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Description
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- Yes, it is related to a problem
Describe the feature you'd like
🌟 Feature Description
Implement an intelligent in-memory state management system using LangGraph's InMemorySaver that provides conversation continuity across user sessions with automatic summarization and cleanup. This system will enable the DevRel agent to remember user interactions, build relationships, and provide personalized assistance within Discord thread lifetimes (1-hour timeout).
The feature includes:
- Thread-based conversation memory using LangGraph checkpoints
- Enhanced AgentState schema with user profiling and conversation tracking
- State reducers to prevent data overwriting and ensure data integrity
- Automatic summarization workflow that chunks and indexes conversations after thread timeout
- Background cleanup management for expired threads
🔍 Problem Statement
Currently, the DevRel agent suffers from complete memory loss between interactions, creating significant user experience and DevRel effectiveness issues.
🎯 Expected Outcome
Transform the DevRel agent into an intelligent assistant with persistent memory that can:
Immediate Benefits:
- ✅ Conversation Continuity: Users can continue discussions across multiple interactions within thread lifetime
- ✅ Personalized Responses: Agent adapts based on user's previous questions and skill level
- ✅ Progress Tracking: Remember onboarding status, issues being worked on, and follow-up commitments
- ✅ Thread Persistence: Discord thread mappings survive bot restarts (within timeout window)
- ✅ Context-Aware Assistance: Provide relevant help based on conversation history
Enhanced User Experience:
👤 User: "I'm having trouble with that LangGraph issue we discussed."
🤖 Agent: "I remember! You were working on the state reducer for message handling.
Did the solution I suggested yesterday help with the data overwriting problem?"
vs Current:
🤖 Agent: "I'm not sure what issue you're referring to. Can you provide more details?"
Memory System Architecture:
┌─────────────────────────────────────────────────────────────┐
│ ThreadMemoryManager │
│ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────── │
│ │ Thread A │ │ Thread B │ │ Thread C │
│ │ User: alice │ │ User: bob │ │ User: carol │
│ │ Messages: 15 │ │ Messages: 8 │ │ Messages: 23 │
│ │ Context: {...} │ │ Context: {...} │ │ Context: {...}│
│ │ Timeout: 45min │ │ Timeout: 12min │ │ Timeout: 3min │
│ └─────────────────┘ └─────────────────┘ └────────────────│
└─────────────────────────────────────────────────────────────┘
│
▼ (On timeout)
┌─────────────────────────────────────────────────────────────┐
│ Summarization Workflow │
│ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────── │
│ │ Extract Topics │→ │ Create Summary │→ │ Generate │
│ │ & User Info │ │ Using Gemini │ │ Embeddings │
│ └─────────────────┘ └─────────────────┘ └────────────────│
└─────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ Vector DB Storage │
│ Collection: user_conversation_summaries │
│ ┌─────────────────────────────────────────────────────────┐│
│ │ { ││
│ │ "user_id": "alice", ││
│ │ "topics": ["langgraph", "state_management"], ││
│ │ "skill_level": "intermediate", ││
│ │ "summary": "User working on state reducers...", ││
│ │ "next_steps": ["review error handling"], ││
│ │ "preferences": {"communication": "detailed"} ││
│ │ } ││
│ └───────────────────────────────────────────────────────── │
└─────────────────────────────────────────────────────────────┘
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- I agree to follow this project's Code of Conduct
- I want to work on implementing this feature
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