Session Persistence

from praisonaiagents import Agent

agent = Agent(
    name="Reviewer",
    instructions="Review the codebase and answer follow-ups",
    memory={"session_id": "review-2026-06-25"},
)
agent.start("Summarise the auth module")

from praisonaiagents import Agent

# First conversation
agent = Agent(
    name="Assistant",
    memory={"session_id": "my-session-123"}
)
agent.start("My name is Alice and I love pizza")

# Later, in a new process - history is restored automatically
agent = Agent(
    name="Assistant", 
    memory={"session_id": "my-session-123"}
)
agent.start("What is my name?")  # Agent remembers: "Alice"

from praisonaiagents import Agent

agent = Agent(name="Assistant")

# First message
agent.chat("My favorite number is 42")

# Second message - agent remembers
agent.chat("What is my favorite number?")  # Agent responds: "42"

from praisonaiagents import Agent

# Create agent with session_id
agent = Agent(
    name="Assistant",
    instructions="You are a helpful assistant.",
    memory={"session_id": "user-123-chat"}
)

# Conversation is automatically persisted
response = agent.chat("Remember that my birthday is January 15th")

# In a new Python process or after restart
from praisonaiagents import Agent

# Same session_id restores history
agent = Agent(
    name="Assistant",
    instructions="You are a helpful assistant.",
    memory={"session_id": "user-123-chat"}
)

# Agent remembers previous conversation
response = agent.chat("When is my birthday?")
# Agent responds: "Your birthday is January 15th"

{
  "session_id": "user-123-chat",
  "messages": [
    {"role": "user", "content": "Remember my birthday is January 15th", "timestamp": 1704153600.0},
    {"role": "assistant", "content": "I'll remember that!", "timestamp": 1704153601.5}
  ],
  "created_at": "2026-01-02T04:00:00+00:00",
  "updated_at": "2026-01-02T04:01:00+00:00",
  "agent_name": "Assistant",
  "model": "gpt-4o",
  "total_tokens": 125,
  "cost": 0.0032,
  "agent_id": "assistant-001",
  "source": "chat"
}

from praisonaiagents.session import get_default_session_store

store = get_default_session_store()
store.update_session_metadata(
    "user-123-chat",
    custom_field="my value",
    model="gpt-4o-mini",
    total_tokens=125,
)

from praisonaiagents.session import get_default_session_store

store = get_default_session_store()

# Add messages
store.add_user_message("session-123", "Hello")
store.add_assistant_message("session-123", "Hi there!")

# Get history
history = store.get_chat_history("session-123")
# [{"role": "user", "content": "Hello"}, {"role": "assistant", "content": "Hi there!"}]

# List all sessions
sessions = store.list_sessions()

# Delete a session
store.delete_session("session-123")

from praisonaiagents.session import DefaultSessionStore

store = DefaultSessionStore(
    session_dir="/custom/path/sessions",
    max_messages=200,        # Default: 100
    lock_timeout=10.0,       # Default: 5.0 seconds
    retention="compact",     # "compact" (default) | "truncate" | "keep_all"
    active_window=200,       # Recent turns kept live; defaults to max_messages
)

from praisonaiagents import Agent

# Custom DB adapter (e.g., PostgreSQL, MongoDB)
class MyDbAdapter:
    def on_agent_start(self, agent_name, session_id, user_id=None, metadata=None):
        # Load history from database
        return []
    
    def on_user_message(self, session_id, content):
        # Save user message to database
        pass
    
    def on_agent_message(self, session_id, content):
        # Save agent message to database
        pass

agent = Agent(
    name="Assistant",
    memory={"session_id": "my-session"},
    db=MyDbAdapter()
)

agent = Agent(
    name="Assistant",
    memory={"session_id": "my-session"},
    caching=True,  # Enables Anthropic prompt caching
)

channels:
  telegram:
    token: ${TELEGRAM_TOKEN}
    session:
      max_history: 50
      reset:
        mode: idle
        idle_minutes: 30

from praisonaiagents import Agent
from praisonai.bots import TelegramBot

bot = TelegramBot(
    token="YOUR_BOT_TOKEN",
    agent=Agent(name="Assistant", instructions="Help users."),
)
bot.run()

from praisonaiagents.session import SessionStoreProtocol

# Any class with these 5 methods satisfies the protocol:
# add_message(), get_chat_history(), clear_session(),
# delete_session(), session_exists()

assert isinstance(get_default_session_store(), SessionStoreProtocol)

from praisonaiagents import Agent

# Long conversations are now safe — older turns are summarised and archived,
# not silently dropped. This is the default behaviour.
agent = Agent(
    name="assistant",
    instructions="Answer helpfully, remembering everything the user has told you.",
    memory={"session_id": "my-long-chat"},
)

# 100+ turns later, the earliest questions the user asked are still
# accessible — as a summary in the active window, and raw in the archive.
agent.start("What was the first thing I asked you?")

export PRAISONAI_SESSION_RETENTION=compact       # default
export PRAISONAI_SESSION_ACTIVE_WINDOW=200       # keep 200 recent turns live

from praisonaiagents.session import DefaultSessionStore

store = DefaultSessionStore(
    retention="compact",     # or "truncate", or "keep_all"
    active_window=200,       # optional; defaults to max_messages
)

# Passing max_messages != 100 with NO explicit retention keeps the
# LEGACY truncate behaviour. This is intentional backward compatibility.
# Set retention="compact" explicitly to opt into non-destructive rollup.
store = DefaultSessionStore(max_messages=50)  # -> truncate
store = DefaultSessionStore(max_messages=50, retention="compact")  # -> compact