Update app.py

app.py

@@ -10,7 +10,7 @@ from transformers import AutoModel, AutoTokenizer
 import torch
 
 # Set up Groq API key
-GROQ_API_KEY = os.getenv("LawersGuideAPIKey")
+#GROQ_API_KEY = os.getenv("LawersGuideAPIKey")
 
 # Initialize embedding model (using sentence-transformers model)
 tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/all-MiniLM-L6-v2")
@@ -94,7 +94,7 @@ def user_input(user_question, vector_store):
 # Main function to run the Streamlit app
 def main():
     st.set_page_config(page_title="RAG-based PDF Chat", layout="centered", page_icon="📄")
-    st.title("📄 Query PDF Documents on Hugging Face")
+    st.title("📄 Gen AI Lawyers Guide")
 
     # Load documents from Hugging Face
     raw_text = fetch_pdf_text_from_huggingface(PDF_URLS)