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# 05. Advanced Features
Advanced features and implementation patterns.
## Overview
By leveraging LangGraph's advanced features, you can build more sophisticated agent systems.
## Key Features
### 1. [Human-in-the-Loop (Approval Flow)](05_advanced_features_human_in_the_loop.md)
Pause graph execution and request human intervention:
- Dynamic interrupt
- Static interrupt
- Approval, editing, and rejection flows
### 2. [Streaming](05_advanced_features_streaming.md)
Monitor progress in real-time:
- LLM token streaming
- State update streaming
- Custom event streaming
### 3. [Map-Reduce (Parallel Processing Pattern)](05_advanced_features_map_reduce.md)
Parallel processing of large datasets:
- Dynamic worker generation with Send API
- Result aggregation with Reducers
- Hierarchical parallel processing
## Feature Comparison
| Feature | Use Case | Implementation Complexity |
|---------|----------|--------------------------|
| Human-in-the-Loop | Approval flows, quality control | Medium |
| Streaming | Real-time monitoring, UX improvement | Low |
| Map-Reduce | Large-scale data processing | High |
## Combination Patterns
### Human-in-the-Loop + Streaming
```python
# Stream while requesting approval
for chunk in graph.stream(input, config, stream_mode="values"):
print(chunk)
# Pause at interrupt
if chunk.get("__interrupt__"):
approval = input("Approve? (y/n): ")
graph.invoke(None, config, resume=approval == "y")
```
### Map-Reduce + Streaming
```python
# Stream progress of parallel processing
for chunk in graph.stream(
{"items": large_dataset},
stream_mode="updates",
subgraphs=True # Also show worker progress
):
print(f"Progress: {chunk}")
```
## Next Steps
For details on each feature, refer to the following pages:
- [05_advanced_features_human_in_the_loop.md](05_advanced_features_human_in_the_loop.md) - Implementation of approval flows
- [05_advanced_features_streaming.md](05_advanced_features_streaming.md) - How to use streaming
- [05_advanced_features_map_reduce.md](05_advanced_features_map_reduce.md) - Map-Reduce pattern