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klotz: rag* + search*

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1. Using query intent to boost retrieval results

   This article discusses the importance of determining user query intent to enhance search results. It covers how to identify search and answer intents, implement intent detection using language models, and adjust retrieval strategies accordingly.

   2024-10-13 Tags: query intent, llm, search, rag by klotz
2. Rerank API Documentation

   This page provides documentation for the rerank API, including endpoints, request parameters, and response formats.

   2024-09-28 Tags: api, jina, reranker, llm, rag, jina ai, search, relevance, l3 by klotz
3. Jina AI Reranker

   Maximize search relevancy and RAG accuracy with Jina Reranker. Features include multilingual retrieval, code search, and a 6x speedup over the previous version.

   2024-09-28 Tags: reranker, jina ai, search, relevance, rag, l3 by klotz
4. Improving PDF Parsing and Search with Chunking

   A post discussing new techniques developed for parsing and searching PDFs, focusing on turning them into a hierarchical structure for RAG search. The approach involves dynamically generating chunks for searches, sending headers and sub-headers to the Language Model along with relevant chunks.

   2024-06-27 Tags: pdf, parsing, search, rag, llm, reddit by klotz
5. How to Build a Generative Search Engine for Your Local Files Using Llama

   This article provides a step-by-step guide on building a generative search engine for local files using Qdrant, NVidia NIM API, or Llama 3. It includes system design, indexing local files, and creating a user interface.

   2024-06-08 Tags: generative search engine, llama 3, qdrant, search, rag, llm python by klotz
6. Vespa and LLMs

   This article discusses the integration of Large Language Models (LLMs) into Vespa, a full-featured search engine and vector database. It explores the benefits of using LLMs for Retrieval-augmented Generation (RAG), demonstrating how Vespa can efficiently retrieve the most relevant data and enrich responses with up-to-date information.

   2024-06-03 Tags: vespa, search, information retrieval, llm, retrieval-augmented generation by klotz
7. Paper page - Context Tuning for Retrieval Augmented Generation

   2023-12-13 Tags: llm, rag, context, metadata, search, arxiv by klotz
8. Building RAG-Based Chatbots Using Streamlit + Langchain

   2023-11-07 Tags: rag, llm, streamlit, langchain, document, search, summarization, q and a by klotz
9. From RAGs to Riches 10 Applications of vector search to deeply understand your data and models

   Image Similarity Search
   Reverse Image Search
   Object Similarity Search
   Robust OCR Document Search
   Semantic Search
   Cross-modal Retrieval
   Probing Perceptual Similarity
   Comparing Model Representations
   Concept Interpolation
   Concept Space Traversal
   Image Similarity Search

   2023-10-26 Tags: llm, rag, similarity, vision, document, search, machine learning by klotz
10. Forget RAG, the Future is RAG-Fusion The Next Frontier of Search: Retrieval Augmented Generation meets Reciprocal Rank Fusion and Generated Queries

    2023-10-07 Tags: rag, search, llm, query expansion by klotz

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