Telegram integration

Any model specified by a DeepPavlov config can be launched as a Telegram bot. You can do it using command line interface or using python.

Command line interface

To run a model specified by the <config_path> config file as a telegram bot with a <telegram_token>:

python -m deeppavlov interactbot <config_path> -t <telegram_token> [-d] [--no-default-skill]
  • -t <telegram_token>: specifies telegram token as <telegram_token>.

  • -d: downloads model specific data before starting the service.

  • -no-default-skill: states that your model is already implements an interface of a Skill and doesn’t need additional wrapping into a stateless skill DefaultStatelessSkill (models from Skills section require the flag).

The command will print the used host and port. Default web service properties (host, port, model endpoint, GET request arguments) can be modified via changing deeppavlov/utils/settings/server_config.json file. Advanced API configuration is described in REST API section.

If you want to get custom /start and /help Telegram messages for the running model you should:

  • Add section to deeppavlov/utils/settings/models_info.json with your custom Telegram messages

  • In model config file specify metadata.labels.telegram_utils parameter with name which refers to the added section of deeppavlov/utils/settings/models_info.json


To run a model specified by a DeepPavlov config <config_path> as as Telegram bot, you have to turn it to a Skill and then make it an Agent.

from deeppavlov import build_model
from deeppavlov.skills.default_skill.default_skill import DefaultStatelessSkill
from deeppavlov.agents.default_agent.default_agent import DefaultAgent
from deeppavlov.agents.processors.highest_confidence_selector import HighestConfidenceSelector
from deeppavlov.utils.telegram.telegram_ui import init_bot_for_model

model = build_model("<config_path>", download=True)

# Step 1: make it a Skill
skill = DefaultStatelessSkill(model)
# Step 2: make it an Agent
agent = DefaultAgent(skills=[skill])
# Step 3: run server
init_bot_for_model(agent, token="<telegram_token>", name="my_model_name")

If your model is already a subclass of Skill or a subclass of Agent (see skills and agents) you can skip corresponding steps.