Request to generate a presigned URL for model archive upload. This is step 1 of the presigned URL workflow: 1. POST /models/uploads → Returns presigned_url + upload_id 2. PUT presigned_url with model archive (client uploads directly to S3) 3. POST /models/uploads/{upload_id}/confirm → Validates and creates model Requirements: - name: Model name (e.g., 'my_custom_embedder') - version: Semantic version (e.g., '1.0.0') - model_format: Format of the model weights - file_size_bytes: Expected archive size for quota validation
| Name | Type | Description | Notes |
|---|---|---|---|
| name | str | Model name (alphanumeric with underscores, no spaces) | |
| version | str | Semantic version string | |
| model_format | str | Format of the model weights | |
| description | str | Optional description of the model | [optional] |
| file_size_bytes | int | Expected file size in bytes for quota validation | [optional] |
| presigned_url_expiration | int | Presigned URL expiration time in seconds (1-24 hours) | [optional] [default to 3600] |
| resource_requirements | ModelResourceRequirements | Resource requirements for model deployment | [optional] |
| framework | str | ML framework (e.g., sentence-transformers, transformers) | [optional] |
| task_type | str | Task type (e.g., embedding, classification, generation) | [optional] |
from mixpeek.models.create_model_upload_request import CreateModelUploadRequest
# TODO update the JSON string below
json = "{}"
# create an instance of CreateModelUploadRequest from a JSON string
create_model_upload_request_instance = CreateModelUploadRequest.from_json(json)
# print the JSON string representation of the object
print(CreateModelUploadRequest.to_json())
# convert the object into a dict
create_model_upload_request_dict = create_model_upload_request_instance.to_dict()
# create an instance of CreateModelUploadRequest from a dict
create_model_upload_request_from_dict = CreateModelUploadRequest.from_dict(create_model_upload_request_dict)