The UDF retrieve_sl_metadata() and the code in app.py is not aligned.

[M-SOLITA]

The UDF and the code in app.py is not aligned. retrieve_sl_metadata() function does not take any input variables.

But is used as: sql = f"select retrieve_sl_metadata('{host}', {environment_id}, '{token}')" in app.py

UDF:

create or replace function retrieve_sl_metadata()
    returns object
    language python
    runtime_version = 3.9
    handler = 'main'
    external_access_integrations = (dbt_cloud_semantic_layer_integration)
    packages = ('requests')
    secrets = ('cred' = dbt_cloud_service_token)
as
$$
from typing import Dict
import _snowflake
import requests

query = """
query GetMetrics($environmentId: BigInt!) {
  metrics(environmentId: $environmentId) {
    description
    name
    queryableGranularities
    type
    dimensions {
      description
      name
      type
    }
  }
}

in app.py```

def prepare_app():

host = st.session_state.get("host")
environment_id = st.session_state.get("environment_id")
token = st.session_state.get("token")
if any([is_none(i) for i in [host, environment_id]]):
    st.error("Host and environment ID are required inputs")
    st.stop()

sql = f"select retrieve_sl_metadata('{host}', {environment_id}, '{token}')"
with st.spinner("Retrieving metadata..."):
    response = session.sql(sql).collect()
    data = json.loads(response[0][0])
    try:
        metrics = data["data"]["metrics"]
    except TypeError:

        # `data` is None and there may be an error
        try:
            error = data["errors"][0]["message"]
            st.error(error)
        except (KeyError, TypeError):
            st.warning(
                "No metrics returned.  Ensure your project has metrics defined "
                "and a production job has been run successfully."
            )
    else:
        st.session_state.metric_dict = {m["name"]: m for m in metrics}
        st.session_state.dimension_dict = {
            dim["name"]: dim for metric in metrics for dim in metric["dimensions"]
        }
        st.session_state.metrics = ", ".join(list(st.session_state.metric_dict.keys()))
        st.session_state.dimensions = ", ".join(list(st.session_state.dimension_dict.keys()))
        for metric in st.session_state.metric_dict:
            st.session_state.metric_dict[metric]["dimensions"] = [
                d["name"]
                for d in st.session_state.metric_dict[metric]["dimensions"]
            ]
        if not st.session_state.metric_dict:
            # Query worked, but nothing returned
            st.warning(
                "No Metrics returned!  Ensure your project has metrics defined "
                "and a production job has been run successfully."
            )
        else:
            st.success("Success!  Start asking questions!")
            st.experimental_rerun()

[dpguthrie]

Thanks for opening this up @M-SOLITA - I'll make a quick fix.