Leonardo AI Python Client SDK
Project description
Leonardo-Ai-SDK
Summary
Rest Endpoints: Leonardo.Ai API OpenAPI specification.
Table of Contents
SDK Installation
[!NOTE] Python version upgrade policy
Once a Python version reaches its official end of life date, a 3-month grace period is provided for users to upgrade. Following this grace period, the minimum python version supported in the SDK will be updated.
The SDK can be installed with uv, pip, or poetry package managers.
uv
uv is a fast Python package installer and resolver, designed as a drop-in replacement for pip and pip-tools. It's recommended for its speed and modern Python tooling capabilities.
uv add Leonardo-Ai-SDK
PIP
PIP is the default package installer for Python, enabling easy installation and management of packages from PyPI via the command line.
pip install Leonardo-Ai-SDK
Poetry
Poetry is a modern tool that simplifies dependency management and package publishing by using a single pyproject.toml file to handle project metadata and dependencies.
poetry add Leonardo-Ai-SDK
Shell and script usage with uv
You can use this SDK in a Python shell with uv and the uvx command that comes with it like so:
uvx --from Leonardo-Ai-SDK python
It's also possible to write a standalone Python script without needing to set up a whole project like so:
#!/usr/bin/env -S uv run --script
# /// script
# requires-python = ">=3.10"
# dependencies = [
# "Leonardo-Ai-SDK",
# ]
# ///
from leonardo_ai_sdk import LeonardoAiSDK
sdk = LeonardoAiSDK(
# SDK arguments
)
# Rest of script here...
Once that is saved to a file, you can run it with uv run script.py where
script.py can be replaced with the actual file name.
IDE Support
PyCharm
Generally, the SDK will work well with most IDEs out of the box. However, when using PyCharm, you can enjoy much better integration with Pydantic by installing an additional plugin.
SDK Example Usage
Example
# Synchronous Example
from leonardo_ai_sdk import LeonardoAiSDK
from leonardo_ai_sdk.models import shared
with LeonardoAiSDK(
bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as las_client:
res = las_client.blueprints.execute_blueprint(request={
"blueprint_version_id": "550e8400-e29b-41d4-a716-446655440000",
"input": {
"collection_ids": [],
"node_inputs": [
{
"node_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"setting_name": shared.SettingName.TEXT,
"value": "A futuristic cityscape at sunset",
},
{
"node_id": "b2c3d4e5-f6a7-8901-bcde-f12345678901",
"setting_name": shared.SettingName.TEXT_VARIABLES,
"value": [
{
"name": "characterName",
"value": "Luna",
},
{
"name": "outfit",
"value": "cyberpunk armor",
},
],
},
{
"node_id": "c3d4e5f6-a7b8-9012-cdef-123456789012",
"setting_name": shared.SettingName.IMAGE_URL,
"value": "https://cdn.leonardo.ai/users/example/image.png",
},
],
"public": False,
},
})
assert res.one_of is not None
# Handle response
print(res.one_of)
The same SDK client can also be used to make asynchronous requests by importing asyncio.
# Asynchronous Example
import asyncio
from leonardo_ai_sdk import LeonardoAiSDK
from leonardo_ai_sdk.models import shared
async def main():
async with LeonardoAiSDK(
bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as las_client:
res = await las_client.blueprints.execute_blueprint_async(request={
"blueprint_version_id": "550e8400-e29b-41d4-a716-446655440000",
"input": {
"collection_ids": [],
"node_inputs": [
{
"node_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"setting_name": shared.SettingName.TEXT,
"value": "A futuristic cityscape at sunset",
},
{
"node_id": "b2c3d4e5-f6a7-8901-bcde-f12345678901",
"setting_name": shared.SettingName.TEXT_VARIABLES,
"value": [
{
"name": "characterName",
"value": "Luna",
},
{
"name": "outfit",
"value": "cyberpunk armor",
},
],
},
{
"node_id": "c3d4e5f6-a7b8-9012-cdef-123456789012",
"setting_name": shared.SettingName.IMAGE_URL,
"value": "https://cdn.leonardo.ai/users/example/image.png",
},
],
"public": False,
},
})
assert res.one_of is not None
# Handle response
print(res.one_of)
asyncio.run(main())
Available Resources and Operations
Available methods
ThreeDModelAssets
- delete3_d_model_by_id - Delete 3D Model by ID
- get3_d_model_by_id - Get 3D Model by ID
- get3_d_models_by_user_id - Get 3D models by user ID
- upload_model_asset - Upload 3D Model
Blueprints
- execute_blueprint - Execute a Blueprint
- get_blueprint_by_id - Get Blueprint by ID
- get_blueprint_execution - Get Blueprint Execution by ID
- get_blueprint_execution_generations - Get Blueprint Execution Generations by Execution ID
- get_blueprint_versions_by_blueprint_id - Get Blueprint Versions by Blueprint ID
- list_blueprints - List Blueprints
Dataset
- create_dataset - Create a Dataset
- delete_dataset_by_id - Delete a Single Dataset by ID
- get_dataset_by_id - Get a Single Dataset by ID
- upload_dataset_image - Upload dataset image
- upload_dataset_image_from_gen - Upload a Single Generated Image to a Dataset
Elements
- create_element - Train a Custom Element
- delete_element_by_id - Delete a Single Custom Element by ID
- get_custom_elements_by_user_id - Get a list of Custom Elements by User ID
- get_element_by_id - Get a Single Custom Element by ID
- list_elements - List Elements
Image
- create_generation - Create a Generation of Images
- delete_generation_by_id - Delete a Single Generation
- get_generation_by_id - Get a Single Generation
- get_generations_by_user_id - Get generations by user ID
InitImages
- delete_init_image_by_id - Delete init image
- get_init_image_by_id - Get single init image
- upload_canvas_init_image - Upload Canvas Editor init and mask image
- upload_init_image - Upload init image
Models
- create_model - Train a Custom Model
- delete_model_by_id - Delete a Single Custom Model by ID
- get_custom_models_by_user_id - Get a list of Custom Models by User ID
- get_model_by_id - Get a Single Custom Model by ID
- list_platform_models - List Platform Models
Motion
- create_image_to_video_generation - Create a video generation from an image
- create_svd_motion_generation - Create SVD Motion Generation
- create_text_to_video_generation - Create a video generation from a text prompt
- create_video_upscale - Upscale a generated video
PricingCalculator
- pricing_calculator - Calculating API Cost
Prompt
- prompt_improve - Improve a Prompt
- prompt_random - Generate a Random prompt
RealtimeCanvas
- create_lcm_generation - Create LCM Generation
- perform_alchemy_upscale_lcm - Perform Alchemy Upscale on a LCM image
- perform_inpainting_lcm - Perform inpainting on a LCM image
- perform_instant_refine - Perform instant refine on a LCM image
Texture
- create_texture_generation - Create Texture Generation
- delete_texture_generation_by_id - Delete Texture Generation by ID
- get_texture_generation_by_id - Get Texture Generation by ID
- get_texture_generations_by_model_id - Get texture generations by 3D Model ID
User
- get_user_self - Get user information
Variation
- create_universal_upscaler_job - Create using Universal Upscaler
- create_variation_no_bg - Create no background
- create_variation_unzoom - Create unzoom
- create_variation_upscale - Create upscale
- get_motion_variation_by_id - Get motion variation by ID
- get_variation_by_id - Get variation by ID
Retries
Some of the endpoints in this SDK support retries. If you use the SDK without any configuration, it will fall back to the default retry strategy provided by the API. However, the default retry strategy can be overridden on a per-operation basis, or across the entire SDK.
To change the default retry strategy for a single API call, simply provide a RetryConfig object to the call:
from leonardo_ai_sdk import LeonardoAiSDK
from leonardo_ai_sdk.models import shared
from leonardo_ai_sdk.utils import BackoffStrategy, RetryConfig
with LeonardoAiSDK(
bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as las_client:
res = las_client.blueprints.execute_blueprint(request={
"blueprint_version_id": "550e8400-e29b-41d4-a716-446655440000",
"input": {
"collection_ids": [],
"node_inputs": [
{
"node_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"setting_name": shared.SettingName.TEXT,
"value": "A futuristic cityscape at sunset",
},
{
"node_id": "b2c3d4e5-f6a7-8901-bcde-f12345678901",
"setting_name": shared.SettingName.TEXT_VARIABLES,
"value": [
{
"name": "characterName",
"value": "Luna",
},
{
"name": "outfit",
"value": "cyberpunk armor",
},
],
},
{
"node_id": "c3d4e5f6-a7b8-9012-cdef-123456789012",
"setting_name": shared.SettingName.IMAGE_URL,
"value": "https://cdn.leonardo.ai/users/example/image.png",
},
],
"public": False,
},
},
RetryConfig("backoff", BackoffStrategy(1, 50, 1.1, 100), False))
assert res.one_of is not None
# Handle response
print(res.one_of)
If you'd like to override the default retry strategy for all operations that support retries, you can use the retry_config optional parameter when initializing the SDK:
from leonardo_ai_sdk import LeonardoAiSDK
from leonardo_ai_sdk.models import shared
from leonardo_ai_sdk.utils import BackoffStrategy, RetryConfig
with LeonardoAiSDK(
retry_config=RetryConfig("backoff", BackoffStrategy(1, 50, 1.1, 100), False),
bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as las_client:
res = las_client.blueprints.execute_blueprint(request={
"blueprint_version_id": "550e8400-e29b-41d4-a716-446655440000",
"input": {
"collection_ids": [],
"node_inputs": [
{
"node_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"setting_name": shared.SettingName.TEXT,
"value": "A futuristic cityscape at sunset",
},
{
"node_id": "b2c3d4e5-f6a7-8901-bcde-f12345678901",
"setting_name": shared.SettingName.TEXT_VARIABLES,
"value": [
{
"name": "characterName",
"value": "Luna",
},
{
"name": "outfit",
"value": "cyberpunk armor",
},
],
},
{
"node_id": "c3d4e5f6-a7b8-9012-cdef-123456789012",
"setting_name": shared.SettingName.IMAGE_URL,
"value": "https://cdn.leonardo.ai/users/example/image.png",
},
],
"public": False,
},
})
assert res.one_of is not None
# Handle response
print(res.one_of)
Error Handling
LeonardoAiSDKError is the base class for all HTTP error responses. It has the following properties:
| Property | Type | Description |
|---|---|---|
err.message |
str |
Error message |
err.status_code |
int |
HTTP response status code eg 404 |
err.headers |
httpx.Headers |
HTTP response headers |
err.body |
str |
HTTP body. Can be empty string if no body is returned. |
err.raw_response |
httpx.Response |
Raw HTTP response |
err.data |
Optional. Some errors may contain structured data. See Error Classes. |
Example
from leonardo_ai_sdk import LeonardoAiSDK
from leonardo_ai_sdk.models import errors, shared
with LeonardoAiSDK(
bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as las_client:
res = None
try:
res = las_client.blueprints.execute_blueprint(request={
"blueprint_version_id": "550e8400-e29b-41d4-a716-446655440000",
"input": {
"collection_ids": [],
"node_inputs": [
{
"node_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"setting_name": shared.SettingName.TEXT,
"value": "A futuristic cityscape at sunset",
},
{
"node_id": "b2c3d4e5-f6a7-8901-bcde-f12345678901",
"setting_name": shared.SettingName.TEXT_VARIABLES,
"value": [
{
"name": "characterName",
"value": "Luna",
},
{
"name": "outfit",
"value": "cyberpunk armor",
},
],
},
{
"node_id": "c3d4e5f6-a7b8-9012-cdef-123456789012",
"setting_name": shared.SettingName.IMAGE_URL,
"value": "https://cdn.leonardo.ai/users/example/image.png",
},
],
"public": False,
},
})
assert res.one_of is not None
# Handle response
print(res.one_of)
except errors.LeonardoAiSDKError as e:
# The base class for HTTP error responses
print(e.message)
print(e.status_code)
print(e.body)
print(e.headers)
print(e.raw_response)
# Depending on the method different errors may be thrown
if isinstance(e, errors.ExecuteBlueprintResponseBody):
print(e.data.raw_response) # Optional[httpx.Response]
print(e.data.error) # Optional[str]
Error Classes
Primary error:
LeonardoAiSDKError: The base class for HTTP error responses.
Less common errors (6)
Network errors:
httpx.RequestError: Base class for request errors.httpx.ConnectError: HTTP client was unable to make a request to a server.httpx.TimeoutException: HTTP request timed out.
Inherit from LeonardoAiSDKError:
ExecuteBlueprintResponseBody: Bad Request - Invalid input type or missing required GraphQL field. Status code400. Applicable to 1 of 55 methods.*ResponseValidationError: Type mismatch between the response data and the expected Pydantic model. Provides access to the Pydantic validation error via thecauseattribute.
* Check the method documentation to see if the error is applicable.
Custom HTTP Client
The Python SDK makes API calls using the httpx HTTP library. In order to provide a convenient way to configure timeouts, cookies, proxies, custom headers, and other low-level configuration, you can initialize the SDK client with your own HTTP client instance.
Depending on whether you are using the sync or async version of the SDK, you can pass an instance of HttpClient or AsyncHttpClient respectively, which are Protocol's ensuring that the client has the necessary methods to make API calls.
This allows you to wrap the client with your own custom logic, such as adding custom headers, logging, or error handling, or you can just pass an instance of httpx.Client or httpx.AsyncClient directly.
For example, you could specify a header for every request that this sdk makes as follows:
from leonardo_ai_sdk import LeonardoAiSDK
import httpx
http_client = httpx.Client(headers={"x-custom-header": "someValue"})
s = LeonardoAiSDK(client=http_client)
or you could wrap the client with your own custom logic:
from leonardo_ai_sdk import LeonardoAiSDK
from leonardo_ai_sdk.httpclient import AsyncHttpClient
import httpx
class CustomClient(AsyncHttpClient):
client: AsyncHttpClient
def __init__(self, client: AsyncHttpClient):
self.client = client
async def send(
self,
request: httpx.Request,
*,
stream: bool = False,
auth: Union[
httpx._types.AuthTypes, httpx._client.UseClientDefault, None
] = httpx.USE_CLIENT_DEFAULT,
follow_redirects: Union[
bool, httpx._client.UseClientDefault
] = httpx.USE_CLIENT_DEFAULT,
) -> httpx.Response:
request.headers["Client-Level-Header"] = "added by client"
return await self.client.send(
request, stream=stream, auth=auth, follow_redirects=follow_redirects
)
def build_request(
self,
method: str,
url: httpx._types.URLTypes,
*,
content: Optional[httpx._types.RequestContent] = None,
data: Optional[httpx._types.RequestData] = None,
files: Optional[httpx._types.RequestFiles] = None,
json: Optional[Any] = None,
params: Optional[httpx._types.QueryParamTypes] = None,
headers: Optional[httpx._types.HeaderTypes] = None,
cookies: Optional[httpx._types.CookieTypes] = None,
timeout: Union[
httpx._types.TimeoutTypes, httpx._client.UseClientDefault
] = httpx.USE_CLIENT_DEFAULT,
extensions: Optional[httpx._types.RequestExtensions] = None,
) -> httpx.Request:
return self.client.build_request(
method,
url,
content=content,
data=data,
files=files,
json=json,
params=params,
headers=headers,
cookies=cookies,
timeout=timeout,
extensions=extensions,
)
s = LeonardoAiSDK(async_client=CustomClient(httpx.AsyncClient()))
Server Selection
Override Server URL Per-Client
The default server can be overridden globally by passing a URL to the server_url: str optional parameter when initializing the SDK client instance. For example:
from leonardo_ai_sdk import LeonardoAiSDK
from leonardo_ai_sdk.models import shared
with LeonardoAiSDK(
server_url="https://cloud.leonardo.ai/api/rest/v1",
bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as las_client:
res = las_client.blueprints.execute_blueprint(request={
"blueprint_version_id": "550e8400-e29b-41d4-a716-446655440000",
"input": {
"collection_ids": [],
"node_inputs": [
{
"node_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"setting_name": shared.SettingName.TEXT,
"value": "A futuristic cityscape at sunset",
},
{
"node_id": "b2c3d4e5-f6a7-8901-bcde-f12345678901",
"setting_name": shared.SettingName.TEXT_VARIABLES,
"value": [
{
"name": "characterName",
"value": "Luna",
},
{
"name": "outfit",
"value": "cyberpunk armor",
},
],
},
{
"node_id": "c3d4e5f6-a7b8-9012-cdef-123456789012",
"setting_name": shared.SettingName.IMAGE_URL,
"value": "https://cdn.leonardo.ai/users/example/image.png",
},
],
"public": False,
},
})
assert res.one_of is not None
# Handle response
print(res.one_of)
Authentication
Per-Client Security Schemes
This SDK supports the following security scheme globally:
| Name | Type | Scheme |
|---|---|---|
bearer_auth |
http | HTTP Bearer |
To authenticate with the API the bearer_auth parameter must be set when initializing the SDK client instance. For example:
from leonardo_ai_sdk import LeonardoAiSDK
from leonardo_ai_sdk.models import shared
with LeonardoAiSDK(
bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as las_client:
res = las_client.blueprints.execute_blueprint(request={
"blueprint_version_id": "550e8400-e29b-41d4-a716-446655440000",
"input": {
"collection_ids": [],
"node_inputs": [
{
"node_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"setting_name": shared.SettingName.TEXT,
"value": "A futuristic cityscape at sunset",
},
{
"node_id": "b2c3d4e5-f6a7-8901-bcde-f12345678901",
"setting_name": shared.SettingName.TEXT_VARIABLES,
"value": [
{
"name": "characterName",
"value": "Luna",
},
{
"name": "outfit",
"value": "cyberpunk armor",
},
],
},
{
"node_id": "c3d4e5f6-a7b8-9012-cdef-123456789012",
"setting_name": shared.SettingName.IMAGE_URL,
"value": "https://cdn.leonardo.ai/users/example/image.png",
},
],
"public": False,
},
})
assert res.one_of is not None
# Handle response
print(res.one_of)
Resource Management
The LeonardoAiSDK class implements the context manager protocol and registers a finalizer function to close the underlying sync and async HTTPX clients it uses under the hood. This will close HTTP connections, release memory and free up other resources held by the SDK. In short-lived Python programs and notebooks that make a few SDK method calls, resource management may not be a concern. However, in longer-lived programs, it is beneficial to create a single SDK instance via a context manager and reuse it across the application.
from leonardo_ai_sdk import LeonardoAiSDK
def main():
with LeonardoAiSDK(
bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as las_client:
# Rest of application here...
# Or when using async:
async def amain():
async with LeonardoAiSDK(
bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as las_client:
# Rest of application here...
Debugging
You can setup your SDK to emit debug logs for SDK requests and responses.
You can pass your own logger class directly into your SDK.
from leonardo_ai_sdk import LeonardoAiSDK
import logging
logging.basicConfig(level=logging.DEBUG)
s = LeonardoAiSDK(debug_logger=logging.getLogger("leonardo_ai_sdk"))
Maturity
This SDK is in beta, and there may be breaking changes between versions without a major version update. Therefore, we recommend pinning usage to a specific package version. This way, you can install the same version each time without breaking changes unless you are intentionally looking for the latest version.
Contributions
While we value open-source contributions to this SDK, this library is generated programmatically. Feel free to open a PR or a Github issue as a proof of concept and we'll do our best to include it in a future release !
SDK Created by Speakeasy
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file leonardo_ai_sdk-7.0.0.tar.gz.
File metadata
- Download URL: leonardo_ai_sdk-7.0.0.tar.gz
- Upload date:
- Size: 103.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/2.2.1 CPython/3.10.19 Linux/6.8.0-1044-azure
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ab3857ce7dceb4d0aad8c13d14a20b95ad13f0c0d97a81922be74413a57b5130
|
|
| MD5 |
85250a1564deb723a6eae3559ed99c53
|
|
| BLAKE2b-256 |
5a539ed3c5e96b23f5a4d01dd2247dbd356bace7bf9fb17d8cb9f086528a51c2
|
File details
Details for the file leonardo_ai_sdk-7.0.0-py3-none-any.whl.
File metadata
- Download URL: leonardo_ai_sdk-7.0.0-py3-none-any.whl
- Upload date:
- Size: 206.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/2.2.1 CPython/3.10.19 Linux/6.8.0-1044-azure
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6e6cc5968d1cbeae499d15ec81036bce18d35d4e7bac6b48dd2a158a262e71ef
|
|
| MD5 |
2e41ea489573da576d04fad90d2ba67e
|
|
| BLAKE2b-256 |
f4619034b0e370fb9948eb15f9f2ae330b5feb6d5a3926b78d49a506cd111651
|
