): # Implement logic to update an edited message # This could involve a database update or an in-memory data structure pass # ... # ... (rest of the code) ``` In this example, `on_message_edit` is triggered when a message edit event is received. The `update_message` method would contain the logic to update the stored message content. ## Deploying the Bridge Deploying your Matrix bridge is a critical step to ensure it runs reliably and efficiently. Below, we'll cover the necessary steps to deploy your bridge, including containerisation with Docker and setting up a systemd service. ### Containerisation with Docker Using Docker to containerise your bridge can simplify deployment and provide an isolated environment for your application. Here's how to create a Docker container for your bridge: 1. Create a Dockerfile Start by creating a `Dockerfile` in the root of your project directory. This file will define the environment in which your bridge will run. ```Dockerfile # Use an official Python runtime as a base image FROM python:3.12-slim # Set the working directory in the container WORKDIR /usr/src/app # Copy the local code to the container COPY . . # Install any dependencies RUN pip install --no-cache-dir -r requirements.txt # Make port 5000 available to the world outside this container EXPOSE 5000 # Run bridge.py when the container launches CMD ["python", "./bridge.py"] ``` 2. Build the Docker Image With the `Dockerfile` in place, build your Docker image using the following command: ```bash docker build -t my-matrix-bridge . ``` 3. Run the Docker Container Once the image is built, run your bridge inside a Docker container: ```bash docker run -d --name my-matrix-bridge-instance -p 5000:5000 my-matrix-bridge ``` This command runs the bridge in detached mode, maps port 5000 of the container to port 5000 on the host, and names the container instance `my-matrix-bridge-instance`. ### Systemd Service If you prefer not to use Docker and you're deploying on a Linux server, you can set up a systemd service to manage your bridge. 1. Create a Service File Create a service file for systemd. Save this file as `/etc/systemd/system/matrix-bridge.service`: ```ini [Unit] Description=Matrix Bridge Service After=network.target [Service] Type=simple User= WorkingDirectory=/path/to/your/bridge ExecStart=/path/to/your/bridge/venv/bin/python /path/to/your/bridge/bridge.py Restart=on-failure [Install] WantedBy=multi-user.target ``` Replace `` with the user you want the service to run under, and `/path/to/your/bridge` with the actual path to your bridge application. 2. Enable and Start the Service Enable the service to start on boot and then start the service immediately: ```bash sudo systemctl enable matrix-bridge.service sudo systemctl start matrix-bridge.service ``` 3. Check the Service Status To ensure that the service is running correctly, check its status: ```bash sudo systemctl status matrix-bridge.service ``` ## Monitoring and Maintenance After deploying your Matrix bridge, it's crucial to ensure it operates reliably and efficiently. This section covers monitoring your bridge's performance, setting up logging, handling errors, and performing regular maintenance tasks. ### Implementing Logging Effective logging is essential for monitoring the bridge's activity and diagnosing issues. Python's built-in `logging` module provides a flexible framework for emitting log messages from your application. Here's a basic setup for logging within your bridge: ```python # bridge.py import logging # ... (other imports) # Configure logging logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s' ) logger = logging.getLogger(__name__) class MatrixBridge: # ... (existing methods) async def on_message(self, room: MatrixRoom, event: RoomMessageText): # ... (existing code) logger.info(f"Received message from {event.sender} in {room.room_id}: {event.body}") # ... (rest of the method) # ... (rest of the MatrixBridge class) # ... (rest of the script) ``` This configuration sets the logging level to `INFO` and defines a format that includes the timestamp, logger name, log level, and message. You can adjust the logging level and format to suit your needs. ### Error Handling Robust error handling is necessary to keep your bridge running smoothly. You should catch and log exceptions where appropriate, and ensure that the bridge can recover from common errors without manual intervention. Here's an example of adding error handling to the `on_message` method: ```python class MatrixBridge: # ... (existing methods) async def on_message(self, room: MatrixRoom, event: RoomMessageText): try: # ... (existing code) except Exception as e: logger.error(f"Error handling message from {event.sender}: {e}") # Handle the error or retry as appropriate # ... (rest of the MatrixBridge class) ``` ### Health Checks Implementing health checks can help you monitor the bridge's status and quickly detect when something goes wrong. You might set up an HTTP endpoint that returns the bridge's current status or use a third-party service to ping your bridge at regular intervals. Here's a simple health check endpoint using the `aiohttp` library: ```python # bridge.py from aiohttp import web # ... (other imports) async def health_check(request): # Perform necessary health checks here return web.Response(text="OK") app = web.Application() app.router.add_get('/health', health_check) # ... (rest of the script) if __name__ == "__main__": # ... (existing code to start the bridge) # Start the web server for health checks web.run_app(app, port=8080) ``` ### Regular Maintenance Schedule regular maintenance for your bridge to keep it up-to-date with the latest security patches and feature updates. This includes updating dependencies, the Python runtime, and any other components your bridge relies on. Here's an example of how you might update your dependencies: ```bash # Activate your virtual environment source venv/bin/activate # Update all installed packages pip install --upgrade -r requirements.txt ``` ### Monitoring Tools Consider integrating monitoring tools like Prometheus for metrics collection, Grafana for dashboards, or Sentry for real-time error tracking. These tools can provide insights into your bridge's performance and alert you to issues as they arise. For example, to integrate Prometheus metrics, you could use the `prometheus_client` library: ```python # bridge.py from prometheus_client import start_http_server, Summary # ... (other imports) # Create a metric to track time spent processing messages and the number of messages processed PROCESSING_TIME = Summary('bridge_processing_seconds', 'Time spent processing messages') class MatrixBridge: # ... (existing methods) @PROCESSING_TIME.time() async def on_message(self, room: MatrixRoom, event: RoomMessageText): # ... (existing code for processing messages) # ... (rest of the script) if __name__ == "__main__": # Start up the server to expose the metrics. start_http_server(8000) # ... (existing code to start the bridge) ``` ## Conclusion Congratulations on reaching the end of this guide on developing a Matrix bridge in Python! By now, you should have a functional bridge that facilitates communication between the Matrix ecosystem and an external chat service. This bridge represents a significant step towards creating a more interconnected and open messaging environment. ### Next Steps While this guide gives you a solid foundation, there's always room for improvement and expansion. Here are some suggestions for next steps: - **Enhance Error Handling:** Improve your bridge's robustness by implementing more comprehensive error handling and recovery mechanisms. - **Optimise Performance:** Profile and optimise your bridge's performance to handle larger volumes of traffic and more complex operations. - **Expand Features:** Consider adding additional features such as message edits, reactions, and more sophisticated user profile synchronisation. - **Improve Security:** Ensure that your bridge has strong security measures in place, such as encrypted communication and secure token management. - **Community Feedback:** Engage with the community of users and developers to gather feedback, address issues, and guide the future development of your bridge.