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Quickstart

In this tutorial, you'll learn how to upload your first data table and train your first engine.

Using an agent? Point them to this URL to set up Shaped for the first time.

Install the CLI​

The command-line interface is the fastest way to update your config in Shaped:

pip install shaped

Having trouble installing the CLI? Common errors

The most common issue is with the python version of your local environment.

Create and activate a Python 3.11 environment:

python3.11 -m venv .venv
# or
conda create --name myenv python=3.11
# or
uv venv myenv --python=3.11

Initialize the client with your API key​

Add your API key to authenticate into your account. If you don't have an API key yet, see Get your API key.

shaped init --api-key <YOUR_API_KEY>

Download sample data and engine config​

To start quickly, use our sample data based on movielens to build a semantic search model.

Download the sample data and engine config from S3:

curl -L \
  -O "https://shaped-onboarding-demo-datasets.s3.us-east-2.amazonaws.com/movielens/movielens_items.jsonl" \
  -O "https://shaped-onboarding-demo-datasets.s3.us-east-2.amazonaws.com/movielens/movielens_semantic_search.yaml"

Upload your table​

Upload the table that you downloaded locally:

shaped create-table-from-uri --name movielens_items --path movielens_items.jsonl --type jsonl

Create your engine​

Every relevance engine is configured with YAML. Upload the config in movielens_semantic_search.yaml using the CLI to create a semantic search engine:

shaped create-engine --file movielens_semantic_search.yaml

Full engine config

version: v2
name: movielens_semantic_search
data:
  item_table:
    name: movielens_items
    type: table
index:
  lexical_search: # enables BM25 lexical search on item fields
    item_fields:
      - movie_title
      - description
      - cast
      - genres
      - writers
      - directors
      - interests
  embeddings:
    - name: content_embedding # enables vector search
      encoder:
        type: hugging_face
        model_name: sentence-transformers/all-MiniLM-L6-v2
        batch_size: 256
        item_fields:
          - movie_title
          - description
          - cast
          - genres
          - writers
          - directors
          - interests

Once your engine is up and running, you’re ready to integrate it into your application. Read the Queries guide to learn how to get search results using your engine.