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skills/langgraph-master/03_memory_management_overview.md

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+# 03. Memory Management
+
+State management through persistence and checkpoint features.
+
+## Overview
+
+LangGraph's **built-in persistence layer** allows you to save and restore agent state. This enables conversation continuation, error recovery, and time travel.
+
+## Memory Types
+
+### Short-term Memory: [Checkpointer](03_memory_management_checkpointer.md)
+- Automatically saves state at each superstep
+- Thread-based conversation management
+- Time travel functionality
+
+### Long-term Memory: [Store](03_memory_management_store.md)
+- Share information across threads
+- Persist user information
+- Semantic search
+
+## Key Features
+
+### 1. [Persistence](03_memory_management_persistence.md)
+
+**Checkpoints**: Save state at each superstep
+- Snapshot state at each stage of graph execution
+- Recoverable from failures
+- Track execution history
+
+**Threads**: Unit of conversation
+- Identify conversations by `thread_id`
+- Each thread maintains independent state
+- Manage multiple conversations in parallel
+
+**StateSnapshot**: Representation of checkpoints
+- `values`: State at that point in time
+- `next`: Nodes to execute next
+- `config`: Checkpoint configuration
+- `metadata`: Metadata
+
+### 2. Human-in-the-Loop
+
+**State Inspection**: Check state at any point
+```python
+state = graph.get_state(config)
+print(state.values)
+```
+
+**Approval Flow**: Human approval before critical operations
+```python
+# Pause graph and wait for approval
+```
+
+### 3. Memory
+
+**Conversation Memory**: Memory within a thread
+```python
+# Conversation continues when called with the same thread_id
+config = {"configurable": {"thread_id": "conversation-1"}}
+graph.invoke(input, config)
+```
+
+**Long-term Memory**: Memory across threads
+```python
+# Save user information in Store
+store.put(("user", user_id), "preferences", user_prefs)
+```
+
+### 4. Time Travel
+
+Replay and fork past executions:
+```python
+# Resume from specific checkpoint
+history = graph.get_state_history(config)
+for state in history:
+    print(f"Checkpoint: {state.config['configurable']['checkpoint_id']}")
+
+# Re-execute from past checkpoint
+graph.invoke(input, past_checkpoint_config)
+```
+
+## Checkpointer Implementations
+
+LangGraph provides multiple checkpointer implementations:
+
+### InMemorySaver (For Experimentation)
+```python
+from langgraph.checkpoint.memory import MemorySaver
+
+checkpointer = MemorySaver()
+graph = builder.compile(checkpointer=checkpointer)
+```
+
+### SqliteSaver (For Local Development)
+```python
+from langgraph.checkpoint.sqlite import SqliteSaver
+
+checkpointer = SqliteSaver.from_conn_string("checkpoints.db")
+graph = builder.compile(checkpointer=checkpointer)
+```
+
+### PostgresSaver (For Production)
+```python
+from langgraph.checkpoint.postgres import PostgresSaver
+
+checkpointer = PostgresSaver.from_conn_string(
+    "postgresql://user:pass@localhost/db"
+)
+graph = builder.compile(checkpointer=checkpointer)
+```
+
+## Basic Usage Example
+
+```python
+from langgraph.checkpoint.memory import MemorySaver
+
+# Compile with checkpointer
+checkpointer = MemorySaver()
+graph = builder.compile(checkpointer=checkpointer)
+
+# Execute with thread_id
+config = {"configurable": {"thread_id": "user-123"}}
+
+# First execution
+result1 = graph.invoke({"messages": [("user", "Hello")]}, config)
+
+# Continue in same thread
+result2 = graph.invoke({"messages": [("user", "How are you?")]}, config)
+
+# Check state
+state = graph.get_state(config)
+print(state.values)  # All messages so far
+
+# Check history
+for state in graph.get_state_history(config):
+    print(f"Step: {state.values}")
+```
+
+## Key Principles
+
+1. **Thread ID Management**: Use unique thread_id for each conversation
+2. **Checkpointer Selection**: Choose appropriate implementation for your use case
+3. **State Minimization**: Save only necessary information to keep checkpoint size small
+4. **Cleanup**: Periodically delete old checkpoints
+
+## Next Steps
+
+For details on each feature, refer to the following pages:
+
+- [03_memory_management_persistence.md](03_memory_management_persistence.md) - Persistence details
+- [03_memory_management_checkpointer.md](03_memory_management_checkpointer.md) - Checkpointer implementation
+- [03_memory_management_store.md](03_memory_management_store.md) - Long-term memory management