# Synqed Workspace - Feature Release Notes

## Version 1.0.6 - Workspace & Collaboration

### 🎉 Major New Feature: Workspace

We're excited to introduce **Workspace**, a powerful new feature that enables true multi-agent collaboration in Synqed!

---

## What is Workspace?

Workspace provides a collaborative sandbox environment where AI agents can:

- **Work together** on complex, multi-step tasks
- **Share artifacts** (files, data, results) between agents
- **Maintain shared state** accessible to all participants
- **Communicate directly** with each other
- **Track progress** through comprehensive message history

Think of it as a "project room" for your AI agents—a place where they can collaborate, share resources, and build on each other's work.

---

## Key Features

### 🤝 Multi-Agent Collaboration
Execute tasks across multiple specialized agents with intelligent task distribution.

```python
workspace = synqed.Workspace(name="Content Creation")
workspace.add_agent(research_agent)
workspace.add_agent(writing_agent)

await workspace.start()
results = await workspace.collaborate("Research and write an article on AI")
```

### 📦 Artifact Management
Share files, data, and results between agents with persistent storage.

```python
# Create artifact
workspace.add_artifact(
    name="data.json",
    artifact_type="data",
    content={"sales": [100, 150, 200]},
    created_by="agent1"
)

# Get artifacts
artifacts = workspace.get_artifacts(artifact_type="data")
```

### 💾 Shared State
Maintain context across interactions with a key-value store.

```python
workspace.set_shared_state("project_id", "proj-123")
workspace.set_shared_state("deadline", "2025-12-31")

project_id = workspace.get_shared_state("project_id")
```

### 📬 Message System
Complete message history with filtering and real-time callbacks.

```python
# Get recent messages
messages = workspace.get_messages(limit=10)

# Filter by type
agent_messages = workspace.get_messages(message_type=MessageType.AGENT)

# Real-time callbacks
workspace.on_message(async_callback_function)
```

### 🎯 Orchestrator Integration
Combine with Orchestrator for intelligent agent selection.

```python
orchestrator = synqed.Orchestrator(...)
results = await workspace.collaborate(
    "Complex task",
    orchestrator=orchestrator  # Automatically selects best agents
)
```

### 🔄 Lifecycle Management
Full control over workspace state.

```python
await workspace.start()   # Activate workspace
await workspace.pause()   # Pause operations
await workspace.resume()  # Resume operations
await workspace.complete() # Mark as completed
await workspace.close()   # Cleanup resources
```

### 💬 Direct Communication
Send messages to specific agents or broadcast to all.

```python
# Direct message
response = await workspace.send_message_to_agent(agent_id, "Task")

# Broadcast
responses = await workspace.broadcast_message("Status update?")
```

### 💾 Persistence & Export
Save workspace state and export for auditing.

```python
workspace = synqed.Workspace(
    name="Important Project",
    enable_persistence=True,
    auto_cleanup=False
)

# Export workspace
export_path = await workspace.export_workspace()
```

---

## Quick Start

### Basic Usage

```python
import synqed
import asyncio

async def main():
    # Create agents
    agent1 = synqed.Agent(
        name="ResearchAgent",
        description="Research expert",
        skills=["research", "analysis"]
    )
    
    agent2 = synqed.Agent(
        name="WriterAgent",
        description="Content creator",
        skills=["writing", "editing"]
    )
    
    # Start servers
    server1 = synqed.AgentServer(agent1, port=8001)
    server2 = synqed.AgentServer(agent2, port=8002)
    
    await server1.start_background()
    await server2.start_background()
    
    # Create workspace
    workspace = synqed.Workspace(
        name="Content Creation",
        description="Research and write articles"
    )
    
    # Add agents
    workspace.add_agent(agent1)
    workspace.add_agent(agent2)
    
    # Start collaboration
    await workspace.start()
    
    # Execute task
    results = await workspace.collaborate(
        "Research AI trends and write a summary"
    )
    
    print(results)
    
    # Cleanup
    await workspace.close()
    await server1.stop()
    await server2.stop()

asyncio.run(main())
```

### Context Manager Usage

```python
async with synqed.Workspace(name="Project") as workspace:
    workspace.add_agent(agent1)
    workspace.add_agent(agent2)
    
    results = await workspace.collaborate("Task")
    # Automatically cleaned up on exit
```

---

## New API

### Workspace Class

```python
Workspace(
    name: str,
    description: str,
    workspace_id: str | None = None,
    workspace_dir: Path | None = None,
    auto_cleanup: bool = True,
    enable_persistence: bool = False,
    max_messages: int = 1000,
    message_retention_hours: int = 24
)
```

### Main Methods

- `add_agent()` - Add agent to workspace
- `remove_agent()` - Remove agent from workspace
- `list_participants()` - List all participants
- `start()` - Start workspace
- `pause()` / `resume()` - Pause/resume operations
- `complete()` - Mark as completed
- `close()` - Cleanup resources
- `collaborate()` - Execute collaborative task
- `send_message_to_agent()` - Direct messaging
- `broadcast_message()` - Broadcast to all agents
- `add_artifact()` - Create artifact
- `get_artifact()` / `get_artifacts()` - Retrieve artifacts
- `set_shared_state()` / `get_shared_state()` - Manage state
- `get_messages()` - Retrieve messages
- `on_message()` - Register callback
- `export_workspace()` - Export to JSON

### New Enums

```python
class WorkspaceState(Enum):
    CREATED = "created"
    ACTIVE = "active"
    PAUSED = "paused"
    COMPLETED = "completed"
    CANCELLED = "cancelled"
    ERROR = "error"

class MessageType(Enum):
    SYSTEM = "system"
    AGENT = "agent"
    USER = "user"
    ARTIFACT = "artifact"
    STATUS = "status"
```

### New Data Classes

- `WorkspaceMessage` - Message in workspace
- `WorkspaceArtifact` - Artifact in workspace
- `WorkspaceParticipant` - Participant information

---

## Examples

### Example 1: Recipe Planning

```python
# Create specialized agents
recipe_agent = synqed.Agent(
    name="RecipeAgent",
    skills=["recipe_search", "meal_planning"]
)

shopping_agent = synqed.Agent(
    name="ShoppingAgent",
    skills=["shopping_list", "ingredient_organization"]
)

# Create workspace
workspace = synqed.Workspace(name="Meal Planning")
workspace.add_agent(recipe_agent)
workspace.add_agent(shopping_agent)

await workspace.start()

# Collaborate
results = await workspace.collaborate(
    "Plan a week of healthy dinners and create a shopping list"
)
```

### Example 2: Data Analysis Pipeline

```python
# Create pipeline agents
collector = synqed.Agent(name="DataCollector", skills=["collection"])
analyzer = synqed.Agent(name="DataAnalyzer", skills=["analysis"])
reporter = synqed.Agent(name="Reporter", skills=["reporting"])

# Create workspace with persistence
workspace = synqed.Workspace(
    name="Data Pipeline",
    enable_persistence=True,
    auto_cleanup=False
)

workspace.add_agent(collector)
workspace.add_agent(analyzer)
workspace.add_agent(reporter)

await workspace.start()

# Stage 1: Collection
data = await workspace.send_message_to_agent(collector_id, "Collect data")
workspace.add_artifact("raw_data.json", "data", data, "collector")

# Stage 2: Analysis
analysis = await workspace.send_message_to_agent(analyzer_id, "Analyze data")

# Stage 3: Report
report = await workspace.send_message_to_agent(reporter_id, "Generate report")

# Export
await workspace.export_workspace()
```

---

## Documentation

Comprehensive documentation available:

- **Main README**: Updated with Workspace section
- **API Reference**: Full API documentation in WORKSPACE.md
- **Examples**: 
  - `workspace_basic.py` - Basic usage
  - `workspace_orchestrated.py` - With Orchestrator
  - `workspace_artifacts.py` - Artifact sharing
- **Tests**: Complete test suite in `tests/test_workspace.py`

---

## Installation & Upgrade

### New Installation

```bash
pip install synqed
```

### Upgrade from Previous Version

```bash
pip install --upgrade synqed
```

---

## Breaking Changes

**None!** This is a fully backward-compatible release. All existing code will continue to work without modifications.

---

## Use Cases

### 1. Content Creation Pipelines
Research → Writing → Editing → Publishing

### 2. Data Analysis Workflows
Collection → Processing → Analysis → Reporting

### 3. Software Development
Requirements → Design → Implementation → Testing

### 4. Multi-Step Research
Research → Synthesis → Writing → Fact-Checking

### 5. Customer Support
Ticket Analysis → Response Generation → Quality Check

---

## Technical Details

### Architecture
- **Isolated environments** for each workspace
- **File system integration** for artifact storage
- **Async-first design** for performance
- **Thread-safe** state management
- **Automatic cleanup** with context managers

### Performance
- **Lightweight**: Minimal overhead per workspace
- **Scalable**: Handle multiple concurrent workspaces
- **Efficient**: Lazy resource allocation
- **Fast**: Async operations throughout

### Storage
- Workspaces stored in `~/.synqed/workspaces/` by default
- Customizable workspace directories
- JSON export format for portability
- Automatic cleanup or persistence options

---

## Comparison: Workspace vs TaskDelegator

| Feature | Workspace | TaskDelegator |
|---------|-----------|---------------|
| Purpose | Full collaboration environment | Simple task delegation |
| Artifact Sharing | ✅ Yes | ❌ No |
| Shared State | ✅ Yes | ❌ No |
| Message History | ✅ Complete history | ❌ No |
| Direct Messaging | ✅ Yes | ❌ No |
| Persistence | ✅ Optional | ❌ No |
| Lifecycle Control | ✅ Full control | ❌ Limited |
| Use Case | Complex, multi-step projects | Simple task routing |

**Recommendation**: 
- Use **Workspace** for complex, collaborative projects
- Use **TaskDelegator** for simple task routing

---

## Migration Guide

If you're currently using TaskDelegator, here's how to migrate to Workspace:

### Before (TaskDelegator)

```python
delegator = synqed.TaskDelegator()
delegator.register_agent(agent1)
delegator.register_agent(agent2)

result = await delegator.submit_task("Task description")
```

### After (Workspace)

```python
workspace = synqed.Workspace(name="Project")
workspace.add_agent(agent1)
workspace.add_agent(agent2)

await workspace.start()
results = await workspace.collaborate("Task description")
await workspace.close()
```

**Note**: TaskDelegator is still fully supported and recommended for simple use cases!

---

## Future Enhancements

Planned features for future releases:

- [ ] Real-time workspace UI dashboard
- [ ] Workspace templates for common patterns
- [ ] Advanced access control and permissions
- [ ] Workspace forking and branching
- [ ] Integration with version control systems
- [ ] Multi-workspace coordination
- [ ] Advanced analytics and monitoring
- [ ] Workspace marketplace for sharing

---

## Feedback & Contributions

We'd love to hear from you!

- **Issues**: https://github.com/SynqLabs/synqed/issues
- **Discussions**: https://github.com/SynqLabs/synqed/discussions
- **Contributing**: See CONTRIBUTING.md

---

## Thank You

Thank you for using Synqed! We're excited to see what you'll build with Workspace.

---

## License

Copyright © 2025 Synq Team. All rights reserved.

