使用LangChain框架实现多向量索引: from langchain.retrievers import MultiVectorRetriever from langchain.vectorstores import Chroma from langchain.embeddings import OpenAIEmbeddings # 创建向量存储 vectorstore = Chroma(embedding_function=OpenAIEmbeddings()) # 配置多向量检索器 retriever = MultiVectorRetriever( v...
Rerankers and Two-Stage Retrieval | Pinecone Custom Retriever combining KG Index and VectorStore Index Enhanced QA Integrating Unstructured Knowledge Graph Using Neo4j and LangChain https://blog.langchain.dev/using-a-knowledge-graph-to-implement-a-devops-rag-application/ AI pursuer:揭秘 Self-RAG 技...
原文:Retrieval of originating information in multi-vector documents — Elastic Search Labs
"vector" : [3,2,890], "text_chunk" : "doc 2 chunk 1" }, { "vector" : [129,765,13], "text_chunk" : "doc 2 chunk 2" } ] } 使用inner_hits 查询索引并返回相关文本块: GET my-long-text-index/_search { "knn": { "field": "my_long_text_field.vector", "query_vector": ...
supporting both local and API providers ➡️ Implement hybrid RAG pipelines with full-text & vector retrieval ➡️ Enable multi-modal QA support for documents with figures & tables Kotaemon offers: ✅ Multi-user login and document collection management ✅ Advanced citations with document ...
本教程演示如何使用向量检索服务(DashVector),结合ModelScope上的中文CLIP多模态检索模型,构建实时的“文本搜图片”的多模态检索能力。作为示例,我们采用多模态牧歌数据集作为图片语料库,用户通过输入文本来跨模态检索最相似的图片。 整体流程 主要分为两个阶段: ...