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相關頁面: AI相關工具非常非常的多，RAG開發工具會整理在RAG開發工具，LLM以及相關工具會整理在Large Language Models，Graph RAG開發工具會整理在Graph RAG，其他工具整理在Generative AI開發工具中。目前還有一些資料在Generative AI及RAG中，將逐步整理這些內容。

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開發工具簡介

Web Framework for RAG

• 開源RAG網頁套件研究
  • open-webui
  • Hollama
  • LoLLMs Webui
  • BionicGPT
  • LibreChat
  • LLMStack

Vector Databases

• Everything you need to know about Vector Databases — A Deep Dive
• All You Need to Know about Vector Databases and How to Use Them to Augment Your LLM Apps (Friend Link)
  • Suppose we decide to use a vector store — What options do we have?
    • Pure vector databases
      • Chroma, Pinecone, Weaviate, Milvus
    • Extended capabilities in SQL, NoSQL or text search databases
      • Redis, MongoDB
      • Pgvector, for example, is the open source vector similarity search for Postgres
    • Simple vector libraries
      • FAISS
  • Hands-On Tutorial — Set up your first Vector Store
    • Chroma
• Top Vector Databases— And How To Choose (Friend LInk)
  • Search Indexing Algorithms:
    • Hash-based
      • Locality-Sensitive Hashing (LSH)
    • Tree-based
      • Annoy (Approximate Nearest Neighbors Oh Yeah)
    • Graph-based
      • HNSW (Hierarchical Navigable Small World)
    • Inverted File
      • IVF (Inverted File Index), IVFFlat, IVFPQ, and IVFSQ.
  • Vector Libraries
    • Faiss (Facebook AI Similarity Search)
    • HNSWlib
    • Nmslib (Non-Metric Space Library)
  • Vector Databases
    • Miluvs
    • Weaviate
    • Qdrant
    • Pinecone
    • ElasticSearch
    • Chroma
    • Non-dedicated Vector Databases — Redis, MongoDB, and PGVector
• Optimize Vector Databases, Enhance RAG-Driven Generative AI
  • Milvus Vector Database Optimizations
    • Reducing Memory Movement Overhead in Datanode Buffer Write
    • Inverted Index Building with Reduced Memory Allocation Overhead
  • Redis Vector Search Acceleration through Software Prefetch
• Explaining Vector Databases in 3 Levels of Difficulty (Friend Link)

Chroma

• Integrating Vector Databases with LLMs: A Hands-On Guide
  • Building a Closed-QA Bot with Falcon-7B and ChromaDB

KDB

• Advanced RAG using Llamaindex and KDB.AI

Milvus

• Building RAG with Milvus, vLLM, and Llama 3.1
• Introducing Milvus 2.5: Built-in Full-Text Search, Advanced Query Optimization, and More
• Leveraging Milvus and Friendli Serverless Endpoints for Advanced RAG and Multi-Modal Queries
• Building RAG Applications with Milvus, Qwen, and vLLM

Oracle