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Description
Voyager serves as an admin package for Laravel, providing essential BREAD (Create, Read, Edit, Add, Delete) functionalities, a media manager, a menu construction tool, and a host of additional features. By streamlining your administrative duties, Voyager allows you to concentrate on what you excel at: developing your next amazing application! This package can significantly reduce the time you spend on backend tasks, making the app development process more enjoyable. Just like a warm, freshly baked loaf of BREAD, Voyager integrates seamlessly into your workflow! With its intuitive admin interface, you can effortlessly manage CRUD or BREAD operations for various elements within your database, including posts and pages. It also includes a comprehensive media manager that enables you to view, edit, and delete files stored in your application, ensuring all your assets are centralized and easily accessible whether you're using local storage or S3. Additionally, creating and managing menus for your site is a breeze, as the admin menu itself is crafted using Voyager's menu builder, allowing you to modify menu items with ease. Overall, Voyager is designed to enhance your productivity and make the web development experience smoother than ever.
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
API Access
Has API
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Voyager
Country
United States
Website
voyager.devdojo.com
Vendor Details
Company Name
MongoDB
Founded
2007
Country
United States
Website
blog.voyageai.com/2024/12/04/voyage-code-3/
Product Features
Content Management
Audio Content
Customizable Templates
Document Indexing
E-forms
Full Text Search
Image Editor
SEO Management
Text Editor
Version Control
Video Content
Website Management