Last N Messages

This example demonstrates how to configure agents to search through previous sessions and limit the number of historical sessions included in context. This helps manage context length while maintaining relevant conversation history.

1. Create a Python file

   last_n_session_messages.py

   import os
   
   from agno.agent import Agent
   from agno.db.sqlite import SqliteDb
   from agno.models.openai import OpenAIResponses
   
   # Remove the tmp db file before running the script
   os.remove("tmp/data.db")
   
   agent = Agent(
       model=OpenAIResponses(id="gpt-5.2"),
       user_id="user_1",
       db=SqliteDb(db_file="tmp/data.db"),
       add_history_to_context=True,
       num_history_runs=3,
       search_session_history=True,  # allow searching previous sessions
       num_history_sessions=2,  # only include the last 2 sessions in the search to avoid context length issues
   )
   
   session_1_id = "session_1_id"
   session_2_id = "session_2_id"
   session_3_id = "session_3_id"
   session_4_id = "session_4_id"
   session_5_id = "session_5_id"
   
   agent.print_response("What is the capital of South Africa?", session_id=session_1_id)
   agent.print_response("What is the capital of China?", session_id=session_2_id)
   agent.print_response("What is the capital of France?", session_id=session_3_id)
   agent.print_response("What is the capital of Japan?", session_id=session_4_id)
   agent.print_response(
       "What did I discuss in my previous conversations?", session_id=session_5_id
   )  # It should only include the last 2 sessions
   
2. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   
3. Install dependencies

   uv pip install -U agno openai
   
4. Export your OpenAI API key

   Set OpenAI Key

   Set your OPENAI_API_KEY as an environment variable. You can get one from OpenAI.

   Mac

   export OPENAI_API_KEY=sk-***
   
5. Run Agent

   python last_n_session_messages.py