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jskinner215
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Commit
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f419ec9
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Parent(s):
d6f51dc
Update ui_utils.py
Browse files- ui_utils.py +7 -5
ui_utils.py
CHANGED
@@ -1,4 +1,5 @@
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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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@@ -18,11 +19,11 @@ 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(client, selected_class):
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if selected_class == "New Class":
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@@ -31,18 +32,19 @@ def handle_new_class_selection(client, selected_class):
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if class_name and class_description:
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if st.button("Create Vector DB 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(client, 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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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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import streamlit as st
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import weaviate_utils
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def display_initial_buttons():
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if "upload_flow" not in st.session_state:
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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, key="class_selector_upload")
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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, key="class_selector_query")
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def handle_new_class_selection(client, selected_class):
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if selected_class == "New Class":
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if class_name and class_description:
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if st.button("Create Vector DB Class"):
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# Call function to create new class schema in Weaviate
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weaviate_utils.create_new_class_schema(client, class_name, class_description)
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def csv_upload_and_ingestion(client, selected_class):
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csv_file = st.file_uploader("Upload a CSV file", type=["csv"], key="csv_uploader")
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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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weaviate_utils.ingest_data_to_weaviate(client, 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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# (This function needs to be implemented)
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query_tapas_with_weaviate_data(st.session_state.data_source, question)
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