Added new section in ai-chat-api-design.md explaining:
- LangGraph Agent architecture and main components
- tool_node function and tool output serialization mechanism
- Why serialization happens in tool_node (not agent_service)
- Tool output data flow diagram showing SSE and history paths
- Explanation of JSON format consistency across streaming and storage
This documentation clarifies the fix for single-quotes issue in
conversation history and helps future maintenance.
Co-Authored-By: YueGuobin <yueguobin@outlook.com>
Changed tool output serialization in AgentService._convert_event_to_chunk()
from str() to json.dumps() to ensure structured data (dict/list) is properly
formatted as standard JSON instead of Python string representation.
Changes:
- Added json import to agent_service.py
- Modified on_tool_end event handling to use json.dumps(output, ensure_ascii=False, indent=2)
- Updated ai-chat-api-design.md to document tool_output format
Benefits:
- Frontend can parse tool results with standard JSON.parse()
- Chinese and non-ASCII characters are preserved (not escaped)
- Formatted output (indent=2) improves readability
Co-Authored-By: YueGuobin <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
Translate the GNS3 Copilot Agent Chat API design document from Chinese to English to improve accessibility for international contributors and align with project documentation standards. The translation covers all sections including overview, core features, architecture design, API endpoints, and response formats.
Updated references to the title generation node in both documentation and code:
- Changed node name from `generate_title` to `title_generator_node` in API design documentation
- Updated filtering logic in agent service to exclude `title_generator_node` from LLM call statistics, token counting, and frontend streaming events
- Maintains same functionality while using more descriptive node name for clarity
- 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
- Update AI chat API documentation with revised SSE event schema
- Add support for multiple tool calls in `tool_call` events
- Include `session_id` in all event types for better session tracking
- Implement `on_chat_model_end` handler to process LLM tool call decisions
- Update example JSON payloads to reflect new schema structure
- 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)
- Move AI chat API design document to gns3-copilot directory
- Add comprehensive HITL implementation plan with architecture and workflow
- Introduce human-in-the-loop confirmation for dangerous configuration commands
- Include state management, API endpoints, and frontend integration details
- Provide testing plan and deployment steps for the new feature
