Update app.py

app.py

@@ -120,7 +120,7 @@ if not st.session_state.pdf_loaded and "pdf_path" in st.session_state:
         metadata = extract_metadata_llm(st.session_state.pdf_path)
 
         # Display extracted-metadata
-        if isinstance(metadata, dict):  # Ensure metadata is a dictionary
+        if isinstance(metadata, dict):
             st.subheader("📄 Extracted Document Metadata")
             st.write(f"**Title:** {metadata.get('Title', 'Unknown')}")
             st.write(f"**Author:** {metadata.get('Author', 'Unknown')}")
@@ -129,7 +129,6 @@ if not st.session_state.pdf_loaded and "pdf_path" in st.session_state:
         else:
             st.error("Metadata extraction failed. Check the LLM response format.")
 
-
         # Embedding Model
         model_name = "nomic-ai/modernbert-embed-base"
         embedding_model = HuggingFaceEmbeddings(model_name=model_name, model_kwargs={"device": "cpu"}, encode_kwargs={'normalize_embeddings': False})
@@ -194,7 +193,6 @@ if query:
     st.markdown("### Extracted Relevant Contexts")
     st.json(contexts["relevant_contexts"])
 
-
     st.subheader("context_relevancy_evaluation_chain Statement")
     st.json(final_response["relevancy_response"])