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25.1
25.1
  • 🏠Introduction
    • Vectice overview
      • Autolog
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  • 🚀Log and Manage Assets with Vectice API
    • API cheatsheets
      • Vectice Python API cheatsheet
      • Vectice R API cheatsheet
    • Connect to API
    • Log assets to Vectice
      • Autolog your assets
      • Log datasets
      • Log models
      • Log attachments and notes
      • Log code
      • Log a custom data source
      • Log assets using Vectice IDs
      • Log dataset structure and statistics
      • Log custom metadata in a table format
      • Log MLFLow runs
    • Retrieve assets from app
    • Manage your assets
    • Manage your iteration
    • Preserve your code and asset lineage
  • 🤝Create Model documentation and reports
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    • Streamline documentation with Macros
    • Auto-document Models and Datasets with AskAI Prompts
    • Document phase outcomes
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  • ⭐Glossary
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  • 🎯Release notes
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  • ↗️References
    • Vectice Python API Reference
    • Vectice R API Cheatsheet
    • Notebooks and code samples
    • Vectice website
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  1. Log and Manage Assets with Vectice API
  2. Log assets to Vectice

Autolog your assets

PreviousLog assets to VecticeNextLog datasets

You can auto-document all your assets used in your IDE or notebook environment with a single line of code. Start by importing and configuring the autolog vectice package:

Autolog must be configured at the beginning of your notebook to capture all relevant information.

from vectice import autolog

autolog.config(
    api_token = 'your-api-key',       # Paste your api key
    host = 'https://app.vectice.com', # Paste your host
    phase = 'PHA-XXX'                 # Paste your Phase Id
)

Develop your model as you normally would. Once you are ready to log your data science work and assets, use the following line of code to log all of your current assets and work to the Vectice app:

autolog.notebook()

For more information, view our .

🚀
Autolog API reference