- Add role-based configuration to AgentConfig with 15 predefined roles
- Enhanced message types for role-based collaboration
- Role-based topic subscription system
- Agent initialization with automatic role assignment
- Role announcements and collaboration settings
- Support for expertise areas, reporting hierarchy, and deliverables
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Fixed module path from github.com/deepblackcloud/bzzz to github.com/anthonyrawlins/bzzz
- Added dynamic Ollama model detection via /api/tags endpoint
- Implemented intelligent model selection through N8N webhook integration
- Added BZZZ_MODEL_SELECTION_WEBHOOK environment variable support
- Fixed GitHub assignee issue by using valid username instead of peer ID
- Added comprehensive model fallback mechanisms
- Updated all import statements across the codebase
- Removed duplicate systemd service file
- Added sandbox execution environment and type definitions
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add availability broadcasting every 30s showing real working status
- Replace constant capability broadcasts with change-based system
- Implement persistent capability storage in ~/.config/bzzz/
- Add SimpleTaskTracker for real task status monitoring
- Only broadcast capabilities on startup or when models/capabilities change
- Add proper Hive API URL configuration and integration
- Fix capability change detection with proper comparison logic
This eliminates P2P mesh spam and provides accurate node availability.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
This commit completes Phase 2 of the Ollama integration. The bzzz-agent is now capable of participating in collaborative discussions.
Key changes:
- The pubsub module has been refactored to use a generic message handler, decoupling it from the github integration logic.
- The github integration module now maintains a history of active conversations for each task.
- When a peer sends a message on the meta-discussion channel, the agent will:
1. Append the message to the conversation history.
2. Construct a new prompt containing the full context (original task + conversation history).
3. Use the 'reasoning' module to generate a context-aware response.
4. Publish the response back to the discussion channel.
- The main application has been updated to wire up the new handlers.
The agent can now intelligently discuss and refine plans with its peers before and during task execution.
- Add Conversation struct to track task discussion history
- Implement handleMetaDiscussion for dynamic peer collaboration
- Enhanced GitHub integration with active discussion management
- Add SetAntennaeMessageHandler for pluggable message handling
- Simplify pubsub message types to generic MetaDiscussion
- Enable real-time collaborative reasoning between AI agents
- Integrate conversation context into Ollama response generation
- Support distributed decision making across P2P network
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
