Quickstart

Install Wyvern

pip install wyvern-ai

poetry add wyvern-ai

This will also install the wyvern CLI

Create Wyvern Application

Once Wyvern is installed, run this command to initialize your Wyvern project:

wyvern init my-project
cd my-project

Now that the wyvern init has set up your initial repository, you should see the following file structure in the my-project repository:

├── pipelines
│   ├── __init__.py
│   ├── main.py
│   ├── product_ranking
│   │   ├── __init__.py
│   │   ├── models.py
│   │   ├── ranking_pipline.py
│   │   ├── realtime_features.py
│   │   ├── schemas.py
├── feature-store-python
│   ├── features
│   │   ├── feature_store.yaml
│   │   ├── features.py
│   │   ├── main.py
├── .env
└── .gitignore

The generated template code is an ML pipeline example for ranking products.

Run Wyvern Application

Pre-requisite

Redis service

Wyvern uses redis as its index and online feature store. By default, Wyvern connects to the localhost:6379 Your can run this command to install and spin up local redis

wyvern redis

Run the wyvern service

wyvern run

Now your wyvern service runs on http://0.0.0.0:5001 and the default ranking API schema could be found at http://0.0.0.0:5001/redoc#operation/MyRankingPipeline_api_v1_ranking_post.

Test ranking request

Assuming you have 24 products and you would like to rank them. Here’s a curl request:

curl --location 'http://0.0.0.0:5001/api/v1/ranking' \
--header 'Content-Type: application/json' \
--data '{
    "request_id": "test_request_id",
    "query": {"query": "candle"},
    "candidates": [
        {"product_id": "p1"},
        {"product_id": "p2"},
        {"product_id": "p3"},
        {"product_id": "p4"},
        {"product_id": "p5"},
        {"product_id": "p6"},
        {"product_id": "p7"},
        {"product_id": "p8"},
        {"product_id": "p9"},
        {"product_id": "p10"},
        {"product_id": "p11"},
        {"product_id": "p12"},
        {"product_id": "p13"},
        {"product_id": "p14"},
        {"product_id": "p15"},
        {"product_id": "p16"},
        {"product_id": "p17"},
        {"product_id": "p18"},
        {"product_id": "p19"},
        {"product_id": "p20"},
        {"product_id": "p21"},
        {"product_id": "p22"},
        {"product_id": "p23"},
        {"product_id": "p24"}
    ],
    "user_page_size": 8,
    "user_page": 0,
    "candidate_page_size": 24,
    "candidate_page": 0
}'

The request sends 24 products to Wyvern. Wyvern ranks these products and returns the 8 products (in descending order) to show on the first page ("user_page": 0). You should see a response like the following with the products being ordered descendingly by their ranking score.

{
  "ranked_candidates": [
    {
      "candidate_id": "p9",
      "ranked_score": 43.13991415724884
    },
    {
      "candidate_id": "p18",
      "ranked_score": 42.314880208313376
    },
    {
      "candidate_id": "p17",
      "ranked_score": 41.62010469362527
    },
    {
      "candidate_id": "p3",
      "ranked_score": 40.48391586690772
    },
    {
      "candidate_id": "p19",
      "ranked_score": 39.82504624652922
    },
    {
      "candidate_id": "p24",
      "ranked_score": 39.10042317690844
    },
    {
      "candidate_id": "p11",
      "ranked_score": 38.670359237541945
    },
    {
      "candidate_id": "p21",
      "ranked_score": 37.27313489135458
    }
  ]
}

Congratulations on making your first Wyvern request!

Head over to the Wyvern Application to learn more about Wyvern

Overview

Get Started

Wyvern ML Pipeline

Wyvern Feature Engineering

Advanced

Install Wyvern

Create Wyvern Application

Run Wyvern Application

Pre-requisite

Run the wyvern service

Test ranking request

More

​Install Wyvern

​Create Wyvern Application

​Run Wyvern Application

​Pre-requisite

​Run the wyvern service

​Test ranking request

​More

Install Wyvern

Create Wyvern Application

Run Wyvern Application

Pre-requisite

Run the wyvern service

Test ranking request

More