Vector Database
![A tutorial on building local agent using LangGraph, LLaMA3 and Elasticsearch vector store from scratch](/search-labs/_next/image?url=%2Fsearch-labs%2Fassets%2Fimages%2Fblog-build-fully-local-rag-agent-LLAMA3.jpeg&w=3840&q=100)
A tutorial on building local agent using LangGraph, LLaMA3 and Elasticsearch vector store from scratch
This article will provide a detailed tutorial on implementing a local, reliable agent using LangGraph, combining concepts from Adaptive RAG, Corrective RAG, and Self-RAG papers, and integrating Langchain, Elasticsearch Vector Store, Tavily AI for web search, and LLaMA3 via Ollama.
![Looking back: A timeline of vector search innovations](/search-labs/_next/image?url=%2Fsearch-labs%2Fassets%2Fimages%2F8-15-winding-road.png&w=3840&q=100)
Looking back: A timeline of vector search innovations
Looking back at Elastic's vector search innovations in Elasticsearch and Lucene
![Vector embeddings made simple with the Elasticsearch-DSL client for Python](/search-labs/_next/image?url=%2Fsearch-labs%2Fassets%2Fimages%2Felasticsearch-dsl-python-vectors.png&w=3840&q=100)
Vector embeddings made simple with the Elasticsearch-DSL client for Python
Learn how to ingest and search dense vectors in Python using the Elasticsearch-DSL client.
![Advanced RAG Techniques Part 2: Querying and Testing](/search-labs/_next/image?url=%2Fsearch-labs%2Fassets%2Fimages%2Fsimple_rag.jpg&w=3840&q=100)
Advanced RAG Techniques Part 2: Querying and Testing
Discussing and implementing techniques which may increase RAG performance. Part 2 of 2, focusing on querying and testing an advanced RAG pipeline.
![Advanced RAG Techniques Part 1: Data Processing](/search-labs/_next/image?url=%2Fsearch-labs%2Fassets%2Fimages%2Fadvanced_rag.jpg&w=3840&q=100)
Advanced RAG Techniques Part 1: Data Processing
Discussing and implementing techniques which may increase RAG performance. Part 1 of 2, focusing on the data processing and ingestion component of an advanced RAG pipeline.
![Smart ordering system with Phi-3 small models and Elastic](/search-labs/_next/image?url=%2Fsearch-labs%2Fassets%2Fimages%2Futilizing-phi3-models%2Fcover.png&w=3840&q=100)
Smart ordering system with Phi-3 small models and Elastic
Deploying Phi-3 models on Azure AI Studio and using them with Elastic Open Inference Service to create a RAG application.
![Building multilingual RAG with Elastic and Mistral](/search-labs/_next/image?url=%2Fsearch-labs%2Fassets%2Fimages%2Fbuilding-multilingual-rag-with-elastic-and-mistral%2Fcover.png&w=3840&q=100)
Building multilingual RAG with Elastic and Mistral
Building a multilingual RAG application using Elastic and Mixtral 8x22B model
![Mistral AI embedding models now available via Elasticsearch Open Inference API](/search-labs/_next/image?url=%2Fsearch-labs%2Fassets%2Fimages%2Fmistral-partner-blog.png&w=3840&q=100)
Mistral AI embedding models now available via Elasticsearch Open Inference API
Learn more about how to use Mistral embeddings with Elastic built search experiences!
![Introducing the sparse vector query: Searching sparse vectors with inference or precomputed query vectors](/search-labs/_next/image?url=%2Fsearch-labs%2Fassets%2Fimages%2Fintroducing-sparse-vector-query%2Fdot-product-scoring-example.png&w=3840&q=100)
Introducing the sparse vector query: Searching sparse vectors with inference or precomputed query vectors
Learn about the Elasticsearch sparse vector query, how it works, and how to effectively use it.
![Bit vectors in Elasticsearch](/search-labs/_next/image?url=%2Fsearch-labs%2Fassets%2Fimages%2Fbit-vectors-in-elasticsearch%2Fhamming_dist.png&w=3840&q=100)
Bit vectors in Elasticsearch
Discover what are bit vectors, their practical implications and how to use them in Elasticsearch.