conversation▌

Interactive QA session where users report bugs conversationally, and the agent files GitHub issues while exploring the codebase for context.

Persistent memory systems for LLM conversations with tiered storage and intelligent retrieval. \n \n Implements three memory types: short-term (immediate context), long-term (historical facts), and entity-based (facts about specific entities) \n Provides memory retrieval and consolidation capabilities to surface relevant memories without overwhelming context windows \n Addresses critical concerns including unbounded memory growth, retrieval relevance, and strict user isolation to prevent cross-u

Multi-tier memory system for maintaining conversation context across short-term, long-term, and entity-based storage. \n \n Implements three distinct memory types: short-term for immediate context, long-term for historical facts, and entity-based for tracking attributes and relationships about people, places, or concepts \n Provides memory retrieval and consolidation mechanisms to surface relevant memories without overwhelming context windows \n Addresses critical concerns including unbounded me