1.2.0

app.py

@@ -5,7 +5,7 @@ from widgets import *
 # [![github](https://img.kookapp.cn/assets/2022-09/1w4G0FIWGK00w00w.png)](https://github.com/Mondkuchen/idp_LiteratureResearch_Tool)
 
 # sidebar content
-platforms, number_papers,start_year,end_year, clustering_params = render_sidebar()
+platforms, number_papers, start_year, end_year, hyperparams = render_sidebar()
 
 # body head
 with st.form("my_form",clear_on_submit=False):
@@ -25,7 +25,7 @@ with st.form("my_form",clear_on_submit=False):
 
 if submitted:
     # body
-    render_body(platforms, number_papers, 5, query_input, show_preview,start_year,end_year, clustering_params)
+    render_body(platforms, number_papers, 5, query_input, show_preview, start_year, end_year, hyperparams)
     # '''
     # bar = (
     #     Bar()

setup.py

@@ -1,4 +1,5 @@
 from setuptools import setup, find_packages
+from widgets.sidebar import APP_VERSION
 
 with open("README.md", "r") as readme_file:
     readme = readme_file.read()
@@ -21,7 +22,7 @@ requirements = [
 
 setup(
     name="LiteratureResearchTool",
-    version="1.1.0",
+    version=f'{APP_VERSION[1:]}',
     author="Tao Xiang",
     author_email="tao.xiang@tum.de",
     description="A tool for literature research and analysis",

widgets/body.py

@@ -55,7 +55,7 @@ We have found following papers for you! (displaying 5 papers for each literature
 
         paperInGeneral.markdown(paperInGeneral_md)
 
-def render_body(platforms, num_papers, num_papers_preview, query_input, show_preview:bool,start_year,end_year, clustering_params: dict):
+def render_body(platforms, num_papers, num_papers_preview, query_input, show_preview:bool, start_year, end_year, hyperparams: dict):
 
     tmp = st.empty()
     if query_input != '':
@@ -68,18 +68,18 @@ def render_body(platforms, num_papers, num_papers_preview, query_input, show_pre
 
         # lrt results
         ## baseline
-        if clustering_params['dimension_reduction'] == 'none':
+        if hyperparams['dimension_reduction'] == 'none' and hyperparams['model_cpt'] == 'keyphrase-transformer':
             model = baseline_lrt
         else:
             config = Configuration(
                 plm= '''all-mpnet-base-v2''',
-                dimension_reduction= clustering_params['dimension_reduction'],
+                dimension_reduction= hyperparams['dimension_reduction'],
                 clustering= 'kmeans-euclidean',
-                keywords_extraction='keyphrase-transformer'
+                keywords_extraction=hyperparams['model_cpt']
             )
             model = LiteratureResearchTool(config)
 
-        generator =  model(query_input,num_papers,start_year,end_year,max_k=clustering_params['max_k'],platforms=platforms)
+        generator =  model(query_input, num_papers, start_year, end_year, max_k=hyperparams['max_k'], platforms=platforms)
         for i,plat in enumerate(platforms):
             clusters, articles = next(generator)
             st.markdown(f'''# {i+1} {plat} Results''')

widgets/sidebar.py

@@ -1,6 +1,9 @@
 import streamlit as st
 import datetime
 # from .utils import PACKAGE_ROOT
+from lrt.utils.functions import template
+
+APP_VERSION = 'v1.2.0'
 
 def render_sidebar():
     icons = f'''
@@ -20,7 +23,7 @@ def render_sidebar():
 
 
     <code>
-    v1.1.0
+    {APP_VERSION}
     </code>
 
 
@@ -65,21 +68,25 @@ def render_sidebar():
 
 
     with st.sidebar:
-        st.markdown('## Adjust clustering hyperparameters')
-        with st.expander('Clustering Hyperparameters'):
+        st.markdown('## Adjust hyperparameters')
+        with st.expander('Clustering Options'):
             dr = st.selectbox('1) Dimension Reduction', options=['none', 'pca'], index=0)
             tmp = min(number_papers,15)
             max_k = st.slider('2) Max number of clusters', 2,tmp , tmp//2)
 
+        with st.expander('Keyphrases Generation Options'):
+            model_cpt = st.selectbox(label='Model checkpoint', options=template.keywords_extraction.keys(),index=0)
+
 
         st.markdown('---')
         st.markdown(icons,unsafe_allow_html=True)
-        st.markdown('''<center>copyright@2022</center>''',unsafe_allow_html=True)
+        st.markdown('''<center>Copyright © 2022 by Tao Xiang</center>''',unsafe_allow_html=True)
 
     # st.sidebar.markdown('## Choose the number of clusters')
     # k = st.sidebar.slider('number',1,10,3)
     
     return platforms, number_papers, start_year, end_year, dict(
         dimension_reduction= dr,
-        max_k = max_k
+        max_k = max_k,
+        model_cpt = model_cpt
     )