lintsinghua f05c0073e1 feat(agent): implement comprehensive agent architecture with knowledge base and persistence layer ... - Add database migrations for agent checkpoints and tree node tracking - Implement core agent execution framework with executor, state management, and message handling - Create knowledge base system with framework-specific modules (Django, FastAPI, Flask, Express, React, Supabase) - Add vulnerability knowledge modules covering authentication, cryptography, injection, XSS, XXE, SSRF, path traversal, deserialization, and race conditions - Introduce new agent tools: thinking tool, reporting tool, and agent-specific utilities - Implement LLM memory compression and prompt caching for improved performance - Add agent registry and persistence layer for checkpoint management - Refactor agent implementations (analysis, recon, verification, orchestrator) with enhanced capabilities - Remove legacy agent implementations (analysis_v2, react_agent) - Update API endpoints for agent task creation and project management - Add frontend components for agent task creation and enhanced audit UI - Consolidate agent service architecture with improved separation of concerns - This refactoring provides a scalable foundation for multi-agent collaboration with knowledge-driven decision making and state persistence		2025-12-12 15:27:12 +08:00
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ef6dc788-cc23-4a4d-b1a9-5ce4b32248b8	feat(agent): implement comprehensive agent architecture with knowledge base and persistence layer	2025-12-12 15:27:12 +08:00