this project is built using IBM watson machine learning
To get a local copy up and running follow these simple example steps.
- python
- BAM account
- BAM_API_KEY
- BAM_URL
Below is an example of how you can instruct your audience on installing and setting up your app. This template doesn't rely on any external dependencies or services.
- Get a BAM API Key at https://ibmmid.com
- Clone the repo
git clone <project gti>
- Install python packages
pip install -r requirement.txt
- Create a new file
.env
from thedefault.env
example and enter your BAM_API_KEY in the top line
in order to run the API service
uvicorn ols:app --reload
To send a request to the server you can use the following curl command:
curl -X 'POST' 'http://127.0.0.1:8000/ols' -H2 'accept: application/json' -H 'Content-Type: application/json' -d '{"query": "write a deployment yaml for the mongodb image"}'
- [ ]
See the open issues for a full list of proposed features (and known issues).
Published under the Apache 2.0 License