voyage-code-3MongoDB
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Related Products
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About
Vectorize is a platform designed to transform unstructured data into optimized vector search indexes, facilitating retrieval-augmented generation pipelines. It enables users to import documents or connect to external knowledge management systems, allowing Vectorize to extract natural language suitable for LLMs. The platform evaluates multiple chunking and embedding strategies in parallel, providing recommendations or allowing users to choose their preferred methods. Once a vector configuration is selected, Vectorize deploys it into a real-time vector pipeline that automatically updates with any data changes, ensuring accurate search results. The platform offers connectors to various knowledge repositories, collaboration platforms, and CRMs, enabling seamless integration of data into generative AI applications. Additionally, Vectorize supports the creation and updating of vector indexes in preferred vector databases.
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About
Voyage AI introduces voyage-code-3, a next-generation embedding model optimized for code retrieval. It outperforms OpenAI-v3-large and CodeSage-large by an average of 13.80% and 16.81% on a suite of 32 code retrieval datasets, respectively. It supports embeddings of 2048, 1024, 512, and 256 dimensions and offers multiple embedding quantization options, including float (32-bit), int8 (8-bit signed integer), uint8 (8-bit unsigned integer), binary (bit-packed int8), and ubinary (bit-packed uint8). With a 32 K-token context length, it surpasses OpenAI's 8K and CodeSage Large's 1K context lengths. Voyage-code-3 employs Matryoshka learning to create embeddings with a nested family of various lengths within a single vector. This allows users to vectorize documents into a 2048-dimensional vector and later use shorter versions (e.g., 256, 512, or 1024 dimensions) without re-invoking the embedding model.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Organizations searching for a solution to improve their AI capabilities by optimizing their vector search indexes
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Audience
AI researchers and developers in search of a solution providing an embedding model for code retrieval
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Support
Phone Support
Not Supported
24/7 Live Support
Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Not Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
$0.57 per hour
Free Version
Supported
Free Trial
Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
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Company InformationVectorize
Founded: 2023
United States
vectorize.io
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Company InformationMongoDB
Founded: 2007
United States
blog.voyageai.com/2024/12/04/voyage-code-3/
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Integrations
Amazon S3
Supported
Azure Blob Storage
Supported
Confluence
Supported
Discord
Supported
Dropbox
Supported
Elasticsearch
Not Supported
Google Cloud Storage
Supported
Google Drive
Supported
Intercom
Supported
Milvus
Not Supported
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Integrations
Amazon S3
Not Supported
Azure Blob Storage
Not Supported
Confluence
Not Supported
Discord
Not Supported
Dropbox
Not Supported
Elasticsearch
Supported
Google Cloud Storage
Not Supported
Google Drive
Not Supported
Intercom
Not Supported
Milvus
Supported
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