Update app.py

app.py

@@ -9,10 +9,10 @@ from langchain.vectorstores import FAISS
 from transformers import pipeline
 import torch
 
-# Set up the page configuration as the first Streamlit command
+# Set up the page configuration
 st.set_page_config(page_title="RAG-based PDF Chat", layout="centered", page_icon="📄")
 
-# Load the summarization pipeline model
+# Load the summarization pipeline
 @st.cache_resource
 def load_summarization_pipeline():
     summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
@@ -23,30 +23,28 @@ summarizer = load_summarization_pipeline()
 # Dictionary of Hugging Face PDF URLs grouped by folders
 PDF_FOLDERS = {
     "PPC and Administration": [
-        "https://huggingface.co/spaces/tahirsher/GenAI_Lawyers_Guide/tree/main/PPC%20and%20Administration",
+        "https://huggingface.co/spaces/tahirsher/GenAI_Lawyers_Guide/tree/main/PPC%20and%20Administration"
     ],
     "IHC": [
         "https://huggingface.co/spaces/tahirsher/GenAI_Lawyers_Guide/tree/main/IHC"
-    ]
+    ],
     "LHC": [
         "https://huggingface.co/spaces/tahirsher/GenAI_Lawyers_Guide/tree/main/LHC"
-    ]
+    ],
     "Lahore High Court Rules and Orders": [
         "https://huggingface.co/spaces/tahirsher/GenAI_Lawyers_Guide/tree/main/Lahore%20High%20Court%20Rules%20and%20Orders"
-    ]
+    ],
     "PHC": [
         "https://huggingface.co/spaces/tahirsher/GenAI_Lawyers_Guide/tree/main/PHC"
-    ]
+    ],
     "SC": [
         "https://huggingface.co/spaces/tahirsher/GenAI_Lawyers_Guide/tree/main/SC"
-    ],
+    ]
 }
 
 # Helper function to convert Hugging Face blob URLs to direct download URLs
 def get_huggingface_raw_url(url):
-    if "huggingface.co" in url and "/blob/" in url:
-        return url.replace("/blob/", "/resolve/")
-    return url
+    return url.replace("/blob/", "/resolve/") if "huggingface.co" in url and "/blob/" in url else url
 
 # Fetch and extract text from all PDFs in specified folders
 def fetch_pdf_text_from_folders(pdf_folders):
@@ -119,4 +117,4 @@ def main():
                 st.markdown(f"**🤖 AI:** {answer}")
 
 if __name__ == "__main__":
-    main()
+    main()