This is the third episode of the "Agentic Patterns from Scratch" series. In this video, you'll learn about the Planning Pattern and the ReAct technique for increasing the reasoning capabilities of LLMs. As always, we won't rely on any popular frameworks like LangChain, LlamaIndex or CrewAI: pure Python and Groq's LLMs (llama 3.1 70B π)
π€ Code π https://github.com/neural-maze/agentic_patterns
π€ Deeplearning.ai article π https://www.deeplearning.ai/the-batch/agentic-design-patterns-part-4-planning/
π€ Groq π https://groq.com/
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0:00 Introduction
0:58 ReAct loop explained
2:18 Introducing the Notebook
4:23 ReAct System Prompt
9:13 Example Step by Step
19:23 Moving to VSCode
20:22 ReactAgent Class Implementation
26:07 Running the Agent
28:35 Conclusion
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