The session command manages conversation sessions, allowing you to save, resume, and organize multi-turn interactions.
Quick Start
# List all sessions
praisonai session list
# Start a new session
praisonai session start my-project
Commands
Start a Session
praisonai session start my-project
🆕 Starting new session: my-project
Session created successfully!
┌─────────────────────┬────────────────────────────┐
│ Property │ Value │
├─────────────────────┼────────────────────────────┤
│ Session ID │ my-project │
│ Created │ 2024-12-16 15:30:00 │
│ Status │ active │
│ Messages │ 0 │
└─────────────────────┴────────────────────────────┘
You can now run commands with this session context.
Use: praisonai "your prompt" --session my-project
List Sessions
Expected Output:
📋 Available Sessions:
┌────┬─────────────────┬─────────────────────┬──────────┬──────────┐
│ # │ Session ID │ Last Active │ Messages │ Status │
├────┼─────────────────┼─────────────────────┼──────────┼──────────┤
│ 1 │ my-project │ 2024-12-16 15:45 │ 12 │ active │
│ 2 │ research-task │ 2024-12-16 14:20 │ 8 │ paused │
│ 3 │ code-review │ 2024-12-15 10:30 │ 25 │ paused │
│ 4 │ documentation │ 2024-12-14 09:15 │ 5 │ archived │
└────┴─────────────────┴─────────────────────┴──────────┴──────────┘
Total: 4 sessions
Resume a Session
praisonai session resume my-project
▶️ Resuming session: my-project
Session restored successfully!
┌─────────────────────┬────────────────────────────┐
│ Property │ Value │
├─────────────────────┼────────────────────────────┤
│ Session ID │ my-project │
│ Messages │ 12 │
│ Last Message │ "Can you explain..." │
│ Context Size │ 2,456 tokens │
└─────────────────────┴────────────────────────────┘
Session context loaded. Continue your conversation:
Show Session Details
praisonai session show my-project
📊 Session Details: my-project
┌─────────────────────┬────────────────────────────┐
│ Property │ Value │
├─────────────────────┼────────────────────────────┤
│ Session ID │ my-project │
│ Created │ 2024-12-16 15:30:00 │
│ Last Active │ 2024-12-16 15:45:00 │
│ Status │ active │
│ Total Messages │ 12 │
│ User Messages │ 6 │
│ Agent Messages │ 6 │
│ Total Tokens │ 4,523 │
│ Storage Size │ 45 KB │
└─────────────────────┴────────────────────────────┘
Recent Messages:
────────────────────────────────────────────────────
[User] Can you explain the authentication flow?
[Agent] Based on the code, the authentication...
────────────────────────────────────────────────────
[User] How do I add OAuth support?
[Agent] To add OAuth support, you would need to...
────────────────────────────────────────────────────
Delete a Session
praisonai session delete my-project
⚠️ Delete session 'my-project'?
This will permanently remove all conversation history.
Are you sure? (y/N): y
🗑️ Session 'my-project' deleted successfully.
Help
Expected Output:
Session Commands:
praisonai session start <name> - Start a new session
praisonai session list - List all sessions
praisonai session resume <name> - Resume a session
praisonai session show <name> - Show session details
praisonai session delete <name> - Delete a session
praisonai session help - Show this help
Using Sessions with Prompts:
praisonai "prompt" --session <name> - Run with session context
Using Sessions with Prompts
Continue a Conversation
# First message
praisonai "What is Python?" --session learning
# Follow-up (context preserved)
praisonai "How do I install it?" --session learning
# Another follow-up
praisonai "Show me a hello world example" --session learning
📂 Session: learning (3 messages)
╭────────────────────────────────── Response ──────────────────────────────────╮
│ Based on our conversation about Python, here's a hello world example: │
│ │
│ ```python │
│ print("Hello, World!") │
│ ``` │
│ │
│ After installing Python as we discussed, save this to a file called │
│ `hello.py` and run it with `python hello.py` │
╰──────────────────────────────────────────────────────────────────────────────╯
Session with Other Features
# Session with memory
praisonai "Remember my preferences" --session project --memory
# Session with knowledge
praisonai "Search the docs" --session project --knowledge
# Session with planning
praisonai "Plan the implementation" --session project --planning
Use Cases
Project-Based Conversations
# Start project session
praisonai session start website-redesign
# Multiple conversations over time
praisonai "What's the current design?" --session website-redesign
praisonai "Suggest improvements" --session website-redesign
praisonai "Create implementation plan" --session website-redesign
Learning Sessions
# Create learning session
praisonai session start learn-rust
# Progressive learning
praisonai "Explain ownership in Rust" --session learn-rust
praisonai "Show me an example" --session learn-rust
praisonai "What about borrowing?" --session learn-rust
Code Review Sessions
# Start review session
praisonai session start pr-review-123
# Review conversation
praisonai "Review this PR" --session pr-review-123 --fast-context ./src
praisonai "What about security concerns?" --session pr-review-123
praisonai "Summarize the review" --session pr-review-123
Auto-Save Sessions
Automatically save sessions after each agent run using the --auto-save flag:
# Auto-save session with each interaction
praisonai "Analyze this code" --auto-save my-project
# Continue the conversation (auto-saved)
praisonai "Now refactor it" --auto-save my-project
Python API
from praisonaiagents import Agent
agent = Agent(
name="Assistant",
memory=True,
auto_save="my-project" # Auto-save session after each run
)
agent.start("Analyze this code") # Session saved automatically
History in Context
Load conversation history from previous sessions into the current context:
# Load history from last 5 sessions
praisonai "Continue our discussion" --history 5
Python API
from praisonaiagents import Agent
agent = Agent(
name="Assistant",
memory=True,
context=True, # Enable context management for history
)
# Agent now has context from previous sessions
agent.start("What did we discuss yesterday?")
Workflow Checkpoints
Save and resume workflow execution at any step:
from praisonaiagents import AgentFlowManager
manager = WorkflowManager()
# Execute with checkpoints (saves after each step)
result = manager.execute(
"deploy-workflow",
checkpoint="deploy-v1"
)
# Resume from checkpoint if interrupted
result = manager.execute(
"deploy-workflow",
resume="deploy-v1"
)
# List all checkpoints
checkpoints = manager.list_checkpoints()
# Delete a checkpoint
manager.delete_checkpoint("deploy-v1")
Checkpoint Storage
.praison/
└── checkpoints/
├── deploy-v1.json
└── build-v2.json
Session Storage
Sessions are stored locally in ~/.praisonai/memory/{user_id}/sessions/:
~/.praisonai/
└── memory/
└── praison/
└── sessions/
├── my-project.json
├── research-task.json
└── code-review.json
Storage Backend Options
Store sessions in different backends for production deployments:
# List sessions with SQLite backend
praisonai session list --storage-backend sqlite --storage-path ~/.praisonai/sessions.db
# List sessions with Redis backend (for distributed systems)
praisonai session list --storage-backend redis://localhost:6379
# List sessions with file backend (default)
praisonai session list --storage-backend file --storage-path ~/.praisonai/sessions
| Backend | Best For |
|---|
file | Development, debugging |
sqlite | Production, concurrent access |
redis://url | Distributed systems, shared sessions |
Best Practices
Use descriptive session names that reflect the project or task for easy identification.
Long sessions accumulate tokens. Consider starting fresh sessions for unrelated topics.
Naming
Use descriptive names like project-auth-feature
Organization
Create separate sessions for different projects
Cleanup
Delete old sessions to free up storage
Context
Start new sessions when changing topics significantly
