Vector Databases: Building a Local LangChain Store in Python
Feb 21, 2025 · This tutorial will guide you step by step through building a local vector database using LangChain in Python. By the end, you’ll have a working solution, a deeper understanding of vector databases, and the ability to create your own …
How to Build a Local Vector Database for LangChain Tutorial
Sep 10, 2024 · The following guide walks you through a systematic process, detailing the necessary steps to establish a local vector database optimized for LangChain operations. A vector database is...
How to Create a Local LangChain Vector Database | DataStax
Dec 20, 2024 · In some cases, using a local vector database can both save money and simplify setting up a local dev stack. In this article, we’ll look at the benefits of using a local vector database with LangChain, discuss the best options, and discuss how to manage migrating from a local instance to a hosted one seamlessly.
GitHub - Stevenic/vectra: Vectra is a local vector database for …
Vectra is a local vector database for Node.js with features similar to Pinecone or Qdrant but built using local files. Each Vectra index is a folder on disk. There's an index.json file in the folder that contains all the vectors for the index along with any indexed metadata.
Create and fill a local vector database using python
May 16, 2024 · In this post I will show how to create embeddings for several posts on stack-overflow, save these embeddings in ChromaDB and finally query the database. Everything is done in a small...
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How to Create Vector Embeddings in Python | DataStax
Apr 8, 2025 · A popular local model for vector embedding is all-MiniLM-L6-v2.It’s trained as a good all-rounder that produces a 384-dimension vector from a chunk of text. To use it, import sentence_transformers and create a model using the identifier from Hugging Face, in this case "all-MiniLM-L6-v2". If you want to use a model that isn't in the sentence-transformers project, like the multilingual BGE-M3 ...
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