Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import linktransformer as lt
+
+# Function to convert DataFrame to CSV for download
+def convert_df_to_csv(df):
+    return df.to_csv().encode('utf-8')
+
+st.title('DataFrame Merger using LinkTransformer')
+
+# Function to load DataFrame
+def load_dataframe(upload, path):
+    if upload is not None:
+        return pd.read_csv(upload)
+    elif path != "":
+        return pd.read_csv(path)
+    else:
+        return None
+
+# Options for DataFrame 1
+df1_upload = st.file_uploader("Upload DataFrame 1 (CSV)", type=['csv'], key='df1_upload')
+df1_path = st.text_input("...or enter path for DataFrame 1 (CSV)", key='df1_path')
+
+# Options for DataFrame 2
+df2_upload = st.file_uploader("Upload DataFrame 2 (CSV)", type=['csv'], key='df2_upload')
+df2_path = st.text_input("...or enter path for DataFrame 2 (CSV)", key='df2_path')
+
+# Load and display the DataFrames
+df1 = load_dataframe(df1_upload, df1_path)
+df2 = load_dataframe(df2_upload, df2_path)
+
+if df1 is not None:
+    st.write("DataFrame 1 Preview:")
+    st.dataframe(df1.head())
+
+if df2 is not None:
+    st.write("DataFrame 2 Preview:")
+    st.dataframe(df2.head())
+
+
+# Model selection
+model_path = st.text_input("Model path (HuggingFace or local)", value="all-MiniLM-L6-v2")
+
+# Checkbox for columns to match on
+if not df1.empty and not df2.empty:
+    columns_df1 = df1.columns.tolist()
+    columns_df2 = df2.columns.tolist()
+    
+    selected_columns_df1 = st.multiselect("Select columns from DataFrame 1 to match on:", columns_df1, default=columns_df1[0])
+    selected_columns_df2 = st.multiselect("Select columns from DataFrame 2 to match on:", columns_df2, default=columns_df2[0])
+    
+    # Perform merge
+    if st.button("Merge DataFrames"):
+        model=lt.LinkTransformer(model_path)
+        df_lm_matched = lt.merge(df2, df1, merge_type='1:m', on=None, model=model, left_on=selected_columns_df1, right_on=selected_columns_df2)
+        st.write("Merged DataFrame Preview:")
+        st.dataframe(df_lm_matched.head())
+
+        # Download button for merged DataFrame
+        csv = convert_df_to_csv(df_lm_matched)
+        st.download_button(
+            label="Download merged DataFrame as CSV",
+            data=csv,
+            file_name='merged_dataframe.csv',
+            mime='text/csv',
+        )