import json
from textwrap import dedent
from typing import Optional
import typer
from agno.agent import Agent
from agno.memory.v2.db.sqlite import SqliteMemoryDb
from agno.memory.v2.memory import Memory
from agno.models.openai import OpenAIChat
from agno.storage.sqlite import SqliteStorage
from rich.console import Console
from rich.json import JSON
from rich.panel import Panel
from rich.prompt import Prompt
def create_agent(user: str = "user"):
session_id: Optional[str] = None
# Ask if user wants to start new session or continue existing one
new = typer.confirm("Do you want to start a new session?")
# Initialize storage for both agent sessions and memories
agent_storage = SqliteStorage(table_name="agent_memories", db_file="tmp/agents.db")
if not new:
existing_sessions = agent_storage.get_all_session_ids(user)
if len(existing_sessions) > 0:
session_id = existing_sessions[0]
agent = Agent(
model=OpenAIChat(id="gpt-4o"),
user_id=user,
session_id=session_id,
# Configure memory system with SQLite storage
memory=Memory(
db=SqliteMemoryDb(
table_name="agent_memory",
db_file="tmp/agent_memory.db",
),
),
enable_user_memories=True,
enable_session_summaries=True,
storage=agent_storage,
add_history_to_messages=True,
num_history_responses=3,
# Enhanced system prompt for better personality and memory usage
description=dedent("""\
You are a helpful and friendly AI assistant with excellent memory.
- Remember important details about users and reference them naturally
- Maintain a warm, positive tone while being precise and helpful
- When appropriate, refer back to previous conversations and memories
- Always be truthful about what you remember or don't remember"""),
)
if session_id is None:
session_id = agent.session_id
if session_id is not None:
print(f"Started Session: {session_id}\n")
else:
print("Started Session\n")
else:
print(f"Continuing Session: {session_id}\n")
return agent
def print_agent_memory(agent):
"""Print the current state of agent's memory systems"""
console = Console()
messages = []
session_id = agent.session_id
session_run = agent.memory.runs[session_id][-1]
for m in session_run.messages:
message_dict = m.to_dict()
messages.append(message_dict)
# Print chat history
console.print(
Panel(
JSON(
json.dumps(
messages,
),
indent=4,
),
title=f"Chat History for session_id: {session_run.session_id}",
expand=True,
)
)
# Print user memories
for user_id in list(agent.memory.memories.keys()):
console.print(
Panel(
JSON(
json.dumps(
[
user_memory.to_dict()
for user_memory in agent.memory.get_user_memories(user_id=user_id)
],
indent=4,
),
),
title=f"Memories for user_id: {user_id}",
expand=True,
)
)
# Print session summary
for user_id in list(agent.memory.summaries.keys()):
console.print(
Panel(
JSON(
json.dumps(
[
summary.to_dict()
for summary in agent.memory.get_session_summaries(user_id=user_id)
],
indent=4,
),
),
title=f"Summary for session_id: {agent.session_id}",
expand=True,
)
)
def main(user: str = "user"):
"""Interactive chat loop with memory display"""
agent = create_agent(user)
print("Try these example inputs:")
print("- 'My name is [name] and I live in [city]'")
print("- 'I love [hobby/interest]'")
print("- 'What do you remember about me?'")
print("- 'What have we discussed so far?'\n")
exit_on = ["exit", "quit", "bye"]
while True:
message = Prompt.ask(f"[bold] :sunglasses: {user} [/bold]")
if message in exit_on:
break
agent.print_response(message=message, stream=True, markdown=True)
print_agent_memory(agent)
if __name__ == "__main__":
typer.run(main)
