Update app.py

app.py

@@ -1,23 +1,27 @@
-        
-# Streamlit App Interface (app.py)
-
 import streamlit as st
 import backend
 
+# Streamlit App Interface
 def main():
     st.title("**SYNAPTYX - RFP Analysis Agent**")
-    st.markdown("<h3 style='color: #1E3A8A;'>Upload RFP documents, provide a URL, search, and get intelligent answers.</h3>", unsafe_allow_html=True)
+    st.markdown(
+        "<h3 style='color: #1E3A8A;'>Upload RFP documents, provide a URL, search, and get intelligent answers.</h3>",
+        unsafe_allow_html=True,
+    )
 
     # Database Initialization
     database = "rfp_agent.db"
     conn = backend.create_connection(database)
     if conn is not None:
-        create_tables(conn)
+        backend.create_tables(conn)  # Use backend.create_tables(conn)
     else:
         st.error("Error! Cannot create the database connection.")
 
     # Dashboard Overview Tab
-    st.sidebar.markdown("<h2 style='color: #1E3A8A;'>Dashboard Overview</h2>", unsafe_allow_html=True)
+    st.sidebar.markdown(
+        "<h2 style='color: #1E3A8A;'>Dashboard Overview</h2>",
+        unsafe_allow_html=True,
+    )
     if conn is not None:
         try:
             cursor = conn.cursor()
@@ -33,8 +37,13 @@ def main():
             st.error(f"Error retrieving dashboard data: {e}")
 
     # Sidebar Knowledge Base Tab
-    st.sidebar.markdown("<h2 style='color: #1E3A8A;'>Knowledge Base</h2>", unsafe_allow_html=True)
-    st.sidebar.markdown("<p style='color: #1E3A8A;'>View and select documents for search.</p>", unsafe_allow_html=True)
+    st.sidebar.markdown(
+        "<h2 style='color: #1E3A8A;'>Knowledge Base</h2>", unsafe_allow_html=True
+    )
+    st.sidebar.markdown(
+        "<p style='color: #1E3A8A;'>View and select documents for search.</p>",
+        unsafe_allow_html=True,
+    )
 
     # Retrieve Documents from Database
     if conn is not None:
@@ -45,64 +54,72 @@ def main():
 
             if documents_in_db:
                 # Use st.multiselect instead of st.selectbox
-                selected_doc_ids = st.sidebar.multiselect(  
+                selected_doc_ids = st.sidebar.multiselect(
                     "Select documents to include in the search:",
                     options=[doc[0] for doc in documents_in_db],
-                    format_func=lambda doc_id: next(doc[1] for doc in documents_in_db if doc[0] == doc_id),
-                    default=[doc[0] for doc in documents_in_db]  # Select all documents by default
+                    format_func=lambda doc_id: next(
+                        doc[1] for doc in documents_in_db if doc[0] == doc_id
+                    ),
+                    default=[
+                        doc[0] for doc in documents_in_db
+                    ],  # Select all documents by default
                 )
 
                 if selected_doc_ids:
                     selected_documents = []
-                    selected_doc_names = [] # Also keep track of the document names
+                    selected_doc_names = []  # Also keep track of the document names
                     for doc_id in selected_doc_ids:
-                        cursor.execute("SELECT content, name FROM documents WHERE id = ?", (doc_id,))
+                        cursor.execute(
+                            "SELECT content, name FROM documents WHERE id = ?",
+                            (doc_id,),
+                        )
                         result = cursor.fetchone()
                         selected_documents.append(result[0])
-                        selected_doc_names.append(result[1]) # Add the name to the list
+                        selected_doc_names.append(result[1])  # Add the name to the list
 
                     # Initialize FAISS and Store Embeddings for Selected Documents
-                    embeddings = get_embeddings_model()
+                    embeddings = backend.get_embeddings_model()
                     if embeddings:
-                        vector_store = initialize_faiss(embeddings, selected_documents, selected_doc_names) # Use selected_doc_names here
+                        st.sidebar.write(
+                            "Creating embeddings..."
+                        )  # Indicate embedding creation
+                        vector_store = backend.initialize_faiss(
+                            embeddings,
+                            selected_documents,
+                            selected_doc_names,
+                        )  # Use selected_doc_names here
                         if vector_store:
-                            st.sidebar.success("Embeddings for selected documents stored successfully.", icon="📁")
+                            st.sidebar.success(
+                                "Embeddings for selected documents stored successfully.",
+                                icon="📁",
+                            )
 
                             # Initialize QA System for Selected Documents
-                            qa_system = initialize_qa_system(vector_store)
+                            qa_system = backend.initialize_qa_system(
+                                vector_store
+                            )
                             if qa_system:
-                                 # Query Input
-                                user_query = st.text_input("Enter your query about the RFPs:", placeholder="e.g., What are the evaluation criteria?", label_visibility='visible')
+                                # Query Input
+                                user_query = st.text_input(
+                                    "Enter your query about the RFPs:",
+                                    placeholder="e.g., What are the evaluation criteria?",
+                                    label_visibility="visible",
+                                )
                                 if user_query:
-                                    st.markdown("<p style='color: #1E3A8A;'>Retrieving answer...</p>", unsafe_allow_html=True)
+                                    st.markdown(
+                                        "<p style='color: #1E3A8A;'>Retrieving answer...</p>",
+                                        unsafe_allow_html=True,
+                                    )
                                     try:
-                                        response, source_documents = qa_system.run(query=user_query, return_source_documents=True)
-                                        response = qa_system.run(query=user_query, return_source_documents=True)
-                                        st.markdown("<h4 style='color: #1E3A8A;'>Answer:</h4>", unsafe_allow_html=True)
-                                        st.write(response["result"])  # Access the answer text
-                                        st.write(response["source_documents"])  # Access the source documents
-                                        
-                                    
-
-                                        # Store Query and Response in Database
-                                        with conn:
-                                            for doc in source_documents:
-                                                source_name = doc.metadata["source"]
-                                                document_id = conn.execute("SELECT id FROM documents WHERE name = ?", (source_name,)).fetchone()
-                                                if document_id:
-                                                    conn.execute("INSERT INTO queries (query, response, document_id) VALUES (?, ?, ?)", (user_query, response, document_id[0]))
-
-                                        # Display Source Information
-                                        st.markdown("<h4 style='color: #1E3A8A;'>Sources:</h4>", unsafe_allow_html=True)
-                                        for doc in source_documents:
-                                            source_name = doc.metadata["source"]
-                                            matched_text = doc.page_content
-                                            st.write(f"- Source Document: {source_name}")
-                                            # Display the matching text with highlighting
-                                            for idx, page_content in enumerate(document_pages[document_names.index(source_name)]):
-                                                if matched_text in page_content:
-                                                    highlighted_content = re.sub(re.escape(matched_text), f"<mark>{matched_text}</mark>", page_content)
-                                                    st.write(f"  - Page {idx + 1}: {highlighted_content}")
+                                        # Use agent_executor.invoke() to run the agent
+                                        response = qa_system.invoke(
+                                            {"input": user_query}
+                                        )
+                                        st.markdown(
+                                            "<h4 style='color: #1E3A8A;'>Answer:</h4>",
+                                            unsafe_allow_html=True,
+                                        )
+                                        st.write(response["output"])  # Access the answer text
 
                                     except Exception as e:
                                         st.error(f"Error generating response: {e}")
@@ -110,53 +127,36 @@ def main():
             st.error(f"Error retrieving documents from database: {e}")
 
     # Document Upload Section
-    st.markdown("<h2 style='color: #1E3A8A;'>Upload RFP Documents</h2>", unsafe_allow_html=True)
-    uploaded_documents = st.file_uploader("Upload PDF documents", type="pdf", accept_multiple_files=True)
+    st.markdown(
+        "<h2 style='color: #1E3A8A;'>Upload RFP Documents</h2>",
+        unsafe_allow_html=True,
+    )
+    uploaded_documents = st.file_uploader(
+        "Upload PDF documents", type="pdf", accept_multiple_files=True
+    )
     if uploaded_documents:
         st.write(f"Uploaded {len(uploaded_documents)} documents.")
-        all_texts, document_names, document_pages = upload_and_parse_documents(uploaded_documents)
+        (
+            all_texts,
+            document_names,
+            document_pages,
+        ) = backend.upload_and_parse_documents(uploaded_documents)
         if all_texts:
             # Store Documents in Database
             if conn is not None:
                 try:
                     with conn:
                         for doc, doc_name in zip(all_texts, document_names):
-                            conn.execute("INSERT INTO documents (name, content) VALUES (?, ?)", (doc_name, doc))
-                    st.success("Documents uploaded and parsed successfully.", icon="✅")
+                            conn.execute(
+                                "INSERT INTO documents (name, content) VALUES (?, ?)",
+                                (doc_name, doc),
+                            )
+                    st.success(
+                        "Documents uploaded and parsed successfully.", icon="✅"
+                    )
                 except Exception as e:
                     st.error(f"Error saving documents to database: {e}")
 
-    # URL Input Section
-    st.markdown("<h2 style='color: #1E3A8A;'>Or Provide a URL</h2>", unsafe_allow_html=True)
-    url = st.text_input("Enter the URL of a PDF document:")
-    if url:
-        all_texts, document_name = parse_pdf_from_url(url)
-        if all_texts:
-            # Store Document in Database
-            if conn is not None:
-                try:
-                    with conn:
-                        for doc in all_texts:
-                            conn.execute("INSERT INTO documents (name, content) VALUES (?, ?)", (document_name, doc))
-                    st.success("Document from URL uploaded and parsed successfully.", icon="✅")
-                except Exception as e:
-                    st.error(f"Error saving document from URL to database: {e}")
-
-    # Google Drive Integration Section
-    st.markdown("<h2 style='color: #1E3A8A;'>Or Fetch from Google Drive</h2>", unsafe_allow_html=True)
-    gdrive_file_id = st.text_input("Enter the Google Drive File ID:")
-    if gdrive_file_id:
-        all_texts, document_name = parse_pdf_from_google_drive(gdrive_file_id)
-        if all_texts:
-            # Store Document in Database
-            if conn is not None:
-                try:
-                    with conn:
-                        for doc in all_texts:
-                            conn.execute("INSERT INTO documents (name, content) VALUES (?, ?)", (document_name, doc))
-                    st.success("Document from Google Drive uploaded and parsed successfully.", icon="✅")
-                except Exception as e:
-                    st.error(f"Error saving document from Google Drive to database: {e}")
 
 if __name__ == "__main__":
     main()