Local Vectorization Package

Unlock the Power of Embeddings, Keep Your Data Secure, and Optimize Your Workflow.

In today's data-driven world, transforming multi-modal content into meaningful vector embeddings is crucial. However, data privacy and efficient processing are paramount, especially when dealing with sensitive information. Our Local Vectorization Package empowers you to generate high-quality embeddings directly on your own machines, granting you complete control over your data and streamlining your vectorization process. Ideal for industries with strict data governance and for anyone seeking faster, more private vector creation.

Key Benefits of Local Vectorization:

  • Uncompromising Data Privacy: Process your sensitive data locally. Your raw data never leaves your environment. Only the resulting embedding vectors are transferred, significantly minimizing data security risks and ensuring compliance with privacy regulations.

  • Enhanced Processing Efficiency: Vectorize data at your convenience, eliminating reliance on network connectivity and cloud processing latency. Experience faster turnaround times and reduced operational costs by leveraging your local computing resources.

  • Multi-Modal Data Expertise: Seamlessly vectorize a wide range of content types, including:

    • Images: jpg, jpeg, png, bmp, gif, tiff, tif

    • Videos: mp4, avi, mov, wmv

    • Sounds: mp3, wav

    • Point Clouds & 3D Models: xyz, xyzn, xyzrgb, pts, pcd, ply, stl, obj, off, gltf

    • Text: txt

    • (And potentially more as the package evolves)

  • Customizable Fine-Tuning for Superior Accuracy: Go beyond generic embeddings. Our package allows you to fine-tune vectorizer models using your own labeled data. This tailored approach significantly increases the relevance and accuracy of your vectors for your specific use cases. Start from pre-trained models or build upon existing fine-tuned models for continuous improvement.

  • Uncertainty Quantification (with Fine-Tuning): When using fine-tuned models, our package provides uncertainty scores for your generated vectors. Gain valuable insights into the reliability of your embeddings, enabling more informed decision-making in downstream applications.

  • Seamless Integration with Your Workflow: Once vectors are generated locally, they can be easily integrated into your existing systems. Specifically, they are designed for seamless uploading via our API index job for efficient data loading and management.

  • Easy to Use Command-Line Interface: Our package provides a user-friendly command-line interface for all key operations: data sampling, vectorization, and model fine-tuning. Clear instructions and flexible options empower both technical and non-technical users.

  • Flexible Vectorization Options: Choose from pre-trained vectorizers for a quick start or leverage custom-trained models for specialized needs. The package supports various vectorization scenarios, adapting to your specific requirements.

How Local Vectorization Works :

  1. Installation: Easily install the package within your local environment using readily available tools like Conda (environment setup instructions provided).

  2. Data Preparation: Organize your raw data and optional fine-tuning data in designated folders.

  3. Sampling: Sample your data to ensure optimal input length for the vectorization models.

  4. Fine-Tuning (Optional but Recommended for Accuracy): Fine-tune a vectorizer model using your labeled data to tailor it to your specific domain and improve vector quality. Configure data augmentations for image and video fine-tuning to enhance model robustness.

  5. Vectorization: Convert your sampled raw data into embedding vectors using either pre-trained or your custom fine-tuned vectorizer.

  6. Vector Utilization: Upload the generated vectors via our API index job or integrate them into your local applications for search, similarity analysis, recommendation systems, and more.