In-Memory Storage

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.storage.in_memory import InMemoryStorage

agent = Agent(
    model=OpenAIChat(id="gpt-4o-mini"),
    storage=InMemoryStorage(),
    add_history_to_messages=True,
)

# Run some conversations
agent.print_response("What is the capital of France?")
agent.print_response("What is its population?")

import json

import boto3
from agno.storage.in_memory import InMemoryStorage
from agno.agent import Agent
from agno.models.openai import OpenAIChat

# Example: Save and load sessions to/from S3
def save_sessions_to_s3(sessions_dict, bucket_name, key_name):
    """Save sessions dictionary to S3"""
    s3 = boto3.client('s3')
    s3.put_object(
        Bucket=bucket_name,
        Key=key_name,
        Body=json.dumps(sessions_dict, default=str)
    )

def load_sessions_from_s3(bucket_name, key_name):
    """Load sessions dictionary from S3"""
    s3 = boto3.client('s3')
    try:
        response = s3.get_object(Bucket=bucket_name, Key=key_name)
        return json.loads(response['Body'].read())
    except:
        return {}  # Return empty dict if file doesn't exist

# Step 1: Create agent with external dictionary
my_sessions = {}
storage = InMemoryStorage(storage_dict=my_sessions)

agent = Agent(
    model=OpenAIChat(id="gpt-4o-mini"),
    storage=storage,
    add_history_to_messages=True,
)

# Run some conversations
agent.print_response("What is the capital of France?")
agent.print_response("What is its population?")

print(f"Sessions in memory: {len(my_sessions)}")

# Step 2: Save sessions to S3
save_sessions_to_s3(my_sessions, "my-bucket", "agent-sessions.json")
print("Sessions saved to S3!")

# Step 3: Later, load sessions from S3 and use with new agent
loaded_sessions = load_sessions_from_s3("my-bucket", "agent-sessions.json")
new_storage = InMemoryStorage(storage_dict=loaded_sessions)

new_agent = Agent(
    model=OpenAIChat(id="gpt-4o-mini"),
    storage=new_storage,
    session_id=agent.session_id,  # Use same session ID
    add_history_to_messages=True,
)

# This agent now has access to the previous conversation
new_agent.print_response("What was my first question?")