Python SDK
client.files
Manage files with the VLM Run Python SDK
Files API
The client.files
lets you upload, retrieve, and manage files used by the VLM Run platform. Files are essential for predictions, fine-tuning, and dataset creation.
Quick Examples
Upload a File
Retrieve a File
List Files
Delete a File
File Lifecycle
Files in VLM Run follow a simple lifecycle:
- Upload - Send files to the platform
- Process - Use files for predictions or other operations
- Manage - List, retrieve, or delete files as needed
Uploading Files
Basic Upload
With Purpose
Files can be categorized by purpose, which affects how they can be used:
From File Object
Available Purposes
Purpose | Description | Common File Types |
---|---|---|
fine-tune | For fine-tuning models | Training data, JSON files |
assistants | General usage (default) | Images, PDFs, text files |
assistants_output | Output from assistants | Generated content |
batch | Input files for batch processing | Large collections |
batch_output | Output from batch processing | Results and reports |
vision | For vision-based models | Images, screenshots |
datasets | For dataset creation | Labeled data collections |
Retrieving Files
Get File Details
List Files
Delete Files
Common Patterns
Upload and Process
The most common pattern is uploading a file and using it immediately:
Batch Processing Multiple Files
Temporary File Management
Clean up files after use:
Optimization Features
File Caching
VLM Run automatically detects duplicate files using content hashing:
Pre-upload Caching Check
Check if a file exists before uploading:
Response Structure
The FileResponse
object has the following structure:
Example usage: