Merge pull request #165 from Snowflake-Labs/jsummer/add-dbt-model-ins…

…tructions

Jsummer/add dbt model instructions

admin_apps/partner/cortex.py

@@ -3,7 +3,10 @@
 import pandas as pd
 import streamlit as st
 
-from semantic_model_generator.data_processing.proto_utils import proto_to_dict
+from semantic_model_generator.data_processing.proto_utils import (
+    proto_to_dict,
+    yaml_to_semantic_model,
+)
 
 
 class CortexDimension:
@@ -134,7 +137,9 @@ def create_comparison_df(self) -> pd.DataFrame:
 
     @staticmethod
     def create_cortex_table_list() -> None:
-        cortex_semantic = proto_to_dict(st.session_state["semantic_model"])
+        cortex_semantic = proto_to_dict(
+            yaml_to_semantic_model(st.session_state["last_saved_yaml"])
+        )
         # Need to replace table details in current entire yaml
         st.session_state["current_yaml_as_dict"] = cortex_semantic
         tables = []

admin_apps/partner/dbt.py

@@ -8,8 +8,20 @@
 
 # Partner semantic support instructions
 DBT_IMAGE = "admin_apps/images/dbt-signature_tm_black.png"
-DBT_INSTRUCTIONS = """
-We extract metadata from your **DBT** semantic yaml file(s) and merge it with a generated Cortex Analyst semantic file.
+DBT_MODEL_INSTRUCTIONS = """
+### [SQL Model](https://docs.getdbt.com/docs/build/sql-models)
+
+Materialize your SQL model(s) as Snowflake table(s) and generate a Cortex Analyst semantic file for them directly.
+> Steps:
+> 1) Update dbt model(s) to be [materialized](https://docs.getdbt.com/docs/build/materializations) in Snowflake.
+> 2) Update dbt model(s) to [persist docs](https://docs.getdbt.com/reference/resource-configs/persist_docs) to capture table/column descriptions.
+> 3) Run dbt model(s) to materialize in Snowflake.
+> 4) Select **🛠 Create a new semantic model** on the homepage and select the materialized Snowflake table(s).
+"""
+DBT_SEMANTIC_INSTRUCTIONS = """
+### [Semantic Model](https://docs.getdbt.com/docs/build/semantic-models)
+
+We extract metadata from your dbt semantic yaml file(s) and merge it with a generated Cortex Analyst semantic file.
 
 **Note**: The DBT semantic layer must be sourced from tables/views in Snowflake.
 > Steps:

admin_apps/partner/looker.py

@@ -42,7 +42,7 @@
 # Partner semantic support instructions
 LOOKER_IMAGE = "admin_apps/images/looker.png"
 LOOKER_INSTRUCTIONS = """
-We materialize your Explore dataset in Looker as Snowflake table(s) and generate a Cortex Analyst semantic file.
+We materialize your [Explore](https://cloud.google.com/looker/docs/reference/param-explore-explore) dataset in Looker as Snowflake table(s) and generate a Cortex Analyst semantic file.
 Metadata from your Explore fields can be merged with the generated Cortex Analyst semantic file.
 
 **Note**: Views referenced in the Looker Explores must be tables/views in Snowflake. Looker SDK credentials are required.

admin_apps/partner/partner_utils.py

@@ -1,5 +1,6 @@
 import json
 import time
+from enum import Enum
 from typing import Any
 
 import numpy as np
@@ -17,20 +18,32 @@
 from semantic_model_generator.data_processing.proto_utils import yaml_to_semantic_model
 
 
+class PartnerTool(Enum):
+    DBT_SQL_MODEL = "dbt - SQL Model"
+    DBT_SEMANTIC_MODEL = "dbt - Semantic Model"
+    LOOKER_EXPLORE = "Looker - Explore"
+
+
 def set_partner_instructions() -> None:
     """
     Sets instructions and partner logo in session_state based on selected partner.
     Returns: None
     """
 
     if st.session_state.get("partner_tool", None):
-        if st.session_state["partner_tool"] == "dbt":
-            from admin_apps.partner.dbt import DBT_IMAGE, DBT_INSTRUCTIONS
+        if st.session_state["partner_tool"] == PartnerTool.DBT_SQL_MODEL.value:
+            from admin_apps.partner.dbt import DBT_IMAGE, DBT_MODEL_INSTRUCTIONS
+
+            instructions = DBT_MODEL_INSTRUCTIONS
+            image = DBT_IMAGE
+            image_size = (72, 32)
+        elif st.session_state["partner_tool"] == PartnerTool.DBT_SEMANTIC_MODEL.value:
+            from admin_apps.partner.dbt import DBT_IMAGE, DBT_SEMANTIC_INSTRUCTIONS
 
-            instructions = DBT_INSTRUCTIONS
+            instructions = DBT_SEMANTIC_INSTRUCTIONS
             image = DBT_IMAGE
             image_size = (72, 32)
-        elif st.session_state["partner_tool"] == "looker":
+        elif st.session_state["partner_tool"] == PartnerTool.LOOKER_EXPLORE.value:
             from admin_apps.partner.looker import LOOKER_IMAGE, LOOKER_INSTRUCTIONS
 
             instructions = LOOKER_INSTRUCTIONS
@@ -47,7 +60,7 @@ def configure_partner_semantic() -> None:
     Returns: None
     """
 
-    partners = [None, "dbt", "looker"]
+    partners = [tool.value for tool in PartnerTool]
 
     st.selectbox(
         "Select the partner tool",
@@ -58,7 +71,7 @@ def configure_partner_semantic() -> None:
     )
     if st.session_state.get("partner_tool", None):
         with st.expander(
-            f"{st.session_state.get('partner_tool', '').title()} Instructions",
+            "Instructions",
             expanded=True,
         ):
             render_image(
@@ -71,12 +84,14 @@ def configure_partner_semantic() -> None:
     if st.session_state.get("partner_tool", None):
         st.session_state["selected_partner"] = st.session_state["partner_tool"]
 
-    if st.session_state["partner_tool"] == "dbt":
+    if st.session_state["partner_tool"] == PartnerTool.DBT_SEMANTIC_MODEL.value:
         upload_dbt_semantic()
-    if st.session_state["partner_tool"] == "looker":
+    if st.session_state["partner_tool"] == PartnerTool.LOOKER_EXPLORE.value:
         from admin_apps.partner.looker import set_looker_semantic
 
         set_looker_semantic()
+    if st.session_state["partner_tool"] == PartnerTool.DBT_SQL_MODEL.value:
+        st.session_state["partner_setup"] = False
 
 
 class PartnerCompareRow:
@@ -231,9 +246,11 @@ def integrate_partner_semantics() -> None:
     """
 
     st.write(
-        "Specify how to merge semantic metadata from partner tools with Cortex Analyst's semantic model."
+        "Specify how to merge semantic metadata from your selected partner tool with Cortex Analyst's semantic model."
     )
 
+    st.write(f"Partner: **{st.session_state.get('selected_partner', None)}**")
+
     COMPARE_SEMANTICS_HELP = """Which semantic file should be checked first for necessary metadata.
     Where metadata is missing, the other semantic file will be checked."""
 
@@ -253,11 +270,17 @@ def integrate_partner_semantics() -> None:
         # Execute pre-processing behind the scenes based on vendor tool
         CortexSemanticTable.create_cortex_table_list()
 
-        if st.session_state.get("selected_partner", None) == "looker":
+        if (
+            st.session_state.get("selected_partner", None)
+            == PartnerTool.LOOKER_EXPLORE.value
+        ):
             from admin_apps.partner.looker import LookerSemanticTable
 
             LookerSemanticTable.create_cortex_table_list()
-        elif st.session_state.get("selected_partner", None) == "dbt":
+        elif (
+            st.session_state.get("selected_partner", None)
+            == PartnerTool.DBT_SEMANTIC_MODEL.value
+        ):
             pass
         else:
             st.error("Selected partner tool not available.")
@@ -303,13 +326,19 @@ def integrate_partner_semantics() -> None:
                 semantic_cortex_tbl
             )
 
-            if st.session_state.get("selected_partner", None) == "looker":
+            if (
+                st.session_state.get("selected_partner", None)
+                == PartnerTool.LOOKER_EXPLORE.value
+            ):
                 from admin_apps.partner.looker import LookerSemanticTable
 
                 partner_fields_df = LookerSemanticTable.retrieve_df_by_name(
                     semantic_partner_tbl
                 )
-            if st.session_state.get("selected_partner", None) == "dbt":
+            if (
+                st.session_state.get("selected_partner", None)
+                == PartnerTool.DBT_SEMANTIC_MODEL.value
+            ):
                 partner_fields_df = DBTSemanticModel.retrieve_df_by_name(
                     semantic_partner_tbl
                 )