Add error_handler utility to detect and format HTML error responses
from misconfigured API base URLs. When the API returns HTML (indicating
configuration issues), users now see a helpful message instead of raw
HTML content.
Refactored test assertions for Huawei CE, Ruijie, and VPCS telnet drivers to compare only class names instead of full module paths. This change reduces test brittleness when classes are imported via different module paths while maintaining validation of correct class registration in CLASS_MAPPER and CLASS_MAPPER_BASE.
Refactor test assertions to compare classes by module and name instead of direct object comparison. This ensures tests remain reliable when classes are imported via different paths, preventing false failures due to import variations. Changes applied to Huawei CE, Ruijie, and VPCS telnet driver tests.
Changed test assertions from `assertIs` to `assertEqual` for class mapper comparisons in Huawei CE, Ruijie, and VPCS telnet driver tests. This ensures proper equality checking rather than identity checking, which is more appropriate for class comparisons in these test cases.
assertIs instead of assertEqual for class comparison
Fix test failures in custom Netmiko driver tests by using assertIs instead
of assertEqual when comparing class objects registered in CLASS_MAPPER.
The issue occurred because test files add project root to sys.path, allowing
the same module to be imported with different paths (e.g., gns3_copilot...
vs gns3server.agent.gns3_copilot...). assertEqual compares class __module__
attributes which differ based on import path, while assertIs checks object
identity which correctly identifies them as the same class.
Modified files:
- test_huawei_ce.py
- test_ruijie_telnet.py
- test_vpcs_telnet.py
- Configure tiktoken cache directory to isolate encoding files
- Add logging and timing for tiktoken initialization process
- Make Huawei CE and Ruijie Telnet device registration idempotent
- Add duplicate registration prevention with global flags
- Add logging for device type registration status
- Update .gitignore to exclude tiktoken cache files
- 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
Add pre-processing of known interactive commands and implement hybrid send strategy for Ruijie Telnet devices. The new approach:
- Pre-processes configuration commands to automatically insert 'yes' responses after known interactive commands (router-id, erase, delete, format, reload, boot system)
- Implements hybrid strategy: first attempts fast batch send with pre-processed commands, then falls back to one-by-one send with real-time prompt detection if batch fails
- Maintains backward compatibility while improving reliability for interactive configuration scenarios
This improves configuration reliability for Ruijie devices that frequently require confirmation prompts during configuration changes.
- 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
- Add script to generate Markdown documentation of all Netmiko supported
devices (SSH and Telnet), grouped by platform with source attribution
- Highlight custom GNS3-Copilot devices with "Custom ✨" marker
- Auto-generate device list to docs/gns3-copilot/netmiko_devices.md
- Simplify HuaweiTelnetCE driver: remove redundant aliases
(huawei_ce, huawei_telnet_ce_telnet), keep only huawei_telnet_ce
- Update tests to match simplified device registration
Disable mypy type checking for the Huawei CE driver module due to
Netmiko library limitations. Netmiko lacks type stubs (py.typed) and
uses dynamic attributes, which causes unresolved import and attribute
errors in static analysis.
Added a comprehensive comment block at the top of the file explaining
the rationale for disabling mypy to prevent future confusion.
Additionally, performed code cleanup including:
- Reformatted module docstrings and comments for better readability
- Added missing imports (importlib, logging)
- Removed unused typing imports (Optional)
- Refactored variable assignments in send_config_set for clarity
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>"
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.
- Improve POST /chat endpoint documentation with request/response examples
- Add session ID management flow explanation
- Enhance GET /sessions endpoint with query parameters and response example
- Update GET /sessions/{session_id}/history with detailed response structure
- Format parameters as tables for better readability
- Clarify session ID usage in streaming conversations
- 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
- 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
Add `normalize_tool_response` function to standardize tool output formats for consistent frontend display. The function converts various response types (dict, list, string) into a unified structure with success metrics, detailed data arrays, and metadata. This ensures backward compatibility while providing predictable response formats for UI components.
- Add message ID generation for initial HumanMessage creation
- Implement message converters for LangChain/OpenAI format interoperability
- Update documentation with detailed message format specifications
- Refactor AgentService to use centralized message conversion utilities
- Ensure tool_calls format compliance with OpenAI API standards
- Replace separate user_id and jwt_token parameters with unified llm_config dict
- Simplify model factory to accept llm_config directly instead of fetching from API
- Update llm_call and generate_title nodes to extract llm_config from LangGraph config
- Remove deprecated API fetching logic from model factory
- Maintain backward compatibility for existing tool usage patterns
This change centralizes LLM configuration management, reducing API calls and improving performance by passing configuration directly from the API layer rather than fetching it repeatedly.
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.
- 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
