deepagents-architecturelisted

# Deep Agents Architecture Decisions ## When to Use Deep Agents ### Use Deep Agents When You Need: - **Long-horizon tasks** - Complex workflows spanning dozens of tool calls - **Planning capabilities** - Task decomposition before execution - **Filesystem operations** - Reading, writing, and editing files - **Subagent delegation** - Isolated task execution with separate context windows - **Persistent memory** - Long-term storage across conversations - **Human-in-the-loop** - Approval gates for sensitive operations - **Context management** - Auto-summarization for long conversations ### Consider Alternatives When: | Scenario | Alternative | Why | |----------|-------------|-----| | Single LLM call | Direct API call | Deep Agents overhead not justified | | Simple RAG pipeline | LangChain LCEL | Simpler abstraction | | Custom graph control flow | LangGraph directly | More flexibility | | No file operations needed | `create_react_agent` | Lighter weight | | Stateless tool use | Function calling | No middleware needed | ## Backend Selection ### Backend Comparison | Backend | Persistence | Use Case | Requires | |---------|-------------|----------|----------| | `StateBackend` | Ephemeral (per-thread) | Working files, temp data | Nothing (default) | | `FilesystemBackend` | Disk | Local development, real files | `root_dir` path | | `StoreBackend` | Cross-thread | User preferences, knowledge bases | LangGraph `store` | | `CompositeBackend` | Mixed | Hybrid memory patterns | Multi