Principle:Googleapis Python genai File Upload
| Knowledge Sources | |
|---|---|
| Domains | File_Management, Multimodal |
| Last Updated | 2026-02-15 00:00 GMT |
Overview
A mechanism for transferring local files to a remote storage service, making them available as references in subsequent model inference requests.
Description
File Upload enables multimodal AI workflows by making local media (images, PDFs, audio, video) accessible to remote models. Rather than embedding raw bytes in every request, files are uploaded once and referenced by URI in subsequent calls. This reduces bandwidth, enables caching, and supports files that exceed inline size limits. The uploaded file receives a unique resource identifier that can be used in content parts, context caches, and other API operations.
Usage
Use file upload when working with media files (images, PDFs, audio, video) that need to be processed by the model. Upload is required for files larger than inline limits, and recommended for files that will be referenced multiple times (e.g., in context caching workflows). For small inline data, Part.from_bytes can be used instead.
Theoretical Basis
File upload follows a Reference Pattern:
- Upload phase: Binary data is transferred to the service, which returns a resource identifier (URI)
- Reference phase: Subsequent API calls reference the file by URI rather than re-transmitting data
- Lifecycle management: Uploaded files have retention policies and can be listed, retrieved, or deleted
# Abstract file reference pattern
file_ref = service.upload(local_path) # Returns URI
content = Part.from_uri(file_ref.uri) # Reference in content
response = model.generate(contents=[text, content])