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Code

cookbook/05_agent_os/interfaces/whatsapp/basic.py
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIChat
from agno.os.app import AgentOS
from agno.os.interfaces.whatsapp import Whatsapp

agent_db = SqliteDb(db_file="tmp/persistent_memory.db")
basic_agent = Agent(
    name="Basic Agent",
    model=OpenAIChat(id="gpt-4o"),
    db=agent_db,
    add_history_to_context=True,
    num_history_runs=3,
    add_datetime_to_context=True,
    markdown=True,
    instructions=[
        "You are chatting on WhatsApp. Keep responses conversational and natural.",
        "Structure your responses as separate short paragraphs separated by double newlines.",
    ],
)

agent_os = AgentOS(
    agents=[basic_agent],
    interfaces=[Whatsapp(agent=basic_agent)],
)
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 WHATSAPP_ACCESS_TOKEN=your_access_token
export WHATSAPP_PHONE_NUMBER_ID=your_phone_number_id
export WHATSAPP_VERIFY_TOKEN=your_verify_token
export WHATSAPP_SKIP_SIGNATURE_VALIDATION=true  # For local dev
export OPENAI_API_KEY=your_openai_api_key
See the WhatsApp Bot setup guide for how to get these values from the Meta Developer Dashboard.
3

Install dependencies

uv pip install -U agno openai
4

Run Example

python cookbook/05_agent_os/interfaces/whatsapp/basic.py

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Key Features

  • WhatsApp Integration: Responds to messages via the WhatsApp Business API
  • Conversation History: Maintains context with last 3 interactions
  • Persistent Memory: SQLite database for session storage
  • Session Reset: Users can send /new to start a fresh conversation
  • Markdown Support: Rich text formatting in messages