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@@ -484,6 +484,15 @@ The following notebooks implement agent architectures prototypical of the "plan-
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- [LLMCompiler](https://github.com/langchain-ai/langgraph/blob/main/examples/llm-compiler/LLMCompiler.ipynb): planner generates a **DAG** of tasks with variable responses. Tasks are **streamed** and executed eagerly to minimize tool execution runtime. Based on the [paper](https://arxiv.org/abs/2312.04511) by Kim, et. al.
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### Reflection / Self-Critique
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When output quality is a major concern, it's common to incorporate some combination of self-critique or reflection and external validation to refine your system's outputs. The following examples demonstrate research that implement this type of design.
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- [Reflexion](./examples/reflexion/reflexion.ipynb): critique missing and superflous aspects of the agent's response to guide subsequent steps. Based on [Reflexion](https://arxiv.org/abs/2303.11366), by Shinn, et. al.
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### Multi-agent Examples
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- [Multi-agent collaboration](https://github.com/langchain-ai/langgraph/blob/main/examples/multi_agent/multi-agent-collaboration.ipynb): how to create two agents that work together to accomplish a task
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