little code improvements

Rock_fact_checker.py

@@ -12,15 +12,13 @@
     entailment_html_messages,
     create_df_for_relevant_snippets,
     create_ternary_plot,
-    build_sidebar
+    build_sidebar,
 )
 from app_utils.config import RETRIEVER_TOP_K
 
 
 def main():
-
     statements = load_statements()
-
     build_sidebar()
 
     # Persistent state
@@ -120,7 +118,6 @@ def main():
         st.markdown(f"###### Most Relevant snippets:")
         df, urls = create_df_for_relevant_snippets(docs)
         st.dataframe(df)
-
         str_wiki_pages = "Wikipedia source pages: "
         for doc, url in urls.items():
             str_wiki_pages += f"[{doc}]({url}) "

app_utils/backend_utils.py

@@ -31,21 +31,19 @@ def load_statements():
 )
 def start_haystack():
     """
-    load document store, retriever, reader and create pipeline
+    load document store, retriever, entailment checker and create pipeline
     """
     shutil.copy(f"{INDEX_DIR}/faiss_document_store.db", ".")
     document_store = FAISSDocumentStore(
         faiss_index_path=f"{INDEX_DIR}/my_faiss_index.faiss",
         faiss_config_path=f"{INDEX_DIR}/my_faiss_index.json",
     )
     print(f"Index size: {document_store.get_document_count()}")
-
     retriever = EmbeddingRetriever(
         document_store=document_store,
         embedding_model=RETRIEVER_MODEL,
         model_format=RETRIEVER_MODEL_FORMAT,
     )
-
     entailment_checker = EntailmentChecker(model_name_or_path=NLI_MODEL, use_gpu=False)
 
     pipe = Pipeline()
@@ -84,8 +82,8 @@ def query(statement: str, retriever_top_k: int = 5):
             break
 
     results["agg_entailment_info"] = {
-        "contradiction": float(round(agg_con / scores, 2)),
-        "neutral": float(round(agg_neu / scores, 2)),
-        "entailment": float(round(agg_ent / scores, 2)),
+        "contradiction": round(agg_con / scores, 2),
+        "neutral": round(agg_neu / scores, 2),
+        "entailment": round(agg_ent / scores, 2),
     }
     return results

app_utils/frontend_utils.py

@@ -9,8 +9,9 @@
     "neutral": 'The knowledge base is <span style="color:darkgray">neutral</span> about your statement',
 }
 
+
 def build_sidebar():
-    sidebar="""
+    sidebar = """
     <h1 style='text-align: center'>Fact Checking 🎸 Rocks!</h1>
     <div style='text-align: center'>
     <i>Fact checking baseline combining dense retrieval and textual entailment</i>
@@ -20,6 +21,7 @@ def build_sidebar():
     """
     st.sidebar.markdown(sidebar, unsafe_allow_html=True)
 
+
 def set_state_if_absent(key, value):
     if key not in st.session_state:
         st.session_state[key] = value
@@ -33,6 +35,9 @@ def reset_results(*args):
 
 
 def create_ternary_plot(entailment_data):
+    """
+    Create a Plotly ternary plot for the given entailment dict.
+    """
     hover_text = ""
     for label, value in entailment_data.items():
         hover_text += f"{label}: {value}<br>"
@@ -83,14 +88,11 @@ def makeAxis(title, tickangle):
     }
 
 
-def highlight_cols(s):
-    coldict = {"con": "#FFA07A", "neu": "#E5E4E2", "ent": "#a9d39e"}
-    if s.name in coldict.keys():
-        return ["background-color: {}".format(coldict[s.name])] * len(s)
-    return [""] * len(s)
-
-
 def create_df_for_relevant_snippets(docs):
+    """
+    Create a dataframe that contains all relevant snippets.
+    Also returns the URLs
+    """
     rows = []
     urls = {}
     for doc in docs:
@@ -106,3 +108,10 @@ def create_df_for_relevant_snippets(docs):
         rows.append(row)
         df = pd.DataFrame(rows).style.apply(highlight_cols)
     return df, urls
+
+
+def highlight_cols(s):
+    coldict = {"con": "#FFA07A", "neu": "#E5E4E2", "ent": "#a9d39e"}
+    if s.name in coldict.keys():
+        return ["background-color: {}".format(coldict[s.name])] * len(s)
+    return [""] * len(s)

pages/Info.py

@@ -1,9 +1,10 @@
 import streamlit as st
+
 from app_utils.frontend_utils import build_sidebar
 
 build_sidebar()
 
-with open('README.md','r') as fin:
-    readme = fin.read().rpartition('---')[-1]
+with open("README.md", "r") as fin:
+    readme = fin.read().rpartition("---")[-1]
 
 st.markdown(readme, unsafe_allow_html=True)