Supported File Types

Jori supports returning various file types as output from the executed code. Users can generate and retrieve the following types of files:

1. Machine Learning Weights:

   • File extensions: .h5, .pkl, .pt, .onnx

   • Machine learning models trained using frameworks such as TensorFlow, Keras, PyTorch, or scikit-learn can be saved as weight files.

   • These files contain the learned parameters and architecture of the trained models.

   • Users can save their trained models and retrieve them for further use, such as making predictions or fine-tuning.

2. Images:

   • File extensions: .png, .jpg, .jpeg, .gif, .bmp, .svg

   • Our platform supports generating and returning various image file formats.

   • Users can create visualizations, plots, or any other graphical output and save them as image files.

   • These image files can be retrieved and used for further analysis, presentation, or integration into other applications.

3. HTML:

   • File extension: .html

   • Users can generate HTML files as output from their code.

   • HTML files can be used to create interactive web pages, dashboards, or reports.

   • The generated HTML files can include text, images, tables, and other web elements.

   • Users can retrieve the HTML files and render them in a web browser or embed them in other applications.

4. CSV (Comma-Separated Values):

   • File extension: .csv

   • CSV files are commonly used for storing and exchanging tabular data.

   • Users can generate CSV files containing structured data, such as results from data analysis or machine learning predictions.

   • CSV files can be easily imported into spreadsheet applications or used as input for further data processing.

5. JSON (JavaScript Object Notation):

   • File extension: .json

   • JSON is a lightweight data interchange format that is easy for humans to read and write and easy for machines to parse and generate.

   • Users can generate JSON files to store structured data, such as configuration settings, metadata, or results from API calls.

   • JSON files can be consumed by various programming languages and are commonly used in web development and data exchange.

6. Text Files:

   • File extensions: .txt, .log, .md

   • Plain text files can be generated to store unstructured data, logs, or documentation.

   • Users can generate text files to save output messages, debugging information, or any other textual content.

   • Text files can be easily viewed and edited using any text editor.

7. Pickle Files:

   • File extension: .pkl

   • Pickle is a Python-specific serialization format used for storing Python objects.

   • Users can save complex Python objects, such as trained models, data structures, or intermediate results, using the pickle format.

   • Pickle files can be loaded back into Python code for further analysis or processing.

Users can generate and retrieve these file types using the appropriate libraries and functions in their code. The platform handles the storage and retrieval of these files, allowing users to access them as needed.