Upload app.py

app.py

@@ -1,17 +1,15 @@
 import pandas as pd
-import os
-import pickle
 from sentence_transformers import SentenceTransformer, util
 import streamlit as st
-import io
-import torch
+from st_aggrid import AgGrid, GridOptionsBuilder, JsCode
+from cpu_unpickler import cpu_unpickler
+st.set_page_config(layout='wide')
 
 @st.cache(allow_output_mutation=True)
 def load_model():
-    return SentenceTransformer('minilm_sbert')
+    return SentenceTransformer('all-MiniLM-L6-v2')
 
 def find_top_similar(sentence, corpus_sentences, corpus_embeddings):
-
     # preprocess query
     model = load_model()
     query_embeddings = model.encode(sentence, convert_to_tensor=True) # encode to tensor
@@ -49,16 +47,6 @@ def get_result(df, query, corpus_sentences, corpus_embeddings):
     result.drop_duplicates(inplace=True)
     return result
 
-class cpu_unpickler(pickle.Unpickler):
-    """
-    Overrides the default behavior of the `Unpickler` class to load
-    a `torch.storage` object from abyte string
-    """
-    def find_class(self, module, name):
-        if module == 'torch.storage' and name == '_load_from_bytes':
-            return lambda b: torch.load(io.BytesIO(b), map_location='cpu')
-        return super().find_class(module, name)
-
 @st.cache(allow_output_mutation=True)
 def load_embedding():
     """Loads the embeddings from the pickle file"""
@@ -74,7 +62,6 @@ def main():
     sheet_id = '1KeuPPVw9gueNmMrQXk1uGFlY9H1vvhErMLiX_ZVRv_Y'
     sheet_name = 'Form Response 3'.replace(' ', '%20')
     url = f'https://docs.google.com/spreadsheets/d/{sheet_id}/gviz/tq?tqx=out:csv&sheet={sheet_name}'
-    print(url)
     df = pd.read_csv(url)
     df  = df.iloc[: , :7]
 
@@ -87,10 +74,43 @@ def main():
     submitted = st.button('Submit')
 
     if submitted:
+        st.info(f'Showing results for { job_title}')
         result = get_result(df, job_title, corpus_sentences, corpus_embeddings)
         result.reset_index(drop=True, inplace=True)
         result.index += 1
-        st.table(result)
+
+        st.download_button(
+            "Press to Download",
+            result.to_csv().encode('utf-8'),
+            "result.csv",
+            "text/csv",
+            key='download-csv'
+        )
+
+        gb = GridOptionsBuilder.from_dataframe(result)
+        gb.configure_pagination(paginationAutoPageSize=True) # Add pagination
+        # gb.configure_side_bar() #Add a sidebar
+        # gb.configure_selection('multiple', use_checkbox=True, groupSelectsChildren="Group checkbox select children") #Enable multi-row selection
+
+        gb.configure_column("LinkedIn Link",
+                            headerName="LinkedIn Link",
+                            # cellRenderer=JsCode('''function(params) {return '<a href=params.value + '" target="_blank">'+ params.value+'</a>'}'''),
+                            cellRenderer=JsCode('''function(params) {return `<a href=${params.value} target="_blank">${params.value}</a>`}'''),
+                            width=300)
+
+        gridOptions = gb.build()
+
+        grid_response = AgGrid(
+            dataframe=result,
+            gridOptions=gridOptions,
+            height=1100,
+            fit_columns_on_grid_load=True,
+            data_return_mode='AS_INPUT',
+            update_mode='VALUE_CHANGED',
+            theme='light',
+            enable_enterprise_modules=True,
+            allow_unsafe_jscode=True,
+        )
 
 if __name__ == '__main__':
     main()