BestHub
Sign in
Tag

document retrieval

0 views collected around this technical thread.

Sohu Tech Products
Sohu Tech Products
Mar 27, 2024 · Artificial Intelligence

Building a RAG Application with Baidu Vector Database and Qianfan Embedding

This tutorial walks through building a Retrieval‑Augmented Generation application by setting up Baidu’s Vector Database and Qianfan embedding service, configuring credentials, creating a document database and vector table, loading and chunking PDFs, generating embeddings, storing them, and performing scalar, vector and hybrid similarity searches, ready for integration with Wenxin LLM for answer generation.

AI applicationsBaidu QianfanEmbedding
0 likes · 11 min read
Building a RAG Application with Baidu Vector Database and Qianfan Embedding
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Mar 22, 2024 · Artificial Intelligence

Improving Document Search with Vector Search: From Elasticsearch Limitations to Milvus Integration

This article explains how traditional keyword search with Elasticsearch often yields inaccurate or incomplete results for document retrieval, introduces vectorization and semantic search using NLP embeddings, and demonstrates a practical workflow that combines these techniques with the Milvus vector database to achieve more accurate and efficient document search.

AIElasticsearchMilvus
0 likes · 13 min read
Improving Document Search with Vector Search: From Elasticsearch Limitations to Milvus Integration
ByteDance Web Infra
ByteDance Web Infra
Jun 16, 2023 · Artificial Intelligence

How AIGC Transforms Document Search: Architecture, Techniques, and Future Directions

This article explains how AI‑generated content (AIGC) reshapes document search by combining traditional indexing with modern embedding and prompt‑tuning techniques, reviews key components such as LangChain and Supabase, compares existing AI‑search products, and discusses the future blend of classic and AI‑driven search.

AI SearchAIGCEmbedding
0 likes · 15 min read
How AIGC Transforms Document Search: Architecture, Techniques, and Future Directions