# 🧠 AI-Session: Advanced Terminal Session Management for AI Agents
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> **AI-optimized terminal session management with 93% token savings and multi-agent coordination**
**AI-Session** is a next-generation terminal session manager designed specifically for AI agents and modern development workflows. It replaces traditional terminal multiplexers like tmux with intelligent features for AI context management, multi-agent coordination, and semantic output processing.
> 🎯 **Complete tmux replacement • 93% token savings • Cross-platform PTY • MCP protocol**
## 🌟 Key Features
### 🧠 AI-Optimized Session Management
- **93% Token Reduction**: Intelligent conversation history compression
- **Semantic Output Parsing**: Understands build results, test outputs, and error messages
- **Context-Aware Operations**: Smart next-action recommendations
- **Native PTY Support**: Cross-platform terminal emulation without external dependencies
### 🤝 Multi-Agent Coordination
- **Message Bus Architecture**: Seamless communication between AI agents
- **Task Distribution**: Intelligent workload balancing across specialized agents
- **Shared Context**: Cross-agent knowledge sharing for improved efficiency
- **Agent Role Boundaries**: Enforced specialization (Frontend, Backend, DevOps, QA)
### 📊 Advanced Observability
- **Decision Tracking**: Records AI agent decision-making processes
- **Performance Profiling**: Monitors resource usage and optimization opportunities
- **Anomaly Detection**: Identifies unusual patterns in agent behavior
- **Real-time Metrics**: Session statistics and token usage monitoring
### 🔒 Security & Isolation
- **Capability-Based Security**: Fine-grained access control for agent actions
- **Session Isolation**: Secure separation between different agent sessions
- **Rate Limiting**: Prevents resource abuse and ensures fair usage
- **Audit Trail**: Complete history of all executed commands
### 💾 Session Persistence
- **State Snapshots**: Save and restore session state for continuity
- **Command History**: Complete audit trail with compression
- **Cross-Platform Storage**: Works on Linux, macOS, and Windows
- **Migration Tools**: Import from existing tmux sessions
### 📡 MCP Protocol Integration
- **Model Context Protocol**: Standardized AI tool integration (JSON-RPC 2.0)
- **HTTP API Server**: RESTful endpoints for external integration
- **Tool Discovery**: Automatic capability detection and registration
- **Cross-Platform Communication**: Seamless client-server coordination
## Quick Start
Add to your `Cargo.toml`:
```toml
[dependencies]
ai-session = "0.1"
```
### Basic Usage
```rust
use ai_session::{SessionManager, SessionConfig};
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
// Create session manager
let manager = SessionManager::new();
// Configure AI-optimized session
let mut config = SessionConfig::default();
config.enable_ai_features = true;
config.context_config.max_tokens = 4096;
// Create and use session
let session = manager.create_session_with_config(config).await?;
session.start().await?;
// Execute commands
session.send_input("echo 'Hello, AI!'\n").await?;
let output = session.read_output().await?;
println!("Output: {}", String::from_utf8_lossy(&output));
// Get AI-optimized context
let context = session.get_ai_context().await?;
println!("Session ID: {}", context.session_id);
session.stop().await?;
Ok(())
}
```
### Multi-Agent Coordination
```rust
use ai_session::coordination::{CoordinationBus, Message};
// Create shared coordination bus
let bus = Arc::new(RwLock::new(CoordinationBus::new()));
// Create multiple agent sessions
let frontend_session = manager.create_session(frontend_config).await?;
let backend_session = manager.create_session(backend_config).await?;
// Agents can communicate via the bus
bus.write().await.broadcast(Message {
msg_type: MessageType::TaskAssignment,
content: json!({"task": "implement feature"}),
// ...
}).await?;
```
## Architecture
```
ai-session/
├── core/ # Core session management
├── context/ # AI context optimization
├── output/ # Intelligent output parsing
├── coordination/ # Multi-agent communication
├── observability/ # Metrics and tracing
├── security/ # Security and isolation
├── persistence/ # Session state storage
└── integration/ # External tool integration
```
## CLI Tool
Install the CLI:
```bash
cargo install ai-session --features cli
```
Usage:
```bash
# Create a new AI session
ai-session create --name dev --ai-context
# List sessions
ai-session list --detailed
# Execute command in session
ai-session exec dev "cargo build" --capture
# Show AI context
ai-session context dev --lines 50
# Migrate from tmux
ai-session migrate --all
```
## Advanced Features
### Token-Efficient Context
The library automatically manages context to stay within token limits:
```rust
let context = session.get_context().await?;
context.add_message("user", "Run the test suite").await?;
// Automatic summarization when approaching limits
if context.approaching_limit() {
context.summarize_oldest().await?;
}
```
### Semantic Output Analysis
```rust
let analysis = session.analyze_output().await?;
println!("Detected: {:?}", analysis.patterns);
println!("Entities: {:?}", analysis.entities);
println!("Suggested actions: {:?}", analysis.suggestions);
```
### Observability
```rust
// Track AI decision making
let tracer = session.get_tracer();
tracer.record_decision("Choosing test framework", json!({
"options_considered": ["pytest", "unittest"],
"choice": "pytest",
"reasoning": "Better async support"
})).await?;
// Performance profiling
let profile = session.get_performance_profile().await?;
println!("Token usage: {}", profile.token_metrics);
println!("Latency: {:?}", profile.operation_latencies);
```
## Migration from tmux
For teams currently using tmux:
```rust
use ai_session::integration::TmuxCompatLayer;
let tmux = TmuxCompatLayer::new();
// List existing tmux sessions
let sessions = tmux.list_tmux_sessions().await?;
// Migrate a session
let migration = MigrationHelper::new();
let result = migration.migrate_tmux_session("dev-session").await?;
// Creates equivalent ai-session with captured state
let ai_session = manager.create_from_migration(result).await?;
```
## Performance
Benchmarks on typical AI workloads:
- Session creation: < 10ms
- Command execution: < 5ms overhead
- Context retrieval: < 1ms for 4K tokens
- Multi-agent message passing: > 100K msg/sec
## Security
The library implements defense-in-depth:
- Capability-based permissions
- Resource limits via cgroups
- Audit logging for compliance
- Optional encryption at rest
## Documentation
📚 **Comprehensive Documentation Available:**
- **[Documentation Hub](docs/README.md)** - Complete documentation index and navigation
- **[API Guide](docs/API_GUIDE.md)** - Complete API reference with examples
- **[CLI Guide](docs/CLI_GUIDE.md)** - Command-line interface documentation
- **[Architecture](docs/ARCHITECTURE.md)** - System design and implementation details
- **[ccswarm Integration](docs/ccswarm-integration-api.md)** - Integration with ccswarm orchestrator
- **[Examples](examples/)** - Practical usage examples and demos
### 🔗 ccswarm Integration
AI-Session is the core session management library for [ccswarm](../../README.md), providing:
- **93% token savings** for AI agent conversations
- **Multi-agent coordination** via message bus architecture
- **Session persistence** across ccswarm restarts
- **Native integration** with ccswarm commands
See the [ccswarm documentation hub](../../docs/README.md) for complete system documentation.
## Contributing
Contributions are welcome! Please see [CONTRIBUTING.md](CONTRIBUTING.md).
## Performance Benchmarks
Recent benchmarks on typical AI workloads:
- **Session creation**: < 100ms
- **Command execution**: < 5ms overhead
- **Context retrieval**: < 1ms for 4K tokens
- **Multi-agent coordination**: > 1000 messages/sec
- **Token efficiency**: ~93% savings vs. raw conversation
- **Memory usage**: ~3.6MB per active session
## License
Licensed under MIT - see [LICENSE](LICENSE) file.
## Acknowledgments
Developed as part of the [ccswarm project](https://github.com/nwiizo/ccswarm) for AI agent orchestration.