Removed GNS3UpdateDrawingTool import and from __all__ list in gns3_client __init__.py to clean up the public interface and eliminate unused or deprecated components.
Update all references from FlowNet-Lab to GNS3-Copilot in package names, documentation, and logging. This includes:
- Module and package __init__.py files
- License headers and file descriptions
- Log messages and internal comments
- Remove deprecated tools: GNS3CreateAreaDrawingTool and LinuxTelnetBatchTool
The renaming aligns with the project's new branding while maintaining all existing functionality.
Refactor model factory to support three configuration sources in priority order:
1. Direct llm_config dictionary parameter
2. Fetch from llm_model_configs system via connector_factory (requires user_id and jwt_token)
3. Environment variables as fallback for backward compatibility
This improves flexibility by allowing runtime configuration while maintaining compatibility with existing environment-based setups.
Removed checkpoint-related imports and exports from the agent package's __init__.py to clean up the public API. This change reduces unnecessary exposure of internal checkpoint utility functions, focusing the public interface on the core agent_builder functionality.
- Add `get_gns3_server_host()` function to `connector_factory.py` for extracting GNS3 server hostname from controller, config, or default URL
- Export new function in `__init__.py` for public API access
- Replace `os.getenv("GNS3_SERVER_HOST", "127.0.0.1")` calls with `get_gns3_server_host()` in Nornir configuration tools (`config_tools_nornir.py`, `display_tools_nornir.py`)
- Ensures consistent host detection across tools using the same priority logic as `get_gns3_connector`
Removed GNS3_SERVER_USERNAME and GNS3_SERVER_PASSWORD environment variables from Nornir configuration tools. Credentials are now set to empty strings by default, simplifying configuration and removing dependency on environment variables for authentication.
- Rename module description from FlowNet-Lab to GNS3 Copilot
- Replace linux_specialist_prompt and experiment_deploy_prompt imports with base_prompt
- Update __all__ export list to include SYSTEM_PROMPT instead of removed prompts
- Improve module docstring with detailed component descriptions and available prompts
- Maintain dynamic version management and module metadata
- Remove direct logging of LLM config from gns3_copilot.py
- Update model_factory to accept configuration from llm_model_configs dictionary
- Add fallback to environment variables for backward compatibility
- Centralize configuration loading in _load_llm_config function
Introduce `get_gns3_connector_with_llm_config` as a convenience function that combines the creation of a GNS3 API connector and retrieval of the user's default LLM configuration. This simplifies initialization for operations requiring both GNS3 connectivity and AI model settings, reducing boilerplate code in callers. The function returns a dictionary containing the connector and LLM config, or None on failure.
Integrate the gns3-copilot AI assistant module to provide intelligent
automation and interaction capabilities for GNS3 network emulation.
Key components:
- AI agent framework with LLM integration (supports Qwen vision model)
- GNS3 client library for project topology management
- Extensive prompt templates for various network operation scenarios
- Tool library for node creation, linking, configuration, and management
- Support for English level assessment (A1-C2) and specialized personas
- Network drawing and topology visualization tools
- Linux device automation via Nornir/Telnetlib
- Window controller for UI interaction
Features:
- Multi-modal AI agent with vision capabilities
- Automated network topology deployment and configuration
- Interactive node and drawing management
- File-based project operations (read, write, list)
- Specialized prompts for different scenarios and skill levels
- Comprehensive tool set for network device management
