Create app.py

app.py

@@ -0,0 +1,61 @@
+import streamlit as st
+from streamlit.logger import get_logger
+from transformers import  pipeline
+import datasets
+import pandas as pd
+from huggingface_hub import login
+
+LOGGER = get_logger(__name__)
+model = "sivan22/halacha-siman-seif-classifier-new"
+
+
+login('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')
+ds = datasets.load_dataset('sivan22/orach-chaim',token=True)
+df = ds['train'].to_pandas()
+def clean(s)->str:
+    return s.replace(" ","")
+df['seif']= df['seif'].apply(clean)
+
+
+
+def get_predicts_local(input)->str:
+    classifier = pipeline("text-classification",model=model,top_k=None)
+    predicts = classifier(input)
+    return predicts
+
+def get_predicts_online(input)->str:
+    import requests
+    API_URL = "https://api-inference.huggingface.co/models/" + model
+    headers = {"Authorization": f"Bearer {'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'}"}
+    def query(input_text):
+        response = requests.post(API_URL, headers=headers, json='{{inputs:' +input_text+'}{wait_for_model:true}}')        
+        return response.json()
+    predicts = query(input)
+    return predicts
+
+def run():
+    st.set_page_config(
+        page_title="Halacha classification",
+        page_icon="",
+    )
+
+    st.write("# חיפוש בשולחן ערוך")
+    use_local = st.checkbox("חיפוש לא מקוון")
+    user_input = st.text_input('כתוב כאן את שאלתך', placeholder='כמה נרות מדליקים בחנוכה')
+    if st.button('חפש') and user_input!="":       
+        get_predicts = get_predicts_local if use_local else get_predicts_online
+        #print(get_predicts(user_input)[0][0:5])
+        for prediction in get_predicts(user_input)[0][:5]:
+            rows = df[((df["bookname"] == " שלחן ערוך - אורח חיים ") |
+                        (df["bookname"] ==" משנה ברורה")) &
+                      (df["siman"] == prediction['label'].split(' ')[0])&
+                      (df["seif"] == prediction['label'].split(' ')[1]) ]
+            rows.sort_values(["bookname"],ascending=False, inplace=True) 
+         
+            print(prediction['label'].split(' '))
+            st.write('סימן ' + str(prediction['label']), rows[['text','sek','seif','siman','bookname']])
+
+    
+
+if __name__ == "__main__":
+    run()