Update the import statement for Nornir from `nornir.core.nornir` to `nornir.core` to align with the latest Nornir library structure and avoid potential import errors. This ensures compatibility with updated Nornir versions.
Optimize GNS3StartNodeTool with device-type-aware wait time calculation
to significantly reduce startup time for fast devices (VPCS, IOU).
Changes:
- Add NODE_STARTUP_TIME configuration
* VPCS: 15s base + 2s per additional node
* IOU: 25s base + 3s per additional node
* Other devices: 120s base + 10s per additional node (conservative)
- Add calculate_startup_time() function
* Detects device types via node.node_type
* Uses fast startup time if all nodes are VPCS/IOU
* Uses conservative time if any slow device present
* Logs selected strategy and detected types
- Optimize GNS3StartNodeTool._run() method
* Retrieve node info (including node_type) before starting
* Calculate wait time based on detected device types
* Send start commands after info retrieval
* Use calculated wait time for progress bar
* Reuse collected node objects for status retrieval
Performance improvements:
- 1 VPCS node: 140s → 15s (89% faster)
- 5 VPCS nodes: 180s → 23s (87% faster)
- 1 IOU node: 140s → 25s (82% faster)
- 5 IOU nodes: 180s → 37s (79% faster)
- Mixed VPCS/IOU: 180s → 33s (82% faster)
Documentation:
- Update node-control-tools.md with dynamic wait time strategy
- Add device type comparison table
- Document performance improvements
- Update changelog
Code quality:
- All comments in English
- flake8 check passed
- mypy check passed
Optimize GNS3StartNodeTool with device-type-aware wait time calculation
to significantly reduce startup time for fast devices (VPCS, IOU).
Changes:
- Add NODE_STARTUP_TIME configuration
* VPCS: 10s base + 2s per additional node
* IOU: 20s base + 3s per additional node
* Other devices: 120s base + 10s per additional node (conservative)
- Add calculate_startup_time() function
* Detects device types via node.node_type
* Uses fast startup time if all nodes are VPCS/IOU
* Uses conservative time if any slow device present
* Logs selected strategy and detected types
- Optimize GNS3StartNodeTool._run() method
* Retrieve node info (including node_type) before starting
* Calculate wait time based on detected device types
* Send start commands after info retrieval
* Use calculated wait time for progress bar
* Reuse collected node objects for status retrieval
Performance improvements:
- 1 VPCS node: 140s → 10s (93% faster)
- 5 VPCS nodes: 180s → 18s (90% faster)
- 1 IOU node: 140s → 20s (86% faster)
- 5 IOU nodes: 180s → 32s (82% faster)
- Mixed VPCS/IOU: 180s → 28s (84% faster)
Documentation:
- Update node-control-tools.md with dynamic wait time strategy
- Add device type comparison table
- Document performance improvements
- Update changelog
Code quality:
- All comments in English
- flake8 check passed
- mypy check passed
Add warnings about 'exit' command in three locations to prevent AI from
disconnecting Telnet/SSH sessions during command execution:
- Prompt system rules (lab_automation_assistant_prompt.py)
- Display tool description (display_tools_nornir.py)
- Config tool description (config_tools_nornir.py)
The 'exit' command disconnects the session and causes all subsequent
commands in the batch to fail. This prevents users from viewing
command outputs properly.
- Rename huawei_telnet_ce to gns3_huawei_telnet_ce for consistent naming
- Add comprehensive test suite for RuijieTelnetEnhanced driver (10 tests)
- Update list_netmiko_telnet_devices.py to include gns3_ruijie_telnet
- Fix all flake8 format issues (line length, unused imports, variables)
- Update documentation to reflect device type rename
- Import and register Ruijie telnet device type in config_tools_nornir.py
- Import and register Ruijie telnet device type in display_tools_nornir.py
- Update custom_netmiko __init__.py to include RuijieTelnetEnhanced driver
- Add Ruijie telnet driver to __all__ exports for proper module exposure
- Extends custom Netmiko support to handle Ruijie devices with interactive prompt handling
- Add explicit AAA/password configuration prohibition to safety reminders
- Implement multiline command expansion for banner and similar commands
- Add error handling for devices with missing device_type tags
- Improve logging for configuration errors and multiline expansions
practice for multi-vendor device support
Refactor Nornir configuration to use host-level connection_options
instead of dynamic groups, following Nornir's configuration priority
model (host > group > defaults).
**Problem:**
Previous implementation used first device's configuration for all
devices, causing Cisco devices to use Huawei driver and vice versa.
**Solution:**
- Each host now has device-specific connection_options at host level
- Single generic "network_devices" group for shared settings
- Host-level config automatically overrides group-level config
**Changes:**
- Remove: _get_nornir_groups_config() helper function
- Remove: _get_nornir_group() helper function
- Simplify: _initialize_nornir() to use single generic group
- Update: get_gns3_device_port.py() to return host-level config
- Reserve: platform field for future NAPALM/scrapli plugin support
**Benefits:**
- Cleaner code structure (no dynamic group creation)
- Follows Nornir best practice ("configuration proximity")
- Easy to extend with new device types
- Properly handles mixed-vendor topologies
Netmiko's `ssh_dispatcher` calculates platform lists at module import
time. When custom device types (like Huawei CE) are registered
dynamically, these cached lists become stale and do not include the
new platforms.
This change imports `netmiko.ssh_dispatcher` and recalculates the
`platforms`, `platforms_base`, and `telnet_platforms` attributes to
ensure Netmiko recognizes the custom device types.
Add comprehensive multi-vendor support for GNS3 network automation,
including a custom Netmiko driver for Huawei CloudEngine devices.
Features:
- Custom HuaweiTelnetCE driver for GNS3 emulation (no authentication)
- Auto-commit before exit to prevent [Y/N/C] prompts
- Dynamic device type detection from GNS3 node tags
- Support for both Cisco IOS and Huawei devices
- Proper VRP command handling (system-view, return confirmation)
Implementation:
- New package: utils/custom_netmiko/
- huawei_ce.py: Huawei CloudEngine driver
- tests/test_huawei_ce.py: Unit tests (9/9 passing)
- README.md: Driver development guide
- Updated tools for multi-vendor support:
- display_tools_nornir.py: Dynamic group generation
- config_tools_nornir.py: Multi-vendor config commands
- get_gns3_device_port.py: Device port extraction
- Documentation: multi-vendor-device-support.md
Limitations:
- huawei_telnet_ce driver requires devices without authentication
- For devices with username/password, use standard huawei_telnet driver
Co-Authored-By: Yue Guobin <yueguobin@outlook.com>"
- Add GNS3StopNodeTool and GNS3SuspendNodeTool to lab automation assistant mode
- Update tools_v2 __init__.py to export new node control tools
- Document node control tools in README with key features and implementation status
- Update last modified date in documentation
The new tools provide complete node lifecycle control for automated lab workflows, including stopping nodes for shutdown and suspending nodes while preserving state.
Updated the author name and copyright statements across the
gns3_copilot module. The name has been standardized from
"Guobin Yue" to "Yue Guobin (岳国宾)" to reflect the correct
author attribution including Chinese characters.
- Import filter_forbidden_commands utility from command_filter module
- Add _filter_forbidden_commands_from_device_configs method to filter out restricted commands before execution
- Store blocked commands information and log filtered commands for audit purposes
- Update _process_task_results to include blocked commands info in response
- Prevent execution of potentially dangerous commands while maintaining transparency about filtered content
- Update API documentation to reflect new streaming tool call mechanism
- Add `message_id` optional field to content and tool_call events
- Change tool_call structure from array to single object with incremental updates
- Add `tool_call_id` to tool_start events for better event correlation
- Implement ToolCallStreamAccumulator class to handle parameter accumulation
- Provide frontend example code for handling streaming tool calls
- Maintain backward compatibility with existing session_id tracking
Set logging level for nornir.core and nornir loggers to WARNING in config_tools_nornir.py and display_tools_nornir.py. This prevents nornir from logging task execution at INFO level to the console, as the logging={"enabled": False} parameter in InitNornir only disables plugin internal logs.
- Added `temperature` parameter to Chat API documentation with implementation notes
- Improved code formatting in context_manager.py with consistent string quotes and line breaks
- Added section on future runtime LLM parameter override capabilities
- Updated API schemas to include temperature parameter (currently unused but reserved for future implementation)
- Add `copilot_mode` field to LLM model configs API with "teaching" (diagnostics only) and "lab_assistant" (full configuration access) modes
- Introduce new `ExecuteMultipleDeviceConfigCommands` tool for executing configuration commands on multiple devices
- Include `tags` field in node data structure for enhanced project management
- Update API documentation examples to reflect new `copilot_mode` field and context limit additions
Add copyright notice and author attribution to multiple Python files in the gns3-copilot module. This ensures proper licensing attribution and clarifies authorship for the project files.
Removed repetitive "This module is part of the GNS3-Copilot project" and GitHub URL comments from multiple module docstrings. These comments were redundant since the project information is already established in the main package documentation. This cleanup improves code readability and reduces maintenance overhead by eliminating duplicate attribution statements across the codebase.
- Refactor system message structure to combine system prompt and topology info using template variables
- Update token calculation process with merged system message approach
- Clarify priority order for message retention during context window management
- Add detailed token counting implementation using tiktoken library
- Include boundary case handling for system message exceeding budget
- Add SPDX license headers to tool files for proper licensing documentation
Enhanced the context window management system to properly account for tool definition tokens when trimming messages. The key changes include:
- Updated `trim_messages_for_context` function to accept `tool_tokens` parameter
- Modified token budget allocation logic to subtract tool tokens before message trimming
- Added detailed documentation explaining the token budget distribution between messages and tool definitions
- Implemented prioritized trimming strategy that preserves system messages and recent conversation history
- Added boundary case handling for scenarios where system messages or tools exceed available budget
The improvements ensure more accurate context window management by accounting for the ~1000-2000 tokens typically consumed by tool definitions that LangChain automatically includes in LLM requests.
Updated import statements across multiple agent files to use absolute paths starting with `gns3server.agent.gns3_copilot` instead of relative `gns3_copilot` imports. This ensures proper module resolution within the gns3-server package structure and prevents import errors when the agent is executed from different contexts.
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.
- 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.
- 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
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
