Update app.py

app.py

@@ -15,20 +15,20 @@ TOKEN=os.getenv('HF_TOKEN')
 subprocess.run(["huggingface-cli", "login", "--token", TOKEN, "--add-to-git-credential"])
 st.sidebar.title("Welcome to MBAL Chatbot")
 class PDFChatbot:
-   def __init__(self):
+    def __init__(self):
        self.azure_client = openai.OpenAI()
        # Store conversation history
        self.conversation_history = []
 
-   def get_relevant_context(self, user_question: str) -> List[str]:
+    def get_relevant_context(self, user_question: str) -> List[str]:
         """Split text into smaller chunks for better processing."""
         db = FAISS.load_local("mbal_faiss_db", embeddings=HuggingFaceEmbeddings(model_name='bkai-foundation-models/vietnamese-bi-encoder'), allow_dangerous_deserialization=True)
         relevant_chunks = db.similarity_search(user_question, k=3)
         relevant_chunks = [chunk.page_content for chunk in relevant_chunks]
         return "\n\n".join(relevant_chunks)
-   def chat_with_pdf(self, user_question: str, pdf_content: str) -> str:
+    def chat_with_pdf(self, user_question: str, pdf_content: str) -> str:
        """Generate response using Azure OpenAI based on PDF content and user question."""
-       try:
+        try:
            # Split PDF content into chunks
            # Get relevant context for the question
            relevant_context = self.get_relevant_context(user_question)
@@ -75,11 +75,11 @@ Please provide a helpful response based on the insurance document content above.
        except Exception as e:
            return f"Error generating response: {str(e)}"
 def main():
-   # st.set_page_config(page_title="Insurance PDF Chatbot", page_icon="🛡️", layout="wide")
-   st.title("🛡️ Insurance Policy Assistant")
-   st.markdown("Upload your insurance policy PDF and ask questions about your coverage, claims, deductibles, and more!")
-   # Initialize chatbot
-   if 'chatbot' not in st.session_state:
+    # st.set_page_config(page_title="Insurance PDF Chatbot", page_icon="🛡️", layout="wide")
+    st.title("🛡️ Insurance Policy Assistant")
+    st.markdown("Upload your insurance policy PDF and ask questions about your coverage, claims, deductibles, and more!")
+    # Initialize chatbot
+    if 'chatbot' not in st.session_state:
        st.session_state.chatbot = PDFChatbot()
        st.session_state.pdf_processed = False
        st.session_state.chat_history = []
@@ -90,10 +90,10 @@ def main():
            st.session_state.chat_history = []
            st.rerun()
    # Main chat interface
-   if st.session_state.pdf_processed:
-       st.header("💬 Ask About Your Insurance Policy")
-       # Display chat history
-       for i, (question, answer) in enumerate(st.session_state.chat_history):
+    if st.session_state.pdf_processed:
+        st.header("💬 Ask About Your Insurance Policy")
+        # Display chat history
+        for i, (question, answer) in enumerate(st.session_state.chat_history):
            with st.container():
                st.markdown(f"**You:** {question}")
                st.markdown(f"**Insurance Assistant:** {answer}")
@@ -139,4 +139,4 @@ def main():
         """)
 
 if __name__ == "__main__":
-   main()
+    main()