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Upload app.py
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app.py
CHANGED
@@ -171,6 +171,8 @@ else:
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st.success('Running in Production mode!', icon="✅")
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st.subheader("Tell us about your Databricks and Labelbox environments", divider='grey')
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title = st.text_input('Enter Databricks Domain (e.g., <instance>.<cloud>.databricks.com)', '')
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databricks_api_key = st.text_input('Databricks API Key', type='password')
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labelbox_api_key = st.text_input('Labelbox API Key', type='password')
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@@ -477,15 +479,21 @@ if new_dataset_name or selected_dataset_name:
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# Schema Map
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row_data_input = selected_row_data
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global_key_input = selected_global_key
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schema_map_dict = {'row_data': row_data_input}
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if global_key_input:
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schema_map_dict['global_key'] = global_key_input
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#
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data = {
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"mode": mode,
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"databricks_instance": databricks_instance,
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"databricks_api_key": databricks_api_key,
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@@ -496,7 +504,7 @@ if new_dataset_name or selected_dataset_name:
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"frequency": frequency,
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"new_cluster": 0,
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"cluster_id": cluster_id,
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"schema_map":
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}
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@@ -504,7 +512,7 @@ if new_dataset_name or selected_dataset_name:
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# Ensure all fields are filled out
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required_fields = [
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mode, databricks_instance, databricks_api_key, new_dataset, dataset_id,
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table_path, labelbox_api_key, frequency, cluster_id,
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]
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st.success('Running in Production mode!', icon="✅")
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st.subheader("Tell us about your Databricks and Labelbox environments", divider='grey')
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cloud = "GCP"
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#cloud = st.selectbox('Which cloud environment does your Databricks Workspace run in?', ['AWS', 'Azure', 'GCP'], index=None)
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title = st.text_input('Enter Databricks Domain (e.g., <instance>.<cloud>.databricks.com)', '')
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databricks_api_key = st.text_input('Databricks API Key', type='password')
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labelbox_api_key = st.text_input('Labelbox API Key', type='password')
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# Schema Map
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row_data_input = selected_row_data
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global_key_input = selected_global_key
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# Create the initial dictionary
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schema_map_dict = {'row_data': row_data_input}
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if global_key_input:
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schema_map_dict['global_key'] = global_key_input
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# Swap keys and values
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reversed_schema_map_dict = {v: k for k, v in schema_map_dict.items()}
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# Convert the reversed dictionary to a stringified JSON
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reversed_schema_map_str = json.dumps(reversed_schema_map_dict)
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data = {
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"cloud": cloud,
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"mode": mode,
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"databricks_instance": databricks_instance,
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"databricks_api_key": databricks_api_key,
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"frequency": frequency,
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"new_cluster": 0,
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"cluster_id": cluster_id,
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"schema_map": reversed_schema_map_str
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}
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# Ensure all fields are filled out
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required_fields = [
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mode, databricks_instance, databricks_api_key, new_dataset, dataset_id,
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table_path, labelbox_api_key, frequency, cluster_id, reversed_schema_map_str
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]
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