comprehensive-session-management.py

# praisonai: skip=true
"""
Comprehensive Session Management Example

This example demonstrates advanced session management capabilities including
session persistence, recovery, state management, and multi-session coordination.

Features demonstrated:
- Session creation and persistence
- State management across sessions
- Session recovery after interruption
- Multi-user session coordination
- Session-specific memory and knowledge
"""

from praisonaiagents import Agent, Task, AgentTeam
from praisonaiagents.session import Session
from praisonaiagents.tools import duckduckgo
import tempfile
import os
import json

# Create a temporary directory for session storage
session_dir = tempfile.mkdtemp()
print(f"Session storage directory: {session_dir}")

# Create agents for session-based workflows
research_agent = Agent(
    name="SessionResearcher",
    role="Research Specialist",
    goal="Conduct research while maintaining session context",
    backstory="You are a research specialist who maintains context across multiple sessions and can resume work from where you left off.",
    tools=[duckduckgo],
    instructions="Conduct thorough research and maintain awareness of previous session context when available."
)

analysis_agent = Agent(
    name="SessionAnalyst", 
    role="Data Analyst",
    goal="Analyze data while preserving session state",
    backstory="You are a data analyst who can maintain analysis context across sessions and build upon previous work.",
    instructions="Analyze research data and build upon any previous analysis from earlier sessions."
)

# Session 1: Initial Research Session
print("="*70)
print("SESSION 1: INITIAL RESEARCH SESSION")
print("="*70)

# Create first session
session1 = Session(
    session_id="research_project_001",
    user_id="user_researcher_01",
    storage_path=session_dir
)

# Create initial research task
research_task1 = Task(
    name="initial_research",
    description="Research the latest trends in sustainable technology for manufacturing",
    expected_output="Comprehensive research report on sustainable manufacturing technology trends",
    agent=research_agent
)

# Create agents with session
agents_session1 = AgentTeam(
    agents=[research_agent],
    tasks=[research_task1],
    output="verbose"
)

# Execute first session
print("Starting initial research session...")
result1 = agents_session1.start()

# Save session state
session1.save()
print(f"Session 1 completed and saved. Result preview: {str(result1)[:200]}...")

# Session 2: Analysis Session (same user, continuation)
print("\n" + "="*70)
print("SESSION 2: ANALYSIS SESSION (CONTINUING WORK)")
print("="*70)

# Create second session for analysis
session2 = Session(
    session_id="research_project_002", 
    user_id="user_researcher_01",  # Same user
    storage_path=session_dir
)

# Load previous session context (simulating session recovery)
# In real usage, you might load from database or persistent storage
session2.set_state("previous_research_summary", str(result1)[:500])

analysis_task = Task(
    name="trend_analysis",
    description="Analyze the research findings to identify the top 5 most promising sustainable manufacturing technologies",
    expected_output="Analysis report with top 5 sustainable manufacturing technologies and their potential impact",
    agent=analysis_agent,
    # Pass context from previous session
    context_variables={"previous_research": str(result1)}
)

agents_session2 = AgentTeam(
    agents=[analysis_agent],
    tasks=[analysis_task], 
    output="verbose"
)

print("Starting analysis session with previous context...")
result2 = agents_session2.start()

# Save session state
session2.save()
print(f"Session 2 completed and saved. Result preview: {str(result2)[:200]}...")

# Session 3: Recovery Demonstration
print("\n" + "="*70)
print("SESSION 3: RECOVERY DEMONSTRATION")
print("="*70)

# Simulate session recovery after interruption
recovery_session = Session(
    session_id="research_project_recovery",
    user_id="user_researcher_01",
    storage_path=session_dir
)

# Load state from previous sessions
recovery_session.set_state("research_summary", str(result1)[:300])
recovery_session.set_state("analysis_summary", str(result2)[:300])

# Create a synthesis task that uses recovered session state
synthesis_agent = Agent(
    name="SynthesisAgent",
    role="Research Synthesizer", 
    goal="Synthesize research and analysis into actionable recommendations",
    backstory="You synthesize research and analysis from multiple sessions into comprehensive recommendations.",
    instructions="Use the session context to create comprehensive recommendations based on all previous work."
)

synthesis_task = Task(
    name="synthesis_report",
    description="Create a comprehensive synthesis report with actionable recommendations based on all previous research and analysis",
    expected_output="Executive synthesis report with strategic recommendations",
    agent=synthesis_agent,
    # Access session state
    context_variables={
        "research_context": recovery_session.get_state("research_summary"),
        "analysis_context": recovery_session.get_state("analysis_summary")
    }
)

agents_recovery = AgentTeam(
    agents=[synthesis_agent],
    tasks=[synthesis_task],
    output="verbose"
)

print("Starting recovery session with full context from previous sessions...")
result3 = agents_recovery.start()

# Save final session
recovery_session.save()
print(f"Recovery session completed. Result preview: {str(result3)[:200]}...")

# Session 4: Multi-User Coordination Demo
print("\n" + "="*70) 
print("SESSION 4: MULTI-USER COORDINATION DEMO")
print("="*70)

# Create sessions for different users working on the same project
reviewer_session = Session(
    session_id="peer_review_001",
    user_id="user_reviewer_01",
    storage_path=session_dir
)

# Reviewer can access shared project context
reviewer_session.set_state("shared_research", str(result1)[:400])
reviewer_session.set_state("shared_analysis", str(result2)[:400])
reviewer_session.set_state("shared_synthesis", str(result3)[:400])

review_agent = Agent(
    name="PeerReviewer",
    role="Research Peer Reviewer",
    goal="Provide expert peer review of research, analysis, and synthesis",
    backstory="You are a peer reviewer who evaluates research quality and provides constructive feedback.",
    instructions="Review all provided work and provide constructive feedback with specific suggestions for improvement."
)

review_task = Task(
    name="peer_review",
    description="Conduct peer review of the research project including research, analysis, and synthesis phases",
    expected_output="Comprehensive peer review with specific feedback and recommendations for improvement",
    agent=review_agent,
    context_variables={
        "research_to_review": reviewer_session.get_state("shared_research"),
        "analysis_to_review": reviewer_session.get_state("shared_analysis"), 
        "synthesis_to_review": reviewer_session.get_state("shared_synthesis")
    }
)

agents_reviewer = AgentTeam(
    agents=[review_agent],
    tasks=[review_task],
    output="verbose"
)

print("Starting peer review session by different user...")
result4 = agents_reviewer.start()

# Save reviewer session
reviewer_session.save()
print(f"Peer review session completed. Result preview: {str(result4)[:200]}...")

# Session Summary and Cleanup
print("\n" + "="*80)
print("SESSION MANAGEMENT DEMONSTRATION SUMMARY")
print("="*80)

# Display session information
print("Sessions created:")
print(f"1. Research Session (ID: research_project_001, User: user_researcher_01)")
print(f"2. Analysis Session (ID: research_project_002, User: user_researcher_01)")  
print(f"3. Recovery Session (ID: research_project_recovery, User: user_researcher_01)")
print(f"4. Review Session (ID: peer_review_001, User: user_reviewer_01)")

print("\nSession capabilities demonstrated:")
print("- Session persistence and state management")
print("- Context passing between sessions")
print("- Session recovery after interruption")
print("- Multi-user session coordination")
print("- State sharing across different users")
print("- Session-specific task execution")

# List session files created
session_files = [f for f in os.listdir(session_dir) if f.endswith('.json')]
print(f"\nSession files created: {len(session_files)}")
for file in session_files:
    print(f"  - {file}")

# Cleanup
import shutil
shutil.rmtree(session_dir)
print(f"\nCleanup completed. Temporary session directory removed.")