- Rename "teaching" mode to "teaching_assistant" for better clarity
- Rename "lab_assistant" mode to "lab_automation_assistant" to reflect expanded capabilities
- Implement mode-specific tool sets: teaching_assistant gets read-only diagnostic tools only, while lab_automation_assistant gets full diagnostic and configuration tools
- Update API documentation examples to reflect new mode names
- Maintain backward compatibility with default tool set initialization
- 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 `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.
- 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
- 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
Update API documentation to reflect new nested `config` object structure in LLM model configurations endpoints. The response format now encapsulates provider-specific fields (provider, base_url, model, temperature, api_key, max_tokens) within a `config` object, while moving ownership metadata (user_id, group_id, is_default, version, created_at, updated_at) to the top level. This aligns the user-facing endpoints with the group configuration structure and improves API consistency.
- 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 `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
- 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
Add three new optional fields to the template schema:
- vendor: Device vendor (e.g., Cisco, Juniper, Huawei)
- model: Device model (e.g., ISR4451-X, MX204, NE40E)
- netmiko_device_type: Netmiko device type for automation (e.g., cisco_ios, juniper_junos, huawei)
These fields enable AI/LLM integration to determine the appropriate
Netmiko device type when automating network device configuration.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
