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Description

Weaviate is an open-source vector database built for the AI era, giving teams one platform for vector search, retrieval-augmented generation, and agent memory. Store data objects together with embeddings from your preferred machine learning models and scale effortlessly to billions of objects. Import your own vectors or rely on Weaviate's built-in vectorization, then search across vector, keyword, and hybrid methods to get highly relevant results, even when filters are applied. By connecting to today's leading large language models, Weaviate helps you build grounded search and question-answering over your own data. The platform reaches well beyond storage: its Query Agent translates plain-language questions into accurate queries with citations, Engram delivers managed long-term memory for AI agents, and Weaviate Embeddings removes the work of running your own embedding pipeline. Available as self-hosted open source or fully managed Weaviate Cloud across AWS, GCP, and Azure, backed by SOC 2 Type II, native multi-tenancy, replication, and role-based access control. From semantic search to recommendation to fully agentic applications, Weaviate is the foundation to ship AI products faster.

Description

Voyage AI has unveiled voyage-code-3, an advanced embedding model specifically designed to enhance code retrieval capabilities. This innovative model achieves superior performance, surpassing OpenAI-v3-large and CodeSage-large by averages of 13.80% and 16.81% across a diverse selection of 32 code retrieval datasets. It accommodates embeddings of various dimensions, including 2048, 1024, 512, and 256, and provides an array of embedding quantization options such as float (32-bit), int8 (8-bit signed integer), uint8 (8-bit unsigned integer), binary (bit-packed int8), and ubinary (bit-packed uint8). With a context length of 32 K tokens, voyage-code-3 exceeds the limitations of OpenAI's 8K and CodeSage Large's 1K context lengths, offering users greater flexibility. Utilizing an innovative approach known as Matryoshka learning, it generates embeddings that feature a layered structure of varying lengths within a single vector. This unique capability enables users to transform documents into a 2048-dimensional vector and subsequently access shorter dimensional representations (such as 256, 512, or 1024 dimensions) without the need to re-run the embedding model, thus enhancing efficiency in code retrieval tasks. Additionally, voyage-code-3 positions itself as a robust solution for developers seeking to improve their coding workflow.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Astro by Astronomer Yes 
Azure OpenAI Service Yes 
Boomi Yes 
Comet Yes 
Context Data Yes 
Contextual AI Yes 
DigitalOcean Yes 
FriendliAI Yes 
GitHub Yes 
Hugging Face Yes 
LangChain Yes 
Mem0 Yes 
Microsoft Azure Yes 
Milvus No 
NVIDIA AI Data Platform Yes 
Nomic Atlas Yes 
Ollama Yes 
Qdrant No 
Unstructured Yes 
n8n Yes 

Integrations

Astro by Astronomer No 
Azure OpenAI Service No 
Boomi No 
Comet No 
Context Data No 
Contextual AI No 
DigitalOcean No 
FriendliAI No 
GitHub No 
Hugging Face No 
LangChain No 
Mem0 No 
Microsoft Azure No 
Milvus Yes 
NVIDIA AI Data Platform No 
Nomic Atlas No 
Ollama No 
Qdrant Yes 
Unstructured No 
n8n No 

Pricing Details

Free
Open source (free); free Weaviate Cloud tier; paid Cloud plans from $45/mo.
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Weaviate

Founded

2019

Country

The Netherlands

Website

weaviate.io

Vendor Details

Company Name

MongoDB

Founded

2007

Country

United States

Website

blog.voyageai.com/2024/12/04/voyage-code-3/

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