abstracting code

.gitignore

@@ -0,0 +1,2 @@
+env/
+*/__pycache__

.streamlit/config.toml

@@ -1,2 +1,12 @@
 [client]
-showSidebarNavigation = false
+showSidebarNavigation = false
+showErrorDetails = false
+
+[theme]
+base="dark"
+primaryColor = "#702963"
+font="serif"
+
+[server]
+fileWatcherType = "auto"
+runOnSave = true

app.py

@@ -1,5 +1,4 @@
-import streamlit as st
-from functions.sidebar import sidebar
+from pages.home import home
+# idea: instead of "redirecting" - you can have redirects render different pages on main page
 
-sidebar()
-st.title('Home')
+home()

functions/gptResponse.py

@@ -5,7 +5,11 @@ from dotenv import load_dotenv
 import os
 
 load_dotenv()
-openai_key = os.getenv('OPENAI_API_KEY')
+openai_key = os.getenv(
+    "OPENAI_API_KEY"
+)  # may wanna ask user for this or handle error when its not there
+# if not openai_key:
+#     raise ValueError("OpenAI API key not found in environment variables.")
 
 def get_response(user_query, chat_history, context):
     template = """
@@ -18,20 +22,21 @@ def get_response(user_query, chat_history, context):
     User question: {user_question}
     """
 
-
     llm = ChatOpenAI(api_key=openai_key)
     try:
         prompt = ChatPromptTemplate.from_template(template)
 
         llm = ChatOpenAI(api_key=openai_key)
-            
+
         chain = prompt | llm | StrOutputParser()
-        
-        value = chain.stream({
-            "chat_history": chat_history,
-            "context": context,
-            "user_question": user_query,
-        })
+
+        value = chain.stream(
+            {
+                "chat_history": chat_history,
+                "context": context,
+                "user_question": user_query,
+            }
+        )
         if value:
             response = " ".join([part for part in value])
             return response

functions/sidebar.py

@@ -1,7 +1,7 @@
 import streamlit as st
 
-def sidebar():
-
-    st.sidebar.page_link("app.py", label="Home")
-    st.sidebar.page_link("pages/ragChat.py", label="RAG CHAT")
 
+def sidebar():
+    st.sidebar.title("Navigation")
+    st.sidebar.page_link("pages/home.py", label="Home", icon="🏠")
+    st.sidebar.page_link("pages/ragChat.py", label="RAG CHAT", icon="💬")

pages/home.py

@@ -0,0 +1,16 @@
+import streamlit as st
+from functions.sidebar import sidebar
+
+
+def home():
+    sidebar()
+    st.header("Home")
+    st.write("add a desc here")
+
+    st.subheader("Goto Chat")
+    st.page_link(page="pages/ragChat.py", label="RAG CHAT", icon="💬")
+
+
+# if page is called directly (/home)
+if __name__ == "__main__":
+    home()

pages/ragChat.py

@@ -6,24 +6,26 @@ from functions.web_chain import vectorize, loadUrlData, get_pdf_text
 import asyncio
 
 
-async def main():
-    sidebar()
+async def add_data():
     st.title("Upload Data")
 
     uploaded_files = st.file_uploader("Upload PDFs", accept_multiple_files=True)
-    st.warning("If you plan to add more files, after processing initial files, make sure the uploaded files you already processed are removed")
+    st.warning(
+        "If you plan to add more files, after processing initial files, make sure the uploaded files you already processed are removed"
+    )
     url = st.text_input("Enter a website link")
-    if "button_pressed" not in st.session_state:
-        st.session_state.button_pressed = False
-    if st.button('Process URL and Files'):
-        st.session_state.button_pressed = True
+
+    if st.button("Process URL and Files"):
         with st.spinner("Vectorizing Data, wait times vary depending on size..."):
             if url:
                 try:
                     if "retriever" not in st.session_state:
-                        st.session_state.retriever = vectorize(loadUrlData(url), "document")
+                        st.session_state.retriever = vectorize(
+                            loadUrlData(url), "document"
+                        )
                 except Exception as e:
                     st.error(f"Failed to load URL: {e}")
+
             if uploaded_files:
                 try:
                     texts = get_pdf_text(uploaded_files)
@@ -36,44 +38,70 @@ async def main():
                         st.error("PDF has no meta data text")
                 except Exception as e:
                     st.error(f"Failed to load PDF: {e}")
+
             st.success("Data is ready to be queried!")
-    
-    if st.session_state.button_pressed:
-        if "chat_history" not in st.session_state:
-            st.session_state.chat_history = [AIMessage(content="Hello, I am a bot. How can I help you?")]
+    st.session_state.data_hungry = False
+    return False
+
 
-        st.title("RAG CHAT")
-        for message in st.session_state.chat_history:
-            if isinstance(message, AIMessage):
-                with st.chat_message("AI"):
-                    st.write(message.content)
-            elif isinstance(message, HumanMessage):
-                with st.chat_message("Human"):
-                    st.write(message.content)
+async def rag_chat():
+    if "chat_history" not in st.session_state:
+        st.session_state.chat_history = [
+            AIMessage(content="Hello, I am a bot. How can I help you?")
+        ]
 
-        user_query = st.chat_input("Type your message here...", key="chat_input")
-        if user_query:
-            st.session_state.chat_history.append(HumanMessage(content=user_query))
+    st.title("RAG CHAT")
+    for message in st.session_state.chat_history:
+        if isinstance(message, AIMessage):
+            with st.chat_message("AI"):
+                st.write(message.content)
+        elif isinstance(message, HumanMessage):
             with st.chat_message("Human"):
-                st.write(user_query)
+                st.write(message.content)
+
+    user_query = st.chat_input("Type your message here...", key="chat_input")
+    if user_query:
+        st.session_state.chat_history.append(HumanMessage(content=user_query))
+        with st.chat_message("Human"):
+            st.write(user_query)
+
+        if "retriever" in st.session_state:
+            try:
+                ragAnswer = (
+                    await st.session_state.retriever.amax_marginal_relevance_search(
+                        user_query, k=4, fetch_k=10
+                    )
+                )
+                context = []
+                for i, doc in enumerate(ragAnswer):
+                    print(f"{i}: {doc.page_content}")
+                    context.append(doc.page_content)
+                with st.spinner("Generating Response"):
+                    response = get_response(
+                        user_query, st.session_state.chat_history, context
+                    )
+                if response:
+                    st.session_state.chat_history.append(
+                        AIMessage(content=response)
+                    )
+                    with st.chat_message("AI"):
+                        st.write(response)
+                else:
+                    st.write("No response received.")
+            except Exception as e:
+                st.error(f"Error during retrieval or response generation: {e}")
+
+
+async def main():
+    if st.session_state.data_hungry:
+        st.session_state.data_hungry = (
+            await add_data()
+        ) 
+    else:
+        await rag_chat()
 
-            if 'retriever' in st.session_state:
-                try:
-                    ragAnswer = await st.session_state.retriever.amax_marginal_relevance_search(user_query, k=4, fetch_k=10)
-                    context = []
-                    for i, doc in enumerate(ragAnswer):
-                        print(f"{i}: {doc.page_content}")
-                        context.append(doc.page_content)
-                    with st.spinner("Generating Response"):
-                        response = get_response(user_query, st.session_state.chat_history, context)
-                    if response:
-                        st.session_state.chat_history.append(AIMessage(content=response))
-                        with st.chat_message("AI"):
-                            st.write(response)
-                    else:
-                        st.write("No response received.") 
-                except Exception as e:
-                    st.error(f"Error during retrieval or response generation: {e}")
 
 if __name__ == "__main__":
+    st.session_state.data_hungry = st.toggle("Add Custom Data", False)
+    sidebar()
     asyncio.run(main())