opencode
f847b92b0a
- run() crea e traccia task nel planner - run_plan() esegue sequenze di goal con progresso - decompose_goal() scompone goal complessi via LLM - Task tracciati con stato: pending->in_progress->completed/failed
Enhancements for LangCode Agent based on LangChain Deep Agents analysis
This directory contains planned enhancements to bring LangCode Agent closer to the architecture patterns revealed in LangChain's Deep Agents framework.
Planned Enhancements
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Enhanced Memory Systems
- Add VectorStoreRetrieverMemory for semantic recall
- Implement SummaryBufferMemory for conversation summarization
- Add persistent memory storage for cross-session learning
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Advanced Planning & Reasoning
- Implement plan-and-execute agent pattern
- Add self-reflection capabilities
- Improve task decomposition and tracking
-
Production Observability
- Add LangChain-style callbacks for tracing
- Implement tool usage monitoring
- Add performance metrics collection
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Advanced Tool Composition
- Implement tool chaining capabilities
- Add async tool execution for parallelism
- Enhance input validation and error handling
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Agent Hierarchies
- Develop specialist subagents for specific domains
- Implement agent routing based on task analysis
- Add agent-to-agent communication patterns
Implementation Approach
Each enhancement will be implemented as a separate module that can be optionally integrated into the main agent, maintaining backward compatibility while extending capabilities.
The enhancements will follow the same patterns already established in the codebase:
- Modular design
- Configuration-driven behavior
- Clear separation of concerns
- Comprehensive error handling