Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.agno.com/llms.txt

Use this file to discover all available pages before exploring further.

Code

basic.py
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.google import Gemini
from agno.os.app import AgentOS
from agno.os.interfaces.telegram import Telegram

agent_db = SqliteDb(session_table="telegram_sessions", db_file="tmp/telegram_basic.db")

telegram_agent = Agent(
    name="Telegram Bot",
    model=Gemini(id="gemini-2.5-pro"),
    db=agent_db,
    instructions=[
        "You are a helpful assistant on Telegram.",
        "Keep responses concise and friendly.",
        "When in a group, you respond only when mentioned with @.",
    ],
    add_history_to_context=True,
    num_history_runs=3,
    add_datetime_to_context=True,
    markdown=True,
)

agent_os = AgentOS(
    agents=[telegram_agent],
    interfaces=[
        Telegram(
            agent=telegram_agent,
            reply_to_mentions_only=True,
        )
    ],
)
app = agent_os.get_app()

if __name__ == "__main__":
    agent_os.serve(app="basic:app", reload=True)

Usage

1

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate
2

Set Environment Variables

export TELEGRAM_TOKEN=your-bot-token-from-botfather
export GOOGLE_API_KEY=your-google-api-key
export APP_ENV=development
3

Install dependencies

uv pip install -U "agno[telegram]"
4

Run Example

python basic.py

Key Features

  • Telegram Integration: Responds to direct messages and group @mentions
  • Conversation History: Maintains context with last 3 interactions
  • Persistent Memory: SQLite database for session storage
  • Group Chat Support: Only responds when mentioned in groups
  • DateTime Context: Time-aware responses