Qdrant
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Efficient Data Conversion: IKEA Products to CommerceTXT
Read Full Article: Efficient Data Conversion: IKEA Products to CommerceTXT![[Resource] 30k IKEA products converted to text files. Saves 24% tokens. RAG benchmark.](https://www.tweakedgeek.com/wp-content/uploads/2026/01/featured-article-9368-300x171.png)
Converting 30,511 IKEA products from JSON to a markdown-like format called CommerceTXT significantly reduces token usage by 24%, allowing more efficient use of memory for applications like Llama-3. This new format enables over 20% more products to fit within a context window, making it highly efficient for data retrieval and testing, especially in scenarios where context is limited. The structured format organizes data into folders by categories without the clutter of HTML or scripts, making it ready for use with tools like Chroma or Qdrant. This approach highlights the potential benefits of simpler data formats for improving retrieval accuracy and overall efficiency. This matters because optimizing data formats can enhance the performance and efficiency of machine learning models, particularly in resource-constrained environments.
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Build a Local Agentic RAG System Tutorial
Read Full Article: Build a Local Agentic RAG System Tutorial
The tutorial provides a comprehensive guide on building a fully local Agentic RAG system, eliminating the need for APIs, cloud services, or hidden costs. It covers the entire pipeline, including often overlooked aspects such as PDF to Markdown ingestion, hierarchical chunking, hybrid retrieval, and the use of Qdrant for vector storage. Additional features include query rewriting with human-in-the-loop, context summarization, and multi-agent map-reduce with LangGraph, all demonstrated through a simple Gradio user interface. This resource is particularly valuable for those who prefer hands-on learning to understand Agentic RAG systems beyond theoretical knowledge.