Tags: llamaindex* + rag*

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  1. An AI-powered document search agent that explores files like a human would — scanning, reasoning, and following cross-references. Unlike traditional RAG systems that rely on pre-computed embeddings, this agent dynamically navigates documents to find answers.
  2. This article details how to build a 100% local MCP (Model Context Protocol) client using LlamaIndex, Ollama, and LightningAI. It provides a code walkthrough and explanation of the process, including setting up an SQLite MCP server and a locally served LLM.
  3. The article explores whether combining a command-line agent (like Claude Code or Gemini CLI) with Unix-like file system tools and SemTools is sufficient for complex tasks, particularly document search. It details a benchmark testing the limits of coding agents with and without SemTools, focusing on search, cross-referencing, and temporal analysis. The conclusion is that CLI access is powerful and SemTools enhances agent capabilities for document search and RAG.
  4. An exploration of Retrieval-Augmented Generation (RAG) using Langchain and LlamaIndex, explaining how these tools can enhance Large Language Models (LLMs) by combining retrieval and generation techniques.
    2025-01-04 Tags: , , , by klotz
  5. Jupyter notebook for using LlamaIndex with arXiv papers for retrieval-augmented generation (RAG).
    2024-12-26 Tags: , , , , by klotz
  6. This article guides you through the process of building a local RAG (Retrieval-Augmented Generation) system using Llama 3, Ollama for model management, and LlamaIndex as the RAG framework. The tutorial demonstrates how to get a basic local RAG system up and running with just a few lines of code.
    2024-06-21 Tags: , , , , , by klotz
  7. A CLI tool for interacting with local or remote LLMs to retrieve information about files, execute queries, and perform other tasks in a Retrieval-Augmented Generation (RAG) fashion.
    2024-06-21 Tags: , , , by klotz
  8. LlamaIndex comes with a built-in indexing feature, which allows developers to index large datasets efficiently. This makes it easier to search and retrieve information from these datasets, ultimately improving the overall performance of LLM-based applications.
    2024-06-18 Tags: , , by klotz
  9. A step-by-step guide on deploying LlamaIndex RAGs to AWS ECS fargate
    2024-01-15 Tags: , , , , by klotz
  10. A deep dive into model quantization with GGUF and llama.cpp and model evaluation with LlamaIndex

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