Multi-step Reasoning In Agentic RAG Systems | Multi-step reasoning #3
Welcome back to the third installment of our Agentic RAG series! In this video, we're diving deep into the limitations of single-shot prompting and how we can overcome them with multi-step reasoning in our Agentic RAG architecture. If you’ve been following along, you know that up until now, our focus has been on single-shot prompting, where tasks are completed in a single loop. While this approach works for simpler tasks, it falls short when dealing with complex problems that require multiple steps to solve.
Github Repo: https://github.com/Princekrampah/agen...
Medium Article: / agentic-rag-with-llama-index-multi-step-re...
In this episode, we’ll explore how to implement a multi-step reasoning loop, demonstrating the power and efficiency of agents in handling intricate, multi-step tasks. We’ll break down the process step-by-step, showing you how agents can work with LLMs and Agentic RAG applications to achieve precise and effective outcomes. This is a crucial development for anyone looking to push the boundaries of what’s possible with AI and agentic systems.
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Tags:
#AgenticRAG #MultiStepReasoning #AI #ArtificialIntelligence #MachineLearning #LLM #DeepLearning #AIAgents #TechTutorial #AIResearch #AdvancedAI #ComplexTasks #TechInnovation
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