Python client for the Aleph Alpha API.
import os
from aleph_alpha_client import Client, CompletionRequest, Prompt
client = Client(token=os.getenv("AA_TOKEN"))
request = CompletionRequest(
prompt=Prompt.from_text("Provide a short description of AI:"),
maximum_tokens=64,
)
response = client.complete(request, model="luminous-extended")
print(response.completions[0].completion)
import os
from aleph_alpha_client import AsyncClient, CompletionRequest, Prompt
# Can enter context manager within an async function
async with AsyncClient(token=os.environ["AA_TOKEN"]) as client:
request = CompletionRequest(
prompt=Prompt.from_text("Provide a short description of AI:"),
maximum_tokens=64,
)
response = client.complete_with_streaming(request, model="luminous-base")
async for stream_item in response:
print(stream_item)
This table contains interactive code examples, further exercises can be found in the examples repository.
Template | Description | Internal Link | Colab Link |
---|---|---|---|
1 | Calling the API | Template 1 | |
2 | Simple completion | Template 2 | |
3 | Simple search | Template 3 | |
4 | Symmetric and Asymmetric Search | Template 4 | |
5 | Hidden Embeddings | Template 5 | |
6 | Task-specific Endpoints | Template 6 |
The latest stable version is deployed to PyPi so you can install this package via pip.
pip install aleph-alpha-client
Get started using the client by first creating an account. Afterwards head over to your profile to create an API token. Read more about how you can manage your API tokens here.
For local development, start by creating a Python virtual environment as follows:
python3 -m venv venv
. ./venv/bin/activate
Next, install the test and dev dependencies:
poetry install --extras "dev"
Now you should be able to ...
- run all the tests using
pytest
or,pytest -k <test_name>
to run a specific test - typecheck the code and tests using
mypy aleph_alpha_client
resp.mypy tests
- format the code using
black .