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jskinner215
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7ba8571
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Parent(s):
d934c26
Update ui_utils.py
Browse files- ui_utils.py +10 -30
ui_utils.py
CHANGED
@@ -1,6 +1,11 @@
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import streamlit as st
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def display_initial_buttons():
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if st.button("Upload new CSV"):
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st.session_state.upload_flow = True
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st.session_state.query_flow = False
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@@ -9,19 +14,17 @@ def display_initial_buttons():
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st.session_state.query_flow = True
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st.session_state.upload_flow = False
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def display_class_dropdown(client):
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if st.session_state.upload_flow:
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existing_classes = [cls["class"] for cls in client.schema.get()["classes"]]
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class_options = existing_classes + ["New Class"]
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existing_classes = [cls["class"] for cls in client.schema.get()["classes"]]
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class_options = existing_classes + ["Query all data"]
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def handle_new_class_selection():
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if selected_class == "New Class":
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class_name = st.text_input("Enter the new class name:")
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class_description = st.text_input("Enter a description for the class:")
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@@ -30,39 +33,16 @@ def handle_new_class_selection():
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# Call function to create new class schema in Weaviate
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create_new_class_schema(class_name, class_description)
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# Display data preview for selected class
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display_data_preview(selected_class)
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if st.button("Confirm Data Selection"):
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# Set the selected class as the data source for TAPAS queries
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st.session_state.data_source = selected_class
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else:
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# Display all class schemas
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display_all_class_schemas()
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if st.button("Confirm Data Selection"):
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# Set all data as the source for TAPAS queries
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st.session_state.data_source = "all_data"
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def csv_upload_and_ingestion():
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csv_file = st.file_uploader("Upload a CSV file", type=["csv"])
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if csv_file:
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if st.button("Confirm CSV upload"):
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# Call function to ingest CSV data into Weaviate
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ingest_csv_to_weaviate(csv_file, selected_class)
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def display_query_input():
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question = st.text_input("Enter your question:")
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if question:
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if st.button("Submit Query"):
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# Call function to query TAPAS with selected data and entered question
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query_tapas_with_weaviate_data(selected_class, question)
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question = st.text_input("Enter your question:")
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if question:
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if st.button("Submit Query"):
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# Call function to query TAPAS with selected data source and entered question
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query_tapas_with_weaviate_data(st.session_state.data_source, question)
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import streamlit as st
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def display_initial_buttons():
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if "upload_flow" not in st.session_state:
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st.session_state.upload_flow = False
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if "query_flow" not in st.session_state:
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st.session_state.query_flow = False
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if st.button("Upload new CSV"):
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st.session_state.upload_flow = True
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st.session_state.query_flow = False
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st.session_state.query_flow = True
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st.session_state.upload_flow = False
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def display_class_dropdown(client):
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if st.session_state.upload_flow:
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existing_classes = [cls["class"] for cls in client.schema.get()["classes"]]
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class_options = existing_classes + ["New Class"]
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return st.selectbox("Select a class or create a new one:", class_options)
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elif st.session_state.query_flow:
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existing_classes = [cls["class"] for cls in client.schema.get()["classes"]]
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class_options = existing_classes + ["Query all data"]
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return st.selectbox("Select a class or query all data:", class_options)
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def handle_new_class_selection(selected_class):
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if selected_class == "New Class":
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class_name = st.text_input("Enter the new class name:")
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class_description = st.text_input("Enter a description for the class:")
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# Call function to create new class schema in Weaviate
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create_new_class_schema(class_name, class_description)
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def csv_upload_and_ingestion(selected_class):
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csv_file = st.file_uploader("Upload a CSV file", type=["csv"])
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if csv_file:
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if st.button("Confirm CSV upload"):
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# Call function to ingest CSV data into Weaviate
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ingest_csv_to_weaviate(csv_file, selected_class)
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def display_query_input():
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question = st.text_input("Enter your question:")
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if question:
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if st.button("Submit Query"):
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# Call function to query TAPAS with selected data and entered question
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query_tapas_with_weaviate_data(st.session_state.data_source, question)
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