The session system provides stateful conversation management and remote agent connectivity, enabling persistent interactions and distributed agent deployments.
# Create new session instancesession = Session(session_id="chat_123")# Restore previous statesession.restore_state()# Continue where you left offagent = session.Agent(name="Assistant")response = agent.chat("What were we discussing?")
from praisonaiagents import Session, Task, PraisonAIAgents# Create or restore sessionsession = Session( session_id="personal_assistant", user_id="john_doe", memory_config={ "provider": "rag", "use_embedding": True }, knowledge_config={ "vector_store": { "provider": "chroma", "config": {"collection_name": "personal_docs"} } })# Try to restore previous statetry: session.restore_state() print("Restored previous session")except: print("Starting new session")# Create session agentassistant = session.Agent( name="Personal Assistant", instructions="""You are a personal assistant that remembers everything. Use your memory and knowledge to provide personalised help.""", memory=True, knowledge=True)# Add some knowledgesession.add_knowledge("calendar.pdf")session.add_memory("User prefers morning meetings")# Have a conversationresponse = assistant.chat("Schedule a meeting for tomorrow")print(response)# Save state for next timesession.save_state()