Security Enhancement:
- API keys are now always filtered to null in all LLM config API responses
- Created LLMModelConfigDataWithoutSecret schema for response validation
- Added _filter_api_key_from_config() helper in API routes
- Modified repository to always hide api_key in get_user_effective_configs()
- Update/create operations still accept and store api_key securely
Documentation Updates:
- Updated API key visibility section to reflect new security policy
- Updated all response examples to show api_key as null
- Marked max_tokens field as reserved for future use
- Added "Reserved Fields" section explaining unused fields
This defense-in-depth approach prevents API keys from being leaked through
logs, browser devtools, or network monitoring.
Fix the path mismatch between /acl/endpoints API and actual routes:
- Users: /users/{id} → /access/users/{id}
- Groups: /groups/{id} → /access/groups/{id}
- Roles: /roles/{id} → /access/roles/{id}
This fixes the error where creating ACE entries fails with:
"Path '/groups/{id}' doesn't match any existing endpoint"
The actual routes are registered under /access/ prefix, but the
endpoints API was returning paths without the prefix.
Co-Authored-By: Yue Guobin <yueguobin@outlook.com>
- 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 `context_limit` as required field for LLM model configurations
- Add `context_strategy` as optional field with three trimming strategies
- Update API documentation with detailed examples for GPT-4o and Claude 3.5 Sonnet
- Clarify that context limit is specified in K tokens (thousands of tokens)
- Update example payloads to reflect current model versions and new fields
- Add `pinned` column to chat_sessions table with default FALSE
- Implement database migration for existing installations using PRAGMA table_info
- Create composite index for pinned + updated_at sorting
- Add pin/unpin API endpoints (PUT/DELETE /sessions/{id}/pin)
- Update session listing to sort by pinned status then updated_at
- Extend ChatSessionsRepository with pin_session method
- Update API documentation to reflect new pinning functionality
The feature allows users to pin important chat sessions to the top of the list. Sessions are sorted with pinned sessions first (by updated_at), followed by regular sessions (by updated_at). Database migration ensures backward compatibility with existing installations.
- Add info and debug logging to llm_call node for tracking LLM invocations and configuration
- Add error handling and logging to tool_node for tool execution failures
- Add startup logging to stream_chat method with session details
- Improve observability of agent workflow and debugging capabilities
Add project status validation to all chat API endpoints to ensure the project is opened before allowing chat operations. This prevents unauthorized access and ensures chat functionality only works with active projects.
- Check project.status == "opened" in stream_chat, list_sessions, get_history, and delete_session endpoints
- Return HTTP 403 FORBIDDEN with descriptive error message if project is not opened
- Update docstring for stream_chat endpoint to document the requirement
- Move JWT token from state to configurable context for better security and request isolation
- Add user_id parameter to agent service for enhanced metadata tracking
- Update checkpoint directory name from .gns3-copilot to gns3-copilot
- Implement context-aware JWT token management using ContextVar
- Improve tool node to extract JWT token from config instead of state
- 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.
- Change chat router prefix from `/chat` to `/projects/{project_id}/chat`
- Add `dep_project` dependency to inject Project instance into endpoints
- Remove manual project validation in `stream_chat` and use dependency instead
- Add placeholder `list_sessions` endpoint for future session listing
- Update `get_history` endpoint to use project dependency and adjust path
- Improve code organization and error handling for project retrieval
Add explicit Query parameter with description to the `list_sessions` endpoint for better API documentation and clarity. The `project_id` parameter now includes a descriptive label indicating it is a GNS3 project ID.
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.
- Modified `llm_call` and `generate_title` functions to accept `config` parameter, extracting `user_id` and `jwt_token` for per-user LLM configuration and API authentication
- Updated `create_base_model_with_tools` and `create_title_model` calls to pass user authentication details
- Added `jwt_token` to state for tool usage in GNS3 API calls
- Integrated chat router into controller API routes under `/chat` endpoint
- Implemented `_cleanup_copilot_agent` method in `Project` class to remove AgentService resources upon project closure, preventing resource leaks
- Enhanced error handling in agent cleanup to avoid interrupting project close operations
- Add note clarifying that GET endpoints for groups return the same structure as user endpoints
- Document LLMModelConfigListResponse schema with default configuration selection logic
- Add comprehensive example for GET group configurations endpoint
- Update endpoint numbering to accommodate new group endpoints
- Ensure consistency between user and group API documentation
- Add `/default` endpoints for users and groups to retrieve default LLM model configurations
- Update documentation to clarify that users receive both own and inherited configurations
- Improve response examples to show combined configs with source field
- Add 404 response example for missing default configurations
- Fix optimistic locking documentation formatting
- Add `model_type` field to database schema with supported values (text, vision, stt, tts, multimodal, embedding, reranking, other)
- Add `name` field as table-level column for indexing and filtering
- Add reserved JSONB fields for future extensibility
- Update API request/response schemas to include `model_type` and `name` fields
- Add new `LLMModelConfigWithSource` schema for detailed configuration responses
- Update usage examples to reflect new required fields
- Improve database constraints and indexing documentation
- Include `version` field in all LLM model config response schemas
- Add `expected_version` parameter to update endpoints for optimistic locking
- Handle concurrent modification errors with HTTP 409 Conflict status
- Update both user and group config endpoints consistently
- Introduce new API route `/access` for managing LLM model configurations
- Add LLMModelConfig model to database models
- Include comprehensive schemas for LLM model config CRUD operations
- Register new router with tags for LLM Model Configurations
- Use `default=str` in `json.dumps` to handle non-serializable objects
- Return proper HTTP 304 response with ETag header instead of raising exception
- Ensure consistent ETag generation for template caching
- Add optional `tags` query parameter to `/nodes` and `/templates` endpoints
- Support filtering by tags in format "key:value" with multiple tags ANDed together
- Example: `?tags=vendor:cisco&tags=model:7200` filters nodes/templates with both tags
- Maintain backward compatibility for existing API usage without tags parameter
