deleted revision files

app.py

@@ -6,6 +6,7 @@
 import os
 import streamlit as st
 import sys
+
 __import__("pysqlite3")
 sys.modules["sqlite3"] = sys.modules.pop("pysqlite3")
 load_dotenv()
@@ -23,11 +24,13 @@
     unsafe_allow_html=True,
 )
 
+
 def on_api_key_change():
     api_key = ss.get("api_key") or os.getenv("OPENAI_API_KEY")
     os.environ["OPENAI_API_KEY"] = api_key
     openai.api_key = api_key
 
+
 def save_uploadfile(uploadedfile):
     dirpath = os.path.join("data", "lit_dir")
     if os.path.exists(dirpath):
@@ -36,6 +39,7 @@ def save_uploadfile(uploadedfile):
     with open(os.path.join(dirpath, uploadedfile.name), "wb") as f:
         f.write(uploadedfile.getbuffer())
 
+
 st.write(
     "## Xpert AI: Extract human interpretable structure-property relationships from raw data"
 )
@@ -44,11 +48,13 @@ def save_uploadfile(uploadedfile):
 Currently, GPT-4o model is used to generate natural language explanations."""
 )
 
+
 def run_autofill():
     st.session_state.auto_target = "toxicity of small molecules"
     st.session_state.auto_df = "tests/toxicity_sample_data.csv"
     st.experimental_rerun()
 
+
 auto_target = st.session_state.get("auto_target", None)
 auto_arxiv = st.session_state.get("auto_arxiv", None)
 
@@ -93,7 +99,8 @@ def run_autofill():
         "### Provide literature to generate scientific explanations! \nIf you don't provide literature, you will receive an explanation based on XAI tools."
     )
     lit_files = st.file_uploader(
-        "Upload your literature here. Files must be in `pdf` format (Suggested):", accept_multiple_files=True
+        "Upload your literature here. Files must be in `pdf` format (Suggested):",
+        accept_multiple_files=True,
     )
     arxiv_keywords = st.text_input(
         "If you want to scrape arxiv, provide keywords for arxiv scraping:",
@@ -190,7 +197,11 @@ def run_autofill():
 
         # scrape arxiv.org
         if arxiv_keywords:
-            arg_dict_arxiv = {"key_words": arxiv_keywords, "max_papers": max_papers,"lit_files":lit_files_given}
+            arg_dict_arxiv = {
+                "key_words": arxiv_keywords,
+                "max_papers": max_papers,
+                "lit_files": lit_files_given,
+            }
 
             scrape_arxiv(arg_dict_arxiv)
 
@@ -228,4 +239,4 @@ def run_autofill():
         with open("./data/figs.zip", "rb") as f:
             st.download_button(
                 "Download the outputs!", f, file_name="XpertAI_output.zip"
-            )
+            )