Zulip bot system

Zulip's features can be extended by the means of bots and integrations.

  • Integrations are used to connect Zulip with different chat, scheduling and workflow software. If this is what you are looking for, please check out the integrations guide.
  • Bots, as a more general concept, intercept and react to messages. If this is what you are looking for, read on!

The purpose of this documentation is to provide you with information about Zulip's bot system.

On this page you'll find:

  • A step-by-step tutorial on how to run a bot.
  • A step-by-step tutorial on how to develop a bot.
  • A documentation of the bot API.
  • Common problems when developing/running bots and their solutions.

Contributions to this guide are very welcome, so if you run into any issues following these instructions or come up with any tips or tools that help with writing bots, please visit #integrations on the Zulip development community server, open an issue, or submit a pull request to share your ideas!

The bots system

Zulip's bot system resides in the python-zulip-api repository.

The structure of the bots ecosystem looks like the following:

    │   ├───bot1
    │   └───bot2
    │       │
    │       ├───bot2.py
    │       ├───bot2.conf
    │       ├───doc.md
    │       ├───test_bot2.py
    │       ├───assets
    │       │   │
    │       │   └───pic.png
    │       ├───fixtures
    │       │   │
    │       │   └───test1.json
    │       └───libraries
    │           │
    │           └───lib1.py
    ├─── lib.py
    ├─── test_lib.py
    ├─── run.py
    └─── provision.py

Each subdirectory in bots contains a bot. When developing bots, try to use the structure outlined above as an orientation.

Installing the zulip_bots package

The zulip_bots package comes with all you need to run a bot.

Installing a stable version

Run pip install zulip_bots.

Installing a development version

  1. git clone https://github.com/zulip/python-zulip-api.git - clone the python-zulip-api repository.
  2. cd python-zulip-api - navigate into your cloned repository.
  3. ./tools/provision - install all requirements in a Python virtualenv.
  4. Run the source <activation/path> command printed in the previous step to activate the virtualenv.
  5. Finished. You should now see the name of your venv preceding your prompt, e.g. (ZULIP-~1).

Hint: ./tools/provision installs zulip, zulip_bots, and zulip_botserver in developer mode. This enables you to make changes to the code after the packages are installed.

How to run a bot

This guide will show you how to run a bot on a running Zulip server. It assumes you want to use one of the existing zulip_bots/bots bots in your Zulip organization. If you want to write a new one, you just need to write the <my-bot>.py script and put it into zulip_bots/bots/<my-bot> directory.

Looking for an easy way to test a bot's output? Check out this section.

You need:

  • An account in an organization on a Zulip server (e.g. chat.zulip.org or yourSubdomain.zulipchat.com, or your own development server). Within that Zulip organization, users will be able to interact with your bot.
  • A computer where you're running the bot from.

Note: Please be considerate when testing experimental bots on public servers such as chat.zulip.org.

  1. Install all requirements.

  2. Register a new bot user on the Zulip server's web interface.

    • Log in to the Zulip server.
    • Navigate to Settings () -> Your bots -> Add a new bot. Select Generic bot for bot type, fill out the form and click on Create bot.
    • A new bot user should appear in the Active bots panel.
  3. Download the bot's .zuliprc configuration file to your computer.

    • In the Active bots panel, click on the little green download icon to download its configuration file .zuliprc (the structure of this file is explained here).
    • Copy the file to a destination of your choice, e.g. to ~/.zuliprc.
  4. Subscribe the bot to the streams that the bot needs to interact with.

    • To subscribe your bot to streams, navigate to Manage Streams. Select a stream and add your bot by its email address (the address you assigned in step 2).
    • Now, the bot can do its job on the streams you subscribed it to.
    • (In future versions of the API, this step may not be required).
  5. Run the bot.

    • Run

      zulip-run-bot <bot-name> --config-file ~/.zuliprc

      (using the path to the .zuliprc file from step 3).

    • Check the output of the command. It should start with the text the usage function returns, followed by logging output similar to this:

      INFO:root:starting message handling...
      INFO:requests.packages.urllib3.connectionpool:Starting new HTTP connection (1): localhost
    • Congrats! Now, your bot should be ready to test on the streams you've subscribed it to.

Testing the helloworld bot

  • The helloworld bot is a simple bot that responds with a 'beep boop' when queried. It can be used as a template to build more complex bots.
  • Go to a stream your bot is subscribed to. Talk to the bot by typing @<your bot name> followed by some commands. If the bot is the helloworld bot, you should expect the bot to respond with "beep boop".

Testing a bot's output

If you just want to see how a bot reacts to a message, but don't want to set it up on a server, we have a little tool to help you out: zulip-bot-output

  • Install all requirements.

  • Run zulip-bot-output <bot-name> --message "<your-message>" to test one of the bots in zulip_bots/bots

    • Example: zulip-bot-output converter --message "12 meter yard"

      Response: 12.0 meter = 13.12336 yard

  • Run zulip-bot-output <path/to/bot.py> --message "<your-message>" to specify the bot's path yourself.

    • Example: zulip-bot-output zulip_bots/zulip_bots/bots/converter/converter.py --message "12 meter yard"

      Response: 12.0 meter = 13.12336 yard

Zulip Botserver

The Zulip Botserver is for people who want to

  • run bots in production.
  • run multiple bots at once.

The Zulip Botserver is a Python (Flask) server that implements Zulip's Outgoing Webhooks API. You can of course write your own servers using the Outgoing Webhooks API, but the Botserver is designed to make it easy for a novice Python programmer to write a new bot and deploy it in production.

Installing the Zulip Botserver

Install the zulip_botserver PyPI package using pip:

pip install zulip_botserver

Running bots using the Zulip Botserver

  1. Register new bot users on the Zulip server's web interface.

    • Log in to the Zulip server.
    • Navigate to Settings () -> Your bots -> Add a new bot. Select Outgoing webhook for bot type, fill out the form and click on Create bot.
    • A new bot user should appear in the Active bots panel.
  2. Download the flaskbotrc from the your-bots settings page. It contains the configuration details for all the active outgoing webhook bots. It's structure is very similar to that of .zuliprc.

  3. Run the Zulip Botserver by passing the flaskbotrc to it. The command format is:

    zulip-bot-server  --config-file <path_to_flaskbotrc> --hostname <address> --port <port>

    If omitted, hostname defaults to and port to 5002.

  4. Now set up the outgoing webhook service which will interact with the server: Create an Outgoing webhook bot with its base url of the form:


    bot_name refers to the name in the email address you specified for the bot. It can be obtained by removing -bot@*.* from the bot email: For example, the bot name of a bot with an email followup-bot@zulip.com is followup.

    In the development environment, an outgoing webhook bot and corresponding service already exist, with the email outgoing-webhook@zulip.com. This can be used for interacting with flask server bots.

  5. Congrats, everything is set up! Test your botserver like you would test a normal bot.

    Please note that in order to @-mention trigger a bot on a stream, the bot and the outgoing webhook bot need to be subscribed to it.

Running Zulip Botserver with supervisord

supervisord is a popular tool for running services in production. It helps ensure the service starts on boot, manages log files, restarts the service if it crashes, etc. This section documents how to run the Zulip Botserver using supervisord.

Running the Zulip Botserver with supervisord works almost like running it manually.

  1. Install supervisord via your package manager; e.g. on Debian/Ubuntu:

    sudo apt-get install supervisor
  2. Configure supervisord. supervisord stores its configuration in /etc/supervisor/conf.d.

    • Do one of the following:

      • Download the sample config file and store it in /etc/supervisor/conf.d/zulip-botserver.conf.

      • Copy the following section into your existing supervisord config file.

        command=zulip-bot-server --config-file=<path/to/your/flaskbotrc> --hostname <address> --port <port>
        stdout_logfile=/var/log/zulip-botserver.log ; all output of your botserver will be logged here
    • Edit the <> sections according to your preferences.

  3. Update supervisord to read the configuration file:

    supervisorctl reread
    supervisorctl update

    (or you can use /etc/init.d/supervisord restart, but this is less disruptive if you're using supervisord for other services as well).

  4. Test if your setup is successful:

    supervisorctl status

    The output should include a line similar to this:

    zulip-bot-server RUNNING pid 28154, uptime 0:00:27

    The standard output of the bot server will be logged to the path in your supervisord configuration.

How to develop a bot

The tutorial below explains the structure of a bot <my-bot>.py, which is the only file you need to create for a new bot. You can use this as boilerplate code for developing your own bot.

Every bot is built upon this structure:

class MyBotHandler(object):
    A docstring documenting this bot.

    def usage(self):
        return '''Your description of the bot'''

    def handle_message(self, message, bot_handler, state_handler):
        # add your code here

handler_class = MyBotHandler
  • The class name (in this case MyBotHandler) can be defined by you and should match the name of your bot. To register your bot's class, adjust the last line handler_class = MyBotHandler to match your class name.
  • Every bot needs to implement the functions
    • usage(self)
    • handle_message(self, message, bot_handler)
  • These functions are documented in the next section.


This section documents functions available to the bot and the structure of the bot's config file.

With this API, you can

  • intercept, view, and process messages sent by users on Zulip.
  • send out new messages as replies to the processed messages.

With this API, you cannot

  • modify an intercepted message (you have to send a new message).
  • send messages on behalf of or impersonate other users.
  • intercept private messages (except for PMs with the bot as an explicit recipient).



is called to retrieve information about the bot.

  • self - the instance the method is called on.
Return values
  • A string describing the bot's functionality
Example implementation
def usage(self):
    return '''
        This plugin will allow users to flag messages
        as being follow-up items.  Users should preface
        messages with "@followup".
        Before running this, make sure to create a stream
        called "followup" that your API user can send to.


handle_message(self, message, bot_handler)

handles user message.

  • self - the instance the method is called on.
  • message - a dictionary describing a Zulip message
  • bot_handler - used to interact with the server, e.g. to send a message
  • state_handler - used to save states/information of the bot beta
    • use state_handler.set_state(state) to set a state (any object)
    • use state_handler.get_state() to retrieve the state set; returns a NoneType object if no state is set
Return values


Example implementation
 def handle_message(self, message, bot_handler, state_handler):
    original_content = message['content']
    original_sender = message['sender_email']
    new_content = original_content.replace('@followup',
                                           'from %s:' % (original_sender,))




will send a message as the bot user. Generally, this is less convenient than send_reply, but it offers additional flexibility about where the message is sent to.


  • message - a dictionary describing the message to be sent by the bot

Example implementation

    type='stream', # can be 'stream' or 'private'
    to=stream_name, # either the stream name or user's email
    subject=subject, # message subject
    content=message, # content of the sent message


bot_handler.send_reply(message, response)

will reply to the triggering message to the same place the original message was sent to, with the content of the reply being response.


  • message - Dictionary containing information on message to respond to (provided by handle_message).
  • response - Response message from the bot (string).



will edit the content of a previously sent message.


  • message - dictionary defining what message to edit and the new content


From zulip_bots/bots/incrementor/incrementor.py:

    message_id=self.message_id, # id of message to be updated
    content=str(self.number), # string with which to update message with

Configuration file

  • key - the API key you created for the bot; this is how Zulip knows the request is from an authorized user.
  • email - the email address of the bot, e.g. some-bot@zulip.com
  • site - your development environment URL; if you are working on a development environment hosted on your computer, use localhost:9991

Writing tests for bots

Bots, like most software that you want to work, should have unit tests. In this section, we detail our framework for writing unit tests for bots. We require that bots in the main python-zulip-api repository include a reasonable set of unit tests, so that future developers can easily refactor them.

Unit tests for bots make heavy use of mocking. If you want to get comfortable with mocking, mocking strategies, etc. you should check out our mocking guide.

A simple example

Let's have a look at a simple test suite for the helloworld bot (the actual test is written slightly more compact).

from __future__ import absolute_import
from __future__ import print_function

from zulip_bots.test_lib import BotTestCase  # The test system library

class TestHelloWorldBot(BotTestCase):
    bot_name = "helloworld"  # The bot's name (should be the name of the bot module to test).

    def test_bot(self): # A test case (must start with `test`)
        # Messages we want to test and the expected bot responses.
        message_response_pairs = {"" : "beep boop",
                                  "foo" : "beep boop",
                                  "Hi, my name is abc" : "beep boop"}
        self.check_expected_responses(message_response_pairs)  # Test the bot with our message_response_pair dict.

The helloworld bot replies with "beep boop" to every message @-mentioning it. Note that our helper method check_expected_responses adds the @-mention for us - the only thing we need to do is to specify the rest of the message and the expected response. In this case, we want to assert that the bot always replies with "beep boop". To do so, we specify several test messages ("", "foo", "Hi, my name is abc") and assert that the response is always correct, which for this simple bot, means always sending a reply with the content "beep boop".

Test your test

Once you have written a test suite, you want to verify that everything works as expected.

  • To test a bot in Zulip's bot directory: tools/test-bots <botname>
  • To run any test: python -m unittest -v <package.bot_test>
  • To run all bot tests: tools/test-bots

Advanced testing

This section shows advanced testing techniques for more complicated bots that have configuration files or interact with third-party APIs. The code for the bot testing library can be found here.

Asserting individual messages
    message = {'content': 'foo'},
    response = {'content': 'bar'},

Use assert_bot_response() to test individual messages. Specify additional message settings, such as the stream or subject, in the message and response dicts.

Testing bots with config files

Some bots, such as Giphy, support or require user configuration options to control how the bot works. To test such a bot, you can use the following helper method:

with self.mock_config_info({'entry': 'value'}):
    # self.assert_bot_response(...)

mock_config_info() mocks a bot's config file. All config files are specified in the .ini format, with one default section. The dict passed to mock_config_info() specifies the keys and values of that section.

Testing bots with internet access

Some bots, such as Giphy, depend on a third-party we service, such as the Giphy webapp, in order to work. Because we want our test suite to be reliable and not add load to these third-party APIs, tests for these services need to have "test fixtures": sample HTTP request/response pairs to be used by the tests. You can specify which one to use in your test code using the following helper method:

with self.mock_http_conversation('test_fixture_name'):
    # self.assert_bot_response(...)

mock_http_conversation(fixture_name) patches requests.get and returns the data specified in the file fixtures/<fixture_name>.py. For an example, check out the giphy bot.

Tip: You can use requestb.in or a similar tool to capture payloads from the service your bot is interacting with.

Testing bots that specify initialize()

Some bots, such as Giphy, implement an initialize() method, which is executed on the startup of the bot. To test such a bot, you can call its initialize() method with the following helper method:


Calling initialize_bot() invokes the initialize() method specified by the bot.


Check out our bots to see examples of bot tests.

Common problems

  • I modified my bot's code, yet the changes don't seem to have an effect.
    • Ensure that you restarted the run.py script.
  • My bot won't start
    • Ensure that your API config file is correct (download the config file from the server).
    • Ensure that you bot script is located in zulip_bots/bots/<my-bot>/
    • Are you using your own Zulip development server? Ensure that you run your bot outside the Vagrant environment.
    • Some bots require Python 3. Try switching to a Python 3 environment before running your bot.
  • My bot works only on some streams.
    • Subscribe your bot to other streams, as described here.

Future direction

The long-term plan for this bot system is to allow the same ExternalBotHandler code to eventually be usable in several contexts:

  • Run directly using the Zulip call_on_each_message API, which is how the implementation above works. This is great for quick development with minimal setup.
  • Run in a simple Python webserver server, processing messages received from Zulip's outgoing webhooks integration.
  • For bots merged into the mainline Zulip codebase, enabled via a button in the Zulip web UI, with no code deployment effort required.