Files and attachments

Input attachments (upload)

PyGPT makes it simple for users to upload files to the server and send them to the model for tasks like analysis, similar to attaching files in ChatGPT. There’s a separate Files tab next to the text input area specifically for managing file uploads. Users can opt to have files automatically deleted after each upload or keep them on the list for repeated use.

The attachment feature is available in both the Assistant and Vision modes at default. In Assistant mode, you can send documents and files to analyze, while in Vision mode, you can send images. In other modes, you can enable attachments by activating the Vision (inline) plugin (for providing images only).

Files (download, code generation)

PyGPT enables the automatic download and saving of files created by the model. This is carried out in the background, with the files being saved to an data folder located within the user’s working directory. To view or manage these files, users can navigate to the Files tab which features a file browser for this specific directory. Here, users have the interface to handle all files sent by the AI.

This data directory is also where the application stores files that are generated locally by the AI, such as code files or any other outputs requested from the model. Users have the option to execute code directly from the stored files and read their contents, with the results fed back to the AI. This hands-off process is managed by the built-in plugin system and model-triggered commands. You can also indexing files from this directory (using integrated Llama-index) and use it’s contents as additional context provided to discussion.

The Command: Files I/O plugin takes care of file operations in the data directory, while the Command: Code Interpreter plugin allows for the execution of code from these files.

To allow the model to manage files or python code execution, the Execute commands option must be active, along with the above-mentioned plugins: